Miracle-dz/UniFAR-FTUs huggingface dataset:
Interprocedural strength reduction of critical sections in explicitly-parallel programs

In this paper, we introduce novel compiler optimization techniques to reduce the number of operations performed in critical sections that occur in explicitly-parallel programs. Specifically, we focus on three code transformations: 1) Partial Strength Reduction (PSR) of critical sections to replace critical sections by non-critical sections on certain control flow paths; 2) Critical Load Elimination (CLE) to replace memory accesses within a critical section by accesses to scalar temporaries that contain values loaded outside the critical section; and 3) Non-critical Code Motion (NCM) to hoist thread-local computations out of critical sections. The effectiveness of the first two transformations is further increased by interprocedural analysis. The effectiveness of our techniques has been demonstrated for critical section constructs from three different explicitly-parallel programming models - the isolated construct in Habanero Java (HJ), the synchronized construct in standard Java, and transactions in the Java-based Deuce software transactional memory system. We used two SMP platforms (a 16-core Intel Xeon SMP and a 32-Core IBM Power7 SMP) to evaluate our optimizations on 17 explicitly-parallel benchmark programs that span all three models. Our results show that the optimizations introduced in this paper can deliver measurable performance improvements that increase in magnitude when the program is run with a larger number of processor cores. These results underscore the importance of optimizing critical sections, and the fact that the benefits from such optimizations will continue to increase with increasing numbers of cores in future many-core processors.
Control speculation in multithreaded processors through dynamic loop detection

This paper presents a mechanism to dynamically detect the loops that are executed in a program. This technique detects the beginning and the termination of the iterations and executions of the loops without compiler/user intervention. We propose to apply this dynamic loop detection to the speculation of multiple threads of control dynamically obtained from a sequential program. Based an the highly predictable behavior of the loops, the history of the past executed loops is used to speculate the future instruction sequence. The overall objective is to dynamically obtain coarse grain parallelism (at the thread level) that can be exploited by a multithreaded architecture. We show that for a 4-context multithreaded processor the speculation mechanism provides around 2.6 concurrent threads in average.
Bipolar Person Name Identification of Topic Documents Using Principal Component Analysis

In this paper, we propose an unsupervised approach for identifying bipolar person names in a set of topic documents. We employ principal component analysis (PCA) to discover bipolar word usage patterns of person names in the documents and show that the signs of the entries in the principal eigenvector of PCA partition the person names into bipolar groups spontaneously. Empirical evaluations demonstrate the efficacy of the proposed approach in identifying bipolar person names of topics.
Channel-tolerant FH-MFSK acoustic signaling for undersea communications and networks

Undersea acoustic channels can exhibit multipath propagation with impulse-response duration and coherence time both of the order of tens to hundreds of milliseconds. Signal reception is further impaired by the presence of time-varying nonwhite ambient-noise spectra having a dynamic range of 30 dB or more. Acoustic communication requires appropriate waveform design and associated signal processing to accommodate these adverse transmission characteristics while also providing desired performance features such as low-probability-of-detection (LPD) and multi-access networking. Adaptive-equalization techniques provide good performance only for channels with stable multi-paths and high signal-to-noise ratios (SNR's) accommodating the signaling rates needed to sample and compensate for rapid changes. An alternative approach is to design for robustness against channel fluctuations. This paper describes a channel-tolerant approach identified as "telesonar type-B signaling. " The technique has been designed to accommodate network architectures requiring multiple access to the channel while simultaneously providing covertness and energy efficiency. Specialized frequency-hopped M-ary frequency-shift-key (FH-MFSK) waveforms are combined with related signal processing, including nonlinear adaptive techniques to mitigate the effects of all types of interference. This effectively results in a channel that has uniformly distributed noise in both time and frequency. Powerful error-correction coding permits low SNR transmissions. Nonbinary, long-constraint-length, convolutional coding and related sequential decoding is a classical solution for difficult low-rate channels. The probability of bit errors below 10/sup -10/ is obtainable, even in Rayleigh-faded channels near the computational cutoff rate, and the probability of failure to decode frames of data is extremely small. Both simulations and analyses of at-sea experiments demonstrate the performance of this noncoherent approach to reliable acoustic communications.
FRIENDSHIP AND AUTISM: A MULTIPLE CASE STUDY ECOLOGICAL EXPLORATION OF STUDENT, TEACHER, AND PEER FACTORS RELATING TO THE SOCIAL NETWORK AND FEELINGS OF LONELINESS OF STUDENTS WITH AUTISM SPECTRUM DISORDER IN GENERAL EDUCATION ELEMENTARY CLASSROOMS

