Azerbaijan Journal of High Performance Computing最新文献

{"title":"SIMULATION-BASED NETWORK FAULT INJECTION IN THE CLOUDSIM PLUS CLOUD SIMULATION ENVIRONMENT","authors":"Farida Asadova, Gábor Kertész, R. Lovas","doi":"10.32010/26166127.2023.6.1.121.131","DOIUrl":"https://doi.org/10.32010/26166127.2023.6.1.121.131","url":null,"abstract":"One effective method for assessing the dependability of computer systems is fault injection. This deliberate technique introduces faults into a system to assess its resilience and ability to handle abnormal conditions. Therefore, this study investigates and simulates the different network problems in the CloudSim Plus environment. CloudSim Plus is a simulation framework that enables the modeling and simulation of cloud computing environments, allowing researchers and practitioners to evaluate the performance and behavior of cloud-based systems and algorithms. Network fault detection and its management are essential duties in cloud systems. Moreover, the feasibility of manual monitoring and involvement has decreased as these infrastructures expand and change. This paper briefly introduces network problems and fault injection outcomes in CloudSim Plus nodes.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"47 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130685124","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":"RESEARCH ON DATABASE TYPES AND METHODS TO STANDARDIZE DATABASE TYPES IN THE FIELD OF TRANSPORT INFRASTRUCTURE","authors":"Tran Anh Kiet, Trinh Cong Duy","doi":"10.32010/26166127.2023.6.1.3.18","DOIUrl":"https://doi.org/10.32010/26166127.2023.6.1.3.18","url":null,"abstract":"In truthfully, managing and storing information and data at the Department of Transport and its units in Da Nang city is still done manually and sporadically. Currently, the majority of them still utilize paper or digitized records but still save them separately on personal computers for managing and storing information regarding infrastructure, modes of transportation, etc. (.doc, .xls, .pdf files, Autocad, Video, Audio, Images, ...). Storing, maintaining, looking up, and discovering information is greatly hampered by this. There are still inconsistencies and delays in the deployment of information reporting, management information, digitization, and the availability of exploitation channels. In line with the Ministry of Transport's strategy, information technology should be used to manage transportation activities. Organizations and units in the transportation industry across the nation have developed and implemented various specialized software to assist in managing road transport. Software solutions have offered management information, enhancing professional management effectiveness. The deploying units use each software system separately, storing and handling specialized data in various ways. When it is necessary to handle and review the information of road transport vehicles, including registration information, vehicle registration, and information about traffic safety infractions, the program does not have a connection or data sharing capabilities. To access and compare data, expert employees must look for information and data on each software system to retrieve and compare data. The specificity of the data of each transport infrastructure project is that the data is very large and has many different formats; the information is updated regularly every year according to the maintenance, renovation, and upgrading process, etc. Traditional storage and data representation, like how database management systems and management software are used, will not meet the demand. In this paper, we propose a solution to build a centralized specialized database, have a specific organizational plan according to the specific characteristics of the industry, and be able to integrate data from specialized applications to connect and unify data between authorities. This will be a platform for sharing and exploiting data for professional management between authorities in the city and the whole country. The people and state management agencies highly appreciate this solution, which has been researched and implemented experimentally in Danang City.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116024791","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":"SMART CONTRACT IMPLEMENTATION USING BLOCKCHAIN IOV FOR VEHICLE ACCIDENT INVESTIGATION","authors":"Gulfam Ahmad, Mariam Fareed","doi":"10.32010/26166127.2023.6.1.77.90","DOIUrl":"https://doi.org/10.32010/26166127.2023.6.1.77.90","url":null,"abstract":"Recent advancements in digital accident forensics, a conceptual evidence management paradigm developed using smart contracts and interplanetary file system in iov. This paper comprehensively summarizes the Smart contract implementation blockchain framework for vehicle accident investigation in IoV. We investigate comparing some review papers to find the classification of the smart contract. Using blockchain, evidence management provides an immutable and auditable method for investigating and resolving accident cases. Precisely we first investigate the security and privacy threats; therefore, Smart contracts provide effective access control for proof data and reports. On both the public and private Ethereum blockchains, the cost of setting up and executing transactions using smart contracts is assessed. However, we utilized the Inter Planetary File System most efficiently while minimizing memory and execution costs. Finally, we draw open research directions for building future digital-proof management.