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A proposed model of human consciousness system with applications in pattern recognition

A proposed model of human consciousness system with applicat...

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international conference on Knowledge-Based Intelligent Electronic systems (KES)

作者： Kim Le Faculty of Information Sciences and Engineering University of Canberra Belconnen ACT Australia

Human recognition is a complex, efficient process which, for thousands of years, people have tried to analyse but have not yet fully understood. Recently, with advances in psychology, medicine and computer engineering in some research fields such as neural networks, fuzzy set theory, genetic algorithms, etc., people have tried to simulate the human brain and received significant results in the pattern recognition field. This paper proposes a model of a human consciousness system with applications in pattern recognition. The model explains how our brain saves, extracts and retrieves data. The model can recognise patterns with noise. Furthermore, when part of the model is damaged, the model can be required and re-used. An implementation of the model and some experimental results are also presented.

关键词： Humans Pattern recognition Application software Brain modeling Psychology computer networks Genetic engineering Biological neural networks Fuzzy set theory Genetic algorithms

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Enhanced Building Prediction for Smart City Surveillance 1

Enhanced Building Prediction for Smart City Surveillance

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1st IEEE international conference on Advances in Electronics, Communication, Computing and Intelligent Information systems, ICAECIS 2023

作者： Natarajan, Yuvaraj Wadhwa, Gitanjali Saravanan, Lekshmipriya Natarajan, Mathivathani KPR Institute of Engineering and Technology Dept. of Computer Science and Engineering Coimbatore641407 India KPR Institute of Engineering and Technology Dept. of Artificial Intelligence and Data Science Coimbatore641407 India

ISBN: (纸本)9798350348057

Nearly three-quarters of the total power used in the world is consumed by the built environment sector. Therefore, looking for viable methods to reduce building energy needs and decrease negative environmental repercussions is vital. By incorporating intelligence into applications, everyone in the current situation has become intelligent, which lessens the load of constant interruption or human control. By using Machine to Machine interactions, intelligence enables the ability to connect more real-time parameters and make moral judgments in perilous circumstances. The current study examined the framework, approach, and performance of currently available AI-based techniques. According to the research, choosing the best machine and deep learning model for a given task can be difficult. Among the primary areas of study in relation to the vast amounts of data collected is the viability in the practice of the used algorithms, both standard machine learning and the more recent branch known as deep learning. Present a quantitative analysis contrasting the effectiveness of conventional deep learning and machine learning strategies using the direction of human movement in detecting the applications based on the analogue pyroelectric infrared sensor (PIR) outputs. Here, Random Forest is used as the machine learning method because of its great prediction accuracy. Over deeper datasets, deeper CNNs outperform shallow models as a deep learning method. The study demonstrates that traditional Machine Learning performs with detecting values within the first few seconds, improving real-time detection. Additionally, it might be used on more smart buildings without upgrades. © 2023 IEEE.

关键词： Intelligent buildings

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Soft Iterative Decision Directed Channel Estimation for OFDM systems employing adaptive predictor

Soft Iterative Decision Directed Channel Estimation for OFDM...

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international conference on Wireless Communication, Vehicular Technology, Information theory and Aerospace and Electronic systems Technology (Wireless VITAE)

作者： Olutayo Oyeyemi Oyerinde stanley Henry Mneney School of Electrical Electronic and Computer Engineering University of KwaZulu-Natal Durban South Africa

Soft iterative decision directed channel estimation (DDCE) employing fast data projection method (FDPM) subspace tracking algorithm and variable step size normalized least mean square-based predictor is proposed for OFDM system in this paper. A more realistic fractionally spaced channel impulse response (FS-CIR) model is considered. The performance of the soft iterative DDCE employing FDPM subspace tracking algorithm is validated in comparison with DDCE employing deflated version of projection approximation subspace tracking (PAstd) algorithm through computer simulations. The simulation results show that the soft iterative DDCE scheme based on FDPM algorithm outperformed its counterpart based on PAstd algorithm under both slow and fast fading channel scenarios. The proposed VSSNLMS-based CIR predictor for the iterative DDCE scheme also brings about an improved performance in comparison with the iterative scheme employing NLMS-based predictor.

关键词： Channel estimation Adaptive systems Iterative algorithms Fading Iterative methods Approximation algorithms Quadrature phase shift keying OFDM modulation Robustness Transceivers

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Implementation of Deep Neural Network Using VLSI by Integral stochastic Computation 1

Implementation of Deep Neural Network Using VLSI by Integral...

