Search: "Algorithms" Filter:"Algorithms"

4 tagged events, 26 books found.

Tagged events

February 2023

FEB 15
International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI) ISSN: 2319 - 1015 [Online]; ...


FEB 25
3rd International Conference on AI, Machine Learning and Applications (AIMLA 2023) February 25 ~ 26, 2023, Vancouver, C...

Vancouver, Canada,

May 2023

MAY 13
7 th International Conference on Applied Mathematics and Sciences (AMA 2023) May 13 ~ 14, 2023, Virtual Conference ht...


MAY 30
The 4th Int'l Conference on Computational Science and Numerical Algorithms (CSMA 2023) will be held in Chengdu, China, d...



by Mahendra Gunathilaka Samarawickrama


The modern FPGAs enable system designers to develop high-performance computing (HPC) applications with a large amount of parallelism. Real-time image processing is such a requirement that demands much more processing power than a conventional processor can deliver. In this research, we implemented software and hardware based architectures on FPGA to achieve real-time image processing. Furthermore, we benchmark and compare our implemented architectures with existing architectures. The operational structures of those systems consist of on-chip processors or custom vision coprocessors implemented in a parallel manner with efficient memory and bus architectures. The performance properties such as the accuracy, throughput and efficiency are measured and presented. According to results, FPGA ...

by Mustafa Mikail Ozciloglu & Mehmet Fatih Akay (advisor)


Upper body power (UBP) is one of the most important factors affecting the performance of cross-country skiers during races. Although some initial studies have already attempted to predict UBP, until now, no study has attempted to apply machine learning methods combined with various feature selection algorithms to identify the discriminative features for prediction of UBP. The purpose of this study is to develop new prediction models for predicting the 10-second UBP (UBP10) and 60-second UBP (UBP60) of cross-country skiers by using General Regression Neural Networks (GRNN), Radial-Basis Function Network (RBF), Multilayer Perceptron (MLP), Support Vector Machine (SVM), Single Decision Tree (SDT) and Tree Boost (TB) along with the Relief-F feature selection algorithm, minimum redundancy maxim...

Indoor Wireless Metering Networks

A Collection of Algorithms Enabling Low Power/Low Duty-Cycle Operations

by Nicola Altan


Wireless Metering Networks (WMN), a special class of Wireless Sensor Networks (WSN), consisting of a large number of tiny inexpensive sensor nodes are a viable solution for many problems in the field of building automation, especially if the expected lifetime of the network permits to synchronize the network maintenance with the schedule for routine maintenance of the building. In order to meet the resulting energy constraints, the nodes have to operate according to an extremely low duty cycle schedule. The existence of an energy efficient MAC Layer protocol, the adoption of a robust time synchronization mechanism and the implementation of effective network discovery and maintenance strategies are key elements for the success of a WMN project. The main goal of this work was the developm...

by Rajmohan Madhavan


This thesis is concerned with the theoretical and practical development of reliable and robust localisation algorithms for autonomous land vehicles operating at high speeds in unstructured, expansive and harsh environments. Localisation is the ability of a vehicle to determine its position and orientation within an operating environment. The need for such a localisation system is motivated by the requirement of developing autonomous vehicles in applications such as mining, agriculture and cargo handling. The main drivers in these applications are for safety, efficiency and productivity. The approach taken to the localisation problem in this thesis guarantees that the safety and reliability requirements imposed by such applications are achieved. The ...

by Sylvain R Y Louboutin


Comprehensive global garbage detection (GGD) in object-oriented distributed systems, i.e., GGD intrinsically able to detect distributed cycles of garbage, has mostly been addressed via graph tracing algorithms. Graph tracing algorithms must account for every live object in the system before any resource can actually be reclaimed which compromises both their scalability and robustness in a distributed environment. Alternative non-comprehensive approaches trade-off comprehensiveness for scalability and robustness under the assumptions that distributed cycles of garbage are rare and that all comprehensive algorithms are necessarily unscalable. This thesis contends instead that distributed cycles of garbage are as likely to occur as local cycles and that a comprehensive alternative to g...

