A knowledge-based architecture for implementing military geographical intelligence system on Intranet

Military geographical intelligence analysis in support of both tactical and strategic operation is a process that is associated with data gathering, processing, analyzing, and distribution. It is an important activity, carried out before the preparation of a military operation. A system that can assist in arranging support, exercise analysis training, and manage knowledge on military geographical intelligence have always been ultimate goals for both military intelligence units and intelligence officers alike. Therefore, it can be seen that research into the military geographical intelligence system is a critical and important research subject. This research investigates military geographical intelligence systems as a problem-solving procedure in terms of observing the military geographical intelligence operational procedure, generating situation analysis, and generating planning process. This paper intends to present a knowledge-based architecture that incorporates the function of case base, heuristic base, and rule base for implementing the military geographical intelligence system on Intranet.     

Types of feedback in a computer-based collaborative problem-solving group task

This study measured collaborative problem-solving processes and outcomes in a computer-based knowledge mapping environment. One hundred and twenty Asian American high school students were randomly assigned to be either a group leader, whose responsibility was to construct the map, or a group searcher, whose responsibility was to seek information and access feedback from a Web environment. Each group was randomly assigned to a feedback condition (knowledge of response feedback or adapted knowledge of response feedback). Results showed that adapted knowledge of response feedback was significantly more beneficial than knowledge of response feedback. Further, most of the study hypotheses were supported regarding the relationship between problem-solving processes and outcomes.     

Problem structuring methods in military command and control

In an authorized military hierarchy organization, the procedure of problem solving must be co-ordinated with the tasks of planning, directing, and controlling. In most combat situations, problem solving knowledge is acquired from an expert (commander) or a single group of experts (staff) in a military organization. Therefore, these multiple actors (commander and the staff), multiple perspectives (multi-expertise and knowledge types), incommensurable and/or conflicting interests (resource allocation and distribution among staff planning), important intangibles (ambiguous quantitative or qualitative apparatus), and key uncertainties (unexpected internal and external situations) are part of unstructured problem. In this article, military strategy and tactics are acquired as case knowledge, rule knowledge, and heuristic knowledge content in terms of representing combat formations and planning mechanism to support problem structuring and the solution of military command and control. By doing so, this article presents a knowledge-based system architecture, including case base, rule base, heuristic base, and learning paradigm, for the military command and control procedure with strategic guidance (commander’s strategy and tactics) and tactical planning (staff plans generation) system functions in terms of implementing problem structuring methods in military command and control.     

A strategic knowledge-based planning system for freight forwarding industry

In recent years, over half of the Hong Kong freight forwarding firms experienced a decline in business volume due to the growing challenge from the neighbour ports of Yantian and Shekou in Shenzhen, China, which operated in a much cheaper mode. In order to remain competitive, local freight forwarders in Hong Kong must establish a long-term union relationship with their customers such as the provision of customized logistics services. One of the ways is through the use of a co-loading shipment plan, which is a knowledge intensive and complex process involving multiple knowledge source and decision rules. This paper presents hybrid knowledge and model system, which integrates mathematical models with knowledge rules, in the formulation of such co-loading shipment plans. A strategic knowledge-based planning system, (SKPS) integrates knowledge rules with mathematical model for solving problems of co-loading shipment plans formulation and market constriction prevention, is proposed. The system was implemented in Elite World Logistics Service Limited (EW), a local freight forwarding company, for supporting the planning process of a co-loading shipping plan. The result reveals that both customer retention rate and resource utilization has increased significantly.     

Knowledge-based system for collaborative process specification

This paper presents an ontology-based approach for the design of a collaborative business process model (CBP). This CBP is considered as a specification of needs in order to build a collaboration information system (CIS) for a network of organizations. The study is a part of a model-driven engineering approach of the CIS in a specific enterprise interoperability framework that will be summarised. An adaptation of the Business Process Modelling Notation (BPMN) is used to represent the CBP model. We develop a knowledge-based system (KbS) which is composed of three main parts: knowledge gathering, knowledge representation and reasoning, and collaborative business process modelling. The first part starts from a high abstraction level where knowledge from business partners is captured. A collaboration ontology is defined in order to provide a structure to store and use the knowledge captured. In parallel, we try to reuse generic existing knowledge about business processes from the MIT Process Handbook repository. This results in a collaboration process ontology that is also described. A set of rules is defined in order to extract knowledge about fragments of the CBP model from the two previous ontologies. These fragments are finally assembled in the third part of the KbS. A prototype of the KbS has been developed in order to implement and support this approach. The prototype is a computer-aided design tool of the CBP. In this paper, we will present the theoretical aspects of each part of this KbS as well as the tools that we developed and used in order to support its functionalities.     

