Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Worst Case of Scheduling with Task Replication on Computational Grids

We study the problem of scheduling tasks in a computational grid. We give analytical results for Work queue with Replication (WQR) based algorithms. There are several works presenting simulation results for scheduling algorithms for computational grid, but few provide analytical evidence of the quality of the solution of these algorithms. In this paper we show that under the TPCC metric \cite{FujimotoH03} there is an optimal algorithm if the machines speed are predictable and tasks have the same length. If machines speed are not predictable we show an approximation result for the WQRxx algorithm and show that the result is tight. When tasks have different lengths the problem of minimizing the make span does not admit an approximation algorithm, even when machines speed are predictable. On the other hand, we show that the WQR based algorithm is a $m$-approximation when minimizing the TPCC in the unpredictable case, and this result is tight. To finish we show how to add replication to any scheduling algorithm using a simple interface and present computational simulations comparing the quality of the solutions of some well know algorithms with the addition of replication.
Disposed to Measure Dispositions

During the more than 60 years since Benjamin Bloom and his co-authors trotted out their influential Taxonomy of Educational Objectives (Bloom et al., 1956), American educators have become generally familiar with the distinction among cognitive, affective, and psychomotor curricular aims. Cognitive outcomes, of course, focus on students’ intellectual skills or knowledge; psychomotor outcomes deal with students’ small-muscle or large-muscle skills; and cognitive outcomes center on student’s attitudes, interests, or values. During all those decades, our educational attention has been centered almost exclusively on the promotion and assessment of cognitive curricular aspirations. This, in my view, has been a mistake. Clearly, promoting students’ acquisition of key cognitive skills and mastery of significant bodies of knowledge should be the most important mission of our schools, so there is little disagreement about the need for educators to emphasize students’ attainment of cognitive curricular aims. However, almost no attention—nearly zero—has been given to the promotion or measurement of students’ affective status. This inattention to the affective outcomes of schooling, for more than a half-century—has been short-changing the nation’s students. Students’ affective status, you see, provides us with an indication of the ways students are likely to act in the future. That is, students’ current affective status foreshadows the ways children will act as “grown-ups” long after school is behind them. Clearly, educators should be concerned with the long-term impact of their instructional programs, so it is perplexing that scant attention—instructional as well as assessment—has been given to what we can refer to as the affective or dispositional outcomes of education. In the following analysis, three questions will be addressed related to the dispositional status of students: (a) How educationally important are students’ dispositions? (b) How should students’ dispositions be assessed? (c) How can teachers, if they wish to do so, mold students’ dispositions? Let’s turn to the first of these three questions.
Transformation-based assessment for C programs

In this paper, a new framework, AnalyseC, is proposed for assessing student programming exercises with an aim to free teachers from heavy assessment work and facilitate studentspsila learning. Based on code optimization techniques of compiler, such as inline expansion, data flow analysis and control flow analysis, AnalyseC has been designed to automatically assess programming assignments written in C language at semantic level. The prototype has been implemented in Java. To use the system, teachers are required to provide a simple model program for any given assessment item. The prototype of AnalyseC has been tested on a number of student programming exercises and assignments providing encouraging results.
A Stateful Real Time Intrusion Detection System for high-speed network

The Solutions of security are disturbed by aftermaths of the fast evolution of the infrastructure. Indeed, the new networks use more and more fast links in Gigabits and 10 Gigabits whereas the methods of security most often applied as IDSs, firewalls and cryptography are incapable to follow this fast transfer of data. In this paper, we are interested in the NIDSs. In fact the constant increase in network speed and throughput pose new challenges to these systems. Current NIDSs are designed to 10/100 Mbps [6], nevertheless large network installations are Gigabit Ethernet (1000 Mbps), so the task of detection becomes increasingly difficult with only one NIDS. The purpose of this paper is to discuss a new approach with the aim of accelerating the intrusion detection. The approach is based on three main steps: traffic classification, load balancing and a high availability mechanism. The paper describes all the above mentioned approaches and presents an experimental evaluation of their effectiveness.
NEUROIMAGING AND PATTERN RECOGNITION TECHNIQUES FOR AUTOMATIC DETECTION OF ALZHEIMER’S DISEASE: A REVIEW

Alzheimer’s disease (AD) is the most common form of dementia with currently unavailable firm treatments that can stop or reverse the disease progression. A combination of brain imaging and clinical tests for checking the signs of memory impairment is used to identify patients with AD. In recent years, Neuroimaging techniques combined with machine learning algorithms have received lot of attention in this field. There is a need for development of automated techniques to detect the disease well before patient suffers from irreversible loss. This paper is about the review of such semi or fully automatic techniques with detail comparison of methods implemented, class labels considered, data base used and the results obtained for related study. This review provides detailed comparison of different Neuroimaging techniques and reveals potential application of machine learning algorithms in medical image analysis; particularly in AD enabling even the early detection of the diseasethe class labelled as Multiple Cognitive
Evolving Morphological and Behavioral Diversity Without Predefined Behavior Primitives

