Search results for: Shape Memory Materials

Authors: J. Zach, J. Hroudova, J. Brozovsky

Abstract:

Thermal insulation materials based on natural fibers represent a very promising area of materials based on natural easy renewable row sources. These materials may be in terms of the properties of most competing synthetic insulations, but show somewhat higher moisture sensitivity and thermal insulation properties are strongly influenced by the density and orientation of fibers. The paper described the problem of hygrothermal behavior of thermal insulation materials based on natural plant and animal fibers. This is especially the dependence of the thermal properties of these materials on the type of fiber, bulk density, temperature, moisture and the fiber orientation.

Keywords: Thermal insulating materials, hemp fibers, sheep wool fibers, thermal conductivity, moisture.

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Authors: Oh-Yeol Kwon, Sung-Il Chien

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A conventional image posterization method occasionally fails to preserve the shape and color of objects due to the uneffective color reduction. This paper proposes a new image posterizartion method by using modified color quantization for preserving the shape and color of objects and color contrast enhancement for improving lightness contrast and saturation. Experiment results show that our proposed method can provide visually more satisfactory posterization result than that of the conventional method.

Keywords: Color contrast enhancement, color quantization, color segmentation, image posterization

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Authors: Mandhapati P. Raju, Siddhartha Khaitan

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In-core memory requirement is a bottleneck in solving large three dimensional Navier-Stokes finite element problem formulations using sparse direct solvers. Out-of-core solution strategy is a viable alternative to reduce the in-core memory requirements while solving large scale problems. This study evaluates the performance of various out-of-core sequential solvers based on multifrontal or supernodal techniques in the context of finite element formulations for three dimensional problems on a Windows platform. Here three different solvers, HSL_MA78, MUMPS and PARDISO are compared. The performance of these solvers is evaluated on a 64-bit machine with 16GB RAM for finite element formulation of flow through a rectangular channel. It is observed that using out-of-core PARDISO solver, relatively large problems can be solved. The implementation of Newton and modified Newton's iteration is also discussed.

Keywords: Out-of-core, PARDISO, MUMPS, Newton.

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Authors: N. Azadi-Tinat, H. Oraizi

Abstract:

Design of compact UWB multilayered microstrip filter with E-shape resonator is presented, which provides wide stopband up to 20 GHz and arbitrary impedance matching. The design procedure is developed based on the method of least squares and theory of N-coupled transmission lines. The dimensions of designed filter are about 11 mm × 11 mm and the three E-shape resonators are placed among four dielectric layers. The average insertion loss in the passband is less than 1 dB and in the stopband is about 30 dB up to 20 GHz. Its group delay in the UWB region is about 0.5 ns. The performance of the optimized filter design perfectly agrees with the microwave simulation softwares.

Keywords: Ultra-wideband, method of least square, multilayer microstrip filter, n-coupled transmission lines.

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Authors: M. Areekijseree, W. Pongsawat, M. Pumipaiboon, C. Thepsithar, S. Sengsai, T. Chuen-Im

Abstract:

Morphological interaction of porcine cumulus-oocyte complexes (pCOCs) was investigated on in vitro condition using electron microscope (SEM and TEM). The totals of 1,923 oocytes were round in shape, surrounded by Zona pellucida with layer of cumulus cells ranging between 59.29-202.14 μm in size. They were classified into intact-, multi-, partial cumulus cell layer oocyte, and completely denuded oocyte, at the percentage composition of 22.80% 32.70%, 18.60%, and 25.90 % respectively. The pCOCs classified as intact- and multi cumulus cell layer oocytes were further culturing at 37°C with 5% CO2, 95% air atmosphere and high humidity for 44 h in M199 with Earle’s salts supplemented with 10% HTFCS, 2.2 mg/mL NaHCO3, 1 M Hepes, 0.25 mM pyruvate, 15 μg/mL porcine follicle-stimulating hormone, 1 μg/mL LH, 1μg/mL estradiol with ethanol, and 50 μg/mL gentamycin sulfate. On electron microscope study, cumulus cells were found to stick their processes to secrete substance from the sac-shape end into Zona pellucida of the oocyte and also communicated with the neighboring cells through their microvilli on the beginning of incubation period. It is believed that the cumulus cells communicate with the oocyte by inserting the microvilli through this gap and embedded in the oocyte cytoplasm before secreting substance, through the sac-shape end of the microvilli, to inhibit primary oocyte development at the prophase I. Morphological changes of the complexes were observed after culturing for 24-44 h. One hundred percentages of the cumulus layers were expanded and cumulus cells were peeling off from the oocyte surface. In addition, the round-shape cumulus cells transformed themselves into either an elongate shape or a columnar shape, and no communication between cumulus neighboring cells. After 44 h of incubation time, diameter of oocytes surrounded by cumulus cells was larger than 0 h incubation. The effect of hormones in culture medium is exerted by their receptors present in porcine oocyte. It is likely that all morphological changes of the complexes after hormone treatment were to allow maturation of the oocyte. This study demonstrated that the association of hormones in M199 could promote porcine follicle activation in 44 h in vitro condition. This culture system should be useful for studying the regulation of early follicular growth and development, especially because these follicles represent a large source of oocytes that could be used in vitro for cell technology.

