International Journal of Applied Systemic Studies (16 papers in press)

Regular Issues

• Fault-tolerant control method of fuzzy logic system based on decision tree algorithm
  by Wei Zhao, Feng Gao 
  Abstract: In order to improve the reconstruction effect of fault parameters in fault tolerant control process, a fuzzy logic system fault tolerant control method based on decision tree algorithm is proposed. The linear model of the system is constructed by decision tree algorithm, and the fault model is constructed by adding fault cases. Then the system fault is detected and the influence of different fault parameters on the system is judged. After designing the fault-tolerant controller of the system, the cooperative variable is used to compensate the fault parameters until the output value of the system is restored to the normal condition, so as to complete the fault-tolerant control. Experimental results show that the reconstruction curve of fault current is more consistent with the theoretical value, which proves that the method improves the accuracy of the reconstruction value of fault parameters and makes the system run more stably.
  Keywords: decision tree algorithm; fuzzy logic system; fault tolerant control; cooperative variable; parameter compensation.
  
  
• Fault-tolerant control method of fuzzy logic System based on decision tree algorithm  
  by Wei Zhao, Feng Gao 
  Abstract: In order to improve the reconstruction effect of fault parameters in fault tolerant control process, a fuzzy logic system fault tolerant control method based on decision tree algorithm is proposed. The linear model of the system is constructed by decision tree algorithm, and the fault model is constructed by adding fault cases. Then the system fault is detected and the influence of different fault parameters on the system is judged. After designing the fault-tolerant controller of the system, the cooperative variable is used to compensate the fault parameters until the output value of the system is restored to the normal condition, so as to complete the fault-tolerant control. Experimental results show that the reconstruction curve of fault current is more consistent with the theoretical value, which proves that the method improves the accuracy of the reconstruction value of fault parameters and makes the system run more stably.
  Keywords: decision tree algorithm; fuzzy logic system; fault tolerant control; cooperative variable; parameter compensation.
  DOI: 10.1504/IJASS.2021.10047080
   
  
• Key barriers in the growth of engineering education in the context of Chhattisgarh state: a Fuzzy Kano and TISM integrated approach  
  by NAVEEN JAIN, Prateek Sharma, Bhagwaticharan Patel 
  Abstract: Today, countries depend on knowledge-driven innovation for economic growth which depends on the quality of the engineering education system and management. In India, the All India Council for Technical Education is the flag bearer of planning, formulation, and dissemination of technical education in the country. Since 20122013, there is a drastic decline in admissions in engineering courses across the country. Hence, there is a need to identify the barriers that dominate engineering education and hinder the students from opting for engineering as a career option. The proposed work focuses on determining the key barriers to the growth of technical education in the state of Chhattisgarh by an integrated fuzzy Kano model and total interpretive structural modelling approach. The result of the study will provide deeper insight and a better understanding of the higher engineering scenario in the state and will help decision-makers to take constructive and progressive steps to improve the engineering education scenario.
  Keywords: Kano model; total interpretive structural modelling; TISM; fuzzy Kano; engineering education management; key barriers; interpretive structural modelling; ISM; technical education; critical failure factors; CFFs; reachability matrix; HEI; digraph.
  DOI: 10.1504/IJASS.2023.10047241
   
  
• An e-commerce logistics service customer relationship management system based on RFM model  
  by Fei Tang 
  Abstract: In order to solve the problems of traditional customer relationship management system of e-commerce logistics service, such as high transmission error, long running time and high packet loss rate, a customer relationship management system of e-commerce logistics service based on RFM model is proposed. This system mainly combines RFM model, dynamically displays all contour states of customer consumption behaviour from three aspects of purchase time, frequency and quantity, and obtains user classification rule table. The experimental results show that the transmission error of this system is 0.15%, the system running time is 0.1 s, and the packet loss rate is about 0.06, which is better than the comparison system and has great research value.
  Keywords: RFM model; e-commerce; logistics service; customer relationship management; CRM.
  DOI: 10.1504/IJASS.2023.10048596
   