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129360197","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":"DIRECT MODEL REFERENCE TAKAGI–SUGENO FUZZY CONTROL OF SISO NONLINEAR SYSTEMS DESIGN BY MEMBERSHIP FUNCTION","authors":"F. Hosseini, Meshkat Sadat Hosseini","doi":"10.32010/26166127.2023.6.1.19.29","DOIUrl":"https://doi.org/10.32010/26166127.2023.6.1.19.29","url":null,"abstract":"What is discussed in this article is to find a way for membership functions optimally. In most scholars, these functions are constant and have a limited number. Therefore, in some cases, this limitation reduces control performance improvement. One of the best solutions is finding these functions in a differential form. This article used the Takagi-Sugeno function as a fuzzy detector to identify and control a nonlinear SISO system by direct adaptive reference model control. Using this method with Lyapunov for the stability of the control system makes output fuzzy linguistic variables optimally. Then simultaneously using these values, membership functions can be defined in differential form. Therefore, there is no other limitation in the variance and midpoint.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125714803","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":"TRAFFIC FLOW PREDICTION BASED ON VANET DATA BY COMBINING ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM","authors":"Sara Tavasolian, M. Afzali","doi":"10.32010/26166127.2023.6.1.91.112","DOIUrl":"https://doi.org/10.32010/26166127.2023.6.1.91.112","url":null,"abstract":"In many developing countries, predicting traffic flow is one of the solutions to prevent congestion on highways and routes, and the intelligent transportation system is considered one of the solutions to problems related to transportation and traffic. Knowledge of the predicted situation for traffic flow is essential in traffic management and informing passengers. This research presents a short-term intelligent transportation traffic flow forecasting model, which first examines how traffic forecasting can improve the performance of intelligent transportation system applications. Then the method and basic concepts of traffic flow forecasting are introduced, and the two main categories of forecasting, statistical models and machine learning-based forecasting methods (supervised and unsupervised) are discussed. Finally, a method based on machine learning using a genetic algorithm is Presented. The prediction was used as a powerful method for the mathematical modeling of traffic data in the proposed genetic algorithm method to select important traffic data features and neural networks for classification. The simulation and results presented in this research show a 3 percent improvement in traffic flow prediction with the proposed method, which uses SVM as a classifier in the primary method, and the simulation of this method has output a value of 93.6, But the suggested method has an output of 96.6","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125496411","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":"PROVIDE A MODEL BASED SENTIMENT ANALYSIS SYSTEM FOR SALES PREDICTION IN MARKETING ACCORDING TO THE AGA-LSTM NEURAL NETWORK MODEL","authors":"Shiva Babaei, Mohammad Tahghighi Sharabyan, Akbar Babaei, Zahra Tayyebi Qasabeh","doi":"10.32010/26166127.2023.6.1.30.48","DOIUrl":"https://doi.org/10.32010/26166127.2023.6.1.30.48","url":null,"abstract":"Data is today's most powerful tool; valuable facts and information can be determined by analyzing them using appropriate techniques and algorithms. Also, the rapid increase in access to Internet technology to a large mass of people worldwide has increased the importance of analyzing data generated on the web much more than before. The preceding discussion of this research is sales forecasting in marketing, which is very important in this topic. Marketing is a tool through which people's standard of living is developed, which is done before and after the sale. This research presents a model based on a dynamic analysis system for forecasting marketing sales based on the AGA-LSTM neural network model. It is challenging to recognize emotions in natural language, even for humans, and automatic recognition makes it more complicated. This research presents a hybrid deep-learning model for accurate sentiment prediction in real-time multimodal data. In the proposed method, the work process is such that after extracting emotional data from social networks, they are pre-processed and prepared for pattern discovery. The data is evaluated in the adaptive genetic algorithm, and the pattern is discovered in the designed neural network, and this pattern is discovered after discovery. The cornerstone of sales policies is improved. The adaptive genetic algorithm was used to optimize the parameters of the LSTM model, and the model can predict the types of goods and the total volume of online retail sales. In the simulation of the proposed method, in 3000 rounds of training, an accuracy of 76 has been achieved, which is an improvement of 11% compared to the primary method.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126931621","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":"A UNIFIED PARADIGM OF CLASSIFYING GI TRACT DISEASES IN ENDOSCOPY IMAGES USING MULTIPLE FEATURES FUSION","authors":"Muhammad Afraz, Abdul Haseeb, Abdul Muiz Fayyaz","doi":"10.32010/26166127.2023.6.1.49.76","DOIUrl":"https://doi.org/10.32010/26166127.2023.6.1.49.76","url":null,"abstract":"The automatic identification of Gastrointestinal (GI) tract diseases in endoscopy images has been associated with the domain of medical imaging and computer vision. Its classification has various challenges, including color, low contrast, lesion shape, and complex background. A Deep features-based method for the classification of gastrointestinal disease is implemented in this article. The method suggested involves four significant steps: preprocessing, extraction of handcrafted, and deep Convolutional neural network features (Deep CNN), selection of solid features, fusion, and classification. 