Innovative Practice of Intelligent Business Models in the Field of Communication

As a service format to meet spiritual needs, fashion culture industry is often synchronized in its creation, production, dissemination, display and consumption. In order to explore how artificial intelligence provides technical means, platforms, channels and space for intelligent formats in the field of communication, and how to provide intelligent services for cultural creation, communication, display and consumption. This paper discusses the application and innovation of artificial intelligence in all aspects of communication field, analyzes the problems and puts forward corresponding countermeasures and suggestions.

Big data challenge for monitoring quality in higher education institutions using business intelligence dashboards

As big data becomes an apparent challenge to handle when building a business intelligence(BI)system,there is a motivation to handle this challenging issue in higher education institutions(HEIs).Monitoring quality in HEIs encompasses handling huge amounts of data coming from different sources.This paper reviews big data and analyses the cases from the literature regarding quality assurance(QA)in HEIs.It also outlines a framework that can address the big data challenge in HEIs to handle QA monitoring using BI dashboards and a prototype dashboard is presented in this paper.The dashboard was developed using a utilisation tool to monitor QA in HEIs to provide visual representations of big data.The prototype dashboard enables stakeholders to monitor compliance with QA standards while addressing the big data challenge associated with the substantial volume of data managed by HEIs’QA systems.This paper also outlines how the developed system integrates big data from social media into the monitoring dashboard.

Building a Business and Strategic Intelligence Policy as a Strategy for Promoting Congolese Business Progress and Healthy Economic Development in Eastern DRC

The aim of this study was to verify the existence of business and strategic intelligence policies at the level of Congolese companies and at the state level, likely to foster progress and healthy development in the east of the DRC. The study was based on a mixed perspective consisting of objective analysis of quantitative data and interpretative analysis of qualitative data. The results showed that business and strategic intelligence policies have not been established at either company or state level, as this is an area of activity that is not known to the players in companies and public departments, and there are no units or offices in their organizational structures responsible for managing strategic information for competitiveness on the international market. In addition, there is a real need to establish strategic information management units within companies, upstream, and to set up a national strategic information management department or agency to help local companies compete in the marketplace, downstream. This reflects the importance and timeliness of building business and strategic intelligence policies to ensure economic progress and development in the eastern DRC. Business and strategic intelligence provides companies with an appropriate tool for researching, collecting, processing and disseminating information useful for decision-making among stakeholders, in order to cope with a crisis or competitive situation. The study suggests a number of key recommendations based on its findings. To the government, it is recommended to establish the national policy of business and strategic intelligence by setting up a national agency of strategic intelligence in favor of local companies;and to companies to establish business intelligence units in their organizational structures in favor of stakeholders to foster advantageous decision-making in the competitive market and achieve progress. Finally, the study suggests that studies be carried out to fully understand the opportunities and impact of business and strategic intelligence in African countries, particularly in the DRC.

Web Application Commercial Design for Financial Entities Based on Business Intelligence

Multiple customer data management has become a focus of attention in big organizations.Although much information is available,it does not translate into significant profitable value-added services.We present a design of a commercial web application based on business intelligence that generates information on social and financial behavior of clients in an organization;with the purpose of obtain additional information that allows to get more profits.This app will provide a broader perspective for making strategic decisions to increase profits and reduce internal investment costs.A case in point is the financial sector,a group of financial entities were used to make measurements and test them.A design to build a web application aimed at achieving a large and ambitious goal by means of defined tools reflecting clients’business needs is proposed.In this research,different techniques and technologies are explored,such as diagrams,frameworks,design,architecture,model entity-relationship,tables,equations,mental maps and development tools.Through the Personal Software Process methodology and with the help of information extraction,consolidation,and visualization,the implementation can be carried out.This article provides the importance of implementing business intelligence in an organization and expands on the steps needed for the implementation of this valuable technology.

Using MWD： A Business Intelligence System for Tourism Destination Web

The importance of Internet as mass media in the field of tourism is that it constitutes an important channel of marketing institutions and business network of the tourist destinations. But very few subsequent processes of management, maintenance, improvement, and exploitation of this appearance are deeply studied. The interactive nature of the website, as both transmitter of information and receiver, has attracted the attention of scholars since the interaction allows opening new approaches to the study of the network traffic （the pages user has visited, order them, the time that it has been in them, the actions carried out...） and cyber behavior. Information flows from the physical to the cyber world, and vice versa, adapting the converged world to human behavior and social dynamic. The business intelligence systems based on Internet enable organizations intelligent actions to address time-sensitive business processes and benefit from analytics. As result provides the opportunity to anticipate and estimate visitor habits in a changing environment. This paper presents the research and technological fields which have been incorporated to study of the destination web, a business intelligent tool based on Internet that it aims to increase the performance of the local manager or tour operator by providing an enhanced insight through the behavior of visitors on the website and future trends in research are expressed.

