Miracle-dz/UniFAR-FTUs huggingface dataset:
EFFICIENT APPROXIMATION OF SOCIAL RELATEDNESS OVER LARGE SOCIAL NETWORKS AND APPLICATION TO QUERY ENABLED RECOMMENDER SYSTEMS

Social relatedness measures such as the Katz score and the commute time between pairs of nodes have been subject of significant research effort motivated by social network problems including link prediction, anomalous link detection, and collaborative filtering. In this thesis, we are interested in computing: (1) the score for a given pair of nodes, and (2) the top-k nodes with the highest scores from a specific source node. Unlike most traditional approaches, ours scale to large networks with hundreds of thousands of nodes. We introduce an efficient iterative algorithm which calculates upper and lower bounds for the pairwise measures. For the top-k problem, we propose an algorithm that only has access to a small subset of nodes. Our approaches rely on techniques developed in numerical linear algebra and personalized PageRank computing. Using three real-world networks, we examine scalability and accuracy of our algorithms as in a short time as milliseconds to seconds. We also hypothesize that incorporating item based tags into a recommender system will improve its performance. We model such a system as a tri-partite graph of users, items and tags and use this graph to define a scoring function making use of graph-based proximity measures. Exactly calculating the item scores is computationally expensive, so we use the proposed top-k algorithm to calculate the scores. The usefulness and efficiency of the approaches are compared to a simple, non-graph based, approach. We evaluate these approaches on a combination of the Netflix ratings data and the IMDb tag data.
E-Assessment Tools for Programming Languages: A Review

Continuous Evaluation and feedback not only helps in improving learning of a student, but also acts as a constant motivator to put in more efforts. But then, feedback and assessment are very difficult and time consuming in practice. Thus, automating the entire system of assessment, evaluation and feedback will be highly beneficial. But, building such tools for all courses is yet not feasible. However, e-assessment tools for programming courses in Computer Science discipline can be developed. In this paper, we review various grading techniques used by these tools to assess a student’s programming assignment. Further, this paper discusses various types and features of tools according to which an appropriate tool should be selected. And, in the end, we will be highlighting the extent to which students and instructors are actually benefited by these
Analysis of Online Learning Style Model Based on K-means Algorithm

—Adaptive learning system is an ontology-based system that will provide relevant learning resources as a personalized bespoke online learning package for the learner based on their pedagogical needs. Thus, learner modeling and resources modeling need to be done in order to implementing the adaptive mechanism. Learning styles which refer to learners’ preferred ways to learn can play an important role in learner modeling. This paper, by reviewing existing learning style theories and comparing the differences between traditional learning and online learning, proposes a new learning style model for online learning environment. What’s more, an online learning style survey is designed for investigating learners’ preferences and learning behavior. Then a classification rule for online learning style is discussed after mining the collected data based on k-means clustering algorithm. The results offer insights into a different classification mechanism for learning styles and prove the feasibility of the new online learning style model.
Algorithm Designing for Searching in Unstructured Peer-to-Peer Network

Peer-to-Peer system is now one of the fastest growing and most popular applications. Centralize Peer to peer systems always suffer from the problems of single point of failure, low availability, denial of service attacks. Searching of the required data is a vital issue in both centralized and decentralized P2P network. Many methods have been implemented for searching in P2P network such as Flooding, Random Walk, Expanding Ring or Iterative deepening, K-Walker Random Walk, etc. Some of these generate large traffic while others take long searching time. A probabilistic approach with Two Level K Walker Random Walk for searching has been studied and enhanced in this paper so that these issues can slightly overcome. Advantages of two level walk are further reducing collision of nodes and helping in searching the distant nodes. But it has slightly increased the response time. This disadvantage can be overcome when there are a lot of dull nodes in the network with this enhancement.
Intelligent Web Programming AI System using Automatic Speech Recognition Technique

The objective is to develop an Artificially Intelligent System which helps in designing static web pages for the physically challenged people who have lost their limbs. This system detects the voice signal of the user who wants to create the webpage using Automatic Speech Recognition technique by implementing Hidden Markov Model [1][2] . It obtains the required parameters and creates the corresponding web pages using BBS system with the final decision authority rests with the user.
Opportunistic networking in OMNeT

We describe mechanisms for simulating opportunistic and delay-tolerant networks in the OMNeT++ discrete event simulator. The mechanisms allow for simulating open systems of wireless mobile nodes where mobility- or contact traces are used to drive the simulations. This way mobility generation is separated from the core OMNeT++ protocol simulations which facilitates importing synthetic or real data from external mobility generators, real mobility tracking data or real contact traces. The paper describes the design and implementation of our mechanisms for OMNeT++ and gives an example of how we have used these to simulate opportunistic wireless content distribution in an urban environment.
Reduced instruction set computer architectures for VLSI

