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4th International Conference on Applied Physics, Simulation and Computing, APSAC 2020

作者： González, B.S. Conceio, R. Tomé, B. Pimenta, M. Herrera, L.J. Guillen, A. Computer Architecture and Technology Department University of Granada Granada Spain LIP/IST Lisbon Portugal

The aim of this paper is to study the possibility of improving the gamma/hadron discrimination in extensive air showers. For this purpose, the identification of hadronic extensive air showers is carried out by means of the detection of muons in water Cherenkov detectors (WCDs). Machine learning algorithms have proven to be useful in a wide variety of fields, and due to their outstanding performance in problems involving complex data, Convolutional Neural Networks (CNNs) have been used in the analysis of the signals measured by the WCDs. Taking simulated events, different approaches were proposed attending to the balance of the classes in the training stage. The results obtained are promising and show that machine learning algorithms provide a powerful tool for muon detection and gamma/hadron discrimination to be considered in future gamma-rays detectors like The Southern Wide-field Gamma-ray Observatory (SWGO) to be built in South America. © Published under licence by IOP Publishing Ltd.

关键词： Cosmology

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EskayApp: An Eskaya-Latin Script OCR Transliteration e-Learning Android Application using Supervised Machine Learning 21

EskayApp: An Eskaya-Latin Script OCR Transliteration e-Learn...

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Proceedings of the 5th International Conference on Digital technology in Education

作者： Max Angelo Dapitilla Perin Larmie Santos Feliscuzo Cherry Lyn Cando Sta. Romana Department of Computer Science Cebu Institute of Technology - University Philippines and College of Engineering Architecture and Industrial Design Bohol Island State University - Main Campus Philippines College of Computer Studies Cebu Institute of Technology - University Philippines

ISBN: (纸本)9781450384995

A language dies when the population that speaks it fails to pass it to their future generations. This study aims to address such problems for the Eskayas and Boholanos. The proposed EskayApp is an OCR Transliteration e-Learning Android Application that will serve as a tool to learn Eskaya. The app uses the k-Nearest Neighbors Algorithm (k-NN) for its business logic layer or backend and Supervised Machine Learning to create the application programming interface (API) for the said application. The Android application accesses the camera to capture an image of an Eskaya character and returns the Latin transliteration and the equivalent Latin character. The application got a 4.524-star rating through Google Play Store. After conducting testing, the machine learning model accuracy was 89.93% based on a 2x2 confusion matrix. A usability test was also conducted with members of the tribe as respondents. The usability review has 3 measurement items in which users can respond from 1 (Very Poor) to 5 (Excellent). The average for all the measurement items gathered from the users is 4.3-star and all the respondents want to use the e-Learning application again.

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Design and implementation of a real-time onboard system for a stratospheric balloon mission using commercial off-the-self components and a model-based approach

arXiv

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arXiv 2024年

作者： Pérez-Muñoz, Ángel-Grover Gamazo-Real, Jose-Carlos González-Bárcena, David Zamorano, Juan Universidad Politécnica de Madrid Department of Architecture and Technology of Information Systems ETSI Ingenieros Informáticos Madrid28660 Spain Universidad Politécnica de Madrid Information Systems Department Computer Architecture and Technology Area ETSI Sistemas Informáticos Madrid28031 Spain Universidad Politécnica de Madrid Instituto Universitario de Microgravedad "Ignacio Da Riva" ETSI Aeronáutica y del Espacio Madrid28040 Spain

Stratospheric balloons have emerged as an affordable and flexible alternative to traditional spacecrafts as they are implemented using commercial off-the-shelf (COTS) equipment without following strict methodologies. HERCCULES is a stratospheric balloon mission that aims to characterize the convective heat and radiative environment in the stratosphere. The purpose of this article is to present the HERCCULES onboard software (OBSW) whose design and complexity is comparable to that of satellite systems, since it must control about sixty COTS equipment using a single Raspberry Pi 4B as onboard computer and ensure the real-time requirements. Compared to similar systems, novel contributions are presented as the OBSW is developed following model-based and component-based approaches using the TASTE toolchain from the European Space. © 2024, CC BY.

