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International Conference on Modern Problems of Radio engineering, Telecommunications and Computer Science

作者： Roman Onyshchenko Volodymyr Barannik Kyrylo Revva Oleh Kulitsa Pavlo Pertsev Mykhailo Bielous Dept. of Information network engineering Kharkov National University of Radio Electronics Kharkiv Ukraine Dept. of Information network engineering National University of Civil Defence of Ukraine Cherkasy Ukraine Dept. of Scientific research department simulation modeling Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine

ISBN: (数字)9798331520564

ISBN: (纸本)9798331520571

This article shows that one of the most important directions in the development of information communication systems (ICS) is the construction of new generations of wireless technologies. Including such a direction is important for the creation of information technology support systems and decision-making for the management of critical infrastructure objects. It is shown that increasing the bit rate of the coded video stream is a relevant area of research. Such an advantage is proposed to be formed on the basis of structural and positional coding of segments of dynamic objects. A model for evaluating the informativeness of a transformant is created based on the fact that it is represented in the spectral space according to an uneven diagonal scheme. The construction of the information technology of the code representation of diagonals in the structural-positional space of transformants is considered.

关键词： Wireless communication Image coding Motion segmentation Redundancy Dynamic range Streaming media Market research Encoding Telecommunications Information technology

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ORDER-RELEASE PLANNING USING VARIABLE LEAD TIMES BASED ON A BACKWARD simulation-MODEL

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 1995年第10期33卷 2867-2888页

作者： WATSON, EF MEDEIROS, DJ SADOWSKI, RP Dept. Of Quantitative Business Analysis Louisiana Stale University Baton Rouge LA 70803 6316 3190 CEBA Building United States Dept. Of Industrial and Management Systems Engineering Penn State University University Park PA 16802 United States Simulation Services and Consulting Systems Modeling Corporation University Park Sewickley PA 15090 United States

The problem of order-release planning for discrete parts manufacturing is addressed. Traditionally, order-release planning in a multi-stage shop is performed with material requirements planning (MRP) logic, which generally assumes that capacity is infinite and that lead times can be estimated using historical data, past experience, and general rules-of-thumb. These assumptions often result in infeasible plans. A new approach to order-release planning termed BACKSIM, that is based on discrete simulation, is proposed. With this approach, order-release plans are generated via a backward explosion logic similar to MRP except that a simulation model of the facility is used. Since the simulation model accurately captures real-world capacity constraints and operational rules, the order-release plans are theoretically feasible. Essentially, component lead times are calculated based on the anticipated queueing in the system each time BACKSIM is executed. A technique is developed that allows BACKSIM to be fairly compared with the MRP approach.

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Non-intrusive Polynomial Chaos Expansion Based Uncertainty Analysis of Bioethanol Production Process

Non-intrusive Polynomial Chaos Expansion Based Uncertainty A...

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International Conference on Computing, Mathematics and engineering Technologies (iCoMET)

作者： Iftikhar Ahmad Uzair Ibrahim Zumrud Imdad Gulsayyar Ali Dept. of Chemical and Material Engineering National University of Sciences and Technology Islamabad Pakistan National University of Sciences and Technology Islamabad PK Research Center for Modeling and Simulation National University of Sciences and Technology Islamabad Pakistan

Ethanol production has been a topic of great interest since the world found the significance of renewable biofuels. Process efficiency and sustainability are main points of focus for ethanol production. Uncertainty in input parameters and its effect on the process outcome, i.e., ethanol production, has been a challenge in realizing efficient operations for the process. This study aims quantification of the effect of uncertainty in process inputs on the production of ethanol. The study is based on an Aspen PLUS® flowsheet of ethanol production from corn stover. MATLAB®-Excel®-Aspen® interfacing is used to estimate ethanol production for different values of input variables. The data generated through the interfacing was used to develop a data-driven model. The data-driven model based on the idea of ensemble learning was used within a Polynomial Chaos Expansion to quantify the accumulative effect of uncertainty in process input variable on process output, i.e., ethanol production.

关键词： Uncertainty Production Ethanol Input variables Mathematical model Biochemistry Temperature distribution

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Models and representation of their ownership

Models and representation of their ownership

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simulation Winter Conference

作者： H.S. Sarjoughian B.P. Zeigler Dept. of Electr. & Comput. Eng. Arizona Univ. Tucson AZ USA Arizona Center for Integrative Modeling and Simulation Electrical and Computer Engineering Department University of Arizona Tucson Tucson AZ USA

Models, similar to other intellectual properties, are increasingly being treated as commodities worthy of protection. Providing ownership for models is key for promoting model reusability, composability, and distributed simulation. However, to date, it appears no principled approach has been developed to support ownership of models. Instead, individuals such as modelers and legal personnel employ ad hoc means to obtain and (re)use models developed and owned by others. We briefly describe access control capabilities offered by computer languages, operating systems, and HLA ownership management services. The examinations of such methods suggest the need for formal ownership specification. We discuss, in an informal setting, requirements for model ownership from the point of view of increasing demand and necessity for model reuse, distributed simulation, and future trends for collaborative model development. We develop concepts for model ownership suitable for collaborative model development and distributed execution. Based on the developed concepts, we present an approach, within the DEVS modeling and simulation framework, for specifying model ownership. We close with the consideration of the proposed approach for the Collaborative DEVS modeling environment and a brief discussion of HLA services relevant to model ownership.