Integrated circuits offer compact and low-cost implementation of digital systems, and provide performance gains through their high-bandwidth on-chip communication. When this technology is used to build a general-purpose von Neumann processor, it is desirable to integrate as much functionality as possible on a single chip, so as to minimize off-chip communication. Even in Very Large Scale Integrated (VLSI) circuits, however, the transistors available on the limited chip area constitute a scarce resource when used for the implementation of a complete processor or even computer, and thus, they have to be used effectively. This dissertation shows that the recent trend in computer architecture towards instruction sets of increasing complexity leads to inefficient use of those scarce resources. We investigate the alternative of Reduced Instruction Set Computer (RISC) architectures which allow effective use of on-chip transistors in functional units that provide fast access to frequently used operands and instructions. In this dissertation, the nature of general-purpose computations is studied, showing the simplicity of the operations usually performed and the high frequency of operand accesses, many of which are made to the few local scalar variables of procedures. The architecture of the RISC I and II processors is presented. They feature simple instructions and a large multi-window register file, whose overlapping windows are used for holding the arguments and local scalar variables of the most recently activated procedures. In the framework of the RISC project, which has been a large team effort at UC Berkeley for more than three years, a RISC II nMOS single-chip processor was implemented, in collaboration with R. Sherburne. Its microarchitecture is described and evaluated, followed by a discussion of the debugging and testing methods used. Future VLSI technology will allow the integration of larger systems on a single chip. The effective utilization of the additional transistors is considered, and it is proposed that they should be used in implementing specially organized instruction fetch-and-sequence units and data caches. The architectural study and evaluation of RISC II, as well as its design, layout, and testing after fabrication, have shown the viability and the advantages of the RISC approach. The RISC II single-chip processor looks different from other popular commercial processors: it has been less total transistors, it spends only 10% of the chip area for control rather than one half to two thirds, and it required about five times less design and lay-out effort to get chips that work correctly and at speed on first silicon. And, on top of all that, RISC II executes integer, high level language programs significantly faster than these other processors made in similar technologies.
Analysis on visual design principles of a webpage

Web page means a document which is to be shown on a browser and its design must be internet user based. The crucial aspect of a webpage design fabricated represents the content in webpage and it must be understood by user very effectively This paper/tabloid/thesis particularises/specifies on a decent visual style will build the interactive programs understood and be employed by a lot of precisely, the analytics is that the measuring, assortment and analysis of web page information. Page statistics and user metrics square measure the necessary consider most of the online analytics tool. To convey the certain information, we must design exact emotions regarding what the web page is of about. A unique and individualised emotional/expressive style of a website will impress web users deeply, initiate web users to click/tick sharply/promptly.
The Evidence Base of Clinical Diagnosis

Dr Knottnerus believes that, while ample attention has been given to the evidence basis for therapeutics, formal evaluation of diagnostic methods has been unjustly neglected. With The Evidence Base of Clinical Diagnosis he aims to help not only researchers but also clinicians and students who wish to get a grip on the scientific principles. One would be hard pushed to imagine a better example of globalization than this book, published by the BMJ in London with authors drawn from the Netherlands, the USA and Australia, type set in India and printed in Spain. Contributors discuss the objectives of diagnostic testing and the challenges of designing studies to evaluate these procedures. The various options are dealt with in detail—for example, the cross-sectional study, the randomized controlled trial, and the before-and-after study as well as the systematic review—with a warning that results cannot always be extrapolated from one environment to another, such as hospital to primary care. The reader is offered formulas for calculating sensitivity, specificity, likelihood ratios and other indices that will aid analysis. A chapter on computer-aided diagnosis adopts a general approach, and I would have liked more examples of how computers can change clinical practice (if they do). Of particular interest to me was a discussion of the psychological and cognitive processes involved in clinical reasoning; it offers practical tips on how an experienced clinician can impart personal strategies to students and junior doctors. I was less happy with the contributions on how to improve test-ordering, because they start from the assumption that a great many diagnostic tests are unneccesary and are requested for no clear reason. The discussion focuses, rather predictably and one-sidedly, on the use of medical education, guidelines and other doctor-oriented interventions to reduce test-ordering. The changes that have taken place in society—in terms of patient expectations and the ever more demanding litigation culture—are not really explored. One weakness of the whole book is a failure to examine the issue of diagnostic tests from the patient's viewpoint, and in particular the reassurance value that patients gain from a negative test result. And, not least, there are the vital medicolegal implications of having done or not done a diagnostic investigation. My personal reservations about the book stem partly from its global origins. In many developed health system it may well be true that diagnostic tests are being over-ordered. I need to be persuaded that this applies to the British National Health Service, which has suffered rather from a lack of diagnostic facilities. Nevertheless, this well-written text will be useful to its target audience.
Sistema Ciber-Físico de una CNC para la producción de circuitos impresos