OF DISSERTATION FRIENDSHIP AND AUTISM: A MULTIPLE CASE STUDY ECOLOGICAL EXPLORATION OF STUDENT, TEACHER, AND PEER FACTORS RELATING TO THE SOCIAL NETWORK AND FEELINGS OF LONELINESS OF STUDENTS WITH AUTISM SPECTRUM DISORDER IN GENERAL EDUCATION ELEMENTARY CLASSROOMS The number of children diagnosed with an autism spectrum disorder (ASD) who are being served in the public school system has increased dramatically in recent years. During an increased focus on inclusion within education, research shows that students with ASD educated in the general education classroom generally do not have as many friends as their peers without ASD. However, some students with ASD are found to have more friends than other students with ASD. Therefore, additional research must explore potential factors that may be influencing the success with which students with ASD form friendships within the general education classroom. Using a multiple case study ecological approach, this study examines child, peer, and general education teacher factors related to the friendship patterns of three male students with ASD in fourth or fifth grade general education classrooms. Results from this study indicate that consistent with previous research, some students with ASD are found to be more socially embedded within the social network of the general education classroom and report greater levels of social satisfaction than other students with ASD. Findings suggest that for the three participants within this study, having two solid friendships, regardless of the social status of the friends of the student with ASD, may be related to a higher level of social network status and lower levels of self-reported loneliness for students with ASD. Factors that were found to be important for the three target students in this study included quality of social skills, quality of friendship, understanding of the construct of friendship, and general education teacher experience level. Factors that were found to be less important for the three target students in this study included peer attitudes towards children with disabilities, teacher attitudes towards inclusion of students with autism, teacher knowledge of autism, and teacher knowledge and use of evidence-based practices. Possible explanations for these findings, as well as limitations, directions for future research, and implications are discussed.
Cohesion-Driven Decomposition of Service Interfaces without Access to Source Code

Software cohesion concerns the degree to which the elements of a module belong together. Cohesive software is easier to understand, test and maintain. In the context of service-oriented development, cohesion refers to the degree to which the operations of a service interface belong together. In the state of the art, software cohesion is improved based on refactoring methods that rely on information, extracted from the software implementation. This is a main limitation towards using these methods in the case of web services: web services do not expose their implementation; instead all that they export is the web service interface specification. To deal with this problem, we propose an approach that enables the cohesion-driven decomposition of service interfaces, without information on how the services are implemented. Our approach progressively decomposes a given service interface into more cohesive interfaces; the backbone of the approach is a suite of cohesion metrics that rely on information, extracted solely from the specification of the service interface. We validate the approach in 22 real-world services, provided by Amazon and Yahoo. We assess the effectiveness of the proposed approach, concerning the cohesion improvement, and the number of interfaces that result from the decomposition of the examined interfaces. Moreover, we show the usefulness of the approach in a user study, where developers assessed the quality of the produced interfaces.
Comparison of New Techniques of Representation for 3D Shape Data Base Retrieval

The recent development of retrieval techniques and advances in 3D shape representation has induced a large amount of research. This paper presents a methodology with three options to retrieve shapes in 3D data bases, based on mapping shapes in 1D using representative sequences, which are matched using Fast Dynamic Time Warping distance. The three options are compared through a performance measure showing being better than the ones in literature.
AUTOMATIC ROAD EXTRACTION BASED ON MULTI-SCALE, GROUPING, AND CONTEXT

