H. S. Husin, Nurnasuha Amar, Aznida Abu Bakar Sajak, Mohd Sallehin Mohd Kassim
{"title":"Distribution map of oil palm fresh fruit bunch using LiDAR*","authors":"H. S. Husin, Nurnasuha Amar, Aznida Abu Bakar Sajak, Mohd Sallehin Mohd Kassim","doi":"10.1109/ICICS52457.2021.9464575","DOIUrl":"https://doi.org/10.1109/ICICS52457.2021.9464575","url":null,"abstract":"Oil palm tree has been the key to Malaysia’s economic expansion, where it has become the most important, national agricultural crop. Techniques of planting, assessment, and detection are crucial to harvest a good quality of palm oil. At present, the ripeness of oil palm fresh fruit bunch (FFB) is determined using computer vision, eyesight, near-infrared (NIR) spectroscopy, light detection and ranging (LiDAR), and Hue, Saturation, and Intensity (HSI) techniques. This research objective is to categorize the ripeness of oil palm FFB from data received from the sensor and to create a distribution map. The methodology chosen to develop this project is the waterfall model, while the findings of this study will be the classified ripeness of oil palm FFB are either under-ripe, ripe, or overripe, and the map of distribution.","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131022208","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}
Jacky Casas, S. Berger, Omar Abou Khaled, E. Mugellini, D. Lalanne
{"title":"Country Localisation of Twitter Users","authors":"Jacky Casas, S. Berger, Omar Abou Khaled, E. Mugellini, D. Lalanne","doi":"10.1109/ICICS52457.2021.9464545","DOIUrl":"https://doi.org/10.1109/ICICS52457.2021.9464545","url":null,"abstract":"Localising Twitter users when trying to analyse local trends, events, or mood is a useful capability. However, there is still no method able to reach high precision and recall. Research projects attempting to localise Twitter users to a precise radius (e.g., 10km) managed to localise at most 60% of users correctly. In this paper, we propose a way to classify them by the country they are located in, instead of finding a precise localisation. We apply our technique to Switzerland and locate the users to inside or outside of the country. Among different features, we used relations of users to a list of \"Swiss Influencers\" accounts - that is, accounts which are mostly of interest to Swiss people. A full classification pipeline was implemented and tested. We have found that our best classification models achieved an accuracy of 95%, with a maximum precision of 98%, and a maximum recall of 91%. This goes to show that our binary classification problem, while potentially not being specific enough for certain types of applications, can amount to significantly more reliable results.","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133049067","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}
{"title":"Cooperation-based Interference Mitigation in Heterogeneous Cloud Radio Access Networks without Requiring CSI","authors":"Areen Atrouz, M. Shurman, A. Alma'aitah","doi":"10.1109/ICICS52457.2021.9464547","DOIUrl":"https://doi.org/10.1109/ICICS52457.2021.9464547","url":null,"abstract":"Researchers have developed the development of a Heterogeneous Cloud Radio Access Network (HCRAN) consists of a Small Remote Radio Head (S-RRH) for the secondary users (Small Cell Users SUEs) and macro RRH for the primary users (multiple macrocell users MUEs), to meet the continuous increase in the number of mobile phone users and the change in traffic patterns. However, H-CRAN layers may overlap each other. Researches were able to reduce internal interference between RRHs through central collaborative processing in the BBU group. Layer interference between small RRHs cells (S-RRHs) and RRH Macrocell (RRH macros) was resolved by proposing a framework to reduce interference between Microcell networks and small cellular networks by suggesting a two-way collaborative algorithm. But they assumed that the channel status information (CSI) was available. This assumption makes no sense in the wireless communication environment, due to the possible interruption of specific ranges, which results in devices not obtaining or delaying the information. The study was also limited to fixed users or infantry subjects. They did not predict the movement of people moving at high speeds. In this paper, we will use the frequency hopping (FH) orthogonal frequency division multiplexing-aided differential chaos shift keying (OFDM-DCSK) modulation to overcome an inaccurate or unknown CSI problem, In addition to the ability to predict the movement of users who move between cells, and provide services within the cell in which the user is located.","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129613672","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}
{"title":"DeSAN: De-anonymization against Background Knowledge in Social Networks","authors":"Nidhi Desai, M. Das","doi":"10.1109/ICICS52457.2021.9464573","DOIUrl":"https://doi.org/10.1109/ICICS52457.2021.9464573","url":null,"abstract":"Social network de-anonymization is a challenging research problem. Gigantic volumes of social network data get collected by third-party applications to mine knowledge for devising government policies, business decisions, health records, and many more. Social network data is vulnerable to privacy leakage due to the presence of sensitive information. Furthermore, attackers knowledge and their manipulation capabilities have also expanded in multi-folds. As a result, modelling the attacker’s knowledge helps design a practical privacy model that could overcome attackers capabilities. Semantic knowledge has the potential to disclose privacy where the information is imprecise and inaccurate. This paper proposes a deanonymization technique, DeSAN, against imprecise and inaccurate attacker knowledge. The proposed technique assumes the attacker’s knowledge, comprehensive and realistic. We have implemented the proposed DeSAN technique on a real social dataset, which exhibits encouraging result in terms of deanonymization accuracy.","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114958274","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}
{"title":"Keynote Speech 1: Empowering Pandemic Response and Management Systems using AI and IoT","authors":"","doi":"10.1109/icics52457.2021.9464599","DOIUrl":"https://doi.org/10.1109/icics52457.2021.9464599","url":null,"abstract":"","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130627982","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}
{"title":"Keynote Speech 2: Detecting fake news and profiling fake news spreaders and conspiracy propagators","authors":"","doi":"10.1109/icics52457.2021.9464534","DOIUrl":"https://doi.org/10.1109/icics52457.2021.9464534","url":null,"abstract":"","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134250268","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}
{"title":"ICICS 2021 Cover Page","authors":"","doi":"10.1109/icics52457.2021.9464615","DOIUrl":"https://doi.org/10.1109/icics52457.2021.9464615","url":null,"abstract":"","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123161325","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}
{"title":"Keynote Speech 3: Direct Error Driven Deep Learning for Bigdata Classification","authors":"","doi":"10.1109/icics52457.2021.9464586","DOIUrl":"https://doi.org/10.1109/icics52457.2021.9464586","url":null,"abstract":"","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126673551","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}
{"title":"ICICS 2021 Committee","authors":"","doi":"10.1109/icics52457.2021.9464612","DOIUrl":"https://doi.org/10.1109/icics52457.2021.9464612","url":null,"abstract":"","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121948940","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}