Miracle-dz/UniFAR-FTUs huggingface dataset:
Throughput-Effective On-Chip Networks for Manycore Accelerators

As the number of cores and threads in many core compute accelerators such as Graphics Processing Units (GPU) increases, so does the importance of on-chip interconnection network design. This paper explores throughput-effective network-on-chips (NoC) for future many core accelerators that employ bulk-synchronous parallel (BSP) programming models such as CUDA and OpenCL. A hardware optimization is "throughput-effective" if it improves parallel application level performance per unit chip area. We evaluate performance of future looking workloads using detailed closed-loop simulations modeling compute nodes, NoC and the DRAM memory system. We start from a mesh design with bisection bandwidth balanced with off-chip demand. Accelerator workloads tend to demand high off-chip memory bandwidth which results in a many-to-few traffic pattern when coupled with expected technology constraints of slow growth in pins-per-chip. Leveraging these observations we reduce NoC area by proposing a "checkerboard&quot, NoCwhich alternates between conventional full-routers and half-routers with limited connectivity. Checkerboard employs a new oblivious routing algorithm that maintains a minimum hop-count for architectures that place L2 cache banks at the half-router nodes. Next, we show that increasing network injection bandwidth for the large amount of read reply traffic at the nodes connected to DRAM controllers alleviates a significant fraction of the remaining imbalance resulting from the many-to-few traffic pattern. The combined effect of the above optimizations with an improved placement of memory controllers in the mesh and channel slicing improves application throughput per unit area by 25.4%.
Variability of Practice and Strength Training Periodization: When Theories Collide

The primary purpose of this study was to examine whether variability of practice enhances neuromuscular adaptations when compared to traditional strength training. The secondary purpose was to investigate whether there was a difference in perception of exertion between the two strength programs. Forty one subjects (23 women and 18 men) were assigned to either the control group or one of two treatment groups by a blocked-random method. Subject's one repetition maximum (1RM) for the kettlebell press and leg press were measured at baseline, after 4 weeks of training, and after 8 weeks of training. The treatment groups completed 8 weeks of training consisting of 3 days a week with at least one recovery day in between each session. In weeks 1 through 3, subjects undergoing the traditional treatment completed 3 sets of 8 repetitions at 70% of their 1RM for each exercise. Weeks 4 through 6 were composed of 3 sets of 6 repetitions at 77% 1RM. In weeks 7 and 8, 3 sets of 4 repetitions at 85% 1RM were performed. Over the course of the eight weeks, the variable treatment was comprised of 5 sets of the kettlebell and leg press. A set of 4 repetitions at 77% of the subject's 1RM, one of 5 repetitions at 70% 1RM, another of 3 repetitions at 85% 1RM, one of 6 repetitions at 65% 1RM, and finally a set of 2 repetitions at 93% 1RM were performed every session. The order of these sets were changed every 3 weeks, altering where in the session the highest intensity set was in relation to the lower intensity sets. Ratings of perceived exertion (RPE) were recorded following treatment to determine subject's perception of intensity during each set. Analysis of variance with repeated measures did not reveal significantly different strength gains between treatment groups in either lift, although variable treatment resulted in greater mean strength gains over almost every time interval. Analyses of RPE data revealed significantly lower reported RPE values for the variable treatment compared to the traditional treatment in both lifts. The greater mean strength gains and significantly lower RPEs of the variable treatment program compel us to conclude it is a superior training method for increasing strength compared to the traditional program. v ACKNOWLEDGMENTS I would like to thank my entire committee for all the support and constant guidance over the past two years in developing and implementing my thesis. Without …
Rough sets based reasoning and pattern mining for a two-stage information filtering system

This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern- based approaches to effectively filter sheer volume of infor- mation. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empow- ered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.
Simple trees in complex forests: Growing Take The Best by Approximate Bayesian Computation

How can heuristic strategies emerge from smaller building blocks? We propose Approximate Bayesian Computation as a computational solution to this problem. As a first proof of concept, we demonstrate how a heuristic decision strategy such as Take The Best (TTB) can be learned from smaller, probabilistically updated building blocks. Based on a self-reinforcing sampling scheme, different building blocks are combined and, over time, tree-like non-compensatory heuristics emerge. This new algorithm, coined Approximately Bayesian Computed Take The Best (ABC-TTB), is able to recover a data set that was generated by TTB, leads to sensible inferences about cue importance and cue directions, can outperform traditional TTB, and allows to trade-off performance and computational effort explicitly.
Hidden Markov models compared to the wavelet transform for P-wave segmentation in EGC signals

