Search results for: Machine tools

Authors: C. Lodato, S. Lopes

Abstract:

This paper describes a segmentation algorithm based on the cooperation of an optical flow estimation method with edge detection and region growing procedures. The proposed method has been developed as a pre-processing stage to be used in methodologies and tools for video/image indexing and retrieval by content. The addressed problem consists in extracting whole objects from background for producing images of single complete objects from videos or photos. The extracted images are used for calculating the object visual features necessary for both indexing and retrieval processes. The first task of the algorithm exploits the cues from motion analysis for moving area detection. Objects and background are then refined using respectively edge detection and region growing procedures. These tasks are iteratively performed until objects and background are completely resolved. The developed method has been applied to a variety of indoor and outdoor scenes where objects of different type and shape are represented on variously textured background.

Keywords: Motion Detection, Object Extraction, Optical Flow, Segmentation.

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Authors: A. Shukla, A. Tarsauliya, R. Tiwari, S. Sharma

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Cancer classification to their corresponding cohorts has been key area of research in bioinformatics aiming better prognosis of the disease. High dimensionality of gene data has been makes it a complex task and requires significance data identification technique in order to reducing the dimensionality and identification of significant information. In this paper, we have proposed a novel approach for classification of oral cancer into metastasis positive and negative patients. We have used significance analysis of microarrays (SAM) for identifying significant genes which constitutes gene signature. 3 different gene signatures were identified using SAM from 3 different combination of training datasets and their classification accuracy was calculated on corresponding testing datasets using k-Nearest Neighbour (kNN), Fuzzy C-Means Clustering (FCM), Support Vector Machine (SVM) and Backpropagation Neural Network (BPNN). A final gene signature of only 9 genes was obtained from above 3 individual gene signatures. 9 gene signature-s classification capability was compared using same classifiers on same testing datasets. Results obtained from experimentation shows that 9 gene signature classified all samples in testing dataset accurately while individual genes could not classify all accurately.

Keywords: Cancer, Gene Signature, SAM, Classification.

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Authors: Maziar Ramezani, Zaidi Mohd Ripin

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In a metal forming process, the friction between the material and the tools influences the process by modifying the stress distribution of the workpiece. This frictional behaviour is often taken into account by using a constant coefficient of friction in the finite element simulations of sheet metal forming processes. However, friction coefficient varies in time and space with many parameters. The Stribeck friction model is investigated in this study to predict springback behaviour of AA6061-T4 sheets during V-bending process. The coefficient of friction in Stribeck curve depends on sliding velocity and contact pressure. The plane-strain bending process is simulated in ABAQUS/Standard. We compared the computed punch load-stroke curves and springback related to the constant coefficient of friction with the defined friction model. The results clearly showed that the new friction model provides better agreement between experiments and results of numerical simulations. The influence of friction models on stress distribution in the workpiece is also studied numerically

Keywords: Friction model, Stress distribution, V-bending.

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Authors: Jacopo Baboni Schilingi

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We here describe the theoretical and philosophical understanding of a long term use and development of algorithmic computer-based tools applied to music composition. The findings of our research lead us to interrogate some specific processes and systems of communication engaged in the discovery of specific cultural artworks: artistic creation in the sono-musical domain. Our hypothesis is that the patterns of auditory learning cannot be only understood in terms of social transmission but would gain to be questioned in the way they rely on various ranges of acoustic stimuli modes of consciousness and how the different types of memories engaged in the percept-action expressive systems of our cultural communities also relies on these shadowy conscious entities we named “Reduced Descriptive Structures”.

Keywords: Algorithmic sonic computation, corrected and self-correcting learning patterns in acoustic perception, morphological derivations in sensorial patterns, social unconscious modes of communication.

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Authors: Naser Ahmadi Sani, Karim Solaimani, Lida Razaghnia, Jalal Zandi

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In recent decades, rapid and incorrect changes in land-use have been associated with consequences such as natural resources degradation and environmental pollution. Detecting changes in land-use is one of the tools for natural resource management and assessment of changes in ecosystems. The target of this research is studying the land-use changes in Haraz basin with an area of 677000 hectares in a 15 years period (1996 to 2011) using LANDSAT data. Therefore, the quality of the images was first evaluated. Various enhancement methods for creating synthetic bonds were used in the analysis. Separate training sites were selected for each image. Then the images of each period were classified in 9 classes using supervised classification method and the maximum likelihood algorithm. Finally, the changes were extracted in GIS environment. The results showed that these changes are an alarm for the HARAZ basin status in future. The reason is that 27% of the area has been changed, which is related to changing the range lands to bare land and dry farming and also changing the dense forest to sparse forest, horticulture, farming land and residential area.