Digital Signal Processing Laboratory

LabVIEW-Based FPGA Implementation

by Nasser Kehtarnavaz and Sidharth Mahotra


Field Programmable Gate Arrays (FPGAs) are increasingly becoming the platform of choice to implement DSP algorithms. This book is designed to allow DSP students or DSP engineers to achieve FPGA implementation of DSP algorithms in a one-semester DSP laboratory course or in a short design cycle time based on the LabVIEW FPGA Module. Features: - The first DSP laboratory book that uses the FPGA platform instead of the DSP platform for implementation of DSP algorithms - Incorporating introductions to LabVIEW and VHDL - Lab experiments covering FPGA implementation of basic DSP topics including convolution, digital filtering, fixed-point data representation, adaptive filtering, frequency domain processing - Hardware FPGA implementation applications including wavelet transform, software-de...

by Ruth Shrairman


This research is dedicated to two main problems in finding shortest paths in the graphs. The first problem is to find shortest paths from an origin to all other vertices in non-negatively weighted graph. The second problem is the same, except it is allowed that some edges are negative. This is a more difficult problem that can be solved by relatively complicated algorithms. We attack the first problem by introducing a new data structure - Relaxed Heaps that implements efficiently two main operations critical for the improvement of Dijkstra's shortest path algorithm. R²heaps with suspended relaxation proposed in this research gives the best known worst-case time bounds of O(1) for a decrease_key operation and O(logn) for a delete_min operation. That results in the best worst-case runnin...

by Farayi Musharavati


Trends and perspectives in dynamic environments point towards a need for optimal operating levels in reconfigurable manufacturing activities. Central to the goal of meeting this need is the issue of appropriate techniques for manufacturing process planning optimization in reconfigurable manufacturing, i.e. (i) what decision making models and (ii) what computational techniques, provide an optimal manufacturing process planning solution in a multidimensional decision variables space? Conventional optimization techniques are not robust, hence; they are not suitable for handling multidimensional search spaces. On the other hand, process planning optimization for reconfigurable manufacturing is not amenable to classical modeling approaches due to the presence of complex system dynamics. Therefo...

by Ioan Burda


Introduction to Quantum Computation is an introduction to a new rapidly developing theory of quantum computing. The book is a comprehensive introduction to the main ideas and techniques of quantum computation. It begins with the basics of classical theory of computation: NP-complete problems, Boolean circuits, Finite state machine, Turing machine and the idea of complexity of an algorithm. The general quantum formalism (pure states, qubit, superposition, evolution of quantum system, entanglement, multi-qubit system ...) and complex algorithm examples are also presented. Matlab is a well known in engineer academia as matrix computing environment, which makes it well suited for simulating quantum algorithms. The (Quantum Computer Toolbox) QCT is written entirely in the Matlab and m-files ar...

Toponym Resolution in Text

Annotation, Evaluation and Applications of Spatial Grounding of Place Names

by Jochen L. Leidner


The problem of automatic toponym resolution, or computing the mapping from occurrences of names for places as found in a text to an unambiguous spatial footprint of the location referred to, such as a geographic latitude/longitude centroid is difficult to automate due to insufficient and error-prone geographic databases, and a large degree of place name ambiguity: common words need to be distinguished from proper names (geo/non-geo ambiguity), and the mapping between names and locations is ambiguous (London can refer to the capital of the UK or to London, Ontario, Canada, or to about forty other Londons on earth). This thesis investigates how referentially ambiguous spatial named entities can be grounded, or resolved, with respect to an extensional coordinate model robustly on open-domain...

by Gozde Yigit Ozsert & Mehmet Fatih Akay (advisor)


The purpose of this thesis is to develop new hybrid admission decision prediction models by using different machine learning methods including Support Vector Machines (SVM), Multilayer Perceptron (MLP), Radial Basis Function (RBF) Network, TreeBoost (TB) and K-Means Clustering (KMC) combined with feature selection algorithms to investigate the effect of the predictor variables on the admission decision of a candidate to the School of Physical Education and Sports at Cukurova University. Three feature selection algorithms including Relief-F, F-Score and Correlation-based Feature Selection (CFS) have been considered. Experiments have been conducted on the datasets, which contain data of participants who applied to the School in 2006 and 2007. The datasets have been randomly split into train...

by Kevin T. Reynolds, CISSP, PMP


Are all Wireless LANs equal? A network administrator is faced with a plethora of wireless services, complex radio issues, and products for wireless data. There are brand new protocols and products that could become obsolete a day after installation! Over 40% of all deployed WLANs do not even have minimum security activated, exposing the company's network and records to easy outsider access.The WLAN industry is characterized by rapidly changing, incomplete or proprietary standards, which can impact interoperability goals. There are complicated ownership costs, performance limitations, and security configurations that exist for WLANs which many network administrators may not understand or know how to compare. This dissertation presents a decision support system (DSS) that enables a nov...

by Alex Buchner


Context Mediation is a field of research that is concerned with the interchange of information across different environments, which provides a vehicle to bridge semantic gaps among disparate entities. Knowledge Discovery is concerned with the extraction of actionable information from large databases. A challenge that has received relatively little attention is knowledge discovery in a highly disparate environment, that is multiple heterogeneous data sources, multiple domain knowledge sources and multiple knowledge patterns. This thesis tackles the problem of semantic interoperability among data, domain knowledge and knowledge patterns in a knowledge discovery process using context mediation. Context fundamentals are introduced, which encompasses the concepts of context identity, sem...

