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IEEE Latin American Robotics Symposium, LARS

作者： Héber Renato Fadel de Morais João Paulo Lima Silva de Almeida Lúcia Valéria Ramos de Arruda Graduate Program in Electrical Engineering and Industrial Informatics (CPGEI) Federal University of Technology - Paraná Curitiba Brazil Federal Institute of Paraná Jacarezinho Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

This paper develops a system based on cyber-physical concepts to support robots in tasks that require cooperative work and information sharing. The work's inspiration is the need of the 4.0 industry for cobots visiting different workstations to assist human workers, for tools and raw material transportation, and other tasks. As in any industrial environment, unexpected events may occur, and the cobots must face them, reducing their effects on the production line. In this work, multiple robots (MR) managed by a system with cyber-physical (CP) features cooperate in an experimental dynamic environment to safely accomplish several tasks. For this, the robots must visit targets (analogous to workstations) in an orderly way, while one support robot must deal with oil stains on the environment's floor detected along the robots' navigation (unexpected event). The proposed CP-MR system is evaluated through experimental results allowing a performance analysis.

关键词： Visualization Service robots Federated learning Information sharing Robot sensing systems Workstations Multi-robot systems

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New Energy-Efficient 3-2 and 4-2 Approximate Adder Compressors Topologies

New Energy-Efficient 3-2 and 4-2 Approximate Adder Compresso...

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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Rodrigo Lopes Leonardo Antonietti Morgana M. A. Rosa Eduardo Costa Rafael Soares Sergio Bampi Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil PPGC & PGMICRO - Informatics Institute Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil

Addition units are present across many computational kernels inherent in various error-tolerant applications, including machine learning, signal, image, and video processing. Notably, adder compressors are the target when high speed and low power are the main design concerns. This work introduces energy-efficient structures of 3-2 approximate adder compressors (Ax3-2) and three distinct versions of 4-2 approximate adder compressors (Ax4-2). We compared our proposed Ax3-2 and Ax4-2 compressors with state-of-the-art energy-efficient approximate adder compressors (AxACs). Both Ax3-2 and Ax4-2 models passed through rigorous tests as standalone units. Furthermore, we integrated the Ax4-2 models into an essential application kernel appearing in video coding, i.e., the Sum Squared Differences (SSD) video accelerator. We introduce Ax3-2 and Ax4-2 that yield a new Pareto front concerning both energy-quality and area-quality trade-offs, thereby demonstrating a marked improvement over the prevailing state-of-the-art energy-efficient AxACs.

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programmable multimode squeezed light at visible wavelengths with >400 modes

Programmable multimode squeezed light at visible wavelengths...

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CLEO: Fundamental Science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Presutti, Federico Wright, Logan G. Ma, Shi-Yuan Wang, Tianyu Malia, Benjamin K. Onodera, Tatsuhiro McMahon, Peter L. School of Applied and Engineering Physics Cornell University 142 Sciences Dr IthacaNY14850 United States NTT Physics and Informatics Laboratories NTT Research Inc. 940 Stewart Dr SunnyvaleCA94085 United States Intelligence Community Postdoctoral Research Fellowship Program 142 Sciences Dr IthacaNY14850 United States Kavli Institute Cornell for Nanoscale Science Cornell University 245 Feeney Way IthacaNY14850 United States

We demonstrate a source of highly multimode, high gain vacuum squeezed light, and demonstrate how ultra-broadband frequency conversion enables the use of visible-light detector arrays and programmable frequency-domain... 详细信息

ISBN: (纸本)9781957171395

关键词： Squeezed light

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Evolutionary Trends of Intelligent IoT Networking for Commercial and Industrial Use Cases

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中国通信（英文版） 2023年第8期20卷前插1-前插4页

作者： Shuai Han Rong Bo Nadra Guizani Sai Xu Ruoyu Su Liang Xiao Cheng Li Department of Electronics and Communication Engineering Harbin Institute of Technology Communications Research Centre Canada Engineering program and the computing Research Association School of Cybersecurity Northwestern Polytechnical UniversityXi'anChina Nanjing University of Posts and Telecommunications Department of Informatics and Communication Engineering Xiamen Univer- sityFujianChina Department of Electrical and Computer Engineering of Memorial University St.John'sCanada

