Research on Restoration and Intelligent Management of the Global Village

A sharp rebound in global energy emissions in 2018 is disappointing as the carbon-dioxide data monitored by mon ppm,hawaii reached 415.09 on may 3,the highest level in at least 800,000 years.We are well known to emit 0.272 kg of carbon dust,0.997 kg of carbon dioxide(C02),0.03 kg of sulfur dioxide(S02),0.015 kg of nitrogen oxides(NOX)and huge amounts of heat to the earth for each electricity we use a 1 degree thermal power plant.Therefore,the full use of renewable energy instead of fossil energy,not only to achieve reduction.The effective measures to open the era of boiler and automobile cold emission are also the trend of the development of national environmental protection and energy strategy.

Research on Innovation of Engineering Project Management Mode and Intelligent Management

In order to realize the standardization and normalization of environmental protection project management.This paper uses the literature method to study the current status of the existing project management mode,and points out the problems:lack of a sound project management system,insufficient information application of project management,and unclear decentralization in project management;on this basis,this paper proposes optimization strategies from the aspects of perfecting the engineering project management system,clarifying the allocation of project management authority,and strengthening the construction of engineering project management information.And put forward the future development trend of project engineering management,on the basis of two mainstream management modes of BOT(Build-Operate-Transfer)and EPC(Engineering Procurement Construction),build a standardized project management platform to achieve intelligent management.Realize intelligent management of engineering project management to achieve standardization and standardization,greatly improving the efficiency of project management.

Optimization Management of Industrial Organizations Based on Performance Indicators

This paper proposes an intelligent management system (IMS) to help managers in their delicate and tedious task of exploiting the plethora of data (indicators) contained in management dashboards. This system is based on intelligent agents, ontologies and data mining. It is implemented by PASSI (Process for Agent Societies Specification and Implementation) methods for agent design and implementation, the Methodology for Knowledge Modeling and Hot-Winters for data prediction. Intelligent agents not only track indicators but also store the knowledge of managers within the company. Ontologies are used to manage the representation and presentation aspects of knowledge. Data mining makes it possible to: make the most of all available data;model the industrial process of data selection, exploration and modeling;and transform behaviors into predictive indicators. An instance of the IMS named SYGISS, currently in operation within a large brewery organization, allows us to observe very interesting results: the extraction of indicators is done in less than 5 minutes whereas manual extraction used to take 14 days;the generation of dashboards is instantaneous whereas it used to take 12 hours;the interpretation of indicators is instantaneous whereas it used to take a day;forecasts are possible and are done in less than 5 minutes whereas they did not exist with the old management. These important contributions help to optimize the management of this organization.

Intelligent Parking Management System by Multi-Agent Approach:The Case of Urban Area of Tunis

By coordination and cooperation between multi-agents, this paper proposes the network of intelligent agents which can reduce the search time needed to finding a parking place. Based on multi-agent model, the fined solution is designed to help drivers in finding a parking space at anytime and anywhere. Three services are offered: the search for a vacant place, directions to a parking space and booking a place for parking. The results of this study generated by the platform MATSim transport simulation, show that our approach optimizes the operation of vehicles in a parking need with the aim of reducing congestion, and improve traffic flow in urban area. A comparison between the first method where the vehicles are random and the second method where vehicles are steered to vacant parking spaces shows that the minimization of time looking for a parking space could improve circulation by reducing the number of cars in the morning of 2% and 0.7% of the evening. In addition, the traffic per hour per day was reduced by approximately 4.17%.

Smart Energy Management System Using Machine Learning

Energy management is an inspiring domain in developing of renewable energy sources.However,the growth of decentralized energy production is revealing an increased complexity for power grid managers,inferring more quality and reliability to regulate electricity flows and less imbalance between electricity production and demand.The major objective of an energy management system is to achieve optimum energy procurement and utilization throughout the organization,minimize energy costs without affecting production,and minimize environmental effects.Modern energy management is an essential and complex subject because of the excessive consumption in residential buildings,which necessitates energy optimization and increased user comfort.To address the issue of energy management,many researchers have developed various frameworks;while the objective of each framework was to sustain a balance between user comfort and energy consumption,this problem hasn’t been fully solved because of how difficult it is to solve it.An inclusive and Intelligent Energy Management System(IEMS)aims to provide overall energy efficiency regarding increased power generation,increase flexibility,increase renewable generation systems,improve energy consumption,reduce carbon dioxide emissions,improve stability,and reduce energy costs.Machine Learning(ML)is an emerging approach that may be beneficial to predict energy efficiency in a better way with the assistance of the Internet of Energy(IoE)network.The IoE network is playing a vital role in the energy sector for collecting effective data and usage,resulting in smart resource management.In this research work,an IEMS is proposed for Smart Cities(SC)using the ML technique to better resolve the energy management problem.The proposed system minimized the energy consumption with its intelligent nature and provided better outcomes than the previous approaches in terms of 92.11% accuracy,and 7.89% miss-rate.

