Miracle-dz/UniFAR-FTUs huggingface dataset:
Mutual Coupling Effect on Maximum-Ratio Diversity Combiners and Application to Mobile Radio

The mutual coupling effects on an M -branch maximumratio combiner with correlated signal fading in general are considered. The results in the mobile radio case show that the average power delivered to the receiver becomes less as the antenna spacing of an antenna array decreases (i.e., the mutual coupling increases) with either an optimum load network or an optimum resistive load network connected to the antenna array at the front end of the receiver. However, there is not much effect on the power as long as the antenna spacing is equal to or greater than a certain value dependent on the number of the branches M . For M \leq 4 , the required antenna spacing is equal or greater than 0. 2λ. The value for M > 4 increases gradually as M increases. It can be obtained following the same technique. The mutual coupling effect on the cumulative distribution of the signal from an M branch mobile diversity array is also small. Hence for an in-line array with M \leq 4 , the antenna spacing of 0. 2λ can still provide most of the usual diversity advantage.
An Optimization Technique for Image Search in Social Sharing Websites

sharing websites allow users to personalize media. The user can generate, share, tag and comment on media. The large-scale user-generated meta-data not only facilitates users in sharing and organizing multimedia content, but provides useful information to improve media retrieval and management of the websites. Personalized search serves as one of such examples where the web search experience is improved by generating the returned list according to the modified user search intents. In this paper, we exploit the social annotations and propose a novel framework considering both the user and query relevance to learn to personalized image search. The basic premise is to embed the user preference and query-related search intent into user-specific topic spaces. Since the users' original annotation is too sparse for topic modelling, we need to enrich users' annotation pool before user-specific topic spaces construction. The proposed framework contains two components. Firstly a Ranking based Multi-correlation Tensor Factorization model that is proposed to perform annotation prediction, which is considered as users' potential annotations for the images. Secondly we introduce User-specific Topic Modelling to map the query relevance and user preference into the same user-specific topic space. For performance evaluation, two resources involved with users' social activities are employed. Experiments on a large-scale dataset are used to demonstrate the effectiveness of the proposed method.
Computer Clustering Using Home Network

In the last few years computers have come to dominate almost every aspect of our life. It is hard to imagine the modern office or any other workplace without a computer. Moreover, more and more people use computers at home to work or just for fun. Because of their popularity people continue to find new places for their use. Although computers increase in sophistication every six months, the software and problems that people want to solve in using them have become increasingly complex and demand more computer power. The simplest solution would be to build a more powerful computer or supercomputer, depending on the scale of the problem. However, this is not an available option for two reasons: the limits of technology and the very high cost of this kind of computer. To overcome these problems, programmers had the idea to connect computers together using a network, creating a computer cluster. This paper will discuss a few clustering solutions/technologies that might be used by home computers, increasing their calculation power and graphic capabilities, such as Mosic/openMosci, OpenSSI, Nvidia SLI, BOINC and ClusterKnoppix.
Privacy in Ubiquitous Computing

Privacy is by no means a recent addition to the Ubiquitous Computing (ubicomp) research curriculum. In his 1991 Scientific American article, Mark Weiser already identified it as one of its biggest challenges: “Perhaps key among [the social issues that embodied virtuality will engender] is privacy: hundreds of computers in every room, all capable of sensing people near them and linked by high-speed networks, have the potential to make totalitarianism up to now seem like sheerest anarchy. ” [1] It would be nice if by now, almost two decades later, we would have a standard set of solutions that we could easily prescribe for any ubicomp system (or any computer system in general): “in order to protect privacy, implement subroutines A, B, and C. ”
Using peak analysis for identifying lagged effects between software metrics.

