Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying Implicit Architectural Dependencies Using Measures of Source Code Change Waves

The principles of Agile software development are increasingly used in large software development projects, e.g. using Scrum of Scrums or combining Agile and Lean development methods. When large software products are developed by self-organized, usually feature-oriented teams, there is a risk that architectural dependencies between software components become uncontrolled. In particular there is a risk that the prescriptive architecture models in form of diagrams are outdated and implicit architectural dependencies may become more frequent than the explicit ones. In this paper we present a method for automated discovery of potential dependencies between software components based on analyzing revision history of software repositories. The result of this method is a map of implicit dependencies which is used by architects in decisions on the evolution of the architecture. The software architects can assess the validity of the dependencies and can prevent unwanted component couplings and design erosion hence minimizing the risk of post-release quality problems. Our method was evaluated in a case study at one large product at Saab Electronic Defense Systems (Saab EDS) and one large software product at Ericsson AB.
Framework for Evaluation and Comparison of Primality Testing Algorithms

Nowadays, public-key cryptography is widely used to ensure data protection (privacy, integrity, authentication). Public-key algorithms contain, as an essential part of their construction, the usage of prime numbers and of large composite numbers, which have prime factors. Because of this, the security of these algorithms such as RSA (Rivest-Shamir-Adelman) depend on the difficulty to factorize the public keys. For many centuries, mathematicians have been fascinated by the subject of prime numbers, have studied their proprieties and have focused on developing several theories. Many primality tests, deterministic and probabilistic, were proposed to determine whether a number is prime or not. In this paper, we describe the implementation and performance of several primality tests, in order to determine which is more efficient: Fermat's test, Miller-Rabin test, Solovay-Strassen test, Agrawal-Kayal-Saxena (AKS) test, Lucas-Lehmer test, Baillie-PWS test, Pepin's test, Lucas-Lehmer-Riesel (LLR) test, Proth's theorem, Quadratic Frobenius test, Adleman-Pomerance-Rumley (APR) test, Lucas test or Pocklington test. The tests were implemented using . NET framework (C#) and the performance was determined based on input numbers of various sizes and on the type of the primality test (deterministic/probabilistic). These algorithms were also analyzed taking into account their ability to correctly determine the primality of a given number.
The Services Composition Algorithm in Incomplete Visible and Dynamic Environment

As the increasing of the type and number for web services, how to effectively deal with composition service problem in transparent and dynamic environment has become a hot issue for researchers. Considering most of the current works for service composition are based on the static and known topology, this paper puts forward a new service composition algorithm—NVDSCM, which show great interest for service composition in dynamic and partially-known environment. By dynamically and automatically monitoring the connection state with neighbors, NVDSCM can effectively reduce the number of duplicated and unnecessary composition request. Furthermore, it applies local-repair strategy to maintain the connection relation with neighbors for each web services, which is very important to improve algorithm efficiency for large scope. Based on the analysis of the experiment, NVDSCM can effectively solve the problem of service composition in partially-known and dynamic environment, including better composition path quality and more stability as the change of scope size.
A Novel Feature Selection Method for Affective Recognition Based on Pulse Signal

For the problem of affective recognition from pulse signal, a new feature selection method which combines correlation analysis with max-min ant colony algorithm is proposed in this paper, and stable feature subsets with good performance are found to construct affective recognition model. Firstly, sequential backward selection (SBS) is used for sorting of the original features. Secondly, the linear correlation coefficient is adopted to compute the correlation degrees between the features and features with high correlation degrees are removed through the result of sorting. Finally, max-min ant colony algorithm is used for feature selection, which searches for an optimal subset based on the compact feature subset, and six emotions (happiness, surprise, disgust, grief, anger and fear) are recognized by means of Fisher classifier. The experimental results show that the method can construct effective affective recognition model through stable and effective feature subsets chosen from original features.
Fast Mining of Interesting Phrases from Subsets of Text Corpora

We address the problem of mining interesting phrases from subsets of a text corpus where the subset is specied using a set of features such as keywords that form a query. Previous algorithms for the problem have proposed solutions that involve sifting through a phrase dictionary based index or a document-based index where the solution is linear in either the phrase dictionary size or the size of the document subset. We propose the usage of an independence assumption between query keywords given the top correlated phrases, wherein the pre-processing could be reduced to discovering phrases from among the top phrases per each feature in the query. We then outline an indexing mechanism where per-keyword phrase lists are stored either in disk or memory, so that popular aggregation algorithms such as No Random Access and Sort-merge Join may be adapted to do the scoring at real-time to identify the top interesting phrases. Though such an approach is expected to be approximate, we empirically illustrate that very high accuracies (of over 90%) are achieved against the results of exact algorithms. Due to the simplied list-aggregation, we are also able to provide response times that are orders of magnitude better than state-of-the-art algorithms. Interestingly, our disk-based approach outperforms the in-memory baselines by up to hundred times and sometimes more, conrming the superiority of the proposed method.
Accelerating gene context analysis using bitmaps

