Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.

Weighted Forwarding in Graph Convolution Networks for Recommendation Information Systems

Recommendation Information Systems(RIS)are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the Internet.Graph Convolution Network(GCN)algorithms have been employed to implement the RIS efficiently.However,the GCN algorithm faces limitations in terms of performance enhancement owing to the due to the embedding value-vanishing problem that occurs during the learning process.To address this issue,we propose a Weighted Forwarding method using the GCN(WF-GCN)algorithm.The proposed method involves multiplying the embedding results with different weights for each hop layer during graph learning.By applying the WF-GCN algorithm,which adjusts weights for each hop layer before forwarding to the next,nodes with many neighbors achieve higher embedding values.This approach facilitates the learning of more hop layers within the GCN framework.The efficacy of the WF-GCN was demonstrated through its application to various datasets.In the MovieLens dataset,the implementation of WF-GCN in LightGCN resulted in significant performance improvements,with recall and NDCG increasing by up to+163.64%and+132.04%,respectively.Similarly,in the Last.FM dataset,LightGCN using WF-GCN enhanced with WF-GCN showed substantial improvements,with the recall and NDCG metrics rising by up to+174.40%and+169.95%,respectively.Furthermore,the application of WF-GCN to Self-supervised Graph Learning(SGL)and Simple Graph Contrastive Learning(SimGCL)also demonstrated notable enhancements in both recall and NDCG across these datasets.

Evaluating and Addressing Interoperability Constraints in Health Information Systems for Enhanced Healthcare Delivery in Zimbabwe

Interoperability constraints in health information systems pose significant challenges to the seamless exchange and utilization of health data, hindering effective healthcare delivery. This paper aims to evaluate and address these constraints to enhance healthcare delivery. The study examines the current state of interoperability in health information systems, identifies the key constraints, and explores their impact on healthcare outcomes. Various approaches and strategies for addressing interoperability constraints are discussed, including the adoption of standardized data formats, implementation of interoperability frameworks, and establishment of robust data governance mechanisms. Furthermore, the study highlights the importance of stakeholder collaboration, policy development, and technical advancements in achieving enhanced interoperability. The findings emphasize the need for a comprehensive evaluation of interoperability constraints and the implementation of targeted interventions to promote seamless data exchange, improve care coordination, and enhance patient outcomes in healthcare settings.

Three-Way Behavioral Decision Making With Hesitant Fuzzy Information Systems:Survey and Challenges

Three-way decision(T-WD)theory is about thinking,problem solving,and computing in threes.Behavioral decision making(BDM)focuses on effective,cognitive,and social processes employed by humans for choosing the optimal object,of which prospect theory and regret theory are two widely used tools.The hesitant fuzzy set(HFS)captures a series of uncertainties when it is difficult to specify precise fuzzy membership grades.Guided by the principles of three-way decisions as thinking in threes and integrating these three topics together,this paper reviews and examines advances in three-way behavioral decision making(TW-BDM)with hesitant fuzzy information systems(HFIS)from the perspective of the past,present,and future.First,we provide a brief historical account of the three topics and present basic formulations.Second,we summarize the latest development trends and examine a number of basic issues,such as one-sidedness of reference points and subjective randomness for result values,and then report the results of a comparative analysis of existing methods.Finally,we point out key challenges and future research directions.

Foundations and Applications of Information Systems Dynamics

Although numerous advances have been made in information technology in the past decades,there is still a lack of progress in information systems dynamics(ISD),owing to the lack of a mathematical foundation needed to describe information and the lack of an analytical framework to evaluate information systems.The value of ISD lies in its ability to guide the design,development,application,and evaluation of largescale information system-of-systems(So Ss),just as mechanical dynamics theories guide mechanical systems engineering.This paper reports on a breakthrough in these fundamental challenges by proposing a framework for information space,improving a mathematical theory for information measurement,and proposing a dynamic configuration model for information systems.In this way,it establishes a basic theoretical framework for ISD.The proposed theoretical methodologies have been successfully applied and verified in the Smart Court So Ss Engineering Project of China and have achieved significant improvements in the quality and efficiency of Chinese court informatization.The proposed ISD provides an innovative paradigm for the analysis,design,development,and evaluation of large-scale complex information systems,such as electronic government and smart cities.

