Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Cell Failure on Reliable Cross-Point Resistive Memory Design

Resistive random access memory (ReRAM) technology is an emerging candidate for next-generation nonvolatile memory (NVM) architecture due to its simple structure, low programming voltage, fast switching speed, high on/off ratio, excellent scalability, good endurance, and great compatibility with silicon CMOS technology. The most attractive of the characteristics of ReRAM is its cross-point structure, which features a 4F2 cell size. In a cross-point structure, the existence of sneak current and resulting voltage loss due to the wire's resistance might cause read and write failures if not designed properly. In addition, a robust ReRAM design needs to deal with both soft and hard errors. In this article, we summarize mechanisms of both soft and hard errors of ReRAM cells and propose a unified model to characterize different failure behaviors. We quantitatively analyze the impact of cell failure types on the reliability of the cross-point array. We also propose an error-resilient architecture, which avoids unnecessary writes in the hard error detection unit. Assuming constant soft error rate, our approach can extend the lifetime of ReRAM up to 75% over a design without hard error detection and up to 12% over the design with a “write-verify” detection mechanism. Our approach yields greater significant lifetime improvement when considering postcycling retention degradation.
Optimization of fault diagnosis based on the combination of Bayesian Networks and Case-Based Reasoning

Fault diagnosis is one of the most important tasks in fault management. The main objective of the fault management system is to detect and localize failures as soon as they occur to minimize their effects on the network performance and therefore on the service quality perceived by users. In this paper, we present a new hybrid approach that combines Bayesian Networks and Case-Based Reasoning to overcome the usual limits of fault diagnosis techniques and reduce human intervention in this process. The proposed mechanism allows identifying the root cause failure with a finer precision and high reliability while reducing the process computation time and taking into account the network dynamicity.
School Managers, Emotion Management Competencies During Change Management' Scale: Development, Validity And Reliability

Abstract The purpose of this study is to develop a valid and reliable scale in order to determine the competencies of school managers in managing the emotions of teachers during the change process in schools. In this respect, an item pool, based on the literature and consisting of 52 items, was presented to get the experts’ views. The final-form involving 40 items were constituted in line with the recommendations and suggestions and implemented among 312 teachers working in Usak. The construct validity of the scale was tested with exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). In the result of (EFA), “The scale of emotions management competencies in the change process” which consists of 21 items, were appointed to have three factors. In addition to this, it was revealed that the scale explained the 77.11 percent of variance. In the analysis of items, it was revealed that item-total correlations and item distinctiveness were high. (CFA), which was implemented to confirm the construct, demonstrated the high levels of goodness of fit indexes in three- factor construct of the scale. The Cronbach’s Alpha coefficients of the factors and the whole scale construct points that scale is reliable. In line with these findings, it can be concluded that the scale is a valid and reliable tool which can be used to determine the competencies of school managers in managing the emotions in the change process.
Active Network Coding Based High-Throughput Optimizing Routing for Wireless Ad Hoc Networks

Network coding is often applied to routing protocols for wireless ad hoc networks with the target of improving the throughput and other performance. In most research of network coding, much work has been done on multicast or broadcast applications, and few work gives attention to unicast applications. The most recent work is COPE presented in. Nevertheless, in all the existing network coding methods, nodes passively wait for the straightforward opportunities to network coding, but can't exploit the potential but not straightforward opportunities to network coding. Therefore this paper introduces ANCHOR, an active network coding based high-throughput optimizing routing protocol, where every node not only exploits the existing opportunities to network coding, but also actively optimizes the routing for exploiting potential but not straightforward opportunities to network coding. We implement ANCHOR in Glomosim simulator, and compare the throughput of ANCHOR, COPE and DSR against different parameters. The extensive results show that ANCHOR outperforms COPE and DSR in many scenarios.
Adaptation techniques for ubiquitous Internet multimedia

We identify the importance of adaptation for the ubiquitous access to Internet multimedia content. The variety of media types combined with the diversity of Internet connection characteristics raises momentous challenges to the achievement of this goal. With adaptation, the characteristics of various media can be adjusted to better match those of the network path and the end device. As a result, adaptive streams enjoy superior robustness and provide substantially better presentation quality than traditional, non-adaptive ones, especially in variable, capacity-limited environments. We examine several important factors that influence the design and optimization of the adaptation architecture. First, the location of the adaptation mechanism on the end-to-end path must be chosen. Second, the adaptation policy, i.e., the agility in adapting to variations in network path performance, must be specified. Third, the adaptation mechanism needs to be aware of the value of the perceptual quality that the different representations of each medium and the necessary resources to sustain it. Finally, we emphasize the role of supporting mechanisms in enhancing the adaptation process, namely, prioritization, admission control and hand-off notifications. Based on the aforementioned criteria, we classify existing research approaches and present some of them as case studies. We also describe current commercial solutions and, finally, we discuss future trends in application adaptation in conjunction with recent developments towards wireless access to the Internet. Copyright © 2001 John Wiley & Sons, Ltd.
An Efficient Authenticated Group Key Agreement Protocol

