weekly picks (Nov 1 week 2020)
-
PhysRevB.102.184404 : Current-induced orbital magnetization in systems without inversion symmetry (SMurakami, PRB)
-
PhysRevB.102.174409 : Asymmetric skyrmion-antiskyrmion production in ultrathin ferromagnetic films (JVKim, PRB)
-
PhysRevB.102.174502 : Anisotropic vortices on superconducting Nb(110) (Nb(110), PRB)
-
PhysRevLett.125.196604 : One-Dimensional Quasiperiodic Mosaic Lattice with Exact Mobility Edges (1D quasicrystal, PRL)
-
2011.03007 : Generic Spiral Spin Liquids (GangChen, arXiv)
-
2011.02813 : Clusterization transition between cluster Mott insulators on a breathing Kagom'{e} lattice (GangChen, arXiv)
-
2011.02715 : Antiferromagnetic resonance in a spin-gap magnet with strong single-ion anisotropy (spin-gap, arXiv)
-
2011.02532 : Electron quasi-itinerancy intertwined with quantum order by disorder in pyrochlore iridate magnetism (GangChen, arXiv)
-
acsami.0c15203 : Strong In-Plane Magnetic Field-Induced Reemergent Superconductivity in the van der Waals Heterointerface of NbSe2 and CrCl3 (CrCl3, arXiv)
-
2011.02500 : Highly Tunable Junctions and Nonlocal Josephson Effect in Magic Angle Graphene Tunneling Devices (graphene, arXiv)
-
PhysRevB.102.205407 : Temperature and chemical potential dependence of the parity anomaly in quantum anomalous Hall insulators (QAHE, PRB)
-
PhysRevB.102.205105 : Effect of disorder on the transverse magnetoresistance of Weyl semimetals (Weyl Semimental, PRB)
-
PhysRevB.102.201104 : Quantum phase diagram of a Moir'e-Hubbard model (DasSarma, PRB)
-
2011.02448 : Fractional and composite excitations of antiferromagnetic quantum spin trimer chains (Sandvik, arXiv)
-
2011.02369 : Dynamical spin correlations of the kagome antiferromagnet (DM, arXiv)
-
2011.02380 : Evidence of ideal excitonic insulator in bulk MoS2 under pressure (Excitonic insulator, arXiv)
-
2011.01941 : Inhomogeneous time-reversal symmetry breaking in $\mathrm{Sr}{2}\mathrm{Ru}\mathrm{O}{4}$ (Ruthenate, arXiv)
-
PhysRevB.102.184504 : Quantum geometric contributions to the BKT transition: Beyond mean field theory (BKT, PRB)
-
PhysRevB.102.174404 : Spontaneous time-reversal symmetry breaking without magnetism in an $S=1$ spin chain (PHosur, PRB)
-
PhysRevB.102.174403 : Layer effects on the magnetic textures in magnets with local inversion asymmetry (local inversion breaking, PRB)
-
PhysRevB.102.201102 : Emergence of nearly flat bands through a kagome lattice embedded in an epitaxial two-dimensional Ge layer with a bitriangular structure (kagome Ge, PRB)
-
PhysRevB.102.195404 : Out-of-plane corrugations in graphene based van der Waals heterostructures (graphene, PRB)
-
PhysRevB.102.195201 : Screening of hot electrons in the ferroelectric semiconductor $\mathrm{I}{\mathrm{n}}{2}\mathrm{S}{\mathrm{e}}{3}$ (el-phonon,PRB)
-
PhysRevB.102.195106 : Variational study of the ground state and spin dynamics of the spin-$\frac{1}{2}$ kagome antiferromagnetic Heisenberg model and its implication for herbertsmithite ${\mathrm{ZnCu}}{3}{(\mathrm{OH})}{6}{\mathrm{Cl}}_{2}$ (TaoLi, PRB)
-
PhysRevB.102.180501 : Multichannel superconductivity of monolayer FeSe on ${\mathrm{SrTiO}}_{3}$: Interplay of spin fluctuations and electron-phonon interaction (FeSe/STO, PRB)
-
PhysRevB.102.174301 : Chiral phonons in the indirect optical transition of a ${\mathrm{MoS}}{2}/{\mathrm{WS}}{2}$ heterostructure (chiral phonon, PRB)
-
PhysRevB.102.205404 : Chiral oscillations in electronic transport through graphene nanoribbons induced by pseudospin filters (graphene, PRB)
-
2011.01595 : First-Principles Design of Halide-Reduced Electrides: Magnetism and Topological Phases (Arita, arXiv)
-
2011.01701 : Tunable electron-phonon interactions in long-period superlattices (Levitov, arXiv)
-
2011.01679 : Bond-weighted Tensor Renormalization Group (Tensor RG, arXiv)
-
2011.01597 : Observation of hydrodynamic-like behavior in 3D Dirac semimetal ZrTe5 (phonon hydrodynamics, arXiv)
-
2011.01401 : Ferroic orders in two-dimensional transition/rare-earth metal halides (2D ferroic order, arXiv)
-
2011.01265 : Crossed Andreev reflection in topological insulator nanowire T-junctions (BHZ model, arXiv)
-
PhysRevB.102.205401 : Interacting quantum Hall states in a finite graphene flake and at finite temperature (graphene flake, PRB)
-
PhysRevB.102.195401 : Kramers pairs of Majorana corner states in a topological insulator bilayer (Jelena, PRB)
-
PhysRevB.102.201101 : Spin-orbit coupling effects on spin-phonon coupling in ${\mathrm{Cd}}{2}{\mathrm{Os}}{2}{\mathrm{O}}_{7}$ (JGPark, PRB)
-
PhysRevB.102.184502 : Nematic superconductivity in LiFeAs (nematic order, PRB)
-
PhysRevB.102.174402 : ac susceptibility study of magnetic relaxation phenomena in the antiskyrmion-hosting tetragonal Mn-Pt(Pd)-Sn system (SSP Parkin, PRB)
-
PhysRevLett.125.195301 : Anomalous Spin-Charge Separation in a Driven Hubbard System (Charge spin separation, PRL)
-
PhysRevLett.125.196401 : Blue Phosphorene Bilayer is a Two-Dimensional Metal and an Unambiguous Classification Scheme for Buckled Hexagonal Bilayers (Buckled Hexagonal Bilayers, PRL)
-
PhysRevLett.125.197202 : Simulating Exotic Phases of Matter with Bond-Directed Interactions with Arrays of Majorana-Cooper Pair Boxes (Tsvelik, PRL)
-
2011.00785 : Imaging the coupling between itinerant electrons and localised moments in the centrosymmetric skyrmion magnet GdRu2Si2 (Seki, arXiv)
-
2011.00541 : Neutron scattering investigation of proposed Kosterlitz-Thouless transitions in the triangular-lattice Ising antiferromagnet TmMgGaO4 (KT, arXiv)
-
2011.00036 : Discovery of magnetic topological crystals (magnetic TC, arXiv)
-
2011.01158 : Nematic Order in Twisted Bilayer Graphene by Valley + Spin Fluctuation Interference Mechanism (Kontani, arXiv)
-
2011.00595 : Orbital and Spin Character of Doped Carriers in Infinite-Layer Nickelates (Nickelate, arXiv)
-
2011.00268 : The observation of in-plane quantum Griffiths singularity in two-dimensional crystalline superconductors (Griffiths singularity, arXiv)
-
2011.00185 : Origin of the anomalous Hall effect in two-band chiral superconductors (chiral SC, arXiv)
-
PhysRevB.102.195103 : Entropy and electronic orders of the three-orbital Hubbard model with antiferromagnetic Hund coupling (PWerner, PRB)
-
PhysRevB.102.180402 : Combing the helical phase of chiral magnets with electric currents (Nagaosa, PRB)
-
PhysRevX.10.041023 : Single-Particle Spectral Function Formulated and Calculated by Variational Monte Carlo Method with Application to $d$-Wave Superconducting State (Imada, PRX)
-
2010.16187 : Phase transitions between helices, vortices, and hedgehogs driven by spatial anisotropy in chiral magnets (YMotome, arXiv)
-
2010.16125 : Microscopic Theory of Ultrafast Skyrmion Excitation by Light (skyrmion, arXiv)
-
2010.16109 : Emergence of Charge Loop Current in Geometrically Frustrated Hubbard Model: Functional Renormalization Group Study (Kontani, arXiv)
-
2010.16028 : Doping effects on the valence bond solid of $Li_{2}RuO_{3}$ with $Mn$ substitution (JGPark, arXiv)
-
2010.16390 : Quasiperiodic criticality and spin-triplet superconductivity in superconductor-antiferromagnet moire patterns (Lado, arXiv)
-
2010.16101 : Phase Diagram of Infinite Layer Praseodymium Nickelate Pr${1-x}$Sr${x}$NiO$_2$ Thin Films (Nickelate, arXiv)


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A package for computation of hidden semi markov models
| Version: | 0.4 |
| Depends: | R (≥ 2.0.0), mvtnorm |
| Published: | 2013-04-25 |
| Author: | Jan Bulla, Ingo Bulla |
| Maintainer: | Jan Bulla <bulla at math.unicaen.fr> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| NeedsCompilation: | yes |
| CRAN checks: | hsmm results |
| Reference manual: | hsmm.pdf |
| Package source: | hsmm_0.4.tar.gz |
| Windows binaries: | r-devel: hsmm_0.4.zip, r-release: hsmm_0.4.zip, r-oldrel: hsmm_0.4.zip |
| OS X binaries: | r-release: hsmm_0.4.tgz, r-oldrel: hsmm_0.4.tgz |
| Old sources: | hsmm archive |
Please use the canonical form https://CRAN.R-project.org/package=hsmm to link to this page.


Physical Activities
Playing Soccer
Soccer is a team sport played between two teams of eleven players with a spherical ball.
Dancing
Dance is a performing art form consisting of purposefully selected sequences of human movement.
Relaxing Activities
Watching Movies
A film, also called a movie, motion picture, theatrical film, or photoplay, is a series of still images which, when shown on a screen, creates the illusion of moving images due to the phi phenomenon.


| # | Date | Time | Amount |
|---|---|---|---|
| 3326 | 10/21/2013 | 3:29 PM | $321.33 |
| 3325 | 10/21/2013 | 3:20 PM | $234.34 |
| 3324 | 10/21/2013 | 3:03 PM | $724.17 |
| 3323 | 10/21/2013 | 3:00 PM | $23.71 |
| 3322 | 10/21/2013 | 2:49 PM | $8345.23 |
| 3321 | 10/21/2013 | 2:23 PM | $245.12 |
| 3320 | 10/21/2013 | 2:15 PM | $5663.54 |
| 3319 | 10/21/2013 | 2:13 PM | $943.45 |
September 25th, 11:38 AM
The dashboard is officially made. Nothing is "hooked up", but hopefully that changes soon.
Will try to have Chat working soon.


