Search results for: Medical Image Mining

Authors: M. Derakhshanfar, B. Minaei-Bidgoli

Abstract:

Spatial trends are one of the valuable patterns in geo databases. They play an important role in data analysis and knowledge discovery from spatial data. A spatial trend is a regular change of one or more non spatial attributes when spatially moving away from a start object. Spatial trend detection is a graph search problem therefore heuristic methods can be good solution. Artificial immune system (AIS) is a special method for searching and optimizing. AIS is a novel evolutionary paradigm inspired by the biological immune system. The models based on immune system principles, such as the clonal selection theory, the immune network model or the negative selection algorithm, have been finding increasing applications in fields of science and engineering. In this paper, we develop a novel immunological algorithm based on clonal selection algorithm (CSA) for spatial trend detection. We are created neighborhood graph and neighborhood path, then select spatial trends that their affinity is high for antibody. In an evolutionary process with artificial immune algorithm, affinity of low trends is increased with mutation until stop condition is satisfied.

Keywords: Spatial Data Mining, Spatial Trend Detection, Heuristic Methods, Artificial Immune System, Clonal Selection Algorithm (CSA)

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Authors: Siti Norul Huda Sheikh Abdullah, Farshid Pirahan Siah, Nor Hanisah Haji Zainal Abidin, Shahnorbanun Sahran

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The objective of this paper is to propose an adaptive multi threshold for image segmentation precisely in object detection. Due to the different types of license plates being used, the requirement of an automatic LPR is rather different for each country. The proposed technique is applied on Malaysian LPR application. It is based on Multi Layer Perceptron trained by back propagation. The proposed adaptive threshold is introduced to find the optimum threshold values. The technique relies on the peak value from the graph of the number object versus specific range of threshold values. The proposed approach has improved the overall performance compared to current optimal threshold techniques. Further improvement on this method is in progress to accommodate real time system specification.

Keywords: Multi-threshold approach, license plate recognition system.

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Authors: J. Silvestre, L. Almeida, R. Marau, P. Pedreiras

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Currently, there are many local area industrial networks that can give guaranteed bandwidth to synchronous traffic, particularly providing CBR channels (Constant Bit Rate), which allow improved bandwidth management. Some of such networks operate over Ethernet, delivering channels with enough capacity, specially with compressors, to integrate multimedia traffic in industrial monitoring and image processing applications with many sources. In these industrial environments where a low latency is an essential requirement, JPEG is an adequate compressing technique but it generates VBR traffic (Variable Bit Rate). Transmitting VBR traffic in CBR channels is inefficient and current solutions to this problem significantly increase the latency or further degrade the quality. In this paper an R(q) model is used which allows on-line calculation of the JPEG quantification factor. We obtained increased quality, a lower requirement for the CBR channel with reduced number of discarded frames along with better use of the channel bandwidth.

Keywords: Industrial Networks, Multimedia.

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Authors: Rozilawati Binti Dollah, Masaki Aono

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Classifying biomedical literature is a difficult and challenging task, especially when a large number of biomedical articles should be organized into a hierarchical structure. In this paper, we present an approach for classifying a collection of biomedical text abstracts downloaded from Medline database with the help of ontology alignment. To accomplish our goal, we construct two types of hierarchies, the OHSUMED disease hierarchy and the Medline abstract disease hierarchies from the OHSUMED dataset and the Medline abstracts, respectively. Then, we enrich the OHSUMED disease hierarchy before adapting it to ontology alignment process for finding probable concepts or categories. Subsequently, we compute the cosine similarity between the vector in probable concepts (in the “enriched" OHSUMED disease hierarchy) and the vector in Medline abstract disease hierarchies. Finally, we assign category to the new Medline abstracts based on the similarity score. The results obtained from the experiments show the performance of our proposed approach for hierarchical classification is slightly better than the performance of the multi-class flat classification.

Keywords: Biomedical literature, hierarchical text classification, ontology alignment, text mining.

