2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)最新文献_第2页

Facial Expression Recognition Using Patch-Based LBPS in an Unconstrained Environment 无约束环境下基于patch的LBPS面部表情识别

2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA) Pub Date : 2021-04-06 DOI: 10.1109/CAIDA51941.2021.9425309

T. Saba, Muhammad Kashif, Erum Afzal

引用次数: 1

CPN.Net: An Automated Colored Petri Nets Model Extraction From .Net Based Source Code 尼泊尔共产党。Net:一个基于。Net的彩色Petri网模型自动提取的源代码

2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA) Pub Date : 2021-04-06 DOI: 10.1109/CAIDA51941.2021.9425201

Aghyad Albaghajati, Moataz A. Ahmed

引用次数: 0

Securing E-payment Systems by RFID and Deep Facial Biometry 利用RFID和深度面部生物识别技术保护电子支付系统

2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA) Pub Date : 2021-04-06 DOI: 10.1109/CAIDA51941.2021.9425175

Nadir Kamel Benamara, M. Keche, Murisi Wellington, Zhou Munyaradzi

{"title":"Securing E-payment Systems by RFID and Deep Facial Biometry","authors":"Nadir Kamel Benamara, M. Keche, Murisi Wellington, Zhou Munyaradzi","doi":"10.1109/CAIDA51941.2021.9425175","DOIUrl":"https://doi.org/10.1109/CAIDA51941.2021.9425175","url":null,"abstract":"Security is a major concern in Electronic Payment (E-Payment) systems. Usually, these systems are protected against illegal users, so-called hackers, by different means, such as Personal identification numbers (PINs), passwords, cards, etc. However, these hackers may manage to bypass this protection by having recourse to different strategies. Many techniques have been proposed to counter hacking attempts; however, there are still situations where an illegal user may succeed to access the E-payment system easily by stealing from a legal user its payment card. The use of Artificial Intelligence methods for face authentication, like deep learning, has made facial biometry a highly developing and accurate technology, especially in the past decade. In this paper, we propose the joint use of deep learning-based facial biometry and RFID cards to reinforce the security of an E-Payment system. By doing so, we ensure that a user should be physically present carrying his RFID card to be able to access the E-Payment system. We have tested three deep learning-based face authentication models and validated them on MUCT and CASIA Face-V5 datasets, to choose the most suitable one for our proposed secured E-Payment system, obtaining top verification rates of 99.90% and 99.26%, respectively. Two versions of this system are proposed; in the first version, which is based on a Personnel Computer (PC) and a Raspberry card, face authentication is implemented in a PC and the control of the RFID reader is performed by a Raspberry Pi 3, whereas in the second version, which may be considered as an embedded system, all the job is accomplished by the Raspberry Pi.","PeriodicalId":272573,"journal":{"name":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125158523","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: 2

M-health Concept, Services and Issues 移动医疗的概念、服务和问题

2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA) Pub Date : 2021-04-06 DOI: 10.1109/CAIDA51941.2021.9425262

Anwar D. Alhejaili

引用次数: 1

A Novel Ensemble Learning Approach of Deep Learning Techniques to Monitor Distracted Driver Behaviour in Real Time 一种新的集成学习方法的深度学习技术实时监测分心驾驶行为

2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA) Pub Date : 2021-04-06 DOI: 10.1109/CAIDA51941.2021.9425243