Gene context analysis determines the function of genes by examining the conservation of chromosomal gene clusters and co-occurrence functional profiles across genomes. This is based on the observation that functionally related genes are often collocated on chromosomes as part of so called "gene cassettes", and relies on the identification of such cassettes across a statistically significant and phylogenetically diverse collection of genomes. Gene context analysis is an important part of a genomic data management system such as the Integrated Microbial Genomes (IMG) system, which has one of the largest public genome collections. As of January 2013, IMG contains 3.3 million gene cassettes across 8,000 genomes. A gene context analysis in IMG performs many millions of comparisons among the cassettes and their functions. Using a traditional relational database management system, these cassettes and their functional characteristics are represented by a correlation table of more than 2 billion rows along with a dozen auxiliary tables. This correlation table requires 16.5 hours to build and a typical query requires 5 to 10 minutes to answer. We developed an alternative approach that encodes the cassettes and their functions using bitmaps. Reading the input data now takes about 1.5 hours and constructing the bitmap representations takes only 8 minutes. This amounts to less than one tenth of the time needed to build the correlation table. Furthermore, fairly complex queries can now be answered in seconds. In this work, we considered three basic forms of queries required to support gene context analysis and devised two different bitmap representations to answer such queries. These queries can be answered in less than a second. A more complex query, which we referred to as a "killer query", requires the examination of multi-way cross-products of all cassettes. We developed a progressive pruning strategy that effectively reduces the number of possible combinations examined. Tests have shown that we can now answer "killer queries" in seconds. Even with an extremely complex "killer query" involving 161 genomes (needing a 161-way cross-product), our algorithm took less 10 seconds. A query involving this many genomes is expected to take so much time using a traditional DBMS that it has never been attempted before. Working with the IMG developers, we have verified our implementation and have integrated it into the production version of IMG.
Exploring Perceptron-Based Register Value Prediction

Register value prediction has been proposed as a technique to exploit register value reuse, a form of locality where the result produced by an instruction is the same as the value that is already in a destination register or other registers in the register file. Register value prediction allows increased performance by breaking true dependencies between an instruction that exhibits this locality and its dependents. This paper presents a study into using perceptron-based predictors to guide one form of register value prediction. For a given storage budget, we find that on the average a perceptron predictor performs better than previously proposed register value predictors. Secondly, we demonstrate the impact of perceptron history length on register value prediction. Lastly, we analyze predictor structures which improve upon previous predictors targeting register value reuse. With a 4KB hybrid perceptron predictor we show an average speedup of 7.5% for the benchmarks studied.
An Intelligent and Expert Mining Intrusion Detection and Response System

Intelligent intrusion and detection strategies for reducing false positives and increasing detection within network critical segments of network infrastructures are a major challenge. Current strategies focus on either detection or responses, but often lack both detection and response strategies. This novel approach combines both detection and response strategies involving both real-time analysis and effective statistical analysis of attack and normal traffic. The novel strategy involves a hybrid statistical approach involving Bayesian and Discriminant Analysis Classification. This comprises discriminant analysis of the normal and attack traffic after using Bayes Theorem to evaluate the training data. The results of the statistical analysis is fed into the IDS to reduce misclassification of false positives and distinguish between attacks and false positives in the IDS alert monitor. These intelligent strategies enhance the capability of the IDS to detect and respond to threats and benign traffic in critical segments of network, application and database infrastructures.
Disparities in Medicare Services: Potential Causes, Plausible Explanations, and Recommendations

Race/ethnicity and socioeconomic status (SES) are associated with the use of Medicare services. In this article, the author juxtaposes disparities in health outcome measures (including death rates for heart disease, cancer, and stroke) with disparities in the use of elective services expected to improve health, and with disparities in the use of non-elective services associated with poor management of chronic disease. This approach is intended to provide information for judging (a) the reasonableness of the explanations offered for disparities in Medicare utilization and (b) the recommendations made to effect change.
Structural brain imaging in individuals at high familial risk of schizophrenia

