Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy consumption in VLSI circuits

We study energy consumption in CMOS-style VLSI circuits, where a wire of length / consumes energy &THgr;(<italic>l</italic>)when switching. Three model are considered: the <italic>uniswitch model</italic> where a wire is assumed to switch at most once if the input changes, the <italic>multiswitch model</italic> which allows the possibility of multiple switches caused by uncontrolled delays, and the <italic>clock model</italic> which also takes clock distribution energy into account. Previous lower bound results for the uniswitch model applied only to circuits where intermediate data were not encoded (for example, in unary) by using additional wires and area to reduce the energy. We show that such encodings can be useful for adding two <italic>n</italic>-bit numbers using synchronous Boolean circuits (energy reduction from &THgr;(<italic>n</italic> log <italic>n</italic>) to <italic>&Ogr;</italic>(<italic>n</italic> log <italic>n</italic>/(log log <italic>n</italic>)), but not for transitive functions such as the cyclic shift of <italic>n</italic> bits (energy &THgr;(<italic>n</italic><supscrpt>2</supscrpt>)). For the multiswitch model, we develop layouts that achieve energy close to the uniswitch case for these problems, and show a separation result between the uniswitch and multiswitch models. Finally, some energy-period tradeoffs are shown for the clock model.
The Moderating Effect of Perceived Organizational Support in Job Engagement and Work-Family Conflict

By using questionnaires and statistical hierarchical regression analyses,this study examined the relation-ship between job engagement and work-family conflict, and the moderating effect of perceived organizational support on job engagement and work-family conflict.All together 207 employees were recruited into this study.The result indicated that:1) job en- gagement has a remarkable negative predicative role on time-based conflict and behavior-based conflict; 2) the perceived organizational support indeed moderates the relationship between job engagement and behavior -based conflict.
Pattern formation yia chemical communication : collective and individual hunting strategies

we present a chemotaxis-difusion model that descibes collective hunting strategies using chemical communication. At the level of the irdividual the oien-tation of the animals in a scent field is described by a function that relates a chemical stimulus to a behavioural response. Two funhir rules are needed to describe the communication between the animals via emission of i pheromone and to characterize the interaction of the animals with prey rtems. \ie afpfication of these rules to an ensembre of.equally equipped indi;idu;ts kads to iâàrainarca iunting strategies. The hunting.benefit-of this strarcgy is compared to that of an individtàl strategy. This strategy is only diferent in tha there isio communication between the animals. It is found that collective huwing is more eficient at low prey densities whereas individual strategies are more efictent at high-prey densities.
A Framework for Implementing Mobile Cloud Services in VANETs

The strong potentials that exist in Vehicular Ad hoc Networks (VANETs) has given birth to the concept of Vehicular Clouds, in which cloud computing services are hosted by vehicles that have sufficient resources to act as mobile cloud servers. In this paper, we propose a protocol that enables vehicles to search for mobile cloud servers that are moving nearby and discover their services and resources. The design depends on roadside units (RSUs) that act as cloud directories with which mobile cloud servers register. We evaluate the performance of our protocol using ns2 and explain through comparing the results to another scheme the feasibility and efficiency of our protocol in terms of service discovery and service consuming delays and packet success ratio.
Multi-document text summarization - a survey

In today's world, the daily hustle-bustle does not permit a human being to devote time for manually summarizing various lengthy documents. Hence it is of utmost importance to devise an application that will facilitate automated text summarization. Not only will this application save time but also render higher scope of efficiency. This application will allow the user to automatically summarize relevant information from various sources.
Thermal-Aware Placement of Standard Cells and Gate Arrays: Studies and Observations

In high-performance VLSI circuits, the on-chip power densities are playing dominant role due to increased scaling of technology, increasing number of components, frequency and bandwidth. The consumed power is usually converted into dissipated heat, affecting the performance and reliability of a chip. In this paper, we consider the placement of standard cells and gate arrays (modules) under thermal considerations. Our contributions include: (i) an algorithm for optimal placement of the gates or cells to minimize the possible occurrence of hot spots, (ii) results of sensitivity analysis of thermal characteristic of a layout with respect to the power densities of the modules in the layout, and identifying three classes of modules, and (iii) an algorithm for optimal placement of modules, with minimum possible occurrence of hot spots, and reasonable estimated interconnect lengths. Experimental results on randomly generated and standard benchmark instances are quite encouraging.
Summary structures for frequency queries on large transaction sets

