Search results for: approximate graph matching

Authors: Zhipeng Chen, Peng Zhang, Qingyun Liu, Li Guo

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With the Internet becoming the dominant channel for business and life, many IPs are increasingly masked using web proxies for illegal purposes such as propagating malware, impersonate phishing pages to steal sensitive data or redirect victims to other malicious targets. Moreover, as Internet traffic continues to grow in size and complexity, it has become an increasingly challenging task to detect the proxy service due to their dynamic update and high anonymity. In this paper, we present an approach based on behavioral graph analysis to study the behavior similarity of web proxy users. Specifically, we use bipartite graphs to model host communications from network traffic and build one-mode projections of bipartite graphs for discovering social-behavior similarity of web proxy users. Based on the similarity matrices of end-users from the derived one-mode projection graphs, we apply a simple yet effective spectral clustering algorithm to discover the inherent web proxy users behavior clusters. The web proxy URL may vary from time to time. Still, the inherent interest would not. So, based on the intuition, by dint of our private tools implemented by WebDriver, we examine whether the top URLs visited by the web proxy users are web proxies. Our experiment results based on real datasets show that the behavior clusters not only reduce the number of URLs analysis but also provide an effective way to detect the web proxies, especially for the unknown web proxies.

Keywords: bipartite graph, one-mode projection, clustering, web proxy detection

Procedia PDF Downloads 245

Authors: Mubarack Ahmed, Gabriele Gradoni, Stephen C. Creagh, Gregor Tanner

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High-frequency cables commonly connect modern devices and sensors. Interestingly, the proportion of electric components is rising fast in an attempt to achieve lighter and greener devices. Modelling the propagation of signals through these cable networks in the presence of parameter uncertainty is a daunting task. In this work, we study the response of high-frequency cable networks using both Transmission Line and Quantum Graph (QG) theories. We have successfully compared the two theories in terms of reflection spectra using measurements on real, lossy cables. We have derived a generalisation of the vertex scattering matrix to include non-uniform networks – networks of cables with different characteristic impedances and propagation constants. The QG model implicitly takes into account the pseudo-chaotic behavior, at the vertices, of the propagating electric signal. We have successfully compared the asymptotic growth of eigenvalues of the Laplacian with the predictions of Weyl law. We investigate the nearest-neighbour level-spacing distribution of the resonances and compare our results with the predictions of Random Matrix Theory (RMT). To achieve this, we will compare our graphs with the generalisation of Wigner distribution for open systems. The problem of scattering from networks of cables can also provide an analogue model for wireless communication in highly reverberant environments. In this context, we provide a preliminary analysis of the statistics of communication capacity for communication across cable networks, whose eventual aim is to enable detailed laboratory testing of information transfer rates using software defined radio. We specialise this analysis in particular for the case of MIMO (Multiple-Input Multiple-Output) protocols. We have successfully validated our QG model with both TL model and laboratory measurements. The growth of Eigenvalues compares well with Weyl’s law and the level-spacing distribution agrees so well RMT predictions. The results we achieved in the MIMO application compares favourably with the prediction of a parallel on-going research (sponsored by NEMF21.)

Keywords: eigenvalues, multiple-input multiple-output, quantum graph, random matrix theory, transmission line

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Authors: Bohuslava Juhasova, Martin Juhas, Renata Masarova, Zuzana Sutova

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The article deals with the tool in Matlab GUI form that is designed to analyse a mechatronic system sensitivity and tolerance. In the analysed mechatronic system, a torque is transferred from the drive to the load through a coupling containing flexible elements. Different methods of control system design are used. The classic form of the feedback control is proposed using Naslin method, modulus optimum criterion and inverse dynamics method. The cascade form of the control is proposed based on combination of modulus optimum criterion and symmetric optimum criterion. The sensitivity is analysed on the basis of absolute and relative sensitivity of system function to the change of chosen parameter value of the mechatronic system, as well as the control subsystem. The tolerance is analysed in the form of determining the range of allowed relative changes of selected system parameters in the field of system stability. The tool allows to analyse an influence of torsion stiffness, torsion damping, inertia moments of the motor and the load and controller(s) parameters. The sensitivity and tolerance are monitored in terms of the impact of parameter change on the response in the form of system step response and system frequency-response logarithmic characteristics. The Symbolic Math Toolbox for expression of the final shape of analysed system functions was used. The sensitivity and tolerance are graphically represented as 2D graph of sensitivity or tolerance of the system function and 3D/2D static/interactive graph of step/frequency response.