RESEDA: A knowledge-based advisory system for remote sensing

This article describes the design and implementation of RESEDA (RemoteSensorDataAnalysis), a knowledge-based system for the extraction of environmental information from digital raster images of the earth. The images may have been obtained from airborne or spaceborne sensors. Ancillary data is used to improve the results of the image analysis; in particular, we are using digital map data stored in a geographic information system for this purpose. The main goal of the system is to provide easy access to remote sensing technology for non-expert users, such as decision makers in environmental management.     

Roles for knowledge-based computer systems: Case studies in maternity care

The design of medical knowledge-based computer systems requires effective interdisciplinary communication for the development of a community sharing common goals and a common language for design. Over the past 9 years the Perinatal Research Group, an interdisciplinary team of computer scientists, engineers and clinicians, have developed a prototype knowledge-based computer system to aid clinicians in the care of women in labour. The group were uncertain which approach to adopt to progress this system from a prototype to a useful clinical tool to support decision making. A case study and activity theory analysis, of an existing clinical knowledge-based computer system in routine use, helped to resolve a number of communication and methodological issues that the design team encountered. Sharing of backgrounds and perspectives caused the design team to question previous assumptions and to explore alternative functions and roles for knowledge-based computer systems in maternity care. We are now undertaking a longitudinal case study and activity theory analysis of obstetric teams and women in labour to analyse the relationships between clinicians, patients and technology. This work will inform the development of our knowledge-based computer system to place the patient at the centre of the decision-making process.     

A knowledge-based approach for managing urban infrastructures

This paper presents a knowledge e-based approach dedicated to the efficient management, regulation, interactive and dynamic monitoring of urban infrastructures. This approach identifies the data and related treatments common to several municipal activities and defines the requirements and functionalities of the computer tools developed to improve the delivery and coordination of municipal services to the population. The resulting cooperative system called SIGIU is composed of a set of integrated operating systems (SYDEX) and the global planning and coordination system (SYGEC). The objective is to integrate the set of SYDEX and the SYGEC into a single coherent system for all the SIGIU's users according to their tasks, their roles, and their responsibilities within the municipal administration. SIGIU is provided by different measurement and monitoring instruments installed on some system's elements to be supervised. In this context, the information can be presented in different forms: video, pictures, data and alarms. One of SIGIU's objectives is the real-time management of urban infrastructures' control mechanisms. To carry out this process, the alarm control agent creates a mobile agent associated with the alarm, which is sent to a mobile station and warns an operator. Preliminary implementation results show that SIGIU supports effectively and efficiently the decision making process related to managing urban infrastructures.     

A framework using cluster-based hybrid network architecture for collaborative virtual surgery

Research on collaborative virtual environments (CVEs) opens the opportunity for simulating the cooperative work in surgical operations. It is however a challenging task to implement a high performance collaborative surgical simulation system because of the difficulty in maintaining state consistency with minimum network latencies, especially when sophisticated deformable models and haptics are involved. In this paper, an integrated framework using cluster-based hybrid network architecture is proposed to support collaborative virtual surgery. Multicast transmission is employed to transmit updated information among participants in order to reduce network latencies, while system consistency is maintained by an administrative server. Reliable multicast is implemented using distributed message acknowledgment based on cluster cooperation and sliding window technique. The robustness of the framework is guaranteed by the failure detection chain which enables smooth transition when participants join and leave the collaboration, including normal and involuntary leaving. Communication overhead is further reduced by implementing a number of management approaches such as computational policies and collaborative mechanisms. The feasibility of the proposed framework is demonstrated by successfully extending an existing standalone orthopedic surgery trainer into a collaborative simulation system. A series of experiments have been conducted to evaluate the system performance. The results demonstrate that the proposed framework is capable of supporting collaborative surgical simulation.     

A knowledge-based approach for duplicate elimination in data cleaning

Existing duplicate elimination methods for data cleaning work on the basis of computing the degree of similarity between nearby records in a sorted database. High recall can be achieved by accepting records with low degrees of similarity as duplicates, at the cost of lower precision. High precision can be achieved analogously at the cost of lower recall. This is the recall–precision dilemma. We develop a generic knowledge-based framework for effective data cleaning that can implement any existing data cleaning strategies and more. We propose a new method for computing transitive closure under uncertainty for dealing with the merging of groups of inexact duplicate records and explain why small changes to window sizes has little effect on the results of the sorted neighborhood method. Experimental study with two real-world datasets show that this approach can accurately identify duplicates and anomalies with high recall and precision, thus effectively resolving the recall–precision dilemma.     