  
• An enterprise financial data leakage risk prediction based on ARIMA-SVM combination model.  
  by Qian Cao 
  Abstract: Aiming at the problems of low prediction accuracy and long prediction time in traditional methods, an enterprise financial data leakage risk prediction method based on ARIMA-SVM combination model is proposed. According to the financial data security risks existing at all levels of the enterprise, build the enterprise financial data leakage risk prediction index system and obtain the prediction indexes, including the two first-class indexes of application security and system security, the second-class indexes such as foreign cooperation security, and the third-class indexes such as the identification of sensitive data. Empirical mode decomposition is used to remove the noise data of prediction index, and the data after noise removal is input into ARIMA-SVM combination model, and the output of the model is the prediction result of data leakage risk. The simulation results show that the prediction accuracy of the proposed method is between 95%~100%, and the prediction time is within 16 s.
  Keywords: ARIMA-SVM combined model; enterprise financial data; risk of leakage; empirical mode decomposition method.
  DOI: 10.1504/IJASS.2023.10048600
   
  
• Reliability Analysis of the Financial Management Auxiliary System of Remote Branches Based on Cloud Computing  
  by Suhong Bi 
  Abstract: Aiming at the problem of low system reliability caused by poor recoverability and robustness of traditional remote branch financial management system nodes, a reliability analysis of remote branch financial management auxiliary system based on cloud computing is proposed. J2EE cross platform architecture is adopted to store a large amount of unstructured data in the cloud platform, and classify, retrieve and access control the data. The self immune recovery algorithm of fault data nodes based on cloud computing technology is used to calculate the delayed recovery degree of nodes, so as to improve the reliability of financial management auxiliary system. After experimental analysis, the system recovers nine fault nodes, which is highly consistent with the distribution of standard samples, and the robustness of the system remains above 95%. It can be seen that the financial management auxiliary function of the system designed in this paper has good reliability.
  Keywords: cloud computing; convolution function; financial management; self-immune recovery; failure node; reliability.
  DOI: 10.1504/IJASS.2023.10049015
   
  
• SYSTEMATIC ANALYIS OF AN UNRELIABLE BATCH SERVICE RETRIAL QUEUEING SYSTEM WITH TWO SORT OF VACATION  
  by NIRANJAN S.P, NIRANJAN S.P, INDHIRA K, INDHIRA K, CHANDRASEKARAN V. M, CHANDRASEKARAN V. M 
  Abstract: This paper concentrates on bulk arrival and batch service retrial queueing system with server failure, two types of vacation and constant retrial rate. If an arrival of customers finds a server is free then batch service will be provided with minimum of one customers and maximum of b customers. On the contrary, if the arrival of customers finds the server is busy then entire customers will join in the orbit to explore service again. After service completion, if there are no customers in the orbit then the server leaves for working vacation. During working vacation, the server provides service in lower service rate compared to regular service rate. In the working vacation completion, if the orbit size is zero then the server leaves for non-working vacation. The server may get failure in working period. If the server got failure with probability () then the renewal of service station will be considered. On the other hand, if there is no breakdown and orbit is empty then the server leaves for working vacation with probability (1 ). For this designed queueing model probability generating function of the orbit size will be obtained. Various performance measures are also be derived with suitable numerical illustrations.
  Keywords: working vacation; non-working vacation; constant retrial rate; renewal time.
  DOI: 10.1504/IJASS.2022.10053876
   
  
• Design of enterprise financial information fusion and sharing system based on blockchain technology  
  by Li Zhang  
  Abstract: Aiming at the problems of large information fusion error and low sharing efficiency in the existing information fusion and sharing system, this paper designs a new enterprise financial information fusion and sharing system based on blockchain technology. The hardware part of the system uses the central controller containing ARM STM32F411 chip to upload the obtained financial information, and control the execution command, control program and so on. The software includes three modules of data collection, fusion and sharing. It mainly completes the cross-domain authentication of financial information by setting up the blockchain authorisation centre, so as to build the trust model of financial information sharing. The experiment shows that the system has a low error of financial information fusion, and effectively improves the efficiency of financial information sharing and the accuracy of data authentication.
  Keywords: blockchain technology; information fusion and sharing; central controller; authorisation centre; cross-domain authentication.
  DOI: 10.1504/IJASS.2023.10049955
   