关键词： Real time systems

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Recommendation System Towards Residential Energy Saving Based on Anomaly Detection 5

Recommendation System Towards Residential Energy Saving Base...

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5th International Conference on Signal Processing and Information Security, ICSPIS 2022

作者： Atalla, Shadi Himeur, Yassine Mansoor, Wathiq Amira, Abbes Fadli, Fodil Copiaco, Abigail Sohail, Shahab Saquib University of Dubai College of Engineering and IT Dubai United Arab Emirates University of Sharjah Department of Computer Science Sharjah United Arab Emirates Qatar University Dept. of Architecture & Urban Planning Doha2713 Qatar Jamia Hamdard School of Engineering Sciences & Technology New Delhi110062 India

ISBN: (纸本)9781665492652

This paper presents a recommender system to promote energy consumption reduction behaviors in residential buildings. The system exploits data stream processing methods jointly with machine learning algorithms on real-time residential data. Specifically, the data stream includes disaggregated power consumption, context, and weather conditions data. Internally the system converts time-series data streams into discrete ordered data points, which serve as inputs for training ML models. This method is used to predict power consumption anomalies. Gradually, the system helps to shape its users' activities into more energy-efficient ones. The experimental evaluation on real and simulated datasets demonstrates the promising performance of the proposed method, primarily when the K-neighbors neighbors' algorithm is used to classify the features extracted with interleaving current with the previous data points. The performance assessment of the machine learning algorithms shows the suitability of our implementation for Edge and Fog platforms in terms of accuracy, latency, and model size. © 2022 IEEE.

关键词： Electric power utilization

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Transmission Line Age Determination with Statistical Health Index and Failure Probability Curve Fitting Technique

Transmission Line Age Determination with Statistical Health ...

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International Conference on Condition Monitoring and Diagnosis, CMD

作者： Cattareeya Suwanasri Ittiphong Yongyee Thanapong Suwanasri Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand Department of Mechatronics Engineering Faculty of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi Nonthaburi Thailand Electrical and Software Systems Engineering The Sirindhorn International Thai-German Graduate School of Engineering (TGGS) King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9788986510225

ISBN: (纸本)9798350353877

The deterioration of transmission lines has a profound effect on the reliability and safety of the power grid. Accurate estimation of their age is critical for effective maintenance and investment planning. This paper proposes a method that combines the percentage statistical health index (%SHI) with failure probability curve-fitting (FPCF) to estimate the ages of overhead transmission lines. %SHI assesses equipment condition through scoring and weighting, while FPCF correlates SHI with the probability of failure. Evaluation of 924 towers situated in various terrains across Thailand reveals discrepancies between estimated and actual ages, influenced by environmental factors. To enhance reliability, proactive maintenance strategies such as regular inspections and advanced monitoring are recommended.

关键词： Power transmission lines Poles and towers Probability Inspection Maintenance Safety Planning Curve fitting Monitoring Investment

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A Review on the need of Clustering Techniques Used for Wireless Sensor Networks

A Review on the need of Clustering Techniques Used for Wirel...

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Business Analytics for technology and Security (ICBATS), International Conference on

作者： Salil Bharany Ateeq Ur Rehman M. Tariq Sadiq Muhammad Farrukh Meshal Alharbi Amjad Hussain Ghassan F. Issa CET and Technology Department Amritsar India Department of Electrical Engineering Government College University Lahore Pakistan School of Architecture & Engineering University of Brighton UK Department of Computer Science Minhaj University Lahore Pakistan Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Alkharj Saudi Arabia NCBA&E School of Computer Science Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan School of Information Technology Skyline University College Sharjah UAE