Keywords: Cumulus cells, electron microscopy (SEM and TEM), in vitro, porcine oocyte.

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Authors: G. Candel, D. Naccache

Abstract:

t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embedding. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic, and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n2) to O(n2/k), and the memory requirement from n2 to 2(n/k)2 which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.

Keywords: Concept drift, data visualization, dimension reduction, embedding, monitoring, reusability, t-SNE, unsupervised learning.

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Authors: Pei. P. Tan, Don. U.A. Galagedera, Elizabeth A.Maharaj

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This paper examines predictability in stock return in developed and emergingmarkets by testing long memory in stock returns using wavelet approach. Wavelet-based maximum likelihood estimator of the fractional integration estimator is superior to the conventional Hurst exponent and Geweke and Porter-Hudak estimator in terms of asymptotic properties and mean squared error. We use 4-year moving windows to estimate the fractional integration parameter. Evidence suggests that stock return may not be predictable indeveloped countries of the Asia-Pacificregion. However, predictability of stock return insome developing countries in this region such as Indonesia, Malaysia and Philippines may not be ruled out. Stock return in the Thailand stock market appears to be not predictable after the political crisis in 2008.

Keywords: Asia-Pacific stock market, long-memory, return predictability, wavelet

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Authors: H. B. Tibar, Z. Y. Jiang

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In this study, the influence of rolling process parameters such as the work roll cross angle and work roll shifting value on the strip shape and profile of aluminum have been investigated under dry conditions at a speed ratio of 1.3 using Hille 100 experimental mill. The strip profile was found to improve significantly with increase in work roll cross angle from 0^o to 1^o, with an associated decrease in rolling force. The effect of roll shifting (from 0 to 8mm) was not as significant as the roll cross angle. However, an increase in work roll shifting value achieved a similar decrease in rolling force as that of work roll cross angle. The effect of work roll shifting was also found to be maximum at an optimum roll speed of 0.0986 m/s for the desired thickness. Of all these parameters, the most significant effect of the strip shape profile was observed with variation of work roll cross angle. However, the rolling force can be a significantly reduced by either increasing the the work roll cross angle or work roll shifting.

Keywords: Rolling speed ratio, strip shape, work roll cross angle, work roll shifting.

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Authors: Yehjune Heo

Abstract:

As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: Younes Matar, Fabien Candelier, Camille Solliec

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The aim of this study is to investigate the kinematics of undulatory elongated fish swimming against a velocity flow. We perform the experiments on European eel Anguilla Anguilla swimming in a hydrodynamic re-circulating tank with the velocity flow fixed at 0.2 m/s. We find that the undulating shape of overall eel body changes when it swims slantwise from the flow direction, by comparison to axial undulation shape. We examine this kinematics and we propose a general equation describing the lateral position of undulation body taking into account the direction of the eel-s swimming.

Keywords: Undulatory swimming, maneuver, eel Anguilla Anguilla, biomechanic.