Across: 1,12,13. Novel means of summoning spirits - long sentence by boring sort (5 4 4 10) 6. see 25 (5) 10. Mother has request for flower (6) 11. Prod Iran violently and see what precipitates (8) 12,13. see 1 14. Removing cover of thin dust and revealing historic tract (9) 16. Brutal overseer, typifying historic African leaders (5) 19. Familiar trick now nightly feature (5) 20. MS program, or ultimately sly contributor to criminality (9) 23. He writes massive amounts about Mr Hobbit shedding exterior (3 7) 25,26,27,6. Steady hands grasp music book (4 8 3 3 5) 28. Penned? We penned nonsense! (5) 29. Proud organisation remains focused despite losing one (9) Down: 2. Princess replaces crusty leader in grip of old habits (9) 3. Restraint shown in role as headmaster (5) 4. Smart after facebook reaction to copycat fashion (8) 5. For majority, a timeless land (7) 7. Crazy, ridiculous, deranged, "one short"! (9) 8. Join union despite overseer's objections? (5) 9. Added note about rogue players in sex trade (5) 15. Complete directions for crossword answers (9) 17. Charm her hose... so devious! (9) 18. Updates dining hall times (8) 21. Illegal operators working in the red (7) 22. To bar development? (5) 24. Nose ring not much fun (5) 25. Minor player in sex trade (5)


Visualizing the World Through its Own Worldview
The map shows the distribution of the average value of the variables across countries, excluding missing values.
Variables used for hypothesis
- Leisure time = range[1-4]//Not at all Important to Very Important
- State of health = range[1-4]//poor to very good
- Satisfaction with Life = range[1-10]//Completely dissatisfied to Completely satisfied
- NumberofChildren = range[0-8]//Zero Children to Eight children
- Democracy = range[1-9]//Not a democratic country to democratic country
- Education Attainted = range[1-9]//No formal education to university education
- Scale of income = range[1-10]//Low income to Very high income
- Social Class = range[1-5]//Lower class to upper class
Survey data over 3 periods
- Wave 4 - 1999-2004
- Wave 5 - 2005-2009
- Wave 6 - 2010-2014


This is the mail archive of the
<EMAIL_ADDRESS>mailing list for the GDB project.
[rfc] Work around ARM RV compiler unwind info
- From: Daniel Jacobowitz <drow at false dot org>
- To: gdb-patches at sourceware dot org
- Date: Mon, 18 Dec 2006 16:59:00 -0500
- Subject: [rfc] Work around ARM RV compiler unwind info
ARM's compilers generate, overall, very good debug info. It's poorly
supported by GDB, for various reasons: a few places where the debug info is
in fact wrong, and a number where it is so very right that GDB can't handle
it (since we rely on less correct information typically output by GCC).
Unfortunately this is one of the former cases, but it's one that I think is
tentatively worth supporting in GDB.
The compilers have two problems. Both have been fixed, but the fixes are
conditionalized, for maximum compatibility with other ARM tools that made
the same assumptions.
- When generating DWARF2, with the version field in .debug_frame set to
1, they assume that DW_CFA_def_cfa and DW_CFA_def_cfa_offset take
factored offsets instead of unfactored. Using --dwarf3 makes this
problem go away; the first ARM compilers to generate DWARF3 were
released after this bug was found.
- When generating either DWARF2 or DWARF3 (CIE version 1 or 3), they
assume that a reg_offset rule for the CFA is REG - OFFSET instead of
REG + OFFSET. RVCT 3.0 has this problem. RVCT 3.0 SP1 does not;
but it marks the output with an "armcc+" augmentation to indicate
that it has the standard DWARF meaning, again for compatibility
with other versions of ARM tools.
These aren't reverse engineered fixes, by the way - I spoke with the ARM
compiler team about the proper checks. I only turn on either of the fixes
if the file also has .debug_info, so that we can find a producer string that
unambiguously indicates that the ARM compiler was used.
What do you think? Useful? Too ugly?
--
Daniel Jacobowitz
CodeSourcery
2006-12-18 Daniel Jacobowitz<EMAIL_ADDRESS>* buildsym.c (start_subfile): Handle producer.
(record_producer): New function.
* buildsym.h (struct subfile): Include producer.
(record_producer): New prototype.
* dwarf2-frame.c (struct dwarf2_cie): Add version and augmentation.
(struct dwarf2_frame_state): Add armcc_cfa_offsets_sf and
armcc_cfa_offsets_reversed.
(execute_cfa_program): Handle armcc_cfa_offsets_sf.
(dwarf2_frame_find_quirks): New function.
(dwarf2_frame_cache): Call it. Handle armcc_cfa_offsets_reversed.
(decode_frame_entry_1): Record the CIE version. Record the
augmentation. Skip armcc augmentations.
* dwarf2read.c (read_file_scope): Save the producer.
* symtab.h (struct symtab): Rename unused version member to
producer.
Index: gdb/buildsym.c
===================================================================
RCS file: /scratch/gcc/repos/src/src/gdb/buildsym.c,v
retrieving revision 1.43
diff -u -p -r1.43 buildsym.c
--- gdb/buildsym.c 25 Aug 2006 16:32:32 -0000 1.43
+++ gdb/buildsym.c 6 Nov 2006 19:46:19 -0000
@@ -596,6 +596,9 @@ start_subfile (char *name, char *dirname
later via a call to record_debugformat. */
subfile->debugformat = NULL;
+ /* Similarly for the producer. */
+ subfile->producer = NULL;
+
/* If the filename of this subfile ends in .C, then change the
language of any pending subfiles from C to C++. We also accept
any other C++ suffixes accepted by deduce_language_from_filename. */
@@ -1004,6 +1007,12 @@ end_symtab (CORE_ADDR end_addr, struct o
&objfile->objfile_obstack);
}
+ /* Similarly for the producer. */
+ if (subfile->producer != NULL)
+ symtab->producer = obsavestring (subfile->producer,
+ strlen (subfile->producer),
+ &objfile->objfile_obstack);
+
/* All symtabs for the main file and the subfiles share a
blockvector, so we need to clear primary for everything
but the main file. */
@@ -1026,6 +1035,8 @@ end_symtab (CORE_ADDR end_addr, struct o
{
xfree ((void *) subfile->debugformat);
}
+ if (subfile->producer != NULL)
+ xfree (subfile->producer);
nextsub = subfile->next;
xfree ((void *) subfile);
@@ -1102,6 +1113,12 @@ record_debugformat (char *format)
current_subfile->debugformat = savestring (format, strlen (format));
}
+void
+record_producer (const char *producer)
+{
+ current_subfile->producer = savestring (producer, strlen (producer));
+}
+
/* Merge the first symbol list SRCLIST into the second symbol list
TARGETLIST by repeated calls to add_symbol_to_list(). This
procedure "frees" each link of SRCLIST by adding it to the
Index: gdb/buildsym.h
===================================================================
RCS file: /scratch/gcc/repos/src/src/gdb/buildsym.h,v
retrieving revision 1.13
diff -u -p -r1.13 buildsym.h
--- gdb/buildsym.h 17 Dec 2005 22:33:59 -0000 1.13
+++ gdb/buildsym.h 6 Nov 2006 19:46:19 -0000
@@ -68,6 +68,7 @@ struct subfile
struct linetable *line_vector;
int line_vector_length;
enum language language;
+ char *producer;
char *debugformat;
};
@@ -281,6 +282,8 @@ extern void record_pending_block (struct
extern void record_debugformat (char *format);
+extern void record_producer (const char *producer);
+
extern void merge_symbol_lists (struct pending **srclist,
struct pending **targetlist);
Index: gdb/dwarf2-frame.c
===================================================================
RCS file: /scratch/gcc/repos/src/src/gdb/dwarf2-frame.c,v
retrieving revision 1.63
diff -u -p -r1.63 dwarf2-frame.c
--- gdb/dwarf2-frame.c 28 May 2006 05:56:50 -0000 1.63
+++ gdb/dwarf2-frame.c 6 Nov 2006 20:24:34 -0000
@@ -64,6 +64,9 @@ struct dwarf2_cie
gdb_byte *initial_instructions;
gdb_byte *end;
+ /* Saved augmentation, in case it's needed later. */
+ char *augmentation;
+
/* Encoding of addresses. */
gdb_byte encoding;
@@ -73,6 +76,9 @@ struct dwarf2_cie
/* True if an 'S' augmentation existed. */
unsigned char signal_frame;
+ /* The version recorded in the CIE. */
+ unsigned char version;
+
struct dwarf2_cie *next;
};
@@ -138,6 +144,16 @@ struct dwarf2_frame_state
LONGEST data_align;
ULONGEST code_align;
ULONGEST retaddr_column;
+
+ /* Flags for known producer quirks. */
+
+ /* The ARM compilers, in DWARF2 mode, assume that DW_CFA_def_cfa
+ and DW_CFA_def_cfa_offset takes a factored offset. */
+ int armcc_cfa_offsets_sf;
+
+ /* The ARM compilers, in DWARF2 or DWARF3 mode, may assume that
+ the CFA is defined as REG - OFFSET rather than REG + OFFSET. */
+ int armcc_cfa_offsets_reversed;
};
/* Store the length the expression for the CFA in the `cfa_reg' field,
@@ -430,6 +446,10 @@ bad CFI data; mismatched DW_CFA_restore_
case DW_CFA_def_cfa:
insn_ptr = read_uleb128 (insn_ptr, insn_end, &fs->cfa_reg);
insn_ptr = read_uleb128 (insn_ptr, insn_end, &utmp);
+
+ if (fs->armcc_cfa_offsets_sf)
+ utmp *= fs->data_align;
+
fs->cfa_offset = utmp;
fs->cfa_how = CFA_REG_OFFSET;
break;
@@ -444,6 +464,10 @@ bad CFI data; mismatched DW_CFA_restore_
case DW_CFA_def_cfa_offset:
insn_ptr = read_uleb128 (insn_ptr, insn_end, &utmp);
+
+ if (fs->armcc_cfa_offsets_sf)
+ utmp *= fs->data_align;
+
fs->cfa_offset = utmp;
/* cfa_how deliberately not set. */
break;
@@ -715,6 +739,49 @@ dwarf2_frame_eh_frame_regnum (struct gdb
return regnum;
return ops->eh_frame_regnum (gdbarch, regnum);
}
+
+static void
+dwarf2_frame_find_quirks (struct dwarf2_frame_state *fs,
+ struct dwarf2_fde *fde)
+{
+ static const char *arm_idents[] = {
+ "ARM C Compiler, ADS",
+ "Thumb C Compiler, ADS",
+ "ARM C++ Compiler, ADS",
+ "Thumb C++ Compiler, ADS",
+ "ARM/Thumb C/C++ Compiler, RVCT"
+ };
+ int i;
+
+ struct symtab *s;
+
+ s = find_pc_symtab (fs->pc);
+ if (s == NULL || s->producer == NULL)
+ return;
+
+ for (i = 0; i < ARRAY_SIZE (arm_idents); i++)
+ if (strncmp (s->producer, arm_idents[i], strlen (arm_idents[i])) == 0)
+ {
+ if (fde->cie->version == 1)
+ fs->armcc_cfa_offsets_sf = 1;
+
+ if (fde->cie->version == 1)
+ fs->armcc_cfa_offsets_reversed = 1;
+
+ /* The reversed offset problem is present in some compilers
+ using DWARF3, but it was eventually fixed. Check the ARM
+ defined augmentations, which are in the format "armcc" followed
+ by a list of one-character options. The "+" option means
+ this problem is fixed (no quirk needed). If the armcc
+ augmentation is missing, the quirk is needed. */
+ if (fde->cie->version == 3
+ && (strncmp (fde->cie->augmentation, "armcc", 5) != 0
+ || strchr (fde->cie->augmentation + 5, '+') == NULL))
+ fs->armcc_cfa_offsets_reversed = 1;
+
+ return;
+ }
+}
struct dwarf2_frame_cache
@@ -781,6 +848,9 @@ dwarf2_frame_cache (struct frame_info *n
fs->code_align = fde->cie->code_alignment_factor;
fs->retaddr_column = fde->cie->return_address_register;
+ /* Check for "quirks" - known bugs in producers. */
+ dwarf2_frame_find_quirks (fs, fde);
+
/* First decode all the insns in the CIE. */
execute_cfa_program (fde->cie->initial_instructions,
fde->cie->end, next_frame, fs, fde->eh_frame_p);
@@ -798,7 +868,10 @@ dwarf2_frame_cache (struct frame_info *n
{
case CFA_REG_OFFSET:
cache->cfa = read_reg (next_frame, fs->cfa_reg);
- cache->cfa += fs->cfa_offset;
+ if (fs->armcc_cfa_offsets_reversed)
+ cache->cfa -= fs->cfa_offset;
+ else
+ cache->cfa += fs->cfa_offset;
break;
case CFA_EXP:
@@ -1584,12 +1657,18 @@ decode_frame_entry_1 (struct comp_unit *
cie_version = read_1_byte (unit->abfd, buf);
if (cie_version != 1 && cie_version != 3)
return NULL;
+ cie->version = cie_version;
buf += 1;
/* Interpret the interesting bits of the augmentation. */
- augmentation = (char *) buf;
+ cie->augmentation = augmentation = (char *) buf;
buf += (strlen (augmentation) + 1);
+ /* Ignore armcc augmentations. We only use them for quirks,
+ and that doesn't happen until later. */
+ if (strncmp (augmentation, "armcc", 5) == 0)
+ augmentation += strlen (augmentation);
+
/* The GCC 2.x "eh" augmentation has a pointer immediately
following the augmentation string, so it must be handled
first. */
Index: gdb/dwarf2read.c
===================================================================
RCS file: /scratch/gcc/repos/src/src/gdb/dwarf2read.c,v
retrieving revision 1.206
diff -u -p -r1.206 dwarf2read.c
--- gdb/dwarf2read.c 2 Nov 2006 21:34:07 -0000 1.206
+++ gdb/dwarf2read.c 6 Nov 2006 19:46:19 -0000
@@ -2803,16 +2803,9 @@ read_file_scope (struct die_info *die, s
attr = dwarf2_attr (die, DW_AT_producer, cu);
if (attr)
cu->producer = DW_STRING (attr);
-
+
/* We assume that we're processing GCC output. */
processing_gcc_compilation = 2;
-#if 0
- /* FIXME:Do something here. */
- if (dip->at_producer != NULL)
- {
- handle_producer (dip->at_producer);
- }
-#endif
/* The compilation unit may be in a different language or objfile,
zero out all remembered fundamental types. */
@@ -2820,6 +2813,7 @@ read_file_scope (struct die_info *die, s
start_symtab (name, comp_dir, lowpc);
record_debugformat ("DWARF 2");
+ record_producer (cu->producer);
initialize_cu_func_list (cu);
Index: gdb/symtab.h
===================================================================
RCS file: /scratch/gcc/repos/src/src/gdb/symtab.h,v
retrieving revision 1.98
diff -u -p -r1.98 symtab.h
--- gdb/symtab.h 17 Oct 2006 20:17:45 -0000 1.98
+++ gdb/symtab.h 6 Nov 2006 19:46:19 -0000
@@ -846,9 +846,9 @@ struct symtab
char *debugformat;
- /* String of version information. May be zero. */
+ /* String of producer version information. May be zero. */
- char *version;
+ char *producer;
/* Full name of file as found by searching the source path.
NULL if not yet known. */


