|Soft Computing for Human Spermatozoa Morphology|
A fuzzy data fusion approach was used for human sperm morphology recognition analysis using 3-CCD camera image data. Fuzzy operators were used to create the relationship between abnormal sperm morphology and normal sperm aberrations after digitizing the images. The approaches have focused on frequencies of sperm with either abnormal morphology in semen analysis samples. In order to establish whether various shapes of membership functions, the authors would classify the morphology according to their head, tail, and neck shapes into symmetrical, asymmetrical, irregular and amorphous categories based on the fuzzy region. The images results demonstrated how these findings facilitated approaches on the 100 semen samples. The average probability of morphology recognition analysis was equal to 95% and the average probability of unknown parameter was equal to 4.5%. The fuzzy fusion morphology provided a unified and consistent framework to express different shapes of human spermatozoa.
Solution of the System Structure Reconstruction Problem Based on Generalization of Tellegen’s Principle
Josef HRUSAK, Daniel MAYER, Milan STORK
An extraordinary generality, conceptual simplicity and practical usefulness of the Tellegen’s theorem is well known in the field of electrical engineering . It is one of few general theoretical results that apply in non-linear and time-varying situations, too. For standard linear electrical network models with constant parameters many classical results of electrical circuits theory can be derived as direct consequences of it.
In the paper a more general class of abstract strictly causal system representations is addressed. A new problem, that of the abstract state space system representation structure reconstruc-tion has been formulated in , and partially solved in  and . In this paper a new approach based on a generalized form of the classical Tellegen’s principle, providing an equivalence class of physically as well as mathematically correct solutions is developed and some well-known, as well as new results are shown to be straightforward consequences of the derived struc-ture. Some connections of dissipativity, conservativity, state and parameter minimality, instability and chaos with system representation structures are investigated from this point of view. Analytical results are illustrated by a number of typical examples and visualized by simulations.
Synthesis of State Machines fromMultiple Interrelated Scenarios Using Dependency Diagrams
Simona Vasilache, Jiro Tanaka
Requirements specification is one of the most important phases in developing a software application. In defining the behavior of a system, requirements specifications make use of a number of scenarios that are interrelated in many ways. Most of the current approaches, even though giving directions on how to translate them into state machines, treat each scenario separately. Because different relationships between scenarios result in different state machines, we believe it is significant to emphasize and represent these relationships. In order to illustrate them we propose a new type of diagrams named dependency diagrams. We offer a set of rules and steps for the synthesis of state machines from multiple inter-related scenarios, based on the initial scenarios and on the newly introduced dependency diagrams, as a means to describe the requirements specifications and to offer support during the design and implementation phases of developing a system.
Teaching Financial Data Mining using Stocks and Futures Contracts
Financial data mining models is considered to be “the hardest way to make easy money.” Data miners are certainly motivated by the prospect of discovering a financial “Holy Grail.” However, designing and implementing a successful model poses many intellectual challenges. These include securing and cleaning data; acquiring a sufficient amount of financial domain knowledge; bounding the complexity of the problem; and properly validating results. Teaching financial data mining is especially difficult due to the student’s limited financial domain knowledge and the relatively short period (one semester) for building financial models. This paper describes an application of a financial data mining term project based on Stock and E-Mini futures contracts and discusses “lessons learned” from assigning similar term projects over six different semesters. Results of each case study results are presented and discussed.
The value of criticality: Gauging issues in supply nets
Jochen Speyerer, Andrew Zeller
Modern day supply chains encompass both geographically disparate activities and planning processes for multiple companies or various interdependent time horizons. To be able to effectively manage these supply chains it is not only necessary to strategically plan the future of the underlying network of participating companies but also to schedule and monitor the ongoing production and logistics activities on a regular basis. Unfortunately, available information systems do not provide an adequate way to handle disruptions. If at all, they employ inter-organizational workflows to keep track of activities and notify a pre-set recipient in case something goes wrong. But in order to be able to focus their attention on urgent problems, managers need a means to gauge the criticality of a symptom. This paper tries to fill this gap by introducing a Value of Criticality (VoC) that indicates how serious the faced deviation really is.
Towards Automatic Music Transcription: Extraction of MIDI-Data out of Polyphonic Piano Music
Driven by the increasing amount of music available electronically the need of
automatic search and retrieval systems for music becomes more and more
important. In this paper an algorithm for automatic transcription of
polyphonic piano music into MIDI data is presented, which is a very
interesting basis for database applications and music analysis. The first part
of the algorithm performs a note accurate temporal audio segmentation. The
resulting segments are examined to extract the notes played in the second
part. An algorithm for chord separation based on Independent Subspace Analysis
is presented. Finally, the results are used to build a MIDI file.