An approach for the automatic extraction of roads from digital aerial imagery is proposed. It makes use of several versions of the same aerial image with different resolutions. Roads are modeled as a network of intersections and links between these intersections, and are found by a grouping process. The context of roads is hierarchically structured into a global and a local level. The automatic segmentation of the aerial image into different global contexts, i.e., rural, forest, and urban area, is used to focus the extraction to the most promising regions. For the actual extraction of the roads, edges are extracted in the original high resolution image (0.2 to 0.5 m) and lines are extracted in an image of reduced resolution. Using both resolution levels and explicit knowledge about roads, hypotheses for road segments are generated. They are grouped iteratively into larger segments. In addition to the grouping algorithms, knowledge about the local context, e.g., shadows cast by a tree onto a road segment, is used to bridge gaps. To construct the road network, finally intersections are extracted. Examples and results of an evaluation based on manually plotted reference data are given, indicating the potential of the approach.
Contexts of Accommodation: Developments in Applied Sociolinguistics

List of contributors 1. Accommodation theory: communication, context and consequence Howard Giles, Nikolas Coupland and Justine Coupland 2. Audience accommodation in the mass media Allan Bell 3. Accommodation on trial: processes of communicative accommodation in courtroom interaction Per Linell 4. Accommodation in medical consultations Richard L. Street, Jr 5. Accommodation and mental disability Heidi E. Hamilton 6. Accommodation in therapy Kathleen Ferrara 7. Accommodation in native-nonnative interactions: going beyond the 'what' to the 'why' in second-language research Jane Zuengler 8. Interethnic accommodation: the role of norms Cynthia Gallois and Victor J. Callan 9. Organisational communication and accommodation: toward some conceptual and empirical links Richard Y. Bourhis Index.
Des aires protégées aux réseaux écologiques : science, technique et participation pour penser collectivement la durabilité des territoires

Les strategies de conservation de la nature evoluent, de la protection stricte d’espaces isoles et depourvus d’activites humaines a l’integration des enjeux de biodiversite dans le developpement territorial. Ce changement de perspective, des aires protegees a la territorialisation de l’environnement, suppose de gerer la complexite et d’apprehender la nature collectivement et met l’accent sur les relations entre science, politique et societe. Cette these, fondee sur une approche pluridisciplinaire, a eu pour objectif l’elaboration de recommandations pour repondre aux enjeux d’une conservation integree de la biodiversite. S’inscrivant dans le contexte de l’avenement des strategies de reseau ecologique en France, notre recherche porte a la fois sur les methodes spatiales et sur les dispositifs socio-techniques en charge de planifier la conservation integree de la biodiversite. Chacune de ces parties a mene a des resultats et conclusions qui lui sont propres et a contribue a une reflexion plus globale sur le role de l’expertise pour repondre a ces nouveaux enjeux. Nous montrons comment une approche trop technique, centree notamment sur la spatialisation du reseau ecologique, tend non seulement a limiter le partage au sein du collectif et donc l’adhesion des acteurs mais aussi a fournir une vision reductrice et partielle des enjeux de conservation. A l’inverse, un positionnement de l’expertise en accompagnement du dialogue territorial favorise l’apprentissage social et aboutit a un cadre d’action publique qui integre davantage les incertitudes et la complexite du vivant. Le processus participatif doit donc permettre d’operer un glissement de l’expertise technique comme fondement de l’action publique a l’expertise collective qui assure l’integration des savoirs et savoir-faire de tous. Ainsi l’enjeu n’est pas celui du compromis entre science, technique comme fondement de l’action publique a l’expertise collective qui assure l’integration des savoirs et savoir-faire de tous. Ainsi l’enjeu n’est pas celui du compromis entre science, technique et debat social mais plutot celui de la gestion de leur interaction et de leur complementarite.
Parallel and Distributed Code Clone Detection using Sequential Pattern Mining