Guess a Number Game
Enter A Max Number upto which you want to guess.
Created By : Tushar Kumar Rajput


# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Code related to interfacing with a Neural Network in the DeepSparse Engine using python
"""
import os
import time
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy
from deepsparse.benchmark import BenchmarkResults
try:
from sparsezoo.objects import File, Model
except Exception:
Model = object
File = object
try:
# flake8: noqa
from deepsparse.cpu import cpu_details
from deepsparse.lib import init_deepsparse_lib
from deepsparse.version import *
except ImportError:
raise ImportError(
"Unable to import deepsparse python apis. "
"Please contact<EMAIL_ADDRESS>)
__all__ = ["Engine", "compile_model", "benchmark_model", "analyze_model"]
CORES_PER_SOCKET, AVX_TYPE, VNNI = cpu_details()
LIB = init_deepsparse_lib()
def _model_to_path(model: Union[str, Model, File]) -> str:
if not model:
raise ValueError("model must be a path, sparsezoo.Model, or sparsezoo.File")
if isinstance(model, str):
pass
elif Model is not object and isinstance(model, Model):
# default to the main onnx file for the model
model = model.onnx_file.downloaded_path()
elif File is not object and isinstance(model, File):
# get the downloaded_path -- will auto download if not on local system
model = model.downloaded_path()
if not isinstance(model, str):
raise ValueError("unsupported type for model: {}".format(type(model)))
if not os.path.exists(model):
raise ValueError("model path must exist: given {}".format(model))
return model
def _validate_batch_size(batch_size: int) -> int:
if batch_size < 1:
raise ValueError("batch_size must be greater than 0")
return batch_size
def _validate_num_cores(num_cores: Union[None, int]) -> int:
if not num_cores:
num_cores = CORES_PER_SOCKET
if num_cores < 1:
raise ValueError("num_cores must be greater than 0")
return num_cores
[docs]class Engine(object):
"""
Create a new DeepSparse Engine that compiles the given onnx file
for GPU class performance on commodity CPUs.
Note 1: Engines are compiled for a specific batch size and
for a specific number of CPU cores.
Note 2: multi socket support is not yet built in to the Engine,
all execution assumes single socket
| Example:
| # create an engine for batch size 1 on all available cores
| engine = Engine("path/to/onnx", batch_size=1, num_cores=None)
:param model: Either a path to the model's onnx file, a sparsezoo Model object,
or a sparsezoo ONNX File object that defines the neural network
:param batch_size: The batch size of the inputs to be used with the engine
:param num_cores: The number of physical cores to run the model on.
Pass None or 0 to run on the max number of cores
in one socket for the current machine, default None
"""
def __init__(self, model: Union[str, Model, File], batch_size: int, num_cores: int):
self._model_path = _model_to_path(model)
self._batch_size = _validate_batch_size(batch_size)
self._num_cores = _validate_num_cores(num_cores)
self._num_sockets = 1 # only single socket is supported currently
self._cpu_avx_type = AVX_TYPE
self._cpu_vnni = VNNI
self._eng_net = LIB.deepsparse_engine(
self._model_path, self._batch_size, self._num_cores, self._num_sockets
)
def __call__(
self,
inp: List[numpy.ndarray],
val_inp: bool = True,
) -> List[numpy.ndarray]:
"""
Convenience function for Engine.run(), see @run for more details
| Example:
| engine = Engine("path/to/onnx", batch_size=1, num_cores=None)
| inp = [numpy.random.rand(1, 3, 224, 224).astype(numpy.float32)]
| out = engine(inp)
| assert isinstance(out, List)
:param inp: The list of inputs to pass to the engine for inference.
The expected order is the inputs order as defined in the ONNX graph.
:param val_inp: Validate the input to the model to ensure numpy array inputs
are setup correctly for the DeepSparse Engine
:return: The list of outputs from the model after executing over the inputs
"""
return self.run(inp, val_inp)
def __repr__(self):
"""
:return: Unambiguous representation of the current model instance
"""
return "{}({})".format(self.__class__, self._properties_dict())
def __str__(self):
"""
:return: Human readable form of the current model instance
"""
formatted_props = [
"\t{}: {}".format(key, val) for key, val in self._properties_dict().items()
]
return "{}.{}:\n{}".format(
self.__class__.__module__,
self.__class__.__name__,
"\n".join(formatted_props),
)
@property
def model_path(self) -> str:
"""
:return: The local path to the model file the current instance was compiled from
"""
return self._model_path
@property
def batch_size(self) -> int:
"""
:return: The batch size of the inputs to be used with the model
"""
return self._batch_size
@property
def num_cores(self) -> int:
"""
:return: The number of physical cores the current instance is running on
"""
return self._num_cores
@property
def num_sockets(self) -> int:
"""
:return: The number of sockets the engine is compiled to run on;
only current support is 1
"""
return self._num_sockets
@property
def cpu_avx_type(self) -> str:
"""
:return: The detected cpu avx type that neural magic is running with.
One of {avx2, avx512}. AVX instructions give significant execution speedup
with avx512 > avx2.
"""
return self._cpu_avx_type
@property
def cpu_vnni(self) -> bool:
"""
:return: True if vnni support was detected on the cpu, False otherwise.
VNNI gives performance benefits for quantized networks.
"""
return self._cpu_vnni
[docs] def run(
self,
inp: List[numpy.ndarray],
val_inp: bool = True,
) -> List[numpy.ndarray]:
"""
Run given inputs through the model for inference.
Returns the result as a list of numpy arrays corresponding to
the outputs of the model as defined in the ONNX graph.
Note 1: the input dimensions must match what is defined in the ONNX graph.
To avoid extra time in memory shuffles, the best use case
is to format both the onnx and the input into channels first format;
ex: [batch, height, width, channels] => [batch, channels, height, width]
Note 2: the input type for the numpy arrays must match
what is defined in the ONNX graph.
Generally float32 is most common,
but int8 and int16 are used for certain layer and input types
such as with quantized models.
Note 3: the numpy arrays must be contiguous in memory,
use numpy.ascontiguousarray(array) to fix if not.
| Example:
| engine = Engine("path/to/onnx", batch_size=1, num_cores=None)
| inp = [numpy.random.rand(1, 3, 224, 224).astype(numpy.float32)]
| out = engine.run(inp)
| assert isinstance(out, List)
:param inp: The list of inputs to pass to the engine for inference.
The expected order is the inputs order as defined in the ONNX graph.
:param val_inp: Validate the input to the model to ensure numpy array inputs
are setup correctly for the DeepSparse Engine
:return: The list of outputs from the model after executing over the inputs
"""
if val_inp:
self._validate_inputs(inp)
return self._eng_net.execute_list_out(inp)
[docs] def timed_run(
self, inp: List[numpy.ndarray], val_inp: bool = True
) -> Tuple[List[numpy.ndarray], float]:
"""
Convenience method for timing a model inference run.
Returns the result as a tuple containing (the outputs from @run, time take)
See @run for more details.
| Example:
| engine = Engine("path/to/onnx", batch_size=1, num_cores=None)
| inp = [numpy.random.rand(1, 3, 224, 224).astype(numpy.float32)]
| out, time = engine.timed_run(inp)
| assert isinstance(out, List)
| assert isinstance(time, float)
:param inp: The list of inputs to pass to the engine for inference.
The expected order is the inputs order as defined in the ONNX graph.
:param val_inp: Validate the input to the model to ensure numpy array inputs
are setup correctly for the DeepSparse Engine
:return: The list of outputs from the model after executing over the inputs
"""
start = time.time()
out = self.run(inp, val_inp)
end = time.time()
return out, end - start
[docs] def mapped_run(
self,
inp: List[numpy.ndarray],
val_inp: bool = True,
) -> Dict[str, numpy.ndarray]:
"""
Run given inputs through the model for inference.
Returns the result as a dictionary of numpy arrays corresponding to
the output names of the model as defined in the ONNX graph.
Note 1: this function can add some a performance hit in certain cases.
If using, please validate that you do not incur a performance hit
by comparing with the regular run func
See @run for more details on specific setup for the inputs.
| Example:
| engine = Engine("path/to/onnx", batch_size=1)
| inp = [numpy.random.rand(1, 3, 224, 224).astype(numpy.float32)]
| out = engine.mapped_run(inp)
| assert isinstance(out, Dict)
:param inp: The list of inputs to pass to the engine for inference.
The expected order is the inputs order as defined in the ONNX graph.
:param val_inp: Validate the input to the model to ensure numpy array inputs
are setup correctly for the DeepSparse Engine
:return: The dictionary of outputs from the model after executing
over the inputs
"""
if val_inp:
self._validate_inputs(inp)
out = self._eng_net.execute(inp)
return out
[docs] def benchmark(
self,
inp: List[numpy.ndarray],
num_iterations: int = 20,
num_warmup_iterations: int = 5,
include_inputs: bool = False,
include_outputs: bool = False,
) -> BenchmarkResults:
"""
A convenience function for quickly benchmarking the instantiated model
on a given input in the DeepSparse Engine.
After executing, will return the summary statistics for benchmarking.
:param inp: The list of inputs to pass to the engine for benchmarking.
The expected order is the inputs order as defined in the ONNX graph.
:param num_iterations: The number of iterations to run benchmarking for.
Default is 20
:param num_warmup_iterations: T number of iterations to warm up engine before
benchmarking. These executions will not be counted in the benchmark
results that are returned. Useful and recommended to bring
the system to a steady state. Default is 5
:param include_inputs: If True, inputs from forward passes during benchmarking
will be added to the results. Default is False
:param include_outputs: If True, outputs from forward passes during benchmarking
will be added to the results. Default is False
:return: the results of benchmarking
"""
# define data loader
def _infinite_loader():
while True:
yield inp
return self.benchmark_loader(
loader=_infinite_loader(),
num_iterations=num_iterations,
num_warmup_iterations=num_warmup_iterations,
include_inputs=include_inputs,
include_outputs=include_outputs,
)
[docs] def benchmark_loader(
self,
loader: Iterable[List[numpy.ndarray]],
num_iterations: int = 20,
num_warmup_iterations: int = 5,
include_inputs: bool = False,
include_outputs: bool = False,
) -> BenchmarkResults:
"""
A convenience function for quickly benchmarking the instantiated model
on a give DataLoader in the DeepSparse Engine.
After executing, will return the summary statistics for benchmarking.
:param loader: An iterator of inputs to pass to the engine for benchmarking.
The expected order of each input is as defined in the ONNX graph.
:param num_iterations: The number of iterations to run benchmarking for.
Default is 20
:param num_warmup_iterations: T number of iterations to warm up engine before
benchmarking. These executions will not be counted in the benchmark
results that are returned. Useful and recommended to bring
the system to a steady state. Default is 5
:param include_inputs: If True, inputs from forward passes during benchmarking
will be added to the results. Default is False
:param include_outputs: If True, outputs from forward passes during benchmarking
will be added to the results. Default is False
:return: the results of benchmarking
"""
assert num_iterations >= 1 and num_warmup_iterations >= 0, (
"num_iterations and num_warmup_iterations must be non negative for "
"benchmarking."
)
completed_iterations = 0
results = BenchmarkResults()
while completed_iterations < num_warmup_iterations + num_iterations:
for batch in loader:
# run benchmark
start = time.time()
out = self.run(batch)
end = time.time()
completed_iterations += 1
if completed_iterations >= num_warmup_iterations:
# update results if warmup iterations are completed
results.append_batch(
time_start=start,
time_end=end,
batch_size=self.batch_size,
inputs=batch if include_inputs else None,
outputs=out if include_outputs else None,
)
if completed_iterations >= num_warmup_iterations + num_iterations:
break
return results
def _validate_inputs(self, inp: List[numpy.ndarray]):
if isinstance(inp, str) or not isinstance(inp, List):
raise ValueError("inp must be a list, given {}".format(type(inp)))
for arr in inp:
if arr.shape[0] != self._batch_size:
raise ValueError(
(
"array batch size of {} must match the batch size "
"the model was instantiated with {}"
).format(arr.shape[0], self._batch_size)
)
if not arr.flags["C_CONTIGUOUS"]:
raise ValueError(
"array must be passed in as C contiguous, "
"call numpy.ascontiguousarray(array)"
)
def _properties_dict(self) -> Dict:
return {
"onnx_file_path": self._model_path,
"batch_size": self._batch_size,
"num_cores": self._num_cores,
"num_sockets": self._num_sockets,
"cpu_avx_type": self._cpu_avx_type,
"cpu_vnni": self._cpu_vnni,
}
[docs]def compile_model(
model: Union[str, Model, File], batch_size: int = 1, num_cores: int = None
) -> Engine:
"""
Convenience function to compile a model in the DeepSparse Engine
from an ONNX file for inference.
Gives defaults of batch_size == 1 and num_cores == None
(will use all physical cores available on a single socket).
:param model: Either a path to the model's onnx file, a sparsezoo Model object,
or a sparsezoo ONNX File object that defines the neural network
:param batch_size: The batch size of the inputs to be used with the model
:param num_cores: The number of physical cores to run the model on.
Pass None or 0 to run on the max number of cores
in one socket for the current machine, default None
:return: The created Engine after compiling the model
"""
return Engine(model, batch_size, num_cores)
[docs]def benchmark_model(
model: Union[str, Model, File],
inp: List[numpy.ndarray],
batch_size: int = 1,
num_cores: int = None,
num_iterations: int = 20,
num_warmup_iterations: int = 5,
include_inputs: bool = False,
include_outputs: bool = False,
) -> BenchmarkResults:
"""
Convenience function to benchmark a model in the DeepSparse Engine
from an ONNX file for inference.
Gives defaults of batch_size == 1 and num_cores == None
(will use all physical cores available on a single socket).
:param model: Either a path to the model's onnx file, a sparsezoo Model object,
or a sparsezoo ONNX File object that defines the neural network
:param batch_size: The batch size of the inputs to be used with the model
:param num_cores: The number of physical cores to run the model on.
Pass None or 0 to run on the max number of cores
in one socket for the current machine, default None
:param inp: The list of inputs to pass to the engine for benchmarking.
The expected order is the inputs order as defined in the ONNX graph.
:param num_iterations: The number of iterations to run benchmarking for.
Default is 20
:param num_warmup_iterations: T number of iterations to warm up engine before
benchmarking. These executions will not be counted in the benchmark
results that are returned. Useful and recommended to bring
the system to a steady state. Default is 5
:param include_inputs: If True, inputs from forward passes during benchmarking
will be added to the results. Default is False
:param include_outputs: If True, outputs from forward passes during benchmarking
will be added to the results. Default is False
:return: the results of benchmarking
"""
model = compile_model(model, batch_size, num_cores)
return model.benchmark(
inp, num_iterations, num_warmup_iterations, include_inputs, include_outputs
)
[docs]def analyze_model(
model: Union[str, Model, File],
inp: List[numpy.ndarray],
batch_size: int = 1,
num_cores: int = None,
num_iterations: int = 20,
num_warmup_iterations: int = 5,
optimization_level: int = 1,
imposed_as: Optional[float] = None,
imposed_ks: Optional[float] = None,
) -> dict:
"""
Function to analyze a model's performance in the DeepSparse Engine.
The model must be defined in an ONNX graph and stored in a local file.
Gives defaults of batch_size == 1 and num_cores == None
(will use all physical cores available on a single socket).
:param model: Either a path to the model's onnx file, a sparsezoo Model object,
or a sparsezoo ONNX File object that defines the neural network
graph definition to analyze
:param inp: The list of inputs to pass to the engine for analyzing inference.
The expected order is the inputs order as defined in the ONNX graph.
:param batch_size: The batch size of the inputs to be used with the model
:param num_cores: The number of physical cores to run the model on.
Pass None or 0 to run on the max number of cores
in one socket for the current machine, default None
:param num_iterations: The number of times to repeat execution of the model
while analyzing, default is 20
:param num_warmup_iterations: The number of times to repeat execution of the model
before analyzing, default is 5
:param optimization_level: The amount of graph optimizations to perform.
The current choices are either 0 (minimal) or 1 (all), default is 1
:param imposed_as: Imposed activation sparsity, defaults to None.
Will force the activation sparsity from all ReLu layers in the graph
to match this desired sparsity level (percentage of 0's in the tensor).
Beneficial for seeing how AS affects the performance of the model.
:param imposed_ks: Imposed kernel sparsity, defaults to None.
Will force all prunable layers in the graph to have weights with
this desired sparsity level (percentage of 0's in the tensor).
Beneficial for seeing how pruning affects the performance of the model.
:return: the analysis structure containing the performance details of each layer
"""
model = _model_to_path(model)
num_cores = _validate_num_cores(num_cores)
batch_size = _validate_batch_size(batch_size)
num_sockets = 1
eng_net = LIB.deepsparse_engine(model, batch_size, num_cores, num_sockets)
return eng_net.benchmark(
inp,
num_iterations,
num_warmup_iterations,
optimization_level,
imposed_as,
imposed_ks,
)


