Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Super-scalable Multicast

Large-Scale multicast applications for the Internet require the availability of multicast protocols that can support multicast groups with many thousand simultaneous members. For this it is crucial that there exist mechanisms to e ciently exchange control information between the members of a group. In this paper, we present a new approach for distributing control information within a multicast group which increases the scalability of multicast applications. Multicast group members are organized as a logical n-dimensional hypercube, and all control information is transmitted along the edges of the hypercube. We analyze the scalability of the hypercube control topology and compare it with tree-based approaches. We show that the hypercube balances the load per member for processing control information better than existing topologies. We use actual data traces of the group membership in an MBONE conference to gain insight into the transient changes of the load at each node. In a subsequent companion technical report [19] we will present a set of soft-state protocol mechanisms that maintain the hypercube topology without requiring any entity to have global state information.
LOHIT : AN ONLINE DETECTION & CONTROL SYSTEM FOR CELLULAR SMS SPAM

The efficient and accurate control of spams on mobile handsets is an important problem. Mobile spam incurs a cost on a per-message basis, degrades normal cellular service, and is a nuisance and breach of privacy. It is also a popular enabler of mobile fraud. In countries such as South Korea and Japan, Mobile Spamming generates almost half of the total SMS traffic. In this paper we propose a novel spam control technique based on random projections, designed to run on SS7 links so that spams are supressed before they reach users. Our is a non Bayesian, non–keyword approach, which rate limits candidate spam messages to foil spammers. We demonstrate using real-world spam messages that random projection is a robust, efficient and accurate method to identify SMS spam. We give a mathematical formulation of the SMS spam problem and demonstrate that it models the real world short message spam paradigm accurately. Based on this formulation, we describe a framework and algorithm to efficiently identify and control spam messages at the SMSC switch of a mobile network.
Journal of Information Technology Education Reliability and Factor Analysis of a Blackboard Course Management System Success: a Scale Development and Validation in an Educational Context Editor: Anthony Scime Blackboard Course Management System Success Theoretical Framework Blackboard Course Managem

Executive Summary The suitability of 52 items for measuring Blackboard course management system success was investigated with the aim of validating the Blackboard CMS success scale in an educational context. Through a survey, the Blackboard course management system (BCMS) success scale was administered to 503 students at the University of Botswana. Data collected were subjected to factor and reliability analysis. A total of 13 items were dropped from the pooled items resulting in the retention of 39 items on the final version. The scale has a Cronbach aloha reliability coefficient of 0. 91. Exploratory factor analysis revealed the items on the final version of the scale loaded on eight factors accounted for 75% of the total scale variance. The empirical results emphasized the importance of assuming a multi-dimensional analytical approach. Therefore, it is important for educational institutions implementing Blackboard CMS to put emphasis on various system success levels. Theoretically, this study contributes significantly to the identification of educational oriented factors (teaching and learning quality, students' self-regulated learning) that may lead to Blackboard CMS by modifying the factors pioneered and revised by Delone and Mclean (1992, 2003). In summary, the study discovered that content quality , system quality, support service quality, teaching and learning quality, self-regulated learning, intention to use, user satisfaction, and net benefits are important dimensions for measuring Blackboard CMS success. The final instrument indicates adequate reliability and validity across educational context in e-learning systems. The study outcome implied that the Blackboard success measure developed in this study can be used to compare success for e-learning systems with specific factors (i.e., content quality, system quality, support service quality, teaching and learning quality, self-regulated learning, user satisfaction and net benefits). If any tertiary education institution implementing e-learning finds itself Material published as part of this publication, either on-line or in print, is copyrighted by the Informing Science Institute. Permission to make digital or paper copy of part or all of these works for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage AND that copies 1) bear this notice in full and 2) give the full citation on the first page. It is permissible to abstract these works so long as credit is given. To copy in all other cases or to republish or to post on a server or to redistribute to lists requires specific permission …
Workbench with Authoring Tools for Collaborative Multi-lingual Ontological Knowledge Construction and Maintenance

An ontological knowledge management system requires dynamic and encapsulating operation in order to share knowledge among communities. The key to success of knowledge sharing in the field of agriculture is using and sharing agreed terminologies such as ontological knowledge especially in multiple languages. This paper proposes a workbench with three authoring tools for collaborative multilingual ontological knowledge construction and maintenance, in order to add value and support communities in the field of food and agriculture. The framework consists of the multilingual ontological knowledge construction and maintenance workbench platform, which composes of ontological knowledge management and user management, and three ontological knowledge authoring tools. The authoring tools used are two ontology extraction tools, ATOM and KULEX, and one ontology integration tool.
Development of a highly sensitive immunohistochemical method to detect neurochemical molecules in formalin-fixed and paraffin-embedded tissues from autopsied human brains

