2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC)最新文献_第4页

Ambient Energy Harvesting Chips for IoT End Devices: Review 物联网终端设备环境能量收集芯片:综述

2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) Pub Date : 2021-12-13 DOI: 10.1109/JAC-ECC54461.2021.9691438

Chung‐Hsiang Wang, Kuo-Hsuan Huang, Chung-Yen Wu

引用次数: 2

ASSD: Arabic Semantic Similarity Dataset 阿拉伯语语义相似度数据集

2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) Pub Date : 2021-12-13 DOI: 10.1109/JAC-ECC54461.2021.9691424

Badrya Dahy, M. Farouk, Khaled Fathy

{"title":"ASSD: Arabic Semantic Similarity Dataset","authors":"Badrya Dahy, M. Farouk, Khaled Fathy","doi":"10.1109/JAC-ECC54461.2021.9691424","DOIUrl":"https://doi.org/10.1109/JAC-ECC54461.2021.9691424","url":null,"abstract":"Finding semantic similarity between sentences is very useful in many NLP applications, such as information retrieval, plagiarism detection, information extraction, and machine translation. Limitations in Arabic language resources have led to a poor level of research in Arabic sentence similarity. This challenge makes identifying semantically similar sentences in Arabic even more difficult. This paper presents a new Arabic dataset for the sentence similarity task. This dataset can be used to help develop sentence similarity approaches. In addition, the main purpose of the created dataset is to evaluate the sentence similarity approach. The dataset has been collected from Wikipedia, an intermediate lexicon, and other WWW resources. This paper gives more details about the processes of collecting data, filtering, preprocessing the pairs of sentences and some statistics about the dataset, for building a benchmark for semantic textual similarity. The dataset is available for future research in this field. The experiment shows that the created dataset is an efficient tool for evaluating semantic similarity approaches for the Arabic language.","PeriodicalId":354908,"journal":{"name":"2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133088307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Medical Image Fusion Based on Weighted Least Square Optimization and Deep Learning Algorithm 基于加权最小二乘优化和深度学习算法的医学图像融合

2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) Pub Date : 2021-12-13 DOI: 10.1109/JAC-ECC54461.2021.9691453

C. Ghandour, W. El-shafai, S. El-Rabaie

{"title":"Medical Image Fusion Based on Weighted Least Square Optimization and Deep Learning Algorithm","authors":"C. Ghandour, W. El-shafai, S. El-Rabaie","doi":"10.1109/JAC-ECC54461.2021.9691453","DOIUrl":"https://doi.org/10.1109/JAC-ECC54461.2021.9691453","url":null,"abstract":"Recently, medical image processing has become a hot area of research, especially with the rapid development in technology and instrumentation, and that’s because of its effective role in the health sector. So that it becomes a very active research tool. This research introduces an image fusion algorithm that utilizes a deep learning model to produce only one medical fused image that includes all the traits from the medical source images. Firstly, the source images are separated into detailed content and base parts using the Gaussian and rolling guidance filters (RGF). Secondly, by the weighted averaging strategy, the base parts are fused. For the detail content, to quote traits of multi-layer which employ weighted average strategy to produce the fused detail content several candidates, the deep learning network is utilized. The max selection technique is employed to gain the last detailed content as soon as these candidates are gotten. Eventually, by uniting the fused detail and base layers, the fused image will be recreated. The experimental outcomes show that this algorithm can accomplish better results by comparing the other fusion methods in both thematic assessment and visual quality.","PeriodicalId":354908,"journal":{"name":"2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC)","volume":"49 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134364194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Time-Modulated Plasma ME-dipole Planar Arrays Synthesis for Beam-Shaping Patterns Using PSO 时间调制等离子体me偶极子平面阵列波束整形图的PSO合成

2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) Pub Date : 2021-12-13 DOI: 10.1109/JAC-ECC54461.2021.9691440

A. S. Zainud-Deen, H. Malhat

引用次数: 1

Contactless Vital Signs Monitoring for Public Health Welfare 面向公共卫生福利的非接触式生命体征监测

2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) Pub Date : 2021-12-13 DOI: 10.1109/JAC-ECC54461.2021.9691452

Laila Abbas, Soha Samy, Reem Ghazal, A. Eldeib, Sherif H. Elgohary

引用次数: 0

Virtual, Augmented Reality, and Wearable Devices for Biomedical Applications: A Review 虚拟现实，增强现实和可穿戴设备在生物医学应用:综述