The light drill is gonna turn your game into something never seen before. It has 3 lights on it randomly lighting up, and when you wave your hand over the light they turn off. Forcing the player to become more comfortable with dribbling and forcing them to look up.
The light drill was designed for the most advanced basketball players to beginners. Challenging your dribbling and hand eye coordination skills, to turn you into the best basketball player the world has ever seen.
With the light drill we are focusing on the most fundamental part of basketball, and improving it to an elite level. We use our advanced technology to exponentially improve your skills over a short period of time.


public class StatisticsObject
extends java.lang.Object
| Constructor and Description |
|---|
StatisticsObject(long secondsPlayed,
long jumpsMade,
long levelsFinished,
long diedThisManyTimes,
long healthLost,
long damageInflicted,
long enemiesKilled,
long itemsCollected,
long[] highscoreTimes) |
| Modifier and Type | Method and Description |
|---|---|
long |
getDamageInflicted() |
long |
getDiedThisManyTimes() |
long |
getEnemiesKilled() |
long |
getHealthLost() |
long[] |
getHighscoreTimes() |
long |
getItemsCollected() |
long |
getJumpsMade() |
long |
getLevelsFinished() |
long |
getSecondsPlayed() |
void |
setDamageInflicted(long damageInflicted) |
void |
setDiedThisManyTimes(long diedThisManyTimes) |
void |
setEnemiesKilled(long enemiesKilled) |
void |
setHealthLost(long healthLost) |
void |
setHighscoreTimes(long[] highscoreTimes) |
void |
setItemsCollected(long itemsCollected) |
void |
setJumpsMade(long jumpsMade) |
void |
setLevelsFinished(long levelsFinished) |
void |
setSecondsPlayed(long secondsPlayed) |
public StatisticsObject(long secondsPlayed, long jumpsMade, long levelsFinished, long diedThisManyTimes, long healthLost, long damageInflicted, long enemiesKilled, long itemsCollected, long[] highscoreTimes)
secondsPlayed
- the time played in secondsjumpsMade
- the jumps madelevelsFinished
- the levels finished (counts if one level is completed multiple times)diedThisManyTimes
- the overall deathshealthLost
- the health lost to enemies or other damage inflicting actionsdamageInflicted
- the damage inflicted to enemiesenemiesKilled
- the total amount of killed enemiesitemsCollected
- the amount of items collectedhighscoreTimes
- the highscore list of each level containing times in secondspublic long getSecondsPlayed()
public void setSecondsPlayed(long secondsPlayed)
public long getJumpsMade()
public void setJumpsMade(long jumpsMade)
public long getLevelsFinished()
public void setLevelsFinished(long levelsFinished)
public long getDiedThisManyTimes()
public void setDiedThisManyTimes(long diedThisManyTimes)
public long getHealthLost()
public void setHealthLost(long healthLost)
public long getDamageInflicted()
public void setDamageInflicted(long damageInflicted)
public long getEnemiesKilled()
public void setEnemiesKilled(long enemiesKilled)
public long getItemsCollected()
public void setItemsCollected(long itemsCollected)
public long[] getHighscoreTimes()
public void setHighscoreTimes(long[] highscoreTimes)


