960 resultados para Computer Engineering|Electrical engineering
Resumo:
Recent advances in tissue-engineered cartilage open the door to new clinical treatments of joint lesions. Common to all therapies with in-vitro-engineered autografts is the need for optimal fit of the construct to allow screwless implantation and optimal integration into the live joint. Computer-assisted surgery (CAS) techniques are prime candidates to ensure the required accuracy, while at the same time simplifying the procedure. A pilot study has been conducted aiming at assembling a new set of methods to support ankle joint arthroplasty using bioengineered autografts. Computer assistance allows planning of the implant shape on a computed tomography (CT) image, manufacturing the construct according to the plan, and interoperatively navigating the surgical tools for implantation. A rotational symmetric model of the joint surface was used to avoid segmentation of the CT image; new software was developed to determine the joint axis and make the implant shape parameterizable. A complete cycle of treatment from planning to operation was conducted on a human cadaveric foot, thus proving the feasibility of computer-assisted arthroplasty using bioengineered autografts
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A novel computer-assisted injection device for the delivery of highly viscous bone cements in vertebroplasty is presented. It addresses the shortcomings of manual injection systems ranging from low-pressure and poor level of control to device failure. The presented instrument is capable of generating a maximum pressure of 5000 kPa in traditional 6-ml syringes and provides an advanced control interface for precise cement delivery from outside radiation fields emitted by intraoperative imaging systems. The integrated real-time monitoring of injection parameters, such as flow-rate, volume, pressure, and viscosity, simplifies consistent documentation of interventions and establishes a basis for the identification of safe injection protocols on the longer term. Control algorithms prevent device failure due to overloading and provide means to immediately stop cement flow to avoid leakage into adjacent tissues.
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Many schools do not begin to introduce college students to software engineering until they have had at least one semester of programming. Since software engineering is a large, complex, and abstract subject it is difficult to construct active learning exercises that build on the students’ elementary knowledge of programming and still teach basic software engineering principles. It is also the case that beginning students typically know how to construct small programs, but they have little experience with the techniques necessary to produce reliable and long-term maintainable modules. I have addressed these two concerns by defining a local standard (Montana Tech Method (MTM) Software Development Standard for Small Modules Template) that step-by-step directs students toward the construction of highly reliable small modules using well known, best-practices software engineering techniques. “Small module” is here defined as a coherent development task that can be unit tested, and can be car ried out by a single (or a pair of) software engineer(s) in at most a few weeks. The standard describes the process to be used and also provides a template for the top-level documentation. The instructional module’s sequence of mini-lectures and exercises associated with the use of this (and other) local standards are used throughout the course, which perforce covers more abstract software engineering material using traditional reading and writing assignments. The sequence of mini-lectures and hands-on assignments (many of which are done in small groups) constitutes an instructional module that can be used in any similar software engineering course.
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Much of the knowledge about software systems is implicit, and therefore difficult to recover by purely automated techniques. Architectural layers and the externally visible features of software systems are two examples of information that can be difficult to detect from source code alone, and that would benefit from additional human knowledge. Typical approaches to reasoning about data involve encoding an explicit meta-model and expressing analyses at that level. Due to its informal nature, however, human knowledge can be difficult to characterize up-front and integrate into such a meta-model. We propose a generic, annotation-based approach to capture such knowledge during the reverse engineering process. Annotation types can be iteratively defined, refined and transformed, without requiring a fixed meta-model to be defined in advance. We show how our approach supports reverse engineering by implementing it in a tool called Metanool and by applying it to (i) analyzing architectural layering, (ii) tracking reengineering tasks, (iii) detecting design flaws, and (iv) analyzing features.
Resumo:
Enterprise Applications are complex software systems that manipulate much persistent data and interact with the user through a vast and complex user interface. In particular applications written for the Java 2 Platform, Enterprise Edition (J2EE) are composed using various technologies such as Enterprise Java Beans (EJB) or Java Server Pages (JSP) that in turn rely on languages other than Java, such as XML or SQL. In this heterogeneous context applying existing reverse engineering and quality assurance techniques developed for object-oriented systems is not enough. Because those techniques have been created to measure quality or provide information about one aspect of J2EE applications, they cannot properly measure the quality of the entire system. We intend to devise techniques and metrics to measure quality in J2EE applications considering all their aspects and to aid their evolution. Using software visualization we also intend to inspect to structure of J2EE applications and all other aspects that can be investigate through this technique. In order to do that we also need to create a unified meta-model including all elements composing a J2EE application.
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eLearning supports the education in certain disciplines. Here, we report about novel eLearning concepts, techniques, and tools to support education in Software Engineering, a subdiscipline of computer science. We call this "Software Engineering eLearning". On the other side, software support is a substantial prerequisite for eLearning in any discipline. Thus, Software Engineering techniques have to be applied to develop and maintain those software systems. We call this "eLearning Software Engineering". Both aspects have been investigated in a large joint, BMBF-funded research project, termed MuSofT (Multimedia in Software Engineering). The main results are summarized in this paper.
