Search results for: structure similarity (Ssim)

Authors: Uyen Tran Tu

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The decision on capital structure is one of the most important and sophisticated decisions in financial management in order to improve firm performance. This article would study the two-way impact between capital structure and firm performance. The study use EVIEWS 6.0 software to determine a two-way relationship between the capital structure and firm performance based on two-stage regression (2SLS - Two-Stage Least Squares). The findings are: capital structure has the opposite effect on the business efficiency and vice versa, factors that effect on business efficiency include Size and Opportunities. Factors effects on the capital structure are size; liquidity. These factors also affect the ratio of capital structure (total debt/ total asset) of companies. In particular, liquidity has the opposite effect; and the size of the business has the same impact. The results of the study are in line with the theory and empirical studies presented, and the results of the study are unchanged for all three years 2015-2017.

Keywords: capital structure, firm performance, factors, two-way relationship

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Authors: R. Korchiyne, A. Sbihi, S. M. Farssi, R. Touahni, M. Tahiri Alaoui

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Trabecular bone structure is important texture in the study of osteoporosis. Legendre multifractal spectrum can reflect the complex and self-similarity characteristic of structures. The main objective of this paper is to develop a new technique of medical image classification based on Legendre multifractal spectrum. Novel features have been developed from basic geometrical properties of this spectrum in a supervised image classification. The proposed method has been successfully used to classify medical images of bone trabeculations, and could be a useful supplement to the clinical observations for osteoporosis diagnosis. A comparative study with existing data reveals that the results of this approach are concordant.

Keywords: multifractal analysis, medical image, osteoporosis, fractal dimension, Legendre spectrum, supervised classification

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Authors: Pradeepa Teegala, Ramreddy Chetteti

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This work emphasizes the effects of heat generation/absorption and Joule heating on chemically reacting micropolar fluid flow over a truncated cone with convective boundary condition. For this complex fluid flow problem, the similarity solution does not exist and hence using non-similarity transformations, the governing fluid flow equations along with related boundary conditions are transformed into a set of non-dimensional partial differential equations. Several authors have applied the spectral quasi-linearization method to solve the ordinary differential equations, but here the resulting nonlinear partial differential equations are solved for non-similarity solution by using a recently developed method called the spectral quasi-linearization method (SQLM). Comparison with previously published work on special cases of the problem is performed and found to be in excellent agreement. The influence of pertinent parameters namely Biot number, Joule heating, heat generation/absorption, chemical reaction, micropolar and magnetic field on physical quantities of the flow are displayed through graphs and the salient features are explored in detail. Further, the results are analyzed by comparing with two special cases, namely, vertical plate and full cone wherever possible.

Keywords: chemical reaction, convective boundary condition, joule heating, micropolar fluid, spectral quasilinearization method

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Authors: Shakila N. Senarath, Dinesh Asanka, Janaka Wijayanayake

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The necessity of cosmetic products is arising to fulfill consumer needs of personality appearance and hygiene. A cosmetic product consists of various chemical ingredients which may help to keep the skin healthy or may lead to damages. Every chemical ingredient in a cosmetic product does not perform on every human. The most appropriate way to select a healthy cosmetic product is to identify the texture of the body first and select the most suitable product with safe ingredients. Therefore, the selection process of cosmetic products is complicated. Consumer surveys have shown most of the time, the selection process of cosmetic products is done in an improper way by consumers. From this study, a content-based system is suggested that recommends cosmetic products for the human factors. To such an extent, the skin type, gender and price range will be considered as human factors. The proposed system will be implemented by using Machine Learning. Consumer skin type, gender and price range will be taken as inputs to the system. The skin type of consumer will be derived by using the Baumann Skin Type Questionnaire, which is a value-based approach that includes several numbers of questions to derive the user’s skin type to one of the 16 skin types according to the Bauman Skin Type indicator (BSTI). Two datasets are collected for further research proceedings. The user data set was collected using a questionnaire given to the public. Those are the user dataset and the cosmetic dataset. Product details are included in the cosmetic dataset, which belongs to 5 different kinds of product categories (Moisturizer, Cleanser, Sun protector, Face Mask, Eye Cream). An alternate approach of TF-IDF (Term Frequency – Inverse Document Frequency) is applied to vectorize cosmetic ingredients in the generic cosmetic products dataset and user-preferred dataset. Using the IF-IPF vectors, each user-preferred products dataset and generic cosmetic products dataset can be represented as sparse vectors. The similarity between each user-preferred product and generic cosmetic product will be calculated using the cosine similarity method. For the recommendation process, a similarity matrix can be used. Higher the similarity, higher the match for consumer. Sorting a user column from similarity matrix in a descending order, the recommended products can be retrieved in ascending order. Even though results return a list of similar products, and since the user information has been gathered, such as gender and the price ranges for product purchasing, further optimization can be done by considering and giving weights for those parameters once after a set of recommended products for a user has been retrieved.

