Miracle-dz/UniFAR-FTUs huggingface dataset:
Failure and fault analysis for software debugging

Most studies of software failures and faults have done little more than classify failures and faults collected from long-term projects. The authors propose a model to analyze failures and faults for debugging purposes. In the model, they define "failure modes" and "failure types" to identify the existence of program failures and the nature of the program failures, respectively. The goal of this research is to achieve a systematic process model to localize faults in debugging. They first examine properties of the proposed model from a theoretical point of view, then use the trityp program as a simple example to illustrate the possible usage of the model for debugging. Further study of the failure mode, a pilot experiment of applying the proposed model, and a way to employ heuristics according to different situations for fault localization are areas of future work.
Design of CMOS programmable output binary and fibonacci switched capacitor step-down DC-DC converter

This paper describes the CMOS implementation of an open-loop variable output voltage switched capacitor step-down DC-DC converter with a large number of target voltages. The number of target voltages generated using n-flying capacitors are of the order of 2n. A switch selection scheme is presented that optimizes silicon area. Expressions for equivalent series resistance Req, conduction, switching power loss and efficiency are obtained and compared with the spice simulation results. The Digital Switch Controller is designed to switch between various target voltages and simulated in Cadence Analog-Mixed Signal flow. The 3/4 step-down converter circuit is described and analysed by varying switching frequency and load for different values of bottom plate parasitic capacitance. The optimum value of switching frequency and switch sizes is obtained for a switched capacitor converter. An efficiency of about 78.4% is achieved with 5% bottom plate parasitic capacitance for a load current of 1.35 mA and input voltage of 1.8 V at 20 MHz of switching frequency.
Acquisition of bilingual MT lexicons from OCRed dictionaries

This paper describes an approach to analyzing the lexical structure of OCRed bilingual dictionaries to construct resources suited for machine translation of low-density languages, where online resources are limited. A rule-based, an HMM-based, and a post-processed HMM-based method are used for rapid construction of MT lexicons based on systematic structural clues provided in the original dictionary. We evaluate the effectiveness of our techniques, concluding that: (1) the rule-based method performs better with dictionaries where the font is not an important distinguishing feature for determining information types; (2) the post-processed stochastic method improves the results of the stochastic method for phrasal entries; and (3) Our resulting bilingual lexicons are comprehensive enough to provide the basis for reasonable translation results when compared to human translations.
Proteomics for the Discovery of Biomarkers and Diagnosis of Diseases

Introduction Over the past few years a significant amount of data pertaining to the diagnosis of human diseases has been generated with the help of mRNA (cDNA) microarrays. They have been responsible for identifying new disease subtypes that would not have been possible using conventional techniques. As a result, the need for new molecular based classifications of some types of cancers (Alizadeh, Eisen et al. 2000; Sorlie, Perou et al. 2001) have been highlighted by these studies. If DNA microarrays are so good, do we need proteomics to diagnose diseases, and if so how will it be better than DNA array expression profiling? Before this question is answered, it is instructive to consider what types of changes take place in the proteome with different diseases. In cancers, one would expect an altered expression of proteins responsible for signal transduction processes in the cell. In fact, in many instances the protein products of proto-oncogenes are involved in signal transduction (Alaiya, Franzen et al. 2000) and alterations in these genes result in uncontrolled cellular signaling. Over expression and post-translational modifications of several oncogene products have been detected in transformed liver cells (Sanchez, Wirth et al. 1997). Additionally, cancer has been associated with altered glycosylation of many proteins (Taylor-Papadimitriou and Epenetos 1994). Cardiovascular disease, the leading cause of death in the United States, is most often associated with atherosclerosis. Studies on the molecular basis of atherosclerosis have led to the identification of a number of molecules that may play a critical role in the development of atherosclerotic lesions. A member of the immunoglobulin gene superfamily, intercellular cell adhesion molecule 1 (ICAM-1) has recently been shown to be associated with this disease in humans (Ballantyne and Entman 2002). ICAM-1 is a cell-surface glycoprotein capable of eliciting bidirectional signals that activate signaling pathways in leukocytes, and endothelial, and smooth muscle cells. These molecules can be measured quantitatively in plasma. In the Physicians' Health Study, increased levels of soluble ICAM-1 were noted in individuals who subsequently developed symptomatic arterial disease (Pradhan, Rifai et al. 2002). Proteolytic cleavage may play a role in the altered abundance of ICAM-1 (Champagne, Tremblay et al. 1998). In studies of dilated cardiomyopathy, which results in heart failure, decreased protein abundance of cytoskeletal proteins and proteins associated with mitochondria and energy metabolism have been noted (Banks, Dunn et al. 2000). Also noted was a seven-fold increase in the enzyme ubiquitin C-terminal hydrolase …
Saving fractional bits: A practical entropy efficient code for fair die rolls

We give an implementation of an algorithm that uses fair coin flips to simulate fair rolls of an $n$-sided die. A register plays the role of an entropy pool and holds entropy that is generated as a by-product during each die roll and that is usually discarded. The entropy stored in this register is completely reused during the next rolls. Consequently, we can achieve an almost negligible loss of entropy per roll. The algorithm allows to change the number of sides of the die in each round. We prove that the entropy loss is monotone decreasing with increasing entropy pool size (register length).
Addressing Administrative Needs for Successful Inclusion of Students with Disabilities.

