: Agriculture is an art, a craftsmanship and a scientific way of cultivation, growth and maintenance of edible crops and livestock. Majority of the current farming communities do not have prior knowledge of predicting the suitable crop for their soil and climatic conditions. Difficulty in raising the initial investment for crop cultivation is also one of the serious concerns of these communities. The difficulties faced by the civic agriculture, the insecure monetary transactions, along with the concerns related to the financial process have been identified and listed. The paper proposes a feasible solution by predicting the appropriate crops that could be grown in a specific scenario or environmental conditions using the machine-learning model of Support Vector Classifier and provides data related to quality yields using Fuzzy Decision Merkle Tree (FDMT) Regressor. Additionally, a transparent and secure fund transfer mechanism is provided using Ethereum blockchain-based technology. The proposed model implements a secured, translucent and tamper-resistant digital platform for the farming communities to host their products. A fortified consensus can be formed between the farmer and the investor bounded with a rating mechanism to build the credibility of both the farmer and the investor 7 based on the prior knowledge obtained in the Agri-market.
{"title":"Decentralised and Predictive System for Efficient Agri-Transactions Through Blockchain Technology","authors":"Remegius Praveen Sahayaraj, Muthurajkumar Sannasy","doi":"10.24846/v31i3y202212","DOIUrl":"https://doi.org/10.24846/v31i3y202212","url":null,"abstract":": Agriculture is an art, a craftsmanship and a scientific way of cultivation, growth and maintenance of edible crops and livestock. Majority of the current farming communities do not have prior knowledge of predicting the suitable crop for their soil and climatic conditions. Difficulty in raising the initial investment for crop cultivation is also one of the serious concerns of these communities. The difficulties faced by the civic agriculture, the insecure monetary transactions, along with the concerns related to the financial process have been identified and listed. The paper proposes a feasible solution by predicting the appropriate crops that could be grown in a specific scenario or environmental conditions using the machine-learning model of Support Vector Classifier and provides data related to quality yields using Fuzzy Decision Merkle Tree (FDMT) Regressor. Additionally, a transparent and secure fund transfer mechanism is provided using Ethereum blockchain-based technology. The proposed model implements a secured, translucent and tamper-resistant digital platform for the farming communities to host their products. A fortified consensus can be formed between the farmer and the investor bounded with a rating mechanism to build the credibility of both the farmer and the investor 7 based on the prior knowledge obtained in the Agri-market.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44611406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: This paper deals with the design and development of the B2S4B platform that bridges Smart City ecosystems (the business world) and city sensors: the IoT and citizens (the IoT and the social worlds). This platform allows the reconfiguration of Smart City business processes (BPs) based on the detected events and knowledge derived over time. In support of this, the concept of Smart City Observers (SCO) was introduced which acts as a man-in-a-middle between BPs, and the IoT and the social worlds by defining what should be monitored and how the respective observations could impact these worlds. In its turn, B2S4B analyses the detected events from all active SCOs and based on the predefined knowledge allows the synchronized reconfiguration of a BP and of the city sensors that feed the SCOs with accurate information. This paper proposes an approach for manual and automatic adaptation of Smart City BPs based on events reported by SCOs. In order to demonstrate the usability and effectiveness of the proposed approach this paper illustrates how this platform could be used in a case study on Smart City traffic control.