Shocks are a common phenomenon in the ISM. They can be generated by a number of things:
In short, the ISM is a very dynamic fluid, full of shocks, magnetic fields, and driven supersonic turbulence. In addition, radiative processes play an important role in modifying shock structure (we have not included these effects in our module). Shocked gas is able to cool radiatively if it has propagated long enough time-scales, making energy loss important.
Excellent in-depth tours that show where shocks may be relevant to the ISM and where they are observed are found at the following ISM module links: [MacGregor, Landmarks of the ISM], [Alexander, The Multiphase ISM]. Below are a couple of highlights from observations and simulations.
False color image of a supernova remnant SN 1604 (Kepler's SN; ref). Such objects drive shocks in the ISM:
For more information on the evolution of SN, the link here is a blog post from our Astronomy 201b ISM blog, highlighting the importance of magnetic fields and shocks.
Energy injection (feedback) from stars leads to a very turbulent ISM filled with shocks. Below is a 3D simulation of the turbulent structure by Stella Offner and collaborators (ref):
I also created a subsonic turbulent simulation using the moving mesh fluid solver code AREPO. Below is a movie of the time evolution of the velocity magnitude.
Despite its complicated appearance, such turbulent fluids have certain characteristic properties. Such supersonic, shock-filled fluids as observed in the ISM (Burgers Turbulence) show a powerlaw distribution of kinetic energy at different length scales as well as approximately log-normal density fields.


f3fix
Edit the partition table of a fake flash drive.
See also `f3probe`, `f3write`, `f3read`.
More information: home page
- Fill a fake flash drive with a single partition that matches its real capacity:
sudo f3fix /dev/device_name
- Mark the partition as bootable:
sudo f3fix --boot /dev/device_name
- Specify the filesystem:
sudo f3fix --fs-type=filesystem_type /dev/device_name


The Nest expression language used the jstl expression language as a jumping off point, but tries to be as PHP as possible. Since php has methods like __get and __set there didn't seem to be any point to using bean introspection like java.
Expressions can be between the token tags ${}, or in tag attributes without the tags. The syntax is just like PHP except that attributes are specified without the leading $.
You can specify html text that shouldn't be escaped with #{}. Be aware that doing so can potentially leave you exposed to XSS attacks. Be sure you cleanse the data you're presenting this way.
The simplest form of the expression language are simply outputting variables as we've prevously introduced. The name will be the key when adding the attribute to the view.
$view->addAttribute("myVariable", "myValue"); ${myVariable} Output: myValue
Arrays are accessed just like in php.
Public object members and methods are accessed just like in php.
Mathematical expressions can be done just like in PHP.
${1 == 1} ${1 == 0} ${myVar % 5} ${(1000 * 50) / myvar} ${myvar->price * myvar->tax}
Conditional expressions can be evaluated just like in PHP.
${1 == 1 || myVar == 'bob'} ${1 == myVar && access == 'admin'} ${rowcount % 2 ? 'green' : 'red'}


---
layout: post
title: 'Cut the cord yet? COMCAST wants customer to sign NDA for refund. '
date: '2015-05-15T07:31:00.000-07:00'
author: gojimmypi
tags:
modified_time: '2015-09-13T11:31:36.324-07:00'
blogger_id: tag:blogger.com,1999:blog-4109066286647243251.post-5932444601924042616
blogger_orig_url: https://gojimmypi.blogspot.com/2015/05/cut-cord-yet-comcast-wants-customer-to_15.html
---
and cable companies wonder why they have been losing customers for years....
http://arstechnica.com/business/2015/05/read-the-nda-a-comcast-customer-was-told-to-sign-to-get-a-600-refund/?comments=1
Copyright (c) gojimmypi all rights reserved. Blogger Image Move Cleaned: 5/3/2021 1:35:50 PM


Synalyze
NLP/NLU towards optimizing business meetings
Machine learning (specifically NLP and RL) afficionado and dabbler in many related spheres of technology
About meFirst off, I'm not generally a web or front-end developer. I'm instead interested and passionate about machine learning and artificial intelligence: you can find a showcase of some of my pertinent (and non-pertinent projects) below. Since I'm assuming few people actually want to read about my background, that's probably all I'm gonna say here. But wait, if you want more, feel free to explore my blog!
Much of my past experience was in mathematical modelling and analytics, from health regimes to cryptocurrency
ML (specifically natural language processing) perfectly combines the aspects of math and CS that intrigue me towards awesome projects
Even though my main interests are outside pure web development, many of the projects developed below are showcased on custom websites
Began developing in AR development for the Apple platforms with their recent release of the ARKit SDK
Developed projects deployed using standard cloud services (EC2, EBS) and developer tools that use many of the more niche AWS services (SNS, SQS)
Capable of setting up and maintaining Linux servers, specifically Ubuntu and RHEL, largely on the web end.
Thanks for browsing through my profile! Feel free to reach out through any of the links provided below with any thoughts/comments on these projects, suggestions for others, and/or other general comments!
Feel free to reach out to me through any form of social media or email!


First Month of Waterloo Engineering
Oh man, it’s October already? Time really does fly in university…
My first month in university was incredible. Without a doubt, it was one of the best months of my life. You guys are probably wondering right now: “Bo, what made your month so special?” My response would be: “Everything.”
Academics
First thing’s first, we go to university to learn and indulge in the world of academics. I’m studying Software Engineering, one of the most competitive and rigorous programs in Canada. I am taking six courses: linear algebra, calculus, linear circuits, physics, computer science and a Software Engineering course. This approximates to about 30 hours of class each week. I’ve attached my schedule below, and you can see that from Monday-Thursday I have class from 8:30AM-6:00PM. On Friday, it’s only 8:30AM-1:30PM. The blue represent my lectures, tutorials, labs and seminars. The purple represent due dates, office hours, and other miscellaneous events.
In each course, we either have weekly assignments, quizzes, labs, or a combination of the above. Fortunately, they’re only worth up to 20% of your mark, so doing poorly on one of them won’t kill your mark. They definitely teach you to properly manage your time and prepare you for the big midterm and final exams. As you can imagine, waking up to morning classes every single day is quite tiring. It’s important to get as much sleep as you can, but sometimes it’s quite difficult (unless you have a great work ethic). It’s essential to review your notes and do the assignments to ensure a good understanding of concepts.
To be honest, I started off the year with a poor work ethic, worrying more about my social life than homework. I have slowly been improving my work ethic and have almost caught up! Falling behind in a course is NOT recommended. My advice is to finish your assignments and work well before they are due. DO NOT start your assignment the night before it’s due. Speaking from my personal experience, it’s a horrible idea. This isn’t high school anymore, where you can breeze through homework and assignments in under an hour.
In first-year engineering, students have this week called “Hell Week”, where they have an entire week dedicated for midterms. I don’t have any classes during this week, but the thought of having 5 midterm exams in 5 days is quite intimidating. For the next two weeks, I’m going to be working super hard to get the best marks I can. Hopefully, when I blog about my midterms in two weeks from now, I’ll be in a happy mood.
Extracurriculars
I LOVE extracurriculars and doing stuff outside of the classroom. Actually, I think I like them a bit too much because they’re eating up a big chunk of my time. In high school, I was involved in this awesome club called “SAGE (Students for the Advancement of Global Entrepreneurship.” Basically, students team up to create and implement entrepreneurial projects that addresses a social problem within the community. Joining SAGE was probably one of the best decisions I made in high school.
Because of my involvement with SAGE, I decided to start and lead an Enactus chapter at Waterloo. The logistics involved with starting a club was quite time consuming, but we are now officially a registered club at the University of Waterloo and are affiliated with Enactus Canada. We managed to find an incredible and experienced Faculty Advisor.
The purpose of our club is to utilize the power of social entrepreneurship to transform lives and shape a better world. We will create and implement community projects that empower the lives of individuals to improve their standard of living and quality of life. We will present our projects at the Enactus regional and national competitions where we will be evaluated by global leaders and executives serving as judges. Club members will have the opportunity to attend conferences, competitions, and workshops to enhance their professional development. I will start recruiting members and executives after my “Hell Week” ends. Enactus Waterloo is going to be one heck of a ride!
In addition to starting my own club, I’m involved in a bunch of other clubs. I was elected to be the Engineering Society representative of my Software Engineering class. Check out our class’s website. I’ve only attended two meetings so far, but I can confidently say EngSoc meetings are hilarious! I am going to be attending their events on a regular basis and also volunteer for them. In the future, I’m looking forward to obtaining director and executive roles in Engineering Society.
I am also a Waterloo Engineering Ambassador. I would recommend checking out the Waterloo Engineering Shadow Program. You’ll get to experience a day-in-the-life of an Engineering student! I went on two shadow days last year, and it was two great learning experiences. As an Engineering Ambassador now, it feels like a full circle.
Social Life
Too many stories. Too many awesome moments. I’m compiling a big list of memorable moments at Waterloo and it’s quite long already. I’ll definitely share some of these moments with you guys later. I just want to make it clear that Waterloo is not anti-social. To be more exact, no place is anti-social, it all depends on the person. Let’s just say that I’ve partied at least once every single weekend and that they’re EPICLY FUN.  I’m going to have to sacrifice some aspects of my social life over the next two weeks to focus on exams.
Sleep
The magic number is 49. How did I get that number? 7 days * 7 hours per day. You should aim for that many hours of sleep each week. Personally, I’m falling a bit under 49 hours/ week of sleep due to academics and social life.
Fun fact.
There was one week where I got free dinner every single night. How did I pull this off?
Club meetings, employer info sessions, tech talks always have free food!


Simple expressions
Write a function returning the sum of five integers.
Same question, whithout explicitly writing any abstraction.
Solution
This file
Going home
Pierre Castéran


We are a team of three.
Alex is of Italian ancestry, Benita of Chinese, and Nishanth of South Indian. When we felt that our cultures were different but our love towards food was the same, What The Fork was born. It is a project done for Web Media Production unit at Curtin University for Semester 2, 2019. Benita and Nishanth are master's students and Alex is in his final year of Bachelors.


{include file="Public:header" /}
{include file="Public:nav" /} {include file="Public:footer" /} {include file="Public:form" /} {js file='/static/admin/js/plugins/Sortable/Sortable.min.js' /} {css file='/static/admin/css/wechat/reply.css' /} {js file='/static/admin/js/wechat/reply.js' /}


refactorized version of edu.cmu.lti.nlp.chinese.tagger tested to have similar performance, but not used in J3 yet


Deploy Serverless Kotlin App To Amazon AWS
In this article, we’ll implement a basic Kotlin function and deploy it as AWS Lambda. AWS Lambda is a serverless architecture which lets us to run code without managing servers and the main advantage of this architecture is, this function executes only when needed and scales automatically. AWS charges only for the compute time and there are no charges incurred when the code is not running.
For basic usage we no need to pay anything we just need AWS account. See this link for AWS lambda pricing. Free tier gets 1M requests and 40,000 GB-seconds of compute time per month. This limit is more than enough for our simple application.
I am going to use serverless CLI tool to develop our basic function. serverless: is a simple CLI tool helps us to create, manage and deploy lambda functions and it works with major providers (AWS, Azure, Google, Fn and many more). The main advantage of using this is, it provides single CLI interface for many providers so we no need to learn deployment process for each provider. To install it, make sure you have npm installed on your computer and execute below command;
This command will install serverless globally.
This whole project is available here.
Create AWS Kotlin application
Lets create new Kotlin project. Go to terminal and execute below commands;
We created new folder hello-kotlin for our project and moved into it. sls is the shortcut command for serverless so I used short version. We are creating new project so mention create as sub-command by providing –template to it. In our case we need Kotlin project so I passed aws-kotlin-jvm-maven. Click here to see complete list of available templates for AWS.
Below are the list of files it created in my local
In the next section we will learn about the generated function and configuration.
Lambda function
Serverless generates a normal Kotlin project except with one special file serverless.yml. Serverless depends on this file because it contains the whole configuration needed to deploy and configure lambda. It also creates three Kotlin files out of them Handler.kt is the important file. Below is the content of this file;
Class Handler implements RequestHandler interface which contains single function handleRequest. We need to implement this function because it is the starting point of lambda execution. AWS executes this function by passing input and context. These objects are needed if you want to read input from the request and context is to get the context of execution environment. handleRequest function uses two utility classes Response.kt and ApiGatewayResponse.kt to construct the Response. In this case we are building the response by setting statusCode to 200 and Response with some text and adding custom header ‘X-Powered-By’.
This is a simple function with out much functionality it just responds with some text.
Configuration
serverless.yml comes with basic configuration. I removed everything it comes with and replaced with below configuration.
Properties in this file are self explanatory.
- service is a unique name for this function.
- provider contains provider specific configuration.
- package is the artifact name which is generated in the target folder at the build time.
- functions contains list of functions with there configuration. Each function needs the handler. Handler is the class which implements RequestHandler and we need to provide the events on which this function gets triggered. There are many ways to trigger functions like HTTP, CRON or event based. Here we want our function to get executed when it receives a HTTP request on hello path.
Configure credentials
In-order for serverless to connect AWS it needs our credentials because it will upload and deploy lambda on behalf of us. Follow below steps to configure this.
- Login into AWS Management Console
- Go to Security Credentials page by clicking on the user name at the top right of the page and selecting My Security Credentials from the drop-down menu.
- A confirmation dialog appears so click on Continue to Security Credentials
- Under Access keys click on Create New Access Key which will create new keys and displays them in the new dialog. Click on Show Access Key to view them. Remember to save these values because later you may need them for the reference and keep them securely.
- We need these access keys to set them in serverless so go back to the terminal and execute below command
Replace Access Key ID and Secret Access Key with the values displayed in the AWS Console.
Build & deploy
We have configured our function and now lets build it. Since this is a maven application so we can either use IDE or maven commands to build our application. Here I used maven command to build the application;
Build got completed now lets deploy our app to AWS by executing below command;
It takes some time to deploy. Once the deploy completes then the output shows some key information. Copy the endpoint which is displayed after deployment to your browser and hit. If everything goes normal then you should see response from our function. Our function responds with the message and HTTP headers.
URL will be like **https://
/dev/hello/create**
You can go to AWS lambda console to see more details about this function and also you can even test it from there.
Conclusion
We created a simple Kotlin function and deployed to AWS lambda using serverless. This function returns a text along with HTTP headers in the response. Click here to access the source code.