Keywords: HARAZ Basin, Change Detection, Land-use, Satellite Data.

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Authors: Zain M. Al-Houri, Oday K. Abu-Hadba, Khaled A. Hamdan

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Roof top rainwater harvesting (RWH) has been carried out worldwide to provide an inexpensive source of water for many people. This research aims at evaluating the potential of roof top rain water harvesting as a resource in Jordan. For the purpose of this work, two case studies at Al-Jubiha and Shafa-Badran districts in Amman city were selected. All existing rooftops in both districts were identified by digitizing 2012 satellite images of the two districts using Google earth and ArcGIS tools. Rational method was used to estimate the potential volume of rainwater that can be harvested from the digitized rooftops. Results indicated that 1.17 and 0.526 MCM/yr can be harvested in Al-Jubiha and Shafa-Badran districts, respectively. This study should increase the attention to the importance of implementing RWH technique in Jordanian residences as a viable alternative for ensuring a continued source of non-potable water.

Keywords: Amman districts, ArcGIS, Rational method, Roof top rain water harvesting.

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Authors: Panikos Heracleous

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In this study, the use of silicon NAM (Non-Audible Murmur) microphone in automatic speech recognition is presented. NAM microphones are special acoustic sensors, which are attached behind the talker-s ear and can capture not only normal (audible) speech, but also very quietly uttered speech (non-audible murmur). As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech conversion etc.) for sound-impaired people. Using a small amount of training data and adaptation approaches, 93.9% word accuracy was achieved for a 20k Japanese vocabulary dictation task. Non-audible murmur recognition in noisy environments is also investigated. In this study, further analysis of the NAM speech has been made using distance measures between hidden Markov model (HMM) pairs. It has been shown the reduced spectral space of NAM speech using a metric distance, however the location of the different phonemes of NAM are similar to the location of the phonemes of normal speech, and the NAM sounds are well discriminated. Promising results in using nonlinear features are also introduced, especially under noisy conditions.

Keywords: Speech recognition, unvoiced speech, nonlinear features, HMM distance measures

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Authors: M. Veeresham

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The microstructure, texture, phase stability, and tensile properties of annealed Ta_0.5Nb_0.5Hf_0.5ZrTi_1.5 alloy have been investigated in the present research. The alloy was severely hybrid-rolled up to 93.5% thickness reduction, subsequently rolled samples subjected to an annealing treatment at 800 °C and 1000 °C temperatures for 1 h. Consequently, the rolled condition and both annealed temperatures have a body-centered cubic (BCC) structure. Furthermore, quantitative texture measurements (orientation distribution function (ODF) analysis) and microstructural examinations (analytical electron backscatter diffraction (EBSD) maps) permitted to establish a good relationship between annealing texture and microstructure and universal testing machine (UTM) utilized for obtaining the mechanical properties. Impressive room temperature tensile properties combination with the tensile strength (1380 MPa) and (24.7%) elongation is achieved for the 800 °C heat-treated condition. The evolution of the coarse microstructure featured in the case of 1000 °C annealed temperature ascribed to the influence of high thermal energy.

Keywords: Refractory high entropy alloys, hybrid-rolling, recrystallization, microstructure, tensile properties.

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Authors: Njiri J. G., Ikua B. W., Nyakoe G. N.

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Optimization of cutting parameters important in precision machining in regards to efficiency and surface integrity of the machined part. Usually productivity and precision in machining is limited by the forces emanating from the cutting process. Due to the inherent varying nature of the workpiece in terms of geometry and material composition, the peak cutting forces vary from point to point during machining process. In order to increase productivity without compromising on machining accuracy, it is important to control these cutting forces. In this paper a fuzzy logic control algorithm is developed that can be applied in the control of peak cutting forces in milling of spherical surfaces using ball end mills. The controller can adaptively vary the feedrate to maintain allowable cutting force on the tool. This control algorithm is implemented in a computer numerical control (CNC) machine. It has been demonstrated that the controller can provide stable machining and improve the performance of the CNC milling process by varying feedrate.