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Authors: Anjali Sadanand, R. V. Nagarajan

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Architecture morphs with advances in technology and the roof, wall, and floor as basic elements of a building, follow in redefining themselves over time. Their contribution is bound by time and held by design principles that deal with function, sturdiness, and beauty. Architecture engages with people to give joy through its form, material, design structure, and spatial qualities. This paper attempts to re-interpret John Ruskin’s “Seven lamps of Architecture” in the context of the architecture of the modern and present period. The paper focuses on the “wall” as an element of study in this context. Four of Ruskin’s seven lamps will be discussed, namely beauty, truth, life, and memory, through examples of architecture ranging from modernism to contemporary architecture of today. The study will focus on the relevance of Ruskin’s principles to the “wall” in specific, in buildings of different materials and over a range of typologies from all parts of the world. Two examples will be analyzed for each lamp. It will be shown that in each case, there is relevance to the significance of Ruskin’s lamps in modern and contemporary architecture. Nature to which Ruskin alludes to for his lamp of “beauty” is found in the different expressions of interpretation used by Corbusier in his Villa Stein façade based on proportion found in nature and in the direct expression of Toyo Ito in his translation of an understanding of the structure of trees into his façade design of the showroom for a Japanese bag boutique. “Truth” is shown in Mies van der Rohe’s Crown Hall building with its clarity of material and structure and Studio Mumbai’s Palmyra House, which celebrates the use of natural materials and local craftsmanship. “Life” is reviewed with a sustainable house in Kerala by Ashrams Ravi and Alvar Aalto’s summer house, which illustrate walls as repositories of intellectual thought and craft. “Memory” is discussed with Charles Correa’s Jawahar Kala Kendra and Venturi’s Vana Venturi house and discloses facades as text in the context of its materiality and iconography. Beauty is reviewed in Villa Stein and Toyo Ito’s Branded Retail building in Tokyo. The paper thus concludes that Ruskin’s Lamps can be interpreted in today’s context and add richness to meaning to the understanding of architecture.

Keywords: Beauty, design, façade, modernism.

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Authors: I. S. Jung, W. H. Jung, S. H. Baek, S. Kang

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This paper describes the shape optimization of impeller blades for a anti-heeling bidirectional axial flow pump used in ships. In general, a bidirectional axial pump has an efficiency much lower than the classical unidirectional pump because of the symmetry of the blade type. In this paper, by focusing on a pump impeller, the shape of blades is redesigned to reach a higher efficiency in a bidirectional axial pump. The commercial code employed in this simulation is CFX v.13. CFD result of pump torque, head, and hydraulic efficiency was compared. The orthogonal array (OA) and analysis of variance (ANOVA) techniques and surrogate model based optimization using orthogonal polynomial, are employed to determine the main effects and their optimal design variables. According to the optimal design, we confirm an effective design variable in impeller blades and explain the optimal solution, the usefulness for satisfying the constraints of pump torque and head.

Keywords: Bidirectional axial flow pump, Impeller blade, CFD, Analysis of variance, Polynomial surrogate model

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Authors: Hassan Ghasemzadeh, Sepideh Mazrouee, Hassan Goldani Moghaddam, Hamid Shojaei, Mohammad Reza Kakoee

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Block replacement algorithms to increase hit ratio have been extensively used in cache memory management. Among basic replacement schemes, LRU and FIFO have been shown to be effective replacement algorithms in terms of hit rates. In this paper, we introduce a flexible stack-based circuit which can be employed in hardware implementation of both LRU and FIFO policies. We propose a simple and efficient architecture such that stack-based replacement algorithms can be implemented without the drawbacks of the traditional architectures. The stack is modular and hence, a set of stack rows can be cascaded depending on the number of blocks in each cache set. Our circuit can be implemented in conjunction with the cache controller and static/dynamic memories to form a cache system. Experimental results exhibit that our proposed circuit provides an average value of 26% improvement in storage bits and its maximum operating frequency is increased by a factor of two

Keywords: Cache Memory, Replacement Algorithms, LeastRecently Used Algorithm, First In First Out Algorithm.

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Authors: Hendry Muljadi, Hideaki Takeda, Koichi Ando

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A manufacturing feature can be defined simply as a geometric shape and its manufacturing information to create the shape. In a feature-based process planning system, feature library plays an important role in the extraction of manufacturing features with their proper manufacturing information. However, to manage the manufacturing information flexibly, it is important to build a feature library that is easy to modify. In this paper, a Wiki-based feature library is proposed.

