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International Conference on Intelligent Transportation

作者： Xiaoming Li Hubert Normandin-Taillon Chun Wang Xiao Huang Concordia Institute for Information Systems Engineering (CIISE) Concordia University Montréal QC Canada Department of Computer Science and Software Engineering (CSSE) Concordia University Montréal QC Canada Concordia John Molson School of Business (JMSB) Concordia University Montréal QC Canada

Demand forecasting is one of the essential issues in the Mobility-on-Demand (MoD) systems. Most deep learning-based models address this issue by point prediction, which neglects stochasticity in the forecasting result. In this paper, we propose a novel deep learning-based model, the tailored recurrent mixture density network (RMDN), to forecast the demand density in the MoD systems. The tailored RMDN integrates the time-dependent sequence of historical mobility demand information with the temporal features to forecast the short-term demand density. Unlike the point prediction in the existing work, the forecasting result by tailored RMDN benefits from the predicted parameters. Namely, the predicted weights, means, and variances can be utilized to parameterize a Gaussian mixture model that can denote any shape of demand distribution. We then conduct a group of numerical experiments on the New York yellow taxi trip record data. The validation results show that by integrating the temporal features in MoD data, the tailored RMDN model can significantly improve the demand density forecasting results compared to the statistical time-series prediction model ARIMA. In particular, the tailored RMDN model outperforms the ARIMA model up to 51.3% in terms of the log-likelihood values. In addition, we observe that the tailored RMDN is tremendously superior to ARIMA in handling the high volatility in MoD demand.

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Emergency Vehicle Navigation in Connected Autonomous systems Using Enhanced Traffic Management System

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IEEE Internet of Things Journal 2025年第12期12卷 20670-20677页

作者： Raja, Gunasekaran Anbalagan, Sudha Gurumoorthy, Sugeerthi Jegathesan, Darshini Girivel, Niveditha Subramanian Sundaram, Varsha Mani Shanmuga Khowaja, Sunder Ali Dev, Kapal Anna University NGNLab Department of Computer Technology MIT Campus Chennai600044 India Vellore Institute of Technology Chennai Centre for Smart Grid Technologies School of Computer Science and Engineering Chennai600127 India Citicorp Services Private Ltd Software Development Chennai600113 India Dublin City University School of Computing Faculty of Engineering and Computing Glasnevin Campus DublinD09 V209 Ireland Munster Technological University Department of Computer Science Bishopstown CorkT12 P928 Ireland University of Johannesburg Department of Institute of Intelligent Systems Johannesburg2006 South Africa Chitkara University Institute of Engineering and Technology Centre for Research Impact Outcome Chitkara University Punjab Rajpura140401 India

Autonomous Vehicle (AV) usage has become predominant in the rapidly evolving landscape of urban transportation. Integrating AVs and non-AVs in the existing traffic infrastructure has significantly increased the complexity of traffic patterns. This research work primes the enhanced Traffic Management System (e-TMS), a solution implemented to expedite Emergency Vehicle (EV) travel in the context of Connected AVs (CAVs) and ensured secured communication employing Public Key Infrastructure (PKI) among the Internet of Vehicles (IoV) framework. When an EV is detected, the IoV system verifies the EV's signal using PKI, ensuring its authenticity and integrity by encrypting the communication between the EV and Road Side Units (RSUs). Further, the e-TMS activates the platooning process where CAVs in the EV's lane shift to the adjacent lanes and dynamically form platoons to create a dedicated lane for the EV. To further optimize the platooning process, an Adaptive Smart Leader Selection (ASLS) algorithm is employed to select a leader vehicle spontaneously among the AVs based on the proximity to the EV, communication reliability, and lane position. Radio Detection and Ranging devices aid this platooning process by providing distance and target velocity, which are needed to maintain the required distance between the AVs and ensure safe platoon formation. The e-TMS enhances EV response times and overall traffic flow efficiency and resulted in 27.8% increase in mean speed compared to the traditional methods. © 2014 IEEE.

