2021 Emerging Technology in Computing, Communication and Electronics (ETCCE)最新文献

Improved Attentive Pairwise Interaction (API-Net) for Fine-Grained Image Classification 用于细粒度图像分类的改进细心对交互(API-Net)

2021 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2021-12-21 DOI: 10.1109/ETCCE54784.2021.9689910

Ong Zu Yet, Taha H. Rassem, Md. Arafatur Rahman, M. M. Rahman

{"title":"Improved Attentive Pairwise Interaction (API-Net) for Fine-Grained Image Classification","authors":"Ong Zu Yet, Taha H. Rassem, Md. Arafatur Rahman, M. M. Rahman","doi":"10.1109/ETCCE54784.2021.9689910","DOIUrl":"https://doi.org/10.1109/ETCCE54784.2021.9689910","url":null,"abstract":"Fine-grained classification is a challenging problem as one has to deal with a similar class of objects but with various types of variations. For more elaboration, they are almost similar and have subtle differences, and are confusing. In this study, aircraft will be the fine-grained object to be focused on. Aircraft which has almost similar shapes and patterns can be hardly recognized even for humans, especially those who haven not gone through any training. In recent years, a lot of proposed methods addressed to solve the difficulties in fine-grained problems by learning contrastive clues from an image. This study aims to increase the accuracy of the Attentive Pairwise Interaction Network (API-Net) by introducing data augmentation into the network structure. Some of the previous studies proved that data augmentation does help improve a network. So, this study is going to modify the API-Net with different data augmentation settings. In this study, various settings have been introduced to the API-Net. Several experiments had been done with a simple modification where a portion of the train dataset’s images will randomly convert into greyscale images. These settings are, only brightness & contrast 0.2, only grayscale 0.3, only grayscale 0.5, brightness & contrast 0.2 with grayscale 0.3, and brightness & contrast 0.2 with grayscale 0.5. As a result, the proposed modification achieved with 92.74% with brightness & contrast 0.2, 92.80% on brightness & contrast 0.2 with grayscale 0.5, and 92.86% on brightness & contrast 0.2 with grayscale 0.3. While grayscale 0.3 alone achieve 93.25% and grayscale 0.5 alone achieve 93.46% compared with the original results which reached 92.77%.","PeriodicalId":208038,"journal":{"name":"2021 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129414307","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 Conceptual Anonymity Model to Ensure Privacy for Sensitive Network Data 一种保证敏感网络数据隐私的概念匿名模型

2021 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2021-12-21 DOI: 10.1109/ETCCE54784.2021.9689791

N. Arafat, Md. Ileas Pramanik, Abu Jafar Md Muzahid, B. Lu, Sumaiya Jahan, Saydul Akbar Murad

{"title":"A Conceptual Anonymity Model to Ensure Privacy for Sensitive Network Data","authors":"N. Arafat, Md. Ileas Pramanik, Abu Jafar Md Muzahid, B. Lu, Sumaiya Jahan, Saydul Akbar Murad","doi":"10.1109/ETCCE54784.2021.9689791","DOIUrl":"https://doi.org/10.1109/ETCCE54784.2021.9689791","url":null,"abstract":"In today’s world, a great amount of people, devices, and sensors are well connected through various online platforms, and the interactions between these entities produce massive amounts of useful information. This process of data production and sharing appears to be on the rise. The growing popularity of this industry, as well as the required development of data sharing tools and technology, pose major threats to an individual’s sensitive information privacy. These privacy-related issues may elicit a regularly strong negative reaction and restrain further organizational invention. Researchers have identified the privacy implications of large data collections and contributed to the preservation of data from unauthorised exposure to solve the challenge of information privacy. However, the majority of privacy strategies concentrate solely on traditional data models, such as micro-data. The academe and industry are paying more attention to network data privacy challenges. In this paper, we offer (ℓ, k)-anonymity, a novel privacy paradigm for network data that focuses on maintaining the privacy of both node and link information. Here, original network data will turn to attribute generalization nodes through a complex process, where several algorithms, clustering, node generalization, link generalization and ℓ-diversification will be applied. As a result, (ℓ, k)-anonymous network will be generated and will filter original network data to ensure publishable (ℓ, k)-anonymize data. Hopefully, this anonymity model will have a stronger role against homogeneity attacks of intruders, which will prevent the unauthorized disclosure of sensitive network data for several areas, such as - health sector. This model will also be cost effective and data loss will be controlled using two different ways.","PeriodicalId":208038,"journal":{"name":"2021 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127740329","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