Application of Intelligent Power Consumption Management and Control Technology in Enterprise Off-site Enforcement

Regarding the current difficulties in SME(small and medium enterprise)supervision,especially considering the problem that the emission reduction task cannot be effectively implemented under the off-site daily supervision and the new normal of epidemic prevention with control of heavily polluted weather,a new type of intelligent power management technology has been proposed.Power information collection equipment and intelligent data collection and transmission terminal are installed to collect power consumption information of enterprise production facilities and pollution control facilities,and their operating conditions are monitored in 24 h.Abnormal operation alarm and closed-loop disposal management are provided through the software platform.The practical application of power monitoring technology in Rizhao City proves that the system alarms accurately and monitors efficiently.On the one hand,it has improved the efficiency of daily supervision of the ecological environment department,and can accurately investigate and correct corporate pollution control violations.On the other hand,it has enriched environmental supervision methods to accurately control the implementation of emergency emission reduction measures.The application of this technology has realized the transformation from civil defense to technical defense,from random law enforcement to precise law enforcement,and from on-site law enforcement to off-site law enforcement in the supervision of polluting enterprises in the jurisdiction,creating a new mode of off-site law enforcement for enterprises.

Intelligent Fault-tolerant Management of Electromechanical Equipment

In this paper, a method of intelligent fault tolerant management on electromechanical equipment is presented. It is based on condition monitoring of equipment and realized by condition prediction and condition control. An example is introduced and analyzed in this paper.

Intelligent Information Management in Aquaponics to Increase Mutual Benefits

Aquaponics are feedback and two player systems, in which fish and crops mutually benefit from one another and, therefore require close monitoring, management and control. Vast amount of data and information flow from the aquaponics plant itself with its huge amount of smart sensors for water quality, fish and plant growth, system state etc. and from the stakeholder, e.g., farmers, retailers and end consumers. The intelligent management of aquaponics is only possible if this data and information are managed and used in an intelligent way. Therefore, the main focus of this paper is to introduce an intelligent information management (IIM) for aquaponics. It will be shown how the information can be used to create services such as predictive analytics, system optimization and anomaly detection to improve the aquaponics system. The results show that the system enabled full traceability and transparency in the aquaponics processes (customers can follow what is going on at the farm), reduced water and energy use and increased revenue through early fault detection. In this, paper the information management approach will be introduced and the key benefits of the digitized aquaponics system will be given.

Reliability Management for Information System

An integrated intelligent management is presented to help organizations manage many heterogeneous resources in their information system. A general architecture of management for information system reliability is proposed, and the architecture from two aspects, process model and hierarchical model, described. Data mining techniques are used in data analysis. A data analysis system applicable to real-time data analysis is developed by improved data mining on the critical processes. The framework of the integrated management for information system reliability based on real-time data mining is illustrated, and the development of integrated and intelligent management of information system discussed.

An Intelligent Graph Edit Distance-Based Approach for Finding Business Process Similarities

There are numerous application areas of computing similarity between process models.It includes finding similar models from a repository,controlling redundancy of process models,and finding corresponding activities between a pair of process models.The similarity between two process models is computed based on their similarity between labels,structures,and execution behaviors.Several attempts have been made to develop similarity techniques between activity labels,as well as their execution behavior.However,a notable problem with the process model similarity is that two process models can also be similar if there is a structural variation between them.However,neither a benchmark dataset exists for the structural similarity between process models nor there exist an effective technique to compute structural similarity.To that end,we have developed a large collection of process models in which structural changes are handcrafted while preserving the semantics of the models.Furthermore,we have used a machine learning-based approach to compute the similarity between a pair of process models having structural and label differences.Finally,we have evaluated the proposed approach using our generated collection of process models.