Schizophrenia is often a debilitating psychiatric disorder, characterised by both positive and negative symptoms, and cognitive and psychosocial impairments. The established disorder has been associated with a number of brain abnormalities, however it is at present unknown whether these brain changes occur prior to onset of schizophrenia, or in unaffected relatives with a familial vulnerability to develop the disorder, or only in those at high risk that go on to develop the disorder. Furthermore, most studies have been conducted cross-sectionally, which may have obscured subtle longitudinal changes in familial high risk individuals, and these studies tend to have focused on localized cortical gray matter , and thus it is unclear whether they affect different cortical parameters differentially. Prospective familial high risk studies utilizing surface based MRI programmes provide a good method to investigate this. In the Edinburgh High Risk Study, structural magnetic resonance imaging (MRI) scans of 150 young individuals at familial high risk of schizophrenia, 34 patients with first-episode schizophrenia and 36 matched controls were obtained. Of the high risk participants with scans suitable for analysis, 17 developed schizophrenia after the scans were taken, whilst 57 experienced isolated or sub-clinical psychotic symptoms, and 70 remained well. We used Freesurfer to extract volumetric and surface-based measurements of several cortical and localized sub-cortical regions with the aim of assessing whether any alterations found were
Successive interference cancellation for cdma2000 using a software defined radio

Signal strength imbalance due to imperfect power control and soft handoffs in direct-sequence code division multiple access (CDMA) cellular systems increases the mutual interference among users. This paper discusses the use of successive interference cancellation (SIC) for improving the reception of reverse link signals transmitted by cdma2000 mobile stations. A single-stage SIC algorithm has been implemented in a software defined radio (SDR) which employs general purpose digital signal processing (DSP) chips for interference cancellation and signal demodulation. Computer simulation of the DSP software and measured performance of the SDR have shown SIC to be an effective multiuser detector for the cdma2000 reverse link
Aligning Controlled Vocabularies using a Facet based Approach for Facilitating the Linked Open Data

A vocabulary stores words, synonyms, word sense definitions (i.e. glosses), relations between word senses and concepts; such a vocabulary is generally referred as the Controlled Vocabulary (CV) if choice or selections of terms are done by domain specialists. A facet is a distinct and dimensional feature of a concept or a term that allows taxonomy, ontology or controlled vocabulary to be viewed or ordered in multiple ways, rather than in a distinct way. The facet is also clearly defined, mutually exclusive, and composed by collectively exhaustive aspects, properties or characteristics of a domain. For example, a collection of rice might be represented using a name facet, place facet etc. In this paper an approach has been proposed where a facet has built for each concept by considering more general concepts (broader terms), less general concepts (narrow terms) or related concepts (related terms) that is to be called concept facet (CF). These CF’s have been used for mapping two controlled vocabularies. This methodology is based on hidden semantic matching which is different from the orthodox view of matching. Finally the aim is to contribute in alignment of controlled vocabulary to enrich the Linked Data version of AGROVOC with appropriate links to other thesauri.
Recent experiments in large vocabulary conversational speech recognition

This paper describes the improvements that resulted in the 1998 Byblos large vocabulary conversational speech recognition (LVCSR) system. Salient among these improvements are: improved signal processing, improved hidden Markov model (HMM) topology, use of quinphone context, introduction of diagonal speaker adapted training (DSAT), incorporation of variance adaptation in the MLLR framework, improvements in language modeling, increase in lexicon size and combination of multiple systems. These changes resulted in about a 7% absolute reduction in word error rates on a balanced Switchboard/Callhome English test set.
Avian Assemblages at Bird Baths: A Comparison of Urban and Rural Bird Baths in Australia

Private gardens provide habitat and resources for many birds living in human-dominated landscapes. While wild bird feeding is recognised as one of the most popular forms of human-wildlife interaction, almost nothing is known about the use of bird baths. This citizen science initiative explores avian assemblages at bird baths in private gardens in south-eastern Australia and how this differs with respect to levels of urbanisation and bioregion. Overall, 992 citizen scientists collected data over two, four-week survey periods during winter 2014 and summer 2015 (43% participated in both years). Avian assemblages at urban and rural bird baths differed between bioregions with aggressive nectar-eating species influenced the avian assemblages visiting urban bird baths in South Eastern Queensland, NSW North Coast and Sydney Basin while introduced birds contributed to differences in South Western Slopes, Southern Volcanic Plains and Victorian Midlands. Small honeyeaters and other small native birds occurred less often at urban bird baths compared to rural bird baths. Our results suggest that differences between urban versus rural areas, as well as bioregion, significantly influence the composition of avian assemblages visiting bird baths in private gardens. We also demonstrate that citizen science monitoring of fixed survey sites such as bird baths is a useful tool in understanding large-scale patterns in avian assemblages which requires a vast amount of data to be collected across broad areas.
Impacts of Oxidative Stress and Antioxidants on Semen Functions

