Miracle-dz/UniFAR-FTUs huggingface dataset:
A Characterization Study on Memory Value Reuse

This paper presents a comprehensive characterization study on the exploitable memory value reuse present in programs. We compare three reuse schemes: store value reuse, loaded value reuse, and macro data reuse [12], [13]. Macro data reuse, enabled by macro data loads, capitalizes on under-ut ilized cache port bandwidth and makes use of the spatial locality fo und in port-wide macro data. Using a generalizedmemory value reuse table (MVRT) model, we present the results of (1) per program reuse analysis, (2) per data size analysis, (3) per region an lysis, (4) per MVRT size analysis, and (4) estimating the impact of I SA and machine widths. The macro data load mechanism is shown to open up significantly more loaded value reuse instances comp ared with previous loaded value reuse proposals: over 75% (SPEC2 k integer), 23% (SPEC2k floating-point), and 139% (MiBench) more load-to-load forwarding opportunities using a 64-ent ry MVRT. We also perform a quantitative study using a realistic processor model and show that over 35% of L1 cache accesses in the SPEC2k integer and MiBench programs can be eliminated, resulting in a related energy reduction of 27% and 31% on average, respectively.
Child Emotional Abuse by Parents and Its Risk Factors

Objective To ascertain the prevalence of child emotional abuse (CEA) by parents,to explore the risk factors of CEA by parents.Methods One hundred and eighty-five pupils' parents from an elementary school of a city were surveyed by self-administered questionnaire anonymously in July 2005.Results Overall,30.8% of parents reported having maltreated emotionally towards their children at least one time,one of five forms in the last year,the five forms CEA were humiliating in front of other people,to try to make the child feel that he/she were bad,stupid or worthless (13.5%),saying to the child wish he/she had never been born,or were dead (7.0%),threatening to abandon the child,or banishing the child from the house and family (14.1%),the child had witnessed very severe hitting or beating of family member at home (10.8%),threatening the child that he/she would be badly hurt (6.5%). Comparing those with humiliating experiences by their own parents/guardians or/and teachers to those with no such abuse,the risk of maltreating emotionally to their children was 2.9 times.Parents' CEA behavior was not significantly associated with their children's gender and age,and it was also not significantly associated with parents' education level,gender and age.Conclusion Findings from this research suggests that the problem of CEA by parents is common.Parents' humiliating experience by their own parents/guardians or/and teachers was a risk factor of emotional maltreatment to their own children.
Incorporate Credibility into Context for the Best Social Media Answers

In this paper, we focus on the task of identifying the best answer for a usergenerated question in Collaborative Question Answering (CQA) services. Given that most existing research on CQA has focused on non-textual features such as click-through counts which are relatively difficult to access, we examine the effectiveness of diverse content-based features for the task. Specially, we propose to explore how the information of evidentiality can contribute to the task. By the comparison of diverse textual features and their combinations, the current study provides useful insight into the issues of detecting the best answer to a given question in CQA without user features or system specific link structures.
Solving Large-Scale QAP Problems in Parallel with the Search Library ZRAM

Program libraries are one tool to make the cooperation between specialists from various fields successful: the separation of application-specific knowledge from application-independent tasks ensures portability, maintenance, extensibility, and flexibility. The current paper demonstrates the success in combining problem-specific knowledge for the quadratic assignment problem (QAP) with the raw computing power offered by contemporary parallel hardware by using the library of parallel search algorithms ZRAM. Solutions of previously unsolved large standard test-instances of the QAP are presented.
Ieee Transactions on Visualization and Computer Graphics Automatic Construction of Quad-based Subdivision Surfaces Using Fitmaps

—We present an automatic method to produce a Catmull-Clark subdivision surface that fits a given input mesh. Its control mesh is coarse and adaptive, and it is obtained by simplifying an initial mesh at high resolution. Simplification occurs progressively via local operators and addresses both quality of surface and faithfulness to the input shape throughout the whole process. The method is robust and performs well on rather complex shapes. Displacement mapping or normal mapping can be applied to approximate the input shape arbitrarily well.
The Effects of Rare Economic Crises on Credit Spreads and Leverage