Virtual ecosystems, where natural selection is used to evolve complex agent behavior, are often preferred to traditional genetic algorithms because the absence of an explicitly defined fitness allows for a less constrained evolutionary process. However, these model ecosystems typically pre-specify a discrete set of possible action primitives the agents can perform. We think that this also constrains the evolutionary process with the modellers preconceptions of what possible solutions could be. Therefore, we propose an ecosystem model to evolve complete agents where all higher-level behavior results strictly from the interplay between extremely simple components and where no ‘behavior primitives’ are defined. On the basis of four distinct survival strategies we show that such primitives are not necessary to evolve behavioral diversity even in a simple and homogeneous environment.
"Seeing the Everyday through New Lenses": Pedagogies and Practices of Literacy Teacher Educators with a Critical Stance.

This article explores the practices and pedagogies of six literacy teacher educators with a critical stance. In this qualitative research study, three semi-structured interviews were conducted with each participant over a three-year period. They were able to negotiate a critical stance into their teacher education courses in several ways: using an expansive definition of literacy; helping student teachers shed deficit perspectives; and integrating popular culture and media in the curriculum. The LTEs conceptualizations of literacy transcended traditional notions such as literacy as a set of autonomous skills (e.g., reading, writing) to include expansive notions of literacy including out of school literacy practices such as home literacies and community literacies. The literacy teacher educators modeled valuing expansive conceptions of literacy by including a wide range of texts in their courses, including: videos, blogs, spoken word, spaces, theatre, and social media (e.g., Twitter, Facebook). The teacher educators’ progressive views of literacy were negotiated into their classroom by creating invitations for student teachers to disrupt their assumptions of literacy. Implications for literacy teacher education courses include incorporating a range of texts and genres, which model expansive understandings Pooja Dharamshi is an assistant professr in the Faculty of Education at Simon Fraser University, Burnaby, British Columbia, Canada. Email address: pooja_dharamshi@sfu.ca “Seeing the Everyday Through New Lenses” 8 of literacy, while modeling for student teachers how to effectively integrate them into literacy teaching. Implications for pre-service teacher education programs include building partnerships in the community including both traditional (e.g., schools) and non-traditional (e.g., community centers) learning spaces.
Using spatio-temporal information in API calls with machine learning algorithms for malware detection

Run-time monitoring of program execution behavior is widely used to discriminate between benign and malicious processes running on an end-host. Towards this end, most of the existing run-time intrusion or malware detection techniques utilize information available in Windows Application Programming Interface (API) call arguments or sequences. In comparison, the key novelty of our proposed tool is the use of statistical features which are extracted from both spatial arguments) and temporal (sequences) information available in Windows API calls. We provide this composite feature set as an input to standard machine learning algorithms to raise the final alarm. The results of our experiments show that the concurrent analysis of spatio-temporal features improves the detection accuracy of all classifiers. We also perform the scalability analysis to identify a minimal subset of API categories to be monitored whilst maintaining high detection accuracy.
Histogram-based orientation analysis for junctions

This article presents an algorithm for multiple orientation estimation at junctions which can be used as a first step towards a complete description of the junction structure. The algorithm uses the structure tensor approach to determine the orientations of the edges or lines that meet at a junction and then extracts the principal orientations from a histogram of the orientation angles in a circular region around the junction. In contrast to previous solutions it uses only first-order derivatives and is suited for junctions with an arbitrary number of orientations without increasing the runtime.
Does "Like" Really Mean Like? A Study of the Facebook Fake Like Phenomenon and an Efficient Countermeasure

Social networks help to bond people who share similar interests all over the world. As a complement, the Facebook "Like" button is an efficient tool that bonds people with the online information. People click on the "Like" button to express their fondness of a particular piece of information and in turn tend to visit webpages with high "Like" count. The important fact of the Like count is that it reflects the number of actual users who "liked" this information. However, according to our study, one can easily exploit the defects of the "Like" button to counterfeit a high "Like" count. We provide a proof-of-concept implementation of these exploits, and manage to generate 100 fake Likes in 5 minutes with a single account. We also reveal existing counterfeiting techniques used by some online sellers to achieve unfair advantage for promoting their products. To address this fake Like problem, we study the varying patterns of Like count and propose an innovative fake Like detection method based on clustering. To evaluate the effectiveness of our algorithm, we collect the Like count history of more than 9,000 websites. Our experiments successfully uncover 16 suspicious fake Like buyers that show abnormal Like count increase patterns.
An improved and fast approach to parameter estimation of SFM signal using Carson's rule

