Miracle-dz/UniFAR-FTUs huggingface dataset:
A dual-mode model predictive controller for robot formations

Control of nonholonomic autonomous robots by using an input-output feedback linearization technique has been well explored. It has been noted that model predictive control (MPC) methods may have advantages over state feedback laws when applied to mobile robots, including consideration of constraints on inputs or state vectors. However, MPC algorithms require on-line optimization, resulting in a significant computational burden for large systems or formations of robots. In this paper, we develop a dual-model MPC algorithm which uses an input-output feedback linearization controller for states-within a specified terminal constraint set. Control of formations of nonholonomic robots in leader-follower configurations is simulated off-line, and performance characteristics of the dual-mode MPC controller are contrasted with those of the input-output feedback linearization controller alone.
A new formulation of bubble dynamics for sonoluminescence

A new model of bubble dynamics is constructed for the study of the recently discovered single‐bubble sonoluminescence (SBSL). In the model, the effects of nonequilibrium evaporation and condensation at a bubble wall and that of thermal conduction both inside and outside a bubble are taken into account. Numerical calculations are performed under a condition of SBSL and that of non‐light‐emission. The most important point in this study is the calculation, including the effect of nonequilibrium evaporation and condensation at bubble wall for the first time in the studies of SBSL. The results reveal that the effect is considerable on bubble dynamics. It is clarified that the partial pressure of water vapor in a bubble differs considerably from the saturated vapor pressure at the collapse of the bubble. It is also clarified that the liquid temperature at the bubble wall increases considerably at collapse due to the thermal conduction and the latent heat of intense condensation. It means that chemical reactions.
ROBUST CONCURRENCY CONTROL FOR A DISTRIBUTED INFORMATION SYSTEM

This dissertation presents a collection of protocols for coordinating transactions in a distributed information system. The system is modeled as a collection of processes that communicate only through message passing. Each process manages some portion of the data base, and several processes may cooperate in performing a single transaction. The thesis presents a model for computation in a distributed information system in which the sites and communication links may fail. The effects of such failures on the computation are described in the model. The thesis discusses implementation techniques that could be used to limit the effects of failures in a real system to those described in the model. A hierarchical protocol for coordinating transaction are pre-analyzed to select the protocols needed to coordinate the processes that participate in the implementation of the transaction. This analysis can be used to guide the organization of the data base so as to minimize the amount of locking required in performing frequent or important transactions. An important aspect of this mechanism is that it allows transactions that cannot accurately be pre-analyzed to be performed and correctly synchronized without severely degrading the performance of the system in performing more predictable transactions. A novel approach to the problem of making updates at several different sites atomically is also discussed. This approach is based on the notion of polyvalue, which is used to represent two or more possible values for a single data item. A polyvalue is created for an item involved in an update that has been delayed due to a failure. By assigning a polyvalue to such an item, that item can be made accessible to subsequent transactions, rather than remaining locked until the update can be completed. A polyvalue describes the possible values that may be correct for an item, depending on the outcome of transactions that have been interrupted by failures. Frequently, the most important effects of a transaction (such as the payment of money) can be determined without knowing the exact values of the items in the data base. A polyvalue for an item that is accessed by such a transaction may be sufficient to determine such effects. By using polyvalues, we can guarantee that a data item will not be made inaccessible to any failure other than a failure of the site that holds the item. A strong motivation for the development of these protocols is the desire that the individual sites of a distributed information system fail independently, and that a site or a group of sites be able to continue local processing operations when a failure has isolated them from the rest of the sites. Many of the previous coordination mechanism have only considered the continued operation of the sites that remain with the system to be important. Another motivating factor for the development of these protocols is the idea that in many applications, the processing to be performed exhibits a high degre
Increasing the topological quality of Kohonen's self organising map by using a hit term

The quality of the topology obtained at the end of the training period of Kohonen's self organizing map (SOM) is highly dependent on the learning rate and neighborhood function that are chosen at the beginning. The conventional approaches to determine those parameters do not account for the data statistics and the topological characterization of the neurons. The paper proposes a new parameter, which depends on the hit ratio among the updated neuron and the best matching neuron. It has been shown that by using this parameter with the conventional learning rate and neighborhood functions, much more adequate solution can be obtained since it deserves an information about data statistics during adaptation process.
Proactive Personalization Through Abstraction for Android Phones