As large-scale databases become commonplace, there has been significant interest in mining them for commercial purposes. One of the basic tasks that underlies many of these mining operations is querying of transaction sets for frequencies of specified attribute values. The size of these databases makes it important to develop summary structures capable of high compression ratios as well as supporting fast frequency queries. The nature of the problem and its differences with respect to traditional text compression allows very high compression ratios. In this paper, we propose a binary trie-based summary structure for representing transaction sets. We demonstrate that this trie structure, when augmented with an appropriate set of horizontal pointers, can support frequency queries several orders of magnitude faster than raw transaction data. We improve the memory characteristics of our scheme by compressing the trie into a Patricia trie and demonstrate that this does not have a significant adverse effect on frequency query time. We further reduce the size of this trie by selectively pruning branches to compute a "dominant" trie that is capable of approximate frequency querying. The complement trie called the "deviant" trie is also useful in many data mining applications. Recompressing the "dominant" trie into a Patricia trie results in further compression of the trie. Finally, we demonstrate that our binary compressed trie structure has better memory (compression) characteristics compared to related schemes. We support our claims with experimental results on datasets from the IBM synthetic association data generator.
The Effects of Gender Differences in Patients with Depression on Their Emotional Working Memory and Emotional Experience

A large amount of research has been conducted on the effects of sex hormones on gender differences in patients with depression, yet research on cognitive differences between male and female patients with depression is insufficient. This study uses emotion pictures to investigate the differences of the emotional working memory ability and emotional experience in male and female patients with depression. Despite identifying that the working memory of patients with depression is impaired, our study found no significant gender differences in emotional working memory. Moreover, the research results revealed that memory effects of mood congruence are produced in both men and women, which may explain why the depression state can be maintained. Furthermore, female patients have more emotional experiences than male patients, which is particularly significant in terms of negative emotional experiences. This result provides cognitive evidence to explain why women suffer from longer terms of depression, are more susceptible to relapse, and can more easily suffer from major depressive disorder in the future.
A simple role mining algorithm

Complex organizations need to establish access control policies in order to manage access to restricted resources. Role Based Access Control paradigm has been introduced in '90 years aiming at simplifying the management of centralized access control. The definition of a good set of roles in order to match the organizational requirements of a company is a problem partially solved by role mining techniques, which return automatically a set of roles compatible with the permissions assigned to users. Unfortunately, the problem of finding an optimal role set has been proved to be NP-hard; so heuristics have been introduced in order to approximate the optimal solution. In this work we propose a novel heuristic and compare its results showing its efficiency and effectiveness.
Priority based distributed job scheduler for java compute servers

JavaSpace is a Java based implementation of shared memory distributed system introduced by Gelernter in 1985. Federation of shared memory space type distributed system with the basic command pattern has yielded a very powerful distributed systems architecture, which is known as Java compute servers. Java compute servers leverage the power of shared memory space based distributed systems in addition to the ability to perform any activity\computation by any processing node within the system. Java compute servers perform distributed processing through the shared memory space, where a process known as the master process, places the task that is required processing to the shared memory space. Process known as workers randomly read these entries in the shared memory space and perform the computation and writes back the results to the shared space, were it will be picked up by the master process and delivers to the source of the task.
Does Combining Models Help with Pricing of European Options?

In this study I combine six individual models to price European call options on the S&P500 index. Each model relaxes one or more assumptions of the Black-Scholes (1973) framework. The combining methods considered include three parametric and three non-parametric approaches. Combining outperforms most individual models in terms of the Root Mean Squared Error during the overall period (January 2006-December 2011) and three sub-periods. A simple and easy-implementable way of combining based on the historical performance of the individual models yields the best results among all individual and combining models considered. This method attaches most weight to the Merton (1976) jump diffusion model.
A Fast Gesture Recognition Scheme for Real-Time Human-Machine Interaction Systems

In recent years, the gesture control technique has become a new developmental trend for many human-based electronics products. This technique let people can control these products more naturally, intuitively and conveniently. In this paper, a fast gesture recognition scheme is proposed to be an interface for the human-machine interaction (HMI) of systems. This paper presents some low-complexity algorithms and gestures to reduce the gesture recognition complexity and be more suitable for controlling real-time computer systems. Besides, this paper also implements a HMI interface for a telematic service system to valid the performance of the proposed scheme and to confirm the proposed is suitable to be used to develop a HMI of telematic service systems for the in-vehicle environment. The experimental results show that the proposed scheme can work well in a real-time service system.
Meeting the information needs of the Ulama in the digital world: Challenges for the Muslim information professional