Hafiz Umer Draz, Muhammad Zeeshan Khan, M. U. Ghani Khan, A. Rehman, I. Abunadi

{"title":"A Novel Ensemble Learning Approach of Deep Learning Techniques to Monitor Distracted Driver Behaviour in Real Time","authors":"Hafiz Umer Draz, Muhammad Zeeshan Khan, M. U. Ghani Khan, A. Rehman, I. Abunadi","doi":"10.1109/CAIDA51941.2021.9425243","DOIUrl":"https://doi.org/10.1109/CAIDA51941.2021.9425243","url":null,"abstract":"Driver distraction causes one of the major problems in road safety and accidents. According to the World Health Organization (WHO), over 285,000 estimated accidents happened as a result of distracted drivers per year. To address such a fatal issue and considering the future of Intelligent Transport System, we have proposed a novel ensemble learning approach based on deep learning techniques for detecting a distracted driver. In the proposed approach, we have fine-tuned the Faster-RCNN for detecting the objects involved in distracting the driver during driving and achieved 97.7% validation accuracy. Moreover, to make the prediction strong and reduced the false positive, pose points of the driver have also extracted. By using those pose points, we make sure that we detect only those objects which are directly associated with the driver’s distraction. The interactive association of various objects with the driver has calculated using the intersection over the union between the detected object and the current posture features of the driver. Our proposed ensemble learning technique has achieved over 92.2% accuracy which is far better than previously proposed models. The proposed method is not only time-efficient, robust, but cost-efficient as well. Such a model not only can ensure road safety as well as help Governments to save resources being spent on monetary losses.","PeriodicalId":272573,"journal":{"name":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133651626","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: 2

Robotics to Enhance the Teaching and Learning Process 提高教学和学习过程的机器人技术

2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA) Pub Date : 2021-04-06 DOI: 10.1109/CAIDA51941.2021.9425061

R. Al-Jumeily, H. Kolivand, Shatha Ghareeb, J. Mustafina, M. Al-khafajiy, T. Baker

{"title":"Robotics to Enhance the Teaching and Learning Process","authors":"R. Al-Jumeily, H. Kolivand, Shatha Ghareeb, J. Mustafina, M. Al-khafajiy, T. Baker","doi":"10.1109/CAIDA51941.2021.9425061","DOIUrl":"https://doi.org/10.1109/CAIDA51941.2021.9425061","url":null,"abstract":"In 21st-century learning academic, where collaboration, digital literacy, critical thinking, and problem-solving are considered the core competencies to be enhanced and developed further.In a multinational country, such as the United Arab Emirates (UAE) which remains one of the fastest-growing countries on the planet in all domains including education, tourism and health there is a gap in matching students with different background. To accommodate different background, heritage and education systems for the incoming expats and their family and kids, there are different education systems (America, British, Local, Indian to name but a few) that are currently running in the UAE. However, the move from one system to another is not a straightforward process due to many reasons which can be categorized into three groups: admission stage, leveling stage, and class stage. The implementation of the proposed work will be integrated as a case study in one of the British school systems in Abu Dhabi, UAE. This paper considers the application of the robotics in Education providing the background for current use of the robots in the society.","PeriodicalId":272573,"journal":{"name":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133936854","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

Deep Learning-Based Classification of News Texts Using Doc2Vec Model 基于Doc2Vec模型的深度学习新闻文本分类

2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA) Pub Date : 2021-04-06 DOI: 10.1109/CAIDA51941.2021.9425290

Hasibe Busra Dogru, Sahra Tilki, Akhtar Jamil, Alaa Ali Hameed

引用次数: 16

Smart Car Seat Belt: Accident Detection and Emergency Services in Smart City Environment 智能汽车安全带:智慧城市环境下的事故检测与应急服务

2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA) Pub Date : 2021-04-06 DOI: 10.1109/CAIDA51941.2021.9425108

Majd Khaled Almohsen, Renad khlief alonzi, Taif Hammad Alanazi, Shahad Nasser BinSaif, Maha Mohammed almujally