The intelligent Internet of Things(IIoT)is one of the key enablers for the digital transformation of traditional industries towards Industry *** services have diversified requirements due to the nature of their commercial and industrial *** various devices in IIoT environments have their unique properties in terms of resource limita-tions,network lifetimes,and application Quali-ty-of-Service(QoS)requirements which affect the performance under such applications ***,IoT devices typically have constrained power,storage,computing,high latency,massive multiple access and communications resources which limit the performance of IIoT for commercial and industrial Use *** the other hand,devices used in IIoT were not initially designed with security in mind and they had been considered *** response to the above challenges,domestic and foreign scholars have gradually carried out research on network architecture,collaborative scheduling strategy,energy supply technology,resource man-agement,and ***,the research on IIoT is still in its infancy,and has not yet formed comprehen-sive and systematic theoretical methods and technical standards.

关键词： Special issues and sections Internet of Things Intelligent systems Commercialization Requirements engineering Industrial engineering

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Real-time Vehicular Sensing System Design for Integrated Sensing as Service and IoT Platform in Smart Cities

Real-time Vehicular Sensing System Design for Integrated Sen...

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International Conference on ICT For Smart Society (ICISS)

作者： Mindit Eriyadi Fetty Fitriyanti Lubis Suhono Harso Supangkat Fadhil Hidayat Doctoral Program of Instiut Teknologi Bandung Indonesia School of Applied Science Universitas Telkom Bandung Indonesia School of Electrical Engineering and Informatics Instiut Teknologi Bandung Indonesia Smart City and Community Innovation Center Institut Teknologi Bandung Bandung Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

This study focuses on the design and implementation of a Real-time Vehicular Sensing System (RVSS) aimed at enhancing air quality monitoring in smart cities. By integrating advanced sensors into moving vehicles, the system captures real-time environmental data across diverse urban areas. This research addresses the limitations of static monitoring stations, offering broader geographical coverage and greater data collection flexibility. The proposed system includes low-cost components, enhanced sensor calibration, and optimized data processing algorithms to ensure accurate and reliable data. It also features real-time data transmission and a user-friendly dashboard for dynamic monitoring. The primary contribution of this study is to establish a robust foundation for an effective Vehicular Sensing system, providing valuable insights for researchers and policymakers to improve air quality management in smart cities.

关键词： Smart cities Heuristic algorithms Air quality Real-time systems Sensor systems Reliability Vehicle dynamics Monitoring Intelligent sensors System analysis and design

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Streamlining CLABSI Diagnosis: An Innovative Process Modeling Approach Using UML Activity Diagrams

Streamlining CLABSI Diagnosis: An Innovative Process Modelin...

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2024 Global Digital Health Knowledge Exchange and Empowerment Conference, gDigiHealth.KEE 2024

作者： Daboor, Mohammad Kharbat, Faten Azzuni, Fathi mueen Sultan, Iyad Odeh, Mohammad King Hussein Cancer center Nursing Department Amman Jordan College of Engineering Al Ain University Abu Dhabi United Arab Emirates Kanad Hospital Pediatric Department Abu Dhabi AlAin United Arab Emirates King Hussein Cancer Center Department of Pediatrics Amman Jordan Cancer Care Informatics Program Amman Jordan College of Art Technology and Environment University of the West of England Bristol United Kingdom Global Academy for Digital Health Bristol United Kingdom

ISBN: (纸本)9798331531331

This paper presents the development and validation of a Unified Modeling Language (UML) Activity Diagram for diagnosing Central Line-Associated Bloodstream Infections (CLABSIs) based on guidelines from the Centers for Disease Control and Prevention (CDC) and the National Healthcare Safety Network (NHSN). The activity diagram translates complex guidelines into an accessible visual model, refined through iterative feedback from domain experts in healthcare and software engineering. This tool aims to enhance understanding, adherence, and education regarding CLABSI diagnosis, ultimately improving diagnostic accuracy and consistency. Additionally, the diagram serves as a foundation for developing software applications to automate the detection and diagnosis of CLABSIs, further enhancing clinical efficiency and patient outcomes. By providing a clear and structured process model, this study contributes significantly to the field of healthcare informatics and patient safety. © 2024 IEEE.