| Language | File(s) | A | B | C | D | E | F | G | H |
|---|---|---|---|---|---|---|---|---|---|
| Assembly | retro.s | x | x | x | x | x | x | x | x |
| C | retro.c | x | x | x | x | x | x | x | x |
| C | libretro.c | x | x | x | x | x | x | x | x |
| C# | retro.cs | x | x | x | x | X | x | x | x |
| F# | retro.fsx | x | x | x | x | x | x | x | x |
| Forth | retro.fs | x | x | x | x | x | x | x | |
| Go | go/ | x | x | x | x | x | x | x | x |
| Lisp | lisp/ | x | x | x | x | x | x | x | x |
| Java | retro.java | x | x | x | x | ||||
| Lua | retro.lua | x | x | x | x | ||||
| Perl | retro.pl | x | x | x | x | ||||
| PHP | retro.php | x | x | x | x | x | x | x | x |
| Python | retro.py | x | x | x | x | x | x | x | x |
| Retro | retro.rx | x | x | x | x | x | x | x | x |
| Ruby | retro.rb | x | x | x | x | x | x | x | x |
| Scheme | retro.scm | x | x | ||||||
| JavaScript | html5/* | x | x | x | x |
This is for 32-bit x86 Linux systems.
If you have problems with the input (e.g., under PuTTY), try:
cat - | ./retro retroImage
The C implementation is the oldest and most flexible of the VM implementations. It is feature complete, can track opcode and stack usage, and serves as the reference implementation.
Thiis implementation can be built for 16-bit, 32-bit, or 64-bit cell sizes in little or big endian. The default settings are for a standard little endian, 32-bit image.
Add one of the following flags via CFLAGS to get a non-standard configuration:
| Flag | Usage |
|---|---|
| -DRX16 | 16-bit cells |
| -DRX64 | 32-bit cells |
| -DRXBE | Big endian cells |
To generate a non-standard image, use:
make images
The Forth VM is more of a virtualizer than an actual virtual machine. It maps the image to the host memory, and uses the standard Forth data stack and some native functions. As such it needs to be used with an image that matches your Forth's cell size.
There is no support for getEnv due to lack of a standard function to access this in ANS Forth.
You can build 16-bit and 64-bit images using:
make images
The Lua implementation requires Lua JIT or Lua 5.2. Earlier releases of Lua lack the bitwise operators. Note that a single line needs to be altered in the source to enable use under Lua 5.2.
This implementation does not support include, needs, getEnv, or the files' vocabulary. The scripts used to build the retroImage.js now hide these functions.
Retro can be used on some development boards. There may be limitations to the overall functionality, or special extensions to use features of the target platforms. See the individual implementations for notes.
| CPU | Board |
|---|---|
| ARM | mbed LPX1768 |
| AVR | arduino mega |
| PIC32 | various |
These are all either non-standard in some way or remain mostly untested in real-world applications.
| Language | File(s) | Description |
|---|---|---|
| C | retroht.c | Faster implementation using a hybrid threading model. |
| C | retro-dynamic.c | Provides command line flags for altering stack depth and memory size |
| C | sdl/ | SDL 1.3 based Ngaro w/support for canvas |
| C | retro-sockets.c | Has the non-standard socket device from Retro 10.x |
| Python | retro-skinless.py | Python implementation w/o file I/O for use in testing the ShedSkin compiler |


SSELP(1) suckless-tools SSELP(1) NAME sselp - simple print selection SYNOPSIS sselp DESCRIPTION sselp prints X selection to standard out. OPTIONS sselp has no options. SEE ALSO Homepage <http://www.suckless.org/> AUTHOR sselp was written by Anselm R. Garbe<EMAIL_ADDRESS>and Sander van Dijk<EMAIL_ADDRESS>This manual page was written by Daniel Baumann<EMAIL_ADDRESS>for the Debian project (but may be used by others). 0.1 2008-08-03 SSELP(1)


{% extends 'admin/base.html' %} {% block head %} {% endblock %} {% block body %} User Management Enrolled Users {{ users_count }} Add User add Edit User create Delete User delete_forever {% endblock %}


{% extends "base.html" %} {% block content %}
There was an error and the server crashed... Please report to the service center(010-2901-5627) or try again . We'll find an solution to this problem soon!


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Most website designers do not optimize websites for search engines. What is the point of a new website if your visitors are not able to find it? Get your new website with search engine optimization built in from the start so you can start getting traffic faster!


About
the
Bakers
Kendal and Kelby's Cheesecakes is a small business startrs by two twin sisters. We have always loved cooking and started making cheesecake in high school for our family. Since then, we've been working to perfect our recipe. Currently, we are both full time students at the University of Miami, with major in economics and ecosystem science and policy. We hope that one day we can share our cheesecakes with more people, and open a store!
@kkcheesecakes