Oxidative stress (OS) has been considered a major contributory factor to the infertility. Oxidative stress is the result of imbalance between the reactive oxygen species (ROS) and antioxidants in the body which can lead to sperm damage, deformity, and eventually male infertility. Although high concentrations of the ROS cause sperm pathology (ATP depletion) leading to insufficient axonemal phosphorylation, lipid peroxidation, and loss of motility and viability but, many evidences demonstrate that low and controlled concentrations of these ROS play an important role in sperm physiological processes such as capacitation, acrosome reaction, and signaling processes to ensure fertilization. The supplementation of a cryopreservation extender with antioxidant has been shown to provide a cryoprotective effect on mammalian sperm quality. This paper reviews the impacts of oxidative stress and reactive oxygen species on spermatozoa functions, causes of ROS generation, and antioxidative strategies to reduce OS. In addition, we also highlight the emerging concept of utilizing OS as a tool of contraception.
Book Review: Effective Strategies for Dropout Prevention of At-Risk Youth

tion ofAt-Risk Youth by Lynda L. West. Gaithersburg, MD: Aspen Publishers, Inc., 1991. Effective Strategies for Dropout Prevention of At-Risk Youth addresses specific issues associated with students who drop out of school. The author's research in the areas of dropout and at-risk youth was the basis for identifying issues relevant to education. General issues addressed in this text include: (a) economic, behavioral, family, and psychological factors involved in dropping out of school; (b) optimal classroom and school environments; (c) unemployment; (d) the role of vocational education; (e) transition; and (f) dropout prevention program. The author provides information and materials suitable for special, regular, and vocational educators; parents; and community agency personnel. She also provides information useful for administrators involved with the implementation of dropout prevention programs in schools. The text has 11 chapters, beginning with an introduction to the author's general perspective on dropouts and at-risk youth. Chapter Two covers the topic of program planning. Chapter Three discusses curriculum design and implementation. Chapters Four and Five present informative material concerning the school's role in dropout prevention programs for at-risk youth, including such classroom strategies as cooperative learning. Parent roles and responsibilities are discussed in terms of a partnership with schools in Chapter Six. Chapters Seven through Ten present critical information concerning strategies, the use of community resources for dropout prevention, and evaluation of -dropout programs. The final chapter discusses student and college characteristics that influence academic success and how student and faculty involvement can positively affect dropouts and at-risk youth. The author also includes sections on dropout prevention for students with disabilities and students from minority groups. Prevention programs that work, such as transition, multicultural, and community programs, are discussed. Effective Strategies for Dropout Prevention of At-Risk Youth is a comprehensive text detailing critical issues surrounding dropouts and at-risk youth. Theinforma-
Human protein reference database—2006 update

Human Protein Reference Database (HPRD) () was developed to serve as a comprehensive collection of protein features, post-translational modifications (PTMs) and protein–protein interactions. Since the original report, this database has increased to >20 000 proteins entries and has become the largest database for literature-derived protein–protein interactions (>30 000) and PTMs (>8000) for human proteins. We have also introduced several new features in HPRD including: (i) protein isoforms, (ii) enhanced search options, (iii) linking of pathway annotations and (iv) integration of a novel browser, GenProt Viewer (), developed by us that allows integration of genomic and proteomic information. With the continued support and active participation by the biomedical community, we expect HPRD to become a unique source of curated information for the human proteome and spur biomedical discoveries based on integration of genomic, transcriptomic and proteomic data.
BRA: A Bidirectional Routing Abstraction for Asymmetric Mobile Ad Hoc Networks

Wireless links are often asymmetric due to heterogeneity in the transmission power of devices, non-uniform environmental noise, and other signal propagation phenomena. Unfortunately, routing protocols for mobile ad hoc networks typically work well only in bidirectional networks. This paper first presents a simulation study quantifying the impact of asymmetric links on network connectivity and routing performance. It then presents a framework called BRA that provides a bidirectional abstraction of the asymmetric network to routing protocols. BRA works by maintaining multi-hop reverse routes for unidirectional links and provides three new abilities: improved connectivity by taking advantage of the unidirectional links, reverse route forwarding of control packets to enable off-the-shelf routing protocols, and detection packet loss on unidirectional links. Extensive simulations of AODV layered on BRA show that packet delivery increases substantially (two-fold in some instances) in asymmetric networks compared to regular AODV, which only routes on bidirectional links.