2022 5th International Conference on Computing and Informatics (ICCI)最新文献_第4页

Iris Recognition System Techniques: A Literature Survey and Comparative Study 虹膜识别系统技术:文献综述与比较研究

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756079

Rahmatallah Hossam Farouk, H. Mohsen, Y.M. Abd El-Latif

引用次数: 1

Image Processing-Based Vehicle Class Identification in Mixed Traffic 基于图像处理的混合交通车辆类别识别

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756065

Mohan Kumar Somavarapu, Subhadip Biswas, J. Pal

{"title":"Image Processing-Based Vehicle Class Identification in Mixed Traffic","authors":"Mohan Kumar Somavarapu, Subhadip Biswas, J. Pal","doi":"10.1109/icci54321.2022.9756065","DOIUrl":"https://doi.org/10.1109/icci54321.2022.9756065","url":null,"abstract":"Traffic composition plays a major role to characterize a heterogeneous traffic stream where various categories of vehicles with diverse static and dynamic characteristics share the common carriageway. Due to this diversity, the manual collection of classified traffic volumes often becomes difficult, particularly on busy roads. In this regard, the popularity of the videography method has increased significantly in the last few decades. Because the method offers flexibility to the enumerator(s) to extract the required data at their convenience by playing the video file on a computer screen. However, this method demands ample time and effort from the enumerator(s) that is considered as its major drawback. On this background, the present study proposes an advanced image processing-based approach which is helpful to identify the vehicle class in a video exhibiting the mixed traffic movements. The proposed methodology addresses two major limitations associated with the existing approaches; i) the problem of varying blob size, and ii) the thresholding problem. By eliminating these limitations, the proposed methodology has yielded an accuracy of 96.82% in identifying the right vehicle class. Apart from this, the proposed approach will significantly reduce the time and efforts devoted by the enumerator(s), and hence, it can be a decent substitute for the manual extraction of the classified traffic volume in the future.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126205394","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

An Advisory Student Achievement Model Based on Data Mining Techniques 基于数据挖掘技术的咨询学生成绩模型

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756121

A. N. Zaied, Ehab Moh. Hamza, Rana Wael Ismael

引用次数: 0

A Hybrid Metaheuristic Approach for Automatic Clustering of Breast Cancer 一种混合元启发式的乳腺癌自动聚类方法

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756111

Yasmin A. Badr, Amany H. Abou El-Naga

{"title":"A Hybrid Metaheuristic Approach for Automatic Clustering of Breast Cancer","authors":"Yasmin A. Badr, Amany H. Abou El-Naga","doi":"10.1109/icci54321.2022.9756111","DOIUrl":"https://doi.org/10.1109/icci54321.2022.9756111","url":null,"abstract":"Breast cancer is one of the most widely prevalent cancer in both men and women, however, it is far more common in women. Early diagnosis can help reduce the risk of metastasis to other organs and reduce death rates. Many research studies managed to cluster Breast cancer datasets and help in the accurate detection of tumors nevertheless a few ones could detect the number of clusters automatically. Clustering aims to partition the data into malignant or benign tumors. Recently researchers focused on automatic metaheuristic techniques reforming them to solve the clustering problem. In this paper, a new hybrid technique is proposed to determine the number of clusters with no need of prior information. The genetic algorithm is hybridized with cuckoo search algorithm to automatically cluster the Wisconsin Breast Cancer dataset. Also, a study among obtained results showed that the hybrid genetic cuckoo search algorithm outperformed the standard genetic algorithm and cuckoo search algorithm achieving an adjusted rand index of 0.84 and an adjusted mutual information of 0.74 and accuracy of 84 percent. Moreover, hybrid genetic cuckoo search algorithm was compared to the competing algorithms mentioned in the literature review showing a superior performance.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131338788","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