Measures extracted from software repositories tend to be collected on a regular basis (often daily), forming time series of data. In this context, it is normal to assume that some of the measures collected are having an effect on other measures, potentially with some delay (or “lag”) in the effect. Such delay in the effect may even vary over time, making the identification of the effect difficult. In this paper, we present our initial ideas on a simple analysis method for such situation, in which peaks from the two time series in question are analyzed, and similar ones are
Pushing Novelty Criterion into Incremental Mining Algorithm

Summary Classification is an important problem in data mining. Decision tree induction is one of the most common techniques that are applied to solve the classification problem. Many decision tree induction algorithms have been proposed based on different attribute selection and pruning strategies. Massively increasing volume of data in real life databases has motivated researchers to design novel and incremental algorithms for decision tree induction. In this paper, we propose an incremental tree induction algorithm that integrates novelty criterion during tree induction. One of the main features of the proposed approach is to capture the user background knowledge, which is monotonically augmented. The incremental classifier that reflects the changing data and the user beliefs is attractive in order to make the over all KDD process more effective and efficient. We tested the proposed classifier and experiment with some public datasets and found the results quite promising.
A solution space approach to achieving partially adaptive arrays

Linearly-constrained adaptive arrays have wide application for interference rejection. The authors introduce a method of adding constraints so as to reduce the total number of degrees of freedom available to the processor. For the case of arrays containing a large number of elements, this is a particularly useful approach to providing reduced computational load while preserving the interference rejection capabilities of the array. These additional constraints are chosen to efficiently constrain the adaptive weight vector solution space. The resulting reduced complexity adaptive array is shown to have remarkably good sidelobe control over a wide range of interference conditions. <<ETX>>
The learnability of syntactic categories

"It is a common position in generative acquisition studies to accept Chomsky's view that first language acquisition is determined by a set of innate grammatical a priories. The development of the child would be more a matter of biological maturation than a matter of input-control. Because language universals are innate in the human mind, they cause grammar to grow into the mind almost automatically under the slightest provocations. Early child language would already show the relevance the grammatical a priories. Generative grammarians guided by this view have often drawn far-reaching conclusions about the structure of early child language. The present paper will present an alternative view, the derivation of UG principles from structural acquisition steps. It acknowledges that it is indeed a sentence-generating system that is acquired, but contends that generative systems are learned from the language-specific input material. The basic argument for this approach is that all eventual ‘UG’ properties are identified due to local relations with language specific shapes. One might see the language specific shapes as an entrance to the UG distinctions. Unless a grammar offers a way to identify UG properties, it will not be learnable. This suggests that UG properties may be seen as the outcome of an acquisition procedure rather than being its source"
Dynamic scheduling of network updates

We present Dionysus, a system for fast, consistent network updates in software-defined networks. Dionysus encodes as a graph the consistency-related dependencies among updates at individual switches, and it then dynamically schedules these updates based on runtime differences in the update speeds of different switches. This dynamic scheduling is the key to its speed; prior update methods are slow because they pre-determine a schedule, which does not adapt to runtime conditions. Testbed experiments and data-driven simulations show that Dionysus improves the median update speed by 53--88% in both wide area and data center networks compared to prior methods.
Static Heuristic task scheduling in tree based Environment

The emergence of grid computing has facilitated the linking of heterogeneous and widely distributed resources. A suitable and efficient scheduling algorithm is needed to schedule users jobs to distributed resources. So grid scheduling is an important research area. A tree based grid platform is employed because most of network models can be simplified into tree-based models to resolve and to use parallel processing in grid computing environment. The objective of this paper is to schedule task groups on a tree-based grid computing platform, where resources have different speeds of computation and communication. Due to job grouping, communication of coarse-grained jobs and resources optimizes computation/communication ratio. For this purpose, the multi-level tree is reduced to a single level tree. To transform a multilevel tree to a single level tree push-pull algorithm is used. The proposed approach employs a static distributed heuristic task scheduling algorithm for establishing efficient mapping between tasks and available resources. This scheduling strategy groups the user jobs according to a particular Grid resource’s processing capability, and sends the grouped jobs to the resource. Job grouping in tree based grid environment enhances the computation/communication ratio.
Vehicle Threat Locating via the Detection of Anomalies on Roads and Their Verges

Situational awareness originating from advanced sensor systems augments the ability of sound decision making. This paper considers the image analysis problem given a multi-sensor system mounted on an army patrol vehicle that serves as an early threat alert mechanism. Hence, it concerns forward looking sensors that move through a complex environment whilst detecting events or points of interest. The objective comprises identifying potential threats to the vehicle such as Improvised Explosive Devices (IED). This paper focuses on how an optical sensor and a forward-looking infrared (FLIR) are exploited for detecting and tracking stationary anomalies on the road’s surface and verges. The applied approach consists of a road scene analysis that extracts the road’s surface and verges followed by anomaly detection in each of the extracted regions separately. The detected anomalies from both sensors are tracked and combined in geographical coordinates where their threat-levels also increase due to the response of other sensors. The proposed methodology was assessed during a full system’s demonstration. The obtained results within a simplified real situation show considerable potential. Scene segmentation, Road extraction, Anomaly detection
EFFECT OF MOODLE ON LEARNING: AN OMAN PERCEPTION