关键词： Emergency vehicles

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On the comparison of optimal NOMA and OMA in a paradigm shift of emerging technologies

TechRxiv

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TechRxiv 2022年

作者： Ghosh, Joydev Ra, In-Ho Singh, Saurabh Haci, Hüseyin Al-Utaibi, Khaled A. Sait, Sadiq M. School of Computer Science and Robotics Tomsk Polytechnic University Tomsk Russia School of Computer Information and Communication Engineering Kunsan National University Gunsan Korea Republic of Department of Industrial & Systems Engineering Dongguk University Korea Republic of Department of Electrical and Electronics Engineering Near East University Mersin 10 Turkey Computer Science and Software Engineering Department University of Ha’il Saudi Arabia Department of Computer Engineering King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

Non-orthogonal multiple access (NOMA) is a better multiple access technique than orthogonal multiple access (OMA), precisely orthogonal frequency division multiple access (OFDMA) scheme, at the conceptual level for fifth-generation (5G) networks and beyond 5G (B5G) networks. We investigate the potentials of the schemes by comparing the proposed NOMA scheme with the traditional cooperative communication NOMA (CCNOMA) scheme, rather than the comparison between NOMA and OMA only. To probe the effectiveness of NOMA as a multiple access technique, we propose a novel NOMA scheme considering two adjacent BSs with a special design of the transceiver architecture. The proposed scheme provides a reasonable data rate to both near user (NU) and far user (FU) without compromising the quality of service (QoS) to anyone of them. The conclusive analyses on the optimization framework of multi-user sum rate, capacity, transmit power, spectral efficiency (SE), and energy efficiency (EE) trade-off for NOMA and OFDMA schemes have been established to a succession of derivations. Under the analytical optimization framework, we also prove quite a few properties for them. Simulation results confirm the theoretical findings and show that the two schemes can efficiently approach the optimal power allocation, minimization of power consumption, and optimal SE-EE trade-off, and the proposed NOMA scheme provides comparatively better data sum rates than the baseline OMA scheme. © 2022, CC BY.

关键词： Energy efficiency

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Don’t Forget the Exception! : Considering Robustness Changes to Identify Design Problems

Don’t Forget the Exception! : Considering Robustness Change...

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International Mining software Repositories, MSR

作者： Anderson Oliveira João Correia Leonardo Sousa Wesley K. G. Assunção Daniel Coutinho Alessandro Garcia Willian Oizumi Caio Barbosa Anderson Uchôa Juliana Alves Pereira Informatics Department – Pontifical Catholic University of Rio de Janeiro (PUC-Rio) Rio de Janeiro Brazil Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh United States Institute of Software Systems Engineering Johannes Kepler University (JKU) Linz Austria Federal University of Ceará (UFC) Itapajé Brazil

Modern programming languages, such as Java, use exception-handling mechanisms to guarantee the robustness of software systems. Although important, the quality of exception code is usually poor and neglected by developers. Indiscriminate robustness changes (e.g., the addition of empty catch blocks) can indicate design decisions that negatively impact the internal quality of software systems. As it is known in the literature, multiple occurrences of poor code structures, namely code smells, are strong indicators of design problems. Still, existing studies focus mainly on the correlation of maintainability smells with design problems. However, using only these smells may not be enough since developers need more context (e.g., system domain) to identify the problems in certain scenarios. Moreover, these studies do not explore how changes in the exceptional code of the methods combined with maintainability smells can give complementary evidence of design problems. By covering both regular and exception codes, the developer can have more context about the system and find complementary code smells that reinforce the presence of design problems. This work aims to leverage the identification of design problems by tracking poor robustness changes combined with maintainability smells. We investigated the correlation between robustness changes and maintainability smells on the commit history of more than 160k methods from different releases of 10 open-source software systems. We observed that maintainability smells can be worsened or even introduced when robustness changes are performed. This scenario mainly happened for the smells Feature Envy, Long Method, and Dispersed Coupling. We also analyzed the co-occurrence between robustness and maintainability smells. We identified that the empty catch block and catch throwable robustness smells were the ones that co-occurred the most with maintainability smells related to the Concern Overload and Misplaced Concern design problems. T

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Robust Imagined Speech Production from Electrocorticography with Adaptive Frequency Enhancement

Robust Imagined Speech Production from Electrocorticography ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xu Xu Chong Fu Junxin Chen Gwanggil Jeon David Camacho School of Computer Science and Engineering Northeastern University Shenyang China School of Software Dalian University of Technology Dalian China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang China Engineering Research Center of Security Technology of Complex Network System Ministry of Education Shenyang China College of Information Technology Incheon National University Incheon Korea Department of Computer Systems Engineering Universidad Politécnica de Madrid Madrid Spain