— Use of smart phones is increasing day by day. Many applications are available on AppStore to facilitate the use of smart phones. Users have their personal information saved on smart phones. While downloading the application users have to allow access to personal information (e.g. contacts, coarse and fine location etc) and other facilities of the smart phones (e.g. internet, GPS, Bluetooth). But many times malicious applications which do not have access to these smart phone resources may steal the user’s personal information through different attacks like intent spoofing, confuse deputy attack, permission collusion. The aim of the paper is to implement a Permission Manager (PM) model that enables us to formally define some desired security properties, which can prove a hold on Android system. The mechanism is based upon information flow control. To remain practically relevant we developed personalized Mobile Search Engine (MSE) and with the help of application we can prove that the properties hold on the android framework and we are able to secure the user’s personal information. The MSE will personalize the user’s web search results by considering the content and location concepts and profiling the user behavior. Goal is to develop MSE for personalizing the users search results and with the help of MSE to prove that the additionally added security properties are able to prevent malicious software from gaining access to user’s personal data.
A FRAMEWORK FOR COMMENTS ANALYSIS AND VISUALIZATION

The number of user-contributed comments is increasing exponentially. Such comments are found widely in social media sites including internet discussion forums and news agency websites. Individual users are flooded with thousands of comments in some discussion webpages, so the reading task became costly in time and processing reducing their daily life productivity. Commenting activity can be addictive. The online social activity can bring an unpleasant experience for the comments readers. In this paper, we propose a framework to support readers to analyze and visualize opinion and topics on the comments. We describe experiments on product reviews comments and news comments.
A spatiotemporal second-order algorithm for fMRI data analysis

An important tool for model-free data analysis is given by blind source separation (BSS). Its goal is to achieve either spatial or temporal separation by linearly mapping into a feature space. In this paper, separation is measured by diagonality of the autocovariances. If the data possesses both spatial and temporal structures such as scans from functional magnetic resonance imaging (fMRI), we can require the transformed data to be as auto-decorrelated as possible in both domains. First introduced by Stone in the setting of independent component analysis, spatiotemporal BSS is a promising method for fMRI data analysis. We propose a novel algorithm for performing spatiotemporal BSS by jointly diagonalizing the autocovariances of the mixtures, both in time and in space. This provides a robust method for fMRI analysis. The feasibility of the proposed algorithm is demonstrated in an application to the analysis of fMRI data sets.
Web Application Vulnerabilities: Detect, Exploit, Prevent

This book is about Web Application Hacking. The world-renowned authors teach the reader to use publicly available tools to conduct thorough assessments of web application. This assessment process provides the reader with an understanding of Web application vulnerabilities and how they are exploited. The book goes on to teach the reader to detect, exploit, and ultimately prevent these vulnerabilities. Next, the authors cover advanced techniques of exploiting vulnerabilities such as SQL Injection, Arbitrary command injection, and more. · Learn to defend Web-based applications developed with AJAX, SOAP, XMLPRC, and more. · See why Cross Site Scripting attacks can be so devastating. · Download working code from the companion Web site.
Steganography in Audio Signals using Variable Bit Replacement Method in DCT Domain

Steganography is the method of concealing a message or image within a media, be it audio, image or video. The purpose is the same as that of cryptography, which is to secure data. But the difference is that in steganography, the sole existence of such a secret message is known only to the sender and receiver of that message. Audio steganography is such a technique of hiding a message within an audio file (known as the cover audio). Lately, lot of novel and versatile Audio Steganographic methods have been proposed. A good audio steganographic technique not only intends at embedding data in such a way that the changes made in the cover audio are indiscernible but also at the efficient extraction of the data. The least-significant-bit (LSB) based approach is popular among the steganographic algorithms. Our aim here is creating an audio steganography technique by changing the LSBs of the DiscreteCosine-Transform (DCT) coefficients of the Cover Audio. It is different from the conventional LSB technique in DCT domain because, here in proposed method data is embedded by spreading it all over the layers of the LSBs of the DCT coefficients. The technique has proven to be robust than the conventional LSB technique and to the channel induced noise as well, in terms of performance evaluation. The same conclusion is drawn from the experimental results obtained by using the DCT domain features and the Support Vector Machine (SVM) as the classifier. Besides, check on the integrity of the message and imperceptibility of the changes is also performed.
Policy enforcement via program monitoring