Keywords: mechatronic systems, Matlab GUI, sensitivity, tolerance

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Authors: Ralph Adaimy, Wassim El-Hajj, Ghassen Ben Brahim, Hazem Hajj, Haidar Safa

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Huge amounts of data and personal information are being sent to and retrieved from web applications on daily basis. Every application has its own confidentiality and integrity policies. Violating these policies can have broad negative impact on the involved company’s financial status, while enforcing them is very hard even for the developers with good security background. In this paper, we propose a framework that enforces security-by-construction in web applications. Minimal developer effort is required, in a sense that the developer only needs to annotate database attributes by a security class. The web application code is then converted into an intermediary representation, called Extended Program Dependence Graph (EPDG). Using the EPDG, the provided annotations are propagated to the application code and run against generic security enforcement rules that were carefully designed to detect insecure information flows as early as they occur. As a result, any violation in the data’s confidentiality or integrity policies is reported. As a proof of concept, two PHP web applications, Hotel Reservation and Auction, were used for testing and validation. The proposed system was able to catch all the existing insecure information flows at their source. Moreover and to highlight the simplicity of the suggested approaches vs. existing approaches, two professional web developers assessed the annotation tasks needed in the presented case studies and provided a very positive feedback on the simplicity of the annotation task.

Keywords: web applications security, secure information flow, program dependence graph, database annotation

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Authors: Adamu S. Salawu, Ibrahim O. Isah

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Direct solution to several forms of fourth-order ordinary differential equations is not easily obtained without first reducing them to a system of first-order equations. Thus, numerical methods are being developed with the underlying techniques in the literature, which seeks to approximate some classes of fourth-order initial value problems with admissible error bounds. Multistep methods present a great advantage of the ease of implementation but with a setback of several functions evaluation for every stage of implementation. However, hybrid methods conventionally show a slightly higher order of truncation for any k-step linear multistep method, with the possibility of obtaining solutions at off mesh points within the interval of solution. In the light of the foregoing, we propose the continuous form of a hybrid multistep method with Chebyshev polynomial as a basis function for the numerical integration of fourth-order initial value problems of ordinary differential equations. The basis function is interpolated and collocated at some points on the interval [0, 2] to yield a system of equations, which is solved to obtain the unknowns of the approximating polynomial. The continuous form obtained, its first and second derivatives are evaluated at carefully chosen points to obtain the proposed block method needed to directly approximate fourth-order initial value problems. The method is analyzed for convergence. Implementation of the method is done by conducting numerical experiments on some test problems. The outcome of the implementation of the method suggests that the method performs well on problems with oscillatory or trigonometric terms since the approximations at several points on the solution domain did not deviate too far from the theoretical solutions. The method also shows better performance compared with an existing hybrid method when implemented on a larger interval of solution.

Keywords: Chebyshev polynomial, collocation, hybrid multistep method, initial value problems, interpolation

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Authors: A. Almubrad, R. Clouse, A. Aljlaoud

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Organizational culture (OC) is recognized to have an influence on the propensity of organizations to innovate. It is also presumed that it may impede the innovation process from thriving within the organization. Investigating the role organizational culture plays in enabling or inhibiting innovation merits exploration to investigate organizational cultural attributes necessary to reach innovation goals. This study aims to investigate a preliminary matching heuristic of OC attributes to the type of innovation that has the potential to thrive within those attributes. A mixed methods research approach was adopted to achieve the research aims. Accordingly, participants from a national telecom company in Saudi Arabia took the Organizational Culture Assessment Instrument (OCAI). A further sample selected from the respondents’ pool holding the role of managing directors was interviewed in the qualitative phase. Our study findings reveal that the market culture type has a tendency to adopt radical innovations to disrupt the market and to preserve its market position. In contrast, we find that the adhocracy culture type tends to adopt the incremental innovation type and found this tends to be more convenient for employees due to its low levels of uncertainty. Our results are an encouraging indication that matching organizational culture attributes to the type of innovation aids in innovation management. This study carries limitations while drawing its findings from a limited sample of OC attributes that identify with the adhocracy and market culture types. An extended investigation is merited to explore other types of organizational cultures and their optimal innovation types.

