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.

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.

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.

An Optimized Method for Accounting Information in Logistic Systems

In the era of rapid information development,with the popularity of computers,the advancement of science and technology,and the ongoing expansion of IT technology and business,the enterprise resource planning(ERP)system has evolved into a platform and a guarantee for the fulfilment of company management procedures after long-term operations.Because of developments in information technology,most manual accounting procedures are being replaced by computerized Accounting Information Systems(AIS),which are quicker and more accurate.The primary factors influencing the decisions of logistics firm trading parties are investigated in order to enhance the design of decision-supporting modules and to improve the performance of logistics enterprises through AIS.This paper proposed a novel approach to calculate the weights of each information element in order to establish their important degree.The main purpose of this research is to present a quantitative analytic approach for determining the important information of logistics business collaboration response.Furthermore,the idea of total orders and the significant degrees stated above are used to identify the optimal order of all information elements.Using the three ways of marginal revenue,marginal cost,and business matching degree,the information with cumulative weights is which is deployed to form the data from the intersection of the best order.It has the ability to drastically reduce the time and effort required to create a logistics business control/decision-making system.

Information Management in Disaster and Humanitarian Response: A Case in United Nations Office for the Coordination of Humanitarian Affairs

To guarantee a unified response to disasters, humanitarian organizations work together via the United Nations Office for the Coordination of Humanitarian Affairs (OCHA). Although the OCHA has made great strides to improve its information management and increase the availability of accurate, real-time data for disaster and humanitarian response teams, significant gaps persist. There are inefficiencies in the emergency management of data at every stage of its lifecycle: collection, processing, analysis, distribution, storage, and retrieval. Disaster risk reduction and disaster risk management are the two main tenets of the United Nations’ worldwide plan for disaster management. Information systems are crucial because of the crucial roles they play in capturing, processing, and transmitting data. The management of information is seldom discussed in published works. The goal of this study is to employ qualitative research methods to provide insight by facilitating an expanded comprehension of relevant contexts, phenomena, and individual experiences. Humanitarian workers and OCHA staffers will take part in the research. The study subjects will be chosen using a random selection procedure. Online surveys with both closed- and open-ended questions will be used to compile the data. UN OCHA offers a structure for the handling of information via which all humanitarian actors may contribute to the overall response. This research will enable the UN Office for OCHA better gather, process, analyze, disseminate, store, and retrieve data in the event of a catastrophe or humanitarian crisis.

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.

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.

On Multi-Granulation Rough Sets with Its Applications

Recently,much interest has been given tomulti-granulation rough sets (MGRS), and various types ofMGRSmodelshave been developed from different viewpoints. In this paper, we introduce two techniques for the classificationof MGRS. Firstly, we generate multi-topologies from multi-relations defined in the universe. Hence, a novelapproximation space is established by leveraging the underlying topological structure. The characteristics of thenewly proposed approximation space are discussed.We introduce an algorithmfor the reduction ofmulti-relations.Secondly, a new approach for the classification ofMGRS based on neighborhood concepts is introduced. Finally, areal-life application from medical records is introduced via our approach to the classification of MGRS.

Changes in snow cover extent in the Central Taurus Mountains from 1981 to 2021 in relation to temperature, precipitation, and atmospheric teleconnections

The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central Taurus Mountains(Bolkar, Aladaglar, Tahtali and Binboga Mountains) from 1981 to 2021. Linear trends of snow cover season(November to April) over the last 41 years showed decreases in SCE primarily at lower elevations. The downward trend in SCE was found to be more pronounced and statistically significant for only November and March. SCE in the Central Taurus Mountains has declined about-6.3% per decade for 2500-3000 m in November and about-6.0% per decade for 1000-1500 m and 3000+ m in March over the last 41 years. The loss of SCE has become evident since the 2000s, and the lowest negative anomalies in SCE have been observed in 2014, 2001, and 2007 in the last 41 years, which are consistent with an increase in air temperature and decreased precipitation. SCE was correlated with both mean temperature and precipitation, with temperature having a greater relative importance at all elevated gradients. Results showed that there is a strong linear relationship between SCE and the mean air temperature(r =-0.80) and precipitation(r = 0.44) for all elevated gradients during the snow season. The Arctic Oscillation(AO), the North Atlantic Oscillation(NAO), and the Mediterranean Oscillation(MO) winter indices were used to explain the year-to-year variability in SCE over the Central Taurus Mountains. The results showed that the inter-annual variability observed in the winter SCE on the Central Taurus Mountains was positively correlated with the phases of the winter AO, NAO and MO, especially below 2000 m elevation.

GIS Application in Urban Flood Risk Analysis: Midar as a Case Study

The significance of this study lies in its exploration of the advanced applications of Geographic Information Systems (GIS) in assessing urban flood risks, with a specific focus on Midar, Morocco. This research is pivotal as it showcases that GIS technology is not just a tool for mapping, but a critical component in urban planning and emergency management strategies. By meticulously identifying and mapping flood-prone areas in Midar, the study provides invaluable insights into the potential vulnerabilities of urban landscapes to flooding. Moreover, this research demonstrates the practical utility of GIS in mitigating material losses, a significant concern in flood-prone urban areas. The proactive approach proposed in this study, centered around the use of GIS, aims to safeguard Midar’s population and infrastructure from the devastating impacts of floods. This approach serves as a model for other urban areas facing similar challenges, highlighting the indispensable role of GIS in disaster preparedness and response. Overall, the study underscores the transformative potential of GIS in enhancing urban resilience, making it a crucial tool in the fight against natural disasters like floods.