Authenticated group key agreement is an important cryptographic mechanism underlying many collaborative and distributed applications. Some identity-based authenticated group key agreement schemes are proposed, however most of these protocols are vulnerable to insider attacks, while the other protocols are not efficient in communication. In this paper a new authenticated group key agreement protocol is proposed based on a modified identity-based cryptography infrastructure with new system setup and key extraction algorithms. The main feature of this protocol is that it needs only one round, which is optimal in terms of communication complexity; meanwhile the protocol is secure against insider attacks such as impersonation attacks and other known attacks.
Accuracy of urinary human papillomavirus testing for presence of cervical HPV: systematic review and meta-analysis

Objective To determine the accuracy of testing for human papillomavirus (HPV) DNA in urine in detecting cervical HPV in sexually active women. Design Systematic review and meta-analysis. Data sources Searches of electronic databases from inception until December 2013, checks of reference lists, manual searches of recent issues of relevant journals, and contact with experts. Eligibility criteria Test accuracy studies in sexually active women that compared detection of urine HPV DNA with detection of cervical HPV DNA. Data extraction and synthesis Data relating to patient characteristics, study context, risk of bias, and test accuracy. 2×2 tables were constructed and synthesised by bivariate mixed effects meta-analysis. Results 16 articles reporting on 14 studies (1443 women) were eligible for meta-analysis. Most used commercial polymerase chain reaction methods on first void urine samples. Urine detection of any HPV had a pooled sensitivity of 87% (95% confidence interval 78% to 92%) and specificity of 94% (95% confidence interval 82% to 98%). Urine detection of high risk HPV had a pooled sensitivity of 77% (68% to 84%) and specificity of 88% (58% to 97%). Urine detection of HPV 16 and 18 had a pooled sensitivity of 73% (56% to 86%) and specificity of 98% (91% to 100%). Metaregression revealed an increase in sensitivity when urine samples were collected as first void compared with random or midstream (P=0.004). Limitations The major limitations of this review are the lack of a strictly uniform method for the detection of HPV in urine and the variation in accuracy between individual studies. Conclusions Testing urine for HPV seems to have good accuracy for the detection of cervical HPV, and testing first void urine samples is more accurate than random or midstream sampling. When cervical HPV detection is considered difficult in particular subgroups, urine testing should be regarded as an acceptable alternative.
Information-Theoretic Analysis of Privacy Protection for Noisy Identification Based on Soft Fingerprinting

Identification of contents or objects based on some data that are stored/distributed in public domain is required in various applications. At the same time, these data should not reveal any information about original content or object that may be missused in terms of privacy leakage. We consider a privacy protection strategy based on reliable components of data and investigate the performance of this scheme with respect to achievable identi¯cation rate and privacy leak. The data stored/distributed in the public domain are binary, while the encoder and the decoder operate with real data. The advocated strategy is referred to as soft fingerprinting.
Analysing the Problem and Main Approaches for Ontology Population

Knowledge systems are a suitable computational approach to solve complex problems and to provide decision support. Ontologies are an approach for knowledge representation and Ontology Population looks for instantiating the constituent elements of an ontology, like properties and non-taxonomic relationships. Manual population by domain experts and knowledge engineers is an expensive and time consuming task. Thus, automatic or semi-automatic approaches are needed. This paper discusses the problem of Automatic Ontology Population and proposes a generic process specifying its phases and what kind of techniques can be used to perform the activities of each phase. Some techniques representing the state of the art of this field are also described along with the solutions they adopt for each phase of the AOP process with their advantages and limitations. This work is part of HERMES, a Brazil/Portugal research cooperation project looking for techniques and tools for automating the process of ontology learning and population.
Aerobic Exercise during Pregnancy and Presence of Fetal-Maternal Heart Rate Synchronization