Copyright © 2003 W3C® (MIT, ERCIM, Keio), All Rights Reserved. W3C liability, trademark, document use and software licensing rules apply.
This specification defines a subset of Cascading Style Sheets Level 2 and CSS3 Module: Color specifications tailored to the needs and constraints of TV devices.
This section describes the status of this document at the time of its publication. Other documents may supersede this document. The latest status of this document series is maintained at the W3C.
This specification is being put forth as a W3C Candidate Recommendation by the CSS Working Group (part of the Style Activity, see summary). This document is an editorial revision of the Candidate Recommendation dated 2002-08-07 and has incorporated editorial suggestions made after publication of the previous Candidate Recommendation draft, in addition to updating the supported values for the 'opacity' property in sync with the CSS3 Module: Color Candidate Recommendation draft. The previous draft of this specification, the Candidate Recommendation dated 2002-08-07, was a revision of the Last Call Working Draft dated 2002-05-15, and incorporated suggestions received during Last Call review, comments by implementors, and further deliberations of the W3C CSS Working Group.
All persons are encouraged to review and implement this specification and return comments to the (archived) public mailing list www-style (see instructions). W3C Members can also send comments directly to the CSS Working Group.
For this specification to exit the CR stage, the following conditions shall be met:
There must be at least two interoperable implementations implementing 'all' the features in the TV Profile. An implementation can implement a superset of the features and claim conformance to the profile. For the purposes of this criterion, we define the following terms:
a row in the tables of section 3 and section 4 that has not been marked 'No' in the CSS TV column.
passing the respective test case(s) in the CSS test suite, or, if the implementation is not a web browser, an equivalent test. Every relevant test in the test suite should have an equivalent test created if such a user agent (UA) is to be used to claim interoperability. In addition if such a UA is to be used to claim interoperability, then there must one or more additional UAs which can also pass those equivalent tests in the same way for the purpose of interoperability. The equivalent tests must be made publicly available for the purposes of peer review.
a user agent which:
A minimum of sixth months of the CR period must have elapsed. This is to ensure that enough time is given for any remaining major errors to be caught.
The CSS Working Group believes this document addresses all last call comments, and can be considered stable. It can still be updated by the Working Group, but only to clarify its meaning. If, unexpectedly, serious problems are found, it will be returned to Working Draft status. The duration of the original six month Candidate Recommendation phase (August 2002 - January 2003) has already passed. Therefore, as soon as the exit criteria are met, it will progress to Proposed Recommendation.
Patent disclosures relevant to CSS may be found on the Working Group's public patent disclosure page.
A list of current W3C Recommendations and other technical documents can be found at http://www.w3.org/TR.
This document specifies a profile of the Cascading Style Sheets level 2 (CSS2) and CSS3 Module: Color specifications appropriate for TV devices such as set top boxes or integrated interactive television sets that display their output on a television screen. Conformance to this profile means that a user agent supports, at minimum, the features defined in this specification. This subject is addressed in Section 2, Conformance, below.
As defined in [CSS2]:
CSS2 is a style sheet language that allows authors and users to attach style (e.g., fonts, spacing, and aural cues) to structured documents (e.g., HTML documents and XML applications). By separating the presentation style of documents from the content of documents, CSS2 simplifies Web authoring and site maintenance. CSS2 builds on CSS1 (see [CSS1]) and, with very few exceptions, all valid CSS1 style sheets are valid CSS2 style sheets. CSS2 supports media-specific style sheets so that authors may tailor the presentation of their documents to visual browsers, aural devices, printers, braille devices, handheld devices, etc.
In summary, CSS2 specifies how developers can author style sheets for presenting documents across multiple devices and media types. While this is very important, it is also important that authors have an understanding of what features are supported on these different devices. Likewise, it is important that similar devices operate in a similar manner. Otherwise, authors will need to develop style sheets for each version of each device -- raising the cost of content development and decreasing interoperability.
The CSS TV Profile specifies a conformance profile for TV devices, identifying a minimum set of properties, values, selectors, and cascading rules. The resulting CSS TV Profile includes the vast majority of CSS1, portions of CSS2 and CSS3 Module: Color. The CSS TV Profile is a proper superset of the CSS Mobile Profile, with the use of the 'tv' media type instead of the 'handheld' media type.
The primary role of a profile is to define a subset of features that provides a minimal guarantee of interoperability. In the case of the CSS TV Profile, this guarantee is that a conforming user agent will support the features defined in this specification following the CSS2 conformance clause ([CSS2] Section 3.2), recast and summarized below:
As with CSS2, there are qualifications to this conformance clause:
It is recommended that authors use this conformance profile to take advantage of forward compatibility. Authors should be able to use style properties with an understanding that the cascading rules are processed correctly and that unknown properties and values are ignored. For example:
h3 { display: inline; display: run-in; }
A TV-UA that can process the 'run-in' value for the 'display' property will accept the first display declaration and then "write over" that value with the second display declaration. A TV-UA that cannot process the 'run-in' value will process the first display specification and ignore the second display specification.
In CSS2, pattern matching rules determine which style rules apply to elements in the document tree [CSS2].
The following table summarizes CSS TV Profile selector syntax. In addition to these selectors, the CSS TV Profile includes the CSS2 grouping mechanism (See [CSS2] Section 5.2.1).
Note. Unsupported selectors are parsed as invalid (which would affect valid selectors in the same group), the same as if a purely CSS1 UA were to encounter selectors new in CSS2. Of course a TV-UA is free to implement more selectors than required by CSS TV.
| Pattern | Meaning | Selector type | CSS TV |
|---|---|---|---|
| * | Matches any element | Universal selector | Yes |
| E | Matches any E element (i.e., and element of type E) | Type selectors | Yes |
| E F | Matches any F element that is a descendent of an E element | Descendent selectors | Yes |
| E > F | Matches any F element that is a child of an element E | Child selectors | Yes |
| E:first-child | Matches element E when it is the first child of its parent | The :first-child pseudo-class | Yes |
| E:link E:visited |
Matches element E if E is the source anchor of a hyperlink of which the target is not yet visited (:link) or already visited (:visited). | The link pseudo-classes | Yes |
| E:active | Matches E during certain user actions. | The dynamic pseudo-classes | Yes |
| E:hover | Matches E during certain user actions. | The dynamic pseudo-classes | No |
| E:focus | Matches E during certain user actions. | The dynamic pseudo-classes | Yes |
| E:lang(c) | Matches element of type E if it is in (human) language c (the document language specifies how language is determined). | The :lang() pseudo-class | No |
| E + F | Matches any F element immediately preceded by an element E. | Adjacent selectors | No |
| E[foo] | Matches any E element with the "foo" attribute set (whatever the value). | Attribute selectors | No |
| E[foo="bar"] | Matches any E element whose "foo" attribute value is exactly equal to "bar". | Attribute selectors | No |
| E[foo~="bar"] | Matches any E element whose "foo" attribute value is a list of space-separated values, one of which is exactly equal to "bar". | Attribute selectors | No |
| E[foo|="bar"] | Matches any E element whose "foo" attribute value has a hyphen-separated list of values beginning (from the left) with "bar". | Attribute selectors | No |
| E:first-line | Matches the first formatted line of an E element. | The :first-line pseudo-element | Yes |
| E:first-letter | Matches the first formatted letter of an E element. | The :first-letter pseudo-element | Yes |
| E:before | Matches/creates generated content before an E element. | The :before pseudo-element | No |
| E:after | Matches/creates generated content after an E element. | The :after pseudo-element | No |
| E.bar | Matches any E element whose class attribute (as defined by the document language) value is a list of space-separated values, one of which is exactly equal to "bar". | Class selectors | Yes |
| E#bar | Matches any E element whose ID attribute (as defined by the document language) is equal to "bar". | ID selectors | Yes |
The following table summarizes CSS TV Profile at-rule syntax.
| at-rule | Function | CSS TV |
|---|---|---|
| @import | Imports an external style sheet. | Yes |
| @charset | Defines character set for the style sheet. | Yes |
| @media | Groups a set of style rules to apply only to one or more particular media. | Yes |
| @font-face | Defines a named font-family, including for downloading. | No |
| @page | Defines a (optionally named) page formatting context. | No |
| @color-profile | Defines a named color-profile. | No |
The following table summarizes CSS TV Profile properties and property values from CSS2. Refer to [CSS2] for the definition of these properties and values.
| Name | CSS TV | CSS Values | Initial value |
|---|---|---|---|
| 'azimuth' | No | <angle> | [ left-side | far-left | left | center-left | center | center-right | right | far-right | right-side ] || behind ] | leftwards | rightwards | inherit | center |
| 'background' | ['background-color' || 'background-image' || 'background-repeat' || 'background-position'] | inherit | ['background-color' || 'background-image' || 'background-repeat' || 'background-attachment' || 'background-position'] | inherit | see individual properties |
| 'background-attachment' | No | scroll | fixed | inherit | scroll |
| 'background-color' | Yes | <color> | transparent | inherit | transparent |
| 'background-image' | Yes | <uri> | none | inherit | none |
| 'background-position' | Yes | [ [ <percentage> | <length> ]{1,2} | [ [top | center | bottom] || [left | center | right] ] ] | inherit | 0% 0% |
| 'background-repeat' | Yes | repeat | repeat-x | repeat-y | no-repeat | inherit | repeat |
| 'border' | Yes | [ <border-width> || <border-style> || <border-color> ] | inherit | see individual properties |
| 'border-collapse' | No | collapse | separate | inherit | separate |
| 'border-color' | Yes | <color>{1,4} | transparent | inherit | see individual properties |
| 'border-spacing' | No | <length> <length>? | inherit | 0 |
| 'border-style' | Yes | <border-style>{1,4} | inherit | see individual properties |
| 'border-top' 'border-right' 'border-bottom' 'border-left' | Yes | [ <border-width> || <border-style> || <border-color> ] | inherit | see individual properties |
| 'border-top-color' 'border-right-color' 'border-bottom-color' 'border-left-color' | Yes | <color> | transparent | inherit | the value of the 'color' property |
| 'border-top-style' 'border-right-style' 'border-bottom-style' 'border-left-style' | Yes | <border-style> | inherit | none |
| 'border-top-width' 'border-right-width' 'border-bottom-width' 'border-left-width' | Yes | <border-width> | inherit | medium |
| 'border-width' | Yes | <border-width>{1,4} | inherit | see individual properties |
| 'bottom' | Yes | <length> | <percentage> | auto | inherit | auto |
| 'caption-side' | Yes | top | bottom | left | right | inherit | top |
| 'clear' | Yes | none | left | right | both | inherit | none |
| 'clip' | Yes | <shape> | auto | inherit | auto |
| 'color' | Yes | <color> | inherit | depends on user agent |
| 'content' | No | [ <string> | <uri> | <counter> | attr(X) | open-quote | close-quote | no-open-quote | no-close-quote ]+ | inherit | empty string |
| 'counter-increment' | No | [ <identifier> <integer>? ]+ | none | inherit | none |
| 'counter-reset' | No | [ <identifier> <integer>? ]+ | none | inherit | none |
| 'cue' | No | [ 'cue-before' || 'cue-after' ] | inherit | see individual properties |
| 'cue-after' | No | <uri> | none | inherit | none |
| 'cue-before' | No | <uri> | none | inherit | none |
| 'cursor' | No | [ [<uri> ,]* [ auto | crosshair | default | pointer | move | e-resize | ne-resize | nw-resize | n-resize | se-resize | sw-resize | s-resize | w-resize| text | wait | help ] ] | inherit | auto |
| 'direction' | No | ltr | rtl | inherit | ltr |
| 'display' | inline | block | list-item | none | inherit | inline | block | list-item | run-in | compact | marker | table | inline-table | table-row-group | table-header-group | table-footer-group | table-row | table-column-group | table-column | table-cell | table-caption | none | inherit | inline |
| 'elevation' | No | <angle> | below | level | above | higher | lower | inherit | level |
| 'empty-cells' | No | show | hide | inherit | show |
| 'float' | Yes | left | right | none | inherit | none |
| 'font' | Yes | [ [ 'font-style' || 'font-variant' || 'font-weight' ]? 'font-size' [ / 'line-height' ]? 'font-family' ] | caption | icon | menu | message-box | small-caption | status-bar | inherit | see individual properties |
| 'font-family' | Yes | [[ <family-name> | <generic-family> ],]* [ <family-name> | <generic-family> ] | inherit | depends on user agent |
| 'font-size' | Yes | <absolute-size> | <relative-size> | <length> | <percentage> | inherit | medium |
| 'font-size-adjust' | No | <number> | none | inherit | none |
| 'font-stretch' | No | normal | wider | narrower | ultra-condensed | extra-condensed | condensed | semi-condensed | semi-expanded | expanded | extra-expanded | ultra-expanded | inherit | normal |
| 'font-style' | Yes | normal | italic | oblique | inherit | normal |
| 'font-variant' | Yes | normal | small-caps | inherit | normal |
| 'font-weight' | Yes | normal | bold | bolder | lighter | 100 | 200 | 300 | 400 | 500 | 600 | 700 | 800 | 900 | inherit | normal |
| 'height' | Yes | <length> | <percentage> | auto | inherit | auto |
| 'left' | Yes | <length> | <percentage> | auto | inherit | auto |
| 'letter-spacing' | No | normal | <length> | inherit | normal |
| 'line-height' | Yes | normal | <number> | <length> | <percentage> | inherit | normal |
| 'list-style' | Yes | [ 'list-style-type' || 'list-style-position' || 'list-style-image' ] | inherit | see individual properties |
| 'list-style-image' | Yes | <uri> | none | inherit | none |
| 'list-style-position' | Yes | inside | outside | inherit | outside |
| 'list-style-type' | disc | circle | square | decimal | lower-roman | upper-roman | lower-alpha | lower-latin | upper-alpha | upper-latin | none | inherit | disc | circle | square | decimal | decimal-leading-zero | lower-roman | upper-roman | lower-greek | lower-alpha | lower-latin | upper-alpha | upper-latin | hebrew | armenian | georgian | cjk-ideographic | hiragana | katakana | hiragana-iroha | katakana-iroha | none | inherit | disc |
| 'margin' | Yes | <margin-width>{1,4} | inherit | see individual properties |
| 'margin-top' 'margin-right' 'margin-bottom' 'margin-left' | Yes | <margin-width> | inherit | 0 |
| 'marker-offset' | No | <length> | auto | inherit | auto |
| 'marks' | No | [ crop || cross ] | none | inherit | none |
| 'max-height' | No | <length> | <percentage> | none | inherit | none |
| 'max-width' | No | <length> | <percentage> | none | inherit | none |
| 'min-height' | No | <length> | <percentage> | inherit | 0 |
| 'min-width' | No | <length> | <percentage> | inherit | depends on user agent |
| 'orphans' | No | <integer> | inherit | 2 |
| 'outline' | Yes | [ 'outline-color' || 'outline-style' || 'outline-width' ] | inherit | see individual properties |
| 'outline-color' | Yes | <color> | invert | inherit | invert |
| 'outline-style' | Yes | <border-style> | inherit | none |
| 'outline-width' | Yes | <border-width> | inherit | medium |
| 'overflow' | No | visible | hidden | scroll | auto | inherit | visible |
| 'padding' | Yes | <padding-width>{1,4} | inherit | see individual properties |
| 'padding-top' 'padding-right' 'padding-bottom' 'padding-left' | Yes | <padding-width> | inherit | 0 |
| 'page' | No | <identifier> | auto | auto |
| 'page-break-after' | No | auto | always | avoid | left | right | inherit | auto |
| 'page-break-before' | No | auto | always | avoid | left | right | inherit | auto |
| 'page-break-inside' | No | avoid | auto | inherit | auto |
| 'pause' | No | [ [<time> | <percentage>]{1,2} ] | inherit | depends on user agent |
| 'pause-after' | No | <time> | <percentage> | inherit | depends on user agent |
| 'pause-before' | No | <time> | <percentage> | inherit | depends on user agent |
| 'pitch' | No | <frequency> | x-low | low | medium | high | x-high | inherit | medium |
| 'pitch-range' | No | <number> | inherit | 50 |
| 'play-during' | No | <uri> mix? repeat? | auto | none | inherit | auto |
| 'position' | static | relative | absolute | inherit | static | relative | absolute | fixed | inherit | static |
| 'quotes' | No | [ <string><string>]+ | none | inherit | depends on user agent |
| 'richness' | No | <number> | inherit | 50 |
| 'right' | Yes | <length> | <percentage> | auto | inherit | auto |
| 'size' | No | <length>{1,2} | auto | portrait | landscape | inherit | auto |
| 'speak' | No | normal | none | spell-out | inherit | normal |
| 'speak-header' | No | once | always | inherit | once |
| 'speak-numeral' | No | digits | continuous | inherit | continuous |
| 'speak-punctuation' | No | code | none | inherit | none |
| 'speech-rate' | No | <number> | x-slow | slow | medium | fast | x-fast | faster | slower | inherit | medium |
| 'stress' | No | <number> | inherit | 50 |
| 'table-layout' | No | auto | fixed | inherit | auto |
| 'text-align' | left | right | center | justify | inherit | left | right | center | justify | <string> | inherit | depends on user agent and writing direction |
| 'text-decoration' | none | [ underline || overline || line-through ] | inherit | none | [ underline || overline || line-through || blink ] | inherit | none |
| 'text-indent' | Yes | <length> | <percentage> | inherit | 0 |
| 'text-shadow' | No | none | [<color> || <length> <length> <length>? ,]* [ <color> || <length> <length> <length>?] | inherit | none |
| 'text-transform' | Yes | capitalize | uppercase | lowercase | none | inherit | none |
| 'top' | Yes | <length> | <percentage> | auto | inherit | auto |
| 'unicode-bidi' | No | normal | embed | bidi-override | inherit | normal |
| 'vertical-align' | baseline | sub | super | top | middle | bottom | inherit | baseline | sub | super | top | text-top | middle | bottom | text-bottom | <percentage> | <length> | inherit | baseline |
| 'visibility' | Yes | visible | hidden | collapse | inherit | inherit |
| 'voice-family' | No | [[ <specific-voice> | <generic-voice> ],]* [ <specific-voice> | <generic-voice> ] | inherit | depends on user agent |
| 'volume' | No | <number> | <percentage> | silent | x-soft | soft | medium | loud | x-loud | inherit | medium |
| 'white-space' | Yes | normal | pre | nowrap | inherit | normal |
| 'widows' | No | <integer> | inherit | 2 |
| 'width' | Yes.
Note that a TV UA may implement a UA style sheet rule of *{max-width: 100%} to avoid horizontal scrolling. |
<length> | <percentage> | auto | inherit | auto |
| 'word-spacing' | No | normal | <length> | inherit | normal |
| 'z-index' | Yes | auto | <integer> | inherit | auto |
The following table summarizes CSS TV Profile properties and property values from the CSS3 Module: Color. Refer to [CSS3COLOR] for the definition of these properties and values.
| Name | CSS TV | CSS Values | Initial value |
|---|---|---|---|
| 'color' | HTML4 keywords, RGB and RGBA values, transparent, orange, inherit | HTML4 keywords, RGB, RGBA, HSL, and HSLA values, transparent, X11 keywords, System Colors, flavor, attr(X,color), inherit | depends on user agent |
| 'color-profile' | No | auto | sRGB | <name> | <uri> | inherit | auto |
| 'opacity' | Yes | <alphavalue> | inherit | 1 |
| 'rendering-intent' | no | auto | perceptual | relative-colorimetric | saturation | absolute-colorimetric | inherit | auto |
The CSS TV Profile uses the same syntax as specified in [CSS2]. The CSS TV Profile uses a subset of the values used in CSS2. Specifically:
Similarly, the CSS TV Profile requires that conforming user agents support the character encoding mechanisms specified in [CSS2]. Specifically:
In general, the CSS TV Profile uses the same cascading rules as in CSS2. Specifically:
A CSS TV Profile conforming user agent MUST be able to process media-dependent style sheets as specified in CSS2 ([CSS2] Section 7). Specifically:
tv
media type.all
media type.screen
or print
).The TV-UA is not required to satisfy the CSS2 conformance statement pertaining to the tv
media type (see [CSS2] Section 7.3.1); the TV-UA need only satisfy the conformance statements in this specification.
This document derives from the CSS Level 1 and CSS level 2 Recommendations, the CSS3 Module: Color and the CSS Mobile Profile 1.0. We thank all CSS1, CSS2, CSS3 Module: Color and CSS Mobile Profile authors, editors and contributors.
We would like to thank the participants in the CSS Working Group, especially Bert Bos, Chris Lilley, and Tapas Kanti Roy for their direct feedback on the draft.
We would like to thank the contributors on<EMAIL_ADDRESS>We would like to especially thank ARIB, Akihiko Handa, Joel Zdepski, Etan Wexler, Kynn Bartlett, Björn Höhrmann, fantasai and Susan Lesch for their valuable comments on the drafts of this document.