On the Range of Action of Adult Culex pipiens s.l.

Mosquitoes are an interesting topic due to their medical importance, as they play an active role in the transmission of many pathogens and parasites, acting as vectors for various pathologies that are deadly to humans, such as dengue, yellow fever, chikungunya, West Nile virus, encephalitis and malaria, among many others that are less common. In terms of morbidity and mortality caused by vector-borne diseases, mosquitoes are the most dangerous animals for humanity and, although they also play a role in the ecosystem as a food source for other organisms, their importance for public health cannot be overlooked. As highly efficient vectors, they put more than three billion people at risk, mainly in tropical and subtropical regions as well as in Europe, since heat waves and flooding are becoming more frequent and severe, and summers are getting longer and warmer, accelerating mosquito development, biting rates, and the incubation of the pathogens within their bodies. Female mosquitoes bite to acquire proteins for the development of their ovaries and eggs and, in the process, acquire pathogens and/or parasites from one vertebrate host and transmit them to another, usually after a short period of replication. Three of their four life stages are lived in still freshwater, so it is crucial to understand their range of action when they reach adulthood and leave the water, in order to plan and implement local prevention measures. A set of georeferenced abundance data collected in mainland Portugal over seven years was linked to cartographed water bodies in a geographic information system to estimate the distances at which Culex pipiens s.l. had a significant presence, with criteria based on the size of the catches. The result allows for an estimate of the fly range of those mosquitoes, which can be used to focus countermeasures.

Contribution of the MERISE-Type Conceptual Data Model to the Construction of Monitoring and Evaluation Indicators of the Effectiveness of Training in Relation to the Needs of the Labor Market in the Republic of Congo

This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.

Telematics as a Transformative Agent for the Zimbabwean Auto Insurance Ecosystem

Zimbabwe has witnessed the evolution of Information Communication Technology (ICT). The vehicle population soared to above 1.2 million hence rendering the Transport and Insurance domains complex. Therefore, there is a need to look at ways that can augment conventional Vehicular Management Information Systems (VMIS) in transforming business processes through Telematics. This paper aims to contextualise the role that telematics can play in transforming the Insurance Ecosystem in Zimbabwe. The main objective was to investigate the integration of Usage-Based Insurance (UBI) with vehicle tracking solutions provided by technology companies like Econet Wireless in Zimbabwe, aiming to align customer billing with individual risk profiles and enhance the synergy between technology and insurance service providers in the motor insurance ecosystem. A triangulation through structured interviews, questionnaires, and literature review, supported by Information Systems Analysis and Design techniques was conducted. The study adopted a case study approach, qualitatively analyzing the complexities of the Telematics insurance ecosystem in Zimbabwe, informed by the TOGAF framework. A case-study approach was applied to derive themes whilst applying within and cross-case analysis. Data was collected using questionnaires, and interviews. The findings of the research clearly show the importance of Telematics in modern-day insurance and the positive relationship between technology and insurance business performance. The study, therefore revealed how UBI can incentivize positive driver behavior, potentially reducing insurance premiums for safe drivers and lowering the incidence of claims against insurance companies. Future work can be done on studying the role of Telematics in combating highway crime and corruption.

Computational Quantification of Map Projection Distortion by Fractal Dimension of Coastlines

Maps, essential tools for portraying the Earth’s surface, inherently introduce distortions to geographical features. While various quantification methods exist for assessing these distortions, they often fall short when evaluating actual geographic features. In our study, we took a novel approach by analyzing map projection distortion from a geometric perspective. We computed the fractal dimensions of different stretches of coastline before and after projection using the divide-and-conquer algorithm and image processing. Our findings revealed that map projections, even when preserving basic shapes, inevitably stretch and compress coastlines in diverse directions. This analysis method provides a more realistic and practical way to measure map-induced distortions, with significant implications for cartography, geographic information systems (GIS), and geomorphology. By bridging the gap between theoretical analysis and real-world features, this method greatly enhances accuracy and practicality when evaluating map projections.

Approximation Maintenance When Adding a Conditional Value in Set-Valued Ordered Decision Systems

The integration of set-valued ordered rough set models and incremental learning signify a progressive advancement of conventional rough set theory, with the objective of tackling the heterogeneity and ongoing transformations in information systems. In set-valued ordered decision systems, when changes occur in the attribute value domain, such as adding conditional values, it may result in changes in the preference relation between objects, indirectly leading to changes in approximations. In this paper, we effectively addressed the issue of updating approximations that arose from adding conditional values in set-valued ordered decision systems. Firstly, we classified the research objects into two categories: objects with changes in conditional values and objects without changes, and then conducted theoretical studies on updating approximations for these two categories, presenting approximation update theories for adding conditional values. Subsequently, we presented incremental algorithms corresponding to approximation update theories. We demonstrated the feasibility of the proposed incremental update method with numerical examples and showed that our incremental algorithm outperformed the static algorithm. Ultimately, by comparing experimental results on different datasets, it is evident that the incremental algorithm efficiently reduced processing time. In conclusion, this study offered a promising strategy to address the challenges of set-valued ordered decision systems in dynamic environments.