Keywords: content-based filtering, cosmetics, machine learning, recommendation system

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Authors: Junling Li, Fang Meng, Yichun Zhang

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Image saliency detection has been long studied, while several challenging problems are still unsolved, such as detecting saliency inaccurately in complex scenes or suppressing salient objects in the image borders. In this paper, we propose a new saliency detection algorithm in order to solving these problems. We represent the image as a graph with superixels as nodes. By considering appearance similarity between the boundary and the background, the proposed method chooses non-saliency boundary nodes as background priors to construct the background probability model. The probability that each node belongs to the model is computed, which measures its similarity with backgrounds. Thus we can calculate saliency by the transformed probability as a metric. We compare our algorithm with ten-state-of-the-art salient detection methods on the public database. Experimental results show that our simple and effective approach can attack those challenging problems that had been baffling in image saliency detection.

Keywords: visual saliency, background probability, boundary knowledge, background priors

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Authors: Tamás Gyulavári, Erzsébet Malota

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The main purpose of our study was to investigate the effect of congruence between the perceived self and perceived culture personality on the evaluation of the examined countries as ideal business/tourist destinations. A measure of Culture Personality (CP) has been developed and implemented to assess the perception of French and Turkish culture. Results show that very similar personality structure of both cultures can be extracted along the dimensions of Competence, Interpersonal approach, Aura, Life approach and Rectitude. Regarding the congruence theory, we found that instead of the effect of similarity between the perceived culture personality and actual self, the more positively culture personality is perceived relative to the perceived self, the more positive attitude the individual has toward the country as business and tourist destination.

Keywords: culture personality, ideal business/tourist destination, personality, scale development

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Authors: Deniz Karagöz

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This study is attempt to comprehend the relationship between the spatial characteristics of cultural structure, activities and the tourism demand in Turkey. The analysis divided into four parts. The first part consisted of a cultural structure and cultural activity (CSCA) index provided by principal component analysis. The analysis determined four distinct dimensions, namely, cultural activity/structure, accessing culture, consumption, and cultural management. The exploratory spatial data analysis employed to determine the spatial models of cultural structure and cultural activities in 81 provinces in Turkey. Global Moran I indices is used to ascertain the cultural activities and the structural clusters. Finally, the relationship between the cultural activities/cultural structure and tourism demand was analyzed. The raw/original data of the study official databases. The data on the cultural structure and activities gathered from the Turkish Statistical Institute and the data related to the tourism demand was provided by the Republic of Turkey Ministry of Culture and Tourism.

Keywords: cultural activities, cultural structure, spatial characteristics, tourism demand, Turkey

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Authors: Oh Hyeon Jeon, WooYoung Jung

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In this study, seepage analysis was performed by the level difference between upstream and downstream of weir structure for safety evaluation of weir structure against flooding. Monte Carlo Simulation method was employed by considering the probability distribution of the adjacent ground parameter, i.e., permeability coefficient of weir structure. Moreover, by using a commercially available finite element program (ABAQUS), modeling of the weir structure is carried out. Based on this model, the characteristic of water seepage during flooding was determined at each water level with consideration of the uncertainty of their corresponding permeability coefficient. Subsequently, fragility function could be constructed based on this response from numerical analysis; this fragility function results could be used to determine the weakness of weir structure subjected to flooding disaster. They can also be used as a reference data that can comprehensively predict the probability of failur,e and the degree of damage of a weir structure.

