2020 International Conference on Computational Intelligence (ICCI)最新文献_第4页

IIoT Digital Forensics and Major Security issues 工业物联网数字取证和主要安全问题

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247685

Venkata Venugopal Rao Gudlur Saigopal, Valliappan Raju

引用次数: 2

PITEH: Providing Financial Identities to Those Without Credit Score 皮特:为没有信用评分的人提供金融身份

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247779

Ayu Shahirah Salem, Saipunidzam Mahamad

{"title":"PITEH: Providing Financial Identities to Those Without Credit Score","authors":"Ayu Shahirah Salem, Saipunidzam Mahamad","doi":"10.1109/ICCI51257.2020.9247779","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247779","url":null,"abstract":"Faced with growing competition in the microfinancing market and higher operational risk, it is ever more important for a Microfinancing Institution (MFI) to be able to leverage less conventional customer data to improve the efficiency of their lending models. Most MFIs are active in Malaysia where financial history is generally non-existent on their user base which increases the difficulty in assessing the credit worthiness of individuals. Instead, an alternative source of data such as mobile phone call and SMS logs can be utilised to assist with this problem. In this project, call and SMS logs from the loan applicants are featured and used to train various classification models. PITEH is an Android mobile lending application that offers microfinance ranging from RM500 – RM5,000 by validating the creditworthiness of a loan applicant through the creation of credit scores using machine learning to classify data existing in the call and SMS logs. With users’ explicit permission, the application will collect key pieces of data from users’ Android devices solely for the purposes of underwriting loan applicants who do not have documented financial history. It will select these data sources for the purposes of understanding a user’s potential financial capacity, his or her behavioural attributes, and to validate his identity. With something as simple as a credit score, we are giving people the power to build their own futures.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"6 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130588198","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

Comparative Study of Privacy Preserving-Contact Tracing on Digital Platforms 数字平台上隐私保护-联系追踪的比较研究

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247782

Forum Bhavesh Patel, Nilakshi Jain, Ramesh Menon, Srikanth Kodeboyina

{"title":"Comparative Study of Privacy Preserving-Contact Tracing on Digital Platforms","authors":"Forum Bhavesh Patel, Nilakshi Jain, Ramesh Menon, Srikanth Kodeboyina","doi":"10.1109/ICCI51257.2020.9247782","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247782","url":null,"abstract":"The rapid development in digital infrastructure such as computing power and less expensive mobile devices and explosive growth of the internet has made an impact on digital processing. This revolution has bought many new applications and new technologies, now aiming at replacement with improving effectiveness and efficiency of manual contact tracing with new approaches with maintaining user privacy. The successful containment of the Coronavirus pandemic (COVID-19) depends on the ability to identify quickly and reliably those who have been in close proximity to a contagious positive-tested individual. This can be made possible with contact tracing method. The information about interaction which happens between two users should be revealed only to themselves to maintain privacy of individuals. Users which are detected positive should not share any of their contact details or personal information or history with the authority or any other party but pass the anonymous IDs and help in tracing out the contacted people. This paper presents the most popular contact tracing data privacy techniques.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132474187","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

Performance comparison of CNN and LSTM algorithms for arrhythmia classification CNN与LSTM算法在心律失常分类中的性能比较

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247636

Shahab Ul Hassan, M. Zahid, Khaleel Husain

引用次数: 4

Aedes Larvae Classification and Detection (ALCD) System by Using Deep Learning 基于深度学习的伊蚊幼虫分类检测系统

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247647

Muhammad Izzul Azri Bin Zainol Azman, A. Sarlan

{"title":"Aedes Larvae Classification and Detection (ALCD) System by Using Deep Learning","authors":"Muhammad Izzul Azri Bin Zainol Azman, A. Sarlan","doi":"10.1109/ICCI51257.2020.9247647","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247647","url":null,"abstract":"Nowadays, the presence of the latest technologies like Artificial Intelligence and lenses that can capture the micro-living being like larva have been used in our surrounding environment. Deep Learning technologies which are a subset of Artificial Intelligence have been implemented in used for processing the image. As before this, there is a study to detect the possible place of Aedes mosquito breeding place with the use of Internet of Things (IoT) technologies to detect the humidity of certain places and relate it to the possibility of Aedes mosquito breeding present. To support the study and have verification of the place is the breeding place of Aedes mosquito, a study to classify the larva and detect it has been proposed. The Aedes Larvae Classification and Detection (ALCD) System by using Deep learning is a system that uses deep learning technologies to detect the pattern of the larva and classify it according to its type. The proposed developed system ALCD because Malaysia is having a rapid increase in dengue cases throughout the year. While there are many approaches from the government and non-government organizations (NGOs) to help combat the dengue virus outbreak, this study is focusing on preventing the virus from spreading in the early stages. The life cycle of an Aedes mosquito is starting from the egg to larva to pupa and lastly became an adult mosquito. The early stages of Aedes mosquito that can be used to differentiate between Aedes and Non-Aedes were at the larva stages. This study is meant to do a background study on using the latest technology of deep learning subset of Artificial Intelligence technology to find the pattern of the Aedes and Non-Aedes on the larva. After the pattern of the larva type is recognized, the process to classify it between the Aedes larvae and Non-Aedes larvae can be continued for classification. Real-time classification testing will be conducted to test the accuracy and efficiency of the ALCD system.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121590231","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: 4