One of the most significant developments of electronic systems and their integration with information technology and communication trends, is represented by Cyber Physical Systems (CPS). The latter are associates with computer systems, which are closely related with: the physical world and its processes; provide and use at the same time, data access services and information processing, both available on the Internet; reconfigurability of control systems and processes; and in general with the characteristics of the Internet of Things (IoT), including industrial type or I 2 oT. First, CPS´s depend on the newest and foreseeable future development of information technologies, and on the other hand, of the science and technology of their physical production. Thus, these are a fundamental part of what can lead to the fourth industrial revolution, which has been frequently identified as the Industry 4.0. This paper presents the design of a computerized numerical control (CNC) for manufacturing printed circuit boards and their integration with simulation, and with Cyber-physical system characteristics. Within the context of an automated electronic control, it was proposed visualize the behavior of the system from sensors and actuators connected to a data acquisition card, which interact with a 3-D display platform.
Gaussian process learning for cyber-attack early warning

Network security has been a serious concern for many years. For example, firewalls often record thousands of exploit attempts on a daily basis. Network administrators could benefit from information on potential aggressive attack sources, as such information can help to proactively defend their networks. For this purpose, several large-scale information sharing systems have been established, in which information on cyberattacks targeting each participant network is shared such that a network can be forewarned of attacks observed by others. However, the total number of reported attackers is huge in these systems. Thus, a challenging problem is to identify the attackers that are most relevant to each individual network (i.e. most likely to come to that network in the near future). We present a framework to estimate the relevance of each attacker with respect to each network. In particular, we model each attacker's relevance as a function over the networks. Different attackers have different functions. The distribution of the functions is modeled using a Gaussian process (GP). The relevance function of each attacker is then inferred from the GP, that itself is learned from the collection of attack information. We test our framework on the attack reports in the DShield information sharing system. Experiments show that attackers found relevant to a network by our framework are indeed more likely to come to that network in the future. Copyright © 2009 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 3: 56-68, 2010 The majority of the work was done while the author was working at SRI International.
Acute intensity and motivation to play: comparison of structured and unstructured active video games - a pilot study

Objective: To compare intensity (heart rate, oxygen consumption, and perceived exertion) and motivation to play between AVG types (unstructured, UNS-AVG and structured, S-AVG). Methods: A Pre-test-Post-test experimental study with randomized counterbalanced groups (UNS- and S-AVG type) was performed at the laboratory. Eight male young adults [Mean (SD), age: 19(1) years, body mass index: 23.1(2.4) kg/m²] volunteered to participate in this study. Participants underwent a diagnostic evaluation for health status, anthropometric, cardiovascular and metabolic measures. After this, they were paired according to oxygen consumption levels and randomly assigned to each group and performed a 30-min AVG session (UNS-AVG: Kinect Sports Boxing game or S-AVG: Nike Kinect Training game). Heart rate (HR) was recorded during all AVG session. At the end of the session, motivation to play and rating of perceived exertion (RPE) were self-reported. Oxygen consumption estimated for the AVG session was obtained by linear regression line from HR reached during the game and maximal HR during the test session. Unpaired t-test was used to compare game type groups (P<0.05). Moreover, effect size (ES) was calculated using Cohen’s d statistic. Results: Average HR (%Δ=7.1, P=0.025, ES=0.76) and oxygen consumption estimated (%Δ=69.5, P=0.002, ES=3.63) during the sessions were greater for S-AVG compared to UNS-AVG. Motivation to play was similar between groups (%Δ=18.2, P=0.685, ES=0.72). RPE was greater for S-AVG compared to UNS-AVG group (%Δ=20.6, P=0.045, ES=1.85). Conclusion: S-AVG type requires more physical exertion than UNS-AVG; however, these AVG types can be used interchangeably if the goal is motivation. Due to the strong correlation between the HR and oxygen consumption for both AVG types, this data suggests that S-AVG may be a better tool to exercise and probably contribute to reducing sedentary lifestyle more than UNS-AVG in young adults.
Estimation Load Forecasting Based on the Intelligent Systems

