Miracle-dz/UniFAR-FTUs huggingface dataset:
Quadratic Assignment Problem and its Relevance to the Real World: A Survey

The Quadratic Assignment Problem (QAP) is the well known and significant combinatorial optimization problem. For several decades, it has been of keen interest for researchers and its improvement is still in progress. QAP is very important because it plays an important role in various complex real world problems. In this survey some of the prominent applications of QAP are illustrated which have been optimally applied to real world problems in diverse areas. Here inherent descriptions of various applications are summarized by highlighting the shortcomings of their applications related to QAP. This paper gives the future directions and strong conclusions on the survey of quadratic assignment problem and justify that the performance improvement of QAP is important.
CAPSL integrated protocol environment

CAPSL, a Common Authentication Protocol Specification Language, is a high-level language to support security analysis of cryptographic authentication and key distribution protocols. It is translated to CIL, an intermediate language expressing state transitions with term-rewriting rules. Connectors are being written to adapt CIL to supply input to different security analysis tools, including PVS for inductive verification and Maude for model-checking.
An information model in lean, agile, resilient and green supply chains

Currently the competition is between supply chains rather than between companies. The demands of customers in a market increasingly volatile and turbulent, in conjunction with environmental responsibilities, make supply chains develop strategies to be more flexible, agile, which eliminate processes that add no value and respond to environmental issues, making the supply chains more competitive. This paper presents and discusses an information model to support current integrated paradigms of supply chain management — lean, agile, resilient and green. The information model will provide all the necessary information for decision-makers take the right decisions at the right time and thus optimizing the supply chain performance integrating lean, agile, resilient and green demands.
IL-21 Receptor Is Critical for the Development of Memory B Cell Responses

Development of long-term humoral immunity, characterized by the formation of long-lived plasma cells (PCs) in the bone marrow and memory B cells, is a critical component of protective immunity to pathogens, and as such it is the major goal of vaccination. However, the mechanisms involved in the generation of long-term humoral immunity remain poorly understood. In this study, we used IL-21R–deficient (IL-21R.KO) mice to examine the role of the IL-21 pathway in the development of the B cell memory response. Primary IgG serum Ab responses to the T cell-dependent Ag 4-hydroxy-3-nitrophenylacetyl (NP) hapten conjugated to chicken γ globulin were delayed in IL-21R.KO mice, but reached normal titers within 3 to 4 wk of immunization. IL-21R.KO mice formed germinal centers and generated normal numbers of PCs in their bone marrow. Additionally, memory B cell formation was similar in wild-type and IL-21R.KO mice. However, NP-specific memory B cells and PCs failed to expand following secondary immunization of IL-21R.KO mice, and consequently, secondary IgG Ab responses to NP hapten conjugated to chicken γ globulin were significantly impaired. These results identify the IL-21 pathway as a critical component of the memory B cell response.
The Time Course of Corticospinal Excitability during a Simple Reaction Time Task

The production of movement in a simple reaction time task can be separated into two time periods: the foreperiod, which is thought to include preparatory processes, and the reaction time interval, which includes initiation processes. To better understand these processes, transcranial magnetic stimulation has been used to probe corticospinal excitability at various time points during response preparation and initiation. Previous research has shown that excitability decreases prior to the “go” stimulus and increases following the “go”; however these two time frames have been examined independently. The purpose of this study was to measure changes in CE during both the foreperiod and reaction time interval in a single experiment, relative to a resting baseline level. Participants performed a button press movement in a simple reaction time task and excitability was measured during rest, the foreperiod, and the reaction time interval. Results indicated that during the foreperiod, excitability levels quickly increased from baseline with the presentation of the warning signal, followed by a period of stable excitability leading up to the “go” signal, and finally a rapid increase in excitability during the reaction time interval. This excitability time course is consistent with neural activation models that describe movement preparation and response initiation.
New Cost-Sensitive Model for Intrusion Response Systems Minimizing False Positive

Dynamic Cost-sensitive Intrusion Response System (Dy-COIRS) is considered as one of the challenging intrusion response model in intrusion detection and prevention systems (IDS/IPS) field. This type of intrusion response system is faced to the issue of false positive responses (FPR) such as an error responses toward normal activities that does not affect the integrity, confidentiality availability and authentication of computer systems. This leads to high overhead which harms severally the overall network performances. In this paper, we propose an intelligent automatic dynamic cost sensitive model intended for IRS related to IDS/IPS field where the impact of false positive responses are minimized. This FPR reducing is based on an algorithmic approach with a linear model theory.
Generating generalized distributions from dynamical simulation

