Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of ‘Habit sensitive login system’ An approach to strengthen the login security

Providing reliable security to the computer user without overstepping any of the privacy related issues is the biggest challenge faced by the computer technologists now a day. An attempt is made herein to tailor a solution based on the personality features of an individual as a factor of identification and authentication. The traditional approach based on verification of the username and the password is insufficient. Hence, a new approach is needed to be introduced so as to make the existing login process more secure. To achieve the goal one can use the advantages of data mining techniques as well as the algorithms similar to the apriori algorithm. The suggested method is based on detection of intrusions at the time of logon. The system so designed; not only by verifies the username and password but also verifies the user’s behavior in comparison with the ‘recorded normal behavior’ of the user. The experiments carried herein are fruitful in recognizing the user by their ‘habits as behavior’. And hence the system based on the approach is practicable in real sense.
An Efficient Algorithm for Overlapping Community Detection in Complex Networks

Community structure is an important property of the complex networks. How to detect the communities is significant to understand the network structure and analyze the network properties. Many algorithms, such as K-L and GN, have been proposed to detect the community structure in complex networks. However, the communities detected by these algorithms are always not overlapping. According to daily experience, a node in the network may belong to several communities and a community should have many nodes and connections. Based on these principals and existing researches, an efficient algorithm for overlapping community detection in complex networks is proposed in this paper. The key strategy of the algorithm is to mine a node with the closest relations with the community and assign it to the community. Some real-world networks are used to test the performance of the algorithm. Experimental results demonstrate that the algorithm proposed is rather efficient to detect the overlapping community in complex networks.
Exploiting group communication for highly available video-on-demand services

Video on Demand services are popular today in hotels and luxury cruise boats. Increasing improvement in communication technology, will invite widespread utilization of VoD services in private homes, provided by telecommunication companies and via the Internet. In such an environment, scalability and fault tolerance will be key issues. In this paper we describe a highly available distributed Video on Demand (VoD) service, which is inherently scalable and fault tolerant. The VoD service is provided by multiple servers, that may reside in diierent sites. When a server crashes (or disconnects from its clients), it is replaced by another server in a transparent way; the clients are unaware of the change in the service provider. The VoD service exploits the Transis group communication system. Transis assists in achieving fault tolerance, and greatly simpliies the overall service design. Furthermore, the fault tolerance is achieved practically for free: it consumes negligible bandwidth, storage space, and cpu time.
A hybrid approach for question classification in Persian automatic question answering systems

Question classification plays a major role in automatic question answering systems. The performance of a question answering system depends directly to the performance of its question classification section. A question classifier associates a label or category to each question which represents semantic class of its answer. There exist different approaches such as rule-based, machine learning and hybrid approaches for solving this problem. In this paper we have introduced a novel hybrid question classification approach for Persian closed-domain question answering systems. The proposed approach is used practically in an online automatic question answering system. The experimental results show the usefulness of combining rule-based and machine learning question classification approaches for highly inflectional languages such as Persian. We got the satisfactory results according to high number of question classes.
Wide Field-of-View Fluorescence Imaging with Optical-Quality Curved Microfluidic Chamber for Absolute Cell Counting

Field curvature and other aberrations are encountered inevitably when designing a compact fluorescence imaging system with a simple lens. Although multiple lens elements can be used to correct most such aberrations, doing so increases system cost and complexity. Herein, we propose a wide field-of-view (FOV) fluorescence imaging method with an unconventional optical-quality curved sample chamber that corrects the field curvature caused by a simple lens. Our optics simulations and proof-of-concept experiments demonstrate that a curved substrate with lens-dependent curvature can reduce greatly the distortion in an image taken with a conventional planar detector. Following the validation study, we designed a curved sample chamber that can contain a known amount of sample volume and fabricated it at reasonable cost using plastic injection molding. At a magnification factor of approximately 0.6, the curved chamber provides a clear view of approximately 119 mm2, which is approximately two times larger than the aberration-free area of a planar chamber. Remarkably, a fluorescence image of microbeads in the curved chamber exhibits almost uniform intensity over the entire field even with a simple lens imaging system, whereas the distorted boundary region has much lower brightness than the central area in the planar chamber. The absolute count of white blood cells stained with a fluorescence dye was in good agreement with that obtained by a commercially available conventional microscopy system. Hence, a wide FOV imaging system with the proposed curved sample chamber would enable us to acquire an undistorted image of a large sample volume without requiring a time-consuming scanning process in point-of-care diagnostic applications.
RDF-Based Representation and Query of Information in Digital Library

