Miracle-dz/UniFAR-FTUs huggingface dataset:
CheckFence: checking consistency of concurrent data types on relaxed memory models

Concurrency libraries can facilitate the development of multi-threaded programs by providing concurrent implementations of familiar data types such as queues or sets. There exist many optimized algorithms that can achieve superior performance on multiprocessors by allowing concurrent data accesses without using locks. Unfortunately, such algorithms can harbor subtle concurrency bugs. Moreover, they requirememory ordering fences to function correctly on relaxed memory models. To address these difficulties, we propose a verification approach that can exhaustively check all concurrent executions of a given test program on a relaxed memory model and can verify that they are observationally equivalent to a sequential execution. Our CheckFence prototype automatically translates the C implementation code and the test program into a SAT formula, hands the latter to a standard SAT solver, and constructs counter example traces if there exist incorrect executions. Applying CheckFence to five previously published algorithms, we were able to (1) find several bugs (some not previously known), and (2) determine how to place memory ordering fences for relaxed memory models.
Co-location social networks: Linking the physical world and cyberspace

Various dedicated web services in the cyberspace, e.g., social networks, e-commerce, and instant communications, play a significant role in people's daily-life. Billions of people around the world access them through multiple online identifiers (IDs), and interact with each other in both the cyberspace and the physical world. These two kinds of interactions are highly relevant to each other. In order to link between the cyberspace and the physical world, we propose a new type of social network, i.e., co-location social network (CLSN). A CLSN contains online IDs describing people's online presence and offline interactions when people come across each other. By analyzing real data collected from a mainstream ISP in China, which contains 32.7 million IDs across most popular web services, we build a large-scale CLSN, and evaluate its unique properties. The results verify that the CLSN is quite different from existing online and offline social networks in terms of different classic graph metrics. This paper is the first research to study CLSN at scale and paves the way for future studies of this new type of social network.
Applying Conditional Random Fields to Japanese Morphologiaical Analysis

本稿では, Conditonal Random Fields (CRF) に基づく日本語形態素解析を提案する. CRF を適用したこ れまでの研究の多くは, 単語の境界位置が既知の状況を想定していた. しかし, 日本語には明示的な単語境 界が無く, 単語境界同定と品詞同定を同時に行うタスクである日本語形態素解析に CRF を直接適用するこ とは困難である. 本稿ではまず, 単語境界が存在する問題に対する CRF の適用方法について述べる. さら に, CRF が既存手法 (HMM, MEMM) の問題点を自然にかつ有効に解決することを実データを用いた実験 と共に示す. CRF は, 階層構造を持つ品詞体系や文字種の情報に対して柔軟な素性設計を可能にし, label bias や length bias を低減する効果を持つ. 前者は HMM の欠点であり, 後者は MEMM の欠点である. ま た, 2つの正則化手法 (L1-CRF/L2-CRF) を適用し, それぞれの性質について論じる.
nodes ! private ! ghost ! shared ! edges !

A key problem in parallel programming is how data is partitioned: divided into subsets that can be operated on in parallel and, in distributed memory machines, spread across multiple address spaces. We present a dependent partitioning framework that allows an application to concisely describe relationships between partitions. Applications first establish independent partitions, which may contain arbitrary subsets of application data, permitting the expression of arbitrary applicationspecific data distributions. Dependent partitions are then derived from these using the dependent partitioning operations provided by the framework. By directly capturing inter-partition relationships, our framework can soundly and precisely reason about programs to perform important program analyses crucial to ensuring correctness and achieving good performance. As an example of the reasoning made possible, we present a static analysis that discharges most consistency checks on partitioned data during compilation. We describe an implementation of our framework within Regent, a language designed for the Legion programming model. The use of dependent partitioning constructs results in a 86-96% decrease in the lines of code required to describe the partitioning, eliminates many of the expensive dynamic checks required for soundness by the current Regent partitioning implementation, and speeds up the computation of partitions by 2.6-12.7X even on a single thread. Additionally, we show that a distributed implementation incorporated into the the Legion runtime system allows partitioning of data sets that are too large to fit on a single node and yields a further 29X speedup of partitioning operations on 64 nodes. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. OOPSLA ’16, October 30-November 04 2016, Amsterdam, Netherlands Copyright c © 2016 held by owner/author(s). Publication rights licensed to ACM. ACM 978-1-4503-4444-9/16/10. $15.00 DOI: http://dx.doi. org/10.1145/2983990.2984016
iVR: Integrated Vision and Radio Localization with Zero Human Effort