The aim of this study is to detect P-wave onset and end of electrocardiograms (ECG). This wave is important for detecting people prone to atrial fibrillation, one of the most frequent heart diseases, but the wave is very difficult to segment accurately because of its small amplitude and the very different shapes it can take. Two different methods are tested for the segmentation : the first one is based on Hidden Markov Models. Though results are good, some particular cases are not well segmented. However a second method based on the Continuous Wavelet Transform can solve those problems.
TESTING MAGNETIC STAR FORMATION THEORY

Zeeman observations of molecular clouds yield the line-of-sight component BLOS of the magnetic vector B, which makes it possible to test the two major extreme-case theories of what drives star formation—ambipolar diffusion or turbulence. However, only one of the three components of B is measurable, so tests have been statistical rather than direct, and they have not been definitive. We report here observations of the Zeeman effect in the 18 cm lines of OH in the envelope regions surrounding four molecular cloud cores toward which detections of BLOS have been achieved in the same lines, and evaluate the ratio of mass-to-magnetic flux, M/Φ, between the cloud core and envelope. This relative M/Φ measurement reduces uncertainties in previous studies, such as the angle between B and the line of sight and the value of [OH/H]. Our result is that for all four clouds, the ratios of the core to the envelope values of M/Φ are less than 1. Stated another way, the ratios of the core to the total cloud M/Φ are less than 1. The extreme case or idealized (no turbulence) ambipolar diffusion theory of core formation requires the ratio of the central to total M/Φ to be approximately equal to the inverse of the original subcritical M/Φ, or 1$? >. The probability that all four of our clouds have 1$? > is 3 × 10−7; our results are therefore significantly in contradiction with the hypothesis that these four cores were formed by ambipolar diffusion. Highly super-Alfvénic turbulent simulations yield a wide range of relative M/Φ, but favor a ratio , as we observe. Our experiment is limited to four clouds, and we can only directly test the predictions of the extreme-case “idealized” models of ambipolar-diffusion driven star formation, which have a regular magnetic field morphology. Nonetheless, our experimental results are not consistent with the “idealized” strong field, ambipolar diffusion theory of star formation. Comparisons of our results with more realistic models and simulations that include both ambipolar diffusion and turbulence may help to refine our understanding of the relative importance of magnetic fields and turbulence in the star formation process.
Insulin- and obesity-related variables in early-stage breast cancer: correlations and time course of prognostic associations.

PURPOSE To investigate patterns of prognostic associations over time of insulin- and obesity-related variables measured at diagnosis of early breast cancer (BC), focusing on whether the prognostic associations with distant recurrence and death changed over time. PATIENTS AND METHODS Five hundred thirty-five nondiabetic women with T1-3, N0-1, M0 invasive BC diagnosed from 1989 to 1996 were included in the study. Insulin-related variables included fasting insulin, Homeostasis Model Assessment, C-peptide, and glucose. Obesity-related variables included weight, body mass index (BMI), waist and hip circumference, and leptin. Correlations were examined using the Pearson correlation coefficient and prognostic associations using the Cox model. RESULTS There was evidence that associations of baseline insulin-related variables with distant recurrence and death were not constant over time; univariable adverse prognostic associations were significant only during the first 5 years (eg, insulin quartile 4 v 1: hazard ratio [HR], 2.32; 95% CI, 1.39 to 3.86; P < .001 for distant disease-free survival [DDFS]; and HR, 2.85; 95% CI, 1.48 to 5.50; P = .002 for overall survival [OS], with little attenuation of this pattern in multivariable analyses). In contrast, obesity-related variables (BMI, weight, leptin) exerted significant adverse univariable associations that were constant over time (eg, BMI quartile 4 v 2: HR, 1.40; 95% CI, 1.07 to 1.82 for DDFS; P = .014; and HR, 1.50; 95% CI, 1.16 to 1.93; P < .001 for OS); prognostic associations of leptin remained significant in multivariable analyses. CONCLUSION Baseline insulin- and obesity-related variables exert different patterns of prognostic associations over time in early BC.
Managing Diverse Sentiments at Large Scale

