5,496 research outputs found

    Decision support system for the selection of an ITE or a BTE hearing aid

    Get PDF
    The purpose of this research is to mine a large set of heterogeneous audiology data to create a decision support system (DSS) to choose between two hearing aid types (ITE and BTE aid). This research is based on the data analysis of audiology data using various statistical and data mining techniques. It uses the data of a large NHS (National Health Services, UK) facility. It uses 180,000 records (covering more than 23,000 different patients) from a hearing aid clinic. The developed system uses an unconventional method to predict hearing aid type for a patient and it can be used as a second opinion by audiologists for complex cases. After modifying the system to take account of the feedback from a professional audiologist, the success rates obtained were in the ranges 63 to 66 percent. In this research an automatic system was developed to choose between an ITE or a BTE hearing aid type with an explanation facility that can be used as a second opinion by audiologist in cases where the choice of an ITE or a BTE hearing aid is not clear cut. This analysis of audiology data and DSS will provide supplementary information for audiology experts and hearing aid dispensers. This type of system may also be of interest to manufacturers of hearing technologies in using as a ready means for their telephone customer services staff to check data, discovering data in audiology records will also be good for general awareness about the suitability of hearing aid type

    Enriched Model of Case Based Reasoning and Neutrosophic Intelligent System for DDoS Attack Defence in Software Defined Network based Cloud

    Get PDF
    Software Defined Networking in Cloud paradigm is most suitable for dynamic functionality and reduces the computation complexity. The routers and switches located at the network's boundaries are managed by software-defined netwrking (SDN) using open protocols and specialised open programmable interfaces. But the security threats often degrade the performance of SDN due to its constraints of resource usage. The most sensitive components which are vulnerable to DDoS attacks are controller and control plane bandwidth. The existing conventional classification algorithms lacks in detection of new or unknown traffic packets which are malicious and results in degradation of SDN performance in cloud resources. Hence, in this paper double filtering methodology is devised to detect both known and unknown pattern of malicious packets which affects the bandwidth of the control panel and the controller. The case-based reasoning is adapted for determining the known incoming traffic patterns before entering the SDN system. It classifies the packets are normal or abnormal based on the previous information gathered. The traffic patterns which is not matched from the previous patterns is treated as indeterministic packet and it is defined more precisely using the triplet representation of Neutrosophic intelligent system. The grade of belongingness, non-belongingness and indeterminacyis used as the main factors to detect the new pattern of attacking packets more effectively. From the experimental outcomes it is proved that DDoS attack detection in SDN based cloud environment is improved by adopting CBR-NIS compared to the existing classification model

    Data mining for anomaly detection in maritime traffic data

    Get PDF
    For the past few years, oceans have become once again, an important means of communication and transport. In fact, traffic density throughout the globe has suffered a substantial growth, which has risen some concerns. With this expansion, the need to achieve a high Maritime Situational Awareness (MSA) is imperative. At the present time, this need may be more easily fulfilled thanks to the vast amount of data available regarding maritime traffic. However, this brings in another issue: data overload. Currently, there are so many data sources, so many data to obtain information from, that the operators cannot handle it. There is a pressing need for systems that help to sift through all the data, analysing and correlating, helping in this way the decision making process. In this dissertation, the main goal is to use different sources of data in order to detect anomalies and contribute to a clear Recognised Maritime Picture (RMP). In order to do so, it is necessary to know what types of data exist and which ones are available for further analysis. The data chosen for this dissertation was Automatic Identification System (AIS) and Monitorização Contínua das Atividades da Pesca (MONICAP) data, also known as Vessel Monitoring System (VMS) data. In order to store 1 year worth of AIS and MONICAP data, a PostgreSQL database was created. To analyse and draw conclusions from the data, a data mining tool was used, namely, Orange. Tests were conducted in order to assess the correlation between data sources and find anomalies. The importance of data correlation has never been so important and with this dissertation the aim is to show that there is a simple and effective way to get answers from great amounts of data.Nos últimos anos, os oceanos tornaram-se, mais uma vez, um importante meio de comunicação e transporte. De facto, a densidade de tráfego global sofreu um crescimento substancial, o que levantou algumas preocupações. Com esta expansão, a necessidade de atingir um elevado Conhecimento Situacional Marítimo (CSM) é imperativa. Hoje em dia, esta necessidade pode ser satisfeita mais facilmente graças à vasta quantidade de dados disponíveis de tráfego marítimo. No entanto, isso leva a outra questão: sobrecarga de dados. Atualmente existem tantas fontes de dados, tantos dados dos quais extrair informação, que os operadores não conseguem acompanhar. Existe uma necessidade premente para sistemas que ajudem a escrutinar todos os dados, analisando e correlacionando, contribuindo desta maneira ao processo de tomada de decisão. Nesta dissertação, o principal objetivo é usar diferentes fontes de dados para detetar anomalias e contribuir para uma clara Recognised Maritime Picture (RMP). Para tal, é necessário saber que tipos de dados existem e quais é que se encontram disponíveis para análise posterior. Os dados escolhidos para esta dissertação foram dados Automatic Identification System (AIS) e dados de Monitorização Contínua das Atividades da Pesca (MONICAP), também conhecidos como dados de Vessel Monitoring System (VMS). De forma a armazenar dados correspondentes a um ano de AIS e MONICAP, foi criada uma base de dados em PostgreSQL. Para analisar e retirar conclusões, foi utilizada uma ferramenta de data mining, nomeadamente, o Orange. De modo a que pudesse ser avaliada a correlação entre fontes de dados e serem detetadas anomalias foram realizados vários testes. A correlação de dados nunca foi tão importante e pretende-se com esta dissertação mostrar que existe uma forma simples e eficaz de obter respostas de grandes quantidades de dado