Keywords: Manufacturing feature, feature library, feature ontology, process planning, Wiki, MediaWiki.

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Authors: Motonobu Hattori

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In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.

Keywords: catastrophic forgetting, chaotic neural network, complementary learning systems, dual-network

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Authors: Sarka Keprdova, Nikol Zizkova

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This paper focuses on the presentation of results which were obtained as a part of the project FR-TI 3/742: “System of Lightweight Materials for Finishing of Buildings with Waste Raw Materials”. Attention was paid to the light weighting of polymermodified mortars applicable as adhesives, screeds and repair mortars. In terms of repair mortars, they were ones intended for the sanitation of aerated concrete.

Keywords: Additives, light aggregates, lightweight materials, lightweight mortars, polymer-modified mortars.

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Authors: Kyoungwoo Park, Byeong Sam Kim, Hyo-Jae Lim, Ji Won Han, Park Kyoun Oh, Juhee Lee, Keun-Yeol Yu

Abstract:

Predictions of flow and heat transfer characteristics and shape optimization in internally finned circular tubes have been performed on three-dimensional periodically fully developed turbulent flow and thermal fields. For a trapezoidal fin profile, the effects of fin height h, upper fin widths d1, lower fin widths d2, and helix angle of fin ? on transport phenomena are investigated for the condition of fin number of N = 30. The CFD and mathematical optimization technique are coupled in order to optimize the shape of internally finned tube. The optimal solutions of the design variables (i.e., upper and lower fin widths, fin height and helix angle) are numerically obtained by minimizing the pressure loss and maximizing the heat transfer rate, simultaneously, for the limiting conditions of d1 = 0.5~1.5 mm, d2 = 0.5~1.5 mm, h= 0.5~1.5mm, ? = 10~30 degrees. The fully developed flow and thermal fields are predicted using the finite volume method and the optimization is carried out by means of the multi-objective genetic algorithm that is widely used in the constrained nonlinear optimization problem.

Keywords: Computational fluid dynamics, Genetic algorithm, Internally finned tube with helix angle, Optimization.

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Authors: Rama Shanker, Anil Kumar Sachan

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Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.

Keywords: Aggregate Proportions, Artificial Neural Network, Concrete Grade, Concrete Mix Design.

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Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga

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In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.

Keywords: Optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory.

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Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga

Abstract:

In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.

Keywords: Optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory.

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Authors: Punya Tepsing

Abstract:

This research aimed to study the beliefs in auspicious materials of entrepreneurs in Muang Hat Yai. The data were collected via documentary research and field work including interviews, observations shops in Hat Yai which used auspicious materials to bring lucks to the shops. The results were as follows. The beliefs in auspicious materials that the entrepreneurs had were of three areas: 1) The auspicious materials could correct the improperness of the shop location, for example, the shop situated opposite a branch road, a shrine, or a bank. The owner usually corrected it by putting Chinese auspicious materials in front of or in the shop, for example, a lion holding a sword in his mouth, or a mirror, etc. 2) The auspicious materials could bring in more income. The owner of the shop usually put the auspicious materials such as a cat beckoning and a bamboo fish trap believed to trap money in front of or inside the shop. 3) The auspicious materials like turtles, paired fish and a monster holding the moon in his mouth could solve life problems including health, family, and safety problems. The use of these auspicious materials showed the blending of the beliefs of the Chinese shop entrepreneurs with the Thai folk beliefs. What is interesting is that Hat Yai is located near the three southern border provinces which are the unrest area and this may cause the number of tourists to decline. This prompted them to build a mechanism in adjusting themselves both to save their lives and to increase the number of customers. Auspicious materials can make them feel more confident.

Keywords: Belief, auspicious materials, shop, entrepreneur, Maung Hat Yai.

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Authors: Valeriya Tyo, Serikbolat Yessengabulov

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Regions with extreme climate conditions such as Astana city require energy saving measures to increase energy performance of buildings which are responsible for more than 40% of total energy consumption. Identification of optimal building geometry is one of key factors to be considered. Architectural form of a building has impact on space heating and cooling energy use, however the interrelationship between the geometry and resultant energy use is not always readily apparent. This paper presents a comparative case study of two prototypical buildings with compact building shape to assess its impact on energy performance.

