Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey Paper on RS-MONA: Reliable and Scalable Approach for Secure Multi-Owner Data Sharing for Dynamic Groups in the Cloud

In Today’s world Cloud Computing which moves the application software and databases to the centralized large data centers, where the management of the data and services may not be fully trustworthy. Several trends are opening up the era of Cloud Computing, which is an Internet-based development and use of computer technology. One of the biggest concerns with cloud data storage is that of data integrity verification at untrusted servers. To preserve data privacy, a basic solution is to encrypt data files, and then upload the encrypted data into the cloud. To resolve this problem recently the best efficient method MONA presented for secured multi owner data sharing in however we identified some limitations in the same approach in terms of reliability and scalability. Hence in this paper we are further extending the basic MONA by adding the reliability as well as improving the scalability by increasing the number of group managers dynamically. Keywords– Cloud Computing, dynamic groups, data sharing, reliability, integrity, scalability.
English computer corpora : selected papers and research guide

The future of English linguistics as envisaged by the editors of Topics in English Linguistics lies in empirical studies which integrate work in English linguistics into general and theoretical linguistics on the one hand, and comparative linguistics on the other. The TiEL series features volumes that present interesting new data and analyses, and above all fresh approaches that contribute to the overall aim of the series, which is to further outstanding research in English linguistics.
Data flow modeling techniques

There have been a number of simulation packages developed for the purpose of designing, testing and validating computer systems, digital systems and software systems. Complex analytical tools based on Markov and semi-Markov processes have been designed to estimate the reliability and performance of simulated systems. Petri nets have received wide acceptance for modeling complex and highly parallel computers. In this research data flow models for computer systems are investigated. Data flow models can be used to simulate both software and hardware in a uniform manner. Data flow simulation techniques provide the computer systems designer with a CAD environment which enables highly parallel complex systems to be defined, evaluated at all levels and finally implemented in either hardware or software. Inherent in data flow concept is the hierarchical handling of complex systems. In this paper we will describe how data flow can be used to model computer system.
An Overview of the INQUERY System as Used for the TIPSTER Project

TR #93-85 An Overview of the INQUERY System as Used fo J. Broglio, J. P. Callan and W. Bruce Croft Computer Science Department, LGRC Box 34610 University of Massachusetts Amherst, MA 01003-4601 November 1, 1993. ASTRACT Research in the Information Retrieval laboratory was funded for two years by the TIPSTER program, a large-scale project in information retrieval and fact extraction. This report was written at the end of Phase I (the first two years). It reviews the INQUERY information retrieval system and provides a broad overview of the research results obtained during the TIPSTER project. The results include scaling up to a two gigabtye document collection, significant improvements in processing natural language queries, the WordFinder system that finds new words and phrases related to a query, document routing techniques, and a Japanese version of the system.
Neural Networks: A Comprehensive Foundation

Simon Haykin Neural Networks A Comprehensive Foundation. Neural Networks A Comprehensive Foundation Simon S. Neural Networks A Comprehensive Foundation Simon S. Neural Networks A Comprehensive Foundation. Neural Networks Association for Computing Machinery. Book Review Neural Networks A Comprehensive Foundation. Neural Networks A Comprehensive Foundation Pearson. Neural networks a comprehensive foundation. Neural Networks a Comprehensive Foundation AbeBooks. Neural networks a comprehensive foundation solutions. cdn preterhuman net. Neural Networks A Comprehensive Foundation Goodreads. Neural Networks A Comprehensive Foundation Amazon it. Neural Networks A Comprehensive Foundation Amazon co uk. Neural Networks A Comprehensive Foundation 3rd Edition. Neural Networks A Comprehensive Foundation Simon. Neural Networks A Comprehensive Foundation amazon com. Neural networks a comprehensive foundation Academia edu. Neural Networks A Comprehensive Foundation Amazon. neural networks a comprehensive foundation simon haykin. Simon Haykin Neural Networks A Comprehensive Foundation. Neural Networks A comprehensive Foundation 2 ed. Simon haykin neural networks a comprehensive foundation pdf. Buy Neural Networks A Comprehensive Foundation Book. Neural networks a comprehensive foundation 2e book. Neural Networks A Comprehensive Foundation. NEURAL NETWORKS A COMPREHENSIVE FOUNDATION SIMON. Neural Networks a Comprehensive Foundation by Haykin Simon. Neural Networks A Comprehensive Foundation pdf PDF Drive. Neural Networks A Comprehensive Foundation amazon ca. Simon Haykin Neural Networks A Comprehensive Foundation. NEURAL NETWORKS A Comprehensive Foundation PDF. Neural Networks A Comprehensive Foundation pdf PDF Drive. Neural Networks A Comprehensive Foundation by Haykin. Neural Networks A Comprehensive Foundation 3rd Edition. Neural Networks A Comprehensive Foundation Simon S. Neural Networks A Comprehensive Foundation. Neural networks a comprehensive foundation Book 1994. Neural Networks A Comprehensive Foundation 2nd Edition. Neural Networks A Comprehensive Foundation S S Haykin. Neural Networks A Comprehensive Foundation International. Neural Networks A Comprehensive Foundation 2 e Pearson. Download Neural Networks A Comprehensive Foundation 2Nd. Neural Networks A comprehensive foundation Aalto
Hardware - Software Co-design of embedded telecommunication systems using multiple formalisms for application development