{"title":"Smart Car Seat Belt: Accident Detection and Emergency Services in Smart City Environment","authors":"Majd Khaled Almohsen, Renad khlief alonzi, Taif Hammad Alanazi, Shahad Nasser BinSaif, Maha Mohammed almujally","doi":"10.1109/CAIDA51941.2021.9425108","DOIUrl":"https://doi.org/10.1109/CAIDA51941.2021.9425108","url":null,"abstract":"Delay in the arrival of emergency team after a road accident is one of the main reasons for the increase in the number of deaths in many counties across the globe. Saudi Arabia is not exception. This was the key motivation to undertake this project with an aim to contribute an IoT product that can reduce the number of deaths resulting from the problem of delaying the arrival of emergency team or ambulance. In this project we have designed a seat belt with sensor that senses the heart beat rate of the driver and send a notification to the ambulance about the driver’s location if he had an accident. To determine whether accident has occurred, the raw data from heart beat sensor is collected along with the data from vibration sensor of the car. Based on the value of these two collected data, UNO microcontroller is used to process and determine whether it is an accident. If accident the controller utilizes the GPS in the car to get the current location and sends notification to the pre-stored emergency contact numbers. The system will use GSM technology to send an alert containing the location of the accident. Also, we have added a fingerprint to confirm the identity of the passenger so that the sensor does not make mistakes when monitoring the heart rate if the driver changes. Here, we use Arduino platform to implement the hardware connections and for programming Arduino IDE is used. Thus, the end-product of our project is expected to reduce the percentage of deaths that may occur due to delaying ambulance.","PeriodicalId":272573,"journal":{"name":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128585619","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

Data Analytics and Predictive Modeling for Appointments No-show at a Tertiary Care Hospital 三级护理医院预约未到的数据分析和预测建模

2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA) Pub Date : 2021-04-06 DOI: 10.1109/CAIDA51941.2021.9425258

Amani Moharram, Saud Altamimi, Riyad Alshammari

{"title":"Data Analytics and Predictive Modeling for Appointments No-show at a Tertiary Care Hospital","authors":"Amani Moharram, Saud Altamimi, Riyad Alshammari","doi":"10.1109/CAIDA51941.2021.9425258","DOIUrl":"https://doi.org/10.1109/CAIDA51941.2021.9425258","url":null,"abstract":"This study aims to develop an accurate machine learning model for predicting no-shows in pediatric outpatient clinics at King Faisal Specialist Hospital and Research Centre (KFSH&RC), and understand pediatric patients' characteristics who are most likely will not show to their scheduled appointments. Appointment no-show data collected from KFSH&RC data warehouse over the period (01 Jan – 31 Dec 2019). We analyzed a dataset that consists of 101,534 scheduled appointments for 35,290 pediatric patients. No-shows over the mentioned period was 11,573 for 8,105 patients. Three machine-learning algorithms, namely logistic regression, JRip, and Hoeffding tree, were compared to find the best one. The no-show rate in pediatric outpatient clinics was 11.39%. Accuracy, precision, recall, and F-score were selected to evaluate the built models performance. The precision and recall of the three models was around 90%. The F-score of the three models was similar and equal to 0.86. These models improved our capability to identify pediatric patients’ characteristics at high risk of not attending their appointments.","PeriodicalId":272573,"journal":{"name":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","volume":"415 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126688971","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

Developing a LBPH-based Face Recognition System for Visually Impaired People 基于lbph的视障人士人脸识别系统的开发

2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA) Pub Date : 2021-04-06 DOI: 10.1109/CAIDA51941.2021.9425275

Md. Golam Mahabub Sarwar, Ashim Dey, Annesha Das

{"title":"Developing a LBPH-based Face Recognition System for Visually Impaired People","authors":"Md. Golam Mahabub Sarwar, Ashim Dey, Annesha Das","doi":"10.1109/CAIDA51941.2021.9425275","DOIUrl":"https://doi.org/10.1109/CAIDA51941.2021.9425275","url":null,"abstract":"A large number of people around the world are suffering from visual impairment which is a global health issue. These visually challenged people face a great deal of difficulties in carrying out their day-to-day activities. Recognizing a person is one of the major problems faced by them. This document represents a face recognition system with auditory output which can be beneficial for visually challenged people in recognizing known and unknown persons. Proposed face recognition system is comprised of three main modules including dataset creation, dataset training, and face recognition. Here, Haar Cascade Classifier is used to detect face from a live video stream and then Local Binary Pattern Histogram (LBPH) algorithm is applied to create the recognizer for face recognition using OpenCV-Python library. This system can detect and recognize multiple people and is also capable of recognizing from both front and side face. The overall face recognition accuracy is about 93%. Apart from visually challenged people, old people with Alzheimer’s disease can also be benefited using this system.","PeriodicalId":272573,"journal":{"name":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122095563","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