Power Information System Database Cache Model Based on Deep Machine Learning

At present,the database cache model of power information system has problems such as slow running speed and low database hit rate.To this end,this paper proposes a database cache model for power information systems based on deep machine learning.The caching model includes program caching,Structured Query Language(SQL)preprocessing,and core caching modules.Among them,the method to improve the efficiency of the statement is to adjust operations such as multi-table joins and replacement keywords in the SQL optimizer.Build predictive models using boosted regression trees in the core caching module.Generate a series of regression tree models using machine learning algorithms.Analyze the resource occupancy rate in the power information system to dynamically adjust the voting selection of the regression tree.At the same time,the voting threshold of the prediction model is dynamically adjusted.By analogy,the cache model is re-initialized.The experimental results show that the model has a good cache hit rate and cache efficiency,and can improve the data cache performance of the power information system.It has a high hit rate and short delay time,and always maintains a good hit rate even under different computer memory;at the same time,it only occupies less space and less CPU during actual operation,which is beneficial to power The information system operates efficiently and quickly.

An Optimized Method for Information System Transactions Based on Blockchain

Accounting Information System(AIS),which is the foundation of any enterprise resource planning(ERP)system,is often built as centralized system.The technologies that allow the Internet-of-Value,which is built onfive aspects that are network,algorithms,distributed ledger,transfers,and assets,are based on blockchain.Cryptography and consensus protocols boost the blockchain plat-form implementation,acting as a deterrent to cyber-attacks and hacks.Blockchain platforms foster innovation among supply chain participants,resulting in ecosys-tem development.Traditional business processes have been severely disrupted by blockchains since apps and transactions that previously required centralized struc-tures or trusted third-parties to authenticate them may now function in a decentra-lized manner with the same level of assurance.Because a blockchain split in AIS may easily lead to double-spending attacks,reducing the likelihood of a split has become a very important and difficult research subject.Reduced block relay time between the nodes can minimize the block propagation time of all nodes,resulting in better Bitcoin performance.In this paper,three problems were addressed on transaction and block propagation mechanisms in order to reduce the likelihood of a split.A novel algorithm for blockchain is proposed to reduce the total pro-pagation delay in AIS transactions.Numerical results reveal that,the proposed algorithm performs better and reduce the transaction delay in AIS as compared with existing methods.

Intelligent fire information system based on 3D GIS

Background This work aims to build a comprehensive and effective fire emergency management system based on the Internet of Things(IoT)and achieve an actual intelligent fire rescue.A smart fire protection information system was designed based on the IoT.A detailed analysis was conducted on the problem of rescue vehicle scheduling and the evacuation of trapped persons in the process of fire rescue.Methods The intelligent fire visualization platform based on the three-dimensional(3D)Geographic Information Science(GIS)covers project overview,equipment status,equipment classification,equipment alarm information,alarm classification,alarm statistics,equipment account information,and other modules.The live video accessed through the visual interface can clearly identify the stage of the fire,which facilitates the arrangement of rescue equipment and personnel.The vehicle scheduling model in the system primarily used two objective functions to solve the Pareto Non-Dominated Solution Set Optimization:emergency rescue time and the number of vehicles.In addition,an evacuation path optimization method based on the Improved Ant Colony(IAC)algorithm was designed to realize the dynamic optimization of building fire evacuation paths.Results The experimental results indicate that all the values of detection signals were significantly larger in the smoldering fire scene at t=17s than the initial value.In addition,the probability of smoldering fire and the probability of open fire were relatively large according to the probability function of the corresponding fire situation,demonstrating that this model could detect fire.Conclusions The IAC algorithm reported here avoided the passages near the fire and spreading areas as much as possible and took the safety of the trapped persons as the premise when planning the evacuation route.Therefore,the IoT-based fire information system has important value for ensuring fire safety and carrying out emergency rescue and is worthy of popularization and application.

ISO25000-Related Metrics for Evaluating the Quality of Complex Information Systems

Evaluating complex information systems necessitates deep contextual knowledge of technology, user needs, and quality. The quality evaluation challenges increase with the system’s complexity, especially when multiple services supported by varied technological modules, are offered. Existing standards for software quality, such as the ISO25000 series, provide a broad framework for evaluation. Broadness offers initial implementation ease albeit, it often lacks specificity to cater to individual system modules. This paper maps 48 data metrics and 175 software metrics on specific system modules while aligning them with ISO standard quality traits. Using the ISO25000 series as a foundation, especially ISO25010 and 25012, this research seeks to augment the applicability of these standards to multi-faceted systems, exemplified by five distinct software modules prevalent in modern information ecosystems.