Wireless sensor networks have been implemented in various software to help gather and analyze data from the physical world. Wireless sensor networks are networks of multiple tiny sensors powered by low-energy batteries (WSNs). WSN lifetime is a critical factor. This is because, after WSNs have been deployed in a given application, the inaccessibility of the sensing nodes makes it impossible to recharge or replace the power source that is limited in energy. Until recently, WSNs were thought to be the same. All the network nodes have the same power, processing speed, and operational capacity. However, scientists have developed heterogeneous WSNs, in which the properties of individual nodes may vary, to extend the lifespan of networks. In order to extend a network's helpful life, energy-efficient protocols must be designed. Even though WSN has its own problems, it has brought a fresh perspective to studying real-time intelligent systems. WSN (Wireless Sensor Network) has gained significant popularity in the recent years, owing to its vast applications in real-time scenarios, such as disaster management, pollution monitoring, temperature monitoring, traffic monitoring, transport monitoring, healthcare monitoring, battlefield monitoring, and border security surveillance, to name a few. Numerous sensor nodes are employed in these applications. They are typically placed in the sensing field, where they automatically transfer data to the base station (BS) through energy transmission (i.e., battery in the sensor). In WSN, clustering is one method for optimizing power consumption at the sensor node. The sensor nodes are grouped and given a leader when they undergo clustering. This study overviews various WSN clustering algorithms, each categorized according to various clustering properties.

关键词： Temperature sensors Temperature measurement Wireless sensor networks Traffic control Probabilistic logic Real-time systems Sensors

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A novel Cross-Layer Protocols for Resource Allocation in Mobile Networks

A novel Cross-Layer Protocols for Resource Allocation in Mob...

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International Conference on Computing and Networking technology (ICCNT)

作者： Rakesh Kumar Giri Mani Sarma Vittapu Anoop Dev Chaitali R. Shewale Mohd Aliff Abdul Majid Nandini Kulkarni Department of Computer Science&Engineering Sunrise University Alwar India Department of Computer Science and Engineering Mallareddy Engineering College and Management Sciences Kistapur Village Medchal Hyderabad Telangana India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Information Technology Vishwakarma Institute of Technology Pune India Department of Foodservice Management Faculty of Hotel and Tourism Management University Teknology MARA Malaysia Department of Symbiosis School of Planning Architecture and Design Nagpur Symbiosis International University Nagpur India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Cross-layer Protocols for proper resource Allocation in Mobile Networks are a singular technique to enhance the efficiency of wireless networks. The method utilizes multiple layers of the radio protocol stack better to coordinate cell node scheduling and resource allocation. Using combining communication, routing, and scheduling functionalities in an unmarried protocol, pass-Layer Protocols for proper resource Allocation can offer a sizable will increase in the number of facts that may be transferred and the overall latency and throughput of the community. This technique can also enhance the radio interface’s operation by lowering interference and encouraging collaborative communications. Eventually, by using facts and managing records from the communique and routing layers, go-Layer Protocols for proper resource Allocation can reduce the complexity of the community, even offering greater scalability. This paper affords unique cross-Layer Protocols for resource Allocation in Cellular Networks. The proposed protocol permits integrated resource allocation in the cell network environment, considering communication and computation layers.

关键词： Cross layer design Protocols Scheduling algorithms Wireless networks WiMAX Streaming media Routing Throughput Resource management Wireless fidelity

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Balancing accuracy and interpretability: AI-driven predictive modeling of construction schedule performance in India

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Asian Journal of Civil Engineering 2025年 1-16页

作者： Maurya, Sudhanshu Lakkimsetty, Nageswara Rao Manjunath, T. C. Shukla, Anoop Kumar Sethy, Barada Prasad Behera, Rashmi Rekha Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Nagpur India Department of Chemical and Petroleum Engineering School of Engineering American University of Ras Al Khaimah (AURAK) Ras al Khaimah United Arab Emirates Ras al Khaimah UAE Department of Computer Science & Engineering Cyber Security & Blockchain Technology Rajarajeswari College of Engineering Bengaluru India Manipal School of Architecture and Planning Manipal Academy of Higher Education Manipal India NIST University Berhampur India Centurion University of Technology and Management Gajapati India