A Computerized Navigation Support for Maneuvering Clustered Ship Groups in Close Proximity
Akira Kawaguchi, Xiozhen Xiong, Masaaki Inaishi, Hayato Kondo
The aim of this research is to investigate navigation behaviors and effects of interferences of multiple ocean-going vessels that share the same sailing course like a transport convoy. Detecting and evading other clusters in close proximity is one of the most important tasks in navigation as contacting these will potentially cause serious risks to the ship. Focus of this paper is to investigate computational capabilities added to the so-called ship cluster behavior model of our previous work. Enhancement is made to predict a risky situation and to guide for multiple ship clusters, enabling them to move safely and avoid contact with each other. Such improvement is critical, especially when the traffic becomes congested with a number of clustered ship groups moving to distinctive directions. Foundations
for and preliminary experimental results of this study are discussed.
A Learning Object Approach To Evidence based learning
Zabin Visram, Bruce Elson, Patricia Reynolds
This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology
Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner’s to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has meant increasingly, there is a desperate need to adopt wireless schemes, whereby bespoke courses can be developed to help practitioners keep up with expanding knowledge base. Evidently, without current best evidence, practice risks becoming rapidly out of date, to the detriment of the patient.
There is a need to provide a tactical, operational and effective environment, which allows professional to update their education, and complete specialised training, just-in-time, in their own time and location.
Following this demand in the marketplace the information engineering group, in combination with several medical and dental schools, set out to develop and design a conceptual framework which form the basis of pioneering research, which at last, enables practitioner’s to adopt a philosophy of life long learning.
The body and structure of this framework is subsumed under the term Object oriented approach to Evidence Based learning, Just-in-time, via Internet sustained by Reusable Learning Objects (The OEBJIRLO Progression). The technical pillars which permit this concept of life long learning are pivoted by the foundations of object oriented technology, Learning objects, Just-in-time education, Data Mining, intelligent Agent technology, Flash interconnectivity and remote wireless technology, which allow practitioners to update their professional skills, complete specialised training which leads to accredited qualifications.
This paper sets out to develop and implement a range of teaching and learning strategies that would accommodate the flexibility required by such a scheme. At the same time the specific requirements of individual programmes are satisfied.
The body of elements provide an integrated path taking students through the range of operational, tactical and strategic issues involved in Web Based Learning, sustained by learning object abstract framework and Agent technology, within a distant learning context.
|A Sort-Last Rendering System over an Optical Backplane|
Yasuhiro Kirihata, Jason Leigh, Chaoyue Xiong, Tadao Murata
Sort-Last is a computer graphics technique for rendering extremely large data sets on clusters of computers. Sort-Last works by dividing the data set into even-sized chunks for parallel rendering and then composing the images to form the final result. Since sort-last rendering requires the movement of large amounts of image data among cluster nodes, the network interconnecting the nodes becomes a major bottleneck. In this paper, we describe a sort-last rendering system implemented on a cluster of computers whose nodes are connected by an all-optical switch. The rendering system introduces the notion of the Photonic Computing Engine, a computing system built dynamically by using the optical switch to create dedicated network connections among cluster nodes. The sort-last volume rendering algorithm was implemented on the Photonic Computing Engine, and its performance is evaluated. Prelimi- nary experiments show that performance is affected by the image composition time and average payload size. In an attempt to stabilize the performance of the system, we have designed a flow control mechanism that uses feedback messages to dynamically adjust the data flow rate within the computing engine.
A Specialized Framework for Data Retrieval Web Applications
Jerzy Nogiec, Kelley Trombly-Freytag, Dana Walbridge
Although many general-purpose frameworks have been developed to aid in web application development, they typically tend to be both comprehensive and complex. To address this problem, a specialized server-side Java framework designed specifically for data retrieval and visualization has been developed. The framework’s focus is on maintainability and data security. The functionality is rich with features necessary for simplifying data display design, deployment, user management and application debugging, yet the scope is deliberately kept limited to allow for easy comprehension and rapid application development. The system clearly decouples the application processing and visualization, which in turn allows for clean separation of layout and processing development. Duplication of standard web page features such as toolbars and navigational aids is therefore eliminated. The framework employs the popular Model-View-Controller (MVC) architecture, but it also uses the filter mechanism for several of its base functionalities, which permits easy extension of the provided core functionality of the system.