Keywords: weir structure, seepage, flood disaster fragility, probabilistic risk assessment, Monte-Carlo simulation, permeability coefficient

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Authors: Aleksei Samarin, Artyom Nazarenko, Valentin Malykh

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Image enhancement is becoming more and more popular, especially on mobile devices. Nowadays, it is a common approach to enhance an image using a convolutional neural network (CNN). Such a network should be of significant size; otherwise, a possibility for the artifacts to occur is overgrowing. The existing large CNNs are computationally expensive, which could be crucial for mobile devices. Another important flaw of such models is they are poorly interpretable. There is another approach to image enhancement, namely, the usage of predefined filters in combination with the prediction of their applicability. We present an approach following this paradigm, which outperforms both existing CNN-based and filter-based approaches in the image enhancement task. It is easily adaptable for mobile devices since it has only 47 thousand parameters. It shows the best SSIM 0.919 on RANDOM250 (MIT Adobe FiveK) among small models and is thrice faster than previous models.

Keywords: universal filter, image enhancement, neural networks, computer vision

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Authors: S. M. Hamidi, M. Zamani

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Magneto-plasmonic (MP) structures have turned into essential tools for the amplification of magneto-optical (MO) responses via the combination of MO activity and surface Plasmon resonance (SPR). Both the plasmonic and the MO properties of the resulting MP structure become interrelated because the SPR of the metallic medium. This interconnection can be modified the wave vector of surface plasmon polariton (SPP) in MP multilayer [1] or enhanced the MO activity [2- 3] and also modified the sensor responses [4]. There are several types of MP structures which are studied to enhance MO response in miniaturized configuration. In this paper, we propose a new MP structure based on the nano-metal grating and we investigate the MO and optical properties of this new structure. Our new MP structure fabricate by DC magnetron sputtering method and our home made MO experimental setup use for characterization of the structure.

Keywords: Magneto-plasmonic structures, magneto-optical effect, nano-garting

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Authors: Natalya G. Filimonova, Mariya G. Ozerova, Irina N. Ermakova

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The long-term strategy of the economic development of Russia up to 2030 is based on the concept of sustainable growth. The determining factor of such development is complex changes in the economic system which may be achieved by making progressive changes in its structure. The structural changes determine the character and the direction of economic development, as well as they include all elements of this system without exception, and their regulated character ensures the most rapid aim achievement. This article has discussed the industrial structure of the agriculture in Russia. With the use of the system of indexes, the article has determined the directions, intensity, and speed of structural shifts. The influence of structural changes on agricultural production development has been found out. It is noticed that the changes in the industrial structure are synchronized with the changes in the organisation and economic structure. Efficiency assessment of structural changes allowed to trace the efficiency of structural changes and elaborate the main directions for agricultural policy improvement.

Keywords: Russian agricultural sectors, sectoral structure, organizational and economic structure, structural changes

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Authors: Rajeev, N. K. Raigar

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In this study, one dimensional phase change problem (a Stefan problem) is considered and a numerical solution of this problem is discussed. First, we use similarity transformation to convert the governing equations into ordinary differential equations with its boundary conditions. The solutions of ordinary differential equation with the associated boundary conditions and interface condition (Stefan condition) are obtained by using a numerical approach based on operational matrix of differentiation of shifted second kind Chebyshev wavelets. The obtained results are compared with existing exact solution which is sufficiently accurate.

