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2023 IEEE International Symposium on Antennas and Propagation, ISAP 2023

作者： Iihoshi, Yohei Okubo, Kan Department of Electrical Engineering and Computer Science Faculty of System Design Tokyo Metropolitan University Hino Tokyo Japan

ISBN: (纸本)9798350341140

This study presents a pilot study on the potential future use of aerial sound sources utilizing parametric array loudspeakers (PALs) in drones via fifth-generation (5G) networks. Integrating superdirectional loudspeakers with high-speed wireless communication is essential for projecting sound from the air to specific locations using drones. Herein, as an experimental approach, we have evaluated the performance of wireless communication, specifically local 5G, for realizing aerial sound sources. The results demonstrated the high performance of the local 5G connection intended for PALs in the air. © 2023 IEEE.

关键词： 5G networks aerial sound source millimeter wave band parametric array loudspeaker wireless communication

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Hybrid NN-DT cascade method for generating decision trees from backpropagation neural networks 9

Hybrid NN-DT cascade method for generating decision trees fr...

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9th International Conference on Neural Information Processing, ICONIP 2002

作者： Zorman, M. Kokol, P. Laboratory for System Design Faculty of Electrical Engineering and Computer Science University of Maribor MariborSI-2000 Slovenia

ISBN: (纸本)9810475241

Transforming knowledge between connectionist and symbolic machine learning approaches is not a uniform task and there is no general recipe for performing it. Irrespective of the way the transformation of knowledge, the developed methods usually fall into two classes: methods with high rate of transformed knowledge is done, but with a lot of restrictions concerning the type of data in the training sets, training methods, and the size of data sets;and methods with moderate rate of transformed knowledge, but with less restrictions. Our main interest was to find or develop a technique that would possess the knowledge acquisition power of neural networks and explanation power of decision trees. That is why we developed a NN-DT Cascade method, an embedded hybrid of neural networks and decision trees, which is capable of transforming a part of knowledge from the neural network into a decision tree. © 2002 Nanyang Technological University.

关键词： Decision trees

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Analysis of thickness-profiled gratings for oblique incidence using approximate modeling by plane gratings with surface resistance

Analysis of thickness-profiled gratings for oblique incidenc...

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作者： Wakabayashi, Hideaki Yamakita, Jiro Faculty of Computer Science and System Engineering Okayama Préfectoral University Soja Okayama 719-1197 Japan

In this paper, we demonstrate that thickness-profiled metallic gratings placed in a conical mounting can be approximated by a plane grating with surface resistance as a function of the position parameter. As for the method of analysis of thickness-profiled metallic gratings, we apply the multilayered step method, in which the grating region is partitioned into a set of stratified layers having rectangular-profiled gratings, and the flux densities expansion approach. As for the method of analysis for plane gratings with a thickness of zero, a spectral Galerkin method based on the mixed form of current expansions in the spectral and spatial domains is applied to the resistive boundary condition. Both methods are formulated for the three-dimensional scattering problem by linearly and circularly polarized incidence. From a comparison of the numerical results of thickness-profiled and plane metallic gratings for oblique incidence, the limit of the thickness is investigated. Copyright 2009 by the American Geophysical Union.

关键词： Diffraction gratings

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A code generator for component oriented programming framework

A code generator for component oriented programming framewor...

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2nd IEEE International Conference on Open systems, ICOS 2011

作者： Talab, Mahmood Aghajani Siroos Jawawi, Dayang N. A. Department of Software Engineering Faculty of Computer Science and Information System Universiti Teknologi Malaysia Johor Bahru Malaysia

ISBN: (纸本)9781612849317

A component-based Embedded Real Time (ERT) system can improve the system development through enhancing the ability of experts in developing sophisticated ERT software. In order to generate codes, ERT code generator system frameworks have generally two parts: a graphical semi-formal-model representation to define the components, and an optimal code generator that generates codes for a resource limited microcontroller. The Unified Modelling Language(UML) semi-formal-model system does not deal with minute details of the code generation (e.g. IF, THEN, ..). Currently, code generators use a state diagram semi-formal-model to provide optimal codes. However, manual coding has not been quit entirely since current state diagrams are not capable of providing details in code generation. The Component Oriented Programming framework (COP) is an ERT framework which targets on the code generation required in Autonomous Mobile Robot (AMR). Currently, the COP framework can not provide the AMR with code details. This paper presents an implementation of a code generator through exploiting a previously used algorithm to create a state diagram based on information taken from the component composition in the COP framework. Consequently, manual coding in the COP framework can be minimized. © 2011 IEEE.