Keywords: Ball-end mill, feedrate, fuzzy logic controller, machining optimization, spherical surface.

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Authors: Changyi Liu, Gui Wang, Matthew Dargusch

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Helical milling operations are used to generate or enlarge boreholes by means of a milling tool. The bore diameter can be adjusted through the diameter of the helical path. The kinematics of helical milling on a three axis machine tool is analysed firstly. The relationships between processing parameters, cutting tool geometry characters with machined hole feature are formulated. The feed motion of the cutting tool has been decomposed to plane circular feed and axial linear motion. In this paper, the time varying cutting forces acted on the side cutting edges and end cutting edges of the flat end cylinder miller is analysed using a discrete method separately. These two components then are combined to produce the cutting force model considering the complicated interaction between the cutters and workpiece. The time varying cutting force model describes the instantaneous cutting force during processing. This model could be used to predict cutting force, calculate statics deflection of cutter and workpiece, and also could be the foundation of dynamics model and predicting chatter limitation of the helical milling operations.

Keywords: Helical milling, Hole machining, Cutting force, Analytical model, Time domain

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Authors: Moustapha Bande, Hakima Ould-Slimane, Hanifa Boucheneb

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Software development for complex systems requires efficient and automatic tools that can be used to verify the satisfiability of some critical properties such as security ones. With the emergence of Aspect-Oriented Programming (AOP), considerable work has been done in order to better modularize the separation of concerns in the software design and implementation. The goal is to prevent the cross-cutting concerns to be scattered across the multiple modules of the program and tangled with other modules. One of the key challenges in the aspect-oriented programs is to be sure that all the pieces put together at the weaving time ensure the satisfiability of the overall system requirements. Our paper focuses on this problem and proposes a formal property verification approach for a given property from the woven program. The approach is based on the control flow graph (CFG) of the woven program, and the use of a satisfiability modulo theories (SMT) solver to check whether each property (represented par one aspect) is satisfied or not once the weaving is done.

Keywords: Aspect-oriented programming, control flow graph, satisfiability modulo theories, property verification.

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: Cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet.

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Authors: Nawaporn Srisarankullawong

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The study on the design of decorative flower patterns from Suansunandha Palace is a innovative design using flowers grown in Suansunandha Palace as the original sources. The research tools included: 1) The photographs of flowers in water colors painted by one of the ladies in waiting of Her Royal Highness Princess Saisawareepirom as the source for investigating flowers grown in Suansunandha Palace 2) Pictures of real flowers grown in Suansunandha Palace 3) Adobe Illustrator Program and Adobe Photoshop Program in designing motifs and decorative patterns including prototypes. The researcher chose 3 types of Suansunandha Palace’s flowers; moss roses, orchids, and lignum vitae. The details of the flowers were simplified to create motifs for more elaborative decorative patterns. There were 4 motifs adapted from moss roses, 3 motifs adapted from orchids, and 3 motifs adapted from lignum vitae. The patterns were used to decorate photo frames, wrapping paper, and gift boxes or souvenir boxes.

Keywords: Suansunandha Palace, decoration design, floral pattern.

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Authors: Abu Bakar Sedek Abdul Jamak, Saridan Abu Bakar, Zulkipli Ghazali, Roselind Wan

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The majority of micro-entrepreneurs in Malaysia operate very small-scaled business activities such as food stalls, burger stalls, night market hawkers, grocery stores, constructions, rubber and oil palm small holders, and other agro-based services and activities. Why are they venturing into entrepreneurship - is it for survival, out of interest or due to encouragement and assistance from the local government? And why is it that some micro-entrepreneurs are lagging behind in entrepreneurship, and what do they need to rectify this situation so that they are able to progress further? Furthermore, what are the skills that the micro entrepreneurs should developed to transform them into successful micro-enterprises and become small and medium-sized enterprises (SME)? This paper proposes a 7-Step approach that can serve as a basis for identification of critical entrepreneurial success factors that enable policy makers, practitioners, consultants, training managers and other agencies in developing tools to assist micro business owners. This paper also highlights the experience of one of the successful companies in Malaysia that has transformed from micro-enterprise to become a large organization in less than 10 years.