Assessing Suitable Word Embedding Model for Malay Language through Intrinsic Evaluation 马来语词嵌入模型的内在评价

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247707

Yeong-Tsann Phua, K. Yew, O. Foong, M. Teow

引用次数: 1

Virtual Reality Training and Skill Enhancement for Offshore Workers 海上作业人员虚拟现实培训与技能提升

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247819

S. Sulaiman, S. Ali, Syed Hasan Adil, Mansoor Ebrahim, Kamran Raza

{"title":"Virtual Reality Training and Skill Enhancement for Offshore Workers","authors":"S. Sulaiman, S. Ali, Syed Hasan Adil, Mansoor Ebrahim, Kamran Raza","doi":"10.1109/ICCI51257.2020.9247819","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247819","url":null,"abstract":"This project studies the application of virtual training environment for offshore workers. Working in the oil and gas industry where the technology is rapidly evolving results in the employee to perform tasks to current and new equipment. Many offshore workers require years of experience to obtain the relevant skills in handling with hazardous equipment. Due to the laid off experience workers, many companies are facing difficulty in training their new employee as most of them do not have enough training experience and are facing difficulty with adapting with the offshore environment. This virtual reality (VR) offshore training would provide a convenient training experience to the offshore workers in obtaining relevant machinery crane operating skills and operation in pipeline training. A simulator-based training using the Virtual Reality (VR) technology provides a more immersive training experience in a non-hazardous environment and can be perform in any closed room environment such in the office or at home. The training is programmed to monitor the workers performance based on the criteria evaluated will be recorded. The VR offshore training was conducted to a total of five users and the training was repeated for five times. A fifteen minutes rest was given in between each completed training. The percentage of user’s achievement was recorded, and the results were tabulated.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121683304","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

A Benchmarking of the Effectiveness of Modular Exponentiation Algorithms using the library GMP in C language 用C语言GMP库对模块化求幂算法的有效性进行基准测试

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247766

Tran Quy Ban, Tran Thi Thuy Nguyen, Vu Thanh Long, Pham Dang Dung, Bui Thanh Tung

引用次数: 0

Wave Height and Peak Wave Period Prediction Using Recurrent Neural Networks 用递归神经网络预测波高和波峰周期

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247805

Kazuki Osawa, Hiroki Yamaguchi, Muhammad Umair, M. Hashmani, K. Horio

引用次数: 4

Face Recognition for Smart Door Lock System using Hierarchical Network 基于层次网络的智能门锁系统人脸识别

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247836

M. Waseem, Sundar Ali Khowaja, R. Ayyasamy, Farhan Bashir

{"title":"Face Recognition for Smart Door Lock System using Hierarchical Network","authors":"M. Waseem, Sundar Ali Khowaja, R. Ayyasamy, Farhan Bashir","doi":"10.1109/ICCI51257.2020.9247836","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247836","url":null,"abstract":"Face recognition system is broadly used for human identification because of its capacity to measure the facial points and recognize the identity in an unobtrusive way. The application of face recognition systems can be applied to surveillance at home, workplaces, and campuses, accordingly. The problem with existing face recognition systems is that they either rely on the facial key points and landmarks or the face embeddings from FaceNet for the recognition process. In this paper, we propose a hierarchical network (HN) framework which uses pre-trained architecture for recognizing faces followed by the validation from face embeddings using FaceNet. We also designed a real-time face recognition security door lock system connected with raspberry pi as an implication of the proposed method. The evaluation of the proposed work has been conducted on the dataset collected from 12 students from Faculty of Engineering and Technology, University of Sindh. The experimental results show that the proposed method achieves better results over existing works. We also carried out a comparison on random faces acquired from the Internet to perform face recognition and results shows that the proposed HN framework is resilient to the randomly acquired faces.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132413440","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: 11