The daily peak load forecasting for the next day is the basic operation of generation scheduling. The approach of using ANN methodology alone is limited which has generated interest to explore hybrid system. In this paper a search of genetic programming to a short term load forecasting is presented. A genetic architecture with the fitness normalization has been used to find as optimum data peak load of Baghdad city. The optimize data applied to the ANN to be trained and tested to estimate the daily peak load of Baghdad city. Different cases for load forecasting are considered with the aid of MATLAB 7 package to get the estimation of the next day. So an improvement method of genetic optimization is proposed to get a better solution for the load estimation rather than artificial neural network.
CONSTRAINTS THROUGH THE AGES: LOANWORDS IN BANGLA

This paper looks at loanwords in Bangla from Sanskrit and four non- Indian languages, Persian, Arabic, Portuguese and English, with a view to explaining loanword adaptation in an Optimality-theoretic framework of phonology. The data in Bangla fall into two categories in their treatment and level of adoption into native Bangla: Arabic/ Persian and Portuguese/English. Finding a division of the Bangla lexicon into Tadhbava , Tatsama and Other Borrowing (Kar 2009) inadequate to account for the syllable structure rules and rules of gemination in Bangla, we identify the core and periphery of Bangla in terms of the history of the language. Based on data from different stages, we show how the rankings of the Optimality-theoretic constraints changed over time from Faithfulness to Markedness. Â
Research on Distributed File System Framework Based on Solid State Drive

As the computing power of high performance computing (HPC) systems is developing to exascale, and Big data application tends to be I/O intensive, the storage system is facing high I / O traffic. The poor performance of disk has gradually become the bottleneck of storage system. In recent years, Flash technology has developed rapidly, Flash-based Solid State Drive (SSD) has been widely used in HPC, adding SSD into the storage system can improve the performance of the storage system. In this paper, we designed DSFS, a user-level distributed file system based on SSD. DSFS uses SSD as the underlying storage medium, and adopts Infiniband RDMA (Remote Direct Memory Access) transmission mechanism. The test result shows that DSFS improves the performance of HPC storage system effectively.
Clock frequency synchronisation in OFDM system for power line communications

Orthogonal frequency division multiplexing (OFDM) divides the available spectrum into several narrowband subchannels. To obtain a high spectral efficiency, the frequency responses of the subchannels are overlapping and orthogonal. An OFDM system can suffer from two types of frequency errors-a carrier frequency offset and a master clock frequency offset. Both types of frequency error degrade the performance of the OFDM receiver by loosing orthogonality between the subcarriers and introducing interchannel interference. Since the power line communications are performed in the baseband, only the second type of frequency error can occur. This paper analyses the effect of master clock frequency offset and suggests a method for its estimation based on the pilot signal. Furthermore, a method for frequency error correction is presented.
Reliable and resilient access network design for advanced metering infrastructures in smart grid

Maintaining a high overall network reliability remains one of the most critical requirements for advanced metering infrastructures (AMIs) in smart grid. Ensuring reliable networks not only determines the robust communications of an AMI, but also guarantees assured information delivery in the access network. To prevent any communication failures, incremental designs based on legacy networks should be carried out in advance to improve the overall redundancy. Current communication architecture of an AMI follows a traditional access network structure with a tree-based topology, which does not always satisfy high robustness and is prone to network failures. To address the challenge, this study conducts a reliability study of the access network in an AMI. Specifically, this study first examines the basic network topology adopted in an AMI access network and its underlying connectivity issues. Secondly, this study proposes two practical solutions as parts of incremental network design to improve the communication robustness of existing communication architectures. Thirdly, mathematical models are formulated to solve network connectivity problems, for maintaining a high overall network reliability, while minimising the communication deployment cost at the same time. Simulation results are provided from the aspects of minimal path sets and minimal cut sets to demonstrate the redundancy analysis.
What have labels ever done for us? The linguistic shortcut in conceptual processing

ABSTRACT How does language affect cognition? Is it important that most of our concepts come with linguistic labels, such as car or number? The statistical distributions of how such labels co-occur in language offers a rich medium of associative information that can support conceptual processing in a number of ways. In this article, I argue that the role of language in conceptual processing goes far beyond mere support, and that language is as fundamental and intrinsic a part of conceptual processing as sensorimotor-affective simulations. In particular, because linguistic association tends to be computationally cheaper than simulation (i.e. faster, less effortful, but still information-rich), it enables an heuristic mechanism that can provide adequate conceptual representation without the need to develop a detailed simulation. I review the evidence for this key mechanism – the linguistic shortcut – and propose that it allows labels to sometimes carry the burden of conceptual processing by acting in place of simulated referent meanings, according to context, available resources, and processing goals.