Rare disasters have been shown to explain several asset pricing puzzles, such as the equity risk premium and credit spread puzzles. Existing analysis ignores the impact of corporate financing decisions on asset prices by taking them as exogenous. The aim of this paper is to investigate how rare disasters affect endogenous default and capital structure decisions by firms and how, in turn, these corporate financial decisions affect the way in which rare disasters impact credit spreads, leverage and the equity risk premium. We find that the possibility of rare disasters makes firms more conservative in their financial policy, leading to higher interest coverage, but lower leverage ratios, together with larger credit spreads and equity risk premia. JEL Classification Numbers: E44, G12, G32, G33
High-level learning from demonstration with conceptual spaces and subspace clustering

Learning from demonstration (LfD) aims at robots learning skills from human-demonstrated tasks. Robots should be able to learn at all levels of abstraction. Unlike at the level of motor primitives, high-level LfD requires symbolic representations. It thus faces the classical problem of symbol grounding. Furthermore, it requires the robot to interpret human-demonstrated actions at a higher, conceptual abstraction level. We present a method, that enables a robot to recognize human-demonstrated pick-and-place task goals on an object-relational abstraction layer. The robot can reproduce the task goals in new situations using a symbolic planner. We show that in a robotic context conceptual spaces can serve as a mean for symbol grounding at an object-relational level as well as for the recognition of conceptual similarities in effects of human-demonstrated actions. The method is evaluated in experiments on a real robot.
Several Human Cyclin-Dependent Kinase Inhibitors, Structurally Related to Roscovitine, As New Anti-Malarial Agents

In Africa, malaria kills one child each minute. It is also responsible for about one million deaths worldwide each year. Plasmodium falciparum, is the protozoan responsible for the most lethal form of the disease, with resistance developing against the available anti-malarial drugs. Among newly proposed anti-malaria targets, are the P. falciparum cyclin-dependent kinases (PfCDKs). There are involved in different stages of the protozoan growth and development but share high sequence homology with human cyclin-dependent kinases (CDKs). We previously reported the synthesis of CDKs inhibitors that are structurally-related to (R)-roscovitine, a 2,6,9-trisubstituted purine, and they showed activity against neuronal diseases and cancers. In this report, we describe the synthesis and the characterization of new CDK inhibitors, active in reducing the in vitro growth of P. falciparum (3D7 and 7G8 strains). Six compounds are more potent inhibitors than roscovitine, and three exhibited IC50 values close to 1 µM for both 3D7 and 7G8 strains. Although, such molecules do inhibit P. falciparum growth, they require further studies to improve their selectivity for PfCDKs.
Interpersonal Relations and Social Patterns in Communication Technologies: Discourse Norms, Language Structures and Cultural Variables

Use of mediated channels of communication, such as email and instant messenger, is rapidly increasing, especially with adolescents and college-aged populations. This increase may alter interpersonal relationship maintenance strategies and communication patterns. The role of mediated channels of communication in some types of relationship initiation is well documented however, research investigating use within existing relationships is more limited. Self-disclosure is an important part of relationship maintenance, both in the initial stages of development as well as in existing relationships. This chapter explores motivations for disclosure through computer mediated communication (CMC) in pre-existing relationships and describes theoretical perspectives to advance examination of this area. Examples presented indicate four primary motivations for disclose through computer mediated communication: self, other, relationship, and situational/environmental. Further, we propose several codes within each primary reason, many of which diverged from traditional motivations for FtF disclosure. Implications and future directions for interpersonal CMC research are discussed.
A Novel Secured Data Exchange Mechanism for Text Data Using Encode and Decode Mechanism