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Imagined speech production with electrocorticography (ECoG) plays a crucial role in brain-computer interface system. A challenging issue is the great variation underlying the frequency bands of the ECoG signals’ encode information, which makes current methods difficult to generate imagined speech with stable quality among different persons. To this end, we propose a robust model to generate high-quality imagined speech from ECoG. A frequency enhancement branch is first designed to adaptively modulate the frequency information, whose product is fed into the following multi-scale channel attention module for robust feature extraction and fusion. By incorporating both the mel-spectrum and audio as training constraints, a multi-constraint decoder branch is finally constructed for imagined speech production. The performance of our model is evaluated on a high-quality dateset, i.e, Single Word Production Dutch-iBIDS. It yields Pearson correlation scores that are all above 0.8, and the standard deviationsare are all below 0.2 in different volunteers. Experimental results demonstrate that our model is effective and robust for ECoG based imagined speech production, and has advantages over peer methods.

关键词： Training Adaptation models Frequency modulation Correlation Neuroscience Production Speech enhancement

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Lab Color Model and Contrast Modification as a Tool for Improving the Quality of Medical Images

Lab Color Model and Contrast Modification as a Tool for Impr...

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Computational Intelligence Approaches and Applications (ICCIAA), International Conference on

作者： Amer Abu-Jassar Mohammad Hamdan Kawther Hamash Sardor Boboyorov Vyacheslav Lyashenko Department of Computer Science College of Information Technology Amman Arab University Amman Jordan College of software engineering Amman Arab University Amman Jordan WellStar school of nursing Kennesaw state university Georgia USA Tashkent Medical Academy Termiz branch Termiz Uzbekistan Department of Media Systems and Technology Kharkiv National University of Radio Electronics Kharkiv Ukraine

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

This paper addresses the challenge of enhancing the quality of medical data interpretation, specifically using color microscopic medical images for effective visualization and further analysis. The method employed involves increasing contrast by adjusting the brightness intensity values within the Lab color model, which also considers the reference white point for horizontal light. To determine the parameters for the contrasting procedure, two strategies for selecting gamma correction of the input image are explored, based on the dynamics of the resulting image quality for various no-reference quality metrics. By analyzing these dynamics, the choice of correction conditions for the contrasting procedure can be justified, rather than relying on static metrics. The paper investigates the application of these proposed strategies on different types of images, presents a formal generalization of the strategies for selecting correction parameters, and offers practical recommendations for their use.

关键词： Measurement Image quality Visualization Image color analysis Microscopy Computational modeling Data visualization Quality assessment Computational intelligence Biomedical imaging

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Speaker's Emotions Recognition Module Based on the GoogleLeNet Neural Network

Speaker's Emotions Recognition Module Based on the GoogleLeN...

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2022 International Conference on Smart Information systems and Technologies, SIST 2022

作者： Tereikovskyi, Ihor Tereikovska, Liudmyla Kryvoruchko, Olena Tereikovskyi, Oleh Tyshchenko, Dmytro Franchuk, Tamara National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of System Programming And Specialized Computer Systems Kyiv Ukraine Kyiv National University Of Construction And Architecture Dept. Of Information Technology For Design And Applied Mathematics Kyiv Ukraine Kyiv National University Of Trade And Economics Dept. Of Software Engineering And Cyber Security Kyiv Ukraine National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of Department Of Computer Engineering Kyiv Ukraine

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The article is devoted to the development of means for recognition of the emotions of the speaker, based on the neural network analysis of fixed fragments of the voice signal. The possibility of improving recognition tools through the use of a convolutional neural network of the GoogLeNet type is shown. The expediency of training the network on the examples of the TESS database is determined. A procedure for representing a voice signal in the form of a square grayscale image has been developed. Based on the use of the specified database, the modification of the GoogLeNet network was carried out. The architecture and software implementation of the recognition module have been developed. With the help of computer experiments, it has been established that after 150 epochs of training on a fairly limited training sample, the modified GoogLeNet makes it possible to achieve an accuracy of recognition of the speaker's emotions of approximately 0.97 on test examples. The obtained accuracy is comparable to the accuracy of the best modern systems of this purpose and confirms the promise of using neural network models like GoogLeNet for emotion recognition based on voice signal analysis. The need for further research aimed at reducing the resource intensity of the neural network model is shown. © 2022 IEEE.