It has been shown that short-term direct interaction between maternal and fetal heart rates may take place and that this interaction is affected by the rate of maternal respiration. The aim of this study was to determine the effect of maternal aerobic exercise during pregnancy on the occurrence of fetal-maternal heart rate synchronization. Methods In 40 pregnant women at the 36th week of gestation, 21 of whom exercised regularly, we acquired 18 min. RR interval time series obtained simultaneously in the mothers and their fetuses from magnetocardiographic recordings. The time series of the two groups were examined with respect to their heart rate variability, the maternal respiratory rate and the presence of synchronization epochs as determined on the basis of synchrograms. Surrogate data were used to assess whether the occurrence of synchronization was due to chance. Results In the original data, we found synchronization occurred less often in pregnancies in which the mothers had exercised regularly. These subjects also displayed higher combined fetal-maternal heart rate variability and lower maternal respiratory rates. Analysis of the surrogate data showed shorter epochs of synchronization and a lack of the phase coordination found between maternal and fetal beat timing in the original data. Conclusion The results suggest that fetal-maternal heart rate coupling is present but generally weak. Maternal exercise has a damping effect on its occurrence, most likely due to an increase in beat-to-beat differences, higher vagal tone and slower breathing rates.
The Black Hole Mass of NGC 4151: Comparison of Reverberation Mapping and Stellar Dynamical Measurements

We present a stellar dynamical estimate of the black hole (BH) mass in the Seyfert 1 galaxy, NGC 4151. We analyze ground-based spectroscopy as well as imaging data from the ground and space, and we construct three-integral axisymmetric models in order to constrain the BH mass and mass-to-light ratio. The dynamical models depend on the assumed inclination of the kinematic symmetry axis of the stellar bulge. In the case in which the bulge is assumed to be viewed edge-on, the kinematical data give only an upper limit to the mass of the BH, of ~4 × 107 M☉ (1 σ). If the bulge kinematic axis is assumed to have the same inclination as the symmetry axis of the large-scale galaxy disk (i.e., 23° relative to the line of sight), a best-fit dynamical mass between 4 and 5 × 107 M☉ is obtained. However, because of the poor quality of the fit when the bulge is assumed to be inclined (as determined by the noisiness of the χ2 surface and its minimum value) and because we lack spectroscopic data that clearly resolves the BH sphere of influence, we consider our measurements to be tentative estimates of the dynamical BH mass. With this preliminary result, NGC 4151 is now among the small sample of galaxies in which the BH mass has been constrained from two independent techniques, and the mass values we find for both bulge inclinations are in reasonable agreement with the recent estimate from reverberation mapping (4.57 × 107 M☉) published by Bentz et al.
Macho, mobile and resilient? How workers with impairments are doubly disabled in project-based film and television work

Inequalities in the creative industries are known to be persistent and systemic. The model of production in UK film and television (UKF&TV) is argued to exclude on the basis of gender, race and class. This article considers a social category that has been overlooked in these debates: disability. It argues that workers with impairments are ‘doubly disabled’ – in both the labour markets and labour processes of UKF&TV. It concludes that disability cannot simply be incorporated in an additive way in order to understand the exclusion of these workers, but that they face qualitatively different sources of disadvantage compared with other minorities in UKF&TV workplaces. This has negative implications for workers with impairments in other labour markets, as project and network-based freelance work, a contributor to disadvantage, is seen as both increasingly normative and paradigmatic.
Evaluation of Automatic Text Summarization Methods Based on Rhetorical Structure Theory

Motivated by governmental, commercial and academic interests, automatic text summarization area has experienced an increasing number of researches and products, which led to a countless number of summarization methods. In this paper, we present a comprehensive comparative evaluation of the main automatic text summarization methods based on rhetorical structure theory (RST), claimed to be among the best ones. We also propose new methods and compare our results to an extractive summarizer, which belongs to a summarization paradigm with severe limitations. To the best of our knowledge, most of our results are new in the area and reveal very interesting conclusions. The simplest RST-based method is among the best ones, although all of them present comparable results. We show that all RST-based methods overcome the extractive summarizer and that hybrid methods produce worse summaries. finally, we verify that Mann and Thompson strong assumption in summarization and RST research area is not helpful in the way previously imagined.
Improving Authoritative Sources in a Hyperlinked Environment via Similarity Weighting Or , “ How to get better search results on the Web ”

Recent literature demonstrates that the network structure of a hyperlink environment can serve as an effective source for inferring the importance of content in documents. One such connectivity-analysis algorithm, HITS, determines document importance based upon the hyperlink structure of the Web. In order to compensate for the problems of a pure connectivity-analysis algorithm, we develop and test an algorithm based upon HITS that also considers document content. We investigate whether incorporating the similarity of documents joined by links modifies how the importance of documents is determined. While using similarity does not always compensate for existing problems in pure connectivityanalysis algorithms, similarity provides additional insight into why certain problems exist. The results also demonstrate that importance in our algorithm is often biased by the structure and layout of documents.
Poverty and Children's Schooling in Urban and Rural Senegal

