Miracle-dz/UniFAR-FTUs huggingface dataset:
FAST: A Fast Stencil Autotuning Framework Based On An Optimal-solution Space Model

Stencil computations comprise an important class of kernels in many scientific computing applications. As the diversity of both architectures and programming models grow, autotuning is emerging as a critical strategy for achieving portable performance across a broad range of execution contexts for stencil computations. However, costly tuning overhead is a major obstacle to its popularity. In this work, we propose a fast stencil autotuning framework FAST based on an Optimal-Solution Space (OSS) model to significantly improve tuning speed. It leverages a feature extractor that comprehensively characterizes stencil computation. Using the extracted features, FAST constructs an OSS database to train an off-line model which provides an on-line prediction. We evaluate FAST with five important stencil computation applications on both an Intel Xeon multicore CPU and an NVIDIA Tesla K20c GPU. Compared with state-of-the-art stencil autotuners like Patus and SDSL, FAST improves autotuning speed by 10-2697 times without any user annotation, while achieving comparable performance.
Development and Testing of Index Policies in Internet Routers

In this thesis we address the problem of fast and fair transmission of flows in a router, which is a fundamental issue in networks like the Internet. We develop and test a new policy that can be implemented in Internet routers in order to efficiently manage the packets arriving to their buffers in order to prevent congestion of the network when users want to send too much data. We have formulated a single Transmission Control Protocol (TCP) flow as a Markov decision process and analyzed both theoretically and numerically the existence of optimal control policies of special structure. In particular, we can conclude that for a variety of parameters, TCP flows can be optimally controlled in routers by so-called index policies, but not always by threshold policies. We have also implemented index policies in Network Simulator-3 and tested in a simple topology their applicability in real networks.
Benchmark Suites to Measure Computer Performance

The purpose of this work is to show one particular technique to measure and compare the performance of computers – benchmarking. First an overview is given of what is relevant in a bench rehearsal, and then some of the main benchmarking techniques are presented. A reference is made to the work carried out by the main international benchmarking organisms, focusing on the SPEC consortium and on its CPU2000 benchmark suite.
A simple peer-to-peer algorithm for distributed optimization in sensor networks

We propose a distributed algorithm that solves a special class of optimization problems using only peer-to- peer communication. One application is parameter estimation problems in sensor networks. Current decentralized algorithms for solving this class of optimization problems typically rely on passing around a parameter estimate in a ring consisting of all network nodes. In our algorithm, which extends the randomized incremental subgradient method with fixed stepsize due to Nedic and Bertsekas, nodes maintain individual estimates and need to exchange information only with their neighbors. We establish approach of the solution to an interval around the optimum value. We illustrate the algorithm's performance, in terms of convergence rate and communication cost relative to alternative schemes, through several numerical examples.
Simple Reinforcement Learning for Small-Memory Agent

In this paper, we propose Simple Reinforcement Learning for a reinforcement learning agent that has small memory. In the real world, learning is difficult because there are an infinite number of states and actions that need a large number of stored memories and learning times. To solve a problem, estimated values are categorized as ``GOOD" or ``NO GOOD" in the reinforcement learning process. Additionally, the alignment sequence of estimated values is changed because they are regarded as an important sequence themselves. We conducted some simulations and observed the influence of our methods. Several simulation results show no bad influence on learning speed.
Sequential Composition of Dynamically Dexterous Robot Behaviors

We report on our efforts to develop a sequential robot controller-composition technique in the context of dexterous “batting” maneuvers. A robot with a flat paddle is required to strike repeatedly at a thrown ball until the ball is brought to rest on the paddle at a specified location. The robot’s reachable workspace is blocked by an obstacle that disconnects the free space formed when the ball and paddle remain in contact, forcing the machine to “let go” for a time to bring the ball to the desired state. The controller compositions we create guarantee that a ball introduced in the “safe workspace” remains there and is ultimately brought to the goal. We report on experimental results from an implementation of these formal composition methods, and present descriptive statistics characterizing the experiments.
Biosurfactant production from marine hydrocarbon-degrading consortia and pure bacterial strains using crude oil as carbon source