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This report presents the proceedings of the Biochemical Engineering Symposium held at Kansas State University, April 28, 1973. Since a number of the contributions will be published in detail elsewhere, only brief summaries of each contribution are included here. Requests for additional information on projects conducted at The University of Nebraska should be directed to Dr. Peter J. Reilly, and those at Kansas State University to the editors. ContentsKenneth J. Jacobson, Andrew H.C. Chan, and Raymond C. Eliason, "Properties and Utilization of Small Particulates in Cattle Manure" Cady R. Engler and James S. Yohn, "Protein from Manure" Robert J. Williams, "Kinetics of Sucrose Inversion Using Invertase Immobilized on Hollow Fibers of Cellulose Acetate" David F. Aldis and Thomas A. Carlisle, "Study of a Triiodide-Resin Complex Disinfection System" John C. Heydweiller, "Modeling and Analysis of Symbiotic Growth" Kenneth J. Jacobson, "Synchronized Growth of the Blue Green Alga Microcystis aeruginosa" Clarence C. Y. Ron arui Lincoln L. S. Yang, "Computer Modeling of the Reductive Pentose Phosphate Cycle" Ming-ching T. Kuo, "Application of a Parallel Biochemical Oxidation Kinetic Model to the Design of an Activated Sludge System Including a Primary Clarifier" Prakash N. Mishra, "Optimal Synthesis of Water Renovation Systems"
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This booklet contains abstracts of papers presented at a biochemical engineering symposium conducted at the University of Nebraska-Lincoln on April 29, 1972. This was the second annual symposium on this subject, the first having been held at Kansas State University on June 4, 1971. It is expected that future symposia will alternate between the two campuses. ContentsS.H. Lin, Kansas State University, "Enzyme Reaction in a Tubular Reactor with Laminar Flow" Gregory C. Martin, University of Nebraska, "Estimation of Parameters in Population Models for Schizosaccharomyces pombe from Chemostat Data" Jaiprakash S. Shastry and Prakash N. Mishra, Kansas State University, "Immobilized Enzymes: Analysis of Ultrafiltration Reactors" Mark D. Young, University of Nebraska, "Modelling Unsteady-State Two-Species Data Using Ramkrishna's Staling Model" G.C.Y. Chu, Kansas State University, "Optimization of Step Aeration Waste Treatment Systems Using EVOP" Shinji Goto, University of Nebraska, "Growth of the Blue-Green Alga Microcytis aeruginosa under Defined Conditions" Prakash N. Mishra and Thomas M.C. Kuo, Kansas State University, "Digital Computer Simulation of the Activated Sludge System: Effect of Primary Clarifier on System Performance" Mark D. Young, University of Nebraska, "Aerobic Fermentation of Paunch Liquor"
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The goal of this roadmap paper is to summarize the state-of-the-art and identify research challenges when developing, deploying and managing self-adaptive software systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-adaptive solutions, software engineering processes for self-adaptive systems, from centralized to decentralized control, and practical run-time verification & validation for self-adaptive systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-adaptive systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.
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Course materials for e-learning are a special type of information system (IS). Thus, in the development of educational material one may learn from principles, methods, and tools that originated in the Software Engineering (SE) discipline and that are relevant in similar ways in "Instructional Engineering". An important SE principle is mo dularization, which supports properties like reusability and adaptability of code. To foster the adaptability of courseware we present a concept in which learning material is organized as a library of modular course objects. A certain lecturer may customize the courseware according to his specific course requirements. He must consider logical dependencies of and relationship integrity between selected course objects. We discuss integrity issues that have to be regarded for the composition of consistent course materials.
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Multidisciplinary training is widely appreciated in industry and business, and nevertheless usually is not addressed in the early stages of most undergraduate programs. We outline here a multidisciplinary course for undergraduates studying engineering in which mathematics would be the common language, the transverse tool. The goal is motivating students to learn more mathematics and as a result, improve the quality of engineering education. The course would be structured around projects in four branches in engineering: mechanical, electrical, civil and bio-tech. The projects would be chosen among a wide variety of topics in engineering practice selected with the guidance of professional engineers. In these projects mathematics should interact with at least two other basic areas of knowledge in engineering: chemistry, computers science, economics, design or physics.
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Nowadays, computer simulators are becoming basic tools for education and training in many engineering fields. In the nuclear industry, the role of simulation for training of operators of nuclear power plants is also recognized of the utmost relevance. As an example, the International Atomic Energy Agency sponsors the development of nuclear reactor simulators for education, and arranges the supply of such simulation programs. Aware of this, in 2008 Gas Natural Fenosa, a Spanish gas and electric utility that owns and operate nuclear power plants and promotes university education in the nuclear technology field, provided the Department of Nuclear Engineering of Universidad Politécnica de Madrid with the Interactive Graphic Simulator (IGS) of “José Cabrera” (Zorita) nuclear power plant, an industrial facility whose commercial operation ceased definitively in April 2006. It is a state-of-the-art full-scope real-time simulator that was used for training and qualification of the operators of the plant control room, as well as to understand and analyses the plant dynamics, and to develop, qualify and validate its emergency operating procedures.
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In the beginning of the 90s, ontology development was similar to an art: ontology developers did not have clear guidelines on how to build ontologies but only some design criteria to be followed. Work on principles, methods and methodologies, together with supporting technologies and languages, made ontology development become an engineering discipline, the so-called Ontology Engineering. Ontology Engineering refers to the set of activities that concern the ontology development process and the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. Thanks to the work done in the Ontology Engineering field, the development of ontologies within and between teams has increased and improved, as well as the possibility of reusing ontologies in other developments and in final applications. Currently, ontologies are widely used in (a) Knowledge Engineering, Artificial Intelligence and Computer Science, (b) applications related to knowledge management, natural language processing, e-commerce, intelligent information integration, information retrieval, database design and integration, bio-informatics, education, and (c) the Semantic Web, the Semantic Grid, and the Linked Data initiative. In this paper, we provide an overview of Ontology Engineering, mentioning the most outstanding and used methodologies, languages, and tools for building ontologies. In addition, we include some words on how all these elements can be used in the Linked Data initiative.