ABSTRACT KEYWORDS: Moodle, I.T. , Online-learning, Instruction, Students attitudes 1. INTRODUCTION: We are rising in a global civilization, and the entire world has become a widespread village. The progression in the technology has influenced and has changed the previous outline and our lives. Oman is one, among the nations, on the rise, determined to advance the pedagogical system, up to the level of flourishing accomplishments. Sultan Qaboos University is the sole national university in the country, serving more than 14000 male and female students. At the College of Science, Department of Computer Science, we have introduced Moodle for the students to get access to the digital material of the Basic Computing Skills next to, traditional face to face instruction, communication through online chat session, e-mails etc. Shift from traditional face to face learning towards digital learning atmosphere like Moodle might have implications on students‟ approaches and attitudes. According to
Development of a MATLAB Toolbox for Mobile Radio Channel Simulators

A profound knowledge of mobile radio channels is required for the development, evaluation, and also assessment at practical conditions of present and future mobile radio communication systems. The modelling, analysis, and simulation of mobile radio channels are important key area in current context. In addition to that, knowledge of channel behaviour in mobile radio communication is extensively recommended for the study of transmitter/receiver performances under different propagation scenarios. Our intention in this research work was to develop various kinds of mobile fading channel simulators using MATLAB and embed them into MATLAB software as a toolbox. Implemented channel simulators were combined MATLAB as a toolbox which users can easily select well-known channel models to test and to study the performance of mobile communication systems. It gives better support for the new users to work on the developed channel simulators, run the test procedures as well as parameter computation. The toolbox contains channel simulators for simulating non-stationary land mobile satellite channel, spatial shadowing processes, MIMO channels, multiple uncorrelated Rayleigh fading channels, mobile to mobile channel, frequency hopping channels etc. Set of test procedures were developed such as the autocorrelation function ACF, average duration of fades ADF, the probability density function PDF, and the level-crossing rate LCR etc., in order to test and to confirm the correctness of the implemented channel simulators. Proposed new algorithms to compute the model parameters of the channel simulators were also implemented in the toolbox to enable the parameterization of the channel simulators under specific propagation conditions. Some of the simulation models were implemented based on specification of GSM system by CEPT-COST 207. DOI: http://dx.doi. org/10.4038/jur.v2i1-2.7853 J. Univ. Ruhuna 2014 2 :40-45
Convex Formulations of Learning from Crowds

It has attracted considerable attention to use crowdsourcing services to collect a large amount of labeled data for machine learning, since crowdsourcing services allow one to ask the general public to label data at very low cost through the Internet. The use of crowdsourcing has introduced a new challenge in machine learning, that is, coping with low quality of crowd-generated data. There have been many recent attempts to address the quality problem of multiple labelers, however, there are two serious drawbacks in the existing approaches, that are, (i) non-convexity and (ii) task homogeneity. Most of the existing methods consider true labels as latent variables, which results in non-convex optimization problems. Also, the existing models assume only single homogeneous tasks, while in realistic situations, clients can offer multiple tasks to crowds and crowd workers can work on different tasks in parallel. In this paper, we propose a convex optimization formulation of learning from crowds by introducing personal models of individual crowds without estimating true labels. We further extend the proposed model to multi-task learning based on the resemblance between the proposed formulation and that for an existing multi-task learning model. We also devise efficient iterative methods for solving the convex optimization problems by exploiting conditional independence structures in multiple classifiers.
Corruption detection in MySQL with the help of checker and logs