The large-scale aggregation and analysis of user opinions is becoming increasingly relevant to a variety of applications, from detecting social mood on some political topics to tracking their sentiment changes related to events. The analysis of diverse sentiments is another important application, which becomes possible based on the ability of modern methods to capture sentiment polarity on various topics with high precision and on the ever-growing scale. Therefore, there is a need for a scalable way of sentiment aggregation with respect to the time dimension, which stores enough information to preserve diversity, and which allows statistically accurate analysis of sentiment trends and opinion shifts. In this paper, we are focusing on the novel problem of aggregating diverse sentiments at a large scale, based on data sources that are continuously updated. First, we develop a theoretical framework that models sentiment diversity (contradiction) and defines two types of contradictions, depending on the distribution of sentiments over time. Second, we introduce novel measures that capture sentiment diversity from aggregated sentiment statistics. Third, we develop robust and scalable indexing and storage methods for diverse sentiments. Finally, we propose an adaptive approach for identifying contradictions at different time scales. The experimental evaluation demonstrates the effectiveness of the proposed method of capturing contradictions and its superiority over relational databases in real-world scenarios.
Perceptions of self-concept and actual academic performance in Math and English among High School Students in Kenya

This study examined the relationship between self-concept and students’ academic performance in math and English for high school students in Kenya. Participants included 1990 students from two same sex boarding schools-one for boys and the other for girls. Results showed there were sex and grade differences in academic performance and most aspects of self-concept. Specifically, girls did better in math. Performance in English was not significantly different. Grade level differences showed a downward trend relative to norms in both math and English performance with the lower grade levels performing better. This trend possibly related to the changing standards by the teachers. On the selfconcept measures, boys rated themselves significantly higher than girls except for physical appearance. As the students progressed through each grade level, their perceptions of self increased. Study implications are discussed.
A Low-Dropout Regulator With Tail Current Control for DPWM Clock Correction

A low-dropout (LDO) regulator with tail current control (TCC) is presented. The TCC consists of a dual differential pair, a 5-bit current digital-to-analog converter, and a current summation circuit. The TCC adjusts the tail current ratio of the dual differential pair of the LDO regulator to achieve a programmable output voltage using 5-bit digital signals. A supply-ripple isolation mechanism is added to improve the power supply rejection over a wide frequency range. The proposed design is fabricated in the TSMC 0.18-μm 1-poly 6-metal complementary metal-oxide-semiconductor process. Experimental results show that the LDO regulator has a 32-level programmable output voltage ranging from 1 to 1.2 V, making the LDO regulator suitable for correcting the oscillator frequency of a digital pulsewidth modulator.
Graph Generation with Prescribed Feature Constraints

In this paper, we study the problem of how to generate synthetic graphs matching various properties of a real social network with two applications, privacy preserving social network publishing and significance testing of network analysis results. We present a simple switching based graph generation approach to generate graphs preserving features of a real graph. We then investigate potential disclosures of sensitive links due to the preserved features. Our algorithms on graph generation with feature range and feature distribution constraints are based on the Metropolis-Hastings sampling. This is of importance for significance testing of network analysis results.
A physically-based motion retargeting filter

This article presents a novel constraint-based motion editing technique. On the basis of animator-specified kinematic and dynamic constraints, the method converts a given captured or animated motion to a physically plausible motion. In contrast to previous methods using spacetime optimization, we cast the motion editing problem as a constrained state estimation problem, based on the per-frame Kalman filter framework. The method works as a filter that sequentially scans the input motion to produce a stream of output motion frames at a stable interactive rate. Animators can tune several filter parameters to adjust to different motions, turn the constraints on or off based on their contributions to the final result, or provide a rough sketch (kinematic hint) as an effective way of producing the desired motion. Experiments on various systems show that the technique processes the motions of a human with 54 degrees of freedom, at about 150 fps when only kinematic constraints are applied, and at about 10 fps when both kinematic and dynamic constraints are applied. Experiments on various types of motion show that the proposed method produces remarkably realistic animations.
Nabu - A Semantic Archive for XMPP Instant Messaging

Instant messaging (IM) has become more and more common these days, and is complementing email and other means of electronic communication. However, due to its heavily context-dependent nature, searching archives of instant messages using only full text search is a tedious task. Also, in contrast to mails, files, and other electronic media, instant messages typically do not feature a unique identifier or location, making it difficult to reference a particular instant messaging conversation. Nabu is a semantic archive for XMPP instant messaging designed to address these problems by implementing a semantic message store, using RDF(S) as its storage format. It is implemented as a server module and will log messages, manage access control to the archives on a per-user basis, and allow other components to observe and annotate messages.
Clostridium glycolicum Bacteremia in a Bone Marrow Transplant Patient

ABSTRACT We describe a case of Clostridium glycolicum bacteremia and septic shock in an adult woman with a recent bone marrow transplant for relapsed Hodgkin's disease. The bacterium was identified by 16S rRNA gene sequencing. This is the first published report of the recovery of this organism from human clinical material.
Discriminative approach to dynamic variance adaptation for noisy speech recognition

