2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT)最新文献_第2页

An Application of Artificial Intelligence for an Early and Effective Prediction of Heart Failure 人工智能在心力衰竭早期有效预测中的应用

2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) Pub Date : 2022-11-16 DOI: 10.1109/INTELLECT55495.2022.9969182

Muhammad Owais Butt, Attique ur Rehman, Sabeen Javaid, Tahir Muhammad Ali, Ali Nawaz

{"title":"An Application of Artificial Intelligence for an Early and Effective Prediction of Heart Failure","authors":"Muhammad Owais Butt, Attique ur Rehman, Sabeen Javaid, Tahir Muhammad Ali, Ali Nawaz","doi":"10.1109/INTELLECT55495.2022.9969182","DOIUrl":"https://doi.org/10.1109/INTELLECT55495.2022.9969182","url":null,"abstract":"The purpose of this study is to develop a reliable decision support system for predicting the survival of heart failure patients. Over time, heart disease (CVD) has become one of the most visible diseases in the world. The major factors of Heart failure are Sex, cholesterol, high blood pressure, stress, age, Exercise Angina, and Resting ECG. Many researchers have proposed several methods for early diagnosis on the bases of these features. However, due to the hereditary critique of heart disease and the life-threatening risks, it is important to improve the accuracy of the proposed techniques and methods. In this article, a machine learning framework with high accuracy is proposed for the effective diagnosis of heart failure. Specifically, the framework deals with handling missing values through the first Example filter. In the second stage, the data imbalance problem is solved through the Synthetic Minority Over-sampling Technique (SMOTE Upsampling). In the third step, the feature selection is done using (Optimized Feature Selection). The fourth is to normalize the data using the normalization technique, the fifth is to split the data into portions using split operators (30% and 70%). In the final step, the Decision Tree and K-Nearest Neighbor (KNN) classifiers are introduced for effective forecasting as these classifiers achieve the best accuracy (84.11%). The dataset validation has been performed in the background using four types of datasets. (i.e. Failure Prediction Dataset, Cardiovascular Disease, Stroke Prediction Dataset, heart disease). Comparative analysis proves that (Heart Failure Prediction) Dataset achieves better accuracy (84.11%) with fewer sets of features.","PeriodicalId":219188,"journal":{"name":"2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121432654","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

Reinforcement Learning Based Field Oriented Control Of An Induction Motor 基于强化学习的感应电机磁场定向控制

2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) Pub Date : 2022-11-16 DOI: 10.1109/INTELLECT55495.2022.9969403

Ayesha, A. Memon

{"title":"Reinforcement Learning Based Field Oriented Control Of An Induction Motor","authors":"Ayesha, A. Memon","doi":"10.1109/INTELLECT55495.2022.9969403","DOIUrl":"https://doi.org/10.1109/INTELLECT55495.2022.9969403","url":null,"abstract":"Induction motors are well known in industrial applications due to their low cost and reduced maintenance. Vector control or field-oriented control is the most preferred and reliable control technique in industrial world. Field oriented control is based on conventional controllers such as PID mainly due to their simplest structure and low complexity. However, when they are subjected to external disturbances or internal parameter change, it is quite difficult for these conventional controllers to fulfill the control requirements. The purpose of this research is to design a suitable non-linear feedback controller of an induction motor based on reinforcement learning agent. The proposed controller uses only reference speed and the error (difference) between reference speed and the output as control inputs to produce a torque such that rotor speed tracks the reference speed. Reinforcement learning based speed control algorithm is implemented and overall analysis is carried out of the closed loop system. It is shown that the proposed controller is capable of controlling the outer loop which controls the speed of the induction motor by taking different actions based on the given state. The performance of the proposed control schemes is verified under various operating conditions using simulation results.","PeriodicalId":219188,"journal":{"name":"2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126780280","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 Integrated Machine Learning Framework for Classification of Cirrhosis, Fibrosis, and Hepatitis 肝硬化、纤维化和肝炎分类的集成机器学习框架

2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) Pub Date : 2022-11-16 DOI: 10.1109/INTELLECT55495.2022.9969404