3D-Median filtering in the preprocessing stage increases the lesion contrast. The second stage extracts the features centered on the shape. The extracted features are of three types: HOG features, ResNet50, and Xception. Principal Component Analysis (PCA) is chosen to select extracted features, combined by concatenating them in a single array. A support vector system eventually categorizes fused features into multiple classes. The Kvasir dataset is used for the proposed model. The SVM has outstanding efficiency reached 96.6 percent, showing the proposed system's robustness","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115720698","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":"RESOURCE DISCOVERY IN DISTRIBUTED EXASCALE SYSTEMS USING A MULTI-AGENT MODEL: CATEGORIZATION OF AGENTS BASED ON THEIR CHARACTERISTICS","authors":"Fakhraddin Abdullayev","doi":"10.32010/26166127.2023.6.1.113.120","DOIUrl":"https://doi.org/10.32010/26166127.2023.6.1.113.120","url":null,"abstract":"Resource discovery is a crucial component in high-performance computing (HPC) systems. This paper presents a multi-agent model for resource discovery in distributed exascale systems. Agents are categorized based on resource types and behavior-specific characteristics. The model enables efficient identification and acquisition of memory, process, file, and IO resources. Through a comprehensive exploration, we highlight the potential of our approach in addressing resource discovery challenges in exascale computing systems, paving the way for optimized resource utilization and enhanced system performance.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125992335","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":"A REVIEW SIOT (SOCIAL INTERNET OF THINGS): TECHNIQUES, APPLICATIONS, CHALLENGES AND TRENDS","authors":"Lida Naderlou, N. Ismayilova, Azar Feyziyev","doi":"10.32010/26166127.2022.5.2.236.253","DOIUrl":"https://doi.org/10.32010/26166127.2022.5.2.236.253","url":null,"abstract":"The social or human actions in the IoT platform derive the new paradigm in the IoT environment called the Social Internet of Things (SIoT). The Social Internet of Things is that part of an IoT capable of establishing social relationships with other objects concerning humans. SIoT attempts to moderate IoT challenges in scalability, trust, and resource discovery by taking a cue from social computing. In the IoT family, there is a subset of SIoT, a relatively recent concept. Moreover, a method of integrating IoT with social networking. SIoT is a simulation of human-to-human and object-to-object social networks where Humans are called intellectual and relational objects. They build their social network to accomplish shared objectives such as enhancing accessibility, success, and productivity and providing their needed services. This paper has extensively surveyed the SIoT (social Internet of things) for beginners involved in SIoT Studies. This paper gives you a clear view and ideas about SIoT's architecture, relationships, trust management, and applications and challenges implemented related to SIoT.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125426211","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":"INTRODUCING A NEW MODEL FOR LOCATING THE LOCATION OF FIREFIGHTING FORCES BASED ON FUZZY REGION AND NONDOMINATED SORTING GENETIC ALGORITHM","authors":"Saeed Hassani, Mohammad Tahghighi Sharabyan, Zahra Tayyebi Qasabeh","doi":"10.32010/26166127.2022.5.2.193.211","DOIUrl":"https://doi.org/10.32010/26166127.2022.5.2.193.211","url":null,"abstract":"The establishment of fire stations is considered an essential part of the security of any city. At the time of an accident, the location of fire stations is essential for timely and quick relief. The delay in providing aid causes irreparable damage to the life and property of the city's people, and the correct location of fire stations can prevent such incidents from happening, which is necessary to achieve this goal. It is systematic and integrated based on a suitable model. Therefore, in this research, a suitable model for locating the position of firefighting forces based on fuzzy logic and mutated genetic algorithm is proposed, which has two objective functions: one for optimizing the urban coverage and the other for optimizing Building the number of fires stations. The goal is to deploy stations in such a way as to create maximum urban coverage, and on the other hand, considering the cost of deploying each station, the method seeks to reduce the number of stations. The criteria needed for the stations' location have been examined, including the distance from the existing fire station. S the distance from the areas at risk of earthquakes, the high population density, the density of wooden buildings, the proximity to the roads—the main and density of hazardous materials facilities., the data set of fire stations in Istanbul city was used, to check the results and simulation in this research. This data set contains two parts, one of which contains information about the location of the stations, which has 124 data, and the other contains related information to the areas where the fire occurred and has 107 data. In this research, five scenarios were set, the first scenario of two parameters, the second scenario of three parameters, the third, fourth, and fifth scenarios of four parameters and their influence on the choice of the parent were investigated, and the results showed that the best solution is It is obtained that both goals have the same weight in the scenarios. It happens when the number of stations reaches the desired level. In fact, by increasing the number of stations to the appropriate size, the urban coverage amount reached the desired results.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126684240","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}