Smartphone localization is essential to a wide range of applications in shopping malls, museums, office buildings, and other public places. Existing solutions relying on radio fingerprints and/or inertial sensors suffer from large location errors and considerable deployment efforts. We observe an opportunity in the recent trend of increasing numbers of security surveillance cameras installed in indoor spaces to overcome these limitations and revisit the problem of smartphone localization with a fresh perspective. However, fusing vision-based and radio-based systems is non-trivial due to the absence of absolute location, incorrespondence of identification and looseness of sensor fusion. This study proposes iVR, an integrated vision and radio localization system that achieves sub-meter accuracy with indoor semantic maps automatically generated from only two surveillance cameras, superior to precedent systems that require manual map construction or plentiful captured images. iVR employs a particle filter to fuse raw estimates from multiple systems, including vision, radio, and inertial sensor systems. By doing so, iVR outputs enhanced accuracy with zero start-up costs, while overcoming the respective drawbacks of each individual sub-system. We implement iVR on commodity smartphones and validate its performance in five different scenarios. The results show that iVR achieves a remarkable localization accuracy of 0.7m, outperforming the state-of-the-art systems by > 70%. CCS Concepts: •
Univariate Shrinkage in the Cox Model for High Dimensional Data

We propose a method for prediction in Cox's proportional model, when the number of features (regressors), p, exceeds the number of observations, n. The method assumes that the features are independent in each risk set, so that the partial likelihood factors into a product. As such, it is analogous to univariate thresholding in linear regression and nearest shrunken centroids in classification. We call the procedure Cox univariate shrinkage and demonstrate its usefulness on real and simulated data. The method has the attractive property of being essentially univariate in its operation: the features are entered into the model based on the size of their Cox score statistics. We illustrate the new method on real and simulated data, and compare it to other proposed methods for survival prediction with a large number of predictors.
Models for Discrete Data

Interestingly, the book focuses on modern, practical applications and exercises rather than theory. Hence it is more suitable to professional engineers and mature students. I think this new edition will continue to be useful and helpful for the intended population. However, generally speaking, it is a recipe book and does not lead toward much critical thinking nor is it thought provoking. Having said that, the book is multipurpose, reader friendly and can be used as a quick reference on a variety of topics.
Computer Standards

Adoption of agile values and principles and transformation of organizations towards agility are not easy and straightforward. Misinterpretation of agile principles and values, and adoption of partial solutions with few agile practices instead of holistic approaches prevent organizations to obtain full bene ﬁ ts of agile methods. We developed the Software Agility Assessment Reference Model (AgilityMod) for the appraisal of software projects from agility perspective and to provide guidance on specifying gaps on the road towards agility (agile maturity). The meta-model of AgilityMod was de ﬁ ned in relation with the ISO/IEC 15504-Process Assessment Model. AgilityMod was developed in an iterative and incremental manner by running successive case studies and getting opinions of experts for the evaluation and improvement of the Model. The multiple case study that we present here in detail included the implementation of the Model in eight software development companies. The results of this case study were evaluated by the case study participants. According to the signi ﬁ cant majority of the case study participants, AgilityMod achieves its purpose.
BIOINFORMATICS ORIGINAL PAPER

Motivation: Deciphering the response of a complex biological system to an insulting event, at the gene expression level, requires adopting theoretical models that are more sophisticated than a one-to-one comparison (i.e. t -test). Here, we investigate the ability of a novel reverse engineering approach (System Response Inference) to unveil non-obvious transcriptional signatures of the system response induced by prion infection. Results: To this end, we analyze previously published gene expression data, from which we extrapolate a putative full-scale model of transcriptional gene–gene dependencies in the mouse central nervous system. Then, we use this nominal model to interpret the gene expression changes caused by prion replication, aiming at selecting the genes primarily inﬂuenced by this perturbation. Our method sheds light on the mode of action of prions by identifying key transcripts that are the most likely to be responsible for the overall transcriptional rearrangement from a nominal regulatory network. As a ﬁrst result of our inference, we have been able to predict known targets of prions (i.e. PrP C ) and to unveil the potential role of previously unsuspected genes.
A Survey of Middleware for Sensor Networks : State-ofthe-Art and Future Directions