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Authors: D. Sumathi, P. Poongodi

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Cloud Computing refers to applications delivered as services over the internet, and the datacenters that provide those services with hardware and systems software. These were earlier referred to as Software as a Service (SaaS). Scheduling is justified by job components (called tasks), lack of information. In fact, in a large fraction of jobs from machine learning, bio-computing, and image processing domains, it is possible to estimate the maximum time required for a task in the job. This study focuses on Trust based scheduling to improve cloud security by modifying Heterogeneous Earliest Finish Time (HEFT) algorithm. It also proposes TR-HEFT (Trust Reputation HEFT) which is then compared to Dynamic Load Scheduling.

Keywords: Software as a Service (SaaS), Trust, Heterogeneous Earliest Finish Time (HEFT) algorithm, Dynamic Load Scheduling.

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Authors: Nareenad Panbun

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The objective is to study the knowledge utilization from the participants of the announcer training program by National Broadcasting and Telecommunications Commission (NBTC). This study is a quantitative research based on surveys and self-answering questionnaires. The population of this study is 100 participants randomly chosen by non-probability sampling method. The results have shown that most of the participants were satisfied with the topics of general knowledge about the broadcasting and television business for 37 people representing 37%, followed by the topics of broadcasting techniques. The legal issues, consumer rights, television business ethics, and credibility of the media are, in addition to the media's role and responsibilities in society, the use of language for successful communication. Therefore, the communication language skills are the most important for all of the trainees and will also build up the image of the broadcasting center.

Keywords: Announcer training program, participant, requirements announced, theory of utilization.

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Authors: A. Mohammadi Torkashvand, N. Haghighat

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Some methodologies were compared in providing erosion maps of surface, rill and gully and erosion features, in research which took place in the Varamin sub-basin, north-east Tehran, Iran. A photomorphic unit map was produced from processed satellite images, and four other maps were prepared by the integration of different data layers, including slope, plant cover, geology, land use, rocks erodibility and land units. Comparison of ground truth maps of erosion types and working unit maps indicated that the integration of land use, land units and rocks erodibility layers with satellite image photomorphic units maps provide the best methods in producing erosion types maps.

Keywords: Erosion Features, Geographic Information System, Remote Sensing.

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Authors: Erik Lilienblum, Robert Niese, Bernd Michaelis

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This paper proposes a novel stereo vision technique for top view book scanners which provide us with dense 3d point clouds of page surfaces. This is a precondition to dewarp bound volumes independent of 2d information on the page. Our method is based on algorithms, which normally require the projection of pattern sequences with structured light. We use image sequences of the moving stripe lighting of the top view scanner instead of an additional light projection. Thus the stereo vision setup is simplified without losing measurement accuracy. Furthermore we improve a surface model dewarping method through introducing a difference vector based on real measurements. Although our proposed method is hardly expensive neither in calculation time nor in hardware requirements we present good dewarping results even for difficult examples.

Keywords: stereo vision, 3d surface reconstruction, dewarpingdocuments, book scanner

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Authors: C. Snae Namahoot, M. Brueckner

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Thailand-s health system is challenged by the rising number of patients and decreasing ratio of medical practitioners/patients, especially in rural areas. This may tempt inexperienced GPs to rush through the process of anamnesis with the risk of incorrect diagnosis. Patients have to travel far to the hospital and wait for a long time presenting their case. Many patients try to cure themselves with traditional Thai medicine. Many countries are making use of the Internet for medical information gathering, distribution and storage. Telemedicine applications are a relatively new field of study in Thailand; the infrastructure of ICT had hampered widespread use of the Internet for using medical information. With recent improvements made health and technology professionals can work out novel applications and systems to help advance telemedicine for the benefit of the people. Here we explore the use of telemedicine for people with health problems in rural areas in Thailand and present a Telemedicine Diagnosis System for Rural Thailand (TEDIST) for diagnosing certain conditions that people with Internet access can use to establish contact with Community Health Centers, e.g. by mobile phone. The system uses a Web-based input method for individual patients- symptoms, which are taken by an expert system for the analysis of conditions and appropriate diseases. The analysis harnesses a knowledge base and a backward chaining component to find out, which health professionals should be presented with the case. Doctors have the opportunity to exchange emails or chat with the patients they are responsible for or other specialists. Patients- data are then stored in a Personal Health Record.