Keywords: Entrepreneurship, Micro-entrepreneurs, Transformation, Customers

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Authors: Ayedh Alqahtani, Andrew Whyte

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Life Cycle Cost (LCC) is one of the goals and key pillars of the construction management science because it comprises many of the functions and processes necessary, which assist organisations and agencies to achieve their goals. It has therefore become important to design and control assets during their whole life cycle, from the design and planning phase through to disposal phase. LCCA is aimed to improve the decision making system in the ownership of assets by taking into account all the cost elements including to the asset throughout its life. Current application of LCC approach is impractical during misunderstanding of the advantages of LCC. This main objective of this research is to show a different relationship between capital cost and long-term running costs. One hundred and thirty eight actual building projects in United Kingdom (UK) were used in order to achieve and measure the above-mentioned objective of the study. The result shown that LCC is one of the most significant tools should be considered on the decision making process.

Keywords: Building projects, Capital cost, Life cycle cost, Maintenance costs, Operation costs.

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Authors: J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar

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The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.

Keywords: Medical Image Mining, Data Mining, Feature Weighting, Association Rule Mining, k nearest neighbor classifier.

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Authors: Jieun Song, Taesung Kim, Sokjoon Lee, Howon Kim

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Recently, the RFID (Radio Frequency Identification) technology attracts the world market attention as essential technology for ubiquitous environment. The RFID market has focused on transponders and reader development. But that concern has shifted to RFID software like as high-valued e-business applications, RFID middleware and related development tools. However, due to the high sensitivity of data and service transaction within the RFID network, security consideration must be addressed. In order to guarantee trusted e-business based on RFID technology, we propose a security enhanced RFID middleware system. Our proposal is compliant with EPCglobal ALE (Application Level Events), which is standard interface for middleware and its clients. We show how to provide strengthened security and trust by protecting transported data between middleware and its client, and stored data in middleware. Moreover, we achieve the identification and service access control against illegal service abuse. Our system enables secure RFID middleware service and trusted e-business service.

Keywords: RFID Middleware, ALE (Application Level Events), Security.

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Authors: Md. Ashikur Rahman Khan, M. M. Rahman

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Electrical discharge machining (EDM) is a relatively modern machining process having distinct advantages over other machining processes and can machine Ti-alloys effectively. The present study emphasizes the features of the development of regression equation based on response surface methodology (RSM) for correlating the interactive and higher-order influences of machining parameters on surface finish of Titanium alloy Ti-6Al-4V. The process parameters selected in this study are discharge current, pulse on time, pulse off time and servo voltage. Machining has been accomplished using negative polarity of Graphite electrode. Analysis of variance is employed to ascertain the adequacy of the developed regression model. Experiments based on central composite of response surface method are carried out. Scanning electron microscopy (SEM) analysis was performed to investigate the surface topography of the EDMed job. The results evidence that the proposed regression equation can predict the surface roughness effectively. The lower ampere and short pulse on time yield better surface finish.

Keywords: Graphite electrode, regression model, response surface methodology, surface roughness.

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Authors: Ahmed Arara

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Information sharing and exchange, rather than information processing, is what characterizes information technology in the 21st century. Ontologies, as shared common understanding, gain increasing attention, as they appear as the most promising solution to enable information sharing both at a semantic level and in a machine-processable way. Domain Ontology-based modeling has been exploited to provide shareability and information exchange among diversified, heterogeneous applications of enterprises. Contextual ontologies are “an explicit specification of contextual conceptualization". That is: ontology is characterized by concepts that have multiple representations and they may exist in several contexts. Hence, contextual ontologies are a set of concepts and relationships, which are seen from different perspectives. Contextualization is to allow for ontologies to be partitioned according to their contexts. The need for contextual ontologies in enterprise modeling has become crucial due to the nature of today's competitive market. Information resources in enterprise is distributed and diversified and is in need to be shared and communicated locally through the intranet and globally though the internet. This paper discusses the roles that ontologies play in an enterprise modeling, and how ontologies assist in building a conceptual model in order to provide communicative and interoperable information systems. The issue of enterprise modeling based on contextual domain ontology is also investigated, and a framework is proposed for an enterprise model that consists of various applications.

Keywords: Contextual ontologies, Enterprise model, domainontology.

