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A Web and Mobile Application to Identify the Availability of Drinking Water Information During a Water Crisis

A Web and Mobile Application to Identify the Availability of...

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2023 Intelligent Computing and Control for engineering and Business Systems, ICCEBS 2023

作者： Razeeth, Suhail Shihara, Fathima Pavithra, Kasuni Kaliyamoorthy, Maran Nawaz, Samsudeen Sabraz Kariyapper, R.K.A.R. South Eastern University of Sri Lanka Dept. of Information and Communication Technology Sri Lanka Uva Wellassa University of Sri Lanka Dept. of Computer Science and Informatics Sri Lanka Sri Sai Ram Institute of Management Studies Sri Sai Ram Engineering College India South Eastern University of Sri Lanka Department of Management and Information Technology Sri Lanka

ISBN: (纸本)9798350394580

Sri Lanka faces drinking water related issues often due to many reasons like weather changes, floods, droughts, and tsunamis, affecting the drinking water availability. In such instances, people find difficult to gather information regarding consumable drinking water availability. In order to facilitate the meeting of commercial water sellers and customers and to engage the general public and social services in addressing the drinking water problem, this study is focused on building both web and mobile applications. The web application was implemented with a selected set of functionalities such as social login, social sharing, geocoding, reverse geocoding, viewing, and filtering posts using Angular 6, *** web framework, and Leaflet. The mobile application was developed to direct the customers to the water availability location with a shortest path using the Dijkstra's algorithm. Case evaluation was conducted with the Rotaract Club members in Badulla and thinking aloud method was used to pick up the user's ideas while interacting with the system. It can be concluded that the created web and mobile applications would offer the public a clever way to draw attention to an issue with water availability, and the commercial water service providers are given a venue to market their services and locate potential customers. © 2023 IEEE.

关键词： crowdsourcing GIS mobile application water availability web application

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Normal Vector Direction-based 3D LiDAR Point Cloud Planar Surface Removal for Object Cluster Minimization in Human Activity Monitoring System

Normal Vector Direction-based 3D LiDAR Point Cloud Planar Su...

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IEEE instrumentation and Measurement technology Conference

作者： Nova Eka Budiyanta Eko Mulyanto Yuniarno Tsuyoshi Usagawa Mauridhi Hery Purnomo Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Computer Science and Electrical Engineering Graduate School of Science and Technology Kumamoto University Kumamoto Japan Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember University Center of Excellence on Artificial Intelligence for Healthcare and Society (UCE AIHeS) Surabaya Indonesia

The use of 3-Dimensional Light Detection and Ranging (3D LiDAR) point cloud as the alternative data to reduce privacy exposure in monitoring systems has been carried out in several studies. Unfortunately, various challenges in using point clouds intersect with the amount of data and computational costs. Several studies attempted to optimize the point cloud processing approach by segmenting the ground plane to get the object clusters separated. However, many unnecessary points can still burden the computation process. Since the ground plane mainly represents the horizontal planar plane on the x, y axis, this study tried to reduce the points on the vertical planar plane on the x, z and y, z axes with the x, y horizontal planar plane as well based on the surface normal vector direction of each point. The proposed approach has successfully reduced the raw point cloud by 79.29% removing the point cloud that indicates the planar surface of the three axes while maintaining the essential object of the monitoring system on the KITTI raw dataset. Therefore, the object cluster can be minimized, supporting the computational costs for further research in human activity monitoring systems.

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Multicluster Kernel Intuitionistic Fuzzy C-Means and State Transition Algorithm : Framework for Low Light Segmentation Imaging of Tuberculosis Bacilli Base of Semisupervised Approach

Multicluster Kernel Intuitionistic Fuzzy C-Means and State T...