Decision Making in Uncertain Situations

An Extension to the Mathematical Theory of Evidence

by Fabio Campos


The main problem addressed by this work is how to model and combine bodies of knowledge (or evidence) while maintaining the representation of the unkowledge and of the conflict among the bodies. This is a problem with far-reaching applications in many knowledge segments, in particular for the fields of artificial intelligence, product design, decision making, knowledge engineering and uncertain probability. It must be kept in mind that knowledge based systems depend on algorithms able to relate the inputs of a system to a correct answer coming out of the knowledge-base, and both the inputs and the knowledge-base are subject to information imperfections caused by the unknowledge and the conflict. There are several formalism to deal with knowledge representation and combination, among them...

How to Solve Large Linear Systems

Using a Stable Cybernetic Approach for Non-Cumulative Computation, Avoiding Underflow and Overflow, with Unconditional and Uniform Convergence

by Aleksa Srdanov and Aleksandra Jankovic


Solving the linear equation system n x n can also be a problem for a computer, even when the number of equations and unknowns is relatively small (a few hundred). All existing methods are burdened by at least one of the following problems: 1) Complexity of computation expressed through the number of operations required to be done to obtaining solution; 2) Unrestricted growth of the size of the intermediate result, which causes overflow and underflow problems; 3) Changing the value of some coefficients in the input system, which causes the instability of the solution; 4) Require certain conditions for convergence, etc.In this paper an approximate and exact methods for solving a system of linear equations with an arbitrary number of equations and the same number of unknowns is presented. Al...

by Adel A. Al-Rumaih


In this dissertation, a new spare capacity planning methodology is proposed utilizing path restoration. The approach is based on forcing working flows/traffic which are on paths that are disjoint to share spare backup capacity. The algorithm for determining the spare capacity assignment is based on genetic algorithms and is capable of incorporating non-linear variables such as non-linear cost function and QoS variables into the objective and constraints. The proposed methodology applies to a wider range of fault scenarios than most of the current literature. It can tolerate link-failures, node-failures, and link-and-node failures. It consists of two stages: the first stage generates a set of network topologies that maximize the sharing between backup paths by forcing them to use a subse...

Soft-Computing in Capital Market

Research and Methods of Computational Finance for Measuring Risk of Financial Instruments

by Jibendu Kumar Mantri (editor)


Computational Finance, an exciting new cross-disciplinary research area, depends extensively on the tools and techniques of computer science, statistics, information systems and financial economics for educating the next generation of financial researchers, analysts, risk managers, and financial information technology professionals. This new discipline, sometimes also referred to as “Financial Engineering” or “Quantitative Finance” needs professionals with extensive skills both in finance and mathematics along with specialization in computer science. Soft-Computing in Capital Market hopes to fulfill the need of applications of this offshoot of the technology by providing a diverse collection of cross-disciplinary research. This edited volume covers most of the recent, advanced r...

Topographic Mapping

Covering the Wider Field of Geospatial Information Science & Technology (GIS&T)

by John N. Hatzopoulos


This book is addressed to students and professionals and it is aimed to cover as much as possible the wider region of topographic mapping as it has been evolved into a modern field called geospatial information and technology. More emphasis is given to the use of scientific methods and tools that are materialised in algorithms and software and produce practical results. For this reason beyond the written material there are also many educational and professional software programs written by the author to comprehend the individual methodologies which are developed. Target of this book is to provide the people who work in fields of applications of topographic mapping (environment, geology, geography, cartography, engineering, geotechnical, agriculture, forestry, etc.) a source of knowledge fo...

Patients at Risk

The Rise of the Nurse Practitioner and Physician Assistant in Healthcare

by Niran Al-Agba, M.D. and Rebekah Bernard, M.D.


Patients at Risk: The Rise of the Nurse Practitioner and Physician Assistant in Healthcare exposes a vast conspiracy of political maneuvering and corporate greed that has led to the replacement of qualified medical professionals by lesser trained practitioners. As corporations seek to save money and government agencies aim to increase constituent access, minimum qualifications for the guardians of our nation's healthcare continue to decline--with deadly consequences. This is a story that has not yet been told, and one that has dangerous repercussions for all Americans. With the rate of nurse practitioner and physician assistant graduates exceeding that of physician graduates, if you are not already being treated by a non-physician, chances are, you soon will be. While advocates for these ...