: In this paper a co-design methodology based on multifonnalism modelling is presented. It defines a platfonn that integrates different notations and, the necessary mechanisms to handle different in nature models in a coherent way. The supported fonnalisms cover a wide area of application domains, allowing the designer to select the notations that are mostly appropriate for his/her application. The proposed co-design development cycle provides a full blown path from system specification to a virtual prototype of the system under construction. The methodology has been applied for the design and implementation of a MAC layer protocol, named MASCARA, for providing A TM QoS over wireless connections.
Registration errors in augmented reality systems

Augmented reality (AR) systems combine three-dimensional computer-generated imagery with the view of the real environment in order to make unseen objects visible or to present additional information. A critical problem is that the computer-generated objects do not currently remain correctly registered with the real environment--objects aligned from one viewpoint appear misaligned from another and appear to swim about as the viewer moves. This registration error is caused by a number of factors, such as system delay, optical distortion, and tracker measurement error, and is difficult to correct with existing technology. This dissertation presents a registration error model for AR systems and uses it to gain insight into the nature and severity of the registration error caused by the various error sources. My thesis is that a mathematical error model enables the system architect to determine (1) which error sources are the most significant, (2) the sensitivity of the net registration error to each error, (3) the nature of the distortions caused by each type of error, (4) the level of registration accuracy one can expect, and also provides insights on how best to calibrate the system. Analysis of a surgery planning application yielded the following main results: (1) Even for moderate head velocities, system delay causes more registration error than all other sources combined; (2) Using the eye's center of rotation as the eyepoint in the computer graphics model reduces the error due to eye rotation to zero for points along the line of gaze. This should obviate the need for eye tracking; (3) Tracker error is a significant problem both in head tracking and in system calibration; (4) The World coordinate system should be omitted when possible; (5) Optical distortion is a significant error source, but correcting it computationally in the graphics pipeline often induces delay error larger than the distortion error itself; (6) Knowledge of the nature of the various types of error facilitates identification and correction of errors in the calibration process. Although the model was developed for see-through head-mounted displays (STHMDs) for surgical planning, many of the results are applicable to other HMD systems as well.
Genetic Algorithm Based Similarity Transitivity in Collaborative Filtering

Collaborative filtering is the process of filtering for information or patterns using techniques involving collaboration among viewpoints, data sources, etc. Collaborative filtering methods have been applied to many different kinds of data including: sensing and monitoring data . Collaborative filtering is a method of making automatic predictions (filtering) about the interests of a user by collecting preferences or taste information from many users (collaborating). In this paper similarity based technique makes the prediction of user with similar taste or similar items.It firsty filter out those inaccurate similarities by clustering methods then set proper intersection threshold value then replace them with the transitivity similarity.This paper proposed genetic algorithm based similarity transitivity which is used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution.
Selection of a SONET network architecture-Survivability can be enhanced cost effectively

A number of SONET-based survivable interoffice network architectures were studied. One purpose of the study was to assist network planners in their selection process by assessing the relative benefits and costs of alternative network architectures. Another purpose was to guide future work on requirements for improving survivability benefits in SONET-based networks. The network alternatives were studied from the standpoint of cost, survivability and risk analysis, operations impact, and survivability economics. The results of these studies are summarized. <<ETX>>
Dynamic modeling and simulation for nonholonomic welding mobile robot

为焊接基于 Newton-Euler 方法，左的动态行为和正确驱动轮和机器人身体活动机器人被导出。 以便认识到身体转弯和滑块调整的联合控制，滑块的动态行为也被调查。 作为结果，为焊接的一个系统、完全的动态模型活动机器人被构造。 为了验证上述模型，的有效性，追踪控制方法的一个滑动模式被建议并且模仿，侧面的错误在 0.2 之间稳定公里和 +0.2 公里，吗并且为滑块的旅行的全部的距离是一致地在牯漠汩搠'糖锚? 楷桴琠敨椠据敲獡? 景琠浩? 洠慥睮楨敬? 桴? 楤浡瑥牥漠? 潷湲猠潰? 獩猠慭汬? 湡? 桴? 晲捡? 景眠牯? 灳瑯椠? 浳潯桴? 湡? 潮以内？
On Bayesian MHT for well-separated targets in densely cluttered environment