CrimPapers
Articles published on 26 August 2020
On 26 August 2020, 9 new articles were published in 8 journals.
Plea-Bargaining Law: the Impact of Innocence, Trial Penalty, and Conviction Probability on Plea Outcomes
Researching Race, Racialisation, and Racism in Critical Terrorism Studies: Clarifying Conceptual Ambiguities by Sanne Groothuis
Women Who Volunteer: A Relative Autonomy Perspective in Al-Shabaab Female Recruitment in Kenya by Fathima Azmiya Badurdeen
The Impact of Race, Sex, and Structured Activities on the Intake and Adjudication Processes of Status Offenders by Patrick G. Lowery
Correction
Theoretical and Empirical Advances in the Study and Control of White-Collar Offenders by Michael L. Benson
Talking Stagnation: Thematic Analysis of Terrorism Experts’ Perception of the Health of Terrorism Research by John F. Morrison
The Global Impact of the Pandemic on Institutional and Community Corrections: Assessing Short-Term Crisis Management and Long-Term Change Strategies by Kathryn M. Nowonty, Alex R. Piquero
Intimate Partner Violence and Brain Injury Screening by Shireen S. Rajaram, Peggy Reisher, Matthew Garlinghouse, Kathy S. Chiou, Kate D. Higgins, Moses New-Aaron, Tanushree Ojha, Lynette M. Smith


|
UMI3D Unity SDK
2.4.r.220208
A UMI3D sdk implementation using Unity
|
Abstract UMI3D interaction collection. More...
Public Member Functions | |
| ulong | Id () |
| The public Getter for interactionId. More... | |
| virtual LoadEntity | Register () |
| Check if the Toolbox has been registered to the UMI3DScene and do it if not More... | |
| virtual LoadEntity | GetLoadEntity (HashSet< UMI3DUser > users=null) |
| Return load operation More... | |
| DeleteEntity | GetDeleteEntity (HashSet< UMI3DUser > users=null) |
| Return delete operation More... | |
| ToolboxDto | ToDto (UMI3DUser user) |
| Convert interaction to Data Transfer Object for a given user. More... | |
| Bytable | ToBytes (UMI3DUser user) |
| IEntity | ToEntityDto (UMI3DUser user) |
| bool | LoadOnConnection (UMI3DUser user) |
| bool | AddConnectionFilter (UMI3DUserFilter filter) |
| bool | RemoveConnectionFilter (UMI3DUserFilter filter) |
Public Attributes | |
| InteractionDisplay | display |
Protected Member Functions | |
| virtual void | InitDefinition (ulong id) |
| Initialize interaction's properties. More... | |
| virtual void | OnDestroy () |
| Unity MonoBehaviour OnDestroy method. More... | |
Protected Attributes | |
| UMI3DScene | Scene |
| List< UMI3DTool > | tools = new List<UMI3DTool>() |
| bool | Active |
| bool | inited = false |
| Indicates if InitDefinition has been called. More... | |
| Dictionary< UMI3DUser, bool > | availableLastFrame = new Dictionary<UMI3DUser, bool>() |
| Indicates the availability state of a user for the last frame check of visibility. More... | |
Properties | |
| UMI3DAsyncProperty< UMI3DScene > | objectScene [getprotected set] |
| UMI3DAsyncListProperty< UMI3DTool > | objectTools [getprotected set] |
| UMI3DAsyncProperty< bool > | objectActive [getprotected set] |
Abstract UMI3D interaction collection.
| bool umi3d.edk.interaction.UMI3DToolbox.AddConnectionFilter | ( | UMI3DUserFilter | filter | ) |
Implements umi3d.edk.UMI3DMediaEntity.
| DeleteEntity umi3d.edk.interaction.UMI3DToolbox.GetDeleteEntity | ( | HashSet< UMI3DUser > | users = null | ) |
|
virtual |
| ulong umi3d.edk.interaction.UMI3DToolbox.Id | ( | ) |
The public Getter for interactionId.
Implements umi3d.edk.UMI3DEntity.
|
protectedvirtual |
Initialize interaction's properties.
| bool umi3d.edk.interaction.UMI3DToolbox.LoadOnConnection | ( | UMI3DUser | user | ) |
Implements umi3d.edk.UMI3DMediaEntity.
|
protectedvirtual |
Unity MonoBehaviour OnDestroy method.
|
virtual |
Check if the Toolbox has been registered to the UMI3DScene and do it if not
| bool umi3d.edk.interaction.UMI3DToolbox.RemoveConnectionFilter | ( | UMI3DUserFilter | filter | ) |
Implements umi3d.edk.UMI3DMediaEntity.
| baseSize | |
| user |
Implements umi3d.edk.UMI3DLoadableEntity.
| ToolboxDto umi3d.edk.interaction.UMI3DToolbox.ToDto | ( | UMI3DUser | user | ) |
Convert interaction to Data Transfer Object for a given user.
| user | the user |
Implements umi3d.edk.UMI3DLoadableEntity.
|
protected |
|
protected |
Indicates the availability state of a user for the last frame check of visibility.
| InteractionDisplay umi3d.edk.interaction.UMI3DToolbox.display |
|
protected |
Indicates if InitDefinition has been called.
|
protected |
|
getprotected set |
|
getprotected set |
|
getprotected set |


Santa's TODO list:
Tips:
Click to select, Ctrl-click to toggle selection, Shift-click to select a range.
Drag one or more rows by the handle to reorder.
View Source:
View the source for this example on Github


First we will need to download the Valmod Overhaul to add it to our game. Use the below link for the lastest download.
VALMOD OVERHAUL DOWNLOAD.
Next we will open the directory that holds the game files. To do this right-click on 7 Days To Die in your Steam Library, and click on Properties.
Under the "Local Files" tab click on Browse Files. This will open a new window containing your 7DTD files.
Now in the navigation bar in the folder you should be seeing a path that says \Steam\steamapps\common\7 Days To Die Click on common to go back one level.
You should now see the whole 7DTD folder. Right-click and copy and paste the folder next to itself so that you have 7 Days To Die & 7 Days To Die - Copy, then go head and open the copy.
Going back to your download folder where you earlier downloaded the Valmod pack, open the zip file and extract the files somewhere, if necessary.
Once you have the zip file open simply drag and drop the Data and Mods folder from Valmod into your 7DTD-Copy Folder.
You should be asked to REPLACE some files, make sure to click YES to this.
We are almost done!
In your 7DTD - Copy folder there should be a file called 7DaysToDie_EAC . Double click this files and click on install when the window pops up (If prompeted to. EAC may already be installed on your system).
This may try to start running the game, if it does close the game out when you get a chance. Next we right click the 7DaysToDie_EAC application file.
Create a shortcut, rename it 7DTD-MODDED, or something to where you will know the difference between your normal shortcut to the game, and then place the shortcut where ever you want, like the desktop.
That's it you are done. Make sure to Run the application the new Modded shortcut, so that you get all the nice new pictures and localization files.
If you have any problems with the install, feel free to contact me, and ill be glad to help you.
Good luck and have fun!
{% endblock %}


call p%init(icontx,ptype,info)
This method allocates and initializes the preconditioner p, according to the preconditioner type chosen by the user.
Arguments
icontxt | integer, intent(in). |
| The communication context. |
ptype | character(len=*), intent(in). |
| The type of preconditioner. Its values are specified in Table 1. |
| Note that the strings are case insensitive. |
info | integer, intent(out). |
| Error code. If no error, 0 is returned. See Section 8 for details. |
For compatibility with the previous versions of MLD2P4, this method can be also invoked as follows:
call mld_precinit(p,ptype,info)