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1st international conference on Advances in Computational Science and Engineering, ICACSE 2020

作者： Khan, Vijitha Parameshwaran, R. Arulkumaran, G. Gopi, B. Department of Electronics and Communication Engineering Ahalia School of Engineering and Technology Kerala Kozhippara India Department of Electronics and Communication Engineering National Institute of Technology Tamil Nadu Tiruchirapalli India Department of Electrical and Computer Engineering Bule Hora University Bule Hora Ethiopia Department of Electronics and Communication Engineering Muthayammal Engineering College Tamil Nadu Rasipuram India

Efficient machine learning techniques that need substantial equipment and power usage in its computation phase are computational models. stochastic computation has indeed been added and the solution a compromise between this ability of the project and information systems and organisations to introduce computational models. Technical specifications and energy cost are greatly diminished in stochastic Computing by marginally compromising the precision of inference and calculation pace. However, Sc Neural Network models' efficiency has also been greatly enhanced with recent advances in SC technologies, making it equivalent to standard relational structures and fewer equipment types. Developers start with both the layout of a rudimentary SC nerve cell throughout this essay and instead study different kinds of SC machine learning, including word embedding, reinforcement learning, convolutionary genetic algorithms, and reinforcement learning. Consequently, rapid developments in SC architectures that further enhance machine learning's device speed and reliability are addressed. Both for practice and prediction methods, the generalised statement and simplicity of SC Machine Learning are demonstrated. After this, concerning conditional alternatives, the strengths and drawbacks of SC Machine learning are addressed. © Published under licence by IOP Publishing Ltd.

关键词： stochastic systems

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SL-COMP: Competition of Solvers for Separation Logic 25th

SL-COMP: Competition of Solvers for Separation Logic

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25th international conference on Tools and algorithms for the Construction and Analysis of systems (TACAS) held as part of the 22nd European Joint conferences on theory and practice of Software (ETAPS)

作者： Sighireanu, Mihaela Perez, Juan A. Navarro Rybalchenko, Andrey Gorogiannis, Nikos Iosif, Radu Reynolds, Andrew Serban, Cristina Katelaan, Jens Matheja, Christoph Noll, Thomas Zuleger, Florian Wei-Ngan Chin Le, Quang Loc Quang-Trung Ta Ton-Chanh Le Thanh-Toan Nguyen Khoo, Siau-Cheng Cyprian, Michal Rogalewicz, Adam Vojnar, Tomas Enea, Constantin Lengal, Ondrej Gao, Chong Wu, Zhilin Brno Univ Technol FIT Brno Czech Republic Univ Paris Diderot IRIF Paris France CNRS Paris France Microsoft Res Cambridge England Middlesex Univ London London England Natl Univ Singapore Singapore Singapore Rhein Westfal TH Aachen Aachen Germany Chinese Acad Sci State Key Lab Comp Sci Beijing Peoples R China Stevens Inst Technol Hoboken NJ 07030 USA Teesside Univ Middlesbrough Cleveland England TU Wien Vienna Austria UCL London England Google London England Univ Iowa Iowa City IA USA Univ Grenoble Alpes VERIMAG St Martin Dheres France CNRS St Martin Dheres France

ISBN: (纸本)9783030175023;9783030175016

SL-COMP aims at bringing together researchers interested on improving the state of the art of the automated deduction methods for Separation Logic (SL). The event took place twice until now and collected more than 1K problems for different fragments of SL. The input format of problems is based on the SMT-LIB format and therefore fully typed;only one new command is added to SMT-LIB's list, the command for the declaration of the heap's type. The SMT-LIB theory of SL comes with ten logics, some of them being combinations of SL with linear arithmetics. The competition's divisions are defined by the logic fragment, the kind of decision problem (satisfiability or entailment) and the presence of quantifiers. Until now, SL-COMP has been run on the starExec platform, where the benchmark set and the binaries of participant solvers are freely available. The benchmark set is also available with the competition's documentation on a public repository in GitHub.

关键词： Formal logic

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Plane-Sweep algorithms for the K Group Nearest-Neighbor Query

Plane-Sweep Algorithms for the K Group Nearest-Neighbor Quer...

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international conference on Geographical Information systems theory, Applications and Management

作者： George Roumelis Michael Vassilakopoulos Antonio Corral Yannis Manolopoulos Department of Informatics Aristotle University Department of Electrical and Computer Engineering University of Thessaly Department of Informatics University of Almeria

ISBN: (纸本)9781467384124

One of the most representative and studied queries in Spatial Databases is the (K) Nearest-Neighbor (NNQ), that discovers the (K) nearest neighbor(s) to a query point. An extension that is important for practical applications is the (K) Group Nearest Neighbor Query (GNNQ), that discovers the (K) nearest neighbor(s) to a group of query points (considering the sum of distances to all the members of the query group). This query has been studied during the recent years, considering data sets indexed by efficient spatial data structures. We study (K) GNNQs, considering non-indexed data sets, since this case is frequent in practical applications. And we present two (RAM-based) Plane-Sweep algorithms, that apply optimizations emerging from the geometric properties of the problem. By extensive experimentation, using real and synthetic data sets, we highlight the most efficient algorithm.

关键词： Spatial Query Processing Plane-Sweep Group Nearest-Neighbor Query algorithms

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A novel job scheduling model to enhance efficiency and overall user fairness of cloud computing environment

A novel job scheduling model to enhance efficiency and overa...