2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) Pub Date : 2021-12-13 DOI: 10.1109/JAC-ECC54461.2021.9691434

Aya Taghian, M. Abo-Zahhad, Mohamed S. Sayed, Ahmed Abdel-Malek

引用次数: 2

Chain Based Leader Selection using Neural Network in Wireless Sensor Networks protocols 无线传感器网络协议中基于链的神经网络Leader选择

2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) Pub Date : 2021-12-13 DOI: 10.1109/JAC-ECC54461.2021.9691426

Hamdy H. El-Sayed, Shereen K. Refaay, Samia A. Ali, M. El-Melegy

{"title":"Chain Based Leader Selection using Neural Network in Wireless Sensor Networks protocols","authors":"Hamdy H. El-Sayed, Shereen K. Refaay, Samia A. Ali, M. El-Melegy","doi":"10.1109/JAC-ECC54461.2021.9691426","DOIUrl":"https://doi.org/10.1109/JAC-ECC54461.2021.9691426","url":null,"abstract":"In wireless sensor networks (WSNs), selecting a chain leader is a critical issue. In this paper, we present a novel method for selecting chain leaders in a chain-based routing protocols that utilizes a Neural Network (NN). Our proposed method is applicable to any chain-based routing protocol, such as PEGASIS (Power-Efficient Gathering in Sensor Information Systems) [6], CBERP (Cluster Based Energy Efficient Routing Protocol) [15], CCM (Chain-Cluster Based Mixed Routing Protocol) [14], CCBRP (Chain-Chain Based Routing Protocol) [18], and others. To validate our claim that our method can be applied to any chain-based routing protocol, we checked it on two of the most well-known protocols, PEGASIS (the original chain-based routing protocol) and CCBRP. It is well recognized that energy consumption is a critical issue for all WSNs. Our proposed methodology uses the Neural Network as a tool to select chain leaders based on the residual energy of each network member node. The simulation results show that the use of our proposed method improved the performance of both PEGASIS and CCBRP in terms of consumed energy and network lifetime.","PeriodicalId":354908,"journal":{"name":"2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115870264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

An Improved Emotion-based Analysis of Arabic Twitter Data using Deep Learning 使用深度学习改进的基于情感的阿拉伯语Twitter数据分析

2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) Pub Date : 2021-12-13 DOI: 10.1109/JAC-ECC54461.2021.9691416

Ahmed El-Sayed, Shaimaa Y. Lazem, Mohamed M. Abougabal

引用次数: 1

A Deep Pyramid Attention Network for Single Image Super-resolution 单幅图像超分辨率的深度金字塔注意网络

2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) Pub Date : 2021-12-13 DOI: 10.1109/JAC-ECC54461.2021.9691443

Garas Gendy, Hazem Mohammed, Nabil Sabor, Guanghui He

引用次数: 2

Data-Driven Based Positioning Technique for UAV Aided NOMA System 基于数据驱动的无人机辅助NOMA系统定位技术

2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) Pub Date : 2021-12-13 DOI: 10.1109/JAC-ECC54461.2021.9691311

Osama Elnahas, Ahmed Nasser, Babur Jalal

{"title":"Data-Driven Based Positioning Technique for UAV Aided NOMA System","authors":"Osama Elnahas, Ahmed Nasser, Babur Jalal","doi":"10.1109/JAC-ECC54461.2021.9691311","DOIUrl":"https://doi.org/10.1109/JAC-ECC54461.2021.9691311","url":null,"abstract":"Unmanned aerial vehicles (UAVs) have attained prevalent attraction in the mobile networks as a reliable technique which can improve the network capacity and provide efficient communications for ground users during emergency situations. Using UAVs in conjunction with non-orthogonal multiple access (NOMA) can greatly improve the performance of the overall network. In this paper, we study the maximization of the overall achievable cell sum rate in a UAV-aided NOMA network by optimizing UAV positioning vector using the real-time observations. We propose a low complex model-free data driven based approach to find a near-optimal UAV positioning vector in a single cell NOMA system. The proposed approach is based on a dynamic linearization data model with a time-varying pseudo gradient parameter. Numerical simulations show that the proposed algorithm provides the performance very close to the exhaustive search algorithm with low computational complexity. The simulation results show that the proposed algorithm provides the performance very close to the exhaustive search algorithm with low computational complexity.","PeriodicalId":354908,"journal":{"name":"2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130247077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1