关键词： Application programs

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Multi Task Classification Using Deep Learning Approaches for Big Five Personality Traits Prediction: A Review

Multi Task Classification Using Deep Learning Approaches for...

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International Conference on Information Technology, Computer and Electrical engineering (ICITACEE)

作者： Salamun Rohman Nudin Rahmat Gernowo Maman Somantri Adi Wibowo Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Physics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia Department of Electrical Engineering Faculty of Engineering Diponegoro University Semarang Indonesia Department of Informatics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia

ISBN: (数字)9798350389302

ISBN: (纸本)9798350389319

This paper presents a comprehensive review of deep learning methods for the Big Five personality traits prediction using multi-task classification. The purpose of the review is to determine the performance of models developed in previous research to describe research opportunities and challenges in the future. The Big Five model is a framework in psychology that categorizes human personality into five dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. The review begins by analyzing 22 articles from the Science Direct, IEEE Xplore, and Scopus databases by applying screening using the Big Five Personality keywords. Then study the concepts of deep learning for model development such as: input, architecture, method, dataset, and performance to identify the strengths and limitations of each approach. The review results of the highest average accuracy by modality such as unimodal text with essay dataset (80.98 % ), unimodal image with ImageNet dataset (95.36%), unimodal audio with SSPNet dataset (79.48%), bimodal image and audio with Chalearn Video First Impression dataset (91.67 % ), multimodal text, image, and audio with Chalearn Video First Impression dataset (91.88%). The average accuracy of the Big Five Personality traits was highest (95.36 % ) and lowest (59 % ). This highlights the need for standard benchmarks, interpretable models and interdisciplinary collaboration to improve the accuracy, reliability and ethical implications of personality prediction. Future research is expected to pave the way for advancements in understanding human personality through deep learning approaches using other modalities such as EEG, GSR, and PPG.

关键词： Deep learning Accuracy Reviews Psychology Predictive models Brain modeling Multitasking Reliability Information technology Standards

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Energy Preservation in MANET Using Self-Adaptive CH Selection with Advanced Genetic Algorithm 1

Energy Preservation in MANET Using Self-Adaptive CH Selectio...

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1st International Conference on Advanced engineering and Technologies, ICONNIC 2023

作者： Indriyono, Bonifacius Vicky Pamungkas, Natalinda Abbas, Fatima Hashim Mintorini, Ery Almohamadi, Mohammed Mahmood, Sarmad Nozad Alani, Sameer Alkhayyat, Ahmed H. Rachmawanto, Eko Hari University of Dian Nuswantoro Information System Kediri Indonesia Al-Mustaqbal University College Medical Laboratories Techniques Department Hillah51001 Iraq University of Dian Nuswantoro Visual Communication Design Kediri Indonesia College of Information Technology Imam Ja'afar Al-Sadiq University Al-Muthanna66002 Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq University of Mashreq Research Center Medical Laboratories Techniques Baghdad Iraq College of Technical Engineering University of Mashreq the Islamic University Najaf Iraq University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia

ISBN: (纸本)9798350306484

Mobile Adhoc Networks (MANETs) is an emerging technology in both the industrial and academic research. The major drawback in MANETs is improving the battery capacity. MANETs are dynamic in nature therefore during communication it consumes more energy that reduces the overall energy efficiency of the network. Many past and present researches are concern about this problem. In this paper, Energy Preservation in MANETs using Self-Adaptive Cluster Head Selection with Advanced Genetic Algorithm (EPMSA-CHAG) approach is proposed where the CH selection is performed using two segments;they are initial parameter based on CH selection and Advanced Genetic Algorithm (AGA) based CH selection. At the initial stage the parameters which are considered for the CH selection are node degree, node stability, distance, residual energy, and speed and delivery rate. Using these parameters are the best fit for CH selection is chosen then in order to find the optimal best fit from the best fit calculation, Advanced Genetic Algorithm (AGA). The proposed EPMSA-CHAG approach is simulated using NS2 and the parameters which are considered for the performance analysis are packet delivery rate, energy efficiency, end to end delay, routing overhead and throughput. The methods that are taken for the comparative analysis are HLSPM-CHSR and HAMBO-CHLD. From the results calculated it is proven that the proposed EPMSA-CHAG approach achieved high packet delivery rate, energy efficiency and throughput as well as lower end to end delay and routing overhead when compared with the earlier methods HLSPM-CHSR and HAMBO-CHLD. © 2023 IEEE.