The performance of automatic speech recognition suffers from severe degradation in the presence of noise or reverberation. One conventional approach for handling such acoustic distortions is to use a speech enhancement technique prior to recognition. However, most speech enhancement techniques introduce artifacts that create a mismatch between the enhanced speech features and the acoustic model used for recognition, therefore limiting the improvement in recognition performance. Recently, there has been increased interest in methods capable of compensating for such a mismatch by accounting for the feature variance during decoding. In this paper, we propose to estimate the feature variance using an adaptation technique based on a discriminative criterion. In an experiment using the Aurora2 database, the proposed method could achieve significant digit error rate reduction compared with a spectral subtraction pre-processor, and using a discriminative criterion for adaptation provided further improvement compared with maximum likelihood estimation.
Supporting children's social communication skills through interactive narratives with virtual characters

The development of social communication skills in children relies on multimodal aspects of communication such as gaze, facial expression, and gesture. We introduce a multimodal learning environment for social skills which uses computer vision to estimate the children's gaze direction, processes gestures from a large multi-touch screen, estimates in real time the affective state of the users, and generates interactive narratives with embodied virtual characters. We also describe how the structure underlying this system is currently being extended into a general framework for the development of interactive multimodal systems.
Constructing differences in a cross-cultural context: National distance, social differentiation or functional distinction

This article develops theory about the perspectives through which expatriate managers and their employees socially construct differences in a cross-cultural context. On the basis of qualitative research on three kinds of organizations – multinational corporations, small and medium-sized enterprises and start-up companies – we identify three perspectives on differences in a cross-cultural context: the national distance perspective, the social differentiation perspective and the functional distinction perspective. Each perspective relates to a specific basis for categorization (nationality, status and function), focus of attention (values, attitudes and expertise) and definition of diversity (separation, disparity and variety). We find that international experience and country experience on one side, and the purpose of business (business development, business creation or business turnaround) on the other side, explain why some expatriate managers and their employees adopt one perspective or another, sometimes as default. The passing of time, as reflected in growing country experience, growing work experience and growing company tenure, can be the motor of transition from one perspective to another. Our findings contribute to cross-cultural and diversity studies, to social constructionism, and have consequences for international human resource management research and practices.
A grid-based algorithm for on-device GSM positioning

We propose a grid-based GSM positioning algorithm that can be deployed entirely on mobile devices. The algorithm uses Gaussian distributions to model signal intensity variations within each grid cell. Position estimates are calculated by combining a probabilistic centroid algorithm with particle filtering. In addition to presenting the positioning algorithm, we describe methods that can be used to create, update and maintain radio maps on a mobile device. We have implemented the positioning algorithm on Nokia S60 and Nokia N900 devices and we evaluate the algorithm using a combination of offline and real world tests. The results indicate that the accuracy of our method is comparable to state-of-the-art methods, while at the same time having significantly smaller storage requirements.
Spam Filtering Based On The Analysis Of Text Information Embedded Into Images

In recent years anti-spam filters have become necessary tools for Internet service providers to face up to the continuously growing spam phenomenon. Current server-side anti-spam filters are made up of several modules aimed at detecting different features of spam e-mails. In particular, text categorisation techniques have been investigated by researchers for the design of modules for the analysis of the semantic content of e-mails, due to their potentially higher generalisation capability with respect to manually derived classification rules used in current server-side filters. However, very recently spammers introduced a new trick consisting of embedding the spam message into attached images, which can make all current techniques based on the analysis of digital text in the subject and body fields of e-mails ineffective. In this paper we propose an approach to anti-spam filtering which exploits the text information embedded into images sent as attachments. Our approach is based on the application of state-of-the-art text categorisation techniques to the analysis of text extracted by OCR tools from images attached to e-mails. The effectiveness of the proposed approach is experimentally evaluated on two large corpora of spam e-mails.
A Method Factor Predictor of Performance Ratings

A method factor estimated from a Big Five questionnaire was positively correlated with supervisor ratings of performance. Validities of the Big Five variables were negligible or negative in the context of the method factor. The possibility that the method factor represented impression management is discussed. PRESS PARAGRAPH This study investigated validity of the Big Five in a model in which a common method factor was estimated. In this model, the common method factor had significant positive validity for prediction of supervisor ratings of customer service, sales, and collections performance of financial services employees while the validities of the Big Five were negligible or negative. The possibility that the method factor found here represented impression management, i.e., faking, is discussed.