{"title":"B2S4B: A Platform for Smart City Business Processes Management and Adaptation","authors":"E. Ugljanin, D. Stojanović, E. Kajan, Z. Maamar","doi":"10.24846/v31i3y202207","DOIUrl":"https://doi.org/10.24846/v31i3y202207","url":null,"abstract":": This paper deals with the design and development of the B2S4B platform that bridges Smart City ecosystems (the business world) and city sensors: the IoT and citizens (the IoT and the social worlds). This platform allows the reconfiguration of Smart City business processes (BPs) based on the detected events and knowledge derived over time. In support of this, the concept of Smart City Observers (SCO) was introduced which acts as a man-in-a-middle between BPs, and the IoT and the social worlds by defining what should be monitored and how the respective observations could impact these worlds. In its turn, B2S4B analyses the detected events from all active SCOs and based on the predefined knowledge allows the synchronized reconfiguration of a BP and of the city sensors that feed the SCOs with accurate information. This paper proposes an approach for manual and automatic adaptation of Smart City BPs based on events reported by SCOs. In order to demonstrate the usability and effectiveness of the proposed approach this paper illustrates how this platform could be used in a case study on Smart City traffic control.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42668266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Alaoui, Obaid S. Alshammari, Abdelhamid IRATNI, A. Hafaifa, H. Jerbi
: The outstanding performance of modern gas turbine power plants requires an efficient and robust control strategy in order to recover the losses caused by the undesirable effects and the instabilities related to their operation. Also, these losses can be the cause of their unstable dynamic behaviour during full-load and partial load operation in the unplanned shutdown state. Hence, choosing the right control strategy can improve the operation of this type of machine by increasing its efficiency by up to 60%. This paper proposes the implementation of an innovative control strategy based on a generalized predictive adaptive control algorithm for monitoring the rotation speed of a Solar Titan 130 gas turbine, with the purpose of considering the constraints related to the nonlinear behavior of a turbine during large variations in machine load. The aim is to automatically adjust the parameters of the regulator of the turbine’s control loop in real time, with a recursive estimation of these parameters. Using the experimental input/output measurements in order to study its behavior, by integrating the predictive control estimators, ensures the superior performance of the analyzed gas turbine in terms of energy, efficiency and robustness regarding the parametric uncertainties and the variation of the turbine load.
{"title":"Gas Turbine Speed Monitoring Using a Generalized Predictive Adaptive Control Algorithm","authors":"M. Alaoui, Obaid S. Alshammari, Abdelhamid IRATNI, A. Hafaifa, H. Jerbi","doi":"10.24846/v31i3y202208","DOIUrl":"https://doi.org/10.24846/v31i3y202208","url":null,"abstract":": The outstanding performance of modern gas turbine power plants requires an efficient and robust control strategy in order to recover the losses caused by the undesirable effects and the instabilities related to their operation. Also, these losses can be the cause of their unstable dynamic behaviour during full-load and partial load operation in the unplanned shutdown state. Hence, choosing the right control strategy can improve the operation of this type of machine by increasing its efficiency by up to 60%. This paper proposes the implementation of an innovative control strategy based on a generalized predictive adaptive control algorithm for monitoring the rotation speed of a Solar Titan 130 gas turbine, with the purpose of considering the constraints related to the nonlinear behavior of a turbine during large variations in machine load. The aim is to automatically adjust the parameters of the regulator of the turbine’s control loop in real time, with a recursive estimation of these parameters. Using the experimental input/output measurements in order to study its behavior, by integrating the predictive control estimators, ensures the superior performance of the analyzed gas turbine in terms of energy, efficiency and robustness regarding the parametric uncertainties and the variation of the turbine load.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42909666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Inventory optimization is a significant problem that is tied directly to financial gains. Its complexity has led to the development of new inventory models and optimization techniques. Evolutionary algorithms, particularly Pareto based evolutionary algorithms have been proven to be reliable for solving such problems. However, these evolutionary algorithms concentrate mostly on global search and have limited local search abilities. This leads to a poor convergence to the Pareto front. Among these algorithms the most studied are non-dominated sorting genetic algorithm-II and strength Pareto evolutionary algorithm2. This paper proposes a novel method that increases their convergence. The novelty is based on three techniques: Firstly, a time-based fitness assignment that favours solutions from previous generations is employed. Secondly, before the crossover process, the mating pool is updated with a positive bias towards better solutions. Finally, a more disruptive mutation scheme is used to prevent premature convergence. The novel algorithms were tested on a benchmark problem suite and two inventory problems. The performance of the algorithms is measured using hypervolume, generational distance and spacing metrics. The results illustrated by graphics indicate that the novel algorithms can obtain better convergence without increasing the time complexity.