Data Analytics of an Information System Based on a Markov Decision Process and a Partially Observable Markov Decision Process

Data analytics of an information system is conducted based on a Markov decision process(MDP)and a partially observable Markov decision process(POMDP)in this paper.Data analytics over a finite planning horizon and an infinite planning horizon for a discounted MDP is performed,respectively.Value iteration(VI),policy iteration(PI),and Q-learning are utilized in the data analytics for a discounted MDP over an infinite planning horizon to evaluate the validity of the MDP model.The optimal policy to minimize the total expected cost of states of the information system is obtained based on the MDP.In the analytics for a discounted POMDP over an infinite planning horizon of the information system,the effects of various parameters on the total expected cost of the information system are studied.

Landfill Site Suitability Assessment Using Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) in Butuan City, Philippines

Landfilling is one of the most effective and responsible ways to dispose of municipal solid waste(MSW).Identifying landfill sites,however,is a challenging and complex undertaking because it depends on social,environmental,technical,economic,and legal issues.This study aims to map the optimal sites that were environmentally suitable for locating a landfill site in Butuan City,Philippines.With reference to the policy requirements from DENR Section I,Landfill Site Identification Criteria and Screening Guidelines of National Solid Waste Management Commission,the integration of a Geographic Information System(GIS)model builder and Analytical Hierarchy Process(AHP)has been used in this study to address the aforementioned challenges related to the landfill site suitability analysis.Based on the generated sanitary landfill suitability map,results showed that Barangay Tungao(1131.42967 ha)and Florida(518.48 ha)were able to meet and consider the three(3)main components,namely economic,environmental,and physical criteria,and are highly suit­able as landfill site locations in Butuan City.It is recommended that there will conduct a geotechnical evaluation,involv­ing rigorous geological and hydrogeological assessment employing a combination of site investigation and laboratory techniques.In addition,additional specific social,ecological,climatic,and economic factors need to be considered(i.e.including impact on humans,flora,fauna,soil,water,air,climate,and landscape).

Locating Global System for Mobile Communication(GSM)Base Stations Using Geographic Information System(GIS)

The global system for mobile communication(GSM)is planned to meet the needs of the whole subscribers.The number of subscribers increased as the population increased due to the acceptance of GSM services by the subscribers.Thus,there should be a way to monitor base stations that will meet the increasing demand of subscribers in any area as a population surge will lead to more subscriptions.This will allow GSM network operators to serve their subscribers better and ease network congestion.This work presents a review of mobile evolution from the first generation to the fifth generation.A review of global positioning system(GPS)technology and its applications to geographic information systems(GIS)was done.The coordinates of these base stations were taken using a GPS device.These base station coordinates were then exported to QGIS for the design of the map.Thereafter,the output map was then integrated into the website.The discussions on the results followed and some useful suggestions given will go a long way to help the operators of GSM in Nigeria and in general.If the propositions given are adhered to,it will go a long way to help the operators reduce congestion on their network and thereby increase the satisfaction of the subscribers.

Customization and Performance of Service-Oriented Manufacturing Information System: The Mediating Effect of Information System Flexibility

The purpose of this paper is to provide empirical evidence for the validity of the relationship between service-oriented manufacturing information system (SMIS) customization and performance from three aspects: data flexibility, process flexibility and system flexibility. We select some questionnaires from the third round of High-performance manufacturing (HPM) data to construct the construct, verify the reliability and validity of the construct, extract principal components, and analyze the mediating effect by using multiple chain linear regression and structural equation model. The results show that SMIS customization has a significant impact on its performance, and this effect works through its flexibility. More specifically, it is the multiple chain mediation effect composed of data flexibility, process flexibility and system flexibility. The importance of SMIS customization and flexibility to the organization is made clear, which helps practitioners understand the internal mechanism that affects SMIS performance, so as to use limited resources to improve system performance.

Cybersecurity Requirements for Management Information Systems

Cybersecurity is therefore one of the most important elements of security in developed countries. Especially since there is an overall trend towards cybersecurity in all aspects of life, I have found that the idea of cybersecurity is based on protecting critical facilities: The nation’s information infrastructure. Information systems, including e-government management systems, are managed by key state agencies. As with economic, scientific, commercial, and other systems, threats are threats to a nation’s national security. We have therefore found that many countries are preparing institutions capable of integrating cybersecurity into protection, development, and information security. This concept has become the most important concern of developed countries, which have secured all scientific possibilities and systems to achieve it. The electronic information network has become an integral part of today’s daily lives in all places. In addition to personal uses, digital information is used, processed, stored, and shared. As this information increases and spreads, we have found that its protection has become more vital and has an effective impact on national security and technical progress.