The Internet traffic is increasing day by day. Also, secure data communication is the need of the hour. But the standard compression techniques which are in use, are independent and do not consider the security issues. Hence, we present a general encoding technique for secure data communication over a language L with a finite alphabet set ˇ. The encoded message is a bi-tuple of which, the first is a vector of quotients denoted as Q and the second is a representation of remainders denoted as R with respect to a modulus M. The secrecy of the message is retained by communicating R over a secure channel using some standard encryption mechanism. The computation overhead is also reduced as the encryption is done only on one half of the encoded message. Further, this encoding mechanism provides a lossless compression are using TDEA algorithm for encryption.
Quality Requirements Analysis with Machine Learning

The importance of software quality requirements (QR) is bei ng widely recognized, which motivates studies that investigate software requirements specifications (SR S) in practice and collect data on how much QR are written vs. functional requirements (FR) and what kind of QR are specified. It is useful to develop a tool that automates the process of filtering out QR statements fro m an SRS and classifying them into the quality characteristic attributes such as defined in the ISO/IEC 250 00 quality model. We propose an approach that uses a machine learning technique to mechanize the process. With this mechanism, we can identify how each QR characteristic scatters over the document, i.e. how much in volume and in what way. A tool QRMiner is developed to support the process and case studies were condu cted, taking thirteen SRS documents that were written for real use. We report our findings from these cases.
A simple median-based resilient consensus algorithm

This paper studies the problem of reaching consensus resiliently in the presence of misbehaving nodes. We design a consensus algorithm where, at each time-step, each node updates its value as a weighted average of its own value and the median of its neighbors' values. This algorithm requires no global information about the network, and is computationally lightweight. We develop a novel graph property that we term excess robustness, and use this property to characterize the ability of the median algorithm to succeed under various fault models. We also provide a construction for excess robust graphs. We show that the sensitivity of this algorithm varies greatly under different fault models, and make connections to related ideas from the literature on contagion and graphical games.
Functional and Structural Consequences of Damaging Single Nucleotide Polymorphisms in Human Prostate Cancer Predisposition Gene RNASEL

A commonly diagnosed cancer, prostate cancer (PrCa), is being regulated by the gene RNASEL previously known as PRCA1 codes for ribonuclease L which is an integral part of interferon regulated system that mediates antiviral and antiproliferative role of the interferons. Both somatic and germline mutations have been implicated to cause prostate cancer. With an array of available Single Nucleotide Polymorphism data on dbSNP this study is designed to sort out functional SNPs in RNASEL by implementing different authentic computational tools such as SIFT, PolyPhen, SNPs&GO, Fathmm, ConSurf, UTRScan, PDBsum, Tm-Align, I-Mutant, and Project HOPE for functional and structural assessment, solvent accessibility, molecular dynamics, and energy minimization study. Among 794 RNASEL SNP entries 124 SNPs were found nonsynonymous from which SIFT predicted 13 nsSNPs as nontolerable whereas PolyPhen-2 predicted 28. SNPs found on the 3′ and 5′ UTR were also assessed. By analyzing six tools having different perspectives an aggregate result was produced where nine nsSNPs were found to be most likely to exert deleterious effect. 3D models of mutated proteins were generated to determine the functional and structural effect of the mutations on ribonuclease L. The initial findings were reinforced by the results from I-Mutant and Project HOPE as these tools predicted significant structural and functional instability of the mutated proteins. Expasy-ProSit tool defined the mutations to be situated in the functional domains of the protein. Considering previous analysis this study revealed a conclusive result deducing the available SNP data on the database by identifying the most damaging three nsSNP rs151296858 (G59S), rs145415894 (A276V), and rs35896902 (R592H). As such studies involving polymorphisms of RNASEL were none to be found, the results of the current study would certainly be helpful in future prospects concerning prostate cancer in males.
The Thioesterase of the Erythromycin-Producing Polyketide Synthase: Influence of Acyl Chain Structure on the Mode of Release of Substrate Analogues from the Acyl Enzyme Intermediates.