Keywords: incremental innovation, radical innovation, organization culture, market culture, adhocracy culture, OACI

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Authors: Jyh Sheen, Yong-Lin Wang

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This research dedicates to find a different measurement procedure of microwave dielectric properties of ceramic materials with high dielectric constants. For the composite of ceramic dispersed in the polymer matrix, the dielectric constants of the composites with different concentrations can be obtained by various mixture equations. The other development of mixture rule is to calculate the permittivity of ceramic from measurements on composite. To do this, the analysis method and theoretical accuracy on six basic mixture laws derived from three basic particle shapes of ceramic fillers have been reported for dielectric constants of ceramic less than 40 at microwave frequency. Similar researches have been done for other well-known mixture rules. They have shown that both the physical curve matching with experimental results and low potential theory error are important to promote the calculation accuracy. Recently, a modified of mixture equation for high dielectric constant ceramics at microwave frequency has also been presented for strontium titanate (SrTiO3) which was selected from five more well known mixing rules and has shown a good accuracy for high dielectric constant measurements. However, it is still not clear the accuracy of this modified equation for other high dielectric constant materials. Therefore, the five more well known mixing rules are selected again to understand their application to other high dielectric constant ceramics. The other high dielectric constant ceramic, TiO2 with dielectric constant 100, was then chosen for this research. Their theoretical error equations are derived. In addition to the theoretical research, experimental measurements are always required. Titanium dioxide is an interesting ceramic for microwave applications. In this research, its powder is adopted as the filler material and polyethylene powder is like the matrix material. The dielectric constants of those ceramic-polyethylene composites with various compositions were measured at 10 GHz. The theoretical curves of the five published mixture equations are shown together with the measured results to understand the curve matching condition of each rule. Finally, based on the experimental observation and theoretical analysis, one of the five rules was selected and modified to a new powder mixture equation. This modified rule has show very good curve matching with the measurement data and low theoretical error. We can then calculate the dielectric constant of pure filler medium (titanium dioxide) by those mixing equations from the measured dielectric constants of composites. The accuracy on the estimating dielectric constant of pure ceramic by various mixture rules will be compared. This modified mixture rule has also shown good measurement accuracy on the dielectric constant of titanium dioxide ceramic. This study can be applied to the microwave dielectric properties measurements of other high dielectric constant ceramic materials in the future.

Keywords: microwave measurement, dielectric constant, mixture rules, composites

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Authors: El Montassir Dahmane, Nadia Eladlani, Aziz Ouahrouch, Mohammed Rhazi, Moha Taourirte

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The present study was aimed to approximate the optimal conditions to chromium recovery from wastewater by nanoparticles and whiskers of chitosan. Chitosan with an average molecular weight of 63 kDa and a 96% deacetylation degree was prepared according to our previous study. Chromium recovery is influenced by different parameters. In our search, we determined the appropriate range of pH to form chitosan–Cr(III), nanoparticles Cr(III), and whiskers– Cr(III) complex. We studied also the influence of chromium concentration and the nature of chitosan-based materials on the complexation process. Our main aim is to approximate the optimal conditions to remove chromium(III) from the tanning bath, recuperated from tannery wastewater of Marrakech in Morocco. A Perkin Elmer optima 2000 Inductively Coupled Plasma- Optical Emission Spectrometer (ICP-OES), was used to determine the quantity of chromium persistent in tannery wastewater after complexation phenomenon. To the best of our knowledge, this is the first report interested in the optimal conditions for chromium recovery from wastewater by nanoparticles and whiskers of chitosan. From our research, we found that in chromium solution, the appropriate range of pH to form complex is between 5.6 and 6.7. Also, the complexation of Cr(III) is depending on the nature of complexing ligand and chromium concentration. The obtained results reveal that nanoparticles present an excellent adsorption capacity regardless of chromium concentration. In addition, after a critical chromium concentration (250 mg/l), our ligand becomes saturated, that requires an increase of ligand mass for increasing chromium concentration in order to have a better adsorption capacity. Hence, in the same conditions, we used chitosan, its nanoparticles, whiskers, and chitosan based films to remove Cr(III) from tannery wastewater. The pH of this effluent was around 6, and its chromium concentration was 300 mg/l. The results expose that the sequence of complexing ligand in the effluent is the same in chromium solution, determined via our previous study. However, the adsorbed quantity is less due to the presence of other metallic ions in tannery wastewater. We conclude that the best complexing ligand-based chitosan is chitosan nanoaprticles whether it’s in chromium solution or in tannery wastewater. Nanoparticles are the best complexing ligand after 24 h of contact nanoparticles can remove 70% of chromium from this tannery wastewater.