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作者： Li, Wenjuan Pan, Xuezeng Zhang, Qifei Ping, Lingdi College of Computer Science and Technology Zhejiang University Hangzhou Zhejiang China Hangzhou Normal University Hangzhou Zhejiang China

ISBN: (纸本)9789898425522

Job scheduling and resource allocation are the key factors which affect the performance of parallel and distributed systems. This paper first analyzed several common used job scheduling models in large and distributed environment. Since the main purpose of cloud computing is to provide "low-cost" and "on-demand" services, this paper introduced a novel two-level based cloud scheduling model. In our model, job scheduling in the cloud is divided into User Scheduling and Task Scheduling which were designed to implement different scheduling strategies. In the User Scheduling level, it applies the distribution justice theory in the sociology area to achieve the highest average user fairness. While in Task Scheduling level, it applies adaptive strategies to achieve the binding of micro tasks and the virtual machines according to different objectives of tasks. The new model redefined the messaging mechanism between main cloud entities and a new advertising mode was introduced for cloud providers to promote their services. The results of emulation experiments show that compared to traditional algorithms the proposed model can guarantee the user expectations and the relative fairness of the services on the basis of high overall efficiency of cloud systems.

关键词： Cloud computing

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Intelligent store - An innovative technological solution for retail activities with mobile access

Intelligent store - An innovative technological solution for...

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3rd international Multi-conference on Computing in the Global Information Technology, ICCGI 2008

作者： stan, Carmen E. Dumitrescu, Dan Caras, Vasilca Tiliute, Doru E. Pop, Eugen Anghel, Lucian E. Institute for Computer Bucharest Romania University of Suceava Romania Research and Development Engineering and Manufacturing for Automation Equipment and Systems Bucharest Romania National Institute for Research and Development in Informatics Bucharest Romania

ISBN: (纸本)9780769532752

This paper presents an innovative solution in retail activities, named "Intelligent store- INTELSHOP" based on a technological platform that offers the support for some attractive and efficient services for customers and administrative staff. The technological platform integrates various technologies such as RFID, GPS and GlS, wireless communications, mobile access to information on PDA or SmartPhone, integrated environments for data analysis regarding stocks and customers administration, interfaces with electronic payment systems. The goal pursued is mainly to reduce the time wasted by the customers searching the products on the store's shelf, to offer more and better information about products. On the other hand our solution pursues to maximize the merchant benefit by reducing the provisioning time, to diversify the offer and to create the opportunity to make the best decision in real time. © 2008 IEEE.

关键词： Decision making

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theory and applications of DNA codeword design

Theory and applications of DNA codeword design

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1st international conference on the theory and practice of Natural Computing, TPNC 2012

作者： Garzon, Max H. Computer Science University of Memphis TN 38152 United States

ISBN: (纸本)9783642338595

We survey the origin, current progress and applications on one major roadblock to the development of analytic models for DNA computing and self-assembly, namely the so-called Codeword Design problem. The problem calls for finding large sets of single DNA strands that do not crosshybridize to themselves or to their complements (so-called domains in the language of chemical reaction networks) and has been recognized as an important problem in DNA computing, self-assembly, DNA memories and phylogenetic analyses because of their error correction and prevention properties. Major recent advances include the development of experimental techniques to search for such codes, as well as a theoretical framework to analyze this problem, despite the fact that it has been proven to be NP-complete using any single concrete metric space to model the Gibbs energy. In this framework, codeword design is reduced to finding large sets of strands maximally separated in DNA spaces and, therefore, the key to finding such sets would lie in knowledge of the geometry of these spaces. A new general technique has been recently found to embed them in Euclidean spaces in a hybridization-affinity-preserving manner, i.e., in such a way that oligos with high/low hybridization affinity are mapped to neighboring/remote points in a geometric lattice, respectively. This isometric embedding materializes long-held mataphors about codeword design in terms of sphere packing and leads to designs that are in some cases known to be provable nearly optimal for some oligo sizes. It also leads to upper and lower bounds on estimates of the size of optimal codes of size up to 32-mers, as well as to infinite families of DNA strand lengths, based on estimates of the kissing (or contact) number for sphere packings in Euclidean spaces. Conversely, this reduction suggests interesting new algorithms to find dense sphere packing solutons in high dimensional spheres using prior results for codeword design priorly obtained b

关键词： DNA

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EstABLISHING AN OPTIMAL NETWORK DEFENSE SYstEM: A MONTE CARLO GRAPH SEARCH METHOD

ESTABLISHING AN OPTIMAL NETWORK DEFENSE SYSTEM: A MONTE CARL...

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第一届网络空间安全科学国际会议(The 1st international conference on Science of Cyber Security-SciSec 2018)

作者： Zhengyuan Zhang Kun Lv Changzhen Hu School of Computer Science & Technology Beijing Institute of Technology

Outline *** to Monte Carlo Tree Search *** Model *** Carlo Graph Search Algorithm *** Results *** and the Future Work *** to Monte Carlo Tree Search Monte Carlo tree search is usually be used on the analysis of the mo... 详细信息

ISBN: (纸本)9783030030254

关键词： Monte Carlo Graph Search Network defense system Attack graph Game theory Network security Game theory Network security Defense systems graph search algorithms Hypoderma Line graph weight vectors Heuristic algorithms

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