Immunohistochemistry (IHC) is a valuable method for identifying discrete neurochemical molecules by the interaction of target antigens with validated antibodies tagged with a visible label (e.g., peroxidase). We have developed an immunostaining method that is highly sensitive in detection of neurochemical antigens. Our IHC method, which we call the PBTA method, involves a hybrid protocol that implements aspects of both the polymer and avidin-biotin-complex (ABC) methods in combination with biotin-tyramide amplification. When using [Met]-enkephalin as a target antigen, the sensitivity of the PBTA method for IHC was more than 100-fold higher compared with the polymer and ABC methods. In addition, its sensitivity for enzyme-linked immunosorbent assay was about 1,000-fold higher compared with the ABC method. We examined the utility of our IHC method for both chromogenic and fluorescence detection systems used to visualize neurochemical peptides and proteins in formalin-fixed, paraffin-embedded tissues from autopsied human brains. The results convincingly demonstrate that under optimal conditions, our IHC method is highly sensitive without increasing non-specific background activities. Our IHC method could be a powerful tool for detection and visualization of neurochemical antigens that are present even in trace amounts in autopsied human brains.
Unraveling 14-3-3 Proteins in C4 Panicoids with Emphasis on Model Plant Setaria italica Reveals Phosphorylation-Dependent Subcellular Localization of RS Splicing Factor

14-3-3 proteins are a large multigenic family of regulatory proteins ubiquitously found in eukaryotes. In plants, 14-3-3 proteins are reported to play significant role in both development and response to stress stimuli. Therefore, considering their importance, genome-wide analyses have been performed in many plants including Arabidopsis, rice and soybean. But, till date, no comprehensive investigation has been conducted in any C4 panicoid crops. In view of this, the present study was performed to identify 8, 5 and 26 potential 14-3-3 gene family members in foxtail millet (Si14-3-3), sorghum (Sb14-3-3) and maize (Zm14-3-3), respectively. In silico characterization revealed large variations in their gene structures; segmental and tandem duplications have played a major role in expansion of these genes in foxtail millet and maize. Gene ontology annotation showed the participation of 14-3-3 proteins in diverse biological processes and molecular functions, and in silico expression profiling indicated their higher expression in all the investigated tissues. Comparative mapping was performed to derive the orthologous relationships between 14-3-3 genes of foxtail millet and other Poaceae members, which showed a higher, as well as similar percentage of orthology among these crops. Expression profiling of Si14-3-3 genes during different time-points of abiotic stress and hormonal treatments showed a differential expression pattern of these genes, and sub-cellular localization studies revealed the site of action of Si14-3-3 proteins within the cells. Further downstream characterization indicated the interaction of Si14-3-3 with a nucleocytoplasmic shuttling phosphoprotein (SiRSZ21A) in a phosphorylation-dependent manner, and this demonstrates that Si14-3-3 might regulate the splicing events by binding with phosphorylated SiRSZ21A. Taken together, the present study is a comprehensive analysis of 14-3-3 gene family members in foxtail millet, sorghum and maize, which provides interesting information on their gene structure, protein domains, phylogenetic and evolutionary relationships, and expression patterns during abiotic stresses and hormonal treatments, which could be useful in choosing candidate members for further functional characterization. In addition, demonstration of interaction between Si14-3-3 and SiRSZ21A provides novel clues on the involvement of 14-3-3 proteins in the splicing events.
The Uncertainty Principle in Software Engineering Submitted to ICSE'97, 19th International Conference on Software Engineering

This paper makes two contributions to software engineering research. First, we observe that uncertainty permeates software development but is rarely captured explicitly in software models. We remedy this situation by presenting the Uncertainty Principle in Software Engineering (UPSE), which states that uncertainty is inherent and inevitable in software development processes and products. We substantiate UPSE by providing examples of uncertainty in select software engineering domains. We present three common sources of uncertainty in software development, namely human participation, concurrency, and problem-domain uncertainties. We explore in detail uncertainty in software testing, including test planning, test enactment, error tracing, and quality estimation. Second, we present a technique for modeling uncertainty, called Bayesian belief networks, and justify its applicability to software systems. We apply the Bayesian approach to a simple network of software artifacts based on an elevator control system. We discuss results, implications and potential bene ts of the Bayesian approach. The elevator system therefore serves as an example of applying UPSE to a particular software development situation. Finally we discuss additional aspects of modeling and managing uncertainty in software engineering in general.
Libraries for a global networked world: Toward new educational and design strategies

