2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS)最新文献_第2页

Arabic Sentiment Analysis based on Deep Reinforcement Learning 基于深度强化学习的阿拉伯语情感分析

2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS) Pub Date : 2022-03-30 DOI: 10.1109/NISS55057.2022.10085147

Mohamed Zouidine, Mohammed Khalil

引用次数: 0

Determining Natural Disaster Mitigation Level using Unsupervised k-means Clustering 使用无监督k-均值聚类确定自然灾害缓解水平

2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS) Pub Date : 2022-03-30 DOI: 10.1109/NISS55057.2022.10085620

Abdurrakhman Prasetyadi, Budi Nugroho, Merios Gusan Putra

{"title":"Determining Natural Disaster Mitigation Level using Unsupervised k-means Clustering","authors":"Abdurrakhman Prasetyadi, Budi Nugroho, Merios Gusan Putra","doi":"10.1109/NISS55057.2022.10085620","DOIUrl":"https://doi.org/10.1109/NISS55057.2022.10085620","url":null,"abstract":"This work intends to categorize the number of districts/cities based on their mitigation efforts using unsupervised clustering approaches to generate decision support systems. Using data mining techniques and k-means clustering algorithms, it is possible to address problems involving data on the number of districts/cities based on natural disaster mitigation measures. Ms. Excel is used to estimate the value of the centroid for three clusters: the high expectation level cluster (C1), the medium anticipation level cluster (C2), and the low anticipation level cluster (C3) (C3). Our trials highlighted the outcomes of categorizing districts/cities based on their natural disaster preparedness efforts with two high-level districts/cities, namely Mentawai Islands Regency and South Lampung Regency, 47 regencies/cities at medium level 32 other districts/cities including low-level clusters. The results can be adopted as a recommendation for the district/city government to improve facilities and infrastructure in the district/city conforming to the efforts of natural disaster mitigation based on the clusters.","PeriodicalId":138637,"journal":{"name":"2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128735253","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: 0

A note on attractor selection 关于吸引子选择的注解

2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS) Pub Date : 2022-03-30 DOI: 10.1109/NISS55057.2022.10085669

Samuilik Inna, Sadyrbaev Felix

引用次数: 0

A Review: Augmented Reality Technology-Based Interactive Learning Media 基于增强现实技术的交互式学习媒体综述

2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS) Pub Date : 2022-03-30 DOI: 10.1109/NISS55057.2022.10085418

Astri Widi Astuti, M. Rezaldi, S. Riyanto, R. Richardo

引用次数: 0

Adversarial Networks-Based Speech Enhancement with Deep Regret Loss 基于对抗性网络的深度后悔损失语音增强

2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS) Pub Date : 2022-03-30 DOI: 10.1109/NISS55057.2022.10085296

H. Pardede, Vicky Zilvan, A. Ramdan, A. R. Yuliani, Endang Suryawati, Renni Kusumowardani

{"title":"Adversarial Networks-Based Speech Enhancement with Deep Regret Loss","authors":"H. Pardede, Vicky Zilvan, A. Ramdan, A. R. Yuliani, Endang Suryawati, Renni Kusumowardani","doi":"10.1109/NISS55057.2022.10085296","DOIUrl":"https://doi.org/10.1109/NISS55057.2022.10085296","url":null,"abstract":"Speech enhancement is often applied for speech-based systems due to the proneness of speech signals to additive background noise. While speech processing-based methods are traditionally used for speech enhancement, with advancements in deep learning technologies, many efforts have been made to implement them for speech enhancement. Using deep learning, the networks learn mapping functions from noisy data to clean ones and then learn to reconstruct the clean speech signals. As a consequence, deep learning methods can reduce what is so-called musical noise that is often found in traditional speech enhancement methods. Currently, one popular deep learning architecture for speech enhancement is generative adversarial networks (GAN). However, the cross-entropy loss that is employed in GAN often causes the training to be unstable. So, in many implementations of GAN, the cross-entropy loss is replaced with the least-square loss. In this paper, to improve the training stability of GAN using cross-entropy loss, we propose to use deep regret analytic generative adversarial networks (Dragan) for speech enhancements. It is based on applying a gradient penalty on cross-entropy loss. We also employ relativistic rules to stabilize the training of GAN. Then, we applied it to the least square and Dragan losses. Our experiments suggest that the proposed method improve the quality of speech better than the least-square loss on several objective quality metrics.","PeriodicalId":138637,"journal":{"name":"2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS)","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132643753","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: 0

Review of Dematerialization Models and Systems in Public Procurement 公共采购中的非物质化模式与制度综述