Keywords: operational matrix of differentiation, similarity transformation, shifted second kind chebyshev wavelets, stefan problem

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Authors: Norazlan Alias, Mohd. Hasimi Yaacob

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This study examines the impact of governance structure via corporate restructuring decision on selected firm characteristics and performance. Results of selected ratios that represent corporate decision, governance structure and performance in pre and post restructuring are analyzed for some conclusions. This study uses annual data of companies that are consistently listed on the Main Board of Bursa Malaysia and announced completed corporate restructuring. The results show that only debt ratio is significantly different before and after asset restructuring. This study concludes that firms do not view corporate restructuring namely asset restructuring as an opportunity to simultaneous enhance governance structure that could also contribute enhance firm performance and board of directors’ structure subsequent to asset restructuring only has significantly influence on changing capital structure but not on firm performance.

Keywords: board of directors, capital structure, corporate restructuring, performance

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Authors: Murali Aarthy, Sanjeev Kumar Singh

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High risk human papillomaviruses are highly associated with the carcinoma of the cervix and the other genital tumors. Cervical cancer develops through the multistep process in which increasingly severe premalignant dysplastic lesions called cervical intraepithelial neoplastic progress to invasive cancer. The oncoprotein E7 of human papillomavirus expressed in the lower epithelial layers drives the cells into S-phase creating an environment conducive for viral genome replication and cell proliferation. The replication of the virus occurs in the terminally differentiating epithelium and requires the activation of cellular DNA replication proteins. To date, no suitable drug molecule is available to treat HPV infection whereas identification of potential drug targets and development of novel anti-HPV chemotherapies with unique mode of actions are expected. Hence, our present study aimed to identify the potential inhibitors analogous to EGCG, a green tea molecule which is considered to be safe to use for mammalian systems. A 3D similarity search on the natural small molecule library from natural product database using EGCG identified 11 potential hits based on their similarity score. The structure based docking strategies were implemented in the potential hits and the key interacting residues of protein with compounds were identified through simulation studies and binding free energy calculations. The conformational changes between the apoprotein and the complex were analyzed with the simulation and the results demonstrated that the dynamical and structural effects observed in the protein were induced by the compounds and indicated the dominance to the oncoprotein. Overall, our study provides the basis for the structural insights of the identified potential hits and EGCG and hence, the analogous compounds identified can be potent inhibitors against the HPV 16 E7 oncoprotein.

Keywords: EGCG, oncoprotein, molecular dynamics simulation, analogues

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Authors: Suleiman Ahmed Badayi

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Corporate governance literature is very wide and involves several empirical studies conducted on the relationship between board structure, composition and firm performance. The separation of ownership and control in organizations were aimed at reducing the losses suffered by the investors in the event of financial scandals. This paper reviewed the theoretical and empirical literature on the relationship between board composition and its impact on firm performance. The findings from the studies provide different results while some are of the view that board structure is related to firm performance, many empirical studies indicates no relationship. However, others found a U-shape relationship between firm performance and board structure. Therefore, this study argued that board structure is not much significant to determine the financial performance of a firm.

Keywords: board structure, composition, firm performance, corporate governance

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Authors: Rihab Ben Lamine, Raoudha Ben Jemaa, Ikram Amous Ben Amor

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This paper proposes a graph planning technique for semantic adaptable Web Services composition. First, we use an ontology based context model for extending Web Services descriptions with information about the most suitable context for its use. Then, we transform the composition problem into a semantic context aware graph planning problem to build the optimal service composition based on user's context. The construction of the planning graph is based on semantic context aware Web Service discovery that allows for each step to add most suitable Web Services in terms of semantic compatibility between the services parameters and their context similarity with the user's context. In the backward search step, semantic and contextual similarity scores are used to find best composed Web Services list. Finally, in the ranking step, a score is calculated for each best solution and a set of ranked solutions is returned to the user.

Keywords: semantic web service, web service composition, adaptation, context, graph planning

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Authors: M. Kouyate, M. Sangare, S. Samake, S. Keita, H. G. Kim, D. H. Geschwind

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Background & Objectives: Human genetic studies can be expensive, even unaffordable, in developing countries, partly due to the sequencing costs. Our aim is to pilot the use of bioinformatics tools to guide scientifically valid, locally relevant, and economically sound autism genetic research in Mali. Methods: The following databases, NCBI, HGMD, and LSDB, were used to identify hot point mutations. Phenotype, transmission pattern, theoretical protein expression in the brain, the impact of the mutation on the 3D structure of the protein) were used to prioritize selected autism genes. We used the protein database, Modeller, and clustal W. Results: We found Mef2c (Gly27Ala/Leu38Gln), Pten (Thr131IIle), Prodh (Leu289Met), Nme1 (Ser120Gly), and Dhcr7 (Pro227Thr/Glu224Lys). These mutations were associated with endonucleases BseRI, NspI, PfrJS2IV, BspGI, BsaBI, and SpoDI, respectively. Gly27Ala/Leu38Gln mutations impacted the 3D structure of the Mef2c protein. Mef2c protein sequences across species showed a high percentage of similarity with a highly conserved MADS domain. Discussion: Mef2c, Pten, Prodh, Nme1, and Dhcr 7 gene mutation frequencies in the Malian population will be very informative. PCR coupled with restriction enzyme digestion can be used to screen the targeted gene mutations. Sanger sequencing will be used for confirmation only. This will cut down considerably the sequencing cost for gene-to-gene mutation screening. The knowledge of the 3D structure and potential impact of the mutations on Mef2c protein informed the protein family and altered function (ex. Leu38Gln). Conclusion & Future Work: Bio-informatics will positively impact autism research in Mali. Our approach can be applied to another neuropsychiatric disorder.

Keywords: bioinformatics, endonucleases, autism, Sanger sequencing, point mutations

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Authors: Jing Ning, Kunyuan Gao

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The microstructure and phase structure of Al-Er alloys with Er content of 10, 20, 30wt% at cooling rate of 60, 40 and 5℃/h were analyzed using scanning electron microscope (SEM) and X-ray diffraction (XRD). Experimental results showed that for solidification of the hypereutectic Al-Er alloys at different conditions, a halo of α-Al appeared around the primary Al₃Er phase. Analysis of the solidification process indicated that after the primary Al₃Er phase formed, the composition of supercooled liquid phase located outside the coupled zone of eutectic growth below the eutectic line, which leaded to the formation of Al halo. With the increase of Er content, the blocky primary Al₃Er phase expanded from 200μm to 1mm in size. With the decrease of cooling rate, the morphology and phase structure of alloy were different. At the cooling rate of 60℃/h, it was obtained the primary Al3Er phase with L1₂ structure, whose profile was straight. Meanwhile, the eutectic structure was flocculent. At the quite slow cooling rate of 5℃/h, it was obtained the primary Al₃Er phase with hR20 structure with irregular jagged profile, and the eutectic structure was approximately strip-shaped. These characteristics were closely related to the cooling rate of solidification. The XRD analysis showed that for Al₃Er phase, the lattice constant a of L1₂ structure was 4.2158Å, and a, c of hR20 structure were 6.0321Å and 35.6290Å, respectively.

Keywords: Al-Er alloy, composition, cooling rate, microstructure

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Authors: Khadijah B. Alziyadi, Khawlh A. Alzubaidi, Amor M. Alsayari

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Recently, GaMnAs diluted magnetic semiconductors(DMSs) have received considerable attention because they combine semiconductor and magnetic properties. GaMnAs has been used as a model DMS and as a test bed for many concepts and functionalities of spintronic devices. In this paper, a theoretical study on the band structure ofGaMnAswill be presented. The model that we used in this study is the 8-band k.p methodwherespin-orbit interaction, spin splitting, and strain are considered. The band structure of GaMnAs will be calculated in different directions in the reciprocal space. The effect of manganese content on the GaMnAs band structure will be discussed. Also, the influence of strain, which varied continuously from tensile to compressive, on the different bands will be studied.

Keywords: band structure, diluted magnetic semiconductor, k.p method, strain

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Authors: Sarah Gaßmeyer, Nadine Hülsemann, Raphael Stoll, Kenji Miyamoto, Robert Kourist

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Enzymatic racemization allows the smooth interconversion of stereocenters under very mild reaction conditions. Racemases find frequent applications in deracemization and dynamic kinetic resolutions. Arylmalonate decarboxylase (AMDase) from Bordetella Bronchiseptica has high structural similarity to amino acid racemases. These cofactor-free racemases are able to break chemically strong CH-bonds under mild conditions. The racemase-like catalytic machinery of mutant G74C conveys it a unique activity in the racemisation of pharmacologically relevant derivates of 2-phenylpropionic acid (profenes), which makes AMDase G74C an interesting object for the mechanistic investigation of cofactor-independent racemases. Structure-guided protein engineering achieved a variant of this unique racemase with 40-fold increased activity in the racemisation of several arylaliphatic carboxylic acids. By saturation–transfer–difference NMR spectroscopy (STD-NMR), substrate binding during catalysis was investigated. All atoms of the substrate showed interactions with the enzyme. STD-NMR measurements revealed distinct nuclear Overhauser effects in experiments with and without molecular conversion. The spectroscopic analysis led to the identification of several amino acid residues whose variation increased the activity of G74C. While single-amino acid exchanges increased the activity moderately, structure-guided saturation mutagenesis yielded a quadruple mutant with a 40 times higher reaction rate. This study presents STD-NMR as versatile tool for the analysis of enzyme-substrate interactions in catalytically competent systems and for the guidance of protein engineering.

Keywords: racemase, rational protein design, STD-NMR, structure guided saturation mutagenesis

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Authors: Varsha Hemant Patil, Swati A. Bhavsar, Abolee H. Patil

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Image quality assessment plays an important role in image evaluation. This paper aims to present an investigation of classic techniques in use for image quality assessment, especially for super-resolution imaging. Researchers have contributed a lot towards the development of super-resolution imaging techniques. However, not much attention is paid to the development of metrics for testing the performance of developed techniques. In this paper, the study report of existing image quality measures is given. The paper classifies reviewed approaches according to functionality and suitability for super-resolution imaging. Probable modifications and improvements of these to suit super-resolution imaging are presented. The prime goal of the paper is to provide a comprehensive reference source for researchers working towards super-resolution imaging and suggest a better framework for measuring the performance of super-resolution imaging techniques.

Keywords: interpolation, MSE, PSNR, SSIM, super resolution

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Authors: Samira Laidaoui, Mohammed Djermane, Nazihe Terfaya

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The fluid-structure coupling is a natural phenomenon which reflects the effects of two continuums: fluid and structure of different types in the reciprocal action on each other, involving knowledge of elasticity and fluid mechanics. The solution for such problems is based on the relations of continuum mechanics and is mostly solved with numerical methods. It is a computational challenge to solve such problems because of the complex geometries, intricate physics of fluids, and complicated fluid-structure interactions. The way in which the interaction between fluid and solid is described gives the largest opportunity for reducing the computational effort. In this paper, a problem of fluid structure interaction is investigated with two-way coupling method. The formulation Arbitrary Lagrangian-Eulerian (ALE) was used, by considering a dynamic grid, where the solid is described by a Lagrangian formulation and the fluid by a Eulerian formulation. The simulation was made on the ANSYS software.

Keywords: ALE, coupling, FEM, fluid-structure, interaction, one-way method, two-way method

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Authors: P. Tej, P. Kněž, M. Blank

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The paper presents design and production of thin-walled U-profile footbridge made of UHPFRC. The main structure of the bridge is one prefabricated shell structure made of UHPFRC with dispersed steel fibers without any conventional reinforcement. The span of the bridge structure is 10 m and the clear width of 1.5 m. The thickness of the UHPFRC shell structure oscillated in an interval of 30-45 mm. Several calculations were made during the bridge design and compared with the experiments. For the purpose of verifying the calculations, a segment of 1.5 m was first produced, followed by the whole footbridge for testing. After the load tests were done, the design was optimized to cast the final footbridge.

Keywords: footbridge, non-linear analysis, shell structure, UHPFRC, Ultra-High Performance Fibre Reinforced Concrete

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Authors: Serges Mendomo Meye, Li Guowei, Shen Zhenzhong, Gan Lei, Xu Liqun

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Given the limitations of the original whale optimization algorithm (WAO) in local optimum and low convergence accuracy in truss structure optimization problems, based on the fundamental whale algorithm, an improved whale optimization algorithm (SWAO) based on information entropy is proposed. The information entropy itself is an uncertain measure. It is used to control the range of whale searches in path selection. It can overcome the shortcomings of the basic whale optimization algorithm (WAO) and can improve the global convergence speed of the algorithm. Taking truss structure as the optimization research object, the mathematical model of truss structure optimization is established; the cross-sectional area of truss is taken as the design variable; the objective function is the weight of truss structure; and an improved whale optimization algorithm (SWAO) is used for optimization design, which provides a new idea and means for its application in large and complex engineering structure optimization design.

Keywords: information entropy, structural optimization, truss structure, whale algorithm

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Authors: Jie Huo, Jonathan Wu

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Segmentation of anatomical structures in medical images is essential for scientific inquiry into the complex relationships between biological structure and clinical diagnosis, treatment and assessment. As a method of incorporating the prior knowledge and the anatomical structure similarity between a target image and atlases, multi-atlas segmentation has been successfully applied in segmenting a variety of medical images, including the brain, cardiac, and abdominal images. The basic idea of multi-atlas segmentation is to transfer the labels in atlases to the coordinate of the target image by matching the target patch to the atlas patch in the neighborhood. However, this technique is limited by the pairwise registration between target image and atlases. In this paper, a novel multi-atlas segmentation approach is proposed by introducing a dynamic energy model. First, the target is mapped to each atlas image by minimizing the dynamic energy function, then the segmentation of target image is generated by weighted fusion based on the energy. The method is tested on MICCAI 2012 Multi-Atlas Labeling Challenge dataset which includes 20 target images and 15 atlases images. The paper also analyzes the influence of different parameters of the dynamic energy model on the segmentation accuracy and measures the dice coefficient by using different feature terms with the energy model. The highest mean dice coefficient obtained with the proposed method is 0.861, which is competitive compared with the recently published method.

Keywords: brain MRI segmentation, dynamic energy model, multi-atlas segmentation, energy minimization

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Authors: M. F. Miah, A. Chakrabarty

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Two popular and highly valued fish, Stinging catfish (Heteropneustes fossilis) and Asian catfish (Clarias batrachus) are considered for observing genetic enhancement. Cross breeding was performed considering wild and farmed fish through inducing agent. Five RAPD markers were used to assess genetic diversity among parents and offspring of these two catfish for evaluating genetic enhancement in F1 generation. Considering different genetic data such as banding pattern of DNA, polymorphic loci, polymorphic information content (PIC), inter individual pair wise similarity, Nei genetic similarity, genetic distance, phylogenetic relationships, allele frequency, genotype frequency, intra locus gene diversity and average gene diversity of parents and offspring of these two fish were analyzed and finally in both cases higher genetic diversity was found in F1 generation than the parents.

Keywords: Heteropneustes fossilis, Clarias batrachus, cross breeding, genetic enhancement

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Authors: Debarag Banerjee, Pooja Singh, Arjun Avadhanam, Saksham Srivastava

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Autonomous conversational agents, i.e., chatbots, are becoming an increasingly common mechanism for enterprises to provide support to customers and partners. In order to rate chatbots, especially ones powered by Generative AI tools like Large Language Models (LLMs), we need to be able to accurately assess their performance. This is where chatbot benchmarking becomes important. In this paper, authors propose the use of a benchmark that they call the E2E (End to End) benchmark and show how the E2E benchmark can be used to evaluate the accuracy and usefulness of the answers provided by chatbots, especially ones powered by LLMs. The authors evaluate an example chatbot at different levels of sophistication based on both our E2E benchmark as well as other available metrics commonly used in the state of the art and observe that the proposed benchmark shows better results compared to others. In addition, while some metrics proved to be unpredictable, the metric associated with the E2E benchmark, which uses cosine similarity, performed well in evaluating chatbots. The performance of our best models shows that there are several benefits of using the cosine similarity score as a metric in the E2E benchmark.