Abstract The growth of the Internet and the World Wide Web means that users expect access to information and the world’s knowledge regardless of geographic or political boundaries. Some approaches think of geographic distances as the primary barriers and use information and computer technologies (ICTs) to enable knowledge transfer across these distances (MacCormack 2002). The concept of a digital global library is a natural extension of these ideas, and the technology to accomplish this would seem to be available. However, as others have pointed out (Nonaka and Takeuchi 1995; von Krogh, Ichijo et al. 2000), the technologies used to manage knowledge have a decidedly western, if not North American, perspective. Culture is rarely taken into account in the design of systems intended to help organizations manage knowledge (Mason 2003). This paper posits that developments in Internet technologies can have a profound effect on the concept of a global library. These technical developments enable new ways for people to interact and for communities to form, and the combined technical and social changes challenge the conventional notion of a library as primarily a means for providing access to information. Future library design and the education of library professionals will benefit from conceiving of a global library as a space and infrastructure that enables different ethnic communities and national value systems to create and maintain “third cultures” (Packman and Casmir 1999) in which knowledge from the distinct communities can be shared and new knowledge developed. Such a conceptualization of the future library suggests that we should reassess the skills and systems that will need to emerge if library professionals are to continue to provide leadership for global knowledge sharing.
An Image Sub-pixel Edge Detection Algorithm of Plant Roots Based on Non-linear Fourth-order Interpolation Method

To improve the accuracy of digital image edge detection, an ENO nonlinear fourth-order interpolation based subpixel edge detection algorithm was proposed in this paper. A stencil was constructed through classical Canny operator, followed by processing gray images to generate gradient images. ENO nonlinear fourth-order interpolation was applied in the gradient direction of target edges, and then subpixel subdivision computation was performed to obtain subpixel accurate locations of target edges, the performance of our edge detection algorithm was compared with that of centered cubic convolution and non-centered cubic convolution based edge detection methods. Simulation results demonstrated that the ENO based interpolation detection algorithm improved the abilities of detecting image edges.
An Efficient Computational Approach for Frictional Analysis in ABAQUS

FEA contact modeling with severe interfacial friction is often associated with computational challenges to obtain converged solutions. The challenges may increase for problems with significant non-linear deformation (e.g., hyperelastic materials) and more sophisticated laws of coefficients of frictions (COF). Thus, objectives of the present paper are to propose an efficient FEA-based approach to model frictional behavior and demonstrate its implementation in ABAQUS. Major idea of the proposed approach is based on an iterative process where several contact frictionless problems are considered instead of an initial frictional model. Frictional behavior is modeled for each iteration in form of given boundary conditions (BC) at the interface. Here, the BCs are calculated using corresponding FEA predictions obtained at previous iteration according to known constitutive law of COF. The iterative process continues until desired accuracy is satisfied. Implementation of the approach in ABAQUS is considered in detail. Extremely robust nature of the approach is computationally illustrated on several simple representative examples. Validation with available exact analytical solutions is presented and high accuracy of FEA predictions is emphasized.
Financial market integration, corporate financing and economic growth* Final report (22 November 2002)

This study provides a thorough assessment of the likely effects of financial market integration on the ability of European countries to grow faster and on how the possible benefits will be distributed among the Community countries and industries. It achieves several conclusions strongly supportive of the idea that promoting financial market integration is an important step in promoting economic growth in Europe.
Medical Disorder Recognition with Structural Support Vector Machines

In this paper we present two systems that address the issues of disorder recognition and normalization submitted by the authors as defined by the CLEF/ShARe Evaluation Lab. The first approach to the tasks formed a baseline approach using the cTakes system. Our second approach leveraged Structural Support Vector Machines with an array of feature types including lexical, semantic and cluster based knowledge. The recognition differs from typical NER tasks in that disorder spans may be disjoint i.e. a disorder can be non-contiguous. To address this issue we introduce a new tag type to annotate tokens occurring between disorders.
An Efficient Way of Breaking Value Symmetries

Several methods for breaking value symmetries have been proposed recently in the constraint programming community. They can be used in conjunction with variable symmetry breaking methods. However, this combination does not break all symmetries in general. We present a combination of lex constraints and element constrants that can be used to break all combinations of variable and value symmetries. It is the first time to our knowledge that it is possible to break all combinations of value and variable symmetries by adding constraints. This method is quite efficient when the number of symmetries is not too large, as shown by experiments using graceful graph problems. We also present a new global constraint that deals with the case where there are too many value symmetries. Experiments show that this is highly effective.
Long-Term Impact of War on Healthcare Costs: An Eight-Country Study