2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS) Pub Date : 2022-03-30 DOI: 10.1109/NISS55057.2022.10085599

BA Papa Diadia, J. K. Tamgno, A. Kora

引用次数: 0

Implementing Satellite-borne Synthetic Aperture Radar Imaging Algorithm with Open Source Scientific Software 利用开源科学软件实现星载合成孔径雷达成像算法

2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS) Pub Date : 2022-03-30 DOI: 10.1109/NISS55057.2022.10085323

B. Setiadi, Andria Arisal, A. Fakhrurrozi, H. Septanto, F. Kurniawan, S. Aditya

{"title":"Implementing Satellite-borne Synthetic Aperture Radar Imaging Algorithm with Open Source Scientific Software","authors":"B. Setiadi, Andria Arisal, A. Fakhrurrozi, H. Septanto, F. Kurniawan, S. Aditya","doi":"10.1109/NISS55057.2022.10085323","DOIUrl":"https://doi.org/10.1109/NISS55057.2022.10085323","url":null,"abstract":"Implementing imaging algorithms for satellite-borne Synthetic Aperture Radar (SAR) sensor are challenging because they require complex computations and large storage. SAR imaging algorithms have been implemented in various compiled programming languages, such as Fortran and C/C++. However, in an academic and research environment, we need an interpreted programming language with strong support for mathematical operations, 2D and 3D plotting and visualization tools to support learning and implementing existing algorithms and even designing new ones. We describe our implementation of the Range Doppler algorithm (RDA) for satellite-borne SAR imaging using GNU Octave, an Open Source high-level interpreted programming language for scientific and numerical computation. The software process raw SAR data into a single-look complex image in four steps; range compression, secondary range compression, range cell migration correction, and azimuth compression. The overall implementation strategy for processing the airborne strip map mode raw data is explained, and results are presented.","PeriodicalId":138637,"journal":{"name":"2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115155804","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: 0

Synonym-based Text Generation in Restructuring Imbalanced Dataset for Deep Learning Models 基于同义词的深度学习模型重构不平衡数据集文本生成

2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS) Pub Date : 2022-03-30 DOI: 10.1109/NISS55057.2022.10085156

Febi Siti Sutria Ningsih, P. Khotimah, Andria Arisal, A. Rozie, D. Munandar, D. Riswantini, Ekasari Nugraheni, W. Suwarningsih, D. Kurniasari

{"title":"Synonym-based Text Generation in Restructuring Imbalanced Dataset for Deep Learning Models","authors":"Febi Siti Sutria Ningsih, P. Khotimah, Andria Arisal, A. Rozie, D. Munandar, D. Riswantini, Ekasari Nugraheni, W. Suwarningsih, D. Kurniasari","doi":"10.1109/NISS55057.2022.10085156","DOIUrl":"https://doi.org/10.1109/NISS55057.2022.10085156","url":null,"abstract":"One of which machine learning data processing problems is imbalanced classes. Imbalanced classes could potentially cause bias towards the majority classes due to the nature of machine learning algorithms that presume that the object cardinality in classes is around similar number. Oversampling or generating new objects in minority class are common approaches for balancing the dataset. In text oversampling method, semantic meaning loses often occur when deep learning algorithms are used. We propose synonym-based text generation for restructuring the imbalanced COVID-19 online-news dataset. Three deep learning models (MLP, CNN, and LSTM) using TF/IDF and word embedding (WE) feature are tested with the original and balanced dataset. The results indicate that the balance condition of the dataset and the use of text representative features affect the performance of the deep learning model. Using balanced data and deep learning models with WE greatly affect the classification significantly higher performances as high as 4%, 5%, and 6% in accuracy, precision, recall, and f1-score, respectively.","PeriodicalId":138637,"journal":{"name":"2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130283257","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: 0

Improving Efficiency on BFV-based Encrypted Watermarking using Hadamard Product Decomposition 利用Hadamard积分解提高bfv加密水印的效率

2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS) Pub Date : 2022-03-30 DOI: 10.1109/NISS55057.2022.10085020

A. Basuki, Iwan Setiawan, D. Rosiyadi

引用次数: 1

A Survey on Lightweight Cryptography Approach For IoT Devices Security 面向物联网设备安全的轻量级加密方法研究

2022 5th International Conference on Networking, Information Systems and Security: Envisage Intelligent Systems in 5g//6G-based Interconnected Digital Worlds (NISS) Pub Date : 2022-03-30 DOI: 10.1109/NISS55057.2022.10085144

Ismail El Gaabouri, M. Senhadji, M. Belkasmi

引用次数: 1