We present a general molecular-dynamics simulation scheme, based on the Nose thermostat, for sampling from arbitrary phase space distributions. We formulate numerical methods based on both Nose–Hoover and Nose–Poincare thermostats for two specific classes of distributions; namely, those that are functions of the system Hamiltonian and those for which position and momentum are statistically independent. As an example, we propose a generalized variable temperature distribution that is designed to accelerate sampling in molecular systems.
Modelling of compressive strain softening , fracture and size effect in concrete

It is by now well established that tensile failure of quasibrittle materials such as concrete exhibits a significant nonstatistical size effect on the nominal strength of structure, but it is still widely believed that compression failure does not. Recent researches are showing this belief to be untrue. The present paper reviews recent research results on this problem and presents a simplified quasi-LEFM analysis of the size effect in compression. The basic characteristics and mechanisms of compression failure are reviewed and the distinction between local and global mechanisms is emphasized. The maximum load is considered to be reached because the material develops axial splitting cracks and undergoes internal buckling (microbuckling) in a localized band that propagates in either axial or lateral direction (the latter appearing after reduction of load to zero as a 'shear' failure). The fully fractured and microbuckled tail of crack band may transmit a finite residual stress. J-integral analysis of the energy release is used to obtain the approximate size effect law for compression for a simple specimen shape, and equivalent LEFM (linear elastic fracture mechanics) approximation is then used to derive size effect formulae that take also into account the effect of structure geometry (shape). The cases of failure after long stable growth of crack band and at crack band initiation are distinguished. Experimental results on size effect in reinforced concrete columns and, for the purpose of analogy, also in carbon-PEEK laminates, are discussed. Finally, one practical application in which the truss model for diagonal shear failure is extended to size effect is presented and some implications for finite element analysis are discussed.
Personalization in tag ontology learning for recommendation making

Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. One of the most popular web personalization systems is recommender systems. In recommender systems choosing user information that can be used to profile users is very crucial for user profiling. In Web 2.0, one facility that can help users organize Web resources of their interest is user tagging systems. Exploring user tagging behavior provides a promising way for understanding users' information needs since tags are given directly by users. However, free and relatively uncontrolled vocabulary makes the user self-defined tags lack of standardization and semantic ambiguity. Also, the relationships among tags need to be explored since there are rich relationships among tags which could provide valuable information for us to better understand users. In this paper, we propose a novel approach for learning tag ontology based on the widely used lexical database WordNet for capturing the semantics and the structural relationships of tags. We present personalization strategies to disambiguate the semantics of tags by combining the opinion of WordNet lexicographers and users' tagging behavior together. To personalize further, clustering of users is performed to generate a more accurate ontology for a particular group of users. In order to evaluate the usefulness of the tag ontology, we use the tag ontology in a pilot tag recommendation experiment for improving the recommendation performance by exploiting the semantic information in the tag ontology. The initial result shows that the personalized information has improved the accuracy of the tag recommendation.
Capacity of Relay Channels with Power Splitting and Dual Frequency Carriers

We consider a cooperative relay communication system where the source and the relay have separate frequency bands for message transmission. The relay is assumed to be a decode-forward node, i.e. It can decode the information send from the source node and re-transmit after suitable modifications. With power splitting at the source, we find an optimum relaying function which achieves the capacity of this relay network. The optimal power splitting algorithm is developed under two cases - one when the nodes have complete channel state knowledge and the other when nodes have limited information about the channel state. We extend the work to practical wireless systems and address the issue of message security.
Genders at Work: Exploring the Role of Workplace Equality in Preventing Men’s Violence Against Women

This report examines the role of workplaces, and men in workplaces in particular, in preventing men’s violence against women. The report begins by noting that men’s violence against women is a widespread social problem which requires urgent action. It highlights the need for preventative measures oriented to changing the social and structural conditions at the root of this violence, including through settings such as workplaces. Men’s violence against women is a workplace issue. As well as being a blunt infringement of women’s rights, this violence imposes very substantial health and economic costs on workplaces and organisations.
Rapid Degradation of Hfq-Free RyhB in Yersinia pestis by PNPase Independent of Putative Ribonucleolytic Complexes