Biosurfactants (BSs) are “green” amphiphilic molecules produced by microorganisms during biodegradation, increasing the bioavailability of organic pollutants. In this work, the BS production yield of marine hydrocarbon degraders isolated from Elefsina bay in Eastern Mediterranean Sea has been investigated. The drop collapse test was used as a preliminary screening test to confirm BS producing strains or mixed consortia. The community structure of the best consortia based on the drop collapse test was determined by 16S-rDNA pyrotag screening. Subsequently, the effect of incubation time, temperature, substrate and supplementation with inorganic nutrients, on BS production, was examined. Two types of BS – lipid mixtures were extracted from the culture broth; the low molecular weight BS Rhamnolipids and Sophorolipids. Crude extracts were purified by silica gel column chromatography and then identified by thin layer chromatography and Fourier transform infrared spectroscopy. Results indicate that BS production yield remains constant and low while it is independent of the total culture biomass, carbon source, and temperature. A constant BS concentration in a culture broth with continuous degradation of crude oil (CO) implies that the BS producing microbes generate no more than the required amount of BSs that enables biodegradation of the CO. Isolated pure strains were found to have higher specific production yields than the complex microbial marine community-consortia. The heavy oil fraction of CO has emerged as a promising substrate for BS production (by marine BS producers) with fewer impurities in the final product. Furthermore, a particular strain isolated from sediments, Paracoccus marcusii, may be an optimal choice for bioremediation purposes as its biomass remains trapped in the hydrocarbon phase, not suffering from potential dilution effects by sea currents.
Wide scope indefinites in Russian: an experimental investigation

This paper contributes to the cross-linguistic study of indefinites by reporting on two experimental studies on the scopal and functional properties of the two Russian indefinites koe- and -to. We show that koe- allows not only wide scope readings out of syntactic islands, but also functional readings, much like English a certain. -to, on the other hand, allows all possible scopal readings and both functional and non-functional readings. We then discuss this state of affairs from the perspective of a number of prominent theories of indefinite scope.
Fuzzy-Based Extraction of Vascular Structures from Time-of-Flight MR Images

In this paper an automatic fuzzy based method for the extraction of the cerebrovascular system from 3D Time-of-Flight (TOF) MRA image sequences is presented. In order to exclude non-brain tissue an automatic skull stripping method is applied in a preprocessing step. Based on the TOF images vesselness and maximum parameter images are computed first. These parameter images are then combined with the TOF sequence using a fuzzy inference. The resulting fuzzy image offers an improved enhancement of small as well as malformed vessels against the remaining brain. Finally, the fuzzy-connectedness approach is used to extract the vascular system. A first evaluation showed that the fuzzy-based method proposed performs better than a state of the art method and yields results in the range of the inter-observer variation.
QUANTITATIVE INVESTIGATIONS OF IDIOTYPIC ANTIBODIES

Rabbit anti-idiotypic antibodies were prepared by injection of specifically purified anti-p-azobenzoate antibodies (D) from individual donor rabbits. Benzoate derivatives were found to be strong inhibitors of the reactions of D with anti-D antisera. There was a close correlation between the combining affinities of the benzoate derivatives used and their effectiveness as inhibitors. Compounds tested that are chemically unrelated to benzoate were ineffective. The results indicate either that the combining site of anti-benzoate antibody is part of an important idiotypic determinant, which is sterically blocked by hapten, or that the hapten induces a conformational change which alters idiotypic determinants not involving the active site. Such conformational changes, if they occur, must be restricted since hapten has little effect on the reactions of F(ab')2 fragments of anti-benzoate antibodies with antisera directed to rabbit fragment Fab and no detectable effect on reactions with antibodies directed to allotypic determinants.
POSTER: Fingerprinting Tor Hidden Services

The website fingerprinting attack aims to infer the content of encrypted and anonymized connections by analyzing patterns from the communication such as packet sizes, their order, and direction. Although recent study has shown that no existing fingerprinting method scales in Tor when applied in realistic settings, this does not consider the case of Tor hidden services. In this work, we propose a two-phase fingerprinting approach applied in the scope of Tor hidden services and explore its scalability. We show that the success of the only previously proposed fingerprinting attack against hidden services strongly depends on the Tor version used; i.e., it may be applicable to less than 1.5% of connections to hidden services due to its requirement for control of the first anonymization node. In contrast, in our method, the attacker needs merely to be somewhere on the link between the client and the first anonymization node and the attack can be mounted for any connection to a hidden service.
A Constrained ℓ1 Minimization Approach to Sparse Precision Matrix Estimation