The production of genetically engineered polyketides depends critically on thioesterase activity for product release. In vitro studies with the thioesterase from the erythromycin polyketide synthase (PKS) have demonstrated that the ability of this enzyme to act as a universal decoupler is limited, but stereochemical variation is readily tolerated. Synthetic analogues with all four stereochemical configurations of the natural substrate's 2-methyl-3-hydroxy substitution pattern (1-4; X=p-nitrophenoxy) were substrates for the enzyme.
Do the police really protect and serve the public? Police deviance and public cynicism towards the law in Nigeria

This study empirically examines the everyday problem of corrupt policing and other related abuses in Nigeria, and how these deviant behaviours engender public cynicism towards the law. In any democratic society, police officers are expected to be accountable for their actions and inactions. But the perennial problem in Nigeria is that the police are not accountable to anyone. The history of Nigeria policing is littered with accounts of deviance, malevolent attitudes towards the public and failures of the police organization in detecting or disciplining errant officers. Using a sample of 462 participants from a cross-sectional survey, this study examines whether actual or vicarious experiences of police deviance are likely to predict public cynicism towards the law. This current study corroborates previous assertions that the relationship between the police and the public in Nigeria is poor and that police deviance engenders cynicism towards the law. Implications for policymaking and law-abiding behaviour are discussed.
An Edgel-Based Two Step Approach for Simultaneous Matching of Image Sequences

In this paper we report on a new edgel-based matching approach. High performance is reached using the gradient information of textured regions only and by applying a two step approach. The hierarchical iterative procedure provides fast convergence and avoids local minima. The method performs well in terms of accuracy, robustness and speed. Furthermore it allows to match an arbitrary number of oriented images simultaneously.
Cluster Based Channel Model and Performance Analysis for MIMO Satellite Formation Flying Communication Systems

Satellite formation flying is an essential capability for many space missions that allow several closely spaced smaller satellites to be deployed. Depending on mission requirements, the ground receive station may carry several antennas and receive signal from each of the satellites in order to increase spectral efficiency and Quality of Service (QoS). In this paper, we propose an improved cluster based distributed MIMO channel model based on MIMO models for terrestrial communications in the WINNER/3GPP project for satellite formation flying systems. Monte Carlo simulations were also performed to evaluate the performance of formation flying satellite systems with different configurations using the proposed spatial channel model and comparisons were made with the single satellite-single receive station system using capacity ratio and capacity difference as metrics. Our results show the effects of several factors such as type of formation, number of satellites, number of receive antennas, and SNR on capacity for the single satellite and multi-satellite systems.
Switched UAV-UGV Cooperation Scheme for Target Detection

We develop a switched cooperative control scheme, to coordinate groups of ground and aerial vehicles for the purpose of locating a moving target in a given area. We do so by stabilizing the ground group into a guarding formation using a navigation function, and then steering the aerial group along a trajectory that uniformly scans the enclosed regions. The novelty of the approach lays in combining decentralized flocking algorithms with navigation functions for obstacle avoidance, convergence to designated position, and direction control.
Secured Power Aware Routing Protocol (SPARP) for Wireless Sensor Networks

Several wireless sensor network applications ought to decide the intrinsic variance between energy efficient communication and the requirement to attain preferred quality of service (QoS) such as packet delivery ratio, delay and to reduce the power consumption of wireless sensor nodes. Also the intended protocols that are developed aims in providing better QoS with compromising security aspect. In order to address this challenge, we propose the Secured Power Aware Routing Protocol (PARP), which attains application-specified communication delays at low energy cost by dynamically adapting transmission power and routing decisions along with incorporating a novel cryptosystem. Through extensive simulation in NS2 the results prove that the proposed SPARP attains better QoS and reduced power consumption. Cryptool is used to test the novel proposed cryptosystem.
Multiscale Medical Image Fusion in Wavelet Domain