Keywords: Biomedical engineering, data acquisition, expert system, information management system, and information retrieval.

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Authors: Eva Štěpánková

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Environmental management implementation is presently one of the ways of organization success and value improvement. Increasing an organization motivation to environmental measures introduction is caused primarily by the rising pressure of the society that generates various incentives to endeavor for the environmental performance improvement. The aim of the paper is to identify and characterize the key incentives and expectations leading organizations to the environmental management implementation. The author focuses on five businesses of different size and field, operating in the Czech Republic. The qualitative approach and grounded theory procedure are used in research. The results point out that the significant incentives for environmental management implementation represent primarily demands of customers, the opportunity to declare the environmental commitment and image improvement. The researched enterprises less commonly expect the economical contribution, competitive advantage increase or export rate improvement. The results show that marketing contributions are primarily expected from the environmental management implementation.

Keywords: Environmental management, environmental management systems, ISO 14001.

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Authors: Udeni Jayasinghe, Anuja Dharmaratne

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Each year many people are reported missing in most of the countries in the world owing to various reasons. Arrangements have to be made to find these people after some time. So the investigating agencies are compelled to make out these people by using manpower. But in many cases, the investigations carried out to find out an absconding for a long time may not be successful. At a time like that it may be difficult to identify these people by examining their old photographs, because their facial appearance might have changed mainly due to the natural aging process. On some occasions in forensic medicine if a dead body is found, investigations should be held to make sure that this corpse belongs to the same person disappeared some time ago. With the passage of time the face of the person might have changed and there should be a mechanism to reveal the person-s identity. In order to make this process easy, we must guess and decide as to how he will look like by now. To address this problem this paper presents a way of synthesizing a facial image with the aging effects.

Keywords: Cranio-facial growth model, eigenfaces, eigenvectors, Face Anthropometry.

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Authors: Mario Mastriani, Marcelo Naiouf

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This paper introduces a Quantum Correlation Matrix Memory (QCMM) and Enhanced QCMM (EQCMM), which are useful to work with quantum memories. A version of classical Gram-Schmidt orthogonalisation process in Dirac notation (called Quantum Orthogonalisation Process: QOP) is presented to convert a non-orthonormal quantum basis, i.e., a set of non-orthonormal quantum vectors (called qudits) to an orthonormal quantum basis, i.e., a set of orthonormal quantum qudits. This work shows that it is possible to improve the performance of QCMM thanks QOP algorithm. Besides, the EQCMM algorithm has a lot of additional fields of applications, e.g.: Steganography, as a replacement Hopfield Networks, Bilevel image processing, etc. Finally, it is important to mention that the EQCMM is an extremely easy to implement in any firmware.

Keywords: Quantum Algebra, correlation matrix memory, Dirac notation, orthogonalisation.

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Authors: Sana Ktata, Kaïs Ouni, Noureddine Ellouze

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Electrocardiogram (ECG) data compression algorithm is needed that will reduce the amount of data to be transmitted, stored and analyzed, but without losing the clinical information content. A wavelet ECG data codec based on the Set Partitioning In Hierarchical Trees (SPIHT) compression algorithm is proposed in this paper. The SPIHT algorithm has achieved notable success in still image coding. We modified the algorithm for the one-dimensional (1-D) case and applied it to compression of ECG data. By this compression method, small percent root mean square difference (PRD) and high compression ratio with low implementation complexity are achieved. Experiments on selected records from the MIT-BIH arrhythmia database revealed that the proposed codec is significantly more efficient in compression and in computation than previously proposed ECG compression schemes. Compression ratios of up to 48:1 for ECG signals lead to acceptable results for visual inspection.

