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.

基于VB的滚动轴承CAPP系统设计与实现

为了提高滚动轴承工艺设计效率和准确性,利用Access建立轴承工艺标准数据库,实现轴承工艺数据信息的存储和管理,利用VB编程语言对Access系统内存储的数据信息进行关联调用,最终以Excel形式呈现,并通过设计友好的人机交互界面,实现用户与软件系统的良好沟通,最终开发出VB和Access两者有机结合的滚动轴承工艺设计与管理应用软件,实现轴承工艺数据信息的存储、查询、更新、生成与应用,进一步提升轴承工艺设计、管理的质量和效率。

项目教学法在VB程序设计教学中的应用

VB程序设计作为一门以过程程序设计为核心的课程,在职业院校信息技术大类专业教学中占有重要地位。然而,在教学过程中,传统的教学方式不仅会削弱学生的学习积极性,还会让学生长时间处于被动的学习状态,从而难以真正掌握课程的核心要点。因此,为了更好地提高教学效果,就需要采用新的教学模式和方法,使其更加符合当前社会需求。把项目教学法运用于VB程序设计课程,不仅可以获得出色的教学成果,还能助力学生成功地掌握所学知识,提升专业技能。

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.

VB/VGF法制备掺FeInP晶体的电阻率均匀性

针对4.5英寸(1英寸≈2.54 cm)掺Fe InP晶体普遍存在的轴向和径向电学参数分布不均匀问题,深入研究了晶体生长工艺参数对电学参数分布的影响。结合垂直布里奇曼(VB)法和垂直梯度凝固(VGF)法,利用六段温区控制及坩埚线性下降的装置,优化了坩埚的旋转和下降速度,以调节掺杂剂Fe在熔体中的分凝、固液界面形状及晶体头部与尾部的生长速度。这些措施不仅改善了晶体的固液界面形状,使其由较凹变得平缓,同时实现了晶体生长速率的合理匹配与温度梯度的精确控制,显著提升了晶体的位错密度和电学参数的均匀性。与传统VGF法相比,VB/VGF法掺Fe InP晶体的轴向电阻率差值降低了259%,径向电阻率均匀性提高了2.0%~7.1%。

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.

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.

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.

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.

VB6.0在测绘资料整理中的应用

测绘观测资料需要实时处理,然而项目需求却在不断变化,现有的软件无法满足需求。论文详细介绍了VB 6.0操作Microsoft Excel和Microsoft Word的诸多技巧,并基于这些技巧编写了相关的实例程序,合理地解决了实际问题,展示并证明了VB 6.0在测绘工程中资料整理方面的强大优势。

PKS系统中VB脚本程序开发及在基板玻璃成型炉升温控制中的应用

Honeywell PKS系统图形化编程和VB Script脚本程序的应用,给用户提供了更多的开发空间,可以使得一些复杂控制功能的组态更为简单和灵活,本文以基板玻璃成型炉升温自动控制功能的实现过程,进一步阐述PKS系统中VB脚本程序的开发及应用。

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.

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).

基于VB/ANSYS的变压器试验结果分析软件开发与应用

对电力变压器的试验项目进行分析,基于VB平台利用ANSYS二次设计了一套变压器试验结果分析软件,实现了变压器绕组连同套管的直流电阻、变比测量、绝缘电阻、吸收比或极化指数、介质损耗因数测量的试验结果计算与分析。

基于VB的差温推弯成形模具参数化设计

弯管在航空、船舶、汽车等行业应用广泛,随着航空、船舶、汽车业的蓬勃发展,对弯管的需求也越来越大。为了解决弯管推弯过程中薄壁管外侧拉裂、内侧褶皱的问题,本文研究设计了一款同时对弯管内侧壁冷却、外侧壁加热的铝合金薄壁管差温推弯模具,可以更好地提高推弯成形质量。同时,为了解决模具单一性导致的弯管生产效率较低的问题,本文利用VB技术对CATIA进行二次开发,对所设计的铝合金薄壁管差温推弯模具进行参数化设计,实现通过所需弯管尺寸的变动来驱动生成相应的模具,以提升生产效率。