Intelligent tools and techniques for modern management

In order to make decisions all companies need information. As a rule, all the informatics systems of a company contain a multitude of data and turn these data into information that has to be analyzed in order to make decisions. It is a slow process. The solution of this drawback is given by Business Intelligence （BI） applications that can help companies increase income or diminish costs by offering the executive management appropriate information on the basis of which quick and efficient decisions can be taken.The main purpose of the paper is to prove the necessity that BI tools should be used by the modem manager. Managers are aware of that by putting into practice the BI solutions, opportunities of getting control over the business process and methods are improved and better, timely analysis functions of the performance parameters can be obtained.

An Inquiry into Business Intelligence Application in Telecom BOSS

This paper analyzes the application prospect of Business Intelligence (BI) in telecom BOSS construction,describes the technical framework of BI realization and its technical strategies.And it also discusses some typical applications of BI in current construction.It is concluded that BI construction in BOSS is a comprehensive application of a massive amount of accumulated operation support data.

The Effects of Business Intelligence on Strategic Management of Enterprises

Discipline of informatics must contain one of the significant issues that need to develop for especially processing systems of large-scale enterprises. At this point, a well-designed business intelligence （BI） system, which includes a structure of regular business activities and analyses within whole an enterprise, requires to manage stored data and transform the data into information as an output and forecasting targets and provide sustainable growth for an enterprise or an organization. Information systems （IS） support to constitute these processes by using the information technologies （IT） that cause to capture data which will be transformed into information and integrate whole subsystems that need to develop for all departments of the enterprise. BI tools organize all parts of these business analysis and processes and effect on the top management level of enterprises or organizations. Decision makers at the top-level of management must use these information and knowledge to orient future decisions for the enterprise that includes investments, company policies, precautions for the future negations, etc. This study shows that the BI is not only an IS, but also reinforcement for strategic decisions of the enterprises and/or organizations.

Proposal for Design and Application of Business Intelligence as a Decision Support System to the Editorial Sector of Distance Education （DE）

In recent years, industrial and service organizations have invested in improvement projects with emphasis on increasing the performance of processes regarding to the production of manufactured goods and services, applying techniques to optimize production time in order to minimize the restrictive effects of the funds invested in processing or obtaining processes in order to reduce the losses of general scope. This paper discusses the impact of the innovation in making use of business intelligence （BI） concepts about production records of a publishing area in a higher education institution （HEI） that promotes distance education （DE） in Brazil, helping the industry in their managements decisions, having a target minimize time on production of learning material through more effective control with the use of cubes in the form of reports for metric queries of delivery delays and metrics on the production tasks financial values, and filtering the processed information so that managers can view information from various angles and managerial perspectives. The objectives of this paper are to demonstrate the impact on using BI concepts in the process of an editorial department of a HEI focusing on the development of teaching materials for the courses of DE and identify the financial cost-benefit ratio for the HEI with the deploying BI in a software fee platform in its publishing department. The sector is responsible by in courseware publishing organizations that usually do not have systems with this emphasis： support on making managerial decisions.

A Novel Integrated Machine&Business Intelligence Framework for Sensor Data Analysis

Increased smart devices in various industries are creating numerous sensors in each of the equipment prompting the need for methods and models for sensor data.Current research proposes a systematic approach to analyze the data generated from sensors attached to industrial equipment.The methodology involves data cleaning,preprocessing,basics statistics,outlier,and anomaly detection.Present study presents the prediction of RUL by using various Machine Learning models like Regression,Polynomial Regression,Random Forest,Decision Tree,XG Boost.Hyper Parameter Optimization is performed to find the optimal parameters for each variable.In each of the model for RUL prediction RMSE,MAE are compared.Outcome of the RUL prediction should be useful for decision maker to drive the business decision;hence Binary cclassification is performed,and business case analysis is performed.Business case analysis includes the cost of maintenance and cost of non-maintaining a particular asset.Current research is aimed at integrating the machine intelligence and business intelligence so that the industrial operations optimized both in resource and profit.

BigPicture:An Analytical Platform for Business War Gaming

Business war games are strategic management exercises that bring the military scenario simulation to a commercial setting, helping business managers to better understand the environment in which they operate and anticipate scenarios, such as competition movements, new product launching and production capacity planning, among others. These exercises normally take place with players organized in teams, gathered in a room, with a static package of information provided beforehand. In this paper we present an alternative, dynamic way of playing a business war game, with players geographically dispersed, and information dynamically available as it is available from its sources. We introduce BigPicture, an analytical platform with unique features that allow it to be an ideal “playground” for conducting more realistic business war games.