Certain radar applications must cope with rather extreme operational conditions (densely cluttered environment/relatively small detection probabilities). Tracking in such situations calls for refined data association and processing techniques. By simulation results we demonstrate the applicability of Bayesian multiple hypothesis tracking (MRT) to well-separated targets detected with a mechanically rotating radar. Special emphasis is placed on air situations characterized by massively occurring data association conflicts.
Inference, simulation, modeling, and analysis of complex networks, with special emphasis on complex networks in systems biology

Across diverse fields ranging from physics to biology, sociology, and economics, the technological advances of the past decade have engendered an unprecedented explosion of data on highly complex systems with thousands, if not millions of interacting components. These systems exist at many scales of size and complexity, and it is becoming ever-more apparent that they are, in fact, universal, arising in every field of study. Moreover, they share fundamental properties—chief among these, that the individual interactions of their constituent parts may be well-understood, but the characteristic behaviour produced by the confluence of these interactions— by these complex networks-is unpredictable; in a nutshell, the whole is more than the sum of its parts. There is, perhaps, no better illustration of this concept than the discoveries being made regarding complex networks in the biological sciences. In particular, though the sequencing of the human genome in 2003 was a remarkable feat, scientists understand that the “cellular-level blueprints” for the human being are cellular-level parts lists, but they say nothing (explicitly) about cellular-level processes. The challenge of modern molecular biology is to understand these processes in terms of the networks of parts— in terms of the interactions among proteins, enzymes, genes, and metabolites—as it is these processes that ultimately differentiate animate from inanimate, giving rise to life! It is the goal of systems biology—an umbrella field encapsulating everything from molecular
The 4D-approach to dynamic machine vision

In this survey paper covering a decade of experience with recursive estimation methods for visual dynamic scene understanding, the common methodical background of the 4D approach exploiting spatio-temporal models of objects and processes observed is discussed. Applications range from 'balancing an inverted pendulum' over 'vehicle docking', 'road vehicle guidance, 'on-board autonomous aircraft landing approaches', 'landmark navigation for land vehicles' to 'grasping of an object freely floating in a satellite orbit with large delay times. Simultaneous recognition of rough 3D shape and motion parameters for moving road vehicles including occlusions has been achieved in well structured Autobahn scenes in real time (5 Hz). Recognition and tracking of moving humans in well structured environments has been advanced to a stage that real-time performance seems possible with the next generation of micro-processors just around the corner. After a brief review of the general method the aspects of exploiting object-oriented, model-based predictions for very efficient intelligent image feature extraction are discussed for some of the tasks considered. <<ETX>>
The analysis of phonocardiographic signals based on higher-order spectra

This paper investigates the problem for the phonocardiographic cardiographic signal processing by employing the third-order cumulant. The non-Gaussian AR model is proposed to model the signals. The cumulant-based third-order recursion is employed to decide the model parameters for understanding the properties of PCG signals in the bifrequency domain. Moreover, to test the performance of the PCG signal with the background noise, some signals with different SNR are analyzed for the bispectral estimation. The results are exhibited and analyzed to show the effectiveness of the methods based on higher-order spectra.
Context-dependent modeling for acoustic-phonetic recognition of continuous speech

This paper describes the results of our work in designing a system for phonetic recognition of unrestricted continuous speech. We describe several algorithms used to recognize phonemes using context-dependent Hidden Markov Models of the phonemes. We present results for several variations of the parameters of the algorithms. In addition, we propose a technique that makes it possible to integrate traditional acoustic-phonetic features into a hidden Markov process. The categorical decisions usually associated with heuristic acoustic-phonetic algorithms are replaced by automated training techniques and global search strategies. The combination of general spectral information and specific acoustic-phonetic features is shown to result in more accurate phonetic recognition than either representation by itself.
Segment the metallograph images using Gabor filter

We have implemented a texture-based supervised segmentation method to segment a variety of metallograph images which are considered to contain different textured regions. Texture features are computed by using a set of even symmetric Gabor filters which have been successfully used earlier for a variety of texture classification and segmentation tasks. The performance of the proposed method has been shown on a number of test images. These results also demonstrate the ability of our improved approach to separate the untextured regions from the textured regions in the same image. <<ETX>>
Power and Thermal-Aware Scheduling for Real-Time Computing Systems

We have been enjoying tremendous benefits thanks to the revolutionary advancement of computing systems, driven by the remarkable semiconductor technology scaling and the advanced processor architecture. However, the exponentially increased transistor density has directly led to increased power consumption and elevated system temperature. The power and thermal issues have posed enormous challenges and threaten to slow down the continuous evolvement of computer technology. Effective power/thermal-aware design techniques are urgently demanded at all design abstraction levels. In this book, we present our research efforts to employ real-time scheduling techniques to solve the resource-constrained power/thermal-aware, design-optimization problems. The novelty of this work is that we integrate the cutting-edge research on power and thermal at the circuit and architectural-level into a set of accurate yet simplified system-level models, and are able to conduct system-level analysis and design based on these models. The theoretical study in this work serves as a solid foundation for the guidance of the power/thermal-aware scheduling algorithms development in practical computing systems.
Ajaxifying classicWeb applications