School Level Information System (IS) Discontinuance Intention: A Case Study on Information System (IS) Discontinuance of Surigao State College of Technology SSCT

Educational institutions implement school information system (IS) solutions for efficient academic processes and improve the student experience, and thus tend to upgrade to new school IS, ceasing the use of old school IS. Extant studies of information system discontinuance are in organizational in general. This study is solely a school organization setting, specifically a thorough understanding of contributing factors that facilitate the intention of school information system (IS) discontinuance. Organizational level IS discontinuance intention OLIDI model was used as a lens and anchored by grounded theory. Semi-Structured interviews were used to collect data from school administrators and users of information system (IS) of Surigao State College of Technology. A qualitative statistics approach and coding of words are used to analyze the intention of IS discontinuance and provide model for school setting IS discontinuance. The findings show that system shortcomings, organizational initiative, environmental change, system investment, and institutional pressures were the critical determinants of increased intentions to replace the existing school information system (IS). The study findings are useful to school administrators to identify long term flexibility required for policies to overcome the capability of shortcomings that emerge over the system life span and underline risk associated with continued use of unsupported systems.

Web service based spatial forest information system using an open source software approach

For technical and other reasons there is a dilemma that data providers cannot find an appropriate way to redistribute spatial forest data and data users who need spatial data cannot access and integrate available forest resources information. To overcome this dilemma, this paper proposed a spatial forest information system based on Web service using an open source software approach. With Web service based architecture, the system can enable interoperability, integrate Web services from other application servers, reuse codes, and shorten the development time and cost. At the same time, it is possible to extend the local system to a regional or national spatial forest information system. The growth of Open Source Software （OSS） provides an alternative choice to proprietary software for operating systems, web servers, Web-based GIS applications and database management systems. Using open source software to develop spatial forest information systems can greatly reduce the cost while providing high performance and sharing spatial forest information. We chose open source software to build a prototype system for Xixia County, Henan Province, China. By integrating OSS packages Deegree and UMN MapServer which are compliant to the OGC open specifications, the prototype system enables users to access spatial forest information and travelling information of Xixia County which come from two different data servers via a standard Web browser and promotes spatial forest information sharing.

Real-Time Information System of Power Plant Based on B/S Computing Mode

This paper introduces the system structure and work principle of the upgraded real time information system in Wangting Power Plant, and then expounds the realization way and function features of this system on B/S computing mode. The results of field application show the new system has good capability, reliability and expandability.

Marine Engineering Geological Exploration Information System(MEGEIS):A GIS-based Application to Marine Resources Exploitation

Based on the ArcGIS geographic information system and the ORACLE database management system,this paper reports our studies on the technology of Marine Engineering Geological Exploration Information System(MEGEIS). By analyzing system structure,designing function modules and discussing data management,this paper systematically proposes a framework of technol-ogy to integrate,manage,and analyze the seabed information comprehensively. Then,the technology is applied to the design and development of the Bohai Sea Oilfield Paradigm Area Information System. The system can not only meet the practical demands of marine resources exploration and exploitation in the Bohai Sea oilfield,but also serve as a preparatory work in theory and technology for the realization of the 'Digital Seabed'.

The Overall Design of Land-Use Information System Based on GIS

The land-use information system (LUIS) is a special geographical information system developed under the support of the geographical information system (GIS). It effectively combines the quantitative analysis with space analysis, mixes the feature of the land-use data and figure de scription, achieves the mutual transfer of the data and figure, and provides some effective methods for the quantitative research and space analysis. The targets, methods and procedures of the overall design of LUIS and its structure function and characteristic are presented in this paper. It pro vides the guide and references for developing the special GIS suitable for the demand of land-use management.

Research and Development of a Network-Based Intelligent Maintenance Information System

A maintenance information system is an important part of equipmentmanagement. An intelligent maintenance information system (IMIS) is a synthesis of networktechnology, information technology and intelligent technology. The IMIS is used to finish flexiblemaintenance decision-making and fast maintenance planning, which helps enterprises to effectivelyreduce maintenance cost and increase working efficiency. Because the IMIS integrates advancedtechnologies, its performance is better than a traditional one. The difference between an IMIS and atraditional maintenance information system, and the functions, structure, important realizations,and application of an IMIS are discussed in this paper.