{"title":"Novel NSGA-II and SPEA2 Algorithms for Bi-Objective Inventory Optimization","authors":"I. Huseyinov, A. Bayrakdar","doi":"10.24846/v31i3y202203","DOIUrl":"https://doi.org/10.24846/v31i3y202203","url":null,"abstract":": Inventory optimization is a significant problem that is tied directly to financial gains. Its complexity has led to the development of new inventory models and optimization techniques. Evolutionary algorithms, particularly Pareto based evolutionary algorithms have been proven to be reliable for solving such problems. However, these evolutionary algorithms concentrate mostly on global search and have limited local search abilities. This leads to a poor convergence to the Pareto front. Among these algorithms the most studied are non-dominated sorting genetic algorithm-II and strength Pareto evolutionary algorithm2. This paper proposes a novel method that increases their convergence. The novelty is based on three techniques: Firstly, a time-based fitness assignment that favours solutions from previous generations is employed. Secondly, before the crossover process, the mating pool is updated with a positive bias towards better solutions. Finally, a more disruptive mutation scheme is used to prevent premature convergence. The novel algorithms were tested on a benchmark problem suite and two inventory problems. The performance of the algorithms is measured using hypervolume, generational distance and spacing metrics. The results illustrated by graphics indicate that the novel algorithms can obtain better convergence without increasing the time complexity.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49588627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alin Zamfiroiu, R. Sharma, Diana Constantinescu, Madalina Pana, C. Toma
: Online education is one of the fastest emerging markets globally. There is a variety of tools, technologies and platforms, which augment learning in the online environments. Moodle and Sakai are probably the most popular open-source learning management systems (LMS) around the world, although there are alternative professional solutions such as TalentLMS or other platforms. Student interaction is one of the success factors of effective online teaching and learning. It is important to understand how students behave in an online environment. This provides good feedback to the syllabus developers and instructors, in order to examine what should be improved. The learning management systems provide a good way for analyzing learners’ behavior through log reports. The LMS records all kinds of interactions by all users. These data are processed using learning analytics, in order to obtain a good picture of the progress achieved by the students during the lectures and the laboratories and of the manner in which the professors manage the students’ learning curves. This paper explains the use of learning analytics in examining learners’ engagement, interaction and behavior in an online environment. The results revealed interesting findings on how the assessment should be organized, in order to find maximum learning attainment.
{"title":"Using Learning Analytics for Analyzing Students’ Behavior in Online Learning","authors":"Alin Zamfiroiu, R. Sharma, Diana Constantinescu, Madalina Pana, C. Toma","doi":"10.24846/v31i3y202206","DOIUrl":"https://doi.org/10.24846/v31i3y202206","url":null,"abstract":": Online education is one of the fastest emerging markets globally. There is a variety of tools, technologies and platforms, which augment learning in the online environments. Moodle and Sakai are probably the most popular open-source learning management systems (LMS) around the world, although there are alternative professional solutions such as TalentLMS or other platforms. Student interaction is one of the success factors of effective online teaching and learning. It is important to understand how students behave in an online environment. This provides good feedback to the syllabus developers and instructors, in order to examine what should be improved. The learning management systems provide a good way for analyzing learners’ behavior through log reports. The LMS records all kinds of interactions by all users. These data are processed using learning analytics, in order to obtain a good picture of the progress achieved by the students during the lectures and the laboratories and of the manner in which the professors manage the students’ learning curves. This paper explains the use of learning analytics in examining learners’ engagement, interaction and behavior in an online environment. The results revealed interesting findings on how the assessment should be organized, in order to find maximum learning attainment.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43321029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: This paper proposes the Generalized Regression Neural Network (GRNN) model based on information granularity and using MATLAB programming for short-term temperature prediction. In this respect, it focuses on the daily average temperature data for the months of July and August for a period of ten years (from 2006 to 2015) for the Jiuhua Mountain scenic spot of Chizhou, in the Anhui Province. The performance of the proposed method is compared with that of the Back Propagation (BP) neural network and with that of the Gauss function for data fitting. This method not only improves the accuracy of short-term prediction, but it also overcomes the disadvantage of inaccurate data fitting. It can slightly improve the effectiveness and practicability of short-term prediction, and it can more effectively analyze short-term data on the Internet.