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Sari Ayu Wulandari I Ketut Eddy Purnama Eko Mulyanto Yuniarno Mauridhi Hery Purnomo Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Biomedical Engineering Faculty of Electrical Engineering Universitas Dian Nuswantoro Semarang Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350319545

ISBN: (纸本)9798350319552

Annotated images are required as ground truth for deep learning. Bacterial segmentation is requires a lot of time and effort when done manually. The autosegmentation task gets more challenging since bacterial images contain low light properties, which have an important effect on auto annotating tasks. In order to solve this issue, we present a system that includes a fuzzy-based clustering method that enhances bacterial object segmentation performance by utilizing the multicluster idea. The State Transform Algorithm (STA) is used to obtain starting centroids in order to increase stability, because the Kernel of Intuitionistic Fuzzy C- Means (KIFCM) is sensitive to starting centroids and hence sensitive to being stuck in local optima. The accuracy of KIFCM-STA with bicluster is poor in low-light images. To boost performance, the multicluster technique (MKIFCM-STA) is presented as a continuation hybrid of KIFCM-STA. This framework allows for the ideal amount of clusters (Silhouette) and cluster ranking to provide clusters containing bacterial objects (Topsis). In order to compare our method against four prior approaches (IFCM, KFCM, KIFCM, and KIFCM-STA), we compare its qualitative aspects (visualization of images) and quantitative aspects (average IOU, Dice, HD, ASD, and Accuracy). In low light image clustering tasks, our model significantly improves and achieves great results in terms of accuracy, with a score of 89.438%. This accomplishment highlights how crucial it is that our framework tackles the problem of low-light image clustering in images of bacteria, eventually improving the image auto-annotation procedure.

关键词： Deep learning Image segmentation Visualization Microorganisms Accuracy Clustering methods Clustering algorithms

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Intra-Datacenter Load Balancing in a Federated Cloud with Throttled Algorithm

Intra-Datacenter Load Balancing in a Federated Cloud with Th...

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2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Akinola, Damola Gideon Adetiba, Emmanuel Abayomi, Abdultaofeek Nnaji, Uche Thakur, Surendra Moyo, Sibusiso Covenant University Covenant Applied Informatics and Communications African Center of Excellence Department of Electrical and Information Engineering Ota Nigeria Durban University of Technology HRA Institute for Systems Science Durban South Africa Mangosuthu University of Technology Department of Information and Communication Technology Durban South Africa Covenant University Dept. of Computer and Information Science Covenant Applied Informatics and Communications African Center of Excellence Ota Nigeria Durban University of Technology KZN E-Skills CoLab Durban South Africa Stellenbosch University School for Data Science and Computational Thinking Department of Mathematical Sciences Stellenbosch7602 South Africa

ISBN: (纸本)9798350358155

The emergence of cloud computing technology has motivated a very high number of users in different organizations to access its services in running and delivering their various operations and services. However, this surge of cloud users has led to the problem of uneven load sharing among the cloud computing infrastructures. As a result, federated cloud infrastructure was initiated to provide more cloud computing resources to accommodate more cloud users' requests and also to provide equal requests mapping with the available cloud resources. Nevertheless, the issue of unequal allocation of requests within the datacenter(s) that makes up the federated cloud environment still persists. This research work presents an intra-datacenter load balancing algorithm in a federated cloud environment named;the intra-balancer adapted throttled algorithm to evenly distribute requests in each datacenter that formulate the federated cloud infrastructures. The simulation of the intra-balancer was carried out in CloudAnalyst, the results of the implementation showed that the intra-balancer outperformed the Round-Robin and ESCE with 98.93ms and 2.26ms for the response and processing time respectively. The results assert that the intra-balancer algorithm provides a better load balancing solution in a federated cloud environment. © 2024 IEEE.

关键词： Cloud platforms

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Sentiment Analysis for Curriculum of Independent Learning Based on Naïve Bayes with Laplace Estimator

Sentiment Analysis for Curriculum of Independent Learning Ba...