This paper presents findings of an investigation into the effects of living-standards and relative poverty on children's schooling in urban and rural areas of Senegal. To measure living standards, we apply a multiple-indicator, multiple-cause (MIMIC) factor-analytic model to a set of proxy variables collected in the 2000 Multiple Indicator Cluster Survey and extract an estimate of the relative standard of living for each household. Using this estimate, we find that in Senegal's urban areas, living standards exert substantial influence on three measures of schooling: Whether a child has ever attended school; whether he or she has completed at least four grades of primary school; and whether he or she is currently enrolled. In rural areas of Senegal, however, the effects are weaker and achieve statistical significance only for the wealthiest fifth of rural households. Two educational inequalities persist with living standards held constant. First, the advantages enjoyed by urban families in Senegal remain considerable: Even the poorest fifth of urban children are more likely than rural children to have attended school, to have completed four years or more of primary education, and to be currently enrolled. Second, gender gaps in schooling are pervasive and are only modestly influenced by standards of living. In both urban and rural areas of Senegal, girls suffer from marked disadvantages relative to boys in all three measures of schooling. In wealthier urban households, girlsi? ½ disadvantages are smaller, but not completely eliminated. Furthermore, no systematic reduction in female disadvantage is apparent in rural Senegal, even in the uppermost stratum of households. To judge from these findings, in Senegal income growth alone is unlikely to close the schooling gap between urban and rural areas or between boys and girls.
Application of remanufacturing principles to an automotive engine valve component

With a motto to introduce concept of remanufacturing in a component manufacturing industry against the belief that remanufacturing is not implementable in such industries, an attempt has been made to modify a component design such that the product is transformedinto assembly of parts and thus facilitating remanufacturing. A case study was conducted in an Indian automotive engine valve manufacturing organisation. The reengineering study identified the potential of using an alternative design to facilitate remanufacturing of automotive engine valves. Further sustainable analysis of optimised design also has been conducted.
A Robust Passage Retrieval Algorithm for Video Question Answering

In this paper, we present a robust passage retrieval algorithm to extend the conventional text question answering (Q/A) to videos. Users interact with our videoQ/A system through natural language queries, while the top-ranked passage fragments with associated video clips are returned as answers. We compare our method with five of the high-performance ranking algorithms that are portable to different languages and domains. The experiments were evaluated with 75.3 h of Chinese videos and 253 questions. The experimental results showed that our method outperformed the second best retrieval model (language models) in relatively 1.43% in mean reciprocal rank (MRR) score and 11.36% when employing a Chinese word segmentation tool. By adopting the initial retrieval results from the retrieval models, our method yields an improvement of at least 5.94% improvement in MRR score. This makes it very attractive for the Asia-like languages since the use of a well-developed word tokenizer is unnecessary.
A Parallel Search Strategy Based on Sparse Representation for Infrared Target Tracking

A parallel search strategy based on sparse representation (PS-L1 tracker) is proposed in the particle filter framework. To obtain the weights of state particles, target templates are represented linearly with the dictionary of target candidates. Sparse constraints on the coefficient guarantee that only true target candidates can be selected, and the nonnegative entries denote the associate weights of efficient target states. Then the optimal target state can be estimated by the linear combination of above weighted states. In this way, efficient target states are selected simultaneously from all the particles, which we call a parallel search strategy. Experimental results demonstrate excellent performance of the proposed method on challenging infrared images.
An Energy-Efficient Nonvolatile In-Memory Computing Architecture for Extreme Learning Machine by Domain-Wall Nanowire Devices

The data-oriented applications have introduced increased demands on memory capacity and bandwidth, which raises the need to rethink the architecture of the current computing platforms. The logic-in-memory architecture is highly promising as future logic-memory integration paradigm for high throughput data-driven applications. From memory technology aspect, as one recently introduced nonvolatile memory device, domain-wall nanowire (or race-track) not only shows potential as future power efficient memory, but also computing capacity by its unique physics of spintronics. This paper explores a novel distributed in-memory computing architecture where most logic functions are executed within the memory, which significantly alleviates the bandwidth congestion issue and improves the energy efficiency. The proposed distributed in-memory computing architecture is purely built by domain-wall nanowire, i.e., both memory and logic are implemented by domain-wall nanowire devices. As a case study, neural network-based image resolution enhancement algorithm, called DW-NN, is examined within the proposed architecture. We show that all operations involved in machine learning on neural network can be mapped to a logic-in-memory architecture by nonvolatile domain-wall nanowire. Domain-wall nanowire-based logic is customized for in machine learning within image data storage. As such, both neural network training and processing can be performed locally within the memory. The experimental results show that the domain-wall memory can reduce 92% leakage power and 16% dynamic power compared to main memory implemented by DRAM; and domain-wall logic can reduce 31% both dynamic and 65% leakage power under the similar performance compared to CMOS transistor-based logic. And system throughput in DW-NN is improved by 11.6x and the energy efficiency is improved by 56x when compared to conventional image processing system.