Survey of Blockchain Methodologies in The Healthcare Industry 医疗保健行业区块链方法调查

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756056

Ashraf Mohey Eldin, E. Hossny, K. Wassif, F. Omara

引用次数: 1

Forecasting Vaccination Growth for COVID-19 using Machine Learning 利用机器学习预测COVID-19疫苗接种增长

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756096

Aimee Putri Hartono, Callista Roselynn Luhur, N. N. Qomariyah

{"title":"Forecasting Vaccination Growth for COVID-19 using Machine Learning","authors":"Aimee Putri Hartono, Callista Roselynn Luhur, N. N. Qomariyah","doi":"10.1109/icci54321.2022.9756096","DOIUrl":"https://doi.org/10.1109/icci54321.2022.9756096","url":null,"abstract":"In this digital era, machine learning (ML) is becoming more common in the healthcare industry. It plays many essential roles in the medical field including clinical forecasting, visualization, and even automated diagnostics. This paper focuses on the future prediction of COVID-19 vaccination rates in different countries. Considering how destructive the novel Coronavirus has been and its continuous mutation and spread, clinical interventions such as vaccines serve as a ray of hope for many individuals. As of 2021, an estimated total of 8,687,201,202 vaccine doses by numerous biopharmaceutical manufacturers have been administered worldwide [1]. This study intends to estimate the probable increase or decrease in global vaccination rates, as well as analyze the correlation between future trends of daily vaccinations and new COVID-19 cases, along with deaths and reproduction rates. Three models were utilized in forecasting and comparing the overall prediction toward the COVID19 vaccine rates; Auto-Regressive Integrated Moving Average (ARIMA), an ML approach, Long-Short Term Memory (LSTM), an artificial Recurrent Neural Networks (RNN), and Prophet which is based on an additive model. The Vector Autoregression (VAR) model will also be utilized to compare COVID-19 cases, deaths and reproduction rates to that of COVID-19 vaccine growth. ARIMA resulted to be the best model, while Prophet turned out to be the worst-performing model. In general, our comparison of employing the ARIMA model vs the other three results in the conclusion that adopting this method shows to be a more effective approach in projecting vaccination growth in the future. Furthermore, a visible increase in future daily vaccinations can be seen to be correlated with the increase in COVID-19 cases, deaths reproduction rates, and a fluctuating trend in COVID-19 deaths.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130748148","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

A Futuristic Appraisal of Malware Detection by Employing Data Mining 基于数据挖掘的恶意软件检测的未来评估

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756097

Fahad Mira

{"title":"A Futuristic Appraisal of Malware Detection by Employing Data Mining","authors":"Fahad Mira","doi":"10.1109/icci54321.2022.9756097","DOIUrl":"https://doi.org/10.1109/icci54321.2022.9756097","url":null,"abstract":"The fourth industrial revolution is the artificial intelligence and digitization of everything, which turns the world into a global hub. The vast use of technology is essential, but it accompanies malwares that destroy confidential information. To overcome these challenges, the latest data mining techniques have been used. It squeezes all invisible information and analyzes massive databases. Malware is unstructured material that can't be determined directly. Various researches have endeavored to turn unstructured data into structured data to overcome this challenge. Due to the rapidly changing and complex pattern of Malware, data mining techniques are used to detect Malware. This survey is furnished with the latest apparatus and pledge information of Malware detection by opting the techniques of data mining. Besides this, it categorizes mainly into two Approaches for-instance signature-based method and the Behaviour-based method. The Focused points of this survey are to layout these First, A a detailed description of Challenges in malware detection by using data mining - Second A complete framework of latest approaches to Machine learning mechanism - Third, a search for an efficient method to detect Malware-Fourth, canvassing of all factor to determine malware approaches in data mining. Moreover, a detailed contrast of detected approaches is also present to facilitate the researchers. Evolution method, advantages and disadvantages are discussed to describe the proficiency. This survey is fully equipped with the latest techniques. In, this report we observed KNN with 22% MLB 16% MLA 12% NB 9% and other SVM 9% KM 7% API 7% and others are less than 5% in detecting malware in data mining., So, we find KNN approach with high accuracy.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114745713","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