Sibgha Islam, A. Rehman, Sabeen Javaid, Tahir Muhammad Ali, Ali Nawaz

{"title":"An Integrated Machine Learning Framework for Classification of Cirrhosis, Fibrosis, and Hepatitis","authors":"Sibgha Islam, A. Rehman, Sabeen Javaid, Tahir Muhammad Ali, Ali Nawaz","doi":"10.1109/INTELLECT55495.2022.9969404","DOIUrl":"https://doi.org/10.1109/INTELLECT55495.2022.9969404","url":null,"abstract":"Hepatitis C is an ailment that causes inflammation of the liver and leads to serious liver damage. In previous research, the accuracy of the model wasn't that accurate but the differences this paper made model worked well for the prediction of Hepatitis C disease. In the dataset, there are mainly four categories (Blood Donor, Suspected Blood Donor, Fibrosis, and Cirrhosis) used that are labeled. Its data type is polynomial with 0 missing values. The minimum value in the category is 7 for suspect blood donors and the most value is 533 for a blood donor. The machine learning algorithms used in medical approaches are increasing day by day for prediction tools, diagnosis tools, and detection of diseases such as the hepatitis C virus. We used the rapid miner Software for the application of machine learning algorithms. Firstly, took the dataset of the hepatitis C virus from the UCI machine learning site and then applied the five Machine Learning Algorithms, which include Naive Bayes, Random Forest, KNN, Decision Tree & Deep Learning (ANN). On applying feature selection, the attributes Age, ALB, ALP, AST, CHE, GGT, and PROT were selected. After applying different algorithms, the best results are shown by deep learning (ANN) with an accuracy of 95.50%. Rest all algorithms showed minimum accuracy as a Decision tree with 93.09%, Naïve Bayes with 91.89%, KNN with 93.09%, and Random Forest showed 94.29% of high accuracy.","PeriodicalId":219188,"journal":{"name":"2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124523466","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

A Novel Model-Driven Approach for Visual Impaired People Assistance OPTIC ALLY 视障人士视障援助的模型驱动新方法

2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) Pub Date : 2022-11-16 DOI: 10.1109/INTELLECT55495.2022.9969400

Laiba Rana, A. Rehman, Sabeen Javaid, Tahir Muhammad Ali

{"title":"A Novel Model-Driven Approach for Visual Impaired People Assistance OPTIC ALLY","authors":"Laiba Rana, A. Rehman, Sabeen Javaid, Tahir Muhammad Ali","doi":"10.1109/INTELLECT55495.2022.9969400","DOIUrl":"https://doi.org/10.1109/INTELLECT55495.2022.9969400","url":null,"abstract":"People having visual impairment can't perform routine tasks on their own such that they are obliged to perform even the simplest task with assistance. Since their issue can't be resolved with visual glasses or lenses, the various mode of advancing technologies is playing an immense role in aiding them. Plenty of research work and development of gadgets have been proposed regarding the assistance of visually impaired people. From deep learning along with sensor-based initiative systems to various ranges of software have been developed but until now every system or software heeds on a particular feature. This article is based on purposing the idea of developing a cross-platform application named Optic Ally, intelligent assistance for visually impaired people that will provide all salient features in it regarding their assistance. For this idea of Optic Ally application, a novel model-driven framework is introduced that comprises a meta-model, tree editor, and graphical modeling tool that is Sirius based with drag and drop palette. The modeling and visualization of the features of this app are done using the Sirius-based graphical modeling tool. Moreover, a case study has been demonstrated for the validity of the proposed framework. The outcome of the case study proves that the proposed framework is competent in modeling and visualizing features effectively. The initial developed stage of the application is also shown in this article. Optic Ally application features include object detection, object finder, location, voice assistance, guardian help, link account and profile setup for the visually impaired user whereas for the guardian user the features include location, profile setup and guardian help","PeriodicalId":219188,"journal":{"name":"2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131261998","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

Future Position Estimation In case of GPS Outages 在GPS中断情况下的未来位置估计

2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) Pub Date : 2022-11-16 DOI: 10.1109/INTELLECT55495.2022.9969387

Muhammad Aseem Uddin Shaikh, Azaan Mahmood, S. S. H. Zaidi, Muhammad Zain, Maria Ashraf

{"title":"Future Position Estimation In case of GPS Outages","authors":"Muhammad Aseem Uddin Shaikh, Azaan Mahmood, S. S. H. Zaidi, Muhammad Zain, Maria Ashraf","doi":"10.1109/INTELLECT55495.2022.9969387","DOIUrl":"https://doi.org/10.1109/INTELLECT55495.2022.9969387","url":null,"abstract":"Global Positioning System (GPS) is the most convenient and accurate position locating systems available today (GPS). It is satellite based positioning method. From any place on the planet, six to eight satellites may normally be seen. For accurate fixing, at least four satellites are required. However, there are certain methods which can severely reduce GPS accuracy. As a result of the accuracy denial measures, the number of satellites available for repair is reduced. These procedures can result in hundreds of meters of inaccuracy. This paper focuses on development of accelerometer based hardware which can be utilized to estimate the location of the vehicle only by knowing basic factors which include the last fixed position, given acceleration and time. Proposed experimental setup suggests that implemented methodology is practical and can be utilized for precise and accurate positioning. Our approach is based on Double Integration Method and Kalman Filter (KF) which augments to future position estimation based on previous known position.","PeriodicalId":219188,"journal":{"name":"2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115574087","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