Digital libraries contains enormous digital resource, which has become important Web application architecture. The data of digital libraries are enormous, heterogeneous, dynamic and semi-structured. It is hotspot of digital libraries how to implement representation and query of the heterogeneous information and to provide intelligent services to users. Digital libraries aim at integration and share of information to provide users integrated retrieval services. The resources of digital libraries are often semi-structured data and have metadata to descript them. RDF can support representation and exchange of metadata, so it can be used as data representation specification in integrated information retrieval system of digital libraries. A demonstrative query language with predicate logic, query based on RDF and RDFS (Query-RB) was proposed in this paper. We sketch syntax and grammar of Query-RB with BNF. RB-Query has characteristic of semantic mapping, logic comprehending and combining of schema with data querying, so it is an effective query mechanism for IIR of digital libraries.
The Relationship between Verbal “Intelligence,” Age, and Verbal Memory in Healthy Individuals in Their Eighties

Verbal intelligence has been shown to affect performance on verbal memory tests for healthy young adults. However, it is not clear that the association between verbal intelligence and memory is the same for healthy older adults because, while performance on verbal intelligence measures remains relatively stable in older age, there is significant normal agerelated memory decline. In fact, the magnitude of age-related decline in verbal memory performance is so substantial that there may be a significant difference between the memory performance of individuals in their early (i.e. 80 to 84) versus late (i.e. 85 to 89) eighties. This raises the possibility of an interactive effect between verbal intelligence and age on verbal memory for individuals in their 9th decade. The purpose of this study was to examine the effect of verbal intelligence and age on verbal memory test performance in the elderly. One hundred thirty-nine healthy participants aged 80-89 were divided into four groups based on Wechsler Adult Intelligence Scale – III (WAIS-III) Vocabulary scaled score: average/below average (< 11) and above average (> 12); and age: early 80’s (80 to 84) and late 80’s (85 to 89). The groups were compared on Rey Auditory Verbal Learning Test (RAVLT) total and delayed recall scores. Results from two-way ANOVA indicated a significant interaction effect between age and Vocabulary score for the RAVLT total score. ANOVA pairwise comparisons revealed a between groups difference that is inconsistent with the established presence of age-related memory decline that yields the current data invalid and ungeneralizable: for individuals in the average and below intelligence group, the younger age group performed worse than the older age group. Two-way ANOVA results indicated no interaction or main effects for age or Vocabulary score on RAVLT delay score. Other significant and marginal findings are discussed which argue for further research on the use of
TOURISTS’ MOTIVATIONS AND OBSTACLES FOR CHOOSING GLAMPING: AN EXPLORATORY STUDY

Although still little-known, glamping has become a nature-based tourism option for people who want a higher level of comfort. The offer of this type of accommodation is growing, namely in Portugal, but there are still few studies that address the motivations and other relevant factors explaining its adoption or refusal by consumers. The present study applied a qualitative approach aimed at exploring consumers’ motivations or obstacles for choosing glamping, and their perceptions as tourists on the differences between glamping and camping. Data were collected through the conduction of focus groups held in 2017 and content analysis techniques for contextualized interpretations were used. The most important motivational driver to go glamping is the direct contact with nature. Glamour, comfort, privacy and a different experience are also important aspects that consumers appreciate. Inversely, the main obstacles are the cost, the limited offer, the lack of knowledge, and the non-authenticity, compared to camping, of the offer.
International Journal of Pure and Applied Sciences and Technology Solving Intuitionistic Fuzzy Assignment Problem by Using Similarity Measures and Score Functions

Classical Assignment Problem (AP) is a well-known topic worldwide. In this problem ij c denotes the cost for assigning the th j job to the th i person. This cost is usually deterministic in nature. But in realistic situations, it may not be practicable to know the precise values of these costs. In such uncertain situations, instead of exact values of costs, if we can evaluate the preferences for assigning the th j job to the th i person in the form of composite relative degree (ij d) of similarity to ideal solution (maximum degree indicates most preferable combination), we can replace ij c by ij d in the classical AP in the maximization form and can solve it by any standard procedure to get the optimal assignment. In this paper the cost ij c has been considered to be intuitionistic fuzzy numbers (IFN) denoted by ij c ~ which involves the positive and the negative evidence for the membership of an element in a set. It is a more realistic description than using the crisp and fuzzy concept. The similarity measures of intuitionistic fuzzy sets have been used in this paper for determining the composite relative degree of similarity ij d. The notion of score function has also been used for validating the solution obtained by the composite relative similarity degree method. Numerical examples show the effectiveness of the proposed method for handling the Intuitionistic Fuzzy Assignment Problem (IFAP). Mathematical formulation of IFAP has been presented in this paper.
Users search trends on WWW and their analysis