Keywords: Building geometry, energy efficiency, heat gain, heat loss.

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Authors: Michael T. Ajayi, Oluwakemi E. Fapojuwo

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Farmers are in need of regular and relevant information relating to new technologies. Production of extension materials has been found to be useful in facilitating the process. Extension materials help to provide information to reach large numbers of farmers quickly and economically. However, as good as extension materials are, previous materials produced are not used by farmers. The reasons for this include lack of involvement of farmers in the production of the extension materials, most of the extension materials are not relevant to the farmers’ environments, the agricultural extension agents lack capacity to prepare the materials, and many extension agents lack commitment. These problems led to this innovative capacity building of extension agents. This innovative approach involves five stages. The first stage is the diagnostic survey of farmers’ environment to collect useful information. The second stage is the development and production of draft extension materials. The third stage is the field testing and evaluation of draft materials by the same famers that were involved at the diagnostic stage. The fourth stage is the revision of the draft extension materials by incorporating suggestions from farmers. The fifth stage is the action plans. This process improves the capacity of agricultural extension agents in the preparation of extension materials and also promotes engagement of farmers and beneficiaries in the process. The process also makes farmers assume some level of ownership of the exercise and the extension materials.

Keywords: Capacity building, dissemination, extension agents, information/technologies.

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Authors: Zeinab Jokar, Mohammad Reza Moslemi

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In this work, we study the behavior of introducing atomic size vacancy in a graphene nanoribbon superlattice. Our investigations are based on the density functional theory (DFT) with the Local Density Approximation in Atomistix Toolkit (ATK). We show that, in addition to its shape, the position of vacancy has a major impact on the electrical properties of a graphene nanoribbon superlattice. We show that the band gap of an armchair graphene nanoribbon may be tuned by introducing an appropriate periodic pattern of vacancies. The band gap changes in a zig-zag manner similar to the variation of band gap of a graphene nanoribbon by changing its width.

Keywords: Antidot, Atomistix ToolKit, Superlattice, Vacancy.

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Authors: Borna Jafarpour, Azadeh Nematzadeh, Vahid Kazempour, Babak Sadeghian

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Cellular automata have been used for design of cryptosystems. Recently some secret sharing schemes based on linear memory cellular automata have been introduced which are used for both text and image. In this paper, we illustrate that these secret sharing schemes are vulnerable to dishonest participants- collusion. We propose a cheating model for the secret sharing schemes based on linear memory cellular automata. For this purpose we present a novel uniform model for representation of all secret sharing schemes based on cellular automata. Participants can cheat by means of sending bogus shares or bogus transition rules. Cheaters can cooperate to corrupt a shared secret and compute a cheating value added to it. Honest participants are not aware of cheating and suppose the incorrect secret as the valid one. We prove that cheaters can recover valid secret by removing the cheating value form the corrupted secret. We provide methods of calculating the cheating value.

Keywords: Cellular automata, cheating model, secret sharing, threshold scheme.

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Authors: Kang-Gyu Park, Sun-Jong Park, Hong Jae Yim, Hyo-Gyung Kwak

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This paper attempts to evaluate the effect of fire damage on concrete by using nonlinear resonance vibration method, one of the nonlinear nondestructive method. Concrete exhibits not only nonlinear stress-strain relation but also hysteresis and discrete memory effect which are contained in consolidated materials. Hysteretic materials typically show the linear resonance frequency shift. Also, the shift of resonance frequency is changed according to the degree of micro damage. The degree of the shift can be obtained through nonlinear resonance vibration method. Five exposure scenarios were considered in order to make different internal micro damage. Also, the effect of post-fire-curing on fire-damaged concrete was taken into account to conform the change in internal damage. Hysteretic nonlinearity parameter was obtained by amplitudedependent resonance frequency shift after specific curing periods. In addition, splitting tensile strength was measured on each sample to characterize the variation of residual strength. Then, a correlation between the hysteretic nonlinearity parameter and residual strength was proposed from each test result.