Comparative Study on Job Scheduling Using Priority Rule and Machine Learning 基于优先级规则和机器学习的作业调度比较研究

2021 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2021-12-21 DOI: 10.1109/ETCCE54784.2021.9689812

Saydul Akbar Murad, Z. R. Azmi, Abu Jafar Md Muzahid, Md Al-Imran

引用次数: 5

Optimal Safety Planning and Driving Decision-Making for Multiple Autonomous Vehicles: A Learning Based Approach 多辆自动驾驶汽车的最优安全规划和驾驶决策:基于学习的方法

2021 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2021-12-21 DOI: 10.1109/ETCCE54784.2021.9689820

Abu Jafar Md Muzahid, M. Rahim, Saydul Akbar Murad, S. F. Kamarulzaman, Md. Arafatur Rahman

{"title":"Optimal Safety Planning and Driving Decision-Making for Multiple Autonomous Vehicles: A Learning Based Approach","authors":"Abu Jafar Md Muzahid, M. Rahim, Saydul Akbar Murad, S. F. Kamarulzaman, Md. Arafatur Rahman","doi":"10.1109/ETCCE54784.2021.9689820","DOIUrl":"https://doi.org/10.1109/ETCCE54784.2021.9689820","url":null,"abstract":"In the early diffusion stage of autonomous vehicle systems, the controlling of vehicles through exacting decision-making to reduce the number of collisions is a major problem. This paper offers a DRL-based safety planning decision-making scheme in an emergency that leads to both the first and multiple collisions. Firstly, the lane-changing process and braking method are thoroughly analyzed, taking into account the critical aspects of developing an autonomous driving safety scheme. Secondly, we propose a DRL strategy that specifies the optimum driving techniques. We use a multiple-goal reward system to balance the accomplishment rewards from cooperative and competitive approaches, accident severity, and passenger comfort. Thirdly, the deep deterministic policy gradient (DDPG), a basic actor-critic (AC) technique, is used to mitigate the numerous collision problems. This approach can improve the efficacy of the optimal strategy while remaining stable for ongoing control mechanisms. In an emergency, the agent car can adapt optimum driving behaviors to enhance driving safety when adequately trained strategies. Extensive simulations show our concept’s effectiveness and worth in learning efficiency, decision accuracy, and safety.","PeriodicalId":208038,"journal":{"name":"2021 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"12 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132592110","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: 5

A Compact Wideband Slotted Hexagonal Patch Antenna with a Modified Ground Structure for WiFi-5/6 Communication 一种适用于WiFi-5/6通信的小型宽带开槽六角贴片天线和改进的接地结构

2021 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2021-12-21 DOI: 10.1109/ETCCE54784.2021.9689801

L. Paul, Md. Tanvir Rahman Jim, T. Rani, M. Samsuzzaman, Nayan Sarker, R. Azim

{"title":"A Compact Wideband Slotted Hexagonal Patch Antenna with a Modified Ground Structure for WiFi-5/6 Communication","authors":"L. Paul, Md. Tanvir Rahman Jim, T. Rani, M. Samsuzzaman, Nayan Sarker, R. Azim","doi":"10.1109/ETCCE54784.2021.9689801","DOIUrl":"https://doi.org/10.1109/ETCCE54784.2021.9689801","url":null,"abstract":"A compact wideband slotted hexagonal patch antenna (CWSHPA) with a modified ground plane structure for WiFi-5/6 communication has been designed and proposed in this paper. In the hexagonal patch antenna, a substrate material named Rogers RT5880 with a thickness of 0.79 mm is used. The modified ground plane structure has a good impact on the antenna size reduction as well as the performance improvement of the antenna. The optimized volume of the antenna is 34×20×0.79 mm3 (537.2mm3) which covers the frequency range of 5.1697 – 7.5388 GHz under the −10 dB scale. It also shows that the radiation efficiency ranges from 79.19% to 89.37% and the efficiency is 83.03% at 6. 33 GHz. The average radiation efficiency within the operating band is about 85%. The gain and the directivity are varying from 3.1 dB to 4.1 dB and 3.6 to 4.9 dBi. The proposed microstrip patch antenna exhibits a gain of 3.995 dB at centre frequency of 6.33 GHz which gives the Omni-directional radiation pattern as well as a competitor of WiFi-5/6 communication. The designed slotted hexagonal microstrip patch antenna (MPA) is simulated by using the CST microwave studio suite 2018.","PeriodicalId":208038,"journal":{"name":"2021 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134530485","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