关键词： Emotion Recognition

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Towards Blockchain-Based Secure Data Management for Remote Patient Monitoring

arXiv

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arXiv 2022年

作者： Faruk, Md Jobair Hossain Shahriar, Hossain Valero, Maria Sneha, Sweta Ahamed, Sheikh I. Rahman, Mohammad Software Engineering Department Kennesaw State University United States Information Technology Department Kennesaw State University United States Information Systems Department Kennesaw State University United States Computer Science Department Marquette University United States Electrical and Computer Engineering Department Florida International University United States

Traditional data collection, storage and processing of Electronic Health Records (EHR) utilize centralized techniques that pose several risks of single point of failure and lean the systems to a number of internal and external data breaches that compromise their reliability and availability. Blockchain is an emerging distributed technology that can solve these issues due to its immutability and architectural nature that prevent records manipulation or alterations. In this paper, we discuss the progress and opportunities of remote patient monitoring using futuristic blockchain technologies and its two primary frameworks: Ethereum and Hyperledger Fabric. We also discuss the possible blockchain use cases in software engineering for systematic, disciplined, and quantifiable application development. The study extends by introducing a system architecture for EHR data management using Ethereum as a model. We discuss the challenges and limitations along with the initial evaluation results of the proposed system and draw future research directions in this promising area. © 2022, CC BY.

关键词： Blockchain

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Development of a deep learning system for preventive detection of heart failure due to pulmonary disease

Development of a deep learning system for preventive detecti...

引用

International Conference on software Process Improvement (CIMPS)

作者： Axel Frederick Félix Jiménez Isaul Ibarra Belmonte Vania Stephany Sánchez Lee Uziel Jaramillo Avila Ezra Federico Parra González Computer Systems Engineering National Polytechnic Institute Zacatecas México Software Engineer Center for Research in Mathematics Zacatecas Zacatecas México Computer Science Department Center for Research in Mathematics Zacatecas Zacatecas México

ISBN: (纸本)9798350398977

In the context of addressing the problem of people who do not undergo a diagnosis of heart failure due to pulmonary conditions on time, a solution to this problem would allow early preventive detection to avoid the development of severe disease efficiently. Our approach employs the use of medical data retrieved from the user to determine and predict whether there is a likelihood of a potential condition. To solve this problem, according to a users medical measurement history, a deep learning model can be implemented to determine a preventive diagnosis or otherwise to follow up on an already detected condition. By posing the problem as a classification task, it can be taken advantage of a deep learning model focused on heart failure or pulmonary conditions to make a preliminary diagnosis and determine if there are signs of any symptomatology.

关键词： Cardiovascular diseases Diseases Deep learning Medical diagnostic imaging Lung Prediction algorithms Medical services

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'Permanent' algorithm for the meeting shedule problem 16

'Permanent' algorithm for the meeting shedule problem

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16th IEEE International Conference on computer Science and Information Technologies, CSIT 2021

作者： Turbal, Yuriy Babych, Sergii Kunanets, Nataliia Melnyk, Leonid Pasichnyk, Volodymyr National University of Water and Environmental Engineering Department of Computer Science and Applied Mathematics Rivne Ukraine College of National University of Life and Environmental Sciences of Ukraine Software Engineering Rivne Ukraine National University 'Lviv Polytechnic' Department of Information Systems and Networks Lviv Ukraine National University of Water and Environmental Engineering Department of Finance and Economic Security Rivne Ukraine

ISBN: (纸本)9781665442572

An algorithm for solving the problem of scheduling meetings in the process of working on a project is proposed in the paper. The problem of project managers meetings with working groups is considered under certain restrictions., the possibility of a simultaneous meeting of the project manager with one or several project groups is considered. The proposed procedure for finding the permanent allows to build all possible combinations of the meeting schedule at a given time. The specificity of the proposed approach is the ability to take into account any number of additional conditions. © 2021 IEEE.

关键词： Managers

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