Keywords: Discrete Wavelet Transform, ECG compression, SPIHT.

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Authors: Guilherme Ribeiro, Alexandre Oliveira, Antonio Ferreira, Shyam Visweswaran, Gregory Cooper

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Patient-specific models are instance-based learning algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the patient-specific decision path (PSDP) entropy-based and CART methods, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions.

Keywords: Approach instance-based, area Under the ROC Curve, Patient-specific Decision Path, clinical predictions.

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Authors: Tin Hninn Hninn Maung

Abstract:

This paper introduces a hand gesture recognition system to recognize real time gesture in unstrained environments. Efforts should be made to adapt computers to our natural means of communication: Speech and body language. A simple and fast algorithm using orientation histograms will be developed. It will recognize a subset of MAL static hand gestures. A pattern recognition system will be using a transforrn that converts an image into a feature vector, which will be compared with the feature vectors of a training set of gestures. The final system will be Perceptron implementation in MATLAB. This paper includes experiments of 33 hand postures and discusses the results. Experiments shows that the system can achieve a 90% recognition average rate and is suitable for real time applications.

Keywords: Hand gesture recognition, Orientation Histogram, Myanmar Alphabet Language, Perceptronnetwork, MATLAB.

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Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

Abstract:

Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original dataset. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 dataset is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: Distributed intrusion detection system, mobile agent, feature selection, Bees Algorithm, decision tree.

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Authors: N. Valliammal, S.N. Geethalakshmi

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This paper describes an optimal approach for feature subset selection to classify the leaves based on Genetic Algorithm (GA) and Kernel Based Principle Component Analysis (KPCA). Due to high complexity in the selection of the optimal features, the classification has become a critical task to analyse the leaf image data. Initially the shape, texture and colour features are extracted from the leaf images. These extracted features are optimized through the separate functioning of GA and KPCA. This approach performs an intersection operation over the subsets obtained from the optimization process. Finally, the most common matching subset is forwarded to train the Support Vector Machine (SVM). Our experimental results successfully prove that the application of GA and KPCA for feature subset selection using SVM as a classifier is computationally effective and improves the accuracy of the classifier.

Keywords: Optimization, Feature extraction, Feature subset, Classification, GA, KPCA, SVM and Computation

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Authors: Jaeyoung Lee

Abstract:

Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: Edge network, embedded network, MMA, matrix multiplication accelerator and semantic segmentation network.

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Authors: Insung Jung, Gi-Nam Wang

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In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: Ali Abdrhman Ukasha

Abstract:

This paper presented two new efficient algorithms for contour approximation. The proposed algorithm is compared with Ramer (good quality), Triangle (faster) and Trapezoid (fastest) in this work; which are briefly described. Cartesian co-ordinates of an input contour are processed in such a manner that finally contours is presented by a set of selected vertices of the edge of the contour. In the paper the main idea of the analyzed procedures for contour compression is performed. For comparison, the mean square error and signal-to-noise ratio criterions are used. Computational time of analyzed methods is estimated depending on a number of numerical operations. Experimental results are obtained both in terms of image quality, compression ratios, and speed. The main advantages of the analyzed algorithm is small numbers of the arithmetic operations compared to the existing algorithms.

Keywords: Polygonal approximation, Ramer, Triangle and Trapezoid methods.

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Authors: Hirofumi Taki, Takuya Sakamoto, Makoto Yamakawa, Tsuyoshi Shiina, Toru Sato

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For the improvement of the ability in detecting small calcifications using Ultrasonography (US) we propose a novel indicator of calcifications in an ultrasound B-mode image without decrease in frame rate. Since the waveform of an ultrasound pulse changes at a calcification position, the decorrelation of adjacent scan lines occurs behind a calcification. Therefore, we employ the decorrelation of adjacent scan lines as an indicator of a calcification. The proposed indicator depicted wires 0.05 mm in diameter at 2 cm depth with a sensitivity of 86.7% and a specificity of 100%, which were hardly detected in ultrasound B-mode images. This study shows the potential of the proposed indicator to approximate the detectable calcification size using an US device to that of an X-ray imager, implying the possibility that an US device will become a convenient, safe, and principal clinical tool for the screening of breast cancer.