Objective Exposure to war can negatively affect health and may impact on healthcare costs. Estimating these costs and identifying their predictors is important for appropriate service planning. We aimed to measure use of health services in an adult population who had experienced war in the former-Yugoslavia on average 8 years previously, and to identify characteristics associated with the use and costs of healthcare. Method War-affected community samples in Bosnia-Herzegovina, Croatia, Kosovo, FYR Macedonia, and Serbia were recruited through a random walk technique. Refugees in Germany, Italy and the UK were contacted through registers, organisations and networking. Current service use was measured for the previous three months and combined with unit costs for each country for the year 2006/7. A two-part approach was used, to identify predictors of service use with a multiple logistic regression model and predictors of cost with a generalised linear regression model. Results 3,313 participants were interviewed in Balkan countries and 854 refugees in Western European countries. In the Balkan countries, traumatic events and mental health status were related to greater service use while in Western countries these associations were not found. Participants in Balkan countries with post traumatic stress disorder (PTSD) had costs that were 63% higher (p = 0.005) than those without PTSD. Distress experienced during the most traumatic war event was associated with higher costs (p = 0.013). In Western European countries costs were 76% higher if non-PTSD anxiety disorders were present (0.027) and 63% higher for mood disorders (p = 0.006). Conclusions War experiences and their effects on mental health are associated with increased health care costs even many years later, especially for those who stayed in the area of conflict. Focussing on the mental health impact of war is important for many reasons including those of an economic nature.
Measuring P2P network topology through geo-location-aware distributed crawlers

Network topology information of peer-to-peer applications is useful for examining their characteristics as well as defining an accurate model to simulate their behaviors. Unfortunately, dynamic behaviors of peers such as join and leave make it difficult to obtain the accurate network topology information. In this paper, we propose a method to accurately measure the topology of a Winny network even under heavy churns by observing search queries through a geographically distributed crawling system. After obtaining topology information from the crawling system, we attempt to identify important nodes, the removal of which would partition the network as an example characterization of the Winny network. We evaluate which metric such as node degree, betweenness centrality, and conductivity efficiently identifies such important nodes.
A cross-layer MAC protocol for contention reduction and pipelined flow optimization in wireless sensor networks

In this paper, we present a novel contention based cross-layer synchronous MAC protocol, CROP-MAC, to reduce the end-to-end transmission delay and energy consumption by optimizing the pipelined flow of data packets in wireless sensor networks. CROP-MAC optimizes pipelined flow with the help of staggered sleep/wake scheduling, efficient synchronization and appropriate use of routing layer information. Staggered sleep/wake scheduling and routing layer information enable CROP-MAC to schedule source to sink transmission of multiple data packets in a single cycle. We evaluate CROP-MAC through ns-2.35 simulations and compare it with PMAC, PRMAC and BulkMAC. Simulation results show, CROP-MAC outperforms best of the three protocols by 608.89 %, 14.36 % and 12.5 % in terms of end-to-end transmission delay, packet delivery ratio and energy consumption, respectively.
A Survey of Various Image Compression Techniques for RGB Images

In this earlier multimedia scenario, the various disputes are the optimized use of storage space and also bandwidth. In order to shrink the storage space of pictures and transmission of information with customize limited bandwidth availability, Image compression plays a crucial role by retreating the size of image and to exploit the bandwidth in economical and valuable manner without demeaning the superiority of image. In this paper we explore the review of different compression of images with their pros and cons. The overall compression process helps to reach a satisfactory level for image transmission in limited bandwidth over a telecommunication medicine application. We analyzed the performance of image compression technique using quality metrics such as Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Compression Ratio (CR). The obtained results show that local thresholding provides better reconstruction of image than Global thresholding.
Emotional speech conversion based on spectrum-prosody dual transformation

A dual transformation system to transform neutral speech to emotional speech is proposed in this paper. Since spectral and prosodic features are key factors that influence the emotional effects of speech, Gaussian Mixture Model (GMM) method and the prosody rules algorithm are applied to transform the spectral and prosodic features respectively. In this paper, we transform neutral speech to angry, happy and sad speech. The training corpus is taken from Danish speech database, and the corpus used to transform is taken from the Berlin Database of Emotional Speech. It is shown in the listening test that the speech synthesized by the proposed method is perceived to portray the targeted speech emotion well. It also shows that emotions can be independent of human language from the same language family.