World Wide Web (WWW) is a huge repository of interlinked hypertext documents known as web pages, spread all over the world on thousands of web servers. User looking to get the required information from WWW uses Search engine interface where they provide their search queries. In response, Search engines use their database to search the relevant documents and produce the result after ranking on the basis of relevance. It generally happens that the entire results produced by search engines may not be relevant to the user. When the users do not get the desired information, they modify the search query again and again till they get the desired information or get tired. The situation becomes more cumbersome when the results produced by the search tools are outdated especially when a bad URL is reported. Owing to the problems faced by users, a survey was being conducted to carry out some quantitative studies that can supplement in better understanding of the user's behavior/requirement while using search engine and consequently helping to improve its working.
Intrinsic and Extrinsic Value for English Learning: Mediation Effects of Self-Efficacy in Chinese EFL Context

Abstract The present study examined how students’ intrinsic and extrinsic value promotes their foreign language proficiency via the mediation effect of self-efficacy beliefs. A total of 1,036 Chinese eighth graders answered an English proficiency test and questionnaires assessing motivational beliefs. Structural equation modelling results with bootstrapping procedures revealed that intrinsic value can directly and indirectly influence foreign language proficiency via partial mediation effect of self-efficacy while extrinsic value can only directly influence foreign language proficiency with a small magnitude. Moreover, there is no gender difference in the mediation model. Our findings suggested that intrinsic value can help students improve foreign language proficiency by improving their self-efficacy beliefs. The findings contribute to the documents of self-determination theory and hold substantive theoretical and practical implications for foreign language teachers.
PeerSoN: P2P social networking: early experiences and insights

To address privacy concerns over Online Social Networks (OSNs), we propose a distributed, peer-to-peer approach coupled with encryption. Moreover, extending this distributed approach by direct data exchange between user devices removes the strict Internet-connectivity requirements of web-based OSNs. In order to verify the feasibility of this approach, we designed a two-tiered architecture and protocols that recreate the core features of OSNs in a decentralized way. This paper focuses on the description of the prototype built for the P2P infrastructure for social networks, as a first step without the encryption part, and shares early experiences from the prototype and insights gained since first outlining the challenges and possibilities of decentralized alternatives to OSNs.
The essence of essentialism

Over the past several decades, psychological essentialism has been an important topic of study, incorporating research from multiple areas of psychology, philosophy and linguistics. At its most basic level, essentialism is the tendency to represent certain concepts in terms of a deeper, unobservable property that is responsible for category membership. Originally, this concept was used to understand people’s reasoning about natural kind concepts, such as TIGER and WATER, but more recently, researchers have identified the emergence of essentialistlike intuitions in a number of other contexts, including people’s representation of concepts like SCIENTIST or CHRISTIAN. This paper develops an account that aims to capture how essentialism may operate across these varied cases. In short, we argue that while there is diversity in the forms essentialism can take, these varied cases reflect the same underlying cognitive structure.
Crystal structure of PHO4 bHLH domain–DNA complex: flanking base recognition

The crystal structure of a DNA‐binding domain of PHO4 complexed with DNA at 2.8 Å resolution revealed that the domain folds into a basic–helix–loop–helix (bHLH) motif with a long but compact loop that contains a short α‐helical segment. This helical structure positions a tryptophan residue into an aromatic cluster so as to make the loop compact. PHO4 binds to DNA as a homodimer with direct reading of both the core E‐box sequence CACGTG and its 3′‐flanking bases. The 3′‐flanking bases GG are recognized by Arg2 and His5. The residues involved in the E‐box recognition are His5, Glu9 and Arg13, as already reported for bHLH/Zip proteins MAX and USF, and are different from those recognized by bHLH proteins MyoD and E47, although PHO4 is a bHLH protein.
Linking GABA and glutamate levels to cognitive skill acquisition during development