Interpretation of Adversarial Attack on Unsupervised Domain Adaptation 无监督域自适应对抗性攻击的解释

2021 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2021-12-21 DOI: 10.1109/ETCCE54784.2021.9689917

Mst. Tasnim Pervin, A. Huq

{"title":"Interpretation of Adversarial Attack on Unsupervised Domain Adaptation","authors":"Mst. Tasnim Pervin, A. Huq","doi":"10.1109/ETCCE54784.2021.9689917","DOIUrl":"https://doi.org/10.1109/ETCCE54784.2021.9689917","url":null,"abstract":"Recent advances in deep neural networks has accelerated the process of automation in several fields like image processing, object detection, segmentation tasks and many more. Though, it has been also proved that these deep neural networks or deep CNNs need large scale dataset to be trained on to produce desired output. Supplying huge dataset often becomes difficult for many fields. Domain adaptation is supposed to be a possible way to cope with this problem of large data requirement as it allows model to gain experience from one large source dataset during training and exploit that experience during working with any smaller, related but technically different dataset. But the threat remains when the concept of adversarial machine learning strikes. Like many other deep learning models, adaptive models seem to be vulnerable to adversarial attacks. We target to analysis how these attack techniques from adversarial machine learning affect unsupervised adaptive models’ performance for two related but structurally different dataset like MNIST and MNISTM. We used three different attack techniques called FGSM, MIFGSM and PGD for the experiment. Experiments show the deadly effect of these attack techniques on both of the baseline and adaptive models where adaptive model seem to be more vulnerable than the baseline non-adaptive model.","PeriodicalId":208038,"journal":{"name":"2021 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133722418","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 Machine Learning Approach to Predict Renal Diseases with SARS-CoV-2 预测SARS-CoV-2肾病的机器学习方法

2021 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2021-12-21 DOI: 10.1109/ETCCE54784.2021.9689894

Md. Ashiq Mahmood, Priti Lata

{"title":"A Machine Learning Approach to Predict Renal Diseases with SARS-CoV-2","authors":"Md. Ashiq Mahmood, Priti Lata","doi":"10.1109/ETCCE54784.2021.9689894","DOIUrl":"https://doi.org/10.1109/ETCCE54784.2021.9689894","url":null,"abstract":"Research has shown that up to a lot of people hospitalized with COVID-19 get an intense kidney injury. In some serious cases, Kidney failure occurs suddenly without any major symptoms that are totally unpredictable to identify in the early stage. The reason behind that we have a lack of knowledge and experience regarding this. The main purpose of our research is to develop a framework that will assist individuals with foreseeing the danger of constant renal sickness growing rate after being infected with COVID-19. Here we have utilized 773 raw data and trained them and we have also taken care of our missing data. In this paper, we have used KNN, Naïve Bayes, ANN model and Ant Colony Optimization (ACO) for making the system ready for assumption. We have carried out these calculations in the python language. The exactness that we acquire by utilizing KNN calculation is 95%, Naïve bayes is 98.30% ANN is 97.5% and Ant Colony Optimization (ACO) is 95.5% separately which is generally outstanding. By utilizing our proposed strategy, prediction of renal diseases after COVID-19 in the beginning phase will be conceivable. All the data are collected from our neighborhood medical clinic. This research has shown us the current situation in this COVID-19 pandemic with regards to Chronic Kidney Sickness which is known as renal disease.","PeriodicalId":208038,"journal":{"name":"2021 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128024607","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

AIMS TALK: Intelligent Call Center Support in Bangla Language with Speaker Authentication 目标演讲:智能呼叫中心支持在孟加拉语与说话者认证

2021 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2021-12-21 DOI: 10.1109/ETCCE54784.2021.9689831

Shehan Irteza Pranto, Rahad Arman Nabid, Ahnaf Mozib Samin, Nabeel Mohammed, F. Sarker, M. N. Huda, K. Mamun