关键词： Unified Modeling Language

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Estimation of growth of ovarian follicles using rigid and elastic ultrasound image registration

Estimation of growth of ovarian follicles using rigid and el...

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3rd International Conference on Bio-inspired systems and Signal Processing, BIOSIGNALS 2010

作者： Šprager, Sebastijan Cigale, Boris Zazula, Damjan System Software Laboratory Faculty of Electrical Engineering and Computer Science Smetanova Ulica 17 2000 Maribor Slovenia

ISBN: (纸本)9789896740184

In this paper, a method for assessment of the ovarian follicle growth is presented. 3D ultrasound volumes of ovaries are processed. Ovarian follicles are shown as hypoechogenic areas in the cross-section images. In first phase, global translations and rotations of two observed follicle constellations from two consecutive ovary examinations are detected. In second phase, detailed local deformations are estimated using elastic registration. The proposed method has been tested using artificial simulated models of ultrasound images of ovaries. Preliminary results shows the proposed method is efficient and reliably detects deformations ovarian follicles cause by their growth.

关键词： Image registration

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Automated biological pathway knowledge retrieval based on semantic web services composition and AI Planning

Automated biological pathway knowledge retrieval based on se...

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2012 International Conference on Information Retrieval and Knowledge Management, CAMP'12

作者： Bin Remli, Muhammad Akmal Bin Deris, Safaai Department of Software Engineering Faculty of Computer Science and Information System University Teknologi Malaysia Skudai Johor Malaysia

ISBN: (纸本)9781467310901

This paper presents the experience gained on semantic web service composition technique applied to the bioinformatics domain. Specifically, the approach presented here consists of knowledge retrieval perspective in biological pathway. Semantic web services, annotated with domain ontology are used to describe services for pathway knowledge retrieval for Kyoto Encyclopedia of Gene and Genomes (KEGG) database. Retrieving knowledge can be seen as high level goals and the tasks involved can be decomposed into subtask to achieve the specified goals. We execute the composition of service by treating composition as planning problem using Hierarchical Task Network (HTN) planning system based on Simple Hierarchical Order Planner 2 (SHOP2). The approach for plan (task) decomposition using SHOP2 is implemented in automated way. We investigate the effectiveness of this approach by applying real world scenario in pathway information retrieval for Lactococcus Lactis (L. lactis) organism where biologists need to find out the pathway description from the given specific gene of interest. © 2012 IEEE.

关键词： Genes

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A stochastic approach to the probability of failure on demand (PFD) with regard to the standard IEC 61508

A stochastic approach to the probability of failure on deman...

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11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012

作者： Wacker, H.D. Ugljesa, E. Boercsoek, J. Department of Computer Architecture and System Programming Faculty of Electrical Engineering /Computer Science University Kassel Wilhelmshöher Allee 71 Germany

ISBN: (纸本)9781622764365

Let there be given a safety related electronic system suffering from random failures or errors. The standard IEC 61508 contains simplified equations for the probability of failure on demand PFDavg for special system architectures, mostly without proof. In various publications PFDavg is defined by several different equations, e.g. as a Laplacian probability, as an integral mean, or by means of the average failure rate of the system. The aim of the paper is to determine PFDavgby stochastic methods and to bring together the different definitions. A formula for PFDavg is given that is valid for most universal electronic systems. The equivalence of 2 different definitions of PFDavgis shown. The special case of a koon-system is investigated, and the resulting equations improve those known so far. The basic idea is to randomize the time to failure, the down time of the system, as well as the repair time, and then, by means of the Stieltjes-Integral, determine the mean or average time as the expectation of the respective random variable.

关键词： Stochastic systems

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Challenges and Recommendation of the Information Technologies Application in Hazardous Medical Waste Management amidst Pandemic Covid-19 2

Challenges and Recommendation of the Information Technologie...