Keywords: Ultrasonography, Calcification, Decorrelation, Forward scattered wave

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Authors: Sumeet S. Nisale, Chandan J. Bharambe, Vidya N.More

Abstract:

We propose our genuine research of geometric moments which detects the mineral inadequacy in the frail groundnut plant. This plant is prone to many deficiencies as a result of the variance in the soil nutrients. By analyzing the leaves of the plant, we detect the visual symptoms that are not recognizable to the naked eyes. We have collected about 160 samples of leaves from the nearby fields. The images have been taken by keeping every leaf into a black box to avoid the external interference. For the first time, it has been possible to provide the farmer with the stages of deficiencies. This paper has applied the algorithms successfully to many other plants like Lady-s finger, Green Bean, Lablab Bean, Chilli and Tomato. But we submit the results of the groundnut predominantly. The accuracy of our algorithm and method is almost 93%. This will again pioneer a kind of green revolution in the field of agriculture and will be a boon to that field.

Keywords: Component image, geometric moments, average intensity, average affected area, black box

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Authors: T. Saarelainen, O. Piha, P. Makkonen, J. Orkas

Abstract:

Global competition is tightening and companies have to think how to remain competitive. The main aim of this paper is to discuss how Finnish foundries will remain competitive. To fulfil the aim, we conducted interviews in nine companies using castings and analysed buyer–supplier relationships, current competitive advantages of Finnish foundries and customer perspectives on how Finnish foundries remain competitive. We found that the customerfoundry relationship is still closer to traditional subcontracting than partnering and general image of foundries is negative. Current competitive advantages of Finnish foundries include designing cooperation, proximity and flexibility. Casting users state that Finnish foundries should sell their know-how and services instead of their capacity, concentrate on prototype, single and short series castings and supply ready-to-install cast components directly to customers- assembly lines.

Keywords: Buyer-supplier relationship, casting, competitiveadvantage, customer prespective.

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Authors: J.L. Higuera Trujillo, F.J. Montero Fernández

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Based on different experiences in the historic centers of Spain, we propose an global strategy for the regeneration of the pre-tertiary fabrics and its application to the specific case of San Mateo neighborhood, in Jerez de la Frontera (Andalusia), through a diagnosis that focus particularly on the punishments the last-decade economic situation (building boom and crisis) and shows the tragic transition from economic center to an imminent disappearance with an image similar to the ruins of war, due to the loss of their traditional roles. From it we will learn their historically-tested mechanisms of environment adaptation, which distill the vernacular architecture essence and that we will apply to our strategy of action based on a dotacional-and-free-space rhizome which rediscovers its hidden character. The architectural fact will be crystallized in one of the example-pieces proposed: The Artistic Revitalization Center.

Keywords: Jerez de la Frontera, pre-tertiary fabrics, sustainable architecture, urban regeneration

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Authors: Asil Y. Zureigat, Ayat A. Oudat

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Analyzing the old and bringing in the new is an ever-ongoing process in driving innovations in architecture. This paper looks at the excessive use of stone in apartment buildings in Amman and speculates on the existing possibilities of changing the cladding material. By looking at architectural exceptions present in Amman, the paper seeks to make the exception the rule, by adding new materials to the architectural library of Amman and in turn, project a series of possible new identities to the existing stone scape. Through distributing a survey, conducting a photographic study on exceptional buildings and shedding light on the historical narrative of stone, the paper highlights the ways in which new finishing materials such as plaster, paint and stone variations could be introduced in an attempt to project a new architectural identity to Amman.

Keywords: Architectural city identity, cladding materials, façade architecture, image of the city.