关键词： Energy efficiency

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Diabetes Classification Problem with CatBoost Method and Optuna Gradient Boosting Optimization

Diabetes Classification Problem with CatBoost Method and Opt...

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International Conference on Information and Communications Technology (ICOIACT)

作者： Safar Dwi Kurniawan Purwono Purwono Alfian Ma’Arif Iswanto Suwarno Department of Computer Engineering Politeknik Harapan Bersama Tegal Indonesia Department of Informatics Universitas Harapan Bangsa Purwokerto Indonesia Department of Electrical Engineering Universitas Ahmad Dahlan Yogyakarta Indonesia Department of Engineer Professional Program Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia

Diabetes mellitus is a dangerous global epidemic that can cause kidney failure, heart attack, blindness, and death. The main cause of this disease is too high blood sugar levels due to the irrelevant work of pancreatic beta cells. Rapid computer technology advances and implementations based on artificial intelligence have penetrated various fields, especially the health sector. Data mining and machine learning are technologies that continue to grow, are reliable, and can be used as research support tools in the medical field. This technology is considered capable of helping to automate diabetes prediction. Based on related research, our contribution to this research is to utilize the CatBoost method with Optuna optimization. In the data preprocessing stage, all 768 data sets have gone through removing outliers, normalizing features to reducing dimensions. The dataset is divided into $85 \%$ composition for training data and $15 \%$ for test data. At the feature selection stage with Correlation Pearson’s, we found that Glucose correlated with diabetes outcome or disease because it had a value range of 0.47. The results’ accuracy is considered less than optimal because it only produces an accuracy value below $80 \%$, even after optimization with Optuna. It can be seen that there was only an increase of $7 \%$ after optimizing with Optuna.

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Energy Planning and Utilization in the North Sulawesi Electricity System

Energy Planning and Utilization in the North Sulawesi Electr...

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International Conference on Electrical engineering and informatics, ICEEI

作者： Arif Majiid Nusa Pratama Bagas Maulana Sutardi Irfan Zidny Irvan Lewi Hasanuddin Syarif Hidayat Pradita Octaviandiningrum Hadi Graduate Program PLN-ITB PLN Corporate University Jakarta Indonesia PLN UIP3B Sulawesi Makassar Indonesia Bandung Institute of Technology School of Electrical and Informatics Engineering Bandung Indonesia

Energy sector is one of the contributors to climate change besides forestry, environment, and transportation sectors. Then, the results of the COP 26 in Glasgow meeting states that Indonesia have a target to achieve Net Zero Emission (NZE) by 2060 if there is international support for funding and technology with some note that this project does not interfere with availability and affordability. In achieving the zero-emission target, the government is implementing five main principles, which include increasing the use of new renewable energy (NRE), reducing fossil energy, explore the use of electric vehicles in the transportation sector, increasing the use of electricity in households and industries, and utilizing Carbon Capture and Storage (CCS). In this paper several proposals can be made to further reduce production costs and reduce greenhouse gas emissions in the North Sulawesi system compared to Electricity Supply Business Plan by PLN which is called RUPTL. Two additional scenarios can be used for the proposal, which are addition of geothermal, solar and pump hydro to replace coal power plant and construction of North Sulawesi interconnection with Central Sulawesi. From the simulation results of the cost and carbon emission analysis between three scenarios, the scenario from RUPTL is the cheapest in terms of cost at 3.295 billion USD and the interconnection scenario is the smallest in terms of emissions, with CO 2 emissions reaching 0 Mt.

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