The selection of a personalized treatment plan for a patient with cancer can be of critical importance for his health or even survival. A Decision Support Platform that can associate the patient clinical situation wit...
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The selection of a personalized treatment plan for a patient with cancer can be of critical importance for his health or even survival. A Decision Support Platform that can associate the patient clinical situation with the patient DNA Single Nucleotide Polymorphisms (SNPs) can provide the oncologist with a better understanding of the personalized conditions of every single patient. In this paper we present the MATCH platform which performs data integration between medicine and molecular biology, by developing a framework where, clinical and genomic features are appropriately combined in order to handle colon cancer diseases. The core of the platform is based on clustering techniques which provide profiles of patients with similar clinical features and genetic predispositions to cancer. The patients which share the same profile should probably have similar treatment plan and follow up. Through the integration of the clinical and genetic data of a patient, real time conclusions can be drawn for his early diagnosis, staging and more effective colon cancer treatment. intelligent components are designed and developed which identify single nucleotide polymorphisms (SNPs) from the gene sequences and combine them with the clinical situation of the patient. The produced clinico-genomic profiles are used as a decision support tool for newly sequenced patients.
This chapter presents a general overview of parallel approaches for multiobjective optimization. For this purpose, we propose a taxonomy for parallel metaheuristics and exact methods. This chapter covers the design as...
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It is well known that speech production and perception process is inherently bimodal consisting of audio and visual components. Recently there has been increased interest in using the visual modality in combination wi...
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It is well known that speech production and perception process is inherently bimodal consisting of audio and visual components. Recently there has been increased interest in using the visual modality in combination with the acoustic modality for improved speech processing. This field of study has gained the title of audio-visual speech processing. Lip movement recognition, also known as lip reading, is a communication skill which involves the interpretation of lip movements in order to estimate some important parameters of the lips that include, but not limited to, size, shape and orientation. In this paper, we represent a hybrid framework for lip reading which is based on both audio and visual speech parameters extracted from a video stream of isolated spoken words. The proposed algorithm is self-tuned in the sense that it starts with an estimations of speech parameters based on visual lip features and then the coefficients of the algorithm are fine-tuned based on the extracted audio parameters. In the audio speech processing part, extracted audio features are used to generate a vector containing information of the speech phonemes. These information are used later to enhance the recognition and matching process. For lip feature extraction, we use a modified version of the method used by F. Huang and T. Chen for tracking of multiple faces. This method is based on statistical color modeling and the deformable template. The experiments based on the proposed framework showed interesting results in recognition of isolated words.
In this paper we present the POCEMON platform, a platform aiming to the early prognosis and diagnosis of autoimmune diseases at any point of care, even the primary. The objective of the POCEMON platform is the develop...
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In this paper we present the POCEMON platform, a platform aiming to the early prognosis and diagnosis of autoimmune diseases at any point of care, even the primary. The objective of the POCEMON platform is the development of a diagnostic lab-on-chip device based on genomic microarrays of HLA-typing. The POCEMON is going to advance and promote the primary health care across Europe by supporting a) point-of-care diagnostics, b) monitoring of immune system status and c) management of the chronic multiple sclerosis (MS) and rheumatoid arthritis (RA) autoimmune diseases. The platform combines high-end Information and Communication Technologies based on microfluidics, microelectronics, microarrays and intelligent diagnosis algorithms.
In networked control systems (NCS), it is considered essential to design a robust controller such that the networked-system is stable against data dropouts during the network transfer. It has been shown that there is ...
In networked control systems (NCS), it is considered essential to design a robust controller such that the networked-system is stable against data dropouts during the network transfer. It has been shown that there is a critical data dropout rate over which the networked-system could be unstable; hence the desired task cannot be achieved. This paper shows that a desired task or trajectories can be still achieved even though there are feedback signal dropouts if the desired task is repetitive, as in the iterative learning control case. Specifically this paper shows how to design stochastic iterative learning control systems such that the networked-system with a repetitive task is robust stable against measurement and process noises and independent, intermittent output channel dropouts.
Implementing and fleshing out a number of psychological and neuroscience theories of cognition, the LIDA conceptual model aims at being a cognitive "theory of everything." With modules or processes for perce...
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This paper describes the use of two machine learning techniques, naive Bayes and decision trees, to address the task of assigning function tags to nodes in a syntactic parse tree. Function tags are extra functional in...
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In this paper, we present LIDA, a working model of, and theoretical foundation for, machine consciousness. LIDA's architecture and mechanisms were inspired by a variety of computational paradigms and LIDA implemen...
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In this work, we propose a novel technique for evolving transistor netlists from truth table descriptions of arbitrary digital circuits. The proposed methods incorporate the effective use of Genetic Algorithms (GAs). ...
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In many applications, transaction data arrive in the form of high speed data streams. These data contain a lot of information about customers that needs to be carefully managed to protect customers' privacy. In th...
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ISBN:
(纸本)1424413176
In many applications, transaction data arrive in the form of high speed data streams. These data contain a lot of information about customers that needs to be carefully managed to protect customers' privacy. In this paper, we consider the problem of preserving customer's privacy on the sliding window of transaction data streams. This problem is challenging because sliding window is updated frequently and rapidly. We propose a novel approach, SWAF (Sliding Window Anonymization Framework), to solve this problem by continuously facilitating kanonymity on the sliding window. Three advantages make SWAF practical: (1) Small processing time for each tuple of data steam. (2) Small memory requirement. (3) Both privacy protection and utility of anonymized sliding window are carefully considered. Theoretical analysis and experimental results show that SWAF is efficient and effective.
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