    Comparative analysis of machine learning and numerical modeling for combined heat transfer in Polymethylmethacrylate

    Full text link
    This study compares different methods to predict the simultaneous effects of conductive and radiative heat transfer in a Polymethylmethacrylate (PMMA) sample. PMMA is a kind of polymer utilized in various sensors and actuator devices. One-dimensional combined heat transfer is considered in numerical analysis. Computer implementation was obtained for the numerical solution of governing equation with the implicit finite difference method in the case of discretization. Kirchhoff transformation was used to get data from a non-linear equation of conductive heat transfer by considering monochromatic radiation intensity and temperature conditions applied to the PMMA sample boundaries. For Deep Neural Network (DNN) method, the novel Long Short Term Memory (LSTM) method was introduced to find accurate results in the least processing time than the numerical method. A recent study derived the combined heat transfers and their temperature profiles for the PMMA sample. Furthermore, the transient temperature profile is validated by another study. A comparison proves a perfect agreement. It shows the temperature gradient in the primary positions that makes a spectral amount of conductive heat transfer from a PMMA sample. It is more straightforward when they are compared with the novel DNN method. Results demonstrate that this artificial intelligence method is accurate and fast in predicting problems. By analyzing the results from the numerical solution it can be understood that the conductive and radiative heat flux is similar in the case of gradient behavior, but it is also twice in its amount approximately. Hence, total heat flux has a constant value in an approximated steady state condition. In addition to analyzing their composition, ROC curve and confusion matrix were implemented to evaluate the algorithm performance.Comment: 15 pages, 11 figure

    Considerations concerning cosumer behaviour theory

    Get PDF
    The consumer`s scale of preference, which is the starting point of the theory of consumer behaviour can be ilustrated very clearly by indifference curves. The point where budget line meets the highest possible indifference curve compatible with the consumer`s income and prices represents the state of equilibrum for the consumer. Consumer behaviuor theory gains still more practical importance if consumer preferences are subjected to detailed psychological and sociological analysis.indifference curve, marginal utility, budget line, consumer`s equilibrum, individual demand curve, Engel curve, market demand curve, psychological and social factors of consumer behaviuor

    Contributions to chatbots and digital analytics in industry

    Get PDF
    Diese kumulative Dissertation umfasst zehn wissenschaftliche Artikel, die zur Forschung digitaler Analytik, Messung von Technologieakzeptanz und Chatbots beitragen. Ziel der Artikel ist es, die Entwicklung, Implementierung und Verwaltung von Technologien zu vereinfachen und zu unterstützen. Modelle werden entwickelt, welche die wichtigsten Schritte beschreiben und unter anderem relevante damit zusammenhängende Fragen auflisten, die zu beteiligenden Interessengruppen benennen und geeignete Tools vorstellen, welche berücksichtigt werden sollten. Es werden Chatbot Taxonomien entwickelt und vorgestellt, welche die Bandbreite der derzeit bestehenden Gestaltungsmöglichkeiten aufzeigen, während identifizierte Archetypen zu beobachtende Kombinationen aufzeigen. Die Identifizierung der häufigsten Gründe für Misserfolge und die Entwicklung kritischer Erfolgsfaktoren tragen ebenfalls zu dem Ziel bei, den Entwicklungs- und Managementprozess zu erleichtern. Da die Endnutzer über die Akzeptanz und Nutzung und damit über den Erfolg einer Technologie entscheiden, werden Ansätze genutzt, wie die Nutzerakzeptanz von Technologien gemessen werden kann und wie Nutzer frühzeitig in den Entwicklungsprozess eingebunden werden können

    Recent Trends in Computational Intelligence

    Get PDF
    Traditional models struggle to cope with complexity, noise, and the existence of a changing environment, while Computational Intelligence (CI) offers solutions to complicated problems as well as reverse problems. The main feature of CI is adaptability, spanning the fields of machine learning and computational neuroscience. CI also comprises biologically-inspired technologies such as the intellect of swarm as part of evolutionary computation and encompassing wider areas such as image processing, data collection, and natural language processing. This book aims to discuss the usage of CI for optimal solving of various applications proving its wide reach and relevance. Bounding of optimization methods and data mining strategies make a strong and reliable prediction tool for handling real-life applications

    Space resources. Volume 2: Energy, power, and transport

    Get PDF
    This volume of the Space Resources report covers a number of technical and policy issues concerning the energy and power to carry out advanced space missions and the means of transportation to get to the sites of those missions. Discussed in the first half of this volume are the technologies which might be used to provide power and a variety of ways to convert power from one form to another, store it, move it wherever it is needed, and use it. In the second half of this volume, various kinds of transportation, including both interplanetary and surface systems, are discussed
    corecore