This article proposes a constrained ℓ1 minimization method for estimating a sparse inverse covariance matrix based on a sample of n iid p-variate random variables. The resulting estimator is shown to have a number of desirable properties. In particular, the rate of convergence between the estimator and the true s-sparse precision matrix under the spectral norm is when the population distribution has either exponential-type tails or polynomial-type tails. We present convergence rates under the elementwise ℓ∞ norm and Frobenius norm. In addition, we consider graphical model selection. The procedure is easily implemented by linear programming. Numerical performance of the estimator is investigated using both simulated and real data. In particular, the procedure is applied to analyze a breast cancer dataset and is found to perform favorably compared with existing methods.
The stability of the O invariant fixed point in three dimensions

We study the stability of the O(N) fixed point in three dimensions under perturbations of the cubic type. We address this problem in the three cases N = 2,3,4 by using finite-size scaling techniques and high-precision Monte Carlo simulations. It is well known that there is a critical value below which the O(N) fixed point is stable and above which the cubic fixed point becomes the stable one. Whilst we cannot exclude that , as recently claimed, our analysis strongly suggests that coincides with 3.
A successive sub-grouping method for multiple sequence alignments analysis

A novel approach to protein multiple sequence alignment is discussed: substantially this method counterparts with substitution matrix based methods (like Blosum or PAM based methods), and implies a more deterministic approach to chemical/physical sub-grouping of amino acids . Amino acids (aa) are divided into sub-groups with successive derivations, that result in a clustering based on the considered property. The properties can be user defined or chosen between default schemes, like those used in the analysis described here. Starting from an initial set of the 20 naturally occurring amino acids, they are successively divided on the basis of their polarity/hydrophobic index, with increasing resolution up to four level of subdivision. Other schemes of subdivision are possible: in this thesis work it was employed also a scheme based on physical/structural properties (solvent exposure, lateral chain mobility and secondary structure tendency), that have been compared to the chemical scheme with testing purposes. In the method described in this chapter, the total score for each position in the alignment accounts for different degree of similarity between amino acids. The scoring value result form the contribution of each level of selectivity for every individual property considered. Simply the method (called M_Al) analyse the n sequence alignment position per position and assigns a score which have contributes by aa identity plus a composed valuation of the chemical or of the structural affinity between the n aligned amino acids. This method has been implemented in a series of programs written in python language; these programs have been tested in some biological cases, with benchmark purposes.
On the Benjamini-Hochberg method

We investigate the properties of the Benjamini-Hochberg method for multiple testing and of a variant of Storey's generalization of it, extending and complementing the asymptotic and exact results available in the literature. Results are obtained under two different sets of assumptions and include asymptotic and exact expressions and bounds for the proportion of rejections, the proportion of incorrect rejections out of all rejections and two other proportions used to quantify the efficacy of the method
Spatial Vision Loss in Bipolar Disorder: Case Series and Literature Review

Several studies have investigated cognition in bipolar disorder (BPD), but there is a large gap in the literature with regard to visual processing in BPD. The contrast sensitivity function (CSF) is one of the main measures that is used to verify and describe spatial processing responses and their mechanisms. The present article describes a retrospective case series and literature review of the presentation and outcome of visual processing in BPD. Our series included 5 patients with Type I BPD, 22- to 41-years-old. None of the patients had a history of neurological or cardiovascular disease, head trauma, chronic contact with such substances as organic solvents, or current or prior drug abuse. They also did not present comorbidities. None of the patients had ocular disease, based on fundoscopic and optical coherence tomography examinations. Patients with BPD had lower CSF at low and high spatial frequencies when compared with a nonclinic group. Further control studies are needed to confirm or refute the assumption that BPD affects visual processing.
Motivational and cognitive components of self-presentation in humor and embarrassment: A multi-measure approach

Different methodological approaches were taken to explore the role of situational variables and personality factors that measure the motivational component of self presentation on degree of subjects' reported feelings of threat and their response time to complete self-directed humorous or embarrassing situations. In Study 1 a questionnaire approach was utilized and qualitative as well as quantitative data was analyzed. Specifically, humorous and embarrassing situations that male and female subjects provided were compared. Relations were found between personality measures and reported degree of threat. Study 2 included a response time measure and number of times a subject made another person the target of the situation as dependent measures in addition to the threat measure. It was found that the threat measure was affected most by the personality factors. When controlling for motivation (personality) and threat (affect), there were still significant effects for condition on response time. Subjects took longer to complete embarrassing than humorous situations. This result suggests that there are cognitive elements involved in self presentation. In Study 3, degree of threat posed by the companion was manipulated. While there were no effects for threat, when motivation and affect were controlled for, there were significant companion gender by degree of threat interactions for response time and number of reversals. Subjects took longer to complete humorous situations when they were with high threat females and low threat males, and they also performed fewer reversals when they were with low threat females than any other companion. It is suggested that this interaction has its basis in cognitive processing. Implications of this research for continuing to explore the role of both motivation and cognition in self presentation are discussed.
Visual Mental Imagery Activates Topographically Organized Visual Cortex: PET Investigations