基于BIM+技术的城市地下综合管廊智能运维管理研究

城市地下综合管廊是保障城市正常运转的“生命线”,关系着广大民众的日常生活和社会的稳定,如何使其平稳、高效运行已成为社会各界广为重视的问题。综合管廊运维管理涉及的主客体众多,以人工监管方式为主的传统运维方式效率低、准确率不足、安全性难以保障,因此,本文基于BIM+技术视角,为城市地下综合管廊的智能运维管理提供一种新思路,以期实现综合管廊管理的标准化、规范化,提高管理效率、降低管理成本。本文包括引言与结语共分为五个部分。首先,介绍本文的研究背景、意义,以及研究思路。其次,阐述综合管廊传统运维管理模式的现状及存在问题。然后,提出综合管廊运维管理的基本目标,并基于BIM+技术,尝试构建城市地下综合管廊的智能运维管理系统。最后,对文章进行总结并提出展望。

Clicking through the Clickstream: A Novel Statistical Modeling Approach to Improve Information Usage of Clickstream Data by E-Commerce Entities

Success or failure of an E-commerce platform is often reduced to its ability to maximize the conversion rate of its visitors. This is commonly regarded as the capacity to induce a purchase from a visitor. Visitors possess individual characteristics, histories, and objectives which complicate the choice of what platform features that maximize the conversion rate. Modern web technology has made clickstream data accessible allowing a complete record of a visitor’s actions on a website to be analyzed. What remains poorly constrained is what parts of the clickstream data are meaningful information and what parts are accidental for the problem of platform design. In this research, clickstream data from an online retailer was examined to demonstrate how statistical modeling can improve clickstream information usage. A conceptual model was developed that conjectured relationships between visitor and platform variables, visitors’ platform exit rate, boune rate, and decision to purchase. Several hypotheses on the nature of the clickstream relationships were posited and tested with the models. A discrete choice logit model showed that the content of a website, the history of website use, and the exit rate of pages visited had marginal effects on derived utility for the visitor. Exit rate and bounce rate were modeled as beta distributed random variables. It was found that exit rate and its variability for pages visited were associated with site content, site quality, prior visitor history on the site, and technological preferences of the visitor. Bounce rate was also found to be influenced by the same factors but was in a direction opposite to the registered hypotheses. Most findings supported that clickstream data is amenable to statistical modeling with interpretable and comprehensible models.

Thoughts on the Emergency Guarantee of Library Electronic Resources in the Post-Pandemic Era

In the post-pandemic era,libraries need to improve the emergency support of electronic resources and establish a relatively perfect electronic resource support system in order to adapt to the construction goal of the national emergency system as well as realize their own transformation and development.It must be realized through enhancing awareness and planning,strengthening policy support and top-level design,realizing rapid response and intelligent response,improving technical support,promoting resource synergy,integration,and sharing,strengthening community integration,as well as providing intelligent management and services.

An Architectural Modelfor Intelligent Network Management

Traditional network management approach involves the management of each vendor's equipment and network segment in isolation through its own proprietary element management system. It is necessary to set up a new network management architecture that calls for operation consolidation across vendor and technology boundaries. In this paper,an architectural model for Intelligent Network Management (INM) is presented. The INM system includes a manager system, which controls all subsystems and coordinates different management tasks; an expert system, which is responsible for handling particularly difficult problems, and intelligent agents, which bring the management closer to applications and user requirements by spreading intelligent agents through network segments or domain. In the expert system model proposed, especially an intelligent fault management system is given. The architectural model is to build the INM system to meet the need of managing modern network systems.

New technology foresight method based on intelligent knowledge management

The increasing importance of technology foresight has simultaneously raised the significance of methods that determine crucial areas and technologies.However,qualitative and quantitative methods have shortcomings.The former involve high costs and many limitations,while the latter lack expert experience.Intelligent knowledge management emphasizes human–machine integration,which combines the advantages of expert experience and data mining.Thus,we proposed a new technology foresight method based on intelligent knowledge management.This method constructs a technological online platform to increase the number of participating experts.A secondary mining is performed on the results of patent analysis and bibliometrics.Thus,forward-looking,innovative,and disruptive areas and relevant experts must be discovered through the following comprehensive process:Topic acquisition→topic delivery→topic monitoring→topic guidance→topic reclamation→topic sorting→topic evolution→topic conforming→expert recommendation.