Recently, a new web development technique for creating interactive web applications, dubbed AJAX, has emerged in response to the limited degree of interactivity in large-grain stateless web interactions. In this new model, the web interface is composed of individual components which can be updated/replaced independently, and the client/server communication is based on a delta-communication style of interaction. With the rise of AJAX web applications classical multi-page web applications are becoming legacy systems. This research seeks to explore how software engineering techniques can assist in comprehending, analyzing, and restructuring classic web applications towards AJAX.
Overcoming uncertainty for within-network relational machine learning

Pfei↵er, Joseph J., III Ph.D., Purdue University, May 2015. Overcoming Uncertainty for Within-Network Relational Machine Learning. Major Professor: Jennifer Neville. People increasingly communicate through email and social networks to maintain friendships and conduct business, as well as share online content such as pictures, videos and products. Relational machine learning (RML) utilizes a set of observed attributes and network structure to predict corresponding labels for items; for example, to predict individuals engaged in securities fraud, we can utilize phone calls and workplace information to make joint predictions over the individuals. However, in large scale and partially observed network domains, missing labels and edges can significantly impact standard relational machine learning methods by introducing bias into the learning and inference processes. In this dissertation, we identify the e↵ects on parameter estimation, correct the biases, and model the uncertainty of the missing data to improve predictive performance. In particular, we investigate this issue on a variety of modeling scenarios and prediction problems. First, we introduce the Transitive Chung Lu (TCL) random graph model for modeling the conditional distribution of edges given a partially observed network. This model fits within a class of scalable generative graph models with scalable sampling processes that we generalize to model distributions of networks with correlated attribute variables via Attributed Graph Models. Second, we utilize TCL to incorporate edge probabilities into relational learning and inference models for partially observed network domains. As part of this work, we give a linear time algorithm to perform variational inference over a squared network. We apply the resulting semi-supervised model, Probabilistic Relational EM (PR-EM) to the Active Exploration domain to
Performance Comparison of DCT and VQ Based Techniques for Iris Recognition

Iris recognition enjoys universality, high degree of uniqueness and moderate user co-operation. This makes iris recognition systems unavoidable in emerging security & authentication mechanisms. An iris recognition system based on vector quantization (VQ) techniques is proposed and its performance is compared with the discrete cosine transform (DCT). The proposed system does not need any pre-processing and segmentation of the iris. We have tested Linde-Buzo- Gray (LBG), Kekre's proportionate error (KPE) algorithm and Kekre's fast codebook generation (KFCG) algorithm for the clustering purpose. Proposed vector quantization based method using KFCG requires 99.99% less computations as that of full 2-dimensional DCT. Further, the KFCG method gives better performance with the accuracy of 89.10% outperforming DCT that gives accuracy around 66.10%.
MPEG-2 TS generate system and its implementation with FPGA

In this paper, a MPEG-2 TS (transport stream) generation system is introduced. It can work as a TS generator source to provide a TS from hard disk in a cycling mode; it can also work as a TS recorder to receive a TS from a peripheral. A real-time PID filter, PID changing and bit rate changing are also realized in this system; Further the received TS can be analyzed and processed by a PC. In this paper, we briefly introduce the TS generate system's hardware architecture and working process. The system consists of a PCI interface card and a PC. The PCI interface card is implemented mainly with one FPGA (APEX 20K200 E). The system takes full advantage of the APEX20K's features of high integrity and flexibility that most functions are realized within one FPGA.
Modelling Supercomputer Maintenance Interrupts: Maintenance Policy Recommendations

A supercomputer is a repairable system with large number of compute nodes interconnected to work in harmony to achieve superior computational performance. Reliability of such a complex system depends on an effective maintenance strategy that involves both emergency and preventive maintenance. This thesis analyzes the maintenance records of four supercomputers operational at The National Institute of Computational Science located at Oak Ridge National Laboratory. We propose to use the generalized proportional intensities model (GPIM) to model the maintenance interrupts as it can capture both the reliability parameters and maintenance parameters and allows the inclusion of both emergency and preventive maintenance. We use this model to obtain the reliability parameters indicating the system performance and maintenance parameters indicating the effectiveness of maintenance actions for each of the four supercomputers. System performance measures such as reliability and availability are used to evaluate the effectiveness of the existing maintenance policy and to propose a new maintenance policy that increases the system availability and reduces maintenance cost.