As inclusion increasingly becomes the accepted model for meeting the needs of students with disabilities, administrator involvement becomes critical because the attitudes of school personnel and students toward inclusion frequently mirror those of the administrator. In rural areas, the building administrator is often isolated from other school district administrators and must make decisions based on available information. This paper provides guidelines to assist teachers and parents in furnishing the information that principals need to support successful changes toward inclusion. The administrator must be informed of, ond actively involved in, tho planning and implementation of the following areas: (1) number of students to be included; (2) impact on students with and without disabilities; (3) specific needs of students with disabilities; (4) strategies and supports needed for successful inclusion; (5) roles of general and special education teachers, administrators, and paraprofessionals; (6) training needs of all school staff; (7) parent/caregiver involvement; (8) potential costs and funding sources; and (9) potential resource personnel to assist with training and implementation. The key to success of any inclusionary program is open and honest communication between all parties involved. The building administrator can help guarantee success, but can also, perhaps unwittingly, be a hindrance to the process. If the building administrator is involved and informed from the beginning, the change to inclusive educational programs has a much higher chance of success. (ID) *********************************************************************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * *********************************************************************** U. & DEPARTMENT OF EDUCATION Office of Educational Resesrch and improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) "(This document Ms Mn reproduced as received from the porton or organization originating it O Minor changes have men made to improve reproduction Quality Points ot vet* Of opinions stated in this document do not ileC111$4.11rily represent official OERI position or policy PERMISSIONTO REPRODUCE AND DISSEMNATETHISINWERML HASBEENGRANTEDSY
VERSION hep-th RU-06-08 , SCIPP-06-07 II ∞ Factors and M-theory in Asymptotically Flat Space

I discuss a formulation of M-theory at null infinity, which is based on general principles of holographic space-time, and is manifestly covariant. The construction utilizes a certain Type II Von Neumann algebra, which provides a kinematic framework, alternative to Fock Space, for describing the scattering states of eleven dimensional asymptotically flat M-theory. The construction provides a greatly clarified statement of the connection between SUSY and holography. I make preliminary remarks about dynamical equations for the S-matrix, and compactifications.
Product and Price Competition with Satiation Effects

Consumers become satiated with a product when purchasing too much too quickly. How much is too much and how quickly is too quickly depends on the characteristics of the product relative to the time interval between consumption periods. Knowing that, consumers allocate their budget to products that generate less satiation effects. Retailers should then choose to sell products that induce minimal satiation, but usually this is operationally more costly. To study this trade-off, we provide an analytical model based on utility theory that relates customer consumption to price and satiation, in the context of multiple competing retailers. We determine the purchasing pattern over time and provide an explicit expression to determine the consumption level in steady state. We derive market shares and show that they take the form of an attraction model in which the attractiveness depends on price and product satiation. We use this to analyze the competition between firms that maximize long-term average profit. We characterize the equilibrium under three scenarios: (i) price-only competition, (ii) product-only competition, and (iii) price and product competition. The results reveal the interplay between a key marketing lever (price) and the firm's ability to offer products that generate less satiation. In particular, we show that when a firm becomes more efficient at reducing satiation, its competitor may benefit if competition is on product only, but not if it is on price and product. We also find that when satiation effects are not managed, a firm's profit may be significantly reduced while a strategic competitor can largely benefit. This paper was accepted by Yossi Aviv, operations management.
Improving User Experience via Motion Sensors in an Ambient Intelligence Scenario

Ambient Intelligence (AmI) is a new paradigm in Artificial Intelligence that aims at exploiting the information about the environment state in order to adapt it to the user preferences. AmI systems are usually based on several cheap and unobtrusive sensing devices that allow for continuous monitoring in different scenarios. In this work we present a gesture recognition module for the management of an office environment using a motion sensor device, namely Microsoft Kinect, as the primary interface between the user and the AmI system. The proposed gesture recognition method is based on both RGB and depth information for detecting the hand of the user and a fuzzy rule for determining the state of the detected hand. The shape of the hand is interpreted as one of the basic symbols of a grammar expressing a set of commands for the actuators of the AmI system. In order to maintain a high level of pervasiveness, the Kinect sensor is connected to a miniature computer capable of real-time processing.
Non-Intrusive Performance Profiling for Entire Software Stacks Based on the Flow Reconstruction Principle

