Miracle-dz/UniFAR-FTUs huggingface dataset:
Big Data: Principles and best practices of scalable realtime data systems

Services like social networks, web analytics, and intelligent e-commerce often need to manage data at a scale too big for a traditional database. As scale and demand increase, so does Complexity. Fortunately, scalability and simplicity are not mutually exclusiverather than using some trendy technology, a different approach is needed. Big data systems use many machines working in parallel to store and process data, which introduces fundamental challenges unfamiliar to most developers. Big Data shows how to build these systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy to understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to use them in practice, and how to deploy and operate them once they're built. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
Optimization of a human interface to access image data bases

The authors describe an experimental evaluation of the usability of a user interface for accessing image databases by means of relational queries. After evaluating the performance of an earlier version of the interface, a human factors study was carried out to improve its friendliness. Then a second usability test was performed and the results were compared with those of the previous one. Both naive and experienced users took part in the experiments. They had to solve three tasks which consisted of retrieving a given image from the database. The following data were collected automatically: performance time and error rate as a function of the number of trials and the experience level, and subjective reactions to the use of the interface. The results show that the second version of the interface is characterized by better performance times and error rates. Moreover, the gap between the performances of experienced and naive users was reduced. Attitude assessments show that the second version reported better scores as regards ease-of-use, usability, and satisfaction. <<ETX>>
Design of reliable decentralized control systems guaranteeing H/sub /spl infin//-norm performance bound for a class of uncertain linear plants

A decentralized control scheme with observer-based feedback controllers is developed for a class of uncertain linear plants, and it is shown that the resulting closed-loop system is reliable in the sense that the control scheme provides guaranteed stability and H/sub /spl infin//-norm bounded performance in the event of soft-type sensor and/or actuator failures as well as in the presence of parameter uncertainties. We observed that soft-type failures were additional exogenous inputs in the closed-loop system. As a result, the sensor and/or actuator failures can be tolerated in the design, which is achieved by extending the result developed by the authors (1994).
Characterizing image quality of autostereoscopic displays by using the maximum luminance at each viewing position

A metric of the 3D image quality of autostereoscopic displays based on optical measurements is proposed. This metric uses each view's luminance contrast, which is defined as the ratio of maximum luminance at each viewing position to total luminance at that position. Conventional metrics of the autostereoscopic display based on crosstalk, which uses “wanted” and “unwanted” lights. However, in case of the multiple‐views‐type autostereoscopic displays, it is difficult to distinguish exactly which lights are wanted lights and which are unwanted lights. This paper assumes that the wanted light has a maximum luminance at the good stereoscopic viewing position, and the unwanted light also has a maximum luminance at the worst pseudo‐stereoscopic viewing position. By using the maximum luminance that is indexed by view number of the autostereoscopic display, the proposed method enables characterizing stereoscopic viewing conditions without using wanted/unwanted light. A 3D image quality metric called “stereo luminance contrast,” the average of both eyes' contrast, is proposed. The effectiveness of the proposed metric is confirmed by the results of optical measurement analyses of different types of autostereoscopic displays, such as the two‐view, scan‐backlight, multi‐view, and integral.
Periscopic stereo for virtual world creation

Virtual reality-interaction with simulated models of “scenes” or “worlds”- is an area that is undergoing rapid development. Representing a real scene as a three-dimensional model is a time-consuming process if created manually. However, there is a variety of image analysis techniques that can be used to aid, and even automate, virtual world creation. For acquiring individual objects, well-established approaches include stereo cameras and laser range-finding. We concentrate upon stereo systems, since they are typically much less expensive. For acquiring a 3D model of, say, the inside of a room, a single stereo image is insufficient. One must introduce ego-motion to view all parts of the room, perhaps by panning the camera. Although there has been much good work on the solution of this general problem, ego-motion remains a factor that significantly complicates subsequent computations. This paper explores the use of an unusual stereo configuration to side-step ego-motion problems, producing imagery that can be used directly for computational stereo over an entire 360° panorama. Potential applications of the technique include building virtual shops whose layouts match real ones, capturing archaeological sites for virtual heritage, and so on.
Analysis of rxbot