  
• Study on Product configuration of touch human computer interaction based on feedback control  
  by Gangling Liu 
  Abstract: In order to solve the problems of long configuration time, low configuration accuracy and high energy consumption in the configuration process of traditional configuration system, a touch human-computer interactive product configuration system based on feedback control is designed. Based on the existing system hardware configuration, the system software is designed. According to the feedback control principle, the proportional integral controller is used to establish the feedback control model, and the results of feedback control variables are calculated. Based on the calculation results of feedback control variables, a human-computer interaction product configuration perception model is established. The experimental results show that the system configuration process takes an average of 6.8 s, the configuration accuracy is always more than 90%, and the minimum energy consumption is 76.18 dB, which fully proves the effectiveness of the touch human-computer interaction product configuration system based on feedback control.
  Keywords: touch-based human-computer interaction products; product configuration; feedback control; component class; attribute characteristics.
  DOI: 10.1504/IJASS.2023.10050001
   
  
• Early warning of financial statement data leakage risk based on grey fuzzy comprehensive evaluation  
  by Shanshan Li, Dannan Lin 
  Abstract: In order to improve the low accuracy of risk identification and early warning success rate of traditional data leakage risk early warning methods, this paper proposes a financial statement data leakage risk early warning method based on grey fuzzy comprehensive evaluation. Firstly, the grey fuzzy matrix and the set of risk identification factors are constructed. Secondly, according to the factor set constructed above, calculate the weight of each factor, and accurately identify the risk of data leakage of financial statements by using grey fuzzy comprehensive evaluation method. Finally, the least squares support vector mechanism is used to build the financial data report data leakage risk early warning function, and the output result of the early warning function is the early warning result. The experimental results show that the risk identification accuracy of this method is high, and the average success rate of early warning is 99.07%.
  Keywords: grey fuzzy comprehensive evaluation; financial statement data; leakage risk warning.
  DOI: 10.1504/IJASS.2023.10050058
   
  
• A Multi-layer distributed power material allocation system based on intelligent optimal scheduling model  
  by Yong Deng 
  Abstract: The traditional power material allocation system has the problems of long material distribution path and long material scheduling time. Therefore, a multi-layer distributed power material allocation system based on intelligent optimisation scheduling model is designed. In the hardware part, the material allocation decision-making module, scheduling data storage module, material transportation risk measurement module and material allocation path information acquisition module are designed. In the software part, the minimisation of material allocation time and the shortest transportation path are determined as the objective function, the intelligent optimisation scheduling model is established, and the genetic algorithm is used to solve the model to complete the power material allocation. The test results show that the deployment effect of this system is better and the deployment path is shorter, which is about 4 km shorter than the traditional method.
  Keywords: intelligent optimisation scheduling model; material allocation; risk measurement; genetic algorithm.
  DOI: 10.1504/IJASS.2023.10050120
   
  
• Predicting Code Beauty with Machine Learning Model  
  by Ermira Daka 
  Abstract: Software maintenance is one of the most expensive phases of the software development life cycle. This cost increases more when maintenance is performed on poorly written code. There exist a set of code writing patterns that developers need to follow to write good looking code. However, coding that conforms to rules is not always possible. During software evolution, code goes through different changes, which are the main reasons for breaking the rules of beautiful code. In this paper, we propose a machine learning (ML)-based model which will measure the beauty of a written code. The model built on a set of ten code-based features is learned using logic regression algorithm and is able to predict how beautiful is given peace of code. Furthermore, the model is evaluated using an empirical study, which shows that it has a moderate agreement with developers about the beauty of the code.
  Keywords: machine learning; code beauty; software maintenance.
  DOI: 10.1504/IJASS.2023.10050940
   