Keywords: nanoparticles, whiskers, chitosan, chromium

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Authors: Farhat Imtiaz, Umar Farooq

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In this work, we developed a computational model to predict ply level failure in impacted composite laminates. Data obtained from physical testing from flat and round nose impacts of 8-, 16-, 24-ply laminates were considered. Routine inspections of the tested laminates were carried out to approximate ply by ply inflicted damage incurred. Plots consisting of load–time, load–deflection, and energy–time history were drawn to approximate the inflicted damages. Impact test generated unwanted data logged due to restrictions on testing and logging systems were also filtered. Conventional filters (built-in, statistical, and numerical) reliably predicted load thresholds for relatively thin laminates such as eight and sixteen ply panels. However, for relatively thick laminates such as twenty-four ply laminates impacted by flat nose impact generated clipped data which can just be de-noised using oscillatory algorithms. The literature search reveals that modern oscillatory data filtering and extrapolation algorithms have scarcely been utilized. This investigation reports applications of filtering and extrapolation of the clipped data utilising fast Fourier Convolution algorithm to predict load thresholds. Some of the results were related to the impact-induced damage areas identified with Ultrasonic C-scans and found to be in acceptable agreement. Based on consistent findings, utilizing of modern data filtering and extrapolation algorithms to data logged by the existing machines has efficiently enhanced data interpretations without resorting to extra resources. The algorithms could be useful for impact-induced damage approximations of similar cases.

Keywords: fibre reinforced laminates, fast Fourier algorithms, mechanical testing, data filtering and extrapolation

Procedia PDF Downloads 135

Authors: Shi-xia Xu, Zai-wen Zhang, Ru-xue Chen, Shan Zhou, Xiang-feng Tang

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Objective: The clinical influence of HLA-DPB1 mismatches on clinical outcome of HSCT is less clear. This is the first meta-analysis to study the HLA-DPB1 matching statues on clinical outcomes after unrelated donor HSCT. Methods: We searched the CIBMTR, Cochrane Central Register of Controlled Trials (CENTRAL) and related databases (1995.01–2017.06) for all relevant articles. Comparative studies were used to investigate the HLA-DPB1 loci mismatches on clinical outcomes after unrelated donor HSCT, such as the disease-free survival (DFS), overall survival, GVHD, relapse, and transplant-related mortality (TRM). We performed meta-analysis using Review Manager 5.2 software and funnel plot to assess the bias. Results: At first, 1246 articles were retrieved, and 18 studies totaling 26368 patients analyzed. Pooled comparisons of studies found that the HLA-DPB1 mismatched group had a lower rate of DFS than the DPB1-matched group, and lower OS in non-T cell depleted transplantation. The DPB1 mismatched group has a higher incidence of aGVHD and more severe ( ≥ III degree) aGvHD, lower rate of relapse and higher TRM. Moreover, compared with 1-antigen mismatch, 2-antigen mismatched led to a higher risk of TRM and lower relapse rate. Conclusions: This meta-analysis indicated HLA-DPB1 has important influence on survival and transplant-related complications during unrelated donor HSCT and HLA-DPB1 donor selection strategies have been proposed based on a personalized algorithm.

Keywords: human leukocyte antigen, DPB1, transplant, meta-analysis, outcome

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Authors: Nguyen Van Toan, Suguru Sangu, Tetsuro Saito, Naoki Inomata, Takahito Ono

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This paper presents the design and fabrication of an optical window for an optical modulator toward image sensing applications. An optical window consists of micrometer-order SiO2 capillaries (porous solid) that can modulate transmission light intensity by moving the liquid in and out of porous solid. A high optical transmittance of the optical window can be achieved due to refractive index matching when the liquid is penetrated into the porous solid. Otherwise, its light transmittance is lower because of light reflection and scattering by air holes and capillary walls. Silicon capillaries fabricated by deep reactive ion etching (DRIE) process are completely oxidized to form the SiO2 capillaries. Therefore, high aspect ratio SiO2 capillaries can be achieved based on silicon capillaries formed by DRIE technique. Large compressive stress of the oxide causes bending of the capillary structure, which is reduced by optimizing the design of device structure. The large stress of the optical window can be released via thin supporting beams. A 7.2 mm x 9.6 mm optical window area toward a fully integrated with the image sensor format is successfully fabricated and its optical transmittance is evaluated with and without inserting liquids (ethanol and matching oil). The achieved modulation range is approximately 20% to 35% with and without liquid penetration in visible region (wavelength range from 450 nm to 650 nm).

