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Fleet Optimization of Smart Electric Motorcycle System Using Deep Reinforcement Learning

Computers, Materials & Continua 2022年第4期71卷 1925-1943页

作者： Patikorn Anchuen Peerapong Uthansakul Monthippa Uthansakul settawit poochaya School of Telecommunication Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand

Smart electric motorcycle-sharing systems based on the digital platform are one of the public transportations that we use in daily lives when the sharing economy is considered.This transportation provides convenience for users with low-cost systems while it also promotes an environmental conservation.Normally,users rent the vehicle to travel from the origin station to another station near their destination with a one-way trip in which the demand of renting and returning at each station is different.This leads to unbalanced vehicle rental systems.To avoid the full or empty inventory,the electric motorcycle-sharing rebalancing with the fleet optimization is employed to deliver the user experience and increase rental opportunities.In this paper,the authors propose a fleet optimization to manage the appropriate number of vehicles in each station by considering the cost of moving tasks and the rental opportunity to increase business return.Although the increasing number of service stations results in a large action space,the proposed routing algorithm is able filter the size of the action space to enable computing tasks.In this paper,a Deep Reinforcement Learning(DRL)creates the decisionmaking function to decide the appropriate action for fleet allocation from the last state of the number of vehicles at each station in the real environment at Suranaree University of Technology(SUT),Thailand.The obtained results indicate that the proposed concept can reduce the Operating Expenditure(OPEX).

关键词： Electric motorcycle-sharing sharing economy reinforcement learning OPEX

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Automatic Leukaemia Segmentation Approach for Blood Cancer Classification Using Microscopic Images

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Computers, Materials & Continua 2022年第11期73卷 3629-3648页

作者： Anuj Sharma Deepak Prashar Arfat Ahmad Khan Faizan Ahmed Khan settawit poochaya School of Computer Applications Lovely Professional UniversityPhagwara144411India School of Computer Science&Engineering Lovely Professional UniversityPhagwara144411India Suranaree University of Technology Nakhon Ratchasima30000Thailand COMSATS University Lahore 54000Pakistan

Leukaemia is a type of blood cancer that is caused by undeveloped White Blood Cells(WBC),and it is also called a blast blood cell.In the marrow of human bones,leukaemia is developed and is responsible for blood cell generation with leukocytes and WBC,and if any cell gets blasted,then it may become a cause of death.Therefore,the diagnosis of leukaemia in its early stages helps greatly in the treatment along with saving human lives.Subsequently,in terms of detection,image segmentation techniques play a vital role,and they turn out to be the important image processing steps for the extraction of feature patterns from the Acute Lymphoblastic Leukaemia(ALL)type of blood cancer.Moreover,the image segmentation technique focuses on the division of cells by segmenting a microscopic image into background and cancer blood cell nucleus,which is well-known as the Region Of Interest(ROI).As a result,in this article,we attempt to build a segmentation technique capable of solving blood cell nucleus segmentation issues using four distinct scenarios,including K-means,FCM(Fuzzy Cmeans),K-means with FFA(Firefly Algorithm),and FCM with FFA.Also,we determine the most effective method of blood cell nucleus segmentation,which we subsequently use for the Leukaemia classification model.Finally,using the Convolution Neural Network(CNN)as a classifier,we developed a leukaemia cancer classification model from the microscopic images.The proposed system’s classification accuracy is tested using the CNN to test the model on the ALL-IDB dataset and equate it to the current state of the art.In terms of experimental analysis,we observed that the accuracy of the model is near to 99%,and it is far better than other existing models that are designed to segment and classify the types of leukaemia cancer in terms of ALL.