Towards ubiquitous tourist service coordination and process integration: A collaborative travel agent system architecture with semantic web services

With the recent advances in Internet and mobile technologies, there are increasing demands for ubiquitous access to tourist information systems for service coordination and process integration. However, due to disparate tourist information and service resources such as airlines, hotels, tour operators, it is still difficult for tourists to use them effectively during their trips or even in the planning stage. Neither can current tourist portals assist tourists proactively. To overcome this problem, we propose a Collaborative Travel Agent System (CTAS) based on a scalable, flexible, and intelligent Multi-Agent Information System (MAIS) architecture for proactive aids to Internet and mobile users. We also employ Semantic Web technologies for effective organization of information resources and service processes. We formulate our MAIS architecture for CTAS further with agent clusters based on a case study of a large service-oriented travel agency. Agent clusters may comprise several types of agents to achieve the goals involved in the major processes of a tourist’s trip. We show how agents can make use of ontology from the Semantic Web to help tourists better plan, understand, and specify their requirements collaboratively with the CTAS. We further illustrate how this can be successfully implemented with Web service technologies to integrate disparate Internet tourist resources. To conclude, we discuss and evaluate our approach from different stakeholders’ perspectives.

Information technology for collaborative advantage in healthcare revisited

Interorganizational systems are expected to provide opportunities for various stakeholders, often competitors, to collaborate. At the moment, there is a great need for research evidence on the factors facilitating or impeding the achievement of collaborative advantage between interorganizational systems stakeholders. A recent contribution has been the use of a health-information network case to derive lessons for policy makers in this respect. The development and use of the NHSnet in the United Kingdom provides an opportunity to review these lessons in a different context of health-information exchange. Combined with the use of stakeholder analysis, these lessons can enhance our understanding of the context, the stakeholders involved and affected by the network, their interests and their perceptions of collaborative advantage. It, therefore, provides useful insights in the lessons that healthcare policy makers can apply in the development and use of a collaborative network. Further theoretical and practical research is, however, needed to improve our understanding of success and failure factors for the achievement of collaborative advantage in different environments.     

A knowledge-based system for the prediction of surface roughness in turning process

In the present work, a knowledge-based system is developed for the prediction of surface roughness in turning process. Neural networks and fuzzy set theory are used for this purpose. Knowledge acquired from the shop floor is used to train the neural network. The trained network provides a number of data sets, which are fed to a fuzzy-set-based rule generation module. A large number of IF–THEN rules are generated, which can be reduced to a smaller set of rules by using Boolean operations. The developed rule base may be used for predicting surface roughness for given process variables as well as for the prediction of process variables for a given surface roughness. The concise set of rules helps the user in understanding the behavior of the cutting process and to assess the effectiveness of the model. The performance of the developed knowledge-based system is studied with the experimental data of dry and wet turning of mild steel with HSS and carbide tools.     

A method for topological entity correspondence in a replicated collaborative CAD system

In order to utilize the potential advantages of replicated collaborative CAD system to support natural, free, fast and less-constrained multi-user human-to-human interaction, a local-locking mechanism, which can provide fast modeling response, is adopted as concurrency control mechanism for a replicated on-line collaborative CAD system. A human–human interactive modeling is achieved by immediate local execution of modeling operations and exchange of modeling operations across all collaborative sites real-time. In particular, an approach to achieve topological entity correspondence across collaborative sites during modeling procedure, which is critical to guarantee the correctness and consistency of collaborative modeling result, is proposed. A prototype system based on the ACIS geometric modeling kernel is implemented to verify availability of the proposed solution.     

A knowledge-based decision support system for the management of parts and tools in FMS

Flexible manufacturing systems (FMS) are very complex systems with large part, tool, and information flows. The aim of this work is to develop a knowledge-based decision support system (KBDSS) for short-term scheduling in FMS strongly influenced by the tool management concept to provide a significant operational control tool for a wide range of machining cells, where a high level of flexibility is demanded, with benefits of more efficient cell utilization, greater tool flow control, and a dependable way of rapidly adjusting short-term production requirements. Development of a knowledge-based system to support the decision making process is justified by the inability of decision makers to diagnose efficiently many of the malfunctions that arise at machine, cell, and entire system levels during manufacturing. In this context, this paper proposes three knowledge-based models to ease the decision making process: an expert production scheduling system, a knowledge-based tool management decision support systems, and a tool management fault diagnosis system. The entire system has been created in a hierarchical manner and comprises more than 400 rules. The expert system (ES) was implemented in a commercial expert system shell, Knowledge Engineering System (KES) Production System (PS).     

