User centered neuro-fuzzy energy management through semantic-based optimization

This paper presents a cloud-based building energy management system, underpinned by semantic middleware, that integrates an enhanced sensor network with advanced analytics, accessible through an intuitive Web-based user interface. The proposed solution is described in terms of its three key layers: 1) user interface; 2) intelligence; and 3) interoperability. The system’s intelligence is derived from simulation-based optimized rules, historical sensor data mining, and a fuzzy reasoner. The solution enables interoperability through a semantic knowledge base, which also contributes intelligence through reasoning and inference abilities, and which are enhanced through intelligent rules. Finally, building energy performance monitoring is delivered alongside optimized rule suggestions and a negotiation process in a 3-D Web-based interface using WebGL. The solution has been validated in a real pilot building to illustrate the strength of the approach, where it has shown over 25% energy savings. The relevance of this paper in the field is discussed, and it is argued that the proposed solution is mature enough for testing across further buildings

ASSEMBLY DIFFERENTIATION IN CAD SYSTEMS

This work presents a data model for differentiating and sharing assembly design (AsD) information during collaborative design. Joints between parts are an important aspect of assembly models that are often ambiguous when sharing of models takes place. Although various joints may have similar geometries and topologies, their joining methods and process parameters may vary significantly. It is possible to attach notes and annotations to geometric entities within CAD environments in order to distinguish joints; however, such textual information does not readily prepare models for sharing among collaborators or downstream processes such as simulation and analysis. At present, textual information must be examined and interpreted by the human designer and cannot be interpreted or utilized by the computer; thus, making the querying of information potentially cumbersome and time consuming.This work presents an AsD ontology that explicitly represents assembly constraints, including joining constraints, and infers any remaining implicit ones. By relating concepts through ontology technology rather than just defining an arbitrary data structure, assembly and joining concepts can be captured in their entirety or extended as necessary. By using the knowledge captured by the ontology, similar-looking joints can be differentiated and the collaboration and downstream product development processes further automated, as the semantics attached to the assembly model prepares it for use within the Semantic Web

Knowledge-based processing for aircraft flight control

This Contractor Report documents research in Intelligent Control using knowledge-based processing in a manner dual to methods found in the classic stochastic decision, estimation, and control discipline. Such knowledge-based control has also been called Declarative, and Hybid. Software architectures were sought, employing the parallelism inherent in modern object-oriented modeling and programming. The viewpoint adopted was that Intelligent Control employs a class of domain-specific software architectures having features common over a broad variety of implementations, such as management of aircraft flight, power distribution, etc. As much attention was paid to software engineering issues as to artificial intelligence and control issues. This research considered that particular processing methods from the stochastic and knowledge-based worlds are duals, that is, similar in a broad context. They provide architectural design concepts which serve as bridges between the disparate disciplines of decision, estimation, control, and artificial intelligence. This research was applied to the control of a subsonic transport aircraft in the airport terminal area

IoT-based Asset Management System for Healthcare-related Industries

The healthcare industry has been focusing efforts on optimizing inventory management procedures through the incorporation of Information and Communication Technology, in the form of tracking devices and data mining, to establish ideal inventory models. In this paper, a roadmap is developed towards a technological assessment of the Internet of Things (IoT) in the healthcare industry, 2010–2020. According to the roadmap, an IoT-based healthcare asset management system (IoT-HAMS) is proposed and developed based on Artificial Neural Network (ANN) and Fuzzy Logic (FL), incorporating IoT technologies for asset management to optimize the supply of resources

Freeform User Interfaces for Graphical Computing

報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専

Function-Based Computer Aided Conceptual Design Support Tool

Conceptual design is considered as the most critical and important phase of design process. It is the stage where product’s fundamental features are determined, large proportion of the lifecycle cost of the product is committed, and other major decisions are made, which have significant impact on the downstream design and related manufacturing processes. It is a knowledge intensive process where diverse knowledge and several years of experience are put together to design quality and cost effective products. Unfortunately, computer support systems for this phase are lagging behind compared to the currently available commercial computer aided design (CAD) tools for the later stage of design to reduce the designers workload and product development time. The overall goal of this research is to provide designers with computational tool that support conceptual design process. To achieve this goal a methodology that integrates systematic design approach with knowledge-based system is proposed in this thesis. Accordingly, a framework of computer based computational tool known as conceptual design support tool (CDST) is developed using the proposed methodology. The tool assists designers in performing functional modeling by providing standard vocabularies of functions in the form of function library, generate concepts stored in the database from previous designs, display the generated concepts on the morphology chart, combine the concepts and evaluate the concepts variants. Concepts from subsea processing equipment design have been collected and saved in the database. The tool also accepts new concepts from the designer through its knowledge acquisition system to be saved in the database for future use. In doing so, it is possible to integrate human creativity with data handling capabilities of computers to perform conceptual design more efficiently than solely manual design. The tool can also be used as a knowledge management system to preserve expert’s knowledge and train novice designers. The applicability of the proposed methodology and developed tool is illustrated and validated by using a case study and validation test conducted by independent evaluators

A novel distributed architecture for IoT image processing using low-cost devices and open internet standards

Industry 4.0 can be defined as the integration of computers and automation to current industrial processes, with addition of smart and autonomous systems leveraged by machine learning techniques. In this scenario, a compact, dependable and fast controller is desired, featuring low energy consumption, easily programming and maintenance, with no mobile parts. Nowadays, computing power in single board computers, e.g. the Raspberry Pi among others, has been increased at a very important rate. In just three generations, Pi computers offer almost a two-fold speed gain, when compared to first models. Its design, an underlying video driver with general capabilities of regular OSes, makes them quite suitable to build image processing systems at very low cost, with no mobile parts and low energy consumption. However, designing such a system for industrial image processing is a tough challenge, since it implies to integrate cameras, image processing libraries, database servers and application software with graphical user interface, in an already resource constrained device. This work presents a new architecture for this kind of systems, by means of open internet standards, using a self-contained, high performance web server to publish a RESTful API and a set of web pages that use latest HTML5 capabilities to manage USB webcams and system data. This proposal also integrates OpenCV as a compiled script on client-side using the new WASM paradigm, with an optimized storage for images using -industry-standard RDBMS and a modular design that can target Windows and Linux as well.Sociedad Argentina de Informática e Investigación Operativ

Smart Intrusion Detection System for DMZ

Prediction of network attacks and machine understandable security vulnerabilities are complex tasks for current available Intrusion Detection System [IDS]. IDS software is important for an enterprise network. It logs security information occurred in the network. In addition, IDSs are useful in recognizing malicious hack attempts, and protecting it without the need for change to client‟s software. Several researches in the field of machine learning have been applied to make these IDSs better a d smarter. In our work, we propose approach for making IDSs more analytical, using semantic technology. We made a useful semantic connection between IDSs and National Vulnerability Databases [NVDs], to make the system semantically analyzed each attack logged, so it can perform prediction about incoming attacks or services that might be in danger. We built our ontology skeleton based on standard network security. Furthermore, we added useful classes and relations that are specific for DMZ network services. In addition, we made an option to mallow the user to update the ontology skeleton automatically according to the network needs. Our work is evaluated and validated using four different methods: we presented a prototype that works over the web. Also, we applied KDDCup99 dataset to the prototype. Furthermore,we modeled our system using queuing model, and simulated it using Anylogic simulator. Validating the system using KDDCup99 benchmark shows good results law false positive attacks prediction. Modeling the system in a queuing model allows us to predict the behavior of the system in a multi-users system for heavy network traffic