  
• The design of library resource personalized recommendation system based on deep belief network  
  by Min Fu 
  Abstract: Aiming at the problems of low accuracy and user satisfaction of traditional library resource recommendation system, this paper designs a library resource personalised recommendation system based on deep belief network. Firstly, the architecture of library resource personalised recommendation system is designed and real-time recommendation module is added. For the real-time recommendation module, the probability function of the best resource in the deep belief network is obtained by combining several limited Boltzmann machines and maximum likelihood principles. The bias value and weight of the visible layer and the hidden layer of the deep belief network are corrected by the contrast divergence method to make the recommendation result more accurate. The experimental results show that the recommendation accuracy of the system can reach more than 97%, the recall rate can reach 92.5%, and the user satisfaction is more than 94.8%, indicating that the system has effectively improved the recommendation effect.
  Keywords: deep belief network; limit Boltzmann machine; parameter modification; library resources; personalised recommendation.
  DOI: 10.1504/IJASS.2023.10052277
   
  
• Response of Singly Reinforced Square Concrete Slab with Varying Standard Concrete Strength and Slab Thickness under Concentric Impact Loading: A Numerical Study  
  by S.M. Anas, Mehtab Alam, Faris A. Uriyar 
  Abstract: Damage evaluation and performance enhancement of the structures due to ever-rising malicious sporadic explosions, vehicular collisions, aircraft crashing, falling construction equipment, and rock/boulder impact from landslips are of considerable concern and thus generate sufficient interest to structural engineers and researchers. In this study, a square RC slab of normal strength concrete (30 MPa) provided with tension steel (0.88%) is modelled in ABAQUS/Explicit software and its investigation has been carried out under impact loading. Following validation, analysis is extended to study the effect of design parameters like slab thickness and concrete strength on the impact response of the slab without altering the cover concrete, percentage and yield strength of the reinforcing steel. Results show that higher-strength concrete in the slab marginally reduces the punching of the slab but enhances the flexural damage. Higher thickness of slab reduces concrete perforation but results in more cracking owing to a decrease in the steel percentage.
  Keywords: impact loading; low-velocity impact; RC slabs; concrete strength; slab thickness; dynamic analysis; damage; ABAQUS/Explicit.
  DOI: 10.1504/IJASS.2023.10053043
   
  
• Risk Investment Heuristics: Applied Systemic Review  
  by Diego Ozorio, Leandro Ferreira Pereira, Rui Gonçalves, Álvaro Dias, Renato Lopes Da Costa 
  Abstract: Investments in projects are judged with rational mathematical parameters. Risky projects can build or destroy companies, careers and fortunes. Being able to fully rationalise the intelligence of the investment judgement seems unlikely. To a greater or lesser extent, cognition interferes with the judges preference. But would it be possible to identify cognitive traits of the judges intelligence when deciding on corporate investments? The article makes a systemic literature review of the field on the judgement of corporate investments. The revision suggests that there are gaps in theories about the judgement of corporate investments, which should be solved.
  Keywords: heuristics; bias; judgement; risk; investments.
  DOI: 10.1504/IJASS.2023.10054294
   
  
• Citizen’s risk perception in crises: A systemic approach to reducing social vulnerability in the prefecture of Attica, Greece  
  by Ioannis Drakos, Gregory Chondrokoukis 
  Abstract: Over the last decades, a series of unexpected catastrophic events, from the Islamic terrorist attacks, the coronavirus disease (COVID-19), to natural disasters due to extreme weather events that hit the European Union, made it clear that risk is an integral part of peoples everyday lives. Given that, in most cases, the Hellenic state and local authorities responsible for the discovery and recovery of the citizens affected by these catastrophic and fatal events do not seem to be able to react. Therefore the occupants have to take their fate into their own hands. Furthermore, the demographic, the social, the economic, and the environmental inequalities significantly increase the social vulnerability of a significant proportion of citizens who, due to the difficulty of state authorities to respond to their particularities, when an incident crisis occurs, easily understand that their chances of survival will decline significantly. This paper proposes an innovation to manage such situations.
  Keywords: risk; hazard; vulnerability; risk perception; position finding; discovery; recovery; Greece.
  DOI: 10.1504/IJASS.2023.10054504