关键词： Collaboration Computational modeling Intellectual property Protection Law Legal factors Personnel Access control Computer languages Operating systems

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An Explainable AI-Enabled Framework for the Diabetes Classification

An Explainable AI-Enabled Framework for the Diabetes Classif...

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Machine Learning and Applied Network Technologies (ICMLANT), IEEE International Conference on

作者： Cu Kim Long Vikram Puri Vijender Kumar Solanki Gloria Jeanette Rincón Aponte Information Technology Center Ministry of Science and Technology (MOST) Hanoi Vietnam Center of Visualization and Simulation Duy Tan University Da Nang Vietnam Dept. of Computer Science and Engineering CMR Institute of Technology Hyderabad TS India Universidad Cooperativa de Colombia Bogota Colombia

Nowadays, Diabetes has become a prominent health issue that spans several categories determined by characteristics such as clinical presentation, disease progression, and pathophysiology. A real-time monitoring and management system is necessary to mitigate this life-threatening disease and safeguard individuals. The potential of Artificial Intelligence (AI) to change the management of Diabetes and enhance outcomes for persons with the condition is substantial. While AI shows promise in its ability to forecast Diabetes, it also presents a challenge due to its black-box nature. To address this concern, a proposed framework incorporating explainable AI is suggested for classifying Diabetes. This framework serves to elucidate the decisions made by the AI model. Furthermore, it was assessed using three distinct datasets categorized according to Diabetes categorization. Understanding the decision-making process of AI in the medical field fosters trust between healthcare providers and patients.

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Design space visualization and its application to a design by shopping paradigm

Design space visualization and its application to a design b...

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2003 ASME Design engineering Technical Conferences and Computers and Information in engineering Conference

作者： Stump, Gary M. Simpson, Timothy W. Yukish, Mike Harris, E. Nathan Applied Research Laboratory Pennsylvania State University University Park PA 16802 United States Dept. of Mechanical Engineering Pennsylvania State University University Park PA 16802 United States Prod. and Process Design Department Applied Research Laboratory Pennsylvania State University University Park PA 16802 United States Modeling and Simulation Lockheed Martin Space Systems Space and Strategic Missiles Denver CO 80201 United States

We have developed a data visualization interface that facilitates a design by shopping paradigm, allowing a decision-maker to form a preference by viewing a rich set of good designs and use this preference to choose an optimal design. Design automation has allowed us to implement this paradigm, since a large number of designs can be synthesized in a short period of time. The interface allows users to visualize complex design spaces by using multi-dimensional visualization techniques that include customizable glyph plots, parallel coordinates, linked views, brushing, and histograms. As is common with data mining tools, the user can specify upper and lower bounds on the design space variables, assign variables to glyph axes and parallel coordinate plots, and dynamically brush variables. Additionally, preference shading for visualizing a user's preference structure and algorithms for visualizing the Pareto frontier have been incorporated into the interface to help shape a decision-maker's preference. Use of the interface is demonstrated using a satellite design example by highlighting different preference structures and resulting Pareto frontiers. The capabilities of the design by shopping interface were driven by real industrial customer needs, and the interface was demonstrated at a spacecraft design conducted by a team at Lockheed Martin, consisting of Mars spacecraft design experts.

关键词： Computer aided design

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Evolutionary Interest Representation Network for Click-Through Rate Prediction

Evolutionary Interest Representation Network for Click-Throu...

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IEEE International Conference on Web Services (ICWS)

作者： Renjie Zhou Zhenming Jin Jian Wan Jilin Zhang Xingyu Guo Qiang Liu Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education ITMO Joint Institute Hangzhou Dianzi University Hangzhou China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou China Dept. of Computer and Information Technology Zhejiang Police College Hangzhou China

The rapid development of the Internet has revo-lutionized our lives, providing us with an array of convenient services. However, this revolution has also led to the problem of data overload. Personalized recommendation services have been widely recognized as an effective solution to this problem by both the industrial and academic communities. Accurate prediction of click-through rate (CTR) is a critical task in personalized recommendation systems since it can improve the user’s shopping experience, ultimately increasing revenue for the platform. To achieve accurate CTR prediction, it is crucial to capture user interests. While several methods for interest modeling exist, challenges related to user interest evolution and user behavior noise need further attention. This paper proposes a novel CTR prediction model named the Evolutionary Interest Representation Network (EIRN), which learns the evolving interest representation of users from their behaviors, profiles, and environmental attributes. In the model, we introduce an advertisement correlation graph decomposition layer and a noise filter layer to enhance and purify the user behavior representation. An interest extraction layer is designed to capture sequential correlations and common characteristics between user behaviors, representing their interests. Additionally, as user interests evolve over time and their importance changes, an attention-based interest evolution layer is designed to track the evolution of user interests. Our proposed method is validated using four public datasets and an industrial dataset, showing its superiority over existing CTR prediction methods.