Wavelet transforms have emerged as a powerful tool in image fusion. However, the study and analysis of medical image fusion is still a challenging area of research. Therefore, in this paper, we propose a multiscale fusion of multimodal medical images in wavelet domain. Fusion of medical images has been performed at multiple scales varying from minimum to maximum level using maximum selection rule which provides more flexibility and choice to select the relevant fused images. The experimental analysis of the proposed method has been performed with several sets of medical images. Fusion results have been evaluated subjectively and objectively with existing state-of-the-art fusion methods which include several pyramid- and wavelet-transform-based fusion methods and principal component analysis (PCA) fusion method. The comparative analysis of the fusion results has been performed with edge strength (Q), mutual information (MI), entropy (E), standard deviation (SD), blind structural similarity index metric (BSSIM), spatial frequency (SF), and average gradient (AG) metrics. The combined subjective and objective evaluations of the proposed fusion method at multiple scales showed the effectiveness and goodness of the proposed approach.
Intelligent System to Recognize Human Brain Signals for finding Brain Diseases based on Neural Networks

— Brain signals recognition has been a problem that computers are not efficient at. It is difficult to find the fine variations in the signal because the signals are too lengthy. Today, efficient brain signal recognition is limited to find different brain diseases such as epilepsy, tumor, encephalitis, and sleep disorders; using hardware like Electroencephalogram (EEG) wherein the strokes are directly detected and the brain signals is recognized. But if you want to convert a brain signal document to digital text, we have to extract the EEG signals and then recognize the brain diseases using brain signals. But the problem with this approach is that there are not many algorithms that could efficiently extract signals from a brain. Therefore brain signals recognition using software is still not as efficient as it could be. Fully automated systems to overcome the above problems are proposed. In this paper, we suggest the design of software which could do this job of translating brain signals to digital text data. We propose a new approach using which the problem of recognizing brain signals can be solved. We also provide the implementation details of this software. For the implementation of ours idea, we propose a new Neural Network Architecture, which is a modified version of the conventional Back Propagation Network. The technique adopted by the Back Propagation Network (BPN) used in neural network guided and stimulated me to design this paper. Details regarding the automatic preprocessing that would be essential and the shortcomings are also included in this paper. Our research work will be in classifying EEG with a neural network based intelligent systems.
Automatic generation of hyperlinks between audio and transcript

We present a prototype that enables the generation of hyperlinks between audio and the corresponding transcript. The main issue in generating such hyperlinks is determining common time points in the transcript and the audio (this is also called aligning). The system is speaker independent and can deal with inexact transcripts. It combines inaccurate modules in such a way that the final results are extremely satisfactory.
Flip-Chip-Assembled  $W$-Band CMOS Chip Modules on Ceramic Integrated Passive Device With Transition Compensation for Millimeter-Wave System-in-Package Integration

In this paper, W-band flip-chip-assembled CMOS chip modules with transition compensation are presented, a three-stage amplifier, a balanced amplifier, and a down-converted Gilbert-cell subharmonic mixer are included in the chip set. The flip-chip process on ceramic integrated passive devices (CIPD) with a bump size of 30 μm × 30 μm × 27 m is developed for millimeter-wave applications. Without the flip-chip transition compensation, the frequency of the return loss of each chip is shifted, which deviates from the bare die measurement results. By applying the compensation network in the transition, the dips of the return loss are tuned back closer to the bare die measurement results. Moreover, a W-band amplifier flip-chip-assembled with a CPW-fed Yagi-Uda antenna on a CIPD and a W-band flip-chip-assembled receiver are presented for SiP integration. The effect of dicing edge variation is also included in the flip-chip model to achieve reasonable agreement between simulated and measured scattering parameters. To the best of our knowledge, this is the first demonstration of a CMOS chip set with flip-chip interconnects in the -band for a system-in-package.