Fast parameter estimation of sinusoidal frequency modulation signal (SFM) in additive white Gaussian noise is considered. A technique based on Carson's rule is developed to estimate the frequency modulation index; the carrier frequency is calculated using the symmetrical property of side-frequency components; the instantaneous frequency is computed to get the modulation frequency. The Cramer-Rao lower bound (CRLB) of parameter estimation of SFM is also been derived. Monte Carlo simulations show that the parameter estimation accuracy is acceptable when the SNR is above 6dB.
The Clavius on the Web Project: Digitization, Annotation and Visualization of Early Modern Manuscripts

This paper describes the full procedure adopted in the context of the Clavius on the Web project, which aims to help Web users to appraise the importance of specific manuscripts by going beyond their digital reproduction. The proposed approach is based on the multilayered explication of linguistic, lexical and semantic data representing the innermost nature of the analyzed manuscripts. The final purpose of the project is to gather and display the results of the three layers of analysis through interactive visualization techniques and export them as Linked Data. All the analyses rely on the XML/TEI encoding of the text, followed by a CTS-based tokenization. As a working example for this paper, the analysis of a portion of a manuscript provided by Historical Archives of the Pontifical Gregorian University will be illustrated. The text is a letter written in Latin and sent by Botvitus Nericius to Christophorus Clavius in 1598 from Madrid.
The New Music Industry : - Understanding the Dynamics of the New Consumer of Music

The music industry today is undergoing a revolution with digital distribution of music taking over the traditional sales of physical CDs (Mewton, 2008). The peer-to-peer networking and illegal music piracy is a problem that lately has been widely discussed in forums of ethics, legal issues and economical aspects, followed by a music industry trying to solve the situation with new business models enhancing digital sales, e.g. the tip jar model (Hiatt & Serpick, 2007). The tip jar model embodies the problem the industry is facing since it allows the consumer to choose whether to pay or not. Therefore the question of what leads the consumer to pay instead of download or pirate music has been researched in many aspects. However it has been made to a lesser extent in theory of loyalty and liking and their implications on the new business models’ success and the new consumer of music. Previous research within music piracy has mainly explored demographics, macro- and micro economical perspectives such as artist and record company loss of welfare and consumer surplus (Coyle et al., 2008). We find it of interest to instead further explore the impacts of theories about consumer liking, loyalty and attitudes (Wells & Prensky, 1996; Shiffman & Kanuk, 1987; Solomon et al., 2002) as an addition to this existing knowledge to enhance the understanding about the new consumer of music. The purpose of this thesis is to analyze artist liking, artist loyalty and attitudinal factors’ impact on consumers’ music piracy intentions. The study is an explanatory study based on quantitative data collected in the region of Jonkoping where the collection of data has been conducted by using two questionnaires; one among students at the School of Education and Communication (Jonkoping University) and one at the A6 shopping-center. This data has been summarized to create independent variables used in a multiple regression analysis to calculate their impacts on piracy to confirm or reject the from theory deduced hypotheses. The results from the multiple regression analysis show that the attitudinal factors do not have a direct impact on piracy intentions; however the other two independent variables, measuring the artist loyalty and artist liking have a larger impact. Surprisingly, a higher level of loyalty increases the intentions to pirate music while, as anticipated from theory (Solomon et al., 2002; Shiffman & Kanuk, 1987), higher liking decreases intentions. The conclusion is that the artist liking variable and artist loyalty variable are resulting in a bridge over piracy where the pillars are built of liking and the bridge itself is built of loyalty, stressing the importance of maintaining high levels of liking to maintain purchasing behavior online.
The Quality of School Life Scale as a predictive indicator of student disengagement from school

Sandra M. Lazar The Quality of School Life Scale as a Predictive Indicator of Student Disengagement from School 1999 Dr. Theodore Johnson, University Mentor School Administration The purpose of this ex post facto, action research project is to test the hypothesis that the Quality of School Life Scale (Epstein & McPartland, 1976) has the predictive capability to identify students, early in a school year, who later in the school year manifest traditional disengaged behaviors. If the hypothesis is supported and students who, as a group, score lower on the QSL Scale display significantly more traditional disengaged behaviors than higher scoring students, the finding would support using the QSL as a proactive assessment tool to identify students who are at-risk for disengagement. This study has several phases: the administration of a survey to a class of 420 sophomores of a suburban high school; a "wait and see" period of time of approximately four months; data collection of behavioral manifestations of disengagement; and statistical analysis of the data using correlations, means/anova/t-tests, crosstabulations and percentages, chi-squares, and discriminant analysis. The QSL scale predicted disengaged behaviors with 69% accuracy. The findings indicate that traditional indicators of disengagement may not be the best indicators . that there are silently disengaged students who do not act out in school.
Towards hand biometrics in mobile devices