Strategies for implementing decision technology systems successfully: a field study in army housing management

A decision technology system (DTS) has been proposed to provide direct support for the entire decision‐making process. In the 1990s, the concept was implemented in stages to facilitate US Army housing management. This implementation has been the first successful field application of the DTS theory. Recent enhancements confirmed earlier insights and offered important new lessons in developing, implementing, and benefiting from DTSs. This paper discusses the original insights and fresh lessons. To provide a context, the article first briefly describes the enhancements and presents a typical, but streamlined, system session. The paper then summarizes the documented gains from implementing the DTS theory, reports the utilized strategies, and infers the implications for the systems analysis and design process.     

An effective architecture for Decision Support Systems

Decision Support Systems (DSS) are, by nature, general- purpose systems, because they must support a variety of managers who have different decision styles and different problems. However, it seems that no effective general-purpose DSS have yet come into existence, although the components of DSS such as data base technology, modeling techniques, inexpensive graphic display etc., have progressed to the point where we should now be able to build effective DSS.This shortcoming seems to result from the following fact: Research on decision support has focused on data enlargement and model refinement, however, little attention has been paid to DSS architecture which integrates these components of DSS. It has not been well appreciated that DSS architecture itself facilitates learning about unstructured-problem solving and enables system evolution.In this paper, we propose a DSS architecture based on the study of unstructured-problem solving and considerations of the needs of managers as non-computer specialists. We illustrate this with a system realized using this architecture.     

Comparing a knowledge-based and a data-driven method in querying data streams for system fault detection: A hydraulic drive system application

The field of fault detection and diagnosis has been the subject of considerable interest in industry. Fault detection may increase the availability of products, thereby improving their quality. Fault detection and diagnosis methods can be classified in three categories: data-driven, analytically based, and knowledge-based methods.     

无人驾驶坦克自主作战决策系统框架

提出了一个分布式解决无人驾驶坦克自主作战决策的框架，将自主作战、动态任务规划和任务策略的智能评估等思想引入无人驾驶坦克自主作战决策系统。包括以下两个重要内容：主体个体的能力和职责；信息和知识如何在主体之间传播使得他们能准确地完成作战任务。文中重点是无人驾驶坦克自主作战决策系统中主体之间动态知识的交换。主体确保自己的行为是一种动态的经验操作和直接与其他主体交流事实、需求和规则的结合。在各个主体中，知识可以作为事实、规则、需求的结合体来传播交换。     

The HORSE framework: A reference architecture for cyber-physical systems in hybrid smart manufacturing

In the Industry 4.0 era, manufacturers strive to remain competitive by using advanced technologies such as collaborative robots, automated guided vehicles, augmented reality support and smart devices. However, only if these technological advancements are integrated into their system context in a seamless way, they can deliver their full potential to a manufacturing organization. This integration requires a system architecture as a blueprint for positioning and interconnection of the technologies. For this purpose, the HORSE framework, resulting from the HORSE EU H2020 project, has been developed to act as a reference architecture of a cyber-physical system to integrate various Industry 4.0 technologies and support hybrid manufacturing processes, i.e., processes in which human and robotic workers collaborate. The architecture has been created using design science research, based on well-known software engineering frameworks, established manufacturing domain standards and practical industry requirements. The value of a reference architecture is mainly established by application in practice. For this purpose, this paper presents the application and evaluation of the HORSE framework in 10 manufacturing plants across Europe, each with its own characteristics. Through the physical deployment and demonstration, the framework proved its goal to be basis for the well-structured design of an operational smart manufacturing cyber-physical system that provides horizontal, cross-functional management of manufacturing processes and vertical control of heterogeneous technologies in work cells. We report on valuable insights on the difficulties to realize such systems in specific situations. The experiences form the basis for improved adoption, further improvement and extension of the framework. In sum, this paper shows how a reference architecture framework supports the structured application of Industry 4.0 technologies in manufacturing environments that so far have relied on more traditional digital technology.