Cerebral blood flow was measured using positron emission tomography (PET) in three experiments while subjects performed mental imagery or analogous perceptual tasks. In Experiment 1, the subjects either visualized letters in grids and decided whether an X mark would have fallen on each letter if it were actually in the grid, or they saw letters in grids and decided whether an X mark fell on each letter. A region identified as part of area 17 by the Talairach and Tournoux (1988) atlas, in addition to other areas involved in vision, was activated more in the mental imagery task than in the perception task. In Experiment 2, the identical stimuli were presented in imagery and baseline conditions, but subjects were asked to form images only in the imagery condition; the portion of area 17 that was more active in the imagery condition of Experiment 1 was also more activated in imagery than in the baseline condition, as was part of area 18. Subjects also were tested with degraded perceptual stimuli, which caused visual cortex to be activated to the same degree in imagery and perception. In both Experiments 1 and 2, however, imagery selectively activated the extreme anterior part of what was identified as area 17, which is inconsistent with the relatively small size of the imaged stimuli. These results, then, suggest that imagery may have activated another region just anterior to area 17. In Experiment 3, subjects were instructed to close their eyes and evaluate visual mental images of upper case letters that were formed at a small size or large size. The small mental images engendered more activation in the posterior portion of visual cortex, and the large mental images engendered more activation in anterior portions of visual cortex. This finding is strong evidence that imagery activates topographically mapped cortex. The activated regions were also consistent with their being localized in area 17. Finally, additional results were consistent with the existence of two types of imagery, one that rests on allocating attention to form a pattern and one that rests on activating stored visual memories.
Exploiting MB level parallelism in H.264/AVC encoder for multi-core platform

H.264/AVC video coding standard has achieved a significant improvement in coding efficiency over previous standards, such as, H.261, H.263 and MPEG-4, at the cost of computational complexity. This paper takes advantage of the macroblock (MB) level parallelism in H.264/AVC encoder and based upon this represents a scheme to implement the encoder for multi-core platform. According to this technique an encoding process of an MB is divided into several independent phases and each phase is executed on a separate processing core. Moreover to efficiently utilize the multi-core processors and to improve the encoder performance, the encoder is pipelined at MB level. The experimental results show that encoding rate of pipelined encoder as compare to sequential encoder is improved from 6 fps to 72 fps and from 2 fps to 32 fps for FD1 (720 × 480) and HD 720p (1280 × 720) resolutions, respectively. The implemented encoder can be used for multimedia applications like video conferencing, smart phones, high quality mobile digital video recorders, tablet computers, mobile digital TVs etc.
Internet Multi-Resolution Analysis : A vision and framework in support of representing , analyzing , and visualizing Internet measurements

Empirical analysis has been the foundation for a great deal of network research and has resulted in significant improvements to Internet systems, protocols and practices. Recent progress applying a constantly expanding set of increasingly more sophisticated statistical tools suggests the emergence of a new type of empirical network research that could benefit from a more principled approach for representing, analyzing, and visualizing a wide variety of Internet-related measurements. To this end, we propose and introduce in this position paper the concept of an Internet-centric multiresolution analysis (MRA). Internet MRA is a structured approach to Internet data representation and establishes a framework for systematically applying statistical analysis, signal processing or machine learning techniques to provide critical insights into a number of challenging network research problems. Ultimately, the success of Internet MRA will be gauged by its ability to solve important problems in network research and operations and in the new lines of inquiry that it enables.
Identifying Important Users in Sina Microblog

Important users are high-status vertices in social networks. They are everywhere in most fields of society and have big impact on those around them. Although a lot of effort has been made on identifying important users, the efficient methods still need to be developed, especially for the web users from Sina microblog, which is the most popular social networking sites in China and has unique characteristics. In this paper, a machine learning-based method which only uses several attributes on Naive Bayes Classifiers (NBC) and Back Propagation Neural Network (BPNN) was proposed to identify important users. Initial experiments indicate that our method is effective. The result of "high" category has more than 55% accuracy rate. We find the NBC can identify more important users while BPNN has higher accuracy rate. What's more, the numbers of follower and followings in Sina microblog is independent.