Construction schedule delays are a persistent challenge in India’s infrastructure sector, leading to significant cost overruns, stakeholder dissatisfaction, and inefficient resource utilization. In this context, the integration of Artificial Intelligence (AI) into project forecasting offers a promising solution. This study presents an AI-driven predictive modeling framework aimed at estimating construction schedule adherence, with a dual focus on predictive accuracy and model interpretability. Three machine learning models—multiple linear regression (MLR), artificial neural networks (ANN), and gradient boosting machine (GBM)—were developed and evaluated using real-world data from 150 construction projects across India. The models were assessed based on standard performance metrics (MAE, RMSE, R²), computational efficiency, and transparency. While MLR offered high interpretability, it lacked accuracy in handling nonlinear interactions. ANN showed high accuracy but limited explainability. GBM outperformed both, achieving the best predictive performance (R² = 0.94) and a favorable trade-off between accuracy and interpretability. Feature importance and sensitivity analyses identified equipment utilization, material availability, and labor productivity as key influencers. Case study validation further reinforced the practical value of GBM in diverse project settings. The findings advocate for the strategic adoption of interpretable AI tools like GBM in construction management to enhance scheduling precision and decision-making efficiency.

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Effect of the Mixing Structure Parameters of a Self-reflux Burner on Combustion Characteristics and NO_(x)Emission

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Journal of Thermal Science 2021年第4期30卷 1224-1236页

作者： XU Qian SHEN Meng SHI Kejian LIU Zhihui AKKURT Nevzat XIONG Yaxuan LIU Lin FENG Junxiao WANG Jiulong School of energy and environmental engineering Shunde Graduate SchoolUniversity of Science and Technology BeijingBeijing 100083China Beijing Key Laboratory of Energy Conservation and Emission Reduction for Metallurgical Industry Beijing 100083China Department of Mechanical Engineering Munzur UniversityTunceli 62000Turkey Key Laboratory of HVAC Beijing University of Civil Engineering and ArchitectureBeijing 100044China School of Mathematics and Physics University of Science and Technology BeijingBeijing 100083China Department of Big Data Technology and Application Development Computer Network Information CenterChinese Academy of SciencesBeijing 100190China

To solve the problem of low efficiency of NO_(x)emission reduction in self-reflux burners,this study is based on the concept of coordinated control of self-reflux burner structural and thermal *** completing the structural design and optimization of thermal parameters,we continue to adjust the two key structural parameters:the nozzle axis distance and the length of the cylindrical section,to minimize NO_(x)*** are the two parameters that chiefly affect the mixing of flue gas and fuel *** results show that increasing nozzle axis distance can delay the mixing of gas and air and create a more uniform oxygen concentration field for the combustion *** maximum combustion temperature is reduced from 1973.65 K to 1935.88 K and the volume fraction of NO_(x)in the flue gas is reduced from 188.08×10^(–6)to 143.47×10^(–6).However,compared with the nozzle axis distance,the length of the cylindrical section of the burner has little effect on the mixing of the flow *** different cylindrical section lengths,the maximum combustion temperature does not change more than 3 K,and the volume fraction of NO_(x)in the flue gas changes within 5×10~(–6).

关键词： self-reflux structure structural parameter control thermal parameter combustion characteristic NO_(x)emission

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Landslide Disaster Assessment with Integration of Seismic, Social Media and Remote Sensing Data

Landslide Disaster Assessment with Integration of Seismic, S...

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International Conference on Signal Processing and Information Security (ICSPIS)

作者： Deepak Rawat M. L. Sharma Roshan Kumar Nishant Saxena Atul Kumar Abdul Kadir Centre of Excellence in Disaster Mitigation and Management Indian Institute of Technology Roorkee Roorkee Uttarakhand India Department of Earthquake Engineering Roorkee Indian Institute of Technology Roorkee Roorkee Uttarakhand India Department of Electronics and Information Technology Miami College Henan University Henan Kaifeng China Department of Architecture and Planning Indian Institute of Technology Roorkee Roorkee Uttarakhand India Computer Science and Engineering Department Indian Institute of Technology Roorkee Roorkee Uttarakhand India

On February 7, 2021, a rockfall in the Rishiganga Valley killed about 200 people. For the integration of seismic, social media, and remote sensing, a case study on this tragedy has been conducted. This study explores the role of social media in managing Himalayan landslides in conjunction with remote sensing data analytics. We look at how these technologies can enhance damage management, quick mobilization, and early warning systems. A literature review and case studies of the successful use of these technologies in other disaster-prone areas will support these suggestions. The intention is to equip decision-makers and experts in disaster management with the practical knowledge they need to effectively prepare for and respond to Himalayan landslide events, saving lives and minimizing the impact of natural hazards.

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