The RNA chaperone Hfq in bacteria stabilizes sRNAs by protecting them from the attack of ribonucleases. Upon release from Hfq, sRNAs are preferably degraded by PNPase. PNPase usually forms multienzyme ribonucleolytic complexes with endoribonuclease E and/or RNA helicase RhlB to facilitate the degradation of the structured RNA. However, whether PNPase activity on Hfq-free sRNAs is associated with the assembly of RNase E or RhlB has yet to be determined. Here we examined the roles of the main endoribonucleases, exoribonucleases, and ancillary RNA-modifying enzymes in the degradation of Y. pestis RyhB in the absence of Hfq. Expectedly, the transcript levels of both RyhB1 and RyhB2 increase only after inactivating PNPase, which confirms the importance of PNPase in sRNA degradation. By contrast, the signal of RyhB becomes barely perceptible after inactivating of RNase III, which may be explained by the increase in PNPase levels resulting from the exemption of pnp mRNA from RNase III processing. No significant changes are observed in RyhB stability after deletion of either the PNPase-binding domain of RNase E or rhlB. Therefore, PNPase acts as a major enzyme of RyhB degradation independent of PNPase-containing RNase E and RhlB assembly in the absence of Hfq.
Globalization and labor conditions

This book explains how three major mechanisms of globalization - international trade, international migration, and the activities of multinational companies - have altered working conditions and labor rights around the world during the 20th century. Drawing on analyses of a database on international labor conditions assembled for this project and a growing research literature on globalization and labor conditions, the book finds that trade, migration, and multinational companies are associated with improvements in world labor conditions. Available in OSO: http://www.oxfordscholarship. com/oso/public/content/economicsfinance/0195306007/toc.html
The Role of Feature Selection with Applications to Eye Movements using Electrooculography

Eyes are the windows to the brain and the eye movements are a rich source of information in information processing. The aim of this paper is to select the features with CBFS Feature selection algorithm using eye movements by ElectroOculoGraph (EOG) signals during reading and writing task. The objective is to impart the fundamental functionality to get an extensive understanding of how EOG signals can be applied in human computer interaction (HCI) and what can be inferred from those signals using feature selection and data mining classification techniques. This paper first identifies the importance of eye movements and EOG signals then analyze EOG signals by CBFS (clearness based feature selection), mRMR (minimum redundancy maximum relevance) feature Selection methods and the third section analyzes the time complexity of CBFS method & describes the performance of data mining classification in EOG signals.
Autoantibodies produced spontaneously by young 1pr mice carry transforming growth factor beta and suppress cytotoxic T lymphocyte responses

Young MRL/MPJ-lpr (lpr) mice 8-12 wk old challenged with alloantigen had significantly lower specific cytolytic T lymphocyte (CTL) responses than control MRL/MPJ +/+ mice. Serum from lpr mice compared with serum from ++ or normal C3H mice powerfully suppressed CTL responses in mixed lymphocyte cultures (MLC); absorbing lpr serum on protein G, adding antibody against transforming growth factor beta (TGF-beta) to cultures or dissociating immunoglobulin G (IgG) and TGF-beta before additions to cultures prevented suppression. Apparently autoantibody, similar to IgG produced by normal mice in response to immunization, carries TGF-beta which suppresses CTL responses in vivo and in vitro.
Competition and cooperation in wireless access misbehavior

With the proliferation of access points and terminals, wireless access misbehavior emerges as important means of protocol misuse, whereby network entities aim at obtaining higher channel share than the one in legitimate operation. We consider the instantiation of misbehavior in the back-off mechanism in IEEE 802.11. First, we study the competition between two malicious entities that affect each other. Each entity has some private target gain in terms of access probability and attempts to misuse the protocol to its benefit so as to prolong the time until detection. We derive conditions for existence of the unique Nash Equilibrium Point (NEP). This is influenced by attacker gains and topology parameters that capture the level of contention from neighboring nodes. These quantities need to be small in order for the NEP to exist. Next, we consider simple types of cooperation between attackers that aim at alleviating the contention caused to each other.
Cyclic Routing in Peer-to-Peer Systems

Basic P2P routing algorithms require log(n) hops to route a message in a geographically distributed network. High latency of basic P2P routes is often unacceptable for delay-sensitive applications such as interactive browsing. Additional routing information at a node could help to reduce the latency at an expense of larger routing tables. We propose cyclic routing as a new approach to balance the routing overhead vs. routing latency. Cycles in a P2P network are collected at a little extra cost by piggybacking node’s ID into forwarded packets. Cyclic routing is proved to be dependable and improves the performance of Chord’s basic routing algorithms.
Polarization-independent optical racetrack resonators using rib waveguides on silicon-on-insulator