The advent of Information and Communication Technology (ICT) and its momentous growth especially in the 21st century, is perhaps the most amazing phenomenon in human history. It has impacted virtually on all aspects of human endeavor, most especially on how information is generated, processed, and disseminated. Individuals have become highly sophisticated, professionalized, and demanding on both the system and the information professionals to satisfy their ever increasing information requirements. While a lot of progress can be seen in efforts being made to meet the needs of various professional groups such as engineers, lawyers, medical practitioners, scientists, administrators etc through the development of specialized databases and tailor-made information retrieval systems (IRS), the Ulama the most influential professional group in the Muslim world, vested with the responsibility of preaching, counseling, administration, and providing religious leadership to the Muslims is neglected. This paper looks at the problems being faced by the Ulama using ICT to search for information to enable them perform their roles effectively. Among several factors identified, lack of a comprehensive Islamic Database and a suitable Information Retrieval System (IRS) is among the factors militating against the use of ICT by the Ulama. The paper challenged Muslim information professionals to come up with suitable data-bases and tailor-made IRS specifically designed to meet Islamic search pattern.
Neuroevolutionary constrained optimization for content creation

This paper presents a constraint-based procedural content generation (PCG) framework used for the creation of novel and high-performing content. Specifically, we examine the efficiency of the framework for the creation of spaceship design (hull shape and spaceship attributes such as weapon and thruster types and topologies) independently of game physics and steering strategies. According to the proposed framework, the designer picks a set of requirements for the spaceship that a constrained optimizer attempts to satisfy. The constraint satisfaction approach followed is based on neuroevolution; Compositional Pattern-Producing Networks (CPPNs) which represent the spaceship's design are trained via a constraint-based evolutionary algorithm. Results obtained in a number of evolutionary runs using a set of constraints and objectives show that the generated spaceships perform well in movement, combat and survival tasks and are also visually appealing.
Mobile Software Ecosystem (MSECO): A Systematic Mapping Study

The development of mobile applications around a central software platform has been impacting the software industry. Software solutions are collaboratively built within a dynamic market, often requiring adaptation of software development processes. This trend has been broadly studied as Software Ecosystem (SECO) - in the mobile platform domain, named as Mobile Software Ecosystem (MSECO). In this paper, we share the results of a systematic mapping study on the MSECO field that analyzed 28 papers identified as relevant to answer our research questions. The results indicate the growing interest in this research field as well as the main software platforms and trending topics. We confirmed the three main MSECOs as Android (Google), iOS (Apple) and Windows Phone (Microsoft). We observed the more investigated area is mobile app development. Finally, we highlighted the main benefits: the attracting and supporting developers, then helping developers to learn and create content and the app store that allows selling and buying processes.
Analyzing confidentiality and privacy concerns: insights from Android issue logs

Context: Post-release user feedback plays an integral role in improving software quality and informing new features. Given its growing importance, feedback concerning security enhancements is particularly noteworthy. In considering the rapid uptake of Android we have examined the scale and severity of Android security threats as reported by its stakeholders. Objective: We systematically mine Android issue logs to derive insights into stakeholder perceptions and experiences in relation to certain Android security issues. Method: We employed contextual analysis techniques to study issues raised regarding confidentiality and privacy in the last three major Android releases, considering covariance of stakeholder comments, and the level of consistency in user preferences and priorities. Results: Confidentiality and privacy concerns varied in severity, and were most prevalent over Jelly Bean releases. Issues raised in regard to confidentiality related mostly to access, user credentials and permission management, while privacy concerns were mainly expressed about phone locking. Community users also expressed divergent preferences for new security features, ranging from more relaxed to very strict. Conclusions: Strategies that support continuous corrective measures for both old and new Android releases would likely maintain stakeholder confidence. An approach that provides users with basic default security settings, but with the power to configure additional security features if desired, would provide the best balance for Android's wide cohort of stakeholders.
Estudio de la actividad cortical espontánea en ratones transgénicos con Alzheimer

Las senales corticales del cerebro permiten una vision mas clara de la actividad neuronal que el estudio clasico de las senales registradas en el cuero cabelludo y son de gran interes en el estudio de enfermedades neurodegenerativas como la enfermedad de Alzheimer. Con las senales adquiridas sobre el cortex prefrontal y somatosensorial de ratones con la mutacion 3xTg-AD, se han estudiado los estados espontaneos UP y DOWN de las oscilaciones lentas del cerebro anestesiado. En primer lugar, se han aplicado tecnicas de filtrado para eliminar interferencias y seleccionar la banda de interes entre 0.1 y 200 Hz, en la cual se aplicaron medidas de analisis espectral. Tras un filtrado adicional entre 30 y 100 Hz para seleccionar la banda gamma asociada a la actividad UP y DOWN, se calcularon variables de conectividad. Entre los resultados obtenidos, se escogieron aquellas variables que presentaban una mayor significacion estadistica mediante las pruebas T-Student y Wilcoxon. Finalmente, con estas variables se disenaron dos procedimientos de clasificacion por analisis discriminante lineal (Stepwise y Leave-one-out) que consiguen diferenciar entre sujetos enfermos de Alzheimer y sujetos control con un 88% y un 82% de precision, respectivamente.
Immunologic issues in type 1 diabetes.