The increasing demand of security oriented to mobile applications has raised the attention to biometrics, as a proper and suitable solution for providing secure environment to mobile devices. With this aim, this document presents a biometric system based on hand geometry oriented to mobile devices, involving a high degree of freedom in terms of illumination, hand rotation and distance to camera. The user takes a picture of their own hand in the free space, without requiring any ﬂat surface to locate the hand, and without removals of rings, bracelets or watches. The proposed biometric system relies on an accurate segmentation procedure, able to isolate hands from any background; a feature extraction, invariant to orientation, illumination, distance to camera and background; and a user classiﬁcation, based on k-Nearest Neighbor approach, able to provide an accurate results on individual identiﬁcation. The proposed method has been evaluated with two own databases collected with a HTC mobile. First database contains 120 individuals, with 20 acquisitions of both hands. Second database is a synthetic database, containing 408000 images of hand samples in different backgrounds: tiles, grass, water, sand, soil and the like. The system is able to identify individuals properly with False Reject Rate of 5.78% and False Acceptance Rate of 0.089%, using 60 features (15 features per ﬁnger)
Imagined motor action and eye movements in schizophrenia

Visual exploration and planning of actions are reported to be abnormal in schizophrenia. Most of the studies monitoring eye movements in patients with schizophrenia have been performed under free-viewing condition. The present study was designed to assess whether mentally performing an action modulates the visuomotor behavior in patients with schizophrenia and in healthy controls. Visual scan paths were monitored in eighteen patients with schizophrenia and in eighteen healthy controls. Participants performed two tasks in which they were asked either to (1) look at a scene on a computer screen (free viewing), or (2) picture themselves making a sandwich in front of a computer screen (active viewing). The scenes contained both task-relevant and task-irrelevant objects. Temporal and spatial characteristics of scan paths were compared for each group and each task. The results indicate that patients with schizophrenia exhibited longer fixation durations, and fewer fixations, than healthy controls in the free viewing condition. The patients' visual exploration improved in the active viewing condition. However, patients looked less at task-relevant objects and looked more at distractors than controls in the active viewing condition in which they were asked to picture themselves making a sandwich in moving their eyes to task-relevant objects on an image. These results are consistent with the literature on deficits in motor imagery in patients with schizophrenia and it extends the impairment to visual exploration in an action imagery task.
Intenção dos Alunos em Seguir Carreira na Área de Contabilidade sob a Perspectiva da Teoria do Comportamento Planejado

Objective: What are the students' intentions related to the profession and, consequently, their career when taking the undergraduate course in Accounting? In view of the diverse options the professionals of the area have in the market, this study investigates the factors that influence the behavioral intention of the students in all phases at a federal university of the South of Brazil to follow a career in the accounting area, in the framework of the Theory of Planned Behavior. Method: Data collection was performed through a questionnaire applied to 302 students. For the analysis of the data, we used descriptive statistics, factorial analysis and Structural Equations. Results: The results obtained emphasize that the opinions of professionals in the area, friends and partners are relevant for this decision. It is also inferred that the students do not see the careers of the accounting profession accompanied by acknowledged status and prestige; that remunerations are not good; and that there are no good opportunities available in the market. Contribution: The research results contribute to clarify factors that can significantly influence the students' intention to pursue a career in the area they study in, and may also provide inputs on aspects that need to be improved to stimulate students' interest.
PCNA acts as a stationary loading platform for transiently interacting Okazaki fragment maturation proteins

In DNA replication, the leading strand is synthesized continuously, but lagging strand synthesis requires the complex, discontinuous synthesis of Okazaki fragments, and their subsequent joining. We have used a combination of in situ extraction and dual color photobleaching to compare the dynamic properties of three proteins essential for lagging strand synthesis: the polymerase clamp proliferating cell nuclear antigen (PCNA) and two proteins that bind to it, DNA Ligase I and Fen1. All three proteins are localized at replication foci (RF), but in contrast to PCNA, Ligase and Fen1 were readily extracted. Dual photobleaching combined with time overlays revealed a rapid exchange of Ligase and Fen1 at RF, which is consistent with de novo loading at every Okazaki fragment, while the slow recovery of PCNA mostly occurred at adjacent, newly assembled RF. These data indicate that PCNA works as a stationary loading platform that is reused for multiple Okazaki fragments, while PCNA binding proteins only transiently associate and are not stable components of the replication machinery.