ANALYSIS OF RXBOT by Esha Patil In recent years, botnets have emerged as a serious threat on the Internet. Botnets are commonly used for exploits such as distributed denial of service (DDoS) attacks, identity theft, spam, and click fraud. The immense size of botnets (hundreds or thousands of PCs connected in a botnet) increases the ubiquity and speed of attacks. Due to the criminally motivated uses of botnets, they pose a serious threat to the community. Thus, it is important to analyze known botnets to understand their working. Most of the botnets target security vulnerabilities in Microsoft Windows platform. Rxbot is a Win32 bot that belongs to the Agobot family. This paper presents an analysis of Rxbot. The observations of the analysis process provide in-depth understanding of various aspects of the botnet lifecycle such as botnet architecture, network formation, propagation mechanisms, and exploit capabilities. The study of Rxbot reveals certain tricks and techniques used by the botnet owners to hide their bots and bypass some security software. TABLE OF CONTENTS
Handbook of ethological methods

Preface 1. Introduction Part I. Getting Started: 2. A conceptual model of animal behavior 3. Choice of subject 4. Reconnaissance observation 5. Delineation of research 6. Design of research 7. Experimental research Part II. Collecting the Data: 8. Data collection methods 9. Data collection equipment 10. Selected examples of data collection and description Part III. Analysing the Results: 11. Introduction to statistical methods 12. Selecting a statistical test 13. Parametric statistical tests 14. Nonparametric statistical tests 15. Rates of behavior and analysis of sequences 16. Statistical analyses for spatial orientation, time and spatial patterns 17. Presentation and interpretation of results Bibliography Appendices: A. Statistical figures and tables B. Microcomputers: an overview for ethologists by James Ha C. Guidelines for the use of animals in research D. Ethics in animal behavior research Index.
Current Perspectives on Personality and Internet Use

The Internet provides a means to take part in various online activities, for example, leisure activities (e.g., online gaming), social activities (e.g., online chat), and information activities (e.g., online newspapers). Patterns of Internet consumption tend to vary greatly and this is said to be a possible function of personality. Therefore, knowing something about the personalities of those who favor specific activities online may provide a better insight into the motivational factors behind use. This article combines and reviews current literature regarding personality and Internet use, using Eysenck’s three-factor personality theory as a framework of convergence. Although the Internet allows us to play with our identities, it would still seem that online behavior tends to somewhat mimic the behavior expected by one’s off-line personality.
Examining students' attitudes to the mobile phone as an educational tool

This study examines students' attitudes to the mobile phone as a medium for learning in terms of learning reliance on technology, improvement of knowledge from the perspective of learning process 'know-how" bJ Ihe 'show-how, enhancement of knowledge on difficult subject, constraint on the learning process, and mobility in learning. A questionnaire containing five open-ended questions was distributed to 20 students. The outcome from descriptive analysis construed that students have yet to embrace M-learning, as they do not usually use the mobile phone to access study materials such as lectures and lab sessions. Students are more comfortable with the face to- face mode of instruction and other conventional methods of learning. In addition, implications and direction for future research are discussed.
Design of integrated fault detection, diagnosis and reconfigurable control systems

In this paper, a novel approach for integrated fault detection, diagnosis and reconfigurable control systems design in the discrete-time stochastic domain is proposed. The scheme is based on a two-stage adaptive Kalman filter for simultaneous state and fault parameter estimation, statistical decisions for fault detection, diagnosis and activation of controller reconfiguration. Using the information provided by the fault detection and diagnosis scheme, the reconfigurable controller is designed automatically using an eigenstructure assignment technique. To eliminate the steady-state tracking error, a feedforward reconfigurable control law is also incorporated. The proposed approach has been evaluated using two examples. The effectiveness and superiority of the proposed approach have been demonstrated in comparison with existing reconfigurable controllers which are based on linear quadratic regulator and other eigenstructure assignment techniques.
The development of machine vision for road vehicles in the last decade

Machine vision for road vehicles started in the mid-80s. After a very brief review of the initial phase of about half a decade, developments over the last decade are discussed in more detail. The EUREKA-project 'Prometheus' set the stage in Europe and spread activities to all major carmakers and to many universities throughout Europe. The US and some Asian countries soon followed The basic perceptual and behavioral capabilities for driving and for driver assistance on well-kept high-speed roads have been demonstrated at the end of the Prometheus project. Later developments took two directions: 1. Simple systems for early application in confined domains, and 2. more complex systems with growth potential for performance levels closer to the human one. In the meantime, first products with machine vision components are on the market; more highly integrated systems have been announced for the second half of this decade. A road map for the development of vision for cars is discussed.
Automotive combustion modelling and control