Developmental adjustments in the balance of excitation and inhibition are thought to constrain the plasticity of sensory areas of the cortex. It is unknown however, how changes in excitatory or inhibitory neurochemical expression (glutamate, γ‐aminobutyric acid (GABA)) contribute to skill acquisition during development. Here we used single‐voxel proton magnetic resonance spectroscopy (1H‐MRS) to reveal how differences in cortical glutamate vs. GABA ratios relate to face proficiency and working memory abilities in children and adults. We show that higher glutamate levels in the inferior frontal gyrus correlated positively with face processing proficiency in the children, but not the adults, an effect which was independent of age‐dependent differences in underlying cortical gray matter. Moreover, we found that glutamate/GABA levels and gray matter volume are dissociated at the different maturational stages. These findings suggest that increased excitation during development is linked to neuroplasticity and the acquisition of new cognitive skills. They also offer a new, neurochemical approach to investigating the relationship between cognitive performance and brain development across the lifespan. Hum Brain Mapp 36:4334–4345, 2015. © 2015 The Authors. Human Brain Mapping Published byWiley Periodicals, Inc.
Competition and fragmentation: a simple model generating lognormal-like distributions

The current distribution of language size in terms of speaker population is generally described using a lognormal distribution. Analyzing the original real data we show how the double-Pareto lognormal distribution can give an alternative fit that indicates the existence of a power law tail. A simple Monte Carlo model is constructed based on the processes of competition and fragmentation. The results reproduce the power law tails of the real distribution well and give better results for a poorly connected topology of interactions.
THE UNRAVELING OF TOOL USE: ANSWERING THE UNANSWERED?

This paper summarizes the results of four experiments exploring the use of tools. The first experiment shows that the use of tools is not only problematic in computer-based learning environments (CBLEs) and that the functionality of tools is relevant. The following experiments explored the impact of tools (concept maps, adjunct questions), tool-related characteristics (tool delivery mode: non-/embedded tool), tool advice (non- /explained tool functionality) and learner-related characteristics (prior knowledge, self-efficacy, goal orientation, perceptions, self-regulation) on tool use in a CBLE. Tool use on performance was also studied. The results indicate that all aforementioned characteristics influence tool use; there seems to be an interaction between the tool and the learner, and time spent on the tool seems crucial to determine performance.
THE BANANA PROJECT. V. MISALIGNED AND PRECESSING STELLAR ROTATION AXES IN CV VELORUM

As part of the Binaries Are Not Always Neatly Aligned project (BANANA), we have found that the eclipsing binary CV Velorum has misaligned rotation axes. Based on our analysis of the Rossiter–McLaughlin effect, we find sky-projected spin-orbit angles of βp = −52° ± 6° and βs = 3° ± 7° for the primary and secondary stars (B2.5V + B2.5V, P = 6.9 days). We combine this information with several measurements of changing projected stellar rotation speeds (vsin i⋆) over the last 30 yr, leading to a model in which the primary star's obliquity is ≈65°, and its spin axis precesses around the total angular momentum vector with a period of about 140 yr. The geometry of the secondary star is less clear, although a significant obliquity is also implicated by the observed time variations in the vsin i⋆. By integrating the secular tidal evolution equations backward in time, we find that the system could have evolved from a state of even stronger misalignment similar to DI Herculis, a younger but otherwise comparable binary.
Efficient Image Retrieval Using Advanced Clustering SURF

Image retrieval is one of the most exciting and fastest growing research areas in the field of multimedia technology. In this paper, we propose and implement a new image retrieval method that extracts the feature of image using efficient clustering for SURF (Speed Up Robust Feature) scheme, applicable to mobile environments. Since SURF works only on gray-scale images, our clustering SURF is combined with well-known dominant color descriptor to improve the performance of the system. Also, we calculate the feature vector to remove an unnecessary feature, which is located in the sparse region, not to be clustered in final target features. To evaluate the performance of the proposed algorithm, we assess the simulation's performance in terms of average precision on two image databases commonly used. Based on the average precision from all queries, 86% and 79% of all relevant images were retrieved. The result shows that the proposed approach obtains an enough results which are applicable to mobile environments.
Diffusion adaptive filtering for modelling brain responses to motor tasks

Diffusion adaptation combined with an adaptive way of estimating brain connectivity is used here in order to model specific motor tasks. We use Kalman filtering to fit an adaptive multivariate autoregressive model to our data and compute the connectivity measure which is a time-varying version of directed transfer function (DTF). The resulting method is used to classify the data from movement-related activities. The comparison between the proposed method and the non-diffusion method shows superiority of the former one.