基于大数据BI技术的智慧工地数据可视化平台的设计与研究--以某大型建筑工程集团为例

大数据BI(Business Intelligence)技术在数据挖掘、数据分析、数据可视化等方面的功能实现较成熟,已广泛应用在制造业、零售业等行业。将大数据BI技术融入智慧工地,建立数据可视化平台,可以解决智慧工地存在的局部“数据孤岛”等问题,让智慧工地的海量数据得到最大价值体现。文章以某大型市政特级资质建筑工程集团为例,采用基于Hadoop+Spark的技术架构,以在建的大型地铁市政工程项目为实践,主要论述数据可视化平台架构选型、建立数据仓库、数据ETL、数据可视、Spark引擎框架与MapReduce在数据处理性能方面的对比等。构建基于大数据BI技术的智慧工地可视化数据平台,能有效推进智慧工地的开展,提升对工程项目在质量安全、绿色施工、成本管控等方面的管理。

Big Data 4.0: The Era of Big Intelligence

Big data has had significant impacts on our lives,economies,academia and industries over the past decade.The current equations are:What is the future of big data?What era do we live in?This article addresses these questions by looking at meta as an operation and argues that we are living in the era of big intelligence through analyzing from meta(big data)to big intelligence.More specifically,this article will analyze big data from an evolutionary perspective.The article overviews data,information,knowledge,and intelligence(DIKI)and reveals their relationships.After analyzing meta as an operation,this article explores Meta(DIKE)and its relationship.It reveals 5 Bigs consisting of big data,big information,big knowledge,big intelligence and big analytics.Applying meta on 5 Bigs,this article infers that 4 Big Data 4.0=meta(big data)=big intelligence.This article analyzes how intelligent big analytics support big intelligence.The proposed approach in this research might facilitate the research and development of big data,big data analytics,business intelligence,artificial intelligence,and data science.

Problems and Countermeasures of the Application of Enterprise Management Accounting Informatization

The development of the internet can have a huge impact on industries from the mode of operation and strategic direction. As the ＂core＂ of enterprises, the financial industry has undergone great changes also, and the mode of traditional accounting in manual has been replaced by a computerized accounting. A computer can do all the financial work from accounting to reporting. Efficient and convenient accounting work allows financial personnel have more energy and time in enterprise management and decision-making, and the core of financial work has shifted to management. Therefore, more and more enterprises realize management accounting＇s value and importance. Management accounting includes information collection, analysis, storage and transfer, as well as data processing and analysis, making information system essential. Thus, management accounting information system will be an indispensable tool for enterprise value management. In the study, based on management accounting information, application of management accounting information in mid and large-size enterprises in China was reviewed to analyze existing problems and propose countermeasures with consideration of financial cloud model and business intelligence.

Big-Data Analytics:Challenges,Key Technologies and Prospects

With the rapid development of the internet, internet of things, mobile internet, and cloud computing, the amount of data in circulation has grown rapidly. More social information has contributed to the growth of big data, and data has become a core asset. Big data is challenging in terms of effective storage, efficient computation and analysis, and deep data mining. In this paper, we discuss the signif- icance of big data and discuss key technologies and problems in big-data analyties. We also discuss the future prospects of big-data analylics.

An LSTM Based Forecasting for Major Stock Sectors Using COVID Sentiment

Stock market forecasting is an important research area,especially for better business decision making.Efficient stock predictions continue to be significant for business intelligence.Traditional short-term stock market forecasting is usually based on historical market data analysis such as stock prices,moving averages,or daily returns.However,major events’news also contains significant information regarding market drivers.An effective stock market forecasting system helps investors and analysts to use supportive information regarding the future direction of the stock market.This research proposes an efficient model for stock market prediction.The current proposed study explores the positive and negative effects of coronavirus events on major stock sectors like the airline,pharmaceutical,e-commerce,technology,and hospitality.We use the Twitter dataset for calculating the coronavirus sentiment with a Long Short-Term Memory(LSTM)model to improve stock prediction.The LSTM has the advantage of analyzing relationship between time-series data through memory functions.The performance of the system is evaluated by Mean Absolute Error(MAE),Mean Squared Error(MSE),and Root Mean Squared Error(RMSE).The results show that performance improves by using coronavirus event sentiments along with the LSTM prediction model.