In future computing environments, networked sensors will play an increasingly important role in mediating between the physical and virtual worlds. However, programming sensor networks, and the applications that depend on the data they produce, is extremely challenging. The need for suitable middleware to address this problem is evident. In the last few years, various middleware solutions for sensor networks have emerged. These differ in terms of their models for querying and data aggregation, and their assumptions about the topology and other characteristics of the network. Naturally, the assumptions made for each particular middleware limit its potential applicability. Most of the current solutions provide relatively simple query abstractions, and therefore are not suitable for applications that have sophisticated requirements for processing of sensor data in the network. This paper presents a survey and analysis of the current state-of-the art in the field, highlighting the open research challenges. It also draws on the authors’ experience with developing middleware for context-aware systems that is, systems that rely on sensor-derived data to intelligently adapt their behaviour to propose some future directions for the development of middleware for sensor networks.
Closing the Dependability Gap: Converging Software Engineering with Middleware

The inertness of today’s software systems turns innovative applications into an obstacle rather than an enabler and results in dependability degradation during the systems’ lifetime. Even more so, heterogeneity, scale, and dynamics open up what Laprie called the dependability gap. In this position paper, we identify the need to converge methods from software engineering with traditional middleware and dependable systems research to close the de-pendability gap. In particular, we suggest a nested control loop approach, where the inner loop addresses short-term changes autonomously, while the outer loop addresses long-term evolution by run-time software engineering.
Algorithms and Data Structures: The Basic Toolbox

Algorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic techniques for modeling, understanding and solving algorithmic problems. This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, and optimization. The algorithms are presented in a modern way, with explicitly formulated invariants, and comment on recent trends such as algorithm engineering, memory hierarchies, algorithm libraries and certifying algorithms. The authors use pictures, words and high-level pseudocode to explain the algorithms, and then they present more detail on efficient implementations using real programming languages like C++ and Java. The authors have extensive experience teaching these subjects to undergraduates and graduates, and they offer a clear presentation, with examples, pictures, informal explanations, exercises, and some linkage to the real world. Most chapters have the same basic structure: a motivation for the problem, comments on the most important applications, and then simple solutions presented as informally as possible and as formally as necessary. For the more advanced issues, this approach leads to a more mathematical treatment, including some theorems and proofs. Finally, each chapter concludes with a section on further findings, providing views on the state of research, generalizations and advanced solutions.
Balance Refinement of Massive Linear Octrees

This paper presents a solution to the problem of balance refinement of massive linear octrees. We combine existing database techniques (B-tree, bulk loading, and range queries) with new algorithms (balance by parts, prioritized ripple propagation) and data structures (the cache octree) into a unified framework that provides new capabilities for large scientific applications.
Design and Applications of Context Aware Data Framework

Context aware data analysis refers to analyzing data with respect to context. Here, context mean location, time or surrounding environment of a person or an object or any other entity. Usually such information can be obtained from some dedicated device or smartphones. However, some of the latest developments in this domain are done using smartphones. Because, context awareness is more relevant to dynamic environment, which is possible when user is mobile and that’s the reason why context aware applications are implemented on smartphones which are much powerful now. Other factors can be their availability and their capabilities of acquiring and processing contextual information. And since they can be conncected to internet, they can be used as a unit for any larger system However, the data which is acquired by the devices is later processed on some server or framework. Usually data is managed at the backend of such servers or frameworks. And later used for decision making or to give some service. But in the end, outcome is generated on the base of context which enhances user experience with the system. The concept of context awareness and context aware data framework will help in developing application which will require least user interaction. But still will in control of user
The WHUTE System in NTCIR-9 RITE Task

paper describes our system of recognizing textual entailment for RITEVAL System Validation and Fact Validation subtasks at NTCIR-11. For System Validation subtask, we employ a transformation model and acquire entailment rules by extracting synonyms and inferable expressions from resources such as lexicons and knowledge bases. Also, a cascaded entailment recognition model is employed to recognize four types of entailment relations. For Fact Validation subtask, we build a pipeline approach to find texts that entails given texts. First, a retrieval model is used to search related sentences from Wikipedia documents provided, then we used the recognition model in System Validation subtask to find such sentences that entailed the given texts. Official results show that our system achieves a performance of 53.48% MacroF1 score in Chinese SVBC subtask, a 25.74% MacroF1 score in Chinese SVMC subtask, a 45.51% MacroF1 score in English FV subtask and a 38.08% MacroF1 score in Chinese FV subtask.
Combining in silico evolution and nonlinear dimensionality reduction to redesign responses of signaling networks