In the world of storage Databases are used to store data needed for computer programs. It is basically used to store very sensitive data. Software and hardware failures are main issues under database corruption. To prevent data loss and inconsistency of database after failure, recovery is needed. MySQL DBMS, it has been find that in certain cases, corruption can greatly harm the system, leading to untimely crashes, data loss, or even incorrect results. In this paper some other techniques are defined to enhance the performance of the checker for corruption detection technique with the help of logs. The checker will work according to type of the corruption. If there is any empty values in the data file then checker create a bad log file which will have only inconsistent values. Other records will be inserted in the database. If there is any data type mismatch then checker will be automatically terminated. Index Terms— ARIES, checksum, MySQL corruption, logs, RAID, redo undo operations, recovery management,
Efficient Password Multicast Authentication

This paper contain secure- password authentication involve third party. The previous methods focus on two party authentications who share the password. In the previous method is week against dictionary attack. Our method provide single sign like previous method and also against for on/off-line dictionary attack. This method provides forward securacy and also reduces the damage of single point failure. The plaintext-equivalent is a piece of data, as the compromised password will not allow an adversary to hashed password, which can be used to obtain the same decrypt past sessions. Also, a compromised session level of access that the adversary gets when the key will not allow an adversary to find out a adversary gets the password. These authentication-key password. exchange protocols have been developed for two parties. Tolerating the compromise of a password file: For These cannot provide Single Sign on (SSO) feature in the this, a server must keep not plaintext-equivalent. distributed computing without modification. Avoiding or reducing the damage of the single point Kerberos, which provides SSO, is focused on a of failure: When KDC is compromised in Kerberos, all password-based authentication protocol evolving on-line users and all target servers have to change the trusted third parties. Kerberos is based on a symmetric password and the key. Also, all past session can be cryptosystem and maintains shared secret keys of entities decrypted. in the Key Distribution Center (KDC) (2). Therefore, the Providing different trust level of servers: The trusted Kerberos server must be extremely secure, as it represents third party should not provide any information about a single point of failure for the entire system and all password to target servers. entities. Moreover, Kerberos is fragile to off-line dictionary attacks and cannot provide forward secrecy. Secure Password Authentication for Distributed
Sobre normalização e classificação de polaridade de textos opinativos na web

AVANCO, L. V. ; On normalization and polarity classification of opinion texts on the web. 2015. 102 p. Dissertation (Master degree Computer Science and Computational Mathematics) Instituto de Ciencias Matematicas e de Computacao (ICMC/USP), Sao Carlos SP. Sentiment Analysis or Opinion Mining has as a main goal to process opinions, feelings and subjectivity expressed in texts. The large number of opinions in social media has increased the interest of companies and governments, who have changed their decisionmaking systems. This has caused a great interest in this research area. Opinions are usually expressed by subjective text, and their processing is a hard task. Moreover, reviews posted on the web are of a especial text type, also called user-generated content (UGC), whose processing is a very challenging task, since they differ in many ways from the standard language. This work describes the design of methods and systems aimed at (a) the normalization of UGC texts, through the use of spell checking, substitution of web slangs, case and punctuation correction, and (b) the classification of opinions at document level, especially for reviews of products in Brazilian Portuguese. The method proposed for normalization of UGC is linguistically motivated. For the classification of opinions, which, in this work, consists in assigning a polarity value (positive or negative) to a opinion text, some lexicon-based and machine learning approaches, as well as a combination of both in a new hybrid manner have been implemented and evaluated. We noticed that the text normalization has improved the results of opinion classification for lexicon-based methods. The quality of the sentiment lexicons for Portuguese was extrinsically evaluated. The reliability of the opinions’ authors was verified, since they are used for labeling samples. We concluded that they significantly impact the performance of the opinion classifiers. Finally, we proposed some opinion classifiers for Brazilian Portuguese whose F1-measures values reach 0.84 (lexicon-based approach) and 0.95 (machine learning approach), which are analogous to the the similar systems for other languages, which represent the state of the art in the domain of reviews of products.
Effectiveness of traditional software metrics for object-oriented systems

An acceptable measure of software quality must quantify software complexity. Traditional software metrics such as lines of code, software science and cyclomatic complexity are investigated as possible indicators of complexity of object-oriented systems. This research reports the effects of polymorphism and inheritance on the complexity of object-oriented systems are measured by the traditional metrics. The results of this research indicate that traditional metrics are applicable to the measurement of the complexity of object-oriented systems. <<ETX>>