One way to guarantee that software behaves securely is to monitor programs at run time and check that they dynamically adhere to constraints specified by a security policy. Whenever a program monitor detects that untrusted software is attempting to execute a dangerous action, it takes remedial steps to ensure that only safe code actually gets executed. This thesis considers the space of policies enforceable by monitoring the run-time behaviors of programs and develops a practical language for specifying monitors' policies. In order to delineate the space of policies that monitors can enforce, we first have to define exactly what it means for a monitor to enforce a policy. We therefore begin by building a formal framework for analyzing policy enforcement; we precisely define policies, monitors, and enforcement. Having this framework allows us to consider the enforcement powers of program monitors and prove that they enforce an interesting set of policies that we define and call the infinite renewal properties. We show how, when given any reasonable infinite renewal property, to construct a program monitor that provably enforces that policy. In practice, the security policies enforced by program monitors grow more complex both as the monitored software is given new capabilities and as policies are refined in response to attacks and user feedback. We propose dealing with policy complexity by organizing policies in such a way as to make them composeable, so that complex policies can be specified more simply as compositions of smaller spicily modules. We present a fully implemented language and system called Polymer that allows security engineers to specify and enforce composeable policies on Java applications. We also formalize the central workings of Polymer by defining an unambiguous semantics for our language.
An approach to implement a network intrusion detection system using genetic algorithms

As the transmission of data over the internet increases, the need to protect connected systems also increases. Intrusion Detection Systems (IDSs) are the latest technology used for this purpose. Although the field of IDSs is still developing, the systems that do exist are still not complete, in the sense that they are not able to detect all types of intrusions. Some attacks which are detected by various tools available today cannot be detected by other products, depending on the types and methods that they are built on. Using a Genetic Algorithm (GA) is one of the methods that IDSs use to detect intrusions. They incorporate the concept of Darwin's theory and natural selection to detect intrusions. Not much research has been conducted in this area besides the Genetic Algorithm as an Alternative Tool for Security Audit Trails Analysis (GASSATA) tool; there are very few IDSs that are completely developed from using GAs. The focus of this paper is to introduce the application of GA, in order to improve the effectiveness of IDSs.
Design and Simulation of Photovoltaic Cell Using Decrement Resistance Algorithm

This paper presents a new approach of the Design and simulation of a photovoltaic cell using decrement resistance algorithm for maximum power point tracking (MPPT). The Simulation is done in the MATLAB. The algorithm detects the maximum power point of the photovoltaic (PV) cell. It includes module BP SX 150S for a solar photovoltaic. This module provides a maximum power of 150 W. The current-voltage (I-V)&power-voltage (P-V) characteristics are obtained for various values of solar irradiance keeping the cell temperature constant. The points indicating module voltage V mp and current I mp at maximum Power P max are obtained.
A MODIFIED TASK SCHEDULING ALGORITHM OF TASK GRAPH WITHOUT COMMUNICATION TIME

The scheduling of tasks on the processors is considered to be a very critical problem in the multiprocessor system. Here, the problem is divided into subtasks and it is assigned on the processors. The overall objective of task scheduling is to minimize the execution time. Considering that the task scheduling is represented by a directed acyclic graph (DAG). In this paper, we are proposing an algorithm for task scheduling without communication time while assigning of tasks on the processors. It is a modified algorithm of task scheduling based on breath first search (TSB) in our previous paper. The new algorithm gives better result than TSB. A comparative study amongst the developed algorithm, TSB and BNP class of scheduling algorithms. It has been done based on the followings matrices: scheduling length, speedup, efficiency, load balancing and normalized scheduling length. According to the comparative results, it is found that the developed algorithm gives better results.
A new approach to generate a self-organizing fuzzy neural network model

This paper presents a new approach for creating a self-organizing fuzzy neural network (SOFNN) from training data, to implement the Takagi-Sugeno-Kang (TSK) model. The center vector and the width vector have been introduced in the RBF neurons in the SOFNN. Novel methods of structure learning and parameter learning, based on new adding and pruning techniques and a recursive on-line learning algorithm, are proposed and developed. The proposed methods are very simple and effective and generate a fuzzy neural model with a high accuracy and a very compact structure. Simulation studies based on a pH neutralization process, confirm that the SOFNN has the capability of self-organization, and can determine the structure and parameters of the network automatically without non-linear optimization.
Notice of Retraction Researching on dual scheme of webpage hyperlink based on the formal concept analysis

We proposed dual scheme in structure of Web page hyperlink by applying the formal concept analysis approach. The existence condition and the computing method of dual scheme were given too. The inner connection among the Web hyperlink is shown by this dual scheme profoundly, it is a special cluster of Web page hyperlink, and it will support to retrieve Web page interested by customer in a new way completely.
Implementation of large-scale distributed information retrieval system