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Information technology Research and Innovation (ICITRI), International Conference on

作者： Amelia Ariefah Widodo Murien Nugraheni Dept. of Informatics and Computer Engineering Education State University of Jakarta Jakarta Indonesia Dept. of Information System and Technology State University of Jakarta Jakarta Indonesia

Curriculum changes have a significant impact on the field of education in Indonesia, especially in universities. This is because the curriculum is used as a means to achieve the goals of educational success as well as guidelines in the implementation of teaching at every level of education. This study aims to determine public sentiment regarding the implementation curriculum of independent learning (MBKM) through Twitter based on Naïve Bayes with Laplace Estimator. Tweet search results use the keywords “kurikulum mbkm” and “mbkm”. The data used in this study amounted to 2500 tweet data which will be divided into 2000 data as training data with details of 1000 positive tweets and 1000 negative tweets and 500 data as testing data. The results showed the performance of Naïve Bayes using Laplace Estimator which resulted in an accuracy value of 80.20%, precision value of 82.00%, and recall value of 79.00%. Meanwhile, the performance of Naïve Bayes without Laplace Estimator resulted in an accuracy value of 77.00%, precision value of 80.00%, and recall value of 74.00%. Naive Bayes with Laplace Estimator reached the highest value in all metrics.

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The Iterative Dichotomiser 3 method improves soft skills training decisions using survey data

The Iterative Dichotomiser 3 method improves soft skills tra...

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2024 IEEE International Conference on Machine Learning and Applied Network Technologies, ICMLANT 2024

作者： Gupta, Subir Hoang, Quang-Trung Roy, Bhaswati Chowdhury, Subrata Mukherjee, Sandip Pathak, Aditya Kumar Duc, Diep Can Haldia Institute of Technology West Bengal 721657 India Faculty of Electrical and Electronic Engineering Phenikaa University Hanoi12116 Viet Nam Dept. of FMS Dr.B.C. Roy Engineering College WB Durgapur India Dept. of Computer Science and Machine Learning Sreenivasa Inst. of Technology and Management Studies Andhra Pradesh Chittoor India Dept. of IT Haldia Institute of Technology West Bengal 721657 India Electric Power University Hanoi Viet Nam

ISBN: (纸本)9798350389180

This investigation explores student expectations and perceptions regarding higher education institutions, focusing on aligning professional programs with student career aspirations. The study evaluates how effectively academic institutions understand and meet training needs essential for student success in professional fields. Students were categorized using the Iterative Dichotomiser 3 methodology to forecast their training requirements. Analytical tools such as the confusion matrix and the ROC curve assessed the precision of these predictions. The results show a specificity rate of 74.1%, a sensitivity of 78.6%, and an overall accuracy of 76.7%. The combined sensitivity and specificity score is 3.527, and the empirical area under the ROC curve is 0.76, suggesting the model’s reasonable efficacy. The findings indicate a significant student demand for enhanced instruction in soft skills, underscoring the need for educational institutions to adapt their curricula to better prepare students for professional challenges. © 2024 IEEE.

关键词： Students

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Acoustic measurement framework for audio systems based on structured periodic test signals 12

Acoustic measurement framework for audio systems based on st...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Kawahara, Hideki Yatabe, Kohei Sakakibara, Ken-Ichi Mizumachi, Mitsunori Kitamura, Tatsuya Wakayama University Cntr. Innovative Research and Liaison Wakayama Japan Tokyo University of Agriculture and Technology Dept. Electrical Engineering and Computer Science Tokyo Japan Health Sciences University of Hokkaido Dept. Speech-Language-Hearing Therapy Hokkaido Japan Kyushu Institute of Technology Dept. Electrical and Electronic Eng. Kitakyushu Japan Konan University Dept. Intelligence and Informatics Kitakyushu Japan

ISBN: (纸本)9798350340181

We introduce a framework for acoustic measurement that allows everyday sounds into acoustic measurement test signals and standard test signals such as swept-sine and MLS (Maximum Length Sequence). The framework extends our extended Time-Stretched-Pulse generation method and safeguarding method for any signals to make them appropriate for acoustic measurement. The extension uses the periodic nature of discrete Fourier transform combined with orthogonalization based on the Walsh-Hadamerd matrix. This framework enables simultaneous measurement of acoustic attributes such as linear time-invariant response, signal-dependent non-linear and time-invariant components, and random time-varying components. We also discuss and demonstrate practical scenarios in classes and laboratory lessons using tools developed based on the proposed framework. © 2023 IEEE.

关键词： Audio systems

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Enhancing Cabbage Plant Protection: CNN Algorithm for Insect Identification

Enhancing Cabbage Plant Protection: CNN Algorithm for Insect...