This is the second in a series of reports on the American Diabetes Association (ADA) 61st Scientific Sessions held in Philadelphia, PA, in June 2001. It covers topics related to immunity and type 1 diabetes. Jay Skyler, Miami, FL, presented the results of the parenteral substudy arm of the Diabetes Prevention Trial for Type 1 Diabetes (DPT-1), in which relatives of patients with type 1 diabetes, whose risk of type 1 diabetes is 10- to 20-fold greater than that of the general population, were screened for islet cell antibodies (ICAs) and enrolled in a study of insulin administration if they showed high risk of developing diabetes. Animal studies in female nonobese diabetic (NOD) mice have shown this to be an effective treatment, and in the early 1990s, Keller et al. (1) reported a pilot study of 12 individuals with a predicted risk of diabetes; 5 subjects were treated with insulin and 7 subjects declined treatment. By 2.5 years, all of those who declined treatment had developed diabetes; at 5 years, only half of the intervention group had the disease. The DPT-1 was initiated in 1993. Screening began in February 1994 and randomization began in January 1995; 339 subjects were enrolled, with follow-up ending 13 April 2001. Screening of 89,827 relatives, with 84,228 samples analyzed, showed that 3,152 (3.7%) were ICA positive. A total of 2,103 subjects were staged, 535 having low first-phase insulin response. Of 372 subjects who were eligible for randomization, 339 were randomized. Skyler pointed out that 354 of the 3,152 ICA-positive individuals had actually already developed diabetes, with 156 identified before further testing. The projected annual event rate was 21%, and the actual finding was of 15.1% developing diabetes (in addition to those developing diabetes before randomization). Of the patients who developed diabetes, 60% were sibs, 25% …
A Penny Saved is a Penny Earned: Applying Optimization Techniques to Power Management

Shortage of electricity is a major problem in many developing countries. Unfortunately, for some of these countries the only solution to this problem is to shut down complete electricity supply to a few neighborhoods to make up for the gap between demand and supply. To this end, we have developed a self-optimization approach to reduce the gap between demand and supply through remotely controlling high powered electric devices such as air conditioners. In this approach we have used mathematical optimization techniques such as linear programming to intelligently manage the electricity distribution. Not only through this approach we have been able to provide service-level guarantees to the consumers but we have also shown that our approach is fast, scalable and has the ability to handle unscheduled spikes in the system.
Finite representations of a quiver arising from string theory

Inspired by Cachazo, Katz and Vafa (``Geometric transitions and $\mathcal {N}=1$ quiver theories'' (hep-th/0108120)), we examine representations of ``${N}=1$ quivers'' arising from string theory. We derive some mathematical consequences of the physics, and show that these results are a natural extension of Gabriel's ADE theorem. Extending the usual ADE case that relates quiver representations to curves on surfaces, we relate these new quiver representations to curves on threefolds.
DualTable: A hybrid storage model for update optimization in Hive

Hive is the most mature and prevalent data warehouse tool providing SQL-like interface in the Hadoop ecosystem. It is successfully used in many Internet companies and shows its value for big data processing in traditional industries. However, enterprise big data processing systems as in Smart Grid applications usually require complicated business logics and involve many data manipulation operations like updates and deletes. Hive cannot offer sufficient support for these while preserving high query performance. Hive using the Hadoop Distributed File System (HDFS) for storage cannot implement data manipulation efficiently and Hive on HBase suffers from poor query performance even though it can support faster data manipulation. There is a project based on Hive issue Hive-5317 to support update operations, but it has not been finished in Hive's latest version. Since this ACID compliant extension adopts same data storage format on HDFS, the update performance problem is not solved. In this paper, we propose a hybrid storage model called DualTable, which combines the efficient streaming reads of HDFS and the random write capability of HBase. Hive on DualTable provides better data manipulation support and preserves query performance at the same time. Experiments on a TPC-H data set and on a real smart grid data set show that Hive on DualTable is up to 10 times faster than Hive when executing update and delete operations.