This thesis seeks to bring together advances in control theory, modelling and controller hardware and apply them to automotive powertrains. Automotive powertrain control is dominated by PID controllers, look-up tables and their derivatives. These controllers have been constantly refined over the last two decades and now perform acceptably well. However, they are now becoming excessively complicated and time consuming to calibrate. At the same time the industry faces ever increasing pressure to improve fuel consumption, reduce emissions and provide driver responsiveness. The challenge is to apply more sophisticated control approaches which address these issues and at the same time are intuitive and straightforward to tune for good performance by calibration engineers. This research is based on a combustion model which, whilst simplified, facilitates an accurate estimate of the harmful NO x and soot emissions. The combustion model combines a representation of the fuel spray and mixing with charge air to give a time varying distribution of in-cylinder air and fuel mixture which is used to calculate flame temperatures and the subsequent emissions. A combustion controller was developed, initially in simulation, using the combustion model to minimise emissions during transient manoeuvres. The control approach was implemented on an FPGA exploiting parallel computations that allow the algorithm to run in real-time. The FPGA was integrated into a test vehicle and tested over a number of standard test cycles demonstrating that the combustion controller can be used to reduce NO x emissions by over 10% during the US06 test cycle. A further use of the combustion model was in the optimisation of fuel injection parameters to minimise fuel consumption, whilst delivering the required torque and respecting constraints on cylinder pressure (to preserve engine integrity) and rate of increase in cylinder pressure (to reduce noise).
A CMOS automatic gain control for hearing aid devices

In this paper a CMOS Automatic Gain Control (AGC) for Hearing aid devices is proposed. Monte Carlo analyses have shown total harmonic distortions below 0.5% and 0.6% for uncompressed and hard compressed operations, respectively. Dynamic Range is 69 dB while the THD is around 0.5%. Power consumption for the complete AGC is 54 /spl mu/Watts under normal conditions and 162 /spl mu/Watts for maximum compression operation. Attack and release times are below than 5 ms. The AGC is operated with /spl plusmn/1.5 supply voltages.
An efficient procedure for locating joint centers on 3D scanned human models: using hip joint centers as an example

This paper presents an efficient procedure to locate joint centers on 3D scanned human models. Using the hip joint centers (HJCs) as an example, we conducted an experiment to study the validity of the procedure. We carried out 3D body scanning on six subjects, which were attached with the necessary body landmarks. Another 12 participants were recruited to perform two tasks. The first task was to identify the locations of the body landmarks. We pre-programmed the estimation method to an in-house rigging system. The lower body bones were then placed by the system according to the estimated HJCs. The second task was to place the lower body bones based on visual judgments. The results show that the HJCs obtained in the first task are more accurate. The results are also visually demonstrated. The promising results of the experiment indicate the possibility of building skeletal structures with 3D body scanning.
Silicon Bipolar LNAs in the X and Ku Bands

Two fully integrated silicon bipolar LNAs at 8 and 12 GHz are presented. Both circuits provide simultaneous noise and input impedance matching. Resonant loads, designed for 50-Ω output matching, are also included. Moreover, the noise and input impedance self-matching trend of the cascode topology in the X and Ku bands was also explored and the design of integrated spiral inductors was discussed. From an on-wafer test, the 8 and the 12-GHz LNAs exhibit a power gain of 11.5 and 8 dB and a noise figure of 2.6 and 4.7 dB, respectively. This performance was achieved with bias currents as low as 4 mA for each circuit. The two LNAs were fabricated in a 46-GHz-fT pure bipolar technology.
Implementation and Evaluation of SIFT Descriptors based Finger-Knuckle-Print Authentication System

Finger-Knuckle-Print (FKP) uses feature detection and matching techniques in its hard core design. It works similar for almost every authentication system. The Scale Invariant Feature Transform (SIFT) is the most reliable feature extraction technique that is used in authentication systems on FKP. The feature descriptors detected by SIFT claim to be capable of distinguishing each and every image in the dataset from one another with the cost involved in its operations. In SIFT based FKP authentication systems, the storage and computational cost will directly depend on the size of the feature descriptors used. Such matching process will directly match these feature descriptors to find an exact match and the descriptors were directly stored in storage media as templates. Hence there is a necessity for storing all the feature descriptors of the enrolled FKP images for future references. The size of these feature descriptors data will be greater than the original FKP image dataset and the performance of the system will rapidly decrease with respect to the increase in enrollment in the database. The proposed work address these issues with FKP based authentication system using SIFT for efficient computation and cost compared with the existing work and proven to be secure and tough resistant for authentication system.
Developing Credible Social Cognitive Agents – Linguistic Behavior, Simulations, Data-Driven Input, and Turing’s Legacy