Acquisition and Reproduction of Color Images

Colorimetric and Multispectral Approaches

by Jon Hardeberg


The goal of the work reported in this dissertation is to develop methods for the acquisition and reproduction of high quality digital color images. To reach this goal it is necessary to understand and control the way in which the different devices involved in the entire color imaging chain treat colors. Therefore we addressed the problem of colorimetric characterization of scanners and printers, providing efficient and colorimetrically accurate means of conversion between a device-independent color space such as the CIELAB space, and the device-dependent color spaces of a scanner and a printer. First, we propose a new method for the colorimetric characterization of color scanners. It consists of applying a non-linear correction to the scanner RGB values followed by a 3rd order 3D polynom...

by Denis V. Popel


Information theory methods are of wide use in contemporary logic design, but their proper application to Computer Aided Design (CAD) is rather impossible without strong theoretical and practical justification. Our research is focused on logic function minimization which is an essential component of any system for digital circuit design. The well-known information theory methods to minimize logic functions should be improved and developed towards new problems appeared while increasing the number of CAD applications. We report new results on logic functions minimization by information theory standpoint. We have developed an information theoretic model of recursive decomposition of logic functions. Based on this model, a novel technique for efficient Decision Tree design of various types (AND...


Mining, Transaction, Security Challenges and Future of This Currency

by Muhammad Aslam Zahid


In this dissertation, I have presented a comprehensive research on Bitcoin. Bitcoin was introduced in 2009. This is a decentralized digital currency and works like cash, but they are mined like gold (Volastro, CNBC Explains: How to mine bitcoins on your own, 2014). In this thesis, I will explain that how this currency works and how users can mine Bitcoins. Bitcoins mining is a very hard process, it is almost impossible to create Bitcoins on simple computer. You need specialist hardware to generate Bitcoins. Pool mining is quite popular these days, as numbers of people are taking interest in making money, so the difficulty level of mining Bitcoin is increasing day by day. I am using codes based on publically available sources in order to explore the algorithms for mining, hashing and transa...

by Mircea Andrecut


The aim of this book is to provide a simple and useful introduction for the fresh students into the vast field of numerical analysis. Like any other introductory course on numerical analysis, this book contains the basic theory, which in the present text refers to the following topics: linear equations, nonlinear equations, eigensystems, interpolation, approximation of functions, numerical differentiation and integration, stochastics, ordinary differential equations and partial differential equations. Because the students need to quickly understand why the numerical methods correctly work, the proofs of theorems were shorted as possible, insisting more on ideas than on a lot of algebra manipulation. The included examples are presented with a minimum of complications, emphasizing the st...

by Christopher Ariza


This dissertation introduces a new design for a computer-aided algorithmic music composition system. Rather than exploring specific algorithms, this study focuses on system and component design. The design introduced here is demonstrated through its implementation in athenaCL, a modular, polyphonic, poly-paradigm algorithmic music composition system in a cross-platform interactive command-line environment. The athenaCL system offers an open-source, object-oriented composition tool written in Python. The system can be scripted and embedded, and includes integrated instrument libraries, post-tonal and microtonal pitch modeling tools, multiple-format graphical outputs, and musical output in Csound, MIDI, audio file, XML, and text formats. Software design analysis is framed within a broad his...

by Bahram Sadeghi Bigham (editor)


The 2012 International Conference on Contemporary Issues in Computer and Information Science (CICIS 2012) is a conference where new advances and research results in the fields of computer science and information technology are presented. CICIS 2012 brought together leading researchers, engineers and scientists from around the world engaged in computer science and related interests. This, the third annual conference, was held with special concentration on Graph and Geometrical Algorithms, Intelligent Systems, Bioinformatics, and IT and Society.

by Jacques Tagoudjeu


This thesis focuses on iterative methods for the treatment of the steady state neutron transport equation in slab geometry, bounded convex domain of Rn (n = 2,3) and in 1-D spherical geometry. We introduce a generic Alternate Direction Implicit (ADI)-like iterative method based on positive definite and m-accretive splitting (PAS) for linear operator equations with operators admitting such splitting. This method converges unconditionally and its SOR acceleration yields convergence results similar to those obtained in presence of finite dimensional systems with matrices possessing the Young property A. The proposed methods are illustrated by a numerical example in which an integro-differential problem of transport theory is considered. In the particular case where the positive definite par...