Renewable and Nonrenewable Energy Flow Resiliency for Day-to-Day Production and Consumption

Energy resilience is about ensuring a business and end-use consumers have a reliable,regular supply of energy and contingency measures in place in the event of a power failure,generating a source of power such as electricity for daily needs from an uninterrupted source of energy no matter either renewable or nonrenewable.Causes of resilience issues include power surges,weather,natural disasters,or man-made accidents,and even equipment failure.The human operational error can also be an issue for grid-power supply to go down and should be factored into resilience planning.As the energy landscape undergoes a radical transformation,from a world of large,centralized coal plants to a decentralized energy world made up of small-scale gas-fired production and renewables,the stability of electricity supply will begin to affect energy pricing.Businesses must plan for this change.The challenges that the growth of renewables brings to the grid in terms of intermittency mean that transmission and distribution costs consume an increasing proportion of bills.With progress in the technology of AI(Artificial Intelligence)integration of such progressive technology in recent decades,we are improving our resiliency of energy flow,so we prevent any unexpected interruption of this flow.Ensuring your business is energy resilient helps insulate against price increases or fluctuations in supply,becoming critical to maintaining operations and reducing commercial risk.In the form short TM(Technical Memorandum),this paper covers this issue.

Ground-0 Axioms vs.First Principles and Second Law:From the Geometry of Light and Logic of Photon to Mind-Light-Matter Unity-AI&QI

Without the geometry of light and logic of photon,observer-observability forms a paradox in modern science,truthequilibrium finds no unification,and mind-light-matter unity is unreachable in spacetime.Subsequently,quantum mechanics has been shrouded with mysteries preventing itself from reaching definable causality for a general purpose analytical quantum computing paradigm.Ground-0 Axioms are introduced as an equilibrium-based,dynamic,bipolar set-theoretic unification of the first principles of science and the second law of thermodynamics.Related literatures are critically reviewed to justify the self-evident nature of Ground-0 Axioms.A historical misinterpretation by the founding fathers of quantum mechanics is identified and corrected.That disproves spacetime geometries(including but not limited to Euclidean and Hilbert spaces)as the geometries of light and truth-based logics(including but not limited to bra-ket quantum logic)as the logics of photon.Backed with logically definable causality and Dirac 3-polarizer experiment,bipolar quantum geometry(BQG)and bipolar dynamic logic(BDL)are identified as the geometry of light and the logic of photon,respectively,and wave-particle complementarity is shown less fundamental than bipolar complementarity.As a result,Ground-0 Axioms lead to a geometrical and logical illumination of the quantum and classical worlds as well as the physical and mental worlds.With logical resolutions to the EPR and Schr?dinger’s cat paradoxes,an analytical quantum computing paradigm named quantum intelligence(QI)is introduced.It is shown that QI makes mind-light-matter unity and quantum-digital compatibility logically reachable for quantumneuro-fuzzy AI-machinery with groundbreaking applications.It is contended that Ground-0 Axioms open a new era of science and philosophy—the era of mind-light-matter unity in which humanlevel white-box AI&QI is logically prompted to join Einstein’s grand unification to foster major scientific advances.

Arithmetic Optimization with Deep Learning Enabled Churn Prediction Model for Telecommunication Industries

Customer retention is one of the challenging issues in different business sectors,and variousfirms utilize customer churn prediction(CCP)process to retain existing customers.Because of the direct impact on the company revenues,particularly in the telecommunication sector,firms are needed to design effective CCP models.The recent advances in machine learning(ML)and deep learning(DL)models enable researchers to introduce accurate CCP models in the telecom-munication sector.CCP can be considered as a classification problem,which aims to classify the customer into churners and non-churners.With this motivation,this article focuses on designing an arithmetic optimization algorithm(AOA)with stacked bidirectional long short-term memory(SBLSTM)model for CCP.The proposed AOA-SBLSTM model intends to proficiently forecast the occurrence of CC in the telecommunication industry.Initially,the AOA-SBLSTM model per-forms pre-processing to transform the original data into a useful format.Besides,the SBLSTM model is employed to categorize data into churners and non-chur-ners.To improve the CCP outcomes of the SBLSTM model,an optimal hyper-parameter tuning process using AOA is developed.A widespread simulation analysis of the AOA-SBLSTM model is tested using a benchmark dataset with 3333 samples and 21 features.The experimental outcomes reported the promising performance of the AOA-SBLSTM model over the recent approaches.

A Decision Support System for Spatial Analysis of Agricultural Production in Madagascar

In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatial data warehouse technique based on the SOLAP spatial analysis tool. After having defined the concepts underlying these systems, we propose to address the research issues related to them from four points of view: needs study of the Malagasy Ministry of Agriculture, modeling of a multidimensional conceptual model according to the MultiDim model and the implementation of the system studied using GeoKettle, PostGIS, GeoServer, SPAGO BI and Géomondrian technologies. This new system helps improve the decision-making process for agricultural production in Madagascar.