Understanding the performance behavior of distributed server stacks at scale is non-trivial. The servicing of just a single request can trigger numerous sub-requests across heterogeneous software components; and many similar requests are serviced concurrently and in parallel. When a user experiences poor performance, it is extremely difficult to identify the root cause, as well as the software components and machines that are the culprits. This paper describes Stitch, a non-intrusive tool capable of profiling the performance of an entire distributed software stack solely using the unstructured logs output by heterogeneous software components. Stitch is substantially different from all prior related tools in that it is capable of constructing a system model of an entire software stack without building any domain knowledge into Stitch. Instead, it automatically reconstructs the extensive domain knowledge of the programmers who wrote the code; it does this by relying on the Flow Reconstruction Principle which states that programmers log events such that one can reliably reconstruct the execution flow a posteriori.
FPGA implementation of trellis coded modulation decode on SDR communication system

This study investigates the constellation mapping of the 3-bit soft-decision Viterbi decoder and the decoding system of the Viterbi decoder for trellis-coded modulation (TCM) decoding. By referring to the IESS-310 TCM standard coding scheme, LabVIEW FPGA is employed to design the corresponding decoding circuits of the 3-bit soft-decision TCM Viterbi decoder in a software-defined radio (SDR) system [1]. Finally, the study employs TCM coding and decoding circuits designed by using LabVIEW FPGA to simulate the error rate curve in the AWGN channel. The simulation results surpass the bit error rate (BER) curves of QPSK and 8PSK and the IESS-310 standard.
Adipose Tissue in Obesity-Related Inflammation and Insulin Resistance: Cells, Cytokines, and Chemokines

Adipose tissue is a complex organ that comprises a wide range of cell types with diverse energy storage, metabolic regulation, and neuroendocrine and immune functions. Because it contains various immune cells, either adaptive (B and T lymphocytes; such as regulatory T cells) or innate (mostly macrophages and, more recently identified, myeloid-derived suppressor cells), the adipose tissue is now considered as a bona fide immune organ, at the cross-road between metabolism and immunity. Adipose tissue disorders, such as those encountered in obesity and lipodystrophy, cause alterations to adipose tissue distribution and function with broad effects on cytokine, chemokine, and hormone expression, on lipid storage, and on the composition of adipose-resident immune cell populations. The resulting changes appear to induce profound consequences for basal systemic inflammation and insulin sensitivity. The purpose of this review is to synthesize the current literature on adipose cell composition remodeling in obesity, which shows how adipose-resident immune cells regulate inflammation and insulin resistance—notably through cytokine and chemokine secretion—and highlights major research questions in the field.
OPTIMIZING EXERCISE SELECTION FOR POWER DEVELOPMENT IN ATHLETES USING VELOCITY-BASED TRAINING

The purpose of this study was to determine which lift and velocity range provide the highest levels of power and force production. 7 highly trained strength professionals performed 3 sets of paired powerlifting exercises: deadlift (DL) and back squat (SQ), power clean (PC) and hang clean (HC), and power clean (PC) and clean pull (CP). Velocity was also controlled for the lifts. Velocity ranges, 0.5-0.75 m/s, 0.75-1.0 m/s, and 1.0-1.3 m/s, were used. A 2 x 3 ANOVA with post-hoc test investigated the data. Lift choice mattered for average power, peak power, and force when controlling the velocity of movement.
Expanding Wallets and Waistlines: The Impact of Family Income on the BMI of Women and Men Eligible for the Earned Income Tax Credit

The rising rate of obesity has reached epidemic proportions and is now one of the most serious public health challenges facing the US. However, the underlying causes for this increase are unclear. This paper examines the effect of family income changes on body mass index (BMI) and obesity using data from the National Longitudinal Survey of Youth 1979 cohort. It does so by using exogenous variation in family income in a sample of low-income women and men. This exogenous variation is obtained from the correlation of their family income with the generosity of state and federal Earned Income Tax Credit (EITC) program benefits. Income is found to significantly raise the BMI and probability of being obese for women with EITC-eligible earnings, and have no appreciable effect for men with EITC-eligible earnings. The results imply that the increase in real family income from 1990 to 2002 explains between 10 and 21% of the increase in sample women's BMI and between 23 and 29% of their increased obesity prevalence.
A Novel Two-Step Approach for the Super-resolution Reconstruction of Video Sequences

In this paper, we propose a two-step approach for the super-resolution reconstruction of video sequences based on the degraded model. Firstly we use the sparse principal component analysis and the linear minimum mean square-error estimation method to remove the noises from the degraded video sequences. Secondly we adopt the Newton-Thiele's vector valued rational interpolation which is one of the nonlinear interpolation methods to magnify the results of the previous step. Our method is effective not only for gray video sequences, but also for color video sequences. Experimental results on a series of video sequences demonstrate that our method achieves better visual effects than those presented in [11] and [16], especially in details.
Low power enhancements for parallel algorithms