{"title":"The Application of the Generalized Regression Neural Network Model Based on Information Granulation for Short-Term Temperature Prediction","authors":"Wang Weiwei, D. Hao","doi":"10.24846/v31i3y202205","DOIUrl":"https://doi.org/10.24846/v31i3y202205","url":null,"abstract":": This paper proposes the Generalized Regression Neural Network (GRNN) model based on information granularity and using MATLAB programming for short-term temperature prediction. In this respect, it focuses on the daily average temperature data for the months of July and August for a period of ten years (from 2006 to 2015) for the Jiuhua Mountain scenic spot of Chizhou, in the Anhui Province. The performance of the proposed method is compared with that of the Back Propagation (BP) neural network and with that of the Gauss function for data fitting. This method not only improves the accuracy of short-term prediction, but it also overcomes the disadvantage of inaccurate data fitting. It can slightly improve the effectiveness and practicability of short-term prediction, and it can more effectively analyze short-term data on the Internet.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43738185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shangbin Ning, Zhen-zhou Yuan, Zhenyu Han, Yang Yang
: Inefficient utilization of existing parking resources is the main cause of parking difficulties, especially in metropolises. Shared parking allocation based on the online parking reservation system (PRS) is an effective way to deal with the inefficient utilization since it increases available parking resources through sharing and avoids blind search through reservation and allocation. This study focuses on the dynamic shared parking allocation problem based on PRS. A meta-heuristic algorithm, namely Advanced and Adaptive Tabu Search (AATS), was designed to cope with the real-time updates of parking demands and shared parking space and to achieve good allocation effect and high allocation speed. The proposed algorithm is based on advanced initialization with multi-factor sequencing and on adaptive neighborhood generation with bi-operator competition. The results of a three-day district-level experiment show that AATS achieves an allocation effect close to the exact algorithm, while having a significant superiority in allocation speed. The proposed AATS is practical to deal with realistic parking problems.
{"title":"An Advanced and Adaptive Tabu Search Algorithm for Dynamic Shared Parking Reservation and Allocation","authors":"Shangbin Ning, Zhen-zhou Yuan, Zhenyu Han, Yang Yang","doi":"10.24846/v31i3y202209","DOIUrl":"https://doi.org/10.24846/v31i3y202209","url":null,"abstract":": Inefficient utilization of existing parking resources is the main cause of parking difficulties, especially in metropolises. Shared parking allocation based on the online parking reservation system (PRS) is an effective way to deal with the inefficient utilization since it increases available parking resources through sharing and avoids blind search through reservation and allocation. This study focuses on the dynamic shared parking allocation problem based on PRS. A meta-heuristic algorithm, namely Advanced and Adaptive Tabu Search (AATS), was designed to cope with the real-time updates of parking demands and shared parking space and to achieve good allocation effect and high allocation speed. The proposed algorithm is based on advanced initialization with multi-factor sequencing and on adaptive neighborhood generation with bi-operator competition. The results of a three-day district-level experiment show that AATS achieves an allocation effect close to the exact algorithm, while having a significant superiority in allocation speed. The proposed AATS is practical to deal with realistic parking problems.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49513344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: In this paper, an equivalence theorem is given, that is, in a weighted graph, the maximum value of the minimum edge weights of all minimal edge cut sets between two points is equal to the minimum value of the maximum edge weights of all paths between the two points. On this basis, the recovery time between two points in the network is defined from the perspective of the minimal edge cut set and the path, respectively, and the equivalence of the two definitions is shown. Two models are established to optimize the partial recovery of network functions, by taking the damaged road network after the earthquake as the scene, based on the definition of the network recovery time and the total network time. Model 1 includes three objective functions, which are the sum of the failure levels between all pairs of the demand points and the facilities serving them, the total network time and the total cost. Different priorities were set for solving these three objectives. Since such a hierarchical model is not conducive to the optimization of the objective functions with lower priorities, model 1 is modified appropriately. The sum of the failure levels is combined with the total network time into an integrated objective function by weighting, and the minimization of this new function is taken as the highest-priority objective and the minimization of the total cost is taken as the secondary-priority objective, in order to achieve the balance between the sum of the failure levels and the total network time. Thus, model 2 is obtained. A case study is used to test the two models and verify their effectiveness.