{"title":"AIMS TALK: Intelligent Call Center Support in Bangla Language with Speaker Authentication","authors":"Shehan Irteza Pranto, Rahad Arman Nabid, Ahnaf Mozib Samin, Nabeel Mohammed, F. Sarker, M. N. Huda, K. Mamun","doi":"10.1109/ETCCE54784.2021.9689831","DOIUrl":"https://doi.org/10.1109/ETCCE54784.2021.9689831","url":null,"abstract":"Call support centers operate over the telephone, connect between customers and receptionists to ensure customer satisfaction by solving their problems. Due to pandemics, customer call support centers have become a popular way of communication that has been used in different domains such as e-commerce, hospitals, banks, credit card support, government offices. Moreover, humans’ limitations to serve 24 hours a day and the fluctuation of waiting time makes it more challenging to satisfy all the customers over call center. So, customer service needs to be automated to handle customers by providing a domain-based response in the native language, especially in a developing country like Bangladesh, where call support centers are increasing. Although most people use the Bangla language to communicate, little work has been done in customer care automation in the native language. Our developed architecture, “AIMS TALK” can respond to that customer’s need by recognizing users’ voices, specifying customers’ problems in the standardized Bangla language, collecting customers’ responses to the database to give feedback according to the queries. Besides, the system uses MFCC feature extraction for speaker recognition with an average accuracy of 94.38% on 42 people in real-time testing, an RNN-based model for Bangla Automatic Speech Recognition (ASR) with a word error rate (WER) of 42.15%, and sentence summarization we used Sentence similarity measurement technique having an average loss of 0.004. Lastly, we used gTTS that works as Text to Speech Synthesis for the Bangla language in WavNet architecture.","PeriodicalId":208038,"journal":{"name":"2021 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124951344","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

Towards Efficient Segmentation and Classification of White Blood Cell Cancer Using Deep Learning 利用深度学习实现白细胞癌的高效分割和分类

2021 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2021-12-21 DOI: 10.1109/ETCCE54784.2021.9689839

Ashik Iqbal, Md. Faysal Ahmed, Md. Naimul Islam Suvon, Sourav Das Shuvho, Ahmed Fahmin

引用次数: 0

Backward Radiation Reduction and Bandwidth Enhancement of Metamaterial Antenna for UWB Applications 超宽带应用中超材料天线的反向辐射抑制和带宽增强

2021 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2021-12-21 DOI: 10.1109/ETCCE54784.2021.9689850

M. Uddin, M. H. Ullah, Barry L. Bentley, M. Shakib, S. Z. Islam, Md. Arafatur Rahman

{"title":"Backward Radiation Reduction and Bandwidth Enhancement of Metamaterial Antenna for UWB Applications","authors":"M. Uddin, M. H. Ullah, Barry L. Bentley, M. Shakib, S. Z. Islam, Md. Arafatur Rahman","doi":"10.1109/ETCCE54784.2021.9689850","DOIUrl":"https://doi.org/10.1109/ETCCE54784.2021.9689850","url":null,"abstract":"A metamaterial inspired planar-patterned microstrip patch antenna, feeding on a Duroid substrate inset bottom ground soft-surface, is presented for ultra-wide band (UWB) applications. The present antenna is configured on a step-edge periodic unit-cell pattern, with a tiny air gap etched on the metal patch and finite ground plane. By employing these structures an ultra-wide band from 4 GHz ~ 16.2 GHz is achieved. The important advantage is retaining the suppression of back radiation while removing grounded edge metallic parts and replacing them with the finite cut-off square unit cell. The feeding ground plane and radiating patch are specially configured to develop artificial structures using series capacitance and shunt inductance. The efficiency of the proposed antenna is above 99.1%. To enhance gain and bandwidth, this antenna has etched Jerusalem crossed slots on the ground plane and star-slots on the patch, with the enhanced gain reaching a maximum of 8 dBi at 9.2 GHz. The antenna’s overall dimensions exhibit 0.72λ × 0.83λ × 0.05λ at a 10.1 GHz cut-off frequency. The high absorption gain, directivity, and enhanced frequency bandwidth, verified by numerical modeling and experimentation, ensure the proposed antenna is well suited to any UWB application.","PeriodicalId":208038,"journal":{"name":"2021 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122251592","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