In this paper we present a general approach for reducing switching activity on the algorithmic level. We concentrate on iterative algorithms that are suitable for an implementation on parallel processor arrays. The reduction is substantially reached by avoiding operations that hardly contribute to the convergence of the implemented algorithm. Our general approach is exemplified on the implementation of a specific algorithm, i.e. the eigenvalue decomposition (EVD) of a real symmetric matrix.
The impact of vendor customizations on android security

The smartphone market has grown explosively in recent years, as more and more consumers are attracted to the sensor-studded multipurpose devices. Android is particularly ascendant; as an open platform, smartphone manufacturers are free to extend and modify it, allowing them to differentiate themselves from their competitors. However, vendor customizations will inherently impact overall Android security and such impact is still largely unknown. In this paper, we analyze ten representative stock Android images from five popular smartphone vendors (with two models from each vendor). Our goal is to assess the extent of security issues that may be introduced from vendor customizations and further determine how the situation is evolving over time. In particular, we take a three-stage process: First, given a smartphone's stock image, we perform provenance analysis to classify each app in the image into three categories: apps originating from the AOSP, apps customized or written by the vendor, and third-party apps that are simply bundled into the stock image. Such provenance analysis allows for proper attribution of detected security issues in the examined Android images. Second, we analyze permission usages of pre-loaded apps to identify overprivileged ones that unnecessarily request more Android permissions than they actually use. Finally, in vulnerability analysis, we detect buggy pre-loaded apps that can be exploited to mount permission re-delegation attacks or leak private information. Our evaluation results are worrisome: vendor customizations are significant on stock Android devices and on the whole responsible for the bulk of the security problems we detected in each device. Specifically, our results show that on average 85.78% of all pre-loaded apps in examined stock images are overprivileged with a majority of them directly from vendor customizations. In addition, 64.71% to 85.00% of vulnerabilities we detected in examined images from every vendor (except for Sony) arose from vendor customizations. In general, this pattern held over time -- newer smartphones, we found, are not necessarily more secure than older ones.
Phase Synchronization Analysis of 14-Channel LFPs in the Anterior Cingulate Cortex of Rats Under Fear Condition via Equal-Time Correlation Matrix

The aim of this study was to investigate phase synchronization of 14-channel LFPs via equal-time correlation matrix under fear conditioning. 14-channel data were recorded at anterior cingulate cortex (ACC) of rats by implicated microelectrode array, including pre-training and testing. Then low-pass filtered (fc=300Hz) to obtain LFP. Temporal phase were acquired via Hilbert Transform, phase synchronization was assessed via equal-time correlation matrix Eigenvalues of matrix were estimated and normalized and principal components were calculated by lambda i/sum(lambda i) times 100%, selected as indicants of LFP phase synchronization. Results were that lambda1 took a (67.132 plusmn 7.995 percent) percent in sum of eigenvalues was the principal component. Value of normalized lambda1 was lower in pre-training and changes to stimulation was not formed while in testing it increased in 0.2s after a tone stimulation, indicating that fear memory had been built up and a causally relation to the increasing synchronization was set up. These results supported that memory of pre-training and testing are based on separate neural patterns, and LFPs in ACC encoded rat's neural activity of fear condition. The effect on measuring neural activity via equal-time correlation matrix was proved.
Wavelength converters in dynamically-reconfigurable WDM networks

In simple wavelength-division multiplexed (WDM) networks, a connection must be established along a route using a common wavelength on all of the links along the route. This constraint may be removed by the introduction of wavelength converters, which are devices which take the data modulated on an input wavelength and transfer it to a different output wavelength. Wavelength converters thus improve network blocking performance. However, the introduction of wavelength converters into WDM cross-connects increases the hardware cost and complexity. Thus, it is important to establish precisely what advantages wavelength converters offer WDM networks. There has been considerable interest in the literature in the performance improvements offered by the introduction of wavelength converters into dynamically-reconfigurable WDM networks. This article provides a review of the conclusions drawn from these investigations. The performance improvements offered by wavelength converters depend on a number of factors, including network topology and size, the number of wavelengths, and the routing and wavelength assignment algorithms used. We discuss these factors here. However, it has been shown that wavelength converters offer only modest performance improvements in many networks. We also consider networks with limited wavelength conversion, in which the set of allowable conversions at a network node is constrained by having limited numbers of wavelength converters, or by using non-ideal wavelength converters. Limited wavelength conversion has been shown to provide performance which is often close to that achieved with ideal wavelength conversion in networks with tunable transmitters and receivers.