关键词： Leukaemia blood cell nucleus image segmentation HOG descriptor K-means FCM CNN microscopic images

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A Multi-Mode Public Transportation System Using Vehicular to Network Architecture

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Computers, Materials & Continua 2022年第12期73卷 5845-5862页

作者： settawit poochaya Peerapong Uthansakul Monthippa Uthansakul Patikorn Anchuen Kontorn Thammakul Arfat Ahmad Khan Niwat Punanwarakorn Pech Sirivoratum Aranya Kaewkrad Panrawee Kanpan Apichart Wantamee School of Telecommunication Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand Office of Graduate Studies Navaminda Kasatriyadhiraj Royal Air Force AcademyBangkok10220Thailand School of Mechanical Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand School of Manufacturing Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand Thaicom Public Company Limited Patumthani12140Thailand

The number of accidents in the campus of Suranaree University of Technology(SUT)has increased due to increasing number of personal vehicles.In this paper,we focus on the development of public transportation system using Intelligent Transportation System(ITS)along with the limitation of personal vehicles using sharing economy model.The SUT Smart Transit is utilized as a major public transportation system,while MoreSai@SUT(electric motorcycle services)is a minor public transportation system in this work.They are called Multi-Mode Transportation system as a combination.Moreover,a Vehicle toNetwork(V2N)is used for developing theMulti-Mode Transportation system in the campus.Due to equipping vehicles with On Board Unit(OBU)and 4G LTE modules,the real time speed and locations are transmitted to the cloud.The data is then applied in the proposed mathematical model for the estimation of Estimated Time of Arrival(ETA).In terms of vehicle classifications and counts,we deployed CCTV cameras,and the recorded videos are analyzed by using You Only Look Once(YOLO)algorithm.The simulation and measurement results of SUT Smart Transit and MoreSai@SUT before the covid-19 pandemic are discussed.Contrary to the existing researches,the proposed system is implemented in the real environment.The final results unveil the attractiveness and satisfaction of users.Also,due to the proposed system,the CO_(2) gas gets reduced when Multi-Mode Transportation is implemented practically in the campus.

关键词： Smart transit intelligent transportation system(ITS) dedicated short range communication(DSRC) vehicle to network(V2N) vehicle to everything(V2X) electric vehicle(EV) you only look once(YOLO)

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Measuring Reliability of A Web Portal Based on Testing Profile

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Computers, Materials & Continua 2023年第3期74卷 6641-6663页

作者： Malik Muhammad Ali Shahid Shahida Sulaiman Mohammed Al-Sarem Aqeel Ur Rahman Salman Iqbal Rab Nawaz Bashir Arfat Ahmad Khan Momen M.Alrawi Rashiq R.Marie settawit poochaya COMSATS University Islamabad Vehari Vehari61100Pakistan Universiti Teknologi Malaysia Johor Bahru81310Malaysia College of Computer Science and Engineering Taibah UniversityMedina41477Saudi Arabia Information System Department Sheba Region UniversityMarib14400Yemen Suranaree University of Technology Nakhon Ratchasima30000Thailand Khon Kaen University Khon Kaen40000Thailand Umm Al-Qura University Mecca24382Saudi Arabia Taibah University Medina42353Saudi Arabia

Conventionally,the reliability of a web portal is validated with generalized conventional methods,but they fail to provide the desired results.Therefore,we need to include other quality factors that affect reliability such as usability for improving the reliability in addition to the conventional reliability testing.Actually,the primary objectives of web portals are to provide interactive integration of multiple functions confirming diverse requirements in an efficient way.In this paper,we employ testing profiles tomeasure the reliability through software operational profile,input space profile and usability profile along with qualitative measures of reliability and usability.Moreover,the case study used for verification is based on aweb application that facilitates information and knowledge sharing among its online members.The proposed scheme is compared with the conventional reliability improvement method in terms of failure detection and reliability.The final results unveil that the computation of reliability by using the traditional method(utilizing failure points with the assistance of Mean Time Between Failures(MTBF)and Mean Time To Failure(MTTF)becomes ineffective under certain situations.Under such situations,the proposed scheme helps to compute the reliability in an effective way.Moreover,the outcomes of the study provide insight recommendations about the testing and measurement of reliability for Web based software or applications.

关键词： Software usability software reliability web portals software testing software testing profile

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