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2020 2nd International Conference on science and Technology, ICoST 2020

作者： Rahayu, P. Rohajawati, S. Fairus, S. Saragih, H. Akbar, H. Information System Computer Science Faculty Universitas Mercu Buana Jakarta Indonesia Information System Informatics and Environmental Engineering Universitas Bakrie Jakarta Indonesia Department of Informatics Computer Science Faculty Universitas Esa Unggul Jakarta Indonesia

Handling of Covid-19 patients requires more medical equipment than normal conditions, increasing the amount of hazardous medical waste. The management of hazardous medical waste has many challenges;therefore, it needed a strategy to solve it using information technology. Based on a filter of 376 articles, this review adopted a systematic Literature Review approach to evaluating the recent challenge and recommendation in the field of Hazardous Medical Waste Management amidst Covid-19. Through a four-phase workflow consisting of searching, screening, excluded, and included literature search, this study identified the most influential journals, scholars, and articles that have been influential in the domain of Hazardous Medical Waste Management. These literature review results are four challenges in Hazardous Medical Waste Management, including Regulation, Technology, Financial and Awareness. The other finding is IT application recommendations such as IoT, Big Data, DSS, AI and GIS. By providing the latest research about the challenges and recommendations in the domain of Hazardous Medical Waste Management amidst Covid-19, the paper serves as a preliminary recommendation for practitioners and researchers to link current research to future trends. © 2021 Published under licence by IOP Publishing Ltd.

关键词： Diagnosis

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Bald Eagle Search Algorithm with Hierarchical Deep Learning for Internet of Things Assisted Sleep Quality Recognition

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SN computer science 2024年第5期5卷 564页

作者： Duhayyim, Mesfer Al Sharif, Mahir Mohammed Munjal, Muskaan Hilal, Anwer A. Department of Computer Science College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University Al-Kharj 16273 Saudi Arabia Department of Computer Science Faculty of Computer Science and Information Technology Omdurman Islamic University Omdurman Sudan Computer Engineering Thapar Institute of Engineering and Technology Punjab Patiala India Department of Information System Faculty of Computer Science and Information Technology Omdurman Islamic University Omdurman Sudan

Sleep quality prediction in Internet of Things (IoT) involves leveraging a system of interrelated devices to gather as well as analyse related data. Smart devices like wearable devices or smart mattresses endlessly monitor many parameters such as body movement, heart rate, and environmental situations in bedroom. Real-time recommendations and feedback transported to consumers, allowing them to create informed lifestyle changes for superior sleep hygiene. As IoT ecosystem continues to develop, a combination of various data streams as well as classy analytics holds assurance for further refining sleep quality forecasts and improving overall well-being. The article designs a Bald Eagle Search Algorithm with Hierarchical Deep Learning for Internet of Things Assisted Sleep Quality Recognition (BESHDL-SQP) technique. The purpose of the BESHDL-SQP technique is to recognize and classify the quality of the sleep level in the IoT environment. In the presented BESHDL-SQP technique, the preliminary stage of data pre-processing using min–max normalization involved to normalize the input data. For predicting sleep quality, hierarchical long short-term memory (LSTM) technique exploited. Lastly, BES model utilized for optimal hyperparameter selection of LSTM method which helps in attaining enhanced results. To validate better performance of BESHDL-SQP technique, a huge range of simulation analysis is carried out. The extensive results stated that the BESHDL-SQP technique exhibits supreme performance over other models. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Bald eagle search Internet of things LSTM Sleep quality recognition Smart devices

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Exploring Deep Insights from Vast Data: An Overview of Deep Learning Techniques for Big Data 4

Exploring Deep Insights from Vast Data: An Overview of Deep ...

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4th International Conference on Electrical engineering and computer science, ICECOS 2024

作者： Baez Hasan, Sarhad Kareem, Shahab Wahhab Ameen, Didar Dlshad Hamad Soran University Faculty of Science Computer Science Department Soran Iraq Erbil Polytechnic University College of Engineering Knowledge University Department of Information System Engineering Department of Computer Engineering Erbil Iraq

ISBN: (纸本)9798350368253

Big data has emerged very fast, and this has brought both opportunities and problems that are related to the application of deep learning. This paper explores how deep learning can be implemented using big data and in particular the Apache Mahout library. Unlike most other machine learning tools, Mahout can perform distributed computation, especially while using the MapReduce frameworks including Apache Hadoop and Apache Spark. However, this study does not only focus on the explanation of the need for Mahout's integration and employment but also carries out a high-fidelity argument on how deep learning algorithms can be incorporated in the Mahout framework to optimize the manipulation of large and complicated datasets. Mahout-based contributions include the comparative analysis of key deep learning paradigms including distributed processing, parallel processing and transfer learning. This paper also includes examples of the Mahout deep learning integration use and its application in real contexts. This article describes the challenges that currently organizations face in handling big data and indeed, the potential threats these challenges pose to the success of deep learning techniques when used in organizations' big data processing and analysis. © 2024 IEEE.

关键词： Adversarial machine learning

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