In an effort to find low-cost alternatives for components currently used in dense wavelength division multiplexing, optical ring resonators fabricated on silicon on insulator are currently being investigated. Their performance can be further enhanced if they are polarization independent. Herein we use rib waveguides to control the polarization properties of the devices and hence produce polarization-independent racetrack ring resonators. Transverse electric and transverse magnetic resonant peaks are measured to within 2 pm of one another over four cycles of the free spectral range. The racetrack resonators also exhibit measured Q factors of approximately 90 000 and finesse values of 12.
Semantic Discovery and Selection: A QoS-Aware, Hybrid Model

Abstract – Most Semantic Web Services discovery ap-proaches are based on Description Logics, allowing alimited expressiveness when describing Quality-of-Servicepreferences. Furthermore, DLs is not suited to perform se-lection tasks, because these are modeled as optimizationproblems. In this work, we present a hybrid discovery andselection model for Semantic Web Services that takes careof Q O S preferences. Our approachsplits the whole processinto two stages, using the most suited engine in each one,depending on its search nature. In order to perform Q O S -aware discovery and selection, user preferences have to besemanticallydescribed as the rest of the service description.Our model provides an ontology for user preferences, so in-stances can be transformed into optimization problems thatcan be solved by using the most suited engine. Keywords: Service Discovery,Quality-of-Service,Seman-tic Web Services, Ontology Languages, QoS-Aware Selec-tion. 1 Introduction Most approaches on automatic discovery of SemanticWeb Services (SWS) use Description Logics (DLs) reason-ers to perform the matching [8,13,16,20,27,28]. Theseapproaches have limitations regarding with the expres-siveness of searches, especially when there are Quality-of-Service (Q
Scheduling Non-Uniform Parallel Loops on Highly Parallel Multicomputers

We consider the problem of scheduling parallel loops that are characterized by highly varying execution times (non-uniform parallel loops), and whose iterations operate on large data structures. A general parallel loop implementation template for message-passing multicomputers is presented. It exploits a partial static replication of the data and a two-phase scheduling strategy. While the rst phase of the strategy is static, the second one is dynamic, and only starts when processor loads are estimated to be lower than a given threshold. The static knowledge of the data distribution strategy, which randomly replicates blocks on a xed set of partner processors, is successfully exploited by the dynamic scheduling phase of our technique. The main advantages of the approach are low-cost scheduling decisions (mainly based on local information) and high scalability, since communications to request further work are overlapped with computations. A simple analytical model of load imbalance, used to tune the template and approximate the actual performances , is also introduced. The template can be used by compilers to generate well-balanced schedules of loops when no static information on processor workloads can be derived. Results of experiments conducted on a 128-node nCUBE 2 are reported and discussed.
Active Learning Management on Social Studies in Thailand: Research Synthesis

There are many researches on active learning management in Thailand applied by different disciplines such as, Mathematics, Sciences, and Social Sciences, etc. The students were found to be fatigued studying subjects with lots of contents such as social studies. Active learning has been found to be the essential tool improving student’s understanding in each subject areas. Additionally, the social studies area was found to be the one employing this method most. This study then aims to synthesize past research on applying active learning social studies subjects during 2012-2017. The data was collected from 68 research papers with topics on active learning in social studies, which were published on the database of Thai-Journal Citation Index Centre (TCI) during 2012 – 2017. Six topics were synthesized : 1) active Learning management techniques 2) attributes to be developed 3)target group 4)research instruments 5) statistics 6) research outcomes. The results found that the mainly employed active learning methods were techniques used to develop cognitive domain such as problem based learning, brain based learning, and building conceptual framework. The timing employing active learning in classroom was seen to be at least 1 – 2 months with the levels of students learning by active learning method were found to be grade 6-12 students, the measurement and evaluation methods were found to be examination, observation, and informal interview during the activities, and the data analysis using descriptive and inferential statistics with t-test revealed that active learning could improve cognitive, affective, and psychomotor domains. The instructors may need to consider the methods that suit students most, as well as the improvement of traits and subjects, to gain the best benefit using active learning methods with the students.
Robust clustering methods for detecting smartphone's abnormal behavior

Smartphones have become increasingly popular, and, nowadays, thanks to the use of 3G networks, the need for connectivity in a business environment is significant. Smartphones provide access to a tremendous amount of sensitive information related to business, such as customer contacts, financial data and Intranet networks. If any of this information were to fall into the hands of hackers, it would be devastating for the company. In this paper, we propose a cluster-based approach to detecting abnormal behaviour in smartphone applications. First we carry out various robust clustering techniques that help to identify and regroup applications that exhibit similar behaviour. The clustering results are then used to define a cluster-based outlier factor for each application, which in turn identifies the top n malware applications. Initial results of the experiments prove the efficiency and accuracy of cluster-based approaches in detecting abnormal smartphone applications and those with a low false-alert rate.