Brain Oscillatory Representations of Vibrotactile Parameters: An EEG Study 振动触觉参数的脑振荡表征:脑电图研究

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756106

Xinrong Wang, Xinyue Fang, Xinyj Zheng, Xuemei Deng, Yong Li, Mei Wang

{"title":"Brain Oscillatory Representations of Vibrotactile Parameters: An EEG Study","authors":"Xinrong Wang, Xinyue Fang, Xinyj Zheng, Xuemei Deng, Yong Li, Mei Wang","doi":"10.1109/icci54321.2022.9756106","DOIUrl":"https://doi.org/10.1109/icci54321.2022.9756106","url":null,"abstract":"In the BCI community, haptic feedback allows us to interact with the world around us and, at the same time, perceive these interactions. For the development and maturation of neurophysiology related to haptic feedback, it is requisite to conduct more in-depth researches. To this end, we explored brain oscillatory representations of vibrotactile parameters. We utilized amplitude-modulated vibrotactile stimuli, which have four envelope frequency levels and four amplitude levels. Relevant brain oscillations in five frequency bands and ten channels were measured by noninvasive EEG technique, and they were represented in baseline-based power spectral density (PSD) forms. Results, expressed in interaction effect maps and P-value topographic maps mainly, showed that there were significant interaction effects among envelop frequency, amplitude, frequency band, and electrode position. In particular, when envelope frequency (Fe)= 40 Hz, from alpha band 1 to beta band 1, for all four amplitude levels, brain oscillations over the ipsilateral sensorimotor cortex decreased gradually. Additionally, a slight decrease of brain activation in the contralateral frontal regions was found in the two higher levels of amplitude. When amplitude (A)= 0.8 Grms, from alpha band 1 to beta band 1, for all four envelope frequency levels, brain oscillations over the bilateral sensorimotor cortex decreased gradually. In addition, a increase of brain oscillation in the frontal and parietal regions was found in the two higher envelope frequency levels. Results contribute to a deeper physiological understanding for physical vibrotactile parameters.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133889195","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

A Survey on Generative Adversarial Networks based Models for Many-to-many Non-parallel Voice Conversion 基于生成对抗网络的多对多非并行语音转换模型研究

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756059

Y. Alaa, Marco Alfonse, M. Aref

引用次数: 1

A predictive schedule based energy efficient MAC protocol for wireless sensor networks 基于预测调度的无线传感器网络节能MAC协议

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756088

Md Nasir Uddin, Md. Obaidur Rahman, Sumaya Kazary

{"title":"A predictive schedule based energy efficient MAC protocol for wireless sensor networks","authors":"Md Nasir Uddin, Md. Obaidur Rahman, Sumaya Kazary","doi":"10.1109/icci54321.2022.9756088","DOIUrl":"https://doi.org/10.1109/icci54321.2022.9756088","url":null,"abstract":"A predictive schedule based energy efficient MAC protocol named as PSE2-MAC is proposed in this paper for asynchronous wireless sensor networks. Although the asynchronous MAC protocol offers better performance than that of synchronous MAC in terms of energy but infrequently it suffers from beacon collisions as well as idle listening problem. Although many researchers avoid discussion on beacon collision but it has a great impact on asynchronous MAC. For this reason, the authors in this paper have highlighted the beacon collision problem and proposed a possible solution with prominent results. Along with the solution, the authors have proposed a prominent technique to solve energy consumption issue caused by idle listening. The performance of the proposed protocol has been evaluated and the evaluation result shows that PSE2-MAC performs much better than conventional IEEE 802.15.4 protocol for managing the beacon collision. Also, the simulation results show minimal energy consumption due to idle listening. Thus, the proposed protocol helps to improve overall network performance and throughput.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123577590","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