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Authors: Hossein Sahoolizadeh, Mahdi Rahimi, Hamid Dehghani

Abstract:

We introduce an algorithm based on the morphological shared-weight neural network. Being nonlinear and translation-invariant, the MSNN can be used to create better generalization during face recognition. Feature extraction is performed on grayscale images using hit-miss transforms that are independent of gray-level shifts. The output is then learned by interacting with the classification process. The feature extraction and classification networks are trained together, allowing the MSNN to simultaneously learn feature extraction and classification for a face. For evaluation, we test for robustness under variations in gray levels and noise while varying the network-s configuration to optimize recognition efficiency and processing time. Results show that the MSNN performs better for grayscale image pattern classification than ordinary neural networks.

Keywords: Face recognition, Neural Networks, Multi-layer Perceptron, masking.

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Authors: V. Kabeer, N.K.Narayanan

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This paper reports a new pattern recognition approach for face recognition. The biological model of light receptors - cones and rods in human eyes and the way they are associated with pattern vision in human vision forms the basis of this approach. The functional model is simulated using CWD and WPD. The paper also discusses the experiments performed for face recognition using the features extracted from images in the AT & T face database. Artificial Neural Network and k- Nearest Neighbour classifier algorithms are employed for the recognition purpose. A feature vector is formed for each of the face images in the database and recognition accuracies are computed and compared using the classifiers. Simulation results show that the proposed method outperforms traditional way of feature extraction methods prevailing for pattern recognition in terms of recognition accuracy for face images with pose and illumination variations.

Keywords: Face recognition, Image analysis, Wavelet feature extraction, Pattern recognition, Classifier algorithms

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Authors: I. Struhár, L. Dovrtělová, M. Kumstát

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Regular exercise promotes reduction in blood pressure, reduction in body weight and it also helps to increase in insulin sensitivity. Participation in physical activity should always be linked to medical screening which can reveal serious medical problems. One of them is high blood pressure. Hypertension is risk factor for one billion people worldwide and the highest prevalence is found in Africa. Another component of hypertension is that people who suffer from hypertension have no symptoms. It is estimated that reduction of 3mm Hg in Systolic Blood Pressure decreases cardiac morbidity at least 5%. The most of the guidelines suggest aerobic exercise in a prevention of cardiovascular diseases. On the other hand, it is important to emphasize the impact of resistance training. Even, it was found higher effect for reduction on the level of systolic blood pressure than aerobic exercise.

Keywords: Coronary artery disease, physical activity, prevention, resistance training.

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Authors: Sasitorn Chetanont

Abstract:

The objectives of this study are to find out the approaches to promote healthy recreation activities for elderly tourists and develop Bang Nam Phueng Floating Market to be a health tourism attraction. The research methodology was to analyze internal and external situations according to MP-MF and the MCSTEPS principles. As for the results of this study the researcher found that the healthy recreational activities for elderly tourists could be divided in 7 groups; travelling Bang Nam Phueng Floating Market activity, homestay relaxation, arts center platform activity, healthy massage activity, paying homage to a Buddha image activity, herbal joss-stick home activity, making local desserts and food activity.

Keywords: Elderly tourists, recreational activities, Bang Nam Phueng Floating Market.

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Authors: H. Nur Gorkemli, Mehmet Fidan

Abstract:

After the first acquaintance with internet in April 1993, number of internet users increased rapidly in Turkey. Almost half of the population between 16-74 age group use internet in the country. Hospitals are one of the areas where the internet is intensively being used like many other businesses. As a part of public relations application, websites are important tools for hospitals to reach a wide range of target audience within and outside the organization. With their websites, hospitals have opportunities to give information about their organization, strengthen their image, compete with their rivals, interact with shareholders, reflect their transparency and meet with new audiences. This study examines web sites of totally 34 hospitals which are located in Konya. Institutions are categorized as public and private hospitals and then three main research categories are determined: content, visual and technical. Main and sub categories are examined by using content analysis method. Results are interpreted in scope of public and private institutions and as a whole.

Keywords: Health Communication, Hospital, Internet, Webpages, Websites

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