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Information technology Research and Innovation (ICITRI), International Conference on

作者： Remi Senjaya Purnawarman Musa Puji Sularsih Novrina Novrina Witari Aryunani Suhartini Suhartini dept. of Informatics Engineering Gunadarma University Depok Indonesia dept. of Electrical Engineering Gunadarma University Depok Indonesia dept. of Information Technology Gunadarma University Depok Indonesia dept. of Computer Science Gunadarma University Depok Indonesia

ISBN: (数字)9798350376210

ISBN: (纸本)9798350376227

People frequently find it straightforward to identify insects that feed on cabbage plants based on the insects’ characteristics. However, challenges arise when employing a computer for precise bug categorization and identification. The implementation of Deep Learning (DL) utilizes the Convolutional Neural Network (CNN) technique, renowned for its effectiveness in categorizing and recognizing objects in digital photo data. The CNN algorithm delivers notable results in photo identification, simulating the human visual brain’s image recognition through artificial neural networks in the Python programming language. To enrich the user experience, frameworks like Keras and TensorFlow are employed in neural network development. Our research will use the CNN algorithm to determine insect species in cabbage images. Achieving high accuracy involves coupling the CNN algorithm with the VGGNet architectural model. Notably, utilizing an epoch value of 150 resulted in a 97.75% accuracy rate during the training model technique; however, the validation accuracy was slightly lower at 94.25%. The corresponding loss and validation rates were 0.0613% and 0.2945%, respectively. Moreover, based on the model (150 epochs), the testing outcomes in the study, involving 48 images beyond the dataset and incorporating additional information, resulted in an accuracy rate of 91.66%.

关键词： Training Visualization Technological innovation Accuracy Insects Prediction algorithms User experience Classification algorithms Convolutional neural networks Testing

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Photonic Signal Transport on Aerospace Platforms: is Analog Signaling Ever Useful?

Photonic Signal Transport on Aerospace Platforms: is Analog ...

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IEEE Research and Applications of Photonics In Defense Conference (RAPID)

作者： Michael T. Hoff Stephen E. Ralph Rick C. Stevens Dept. of Electrical and Computer Engineering Advanced Technology Laboratories Georgia Inst of Technology Lockheed Martin Corporation Atlanta GA USA Dept. of Electrical and Computer Engineering Georgia Inst of Technology Atlanta GA USA Advanced Technology Laboratories Lockheed Martin Corporation Eagan MN USA

For photonic signal transport in multi-GHz, waveform-sensitive RF transport applications, it will be shown that digital-over-fiber fundamentally enables superior SNR performance versus analog-over-fiber. However, for ...

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Challenges in Implementing ICT Rehabilitation Environments in Real Clinical Practice 8

Challenges in Implementing ICT Rehabilitation Environments i...

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8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024

作者： Tibollo, Valentina Sacchi, Lucia Malovini, Alberto Giardini, Anna D'Addio, Giovanni Lunetta, Christian Istituti Clinici Scientifici Maugeri Irccs Laboratory of Medical Informatics and Artificial Intelligence Pavia Italy University of Pavia Dept of Electrical Computer and Biomedical Engineering Pavia Italy Istituti Clinici Scientifici Maugeri Irccs Information Technology Department Pavia Italy Bioengineering Unit Istituti Clinici Scientifici Maugeri Irccs Pavia Italy Istituti Clinici Scientifici Maugeri Irccs Dept of Rehabilitative Neurology Department Pavia Italy

ISBN: (纸本)9798350362138

Fit for Medical Robotics funded under the National Recovery and Resilience Plan, aims to transform current rehabilitation and assistive models for individuals of all ages with impaired motor, sensory, or cognitive functions. The project seeks to achieve this through the implementation of innovative biorobotic technologies and related digital solutions, alongside new continuum of care paradigms. A key element is the full exploitation of information and communication technology (ICT) across all stages of rehabilitation, ranging from prevention to at-home care during the chronic phase. Within this framework, it is crucial to assess the potentialities, challenges, and potential barriers associated with integrating interventions based on advanced technologies into real-world rehabilitation practices. © 2024 IEEE.

关键词： ICT interoperability rehabilitation research data management

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