Parallel and distributed IR holds great potential for tackling the performance and scale issues associated with the large and growing document collections currently available online. We surveyed a number of techniques for exploiting modern parallel architectures. We can easily implement a parallel system that works on both multiprocessor and distributed architectures with relatively little modification. We also present some challenges on parallel and distributed IR, and the future work for tackling these issues.
Automatic Gender Classification Using Neuro Fuzzy System

The automatic classification of gender has important applications in many commercial domains. Existing systems mainly use features such as words, word classes, and POS (part of speech) n-grams, for classification learning. In this paper, we propose a novel automatic classifier which applies accurately designed fuzzy inference system. This system is 2-inputs, 1-output Sugeno type one, applies facial characteristics as inputs and reveals the probability of being male face or not. Choosing proper threshold value, the decision about gender is made. 87.5% rate of obtained classification proves the efficiency of the proposed method.
Improvements to NTSC by Multidimensional Filtering

This article presents, in a tutorial fashion, the basic elements required for understanding compatible improvement techniques for NTSC color multiplexing using multidimensional filtering at the transmitter and receiver. It discusses the multidimensional spectrum of moving pictures and relates the form of this spectrum to different types of image material. It also presents the basics of multidimensional filtering that are key to the techniques we discuss for improving NTSC. Finally, systems for NTSC encoding and decoding using multidimensional processing are described.
Broadcasting the Bedroom: Intimate musical practices and collapsing contexts on YouTube

In an era of social media and online participation, uploading a personal video to a platform such as YouTube appears to be an easy and natural activity for large groups of users. Various discourses on online narcissism and exhibitionism (Balance, 2012; Keen, 2007, 2012; Twenge and Campbell, 2010) give the impression that current generations have become extremely comfortable (perhaps even too comfortable) with the online possibilities of self-exposure and self-representation (Mallan, 2009). As I will argue in this chapter, however, this is largely a misrepresentation of the everyday struggles and experiences of online participants. For many, posting a video on YouTube is a rather ambivalent activity: joyful and fun at times, but also scary and accompanied by feelings of insecurity, especially when the content is relatively delicate.
Design and implementation of interface units for high speed fiber optics local area networks and broadband integrated services digital networks

The design and implementation of interface units for high speed Fiber Optic Local Area Networks and Broadband Integrated Services Digital Networks are discussed. During the last years, a number of network adapters that are designed to support high speed communications have emerged. This approach to the design of a high speed network interface unit was to implement package processing functions in hardware, using VLSI technology. The VLSI hardware implementation of a buffer management unit, which is required in such architectures, is described.
Advanced signal processing techniques for single trial electroencephalography signal classification for brain computer interface applications

Brain Computer Interface (BCI) is a direct communication channel between brain and computer. It allows the users to control the environment without the need to control muscle activity [1-2]. P300-Speller is a well known and widely used BCI system that was developed by Farwell and Donchin in 1988 [3]. The accuracy level of the P300-BCI Speller as measured by the percent of communicated characters correctly identified by the system depends on the ability to detect the P300 event related potential (ERP) component among the ongoing electroencephalography (EEG) signal. Different techniques have been tested to reduce the number of trials needed to be averaged together to allow the reliable detection of the P300 response. Some of them have achieved high accuracies in multiple-trial P300 response detection. However the accuracy of single trial P300 response detection still needs to be improved. In this research, two single trial P300 response classification methods were designed. One is based on independent component analysis (ICA) with blind tracking and the other is based on variance analysis. The purpose of both methods is to detect a chosen character in real-time in the P300-BCI speller. The experimental results demonstrate that the proposed methods dramatically reduce the signal processing time, improve the data communication rate, and achieve overall accuracy of 79.1% for ICA based method and 84.8% for variance analysis based method in single trial P300 response classification task. Both methods showed better performance than that of the single trial stepwise linear discriminant analysis (SWLDA), which has been considered as the most accurate and practical technique working with P300-BCI Speller.
Measurement Optimization for Parameter Estimation in Distributed Systems

This book is organized as follows. In Chapter 1 a brief summary of concrete applications involving the sensor location problem is given. Some of these examples are used throughout the monograph to motivate and illustrate the demonstrated developments. A concise general review of the existing literature and a classication of methods for optimal sensor location are presented