社会化网络服务世界中的有效竞争策略——Information Systems Research, Vol. 21, No. 3, September 2010综述

一个国家的企业与其他国家的企业在本土市场上开展的正面直接竞争过程,既是技术创新与市场营销有效结合并赢得顾客的过程,也是技术创新的竞争过程。面对日益激烈的竞争环境,尤其是高科技企业不仅需要平衡技术和市场策略的投入。

A mixed stochastic user equilibrium model considering influence of advanced traveller information systems in degradable transport network

Advanced traveler information systems （ATIS） can not only improve drivers＇ accessibility to the more accurate route travel time information, but also can improve drivers＇ adaptability to the stochastic network capacity degradations. In this paper, a mixed stochastic user equilibrium model was proposed to describe the interactive route choice behaviors between ATIS equipped and unequipped drivers on a degradable transport network. In the proposed model the information accessibility of equipped drivers was reflected by lower degree of uncertainty in their stochastic equilibrium flow distributions, and their behavioral adaptability was captured by multiple equilibrium behaviors over the stochastic network state set. The mixed equilibrium model was formulated as a fixed point problem defined in the mixed route flows, and its solution was achieved by executing an iterative algorithm. Numerical experiments were provided to verify the properties of the mixed network equilibrium model and the efficiency of the iterative algorithm.

Solution to the Mind-Body Relation Problem: Information

In this paper it is analyzed from the informational perspective the relation between mind and body, an ancientphilosophic issue defined as a problem, which still did not receive up to date an adequate solution. Byintroducing/using the concept of information, it is shown that this concept includes two facets, one of themreferring to the common communications and another one referring to a hidden/structuring matter-relatedinformation, effectively acting in the human body and in the living systems, which determines the dynamicinter-change of information between specific structures of the organism by electric/electronic/chemical agents andgenetic/epigenetic processes. It is shown that the maintenance of body, permanently and obligatory depending onthe external matter (foods, air, water) resources, needed to provide both the structuring/restructuring basic materialand energy, determines the necessary existence of an info-managing system, administrating the internalmechano-chemical/physical processes. As a natural consequence, such a system should organize and assure ownsurvival by an effective informational operability to detect the external food resources, to select the appropriateinterest information and to decide as a function of circumstances. One important component in such aninformational system is memory, allowing to dispose of the reference informational data for analysis/comparisonand the selection between good and bad binary possible decisions. The memory receives and stores thereforesignals from external reality and from the body itself, referring to the emotional reaction, digestion status, creation,and inherited predilections, within specific info-neural communication circuits between the brain and bodyexecution/sensitive organs, the human body appearing as an integrated info-matter self-managed dynamic system.The specific body components memorize information with different degrees of info-integration: short/long-termintegration, emotive/action reaction, info-abilities, culminating with the integration in the chromosomal structuresby epigenetic processes. The new acquired information is transgenerationally transmissible, and is manifested asnew traits, showing the adaptation capability of the human and close relation between mind and body. Analyzingthe results of such a mind-body informational model in comparison with the earlier assumed/proposed/assertedarchaic, Greek and Occidental philosophies, which represent only partial aspects of this relation, it is shown thatthis informational model, elaborated in terms of information on the basis of scientific reasons and arguments,constitutes a general, realist, and coherent model of the mind-body relation, able to integrate and/or explain most ofthe others.

Life Loss Estimation Based on Dam-Break Flood Uncertainties and Lack of Information in Mountainous Regions of Western China

Compared with urban floods, dam-break floods are associated with greater uncertainties, including variable dam-break modes and hydrological characteristics, so conventional flood estimation methods cannot be directly applied in the estimation of dam-break flood loss. In particular, there is scant information regarding the conditions of affected area and hydrological characteristics in southwest China. In this paper, we introduce an integrated model for estimating flood loss that is adapted to the mountainous regions of southwestern China in light of the relative lack of available information. This model has three major components: a basic information model, a dam-routed flood propagation simulation model, and a loss estimation model. We established the basic information model despite the relative lack of available information using 3S technology [remote sensing (RS); geographical information system (GIS); global positioning system (GPS)], data mining technology, and statistical analysis techniques. Our dam-routed flood propagation simulation model consists of major hydrologic processes and their governing equations for flow propagation, which we solve using finite-difference schemes. In this model, the flood propagation area is divided into grids and each grid is determined by the characteristic parameters obtained from the propagation simulation. We present a case study of the Lianghekou hydropower station in Sichuan Province, China to illustrate the practical application of this integrated model for life loss estimation. © 2017, Tianjin University and Springer-Verlag Berlin Heidelberg.