Applying Ant Colony Algorithm and Neural Network Model to Color Deviation Defect Detection in Liquid Crystal Displays
Hong-Dar Lin, Chih-Hao Chien
Thin Film Transistor Liquid Crystal Display (TFT-LCD) has excellent properties such as lower voltage to start and less occupied space if comparing with traditional Cathode-Ray Tube (CRT). But screen flaw points and display color deviation defects on image display exist in TFT-LCD products. This research proposes a new automated visual inspection method to solve the problems. We first use multivariate Hotelling T2 statistic for integrating coordinates of color models to construct a T2 energy diagram for inspecting defects and controlling patterns in TFT-LCD display images. An Ant Colony based approach that integrates computer vision techniques is developed to detect the flaw point defects. Then, Back Propagation Network (BPN) model is proposed to inspect small deviation defects of the LCD display colors. Experimental results show the proposed system can provide good effects and practicality.
Applying Systems Thinking in the Evaluation of Organizational Learning and Knowledge Creation
Petri Paajanen, Jussi Kantola, Waldemar Karwowski, Hannu Vanharanta
Organizational learning and ability continuously create new knowledge are important factors in achieving sustainable com-petitive advantage. It is important that the environment for learning and knowledge creation is analyzed in order to direct development efforts towards right areas. This can be very diffi-cult because organization
Communications tools in research projects to support Semi and Non Structured Information
Astrid Jaime, Mickael Gardoni, Christian Franck
Innovation and thus the production of knowledge becomes a factor of competitiveness. In this context quality management could be complemented by knowledge management to aim the improvement of knowledge production by research activities process. To this end, after describing knowledge and informa-tion typologies in engineering activities, a knowledge man-agement system is proposed. The goal is to support: (1) Semi-Structured Information (e.g. reports, etc.) thanks to the BASIC-Lab tool functions, which are based on attributing points of view and annotations to documents and document zones, and (2) Non-Structured Information (such as mail, dialogues, etc.), thanks to MICA-Graph approach which intends to support ex-change of technical messages that concerns common resolution of research problems within project teams and to capitalise relevant knowledge. For the both approaches, prototype tools have been developed and evaluated, primarily to feed back with manufacturing knowledge in the EADS industrial envi-ronment.
Compensating for Channel Fading in DS-CDMA Communication Systems Employing ICA Neural Network Detectors
David Overbye, Roland Priemer
In this paper we examine the impact of channel fading on the bit error rate of a DS-CDMA communication system. The system employs detectors that incorporate neural networks effecting methods of independent component analysis (ICA), subspace estimation of channel noise, and Hopfield type neural networks. The Rayleigh fading channel model is used. When employed in a Rayleigh fading environment, the ICA neural network detectors that give superior performance in a flat fading channel did not retain this superior performance. We then present a new method of compensating for channel fading based on the incorporation of priors in the ICA neural network learning algorithms. When the ICA neural network detectors were compensated using the incorporation of priors, they give significantly better performance than the traditional detectors and the uncompensated ICA detectors.
Keywords: CDMA, Multi-user Detection, Rayleigh Fading, Multipath Detection, Independent Component Analysis, Prior Probability Hebbian Learning, Natural Gradient
Conceiving Scenario-Based IS Support for Knowledge Synthesis: The Organization Architect
Kam Hou VAT
This paper examines the idea of creating information systems (IS) support for knowledge work through the elaboration of typical organizational scenarios. Specifically, our research is driven by a belief that the design issues of IS support must be situated in the context of social processes in which, in a specific organizational scenario, a particular group of people can conceptualize their knowledge work and hence the purposeful action they wish to undertake. This provides the basis for ascertaining what information support is needed by those who undertake that action, and how modern information technology can help to provide that support. Thereby, designing IS support for knowledge work requires attention to the purposeful action which the IS serves, and hence to the meanings which make those particular actions meaningful and relevant to particular groups of people in a particular situation. This is often facilitated by the provision of an important enquiry process constantly attended to, and integrated into organizational activities by which IS professionals could learn of the organization’s continual adjustments to its changing world. Our discussion here brings forth the notion of the learning organization information systems (LOIS), through which each member of the organization is enabled to create his or her own knowledge space, which is subject to some level of description, and thus may be architected and integrated into an organization. Importantly, in order to develop the various LOIS support for knowledge work, we need the correspondent organization scenarios to contextualize the IS design. And we attribute this development philosophy to the essence of systems thinking in conceiving IS support. The paper concludes by reiterating the work of the organization architect, which entails understanding, analyzing, designing, and communicating the most relevant parts of the organization and how they fit together.