Novel IoT-Based E-Health System: Hospital Management, Telemedicine and Quarantine Management for COVID-19 基于物联网的新型电子医疗系统:新型冠状病毒肺炎的医院管理、远程医疗和隔离管理

2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) Pub Date : 2022-11-16 DOI: 10.1109/INTELLECT55495.2022.9969396

G. H. Palli, G. F. Mirza, B. S. Chowdhry

{"title":"Novel IoT-Based E-Health System: Hospital Management, Telemedicine and Quarantine Management for COVID-19","authors":"G. H. Palli, G. F. Mirza, B. S. Chowdhry","doi":"10.1109/INTELLECT55495.2022.9969396","DOIUrl":"https://doi.org/10.1109/INTELLECT55495.2022.9969396","url":null,"abstract":"Patients commonly visit to hospitals for monitoring and treatment of their chronic diseases especially in COVID-19 epidemic ultimately increases the patients and hospitals' burden. The foremost advancement with respect to examining a patient's critical condition in such pandemic is remote patient monitoring and providing treatment via telemedicine. The main objective of this paper is to provide a novel Internet of Things (IoT) based system for continuous remote monitoring of patients' location, health statistics related to COVID-19 infection, telemedication and maintaining E-health record database. The system monitors oxygen levels and heart-rate signals using MAX30100 (Heart Rate and Pulse Oximeter sensor) and temperature via LM-35 module interfaced with the ESP8266 WI-FI module for web-monitoring. The healthcare sector involving a web server database controlled by cPanel will be used by consultants to have patients' data remotely for telemedicine. Besides, the database is also used as an electronic health record for hospital management system to maintain E-files and history of patients' complications. Moreover, the device monitors the real time location of infected patients using GPS and alerts the medical officials if the patients breach the quarantine norms. The real time location of infected patients also enables the medical authorities to investigate about the total number of COVID-19 cases in any particular area. However, the android application is developed for patients' family/relatives so that they can also monitor the patient condition to take the necessary actions before the worst condition arises. The developed system is efficient in providing integrated services to assist healthcare officials, minimize cost, maintains security and upgrade disease diagnosis speed in less time.","PeriodicalId":219188,"journal":{"name":"2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115319273","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

Design, Development and Control of a Low Cost Vacuuming Robot (Robo Vac) for Classroom 低成本教室吸尘机器人(Robo Vac)的设计、开发与控制

2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) Pub Date : 2022-11-16 DOI: 10.1109/INTELLECT55495.2022.9969405

A. Ashraf, Hira Ahsan, Muhammad Sufyan Arshad

{"title":"Design, Development and Control of a Low Cost Vacuuming Robot (Robo Vac) for Classroom","authors":"A. Ashraf, Hira Ahsan, Muhammad Sufyan Arshad","doi":"10.1109/INTELLECT55495.2022.9969405","DOIUrl":"https://doi.org/10.1109/INTELLECT55495.2022.9969405","url":null,"abstract":"With the overgrowing increase in technology, robots are being used for navigation, industries and household chores due to their ability to finish the work efficiently. One of these tasks is vacuuming. Conventional vacuum cleaners require manual labor and are bulky in size producing noise. In this study, a low cost Vacuuming robot is developed. RoboVac utilizes IMU along with rotary encoders to track the traveled distance and PID controller implementation for close loop control for straight path motion at the desired constant speed. IMU is used for calculating drift in yaw angle to take turn at a precise angle of 90 degrees. The combination of IR sensors with Ultrasonic sensors detect obstacles and get as near to them as possible for better cleaning. The study highlights the design parameters, motor selection, and algorithm for the autonomous motion of the RoboVac. The proposed algorithm was first simulated using WeBots robot simulator and then implemented on actual hardware. The technique developed along with the hardware was tested in the premises of Institute of Space Technology under different environments (with and without obstacles) and showed satisfactory results. Algorithm can be used and modified for indoor navigation of similar robots.","PeriodicalId":219188,"journal":{"name":"2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129435205","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