{"title":"A Multi-objective Model for the Location of the Emergency Facilities and the Selection of the Rescue Path Based on the Restoration of the Damaged Edges","authors":"Yiying Wang, Zeshui Xu, F. Filip","doi":"10.24846/v31i3y202201","DOIUrl":"https://doi.org/10.24846/v31i3y202201","url":null,"abstract":": In this paper, an equivalence theorem is given, that is, in a weighted graph, the maximum value of the minimum edge weights of all minimal edge cut sets between two points is equal to the minimum value of the maximum edge weights of all paths between the two points. On this basis, the recovery time between two points in the network is defined from the perspective of the minimal edge cut set and the path, respectively, and the equivalence of the two definitions is shown. Two models are established to optimize the partial recovery of network functions, by taking the damaged road network after the earthquake as the scene, based on the definition of the network recovery time and the total network time. Model 1 includes three objective functions, which are the sum of the failure levels between all pairs of the demand points and the facilities serving them, the total network time and the total cost. Different priorities were set for solving these three objectives. Since such a hierarchical model is not conducive to the optimization of the objective functions with lower priorities, model 1 is modified appropriately. The sum of the failure levels is combined with the total network time into an integrated objective function by weighting, and the minimization of this new function is taken as the highest-priority objective and the minimization of the total cost is taken as the secondary-priority objective, in order to achieve the balance between the sum of the failure levels and the total network time. Thus, model 2 is obtained. A case study is used to test the two models and verify their effectiveness.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44808531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Salehi, F. Hosseinzadeh lotfi, Mohsen Rostamy Malkhalifeh
: One of the most attractive issues in Data Envelopment Analysis (DEA) is the evaluation of congestion of Decision Making Units (DMUs), which occurs if the decreases in certain inputs lead to increases in certain outputs without worsening any other input or output and equivalently, if the increases in certain inputs lead to decreases in certain outputs without improving any other input or output. Most of the existing approaches for detecting the congestion of DMUs in the literature on DEA employ the traditional definition of congestion and consider the situation in which the inputs and outputs can only change proportionally. This study proposes a method for recognizing the congestion of each input of a selected unit under evaluation for the case when the input and output of the respective unit can change disproportionally. The potential application of the proposed method is illustrated based on a dataset related to 16 institutes of basic research of the Chinese Academy of Sciences (CAS) for the year 2010, which was also reported in the literature.
{"title":"A New Method for Recognizing the Input Congestion in Data Envelopment Analysis","authors":"A. Salehi, F. Hosseinzadeh lotfi, Mohsen Rostamy Malkhalifeh","doi":"10.24846/v31i2y202202","DOIUrl":"https://doi.org/10.24846/v31i2y202202","url":null,"abstract":": One of the most attractive issues in Data Envelopment Analysis (DEA) is the evaluation of congestion of Decision Making Units (DMUs), which occurs if the decreases in certain inputs lead to increases in certain outputs without worsening any other input or output and equivalently, if the increases in certain inputs lead to decreases in certain outputs without improving any other input or output. Most of the existing approaches for detecting the congestion of DMUs in the literature on DEA employ the traditional definition of congestion and consider the situation in which the inputs and outputs can only change proportionally. This study proposes a method for recognizing the congestion of each input of a selected unit under evaluation for the case when the input and output of the respective unit can change disproportionally. The potential application of the proposed method is illustrated based on a dataset related to 16 institutes of basic research of the Chinese Academy of Sciences (CAS) for the year 2010, which was also reported in the literature.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45920380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: This paper presents the implementation of an integrated information system whose purpose is to ensure the management of activities within an organization. Such systems are successfully used in organizations, ensuring the automation of the organizational flow and the efficient and effective management of organizational resources. The architecture of such systems is offered for exploitation by recognized companies, under license. Specific to this system is the approach using open-source software tools, as well as the modularization of the application, which allows the independence of its installation from the existing platforms of the beneficiary. The obtained prototype is the result of a research project, carried out over a period of three years, with direct applicability to the beneficiary and the extension, subsequently, to other organizations. The beneficiaries of the system are public entities, which is why the design, development and implementation require specific conditions determined by the legislative and administrative constraints of the functioning framework of the governmental institutions.
{"title":"Integrated Information System for the Management of Activities in the Organization","authors":"A. Udroiu, Ionut Sandu, M. Dumitrache","doi":"10.24846/v31i2y202203","DOIUrl":"https://doi.org/10.24846/v31i2y202203","url":null,"abstract":": This paper presents the implementation of an integrated information system whose purpose is to ensure the management of activities within an organization. Such systems are successfully used in organizations, ensuring the automation of the organizational flow and the efficient and effective management of organizational resources. The architecture of such systems is offered for exploitation by recognized companies, under license. Specific to this system is the approach using open-source software tools, as well as the modularization of the application, which allows the independence of its installation from the existing platforms of the beneficiary. The obtained prototype is the result of a research project, carried out over a period of three years, with direct applicability to the beneficiary and the extension, subsequently, to other organizations. The beneficiaries of the system are public entities, which is why the design, development and implementation require specific conditions determined by the legislative and administrative constraints of the functioning framework of the governmental institutions.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44300370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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