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Authors: Young Kuen Cho, Dae Won Lee, Young-Jin Jung, Sung Kuk Kim, Dong-Hyun Seo, Chang-Yong Ko, Han Sung Kim

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Many medical devices are driven by motor pumps. Some researchers reported that the vibration mainly affected medical devices using a motor pump. The purpose of this study was to examine the effect of stiffness and damping coefficient in a 3-dimensional (3D) model of a motor pump and spring. In the present paper, experimental and mathematical tests for the moments of inertia of the 3D model and the material properties were investigated by an INSTRON machine. The response surfaces could be generated by using 3D multi-body analysis and the design of experiment method. It showed that differences in contours of the response surface were clearly found for the particular area. Displacement of the center of the motor pump was decreased at K≈2000 N/M, C≈12.5 N-sec/M. However, the frequency was increased at K≈2000 N/M, C≈15 N-sec/M. In this study, this study suggested experimental technique for vibration reduction for a motor pump in medical device. The combined method suggested in this study will greatly contribute to design of medical devices concerning vibration and noise intervention.

Keywords: Motor pump, Spring, Vibration reduction, Medicaldevices, Moment of Inertia

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Authors: Abbas Al-Refaie

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This paper aims at improving the performance of the tableting process using statistical quality control and fuzzy goal programming. The tableting process was studied. Statistical control tools were used to characterize the existing process for three critical responses including the averages of a tablet’s weight, hardness, and thickness. At initial process factor settings, the estimated process capability index values for the tablet’s averages of weight, hardness, and thickness were 0.58, 3.36, and 0.88, respectively. The L₉ array was utilized to provide experimentation design. Fuzzy goal programming was then employed to find the combination of optimal factor settings. Optimization results showed that the process capability index values for a tablet’s averages of weight, hardness, and thickness were improved to 1.03, 4.42, and 1.42, respectively. Such improvements resulted in significant savings in quality and production costs.

Keywords: Fuzzy goal programming, control charts, process capability, tablet optimization.

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Authors: Linnea Stenliden

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The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors within Actor-network theory (ANT). The learning conditions are found to be distinguished by broad complexity, characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.

Keywords: Analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation.

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Authors: Khalid Al Siyabi, Angie Al Habib

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To measure or asses any government’s efficiency we need to measure the performance of this government in regards to the quality of the service it provides. Using a technological platform in service provision became a trend and a public demand. It is also a public need to make sure these services are aligned to values and to the whole government’s strategy, vision and goals as well. Providing services using technology tools and channels can enhance the internal business process and also help establish many essential values to government services like transparency and excellence, since in order to establish e-services many standards and policies must be put in place to enable the handing over of decision making to a mature system oriented mechanism. There was no doubt that the Sultanate of Oman wanted to enhance its services and move it towards automation and establishes a smart government as well as links its services to life events. Measuring government efficiency is very essential in achieving social security and economic growth, since it can provide a clear dashboard of all projects and improvements. Based on this data we can improve the strategies and align the country goals to them.

Keywords: Government, Maturity, Oman, Performance, Service.

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Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

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Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words, classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar.

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Authors: Mariam Abdulaziz Y.Esmaeel

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The study aimed to identify the nature of autistic talent, the manifestations of their weak central coherence, and their sensory characteristics. The case study consisted of four talented autistic males. Two of them in drawing, one in clay formation and one in jigsaw puzzle. Tools of data collection were Group Embedded Figures Test, Block Design Test, Sensory Profile Checklist Revised, Interview forms and direct observation. Results indicated that talent among autistics emerges in limited domain and being extraordinary for each case. Also overlapping construction properties. Indeed, they show three perceptual aspects of weak central coherence: The weak in visual spatial-constructional coherence, the weak in perceptual coherence and the weak in verbal – semantic coherence. Moreover, the majority of the study cases used the three strategies of weak central coherence (segmentation, obliqueness and rotation). As for the sensory characteristics, all study cases have numbers of that characteristics that especially emerges in the visual system.

Keywords: Autism, Central Coherence, Savant, Sensory characteristics, Talent.