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An SDN-IoT-based framework for future smart cities: Addressing perspective

arXiv

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arXiv 2020年

作者： Ghosh, Uttam Chatterjee, Pushpita Shetty, Sachin Datta, Raja Department of EECS Vanderbilt University NashvilleTN37235 United States Department of Computational Modeling and Simulation Engineering Old Dominion University SuffolkVA23435 United States Dept. of Electronics and Electrical Communication Engineering Indian Institute of Technology Kharagpur Kharagpur West Bengal721302 India

In smart this cities Chapter has , been a software-defined proposed and discussed. network (SDN)-based It also comprises framework a distributed for future addressing scheme to facilitate the allocation of addresses to devices in the smart city dynamically. The framework is dynamic and modules can be added and omitted by a centralized controlling unit without disturbing the other components of the framework and other modules may be updated accordingly. In the proposed addressing scheme, a new Internet of Things (IoT) device will receive an IP address from one of their existing neighboring peer devices. This allows devices in the city to act as a proxy and generate a set of unique IP addresses from their own IP addresses, which can then be assigned to new (joining) devices;hence, reducing addressing overhead and latency, as well as avoiding the need to send broadcast messages during the address allocation process. Thus, it achieves considerable bandwidth and energy savings for the IoT devices. Copyright © 2020, The Authors. All rights reserved.

关键词： Internet of things

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Human Activity Classification using G-XGB

Human Activity Classification using G-XGB

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Data Science and Network Security (ICDSNS), International Conference on

作者： Aman Kataria Vikram Puri Piyush Kumar Pareek Sita Rani Amity Institute of Defence Technology Amity University Noida India Center of Visualization and Simulation Duy Tan University Da Nang Vietnam Dept. of Artificial Intelligence and Machine Learning and IPR Cell Nitte Meenakshi Institute of Technology Bengaluru India Department of Computer Science and Engineering Guru Nanak Dev Engineering College Ludhiana India

Wearable body sensors have recently gained popularity because they monitor user behaviors and vital indicators. These sensors are designed to monitor various physiological factors, such as motion, temperature, and heart rate, among others. Making sense of the data gathered by these sensors requires separating the dependent and independent features. The dependent parameters are those that body-worn sensors can read in this scenario. Examples of such elements include blood oxygen levels, heart rate, temperature, mobility, and airflow. These sensors capture data about a person's activity and health. The independent parameters in wearable body sensors are related to the dependent parameters, whereas the dependent parameters are those that the sensors can measure directly. Such characteristics include age, sex, weight, and environmental influences. For example, humidity and airflow might impair a temperature sensor's accuracy. The user's age or level of physical fitness may also influence the accuracy of a heart rate monitor. Activity monitors are used in this study to capture the actions of various people. Static and dynamic properties are derived from the activity monitor recording. The performance evaluations of the eight distinct machine-learning models that were created using the retrieved features are discussed in this paper. The Grid Search method is used to enhance the performance of the XGB model.

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Blockchain-enabled Transparent and Trustworthy Regulation System for Smart Cities

Blockchain-enabled Transparent and Trustworthy Regulation Sy...

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Cyber Physical Systems, Power Electronics and Electric Vehicles (ICPEEV), International Conference on

作者： Vikram Puri Vijender Kumar Solanki Aman Kataria Cu Kim Long Center of Visualization and Simulation Duy Tan University Da Nang Vietnam Dept. of Computer Science and Engineering CMR Institute of Technology Hyderabad TS India Amity Institute of Defence Technology Amity University Uttar Pradesh India Information Technology Center Ministry of Science and Technology (MOST) Hanoi Vietnam

The development and growth of the shared economy in the smart cities are significantly influenced by technology. An online community-based ecosystem that enables peer-to-peer trade between buyers and sellers as well as share- and rental-based access to goods and services. Lack of trust and transparency is the main problem in the shared economy system. A blockchain-enabled architecture is created for the shared economy ecosystem to address this problem. In this study, product registration and product services policies are implemented using smart contracts. This technology aids in distinguishing between genuine and counterfeit goods while also giving consumers access to the product’s metadata via QR codes. An experimental testbed that makes use of the polygon network is taken into consideration in order to validate the suggested framework.

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