This research presents a parallel and distributed data mining approach to code clone detection. It aims to prove the value and importance of deploying parallel and distributed computing for real-time large scale code clone detection. It is implemented this approach in a family of clone detectors, called PD EgyCD (Parallel and Distributed Egypt Clone Detector). In this approach, This research builds on an earlier work of the authors for code clone and plagiarism detection using sequential pattern mining by adding parallelism and distribution to our earlier tool EgyCD. Our approach uses data mining through a tailored Apriori-based algorithm for code clone detection. And it uses parallelization and distribution to achieve excellent performance to scale up to clone detection on very large systems. This approach has been implemented as a database application which leverages the capabilities of modern database tools. Two versions have been developed of this distributed technique. The first one uses client-server technique in which all clients and the server deal with only one database. The second one uses agents where each client acts as a separate agent and has its own database and after working on a sub-problem, it submits its partial solution to the server to finally get the complete solution (set of code clones). Experiments show that agents technique is faster than clientserver one. Distribution enhances performance very much. Speed improvement is a function of the number of clients/agents used. Our conclusion is that data mining, combined with parallel and distributed computing, can efficiently be deployed for code clone detection of very large systems.
Estimating emotion of user via communicative stuffed-toy device with pressure sensors using fuzzy reasoning

In this research, we aim to perform emotion estimation based on the touching manner of communication using our stuffed-toy device that we had previously proposed in order to reduce the user's stress. In this paper, we propose a method to classify a user's emotions into three types: comfort, discomfort, and unknown, by adopting a fuzzy reasoning using histogram distribution of peaks of pressure sensor values. The results of the experiment confirmed the accuracy of classification as 69.1% of the correct answer rate when the results estimated as unknown are included in the correct answers, and 63.1% of the correct answer rate when the unknown results are excluded from the correct answer. We also discuss improvements of future methods.
Docosahexaenoic Acid, but Not Eicosapentaenoic Acid, Supplementation Reduces Vulnerability to Atrial Fibrillation

Background—The potential health benefits of &ohgr;-3 polyunsaturated fatty acids (PUFAs) usually are studied using a combination of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA). This combination reduces vulnerability to experimentally induced atrial fibrillation (AF). It is unknown whether EPA and DHA have differential effects when taken alone. Using a model of pacing-induced atrial hemodynamic overload, we investigated the individual effects of EPA and DHA on vulnerability to AF and atrial remodeling. Methods and Results—Thirty-four dogs were randomized into 3 groups, all of which underwent simultaneous atrial and ventricular pacing at 220 beats per minute for 14 days. One group received purified DHA (≈1 g/d) orally for 21 days beginning 7 days before pacing began. Similarly, 1 group received ≈1 g/d purified EPA. In a third (control) group (No-PUFAs), 8 dogs received ≈1 g/d olive oil, and 12 were unsupplemented. Electrophysiological and echocardiographic measurements were taken at baseline and 21 days. Atrial tissue samples were collected at 21 days for histological and molecular analyses. Persistent AF inducibility was significantly reduced by DHA compared with No-PUFAs median [25–75 percentiles], 0% [0%–3%] for DHA versus 3.1% [2.2%–11%] for No-PUFAs; P=0.007) but not by EPA (3.4% [1.9%–8.9%]). DHA also reduced atrial fibrosis compared with No-PUFAs (11±6% versus 20±4%, respectively; P<0.05), whereas EPA did not (15±5%; P>0.05). Conclusions—DHA is more effective than EPA in attenuating AF vulnerability and atrial remodeling in structural remodeling–induced AF.
A fuzzy expert system design for forecasting return quantity in reverse logistics network