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Authors: S. Chadsuthi, W. Triampo, C. Modchang, P. Kanthang, D. Triampo, N. Nuttavut

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We present analysis of spatial patterns of generic disease spread simulated by a stochastic long-range correlation SIR model, where individuals can be infected at long distance in a power law distribution. We integrated various tools, namely perimeter, circularity, fractal dimension, and aggregation index to characterize and investigate spatial pattern formations. Our primary goal was to understand for a given model of interest which tool has an advantage over the other and to what extent. We found that perimeter and circularity give information only for a case of strong correlation– while the fractal dimension and aggregation index exhibit the growth rule of pattern formation, depending on the degree of the correlation exponent (β). The aggregation index method used as an alternative method to describe the degree of pathogenic ratio (α). This study may provide a useful approach to characterize and analyze the pattern formation of epidemic spreading

Keywords: spatial pattern epidemics, aggregation index, fractaldimension, stochastic, long-rang epidemics

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Authors: Laila Zahran Mohammed Alsibani

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The aim of the research is to understand the aspects of semiotics in contemporary designs by redesigning an Omani donut brand with localized cultural identity. To do so, visual identity samples of Dice brand of donuts in Oman has been selected to be a case study. This study conducted based on semiotic theory by using mixed method research tools which are: documentation analysis, interview and survey. The literature review concentrates on key areas of semiotics in visual elements used in the brand designs. Also, it spotlights on the categories of semiotics in visual design. In addition, this research explores the visual cues in brand identity. The objectives of the research are to investigate the aspects of semiotics in providing meaning to visual cues and to identify visual cues for each visual element. It is hoped that this study will have the contribution to a better understanding of the different ways of using semiotics in contemporary designs. Moreover, this research can be a reference for further studies in understanding and explaining current and future design trends. Future research can also focus on how brand-related signs are perceived by consumers.

Keywords: Brands, semiotics, visual arts, visual communication.

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Authors: Sultan Daud, John P. Forth, Nikolaos Nikitas

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The current study aims to highlight the loading characteristics impact on the time evolution (focusing particularly on long term effects) of the deformation of realized reinforced concrete beams. Namely the tension stiffening code provisions (i.e. within Eurocode 2) are reviewed with a clear intention to reassess their operational value and predicting capacity. In what follows the experimental programme adopted along with some preliminary findings and numerical modeling attempts are presented. For a range of long slender reinforced concrete simply supported beams (4200 mm) constant static sustained and repeated cyclic loadings were applied mapping the time evolution of deformation. All experiments were carried out at the Heavy Structures Lab of the University of Leeds. During tests the mid-span deflection, creep coefficient and shrinkage strains were monitored for duration of 90 days. The obtained results are set against the values predicted by Eurocode 2 and the tools within an FE commercial package (i.e. Midas FEA) to yield that existing knowledge and practise is at times over-conservative.

Keywords: Eurocode2, midas fea, repeated, sustained loading.

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Authors: Siriporn Poolsuwan, Kanyarat Bussaban

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This research aims to investigate and analyze user’s behaviour towards the utilization of the online news clipping database at Suan Sunandha Rajabhat University, Thailand. Data is gathered from 214 lecturers and 380 undergraduate students by using questionnaires. Findings show that most users knew the online news clipping service from their friends, library’s website and their teachers. The users learned how to use it by themselves and others learned by training of SSRU library. Most users used the online news clipping database one time per month at home and always used the service for general knowledge, up-to-date academic knowledge and assignment reference. Moreover, the results of using the online news clipping service problems include the users themselves, service management, service device- computer and tools – and the network, service provider, and publicity. This research would be benefit for librarians and teachers for planning and designing library services in their works and organization

Keywords: Online Database, User Behaviour.

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Authors: M. Michael Gromiha, A. Mary Thangakani, Sandeep Kumar, D. Velmurugan

Abstract:

The main cause of several neurodegenerative diseases such as Alzhemier, Parkinson and spongiform encephalopathies is formation of amyloid fibrils and plaques in proteins. We have analyzed different sets of proteins and peptides to understand the influence of sequence based features on protein aggregation process. The comparison of 373 pairs of homologous mesophilic and thermophilic proteins showed that aggregation prone regions (APRs) are present in both. But, the thermophilic protein monomers show greater ability to ‘stow away’ the APRs in their hydrophobic cores and protect them from solvent exposure. The comparison of amyloid forming and amorphous b-aggregating hexapeptides suggested distinct preferences for specific residues at the six positions as well as all possible combinations of nine residue pairs. The compositions of residues at different positions and residue pairs have been converted into energy potentials and utilized for distinguishing between amyloid forming and amorphous b-aggregating peptides. Our method could correctly identify the amyloid forming peptides at an accuracy of 95-100% in different datasets of peptides.

Keywords: Aggregation prone regions, amyloids, thermophilic proteins, amino acid residues, machine learning.

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