Barring swarm robotics, a substantial share of current machine-human and machine-machine learning and interaction mechanisms are being developed and fed by results of agent-based computer simulations, game-theoretic models, or robotic experiments based on a dyadic communication pattern. Yet, in real life, humans no less frequently communicate in groups, and gain knowledge and take decisions basing on information cumulatively gleaned from more than one single source. These properties should be taken into consideration in the design of autonomous artificial cognitive systems construed to interact with//learn from more than one contact or ‘neighbor’. To this end, significant practical import can be gleaned from research applying strict science methodology to phenomena humanistic and social, e.g. to discovery of realistic creativity potential spans, or the ‘exposure thresholds’ after which new information could be accepted by a cognitive agent. Whether in order to mimic them, or to ‘enhance’ them, parameters gleaned from complexity science approaches to humans’ social and humanistic behavior should subsequently be incorporated as points of reference in the field of robotics and human-machine interaction.
Statistics based fast intra mode detection

The H.264 standard1 describes the intra prediction process to exploit the spatial correlation between adjacent blocks for video compression. The intra prediction for luminance samples can be performed using blocks of size 4x4 or 16x16 pixels. The intra prediction for chrominance samples is performed on 8x8 block size. 4x4 block size luminance samples can be predicted using nine intra prediction modes, 16x16 block size luminance samples and 8x8 block size chrominance samples each can be predicted using four intra prediction modes. The exhaustive evaluation of all possible luminance and chrominance intra prediction modes requires significant amount of computations and thus it reduces the encoding speed. This paper describes a method to approximate optimal luminance intra prediction mode with reduced computations. The results show that significant speed improvement can be gained with negligible loss of objective quality.
An AHP-based framework for selecting knowledge management tools to sustain innovation process

This paper presents a framework based on the analytic hierarchy process (AHP) methodology to select the most appropriate set of Knowledge Management (KM) tools to support the innovation processes in organizations. The framework builds on the theoretical foundations underlying organizational KM to identify key KM processes enabling innovation. The AHP is a multi-criteria decision support technique that can be used to analyse and compare those KM tools that best support innovation processes. Organizations can select the most suitable KM tool by using the proposed framework to identify gaps and overlaps in the extent to which the capabilities provided and utilized by their current KM tools portfolio meet the KM needs of the organization to sustain the innovation. The main contributions of this work are the list of KM processes to support an innovation activity and the hierarchy of importance of such processes able to support the selection process of a KM tool. The framework can be of use to managers and other practitioners because of its ease of implementation. An illustrative example of a case study for the application of the framework is provided.
Inter‐organizational knowledge transfer needs among small and medium enterprises

Purpose – The purpose of this paper is to build upon Chen et al.'s work by investigating inter‐organizational knowledge transfer needs and practices among small and medium enterprises (SMEs) which have received relatively little research attention to date.Design/methodology/approach – A questionnaire survey was conducted on SMEs which have been accorded the Multimedia Super Corridor Malaysia status. Data were analyzed using Statistical Package for the Social Sciences.Findings – In total, nine important areas have been the focus of this study, i.e. the importance of external knowledge; the extent to which external knowledge is more important than internal knowledge to organizational success; areas in which insufficient knowledge contributes to costly errors or mistakes in the SMEs; SMEs' involvement in knowledge transfer activities; number of social networks involved; SMEs' perceptions about networks; use of tools and technologies to transfer inter‐organizational knowledge; constraints of inter‐organizatio.
The Development of a Benchmark Tool for NoSQL Databases

The aim of this article is to describe a proposed benchmark methodology and software application targeted at measuring the performance of both SQL and NoSQL databases. These represent the results obtained during PhD research (being actually a part of a larger application intended for NoSQL database management). A reason for aiming at this particular subject is the complete lack of benchmarking tools for NoSQL databases, except for YCBS [1] and a benchmark tool made specifically to compare Redis to RavenDB. While there are several well-known benchmarking systems for classical relational databases (starting with the canon TPC-C, TPC-E and TPC-H), on the other side of databases world such tools are mostly missing and seriously needed.
The Research on Chinese Automatic Segmentation

Abstract. Word Segmentation is a fundamental problem of the Chinese natural language progressing. Based on the analysis of the state on research and key issues of it . The paper introduces a tree structure statistical method of word frequency, which enables key words to match one another highly-efficiently. by which we can rapidly express texts as the set of high-frequency words,so the classification of texts is conveniently reached.
D4. Dynamic Supply RF Power Amplifier

This work aims at the design and implementation of a 2.14GHz 24dBm class-A radio frequency (RF) power amplifier (P A). Efficiency improvement is then achieved through dynamical control of its constant supply voltage through a DC-DC converter. Control voltage of the DC-DC converter is obtained by closing the loop through sampling the power of the P A output signal using directional coupler and RF power detector. Power response of the power amplifier with and without the dynamic supply is compared as well as other amplifier parameters.