An Optimized Approach to Vehicle-Type Classification Using a Convolutional Neural Network

There are numerous application areas of computing similarity between process models.It includes finding similar models from a repository,controlling redundancy of process models,and finding corresponding activities between a pair of process models.The similarity between two process models is computed based on their similarity between labels,structures,and execution behaviors.Several attempts have been made to develop similarity techniques between activity labels,as well as their execution behavior.However,a notable problem with the process model similarity is that two process models can also be similar if there is a structural variation between them.However,neither a benchmark dataset exists for the structural similarity between process models nor there exist an effective technique to compute structural similarity.To that end,we have developed a large collection of process models in which structural changes are handcrafted while preserving the semantics of the models.Furthermore,we have used a machine learning-based approach to compute the similarity between a pair of process models having structural and label differences.Finally,we have evaluated the proposed approach using our generated collection of process models.

Identifying Where the Values Come from IT-Innovations in Health and Social Care

Studies aimed to capture the effects of IT-innovations in health and social care have shown that there is a gap between expected and factual outcomes. Many decision makers feel the need to articulate an ideal end-state for their organiza-tions. Striking the balance between novelty and believability of such an ideal end-state is often tricky and they become neither satisfied with the ideal not the visioning. In this study, we explore the contribution of IT-innovations to health and social care. The results showed that coherence between context and IT-innovation is important to capture effects and outcomes. Being coherent rather than visionary contributes to identify where you are, as an organization, and to capture effects and outcomes that “make sense” in the context in question. The paper makes an exposition from the model building, algorithm design to performance analysis and contributes to the academic prosperity in Intelligent In-formation Management The knowledge generated is expected to provide input when identifying goals that IT-investments are supposed to achieve.

A Model-Based, Aspiration-Led Decision Support System NY-IEDSS

An AI-aided simulation system embedded in a model-based, aspiration-led decision support system NY-IEDSS is reported. The NY-IEDSS is designed for mid-term development strategic study of the Nanyang Region in Henan, China, and is getting beyond its prototype stage under the decision maker's (the end user) orientation. The integration of simulation model system, decision analysis and expert system for decision support in the system implementation was reviewed. The intent of the paper is to provide insight as to how system capability and acceptability can be enhanced by this integration. Moreover, emphasis is placed on problem orientation in applying the method.

IN2CLOUD: A novel concept for collaborative management of big railway data

In the EU Horizon 2020 Shift2Rail MultiAnnual Action Plan, the challenge of railway maintenance is generating knowledge from data and/or information. Therefore, we promote a novel concept called"IN2CLOUD," which comprises three sub-concepts, to address this challenge: 1) A hybrid cloud, 2) an intelligent cloud with hybrid cloud learning, and 3) collaborative management using asset-related data acquired from the intelligent hybrid cloud. The concept is developed under the assumption that organizations want/need to learn from each other(including domain knowledge and experience)but do not want to share their raw data or information.IN2CLOUD will help the movement of railway industry systems from "local" to "global" optimization in a collaborative way. The development of cutting-edge intelligent hybrid cloud-based solutions, including information technology(IT) solutions and related methodologies, will enhance business security, economic sustainability, and decision support in the field of intelligent asset management of railway assets.

An analysis on possibility of intelligent speed adaptation in terms of drivers' consciousness

Intelligent speed adaptation （ISA） is considered as an effective measure to reduce number of traffic accidents in the field of intelligent transportation systems （ITS）. On the other hand, its effects for traffic safety are still doubted by many people. To make the possibility analysis, an experiment is conducted by using driving simulator. Regarding ISA ap- proaches, there are three modes： mandatory, voluntary and advisory. Among them, the advisory type seems to be the easiest one to introduce. Therefore, we focus on the advisory mode in this study by considering ISA just at the beginning stage in Japan. The experiment consists of four steps： without ISA, ISA using pictures, ISA using voices and again without ISA. The outputs obtained from the driving simulator are analyzed combined with the consciousness of the participants. The experiment shows that the ISA can improve recognition of speed limitation especially for people who have random rambling or looking aside tendency. Furthermore, the ISA especially when using voices can contribute in changing the consciousness of people who are aggressive in driving. Their driving speeds can reduce so that positive effects on traffic safety can be concluded.