Keywords: Fire damaged concrete, nonlinear resonance vibration method, nonlinearity parameter, post-fire-curing, splitting tensile strength.

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Authors: T. Sungkaworn, W. Triampo, P. Nalakarn, D. Triampo, I. M. Tang, Y. Lenbury, P. Picha

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Semiconductor nanomaterials like TiO2 nanoparticles (TiO2-NPs) approximately less than 100 nm in diameter have become a new generation of advanced materials due to their novel and interesting optical, dielectric, and photo-catalytic properties. With the increasing use of NPs in commerce, to date few studies have investigated the toxicological and environmental effects of NPs. Motivated by the importance of TiO2-NPs that may contribute to the cancer research field especially from the treatment prospective together with the fractal analysis technique, we have investigated the effect of TiO2-NPs on colony morphology in the dark condition using fractal dimension as a key morphological characterization parameter. The aim of this work is mainly to investigate the cytotoxic effects of TiO2-NPs in the dark on the growth of human cervical carcinoma (HeLa) cell colonies from morphological aspect. The in vitro studies were carried out together with the image processing technique and fractal analysis. It was found that, these colonies were abnormal in shape and size. Moreover, the size of the control colonies appeared to be larger than those of the treated group. The mean Df +/- SEM of the colonies in untreated cultures was 1.085±0.019, N= 25, while that of the cultures treated with TiO2-NPs was 1.287±0.045. It was found that the circularity of the control group (0.401±0.071) is higher than that of the treated group (0.103±0.042). The same tendency was found in the diameter parameters which are 1161.30±219.56 μm and 852.28±206.50 μm for the control and treated group respectively. Possible explanation of the results was discussed, though more works need to be done in terms of the for mechanism aspects. Finally, our results indicate that fractal dimension can serve as a useful feature, by itself or in conjunction with other shape features, in the classification of cancer colonies.

Keywords: Tumor growth, Cell colonies, TiO2, Nanoparticles, Fractal, Morphology, Aggregation.

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Authors: Boukhzer Abdenbi, El Bikri Khalid, Benamar Rhali

Abstract:

In the present study, the problem of geometrically non-linear free vibrations of functionally graded rectangular plates (FGRP) is studied. The theoretical model, previously developed and based on Hamilton’s principle, is adapted here to determine the fundamental non-linear mode shape of these plates. Frequency parameters, displacements and stress are given for various power-law distributions of the volume fractions of the constituents and various aspect ratios. Good agreement with previous published results is obtained in the case of linear and non-linear analyses.

Keywords: Non-linear vibration, functionally graded materials, rectangular plates.

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Authors: Hui-Yu Huang, Shih-Hang Hsu

Abstract:

In this paper, we propose a robust scheme to work face alignment and recognition under various influences. For face representation, illumination influence and variable expressions are the important factors, especially the accuracy of facial localization and face recognition. In order to solve those of factors, we propose a robust approach to overcome these problems. This approach consists of two phases. One phase is preprocessed for face images by means of the proposed illumination normalization method. The location of facial features can fit more efficient and fast based on the proposed image blending. On the other hand, based on template matching, we further improve the active shape models (called as IASM) to locate the face shape more precise which can gain the recognized rate in the next phase. The other phase is to process feature extraction by using principal component analysis and face recognition by using support vector machine classifiers. The results show that this proposed method can obtain good facial localization and face recognition with varied illumination and local distortion.

Keywords: Gabor filter, improved active shape model (IASM), principal component analysis (PCA), face alignment, face recognition, support vector machine (SVM)

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Authors: N. N. Omehe

Abstract:

CdSiP2 and CdsiAs2 are nonlinear optical materials for near and mid-infrared applications. Density functional theory has been applied to study the structure, band gap, and optical properties of these materials. The pseudopotential method was used in the form of projector augmented wave (PAW) and norm-conserving, the band structure calculations yielded a band gap of 1.55 eV and 0.88 eV for CdSiP2 and CdsiAs2 respectively. The values of ε1(ω)  from the doelectric function calculations are 15 and 14.9 CdSiP2 and CdsiAs2 respectively.

Keywords: Band structure, chalcopyrite, near-infrared materials, mid-infrared materials, nonlinear material, optical properties.

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