Levenberg-Marquardt based ANN for design of Rectangular Dielectric Resonator Antenna for LTE Application 基于Levenberg-Marquardt的LTE矩形介质谐振器天线设计

2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) Pub Date : 2022-11-16 DOI: 10.1109/INTELLECT55495.2022.9969391

Aneeqa Bibi, Syed Nazim Shah, Shoaib Azmat, J. Nasir

{"title":"Levenberg-Marquardt based ANN for design of Rectangular Dielectric Resonator Antenna for LTE Application","authors":"Aneeqa Bibi, Syed Nazim Shah, Shoaib Azmat, J. Nasir","doi":"10.1109/INTELLECT55495.2022.9969391","DOIUrl":"https://doi.org/10.1109/INTELLECT55495.2022.9969391","url":null,"abstract":"Antenna design process requires Electromagnetic (EM) simulations which can be performed on EM simulators such as HFSS, CST, ADS and IE3D etc. To solve the antenna design problems, these EM simulators required large computational resources and time. With the increase of parameters and design complexity, simulation cost and time of EM simulators escalates. To overcome this difficulty, Artificial Neural Network (ANN) can be used as an alternative approach for antenna design which greatly reduces computational cost and time. A design of rectangular dielectric resonator antenna (RDRA) based on Artificial neural network approach is presented in this paper for LTE applications. The rectangular resonator having relative permittivity of 30 is placed on top of substrate which has relative permittivity (∊r) of 4.6 and 1.6mm of thickness and simulated by using well-known 3-D electromagnetic (EM) simulator ANSYS HFSS. ANN used consists of one input layer, one hidden layer and one output layer. The neural network is trained using Levenberg-Marquardt algorithm and the data set is divided into 70%, 15% and 15% for training, testing, and validation respectively. The error, described by the difference between the target data and expected output, is 0.007.","PeriodicalId":219188,"journal":{"name":"2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123927145","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 Computer Aided Technique for Classification of Patients with Diabetes 糖尿病患者分类的计算机辅助技术

2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) Pub Date : 2022-11-16 DOI: 10.1109/INTELLECT55495.2022.9969392

Faiza Mehreen, A. Rehman, Tahir Ali, Sabeen Javaid, Ali Nawaz

{"title":"A Computer Aided Technique for Classification of Patients with Diabetes","authors":"Faiza Mehreen, A. Rehman, Tahir Ali, Sabeen Javaid, Ali Nawaz","doi":"10.1109/INTELLECT55495.2022.9969392","DOIUrl":"https://doi.org/10.1109/INTELLECT55495.2022.9969392","url":null,"abstract":"Diabetes is a chronic disease that occurs when the sugar level is too high in the body or when the body doesn't make enough insulin and it impacts each individual of all age groups. It has a captivating history that has increased significantly in recent years as a result of urbanization and affected millions of people worldwide. Undiagnosed diabetes can cause many life-threatening diseases which usually lead to the death of a person. So, the early detection of diabetes is very vital to maintain a healthy life and it can help to prevent complications and reduce patients' health risks. This paper undertakes to design a model which gives maximum accuracy by using different machine learning algorithms that help detect the disease in its early stage. For this purpose, used five classifiers which are Random Forest, Decision Tree, K-Nearest Neighbor, Naïve Bayes, and Deep learning, then apply the Vote ensemble approach that is considered “best practice” and is a part of the workflow and provides the best possible outcomes with the highest accuracy percentage. The informational data employed as a part of this analysis is taken from the Kaggle dataset of Early Diabetes Classification and preprocessed this all data on the RapidMiner Tool. The main point of this research is the implementation of the different ML based classification models to show their comparative analysis. Thus, by using these algorithms the diagnosis of diabetes is statistically evaluated and compared. The experimental outcomes show that in the vote ensemble, Random Forest with K-NN gives optimum results with the highest accuracy of 97.97% along with parameters like precision, f-measure, and sensitivity.","PeriodicalId":219188,"journal":{"name":"2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127729156","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

Wind's Data Analysis for its Accurate Prediction in Smart Grid Systems 智能电网中风电数据的准确预测分析

2022 Third International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) Pub Date : 2022-11-16 DOI: 10.1109/INTELLECT55495.2022.9969399

M. Ashraf, Asif Gulraiz, S. S. Zaidi, Farhana Ashraf, B. Khan

引用次数: 1