To fully understand themechanisms giving rise to behavior, we need to be able to preciselymeasure it. When coupledwith large behavioral data sets, unsupervised clusteringmethods offer the potential of unbiasedmapping of behavioral spaces. However, unsupervised techniques tomap behavioral spaces are in their infancy, and there have been few systematic considerations of all themethodological options.We compared the performance of seven distinctmappingmethods in clustering awavelettransformed data set consisting of the xand y-positions of the six legs of individual flies. Legs were automatically tracked by small pieces offluorescent dye, while theflywas tethered andwalking on an air-suspended ball.We find that there is considerable variation in the performance of thesemapping methods, and that better performance is attainedwhen clustering is done in higher dimensional spaces (which are otherwise less preferable because they are hard to visualize). High dimensionalitymeans that some algorithms, including the non-parametric watershed cluster assignment algorithm, cannot be used.We developed an alternative watershed algorithmwhich can be used in high-dimensional spaces when a probability density estimate can be computed directly.With these tools in hand, we examined the behavioral space offly leg postural dynamics and locomotion.We find a striking division of behavior intomodes involving the fore legs andmodes involving the hind legs, with few direct transitions between them. By computing behavioral clusters using the data from allflies simultaneously, we show that this division appears to be common to allflies.We also identify individual-to-individual differences in behavior and behavioral transitions. Lastly, we suggest a computational pipeline that can achieve satisfactory levels of performance without the taxing computational demands of a systematic combinatorial approach.
Benchmarking Software-Development Productivity - Applied Research Results

The article examines a statistical analysis of a productivity variation, involving a unique database containing 206 business software projects from 26 Finnish companies. The authors examine differences in the factors, explaining productivity in the banking, insurance, manufacturing, wholesale/retail, and public administration sectors. The authors provide productivity benchmarking equations that are useful both for estimating expected productivity at the start of a new project and for benchmarking a completed project for each business sector.
Fundamentals of Digital Signal Processing Using MATLAB

1. Signal Processing Motivation / Signals and Systems / Signal Sampling / Signal Reconstruction / Prefilters and Postfilters / Conversion Circuits / The FDSP Toolbox / Software Applications / Chapter Summary / Problems 2. Discrete-Time System Analysis Motivation / Z-Transform Pairs / Z-Transform Properties / Inverse Z-Transform / Transfer Functions / Signal Flow Graphs / The Impulse Response and Convolution / Stability / Frequency Response / Software Applications / Chapter Summary / Problems 3. The DFT and Spectral Analysis Motivation / The Discrete-Time Fourier Transform (DTFT). The Discrete Fourier Transform (DFT). DFT Properties. The Fast Fourier Transform (FFT). White Noise. Discrete-Time Frequency Response. Zero Padding. Power Density Spectrum Estimation. The Spectrogram. Software Applications. Chapter Summary. Problems. 4. Convolution and Correlation Motivation / Convolution / Fast Convolution / Cross-Correlation / Fast Correlation / Auto-Correlation / Extracting Periodic Signals from Noise / Software Applications / Chapter Summary / Problems 5. Filter Specifications and Structures Motivation. Filter Design Specifications. Linear-Phase Filters. Minimum-Phase and Allpass Filters. FIR Filter Realization Structures. IIR Filter Realization Structures. FIR Finite Word Length Effects. IIR Finite Word Length Effects. Software Applications. Chapter Summary. Problems. 6. FIR Filter Design Motivation / Windowing Method / Frequency Sampling Method / Least Squares Method / Optimal Equiripple Method / Differentiators and Hilbert Transformers / Software Applications / Chapter Summary / Problems 7. Multirate Signal Processing Motivation / Integer Decimators and Interpolators / Rational Sampling Rate Converters / Multirate Filter Realization Structures / Subband Processing / Oversampling ADC / Oversampling DAC / Software Applications / Chapter Summary / Problems 8. IIR Filter Design Motivation / Filter Design by Pole-Zero Placement / Filter Design Parameters / Classical Analog Filters / Bilinear Transformation Method / Frequency Transformations / Software Applications / Chapter Summary / Problems 9. Adaptive Signal Processing Motivation / Mean Square Error / The Least Mean Square (LMS) Method / Performance Analysis of the LMS Method / Modified LMS Methods / Adaptive FIR Filter Design / The Recursive Least Squares (RLS) Method / Active Noise Control / Nonlinear System Identification / Software Applications / Chapter Summary / Problems APPENDICES: 1. MATLAB Workspace / Variables and Initialization / Mathematical Operators / Input and Output / Branching and Loops / Built-In Functions / User-Defined Functions / GUIs 2. FDSP Toolbox Installation / Driver Module f_dsp / Chapter GUI Modules / FDSP Toolbox Functions 3. Transform Tables Fourier Series / Fourier Transform / Laplace Transform / Z-Transform / Discrete-Time Fourier Transform (DTFT), Discrete Fourier Transform (DFT) 4. Mathematical Identifies Complex Numbers / Euler"s Identity / Trigonometric Identities / Inequalities