Purpose – The purpose of this study is to develop a fuzzy expert system to design robust forecast of return quantity in order to handle uncertainties from the return process in reverse logistic network. Design/methodology/approach – The most important factors which have impact on return of products are defined. Then the factors which have collinearity with others are eliminated by using dimension redundancy analysis. By training data of selected factors with fuzzy expert system, the return amounts of alternative cities are forecasted. Findings – The performance metrics of the proposed model are found as satisfactory. That means the result of this study indicates that fuzzy expert systems can be used as a supportive tool for forecasting return quantity of alternative areas. Research limitations/implications – In the future, the proposed model can be used for forecasting other uncertain parameters such as return quality and return time. Other fuzzy systems such as type-2 fuzzy sets can be used, or other exp.
Built-in Clock Skew System for On-line Debug and Repair

We present a low-cost on-line system for clock skew management in integrated circuits. Our built-in clock skew system (BICSS) uses a centralized approach to identify, quantify and correct skew using a two-step method. The technique assesses the time-off-light between the central debug circuitry and each region, or tap under test to account for the measurement error due to differences in path length common in existing techniques. The system can be used to detect skew above a user-adjustable margin using a variable tolerance phase detector. The result is a solution which provides silicon debug and repair capability of on-chip clock skews with a very small area overhead.
A design for a smartphone-based head mounted display

Thin computing clients, such as smartphones and tablets, have experienced recent growth in display resolutions and graphics processing power. In this poster, we show how to leverage these trends to create an experimental wide field of view, 3D stereoscopic head mounted display (HMD), based on two high resolution smart-phones. This HMD prototype is unique in that the graphics system is entirely onboard, allowing it to be lightweight, wireless, and convenient to use.
Identifying Semantically Deviating Outlier Documents

A document outlier is a document that substantially deviates in semantics from the majority ones in a corpus. Automatic identification of document outliers can be valuable in many applications, such as screening health records for medical mistakes. In this paper, we study the problem of mining semantically deviating document outliers in a given corpus. We develop a generative model to identify frequent and characteristic semantic regions in the word embedding space to represent the given corpus, and a robust outlierness measure which is resistant to noisy content in documents. Experiments conducted on two real-world textual data sets show that our method can achieve an up to 135% improvement over baselines in terms of recall at top-1% of the outlier ranking.
Mechanism of Enhancement of Rat Brain Serotonin Synthesis by Acute Fluoxetine Administration

Tsuiki et a! (1995) reported in this Journal that acute intraperitoneal administration of a 30 mg/kg of body weight dose of the specific serotonin [5-hydroxytryptamine (5-HT)11 reuptake inhibitory (SSRI) antidepressant fluoxetine enhances rat brain 5-HT synthesis, as measured by the a-methyl-L-tryptophan autoradiographic method, and suggested that this is in part due to an increase in tryptophan (Trp) availability to the brain. This process is determined by at least three peripheral factors: binding to albumin, competition between Trp and five other amino acids (valine, leucine, isoleucine, phenylalanine, and tyrosine) for the same cerebral uptake mechanism, and activity of the major Trp-degrading enzyme, hepatic Trp pyrrolase (tryptophan 2,3-dioxygenase; EC 1.13.11.11) (for references, see Badawy and Morgan, 1991). Tsuiki et al. (1995) showed that fluoxetine does not influence the concentrations of the Trp competitors, but increases that of Trp itself (by 18% for the total content and 30% for the free fraction). Whether Trp binding to albumin was significantly altered by fluoxetine could not be ascertained from the data given.
A low-complexity robust estimation of multiple wideband polynomial-phase signals in sensor array

This paper addresses joint estimation of parameters of multiple polynomial-phase signals (PPSs) impinging on a sensor array and corresponding direction-of-arrivals (DOAs). Using a recently proposed method for the fine estimation of multiple PPSs, we first separate signal components and then estimate the parameters of interest from the spatial high-order instantaneous moments (SHIMs) of the obtained components. The parameter estimation is performed through maximizing the spectrum obtained by averaging the spectra of multiple rows and columns of the SHIM matrix. The proposed approach offers lower signal-to-noise ratio (SNR) threshold and higher accuracy with respect to concurrent methods. Since all parameters are estimated through 1-D searches, the calculation complexity is significantly reduced with respect to the maximum likelihood (ML) methods.