Keywords: chatbot benchmarking, end-to-end (E2E) benchmarking, large language model, user centric evaluation.

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Authors: Mona G. Alharbi

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A new family of methionine-sulfoxide reductase (Msr) was recently discovered and was named free methionine sulfoxide reductase (fRMsr). This family includes enzymes with a reductase activity toward the free R isomer of a methionine sulfoxide substrate. The fRMsrs have a GAF domain topology, a domain, which was previously identified as having in some cases a cyclic nucleotide phosphodiesterase activity. The classification of fRMsrs as GAF domains revealed a new function can be added to the GAF domain family. Interestingly the four members identified in the fRMsr family share the GAF domain structure and the presence of three conserved cysteines in the active site with free R methionine sulfoxide substrate specificity. This thesis presents the crystal structures of reduced, free Met-SO substrate-bound and MES-bound forms of a new fRMsr from Burkholderia pseudomallei (BPSL2418). BPSL2418 was cloned, overexpressed and purified to enable protein crystallization. The crystallization trials for reduced, Met-SO-bound and MES-bound forms of BPSL2418 were prepared and reasonable crystals of each form were produced. The crystal structures of BPSL2418MES, BPSL2418Met-SO and BPSL2418Reduced were solved at 1.18, 1.4 and 2.0Å, respectively by molecular replacement. The BPSL2418MES crystal belongs to space group P 21 21 21 while BPSL2418Met-SO and BPSL2418Reduced crystals belong to space group P 1 21 1. All three forms share the GAF domain structure of six antiparallel β-strands and four α-helices with connecting loops. The antiparallel β-strands (β1, β2, β5 and β6) are located in the center of the BPSL2418 structure flanked on one side by a three α-helices (α1, α2 and α4) and on the other side by a (loop1, β3, loop2, α3, β4 loop4) unit where loop4 forms a capping flap and covers the active site. The structural comparison of the three forms of BPSL2418 indicates that the catalytically important cysteine is CYS109, where the resolving cysteine is CYS75, which forms a disulfide bond with CYS109. They also suggest that the third conserved cysteine in the active site, CYS85, which is located in α3, is a non-essential cysteine for the catalytic function but it may play a role in the binding of the substrate. The structural comparison of the three forms reveals that conformational changes appear in the active site particularly involving loop4 and CYS109 during catalysis. The 3D structure of BPSL2418 shows strong structure similarity to fRMsrs enzymes, which further suggests that BPSL2418 acts as a free Met-R-SO reductase and shares the catalytic mechanism of fRMsr family.

Keywords: Burkholderia pseudomallei, GAF domain protein, methionine sulfoxide reductase, protein crystallization

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Authors: Safari Mat Desa, Othman A. Karim, Mohd Kamarulhuda Samion, Saiful Bahri Hamzah

Abstract:

Rubble mound breakwater was one of the most popular designs in Malaysia, constructed at the river mouth to dissipate the incoming wave energy from the seaward. Geometrically characteristics in trapezoid, crest width, and bottom width will determine the hypotonus stability, whilst structural height was designed for wave overtopping consideration. Physical hydraulic modelling in two-dimensional facilities was instigated in the flume to test the stability as well as the overtopping rate complied with the method of similarity, namely kinematic, dynamic, and geometric. Scaling effects of wave characteristics were carried out in order to acquire significant interaction of wave height, wave period, and water depth. Results showed two-dimensional physical modelling has proven reliable capability to ascertain breakwater stability significantly.

Keywords: breakwater, geometrical characteristic, wave overtopping, physical hydraulic modelling, method of similarity, wave characteristic

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

Abstract:

This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

Procedia PDF Downloads 140