Keywords: thermal oxidation process, SiO2 capillaries, optical window, light transmittance, image sensor, liquid penetration

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Authors: Siew Ming Thang, Wong Hoo Keat, Chee Hao Sue, Fung Lan Loo, Ahju Rosalind

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There are numerous studies that explored young learners’ literacy skills in Malaysia but none that uses the eye-tracking device to track their cognitive processes when reading picture storybooks. This study used this method to investigate two groups of prereaders’ cognitive processes in four conditions. (1) A congruent picture was presented, and a matching narration was read aloud by a recorder; (2) Children heard a narration telling about the same characters in the picture but involves a different scene; (3) Only a picture with matching text was present; (4) Students only heard the reading aloud of the text on the screen. The two main objectives of this project are to test which content of pictures helps the prereaders (i.e., young children who have not received any formal reading instruction) understand the narration and whether children try to create a coherent mental representation from the oral narration and the pictures. The study compares two groups of children from two different kindergartens. Group1: 15 Chinese children; Group2: 17 Malay children. The medium of instruction was English. An eye-tracker were used to identify Areas of Interest (AOI) of each picture and the five target elements and calculate number of fixations and total time spent on fixation of pictures and written texts. Two mixed factorial ANOVAs with the storytelling performance (good, average, or weak) and vocabulary level (low, medium, high) as between-subject variables, and the Areas of Interests (AOIs) and display conditions as the within-subject variables were performedon the variables.

Keywords: eye-tracking, cognitive processes, literacy skills, prereaders, visual attention

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Authors: Meng-Jou Chien, Jheng-Cheng Chen, Chang-Hsiung Tsai

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Let maxζG(m) denote the maximum number of edges in a subgraph of graph G induced by m nodes. The n-dimensional augmented cube, denoted as AQn, a variation of the hypercube, possesses some properties superior to those of the hypercube. We study the cases when G is the augmented cube AQn.

Keywords: interconnection network, augmented cube, induced subgraph, bisection width

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Authors: Mehrnoosh Mirzaei

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Children are among the most vulnerable at the occurrence of natural disasters such as earthquakes. Most of the management and measures which are considered for both before and during an earthquake are neither suitable nor efficient for this age group and cannot be applied. On the other hand, due to their age, it is hard to educate and train children to learn and understand the concept of earthquake risk mitigation as matters like earthquake prevention and safe places during an earthquake are not easily perceived. To our knowledge, children’s awareness of such concepts via their own world with the help of games is the best training method in this case. In this article, the researcher has tried to consider the child an active element before and during the earthquake. With training, provided by adults before the incidence of an earthquake, the child has the ability to learn disaster risk reduction (DRR). The focus of this research is on learning risk reduction behavior and regarding children as an individual element. The information of this article has been gathered from library resources, observations and the drawings of 10 children aged 5 whose subject was their conceptual definition of an earthquake who were asked to illustrate their conceptual definition of an earthquake; the results of 20 questionnaires filled in by preschoolers along with information gathered by interviewing them. The design of the suitable educational game, appropriate for the needs of this age group, has been made based on the theory of design with help of the user and the priority of children’s learning needs. The final result is a package of a game which is comprised of a learning table and matching cards showing sign marks for safe and unsafe places which introduce the safe behaviors and safe locations before and during the earthquake. These educational games can be used both in group contexts in kindergartens and on an individual basis at home, and they help in earthquake risk reduction.

Keywords: disaster education, earthquake sign marks, learning table, matching card, risk reduction behavior

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Authors: Kankeyanathan Kannan

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On approximation properties of group C* algebras is everywhere; it is powerful, important, backbone of countless breakthroughs. For a discrete group G, let A(G) denote its Fourier algebra, and let M₀A(G) denote the space of completely bounded Fourier multipliers on G. An approximate identity on G is a sequence (Φn) of finitely supported functions such that (Φn) uniformly converge to constant function 1 In this paper we prove that approximation property pass to free product.

Keywords: approximation property, weakly amenable, strong invariant approximation property, invariant approximation property

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Authors: Jacqueline Żammit

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Recent research indicates that the utilization of right-brain strategies holds significant implications for the acquisition of language skills. Nevertheless, the utilization of visual culture as a means to stimulate these strategies and amplify language retention among adults engaging in second language (L2) learning remains a relatively unexplored area. This investigation delves into the impact of visual culture on activating right-brain processes during the initial stages of language acquisition, particularly in the context of teaching Maltese as a second language (ML2) to adult learners. By employing a qualitative research approach, this study convenes a focus group comprising twenty-seven educators to delve into a range of visual culture techniques integrated within language instruction. The collected data is subjected to thematic analysis using NVivo software. The findings underscore a variety of impactful visual culture techniques, encompassing activities such as drawing, sketching, interactive matching games, orthographic mapping, memory palace strategies, wordless picture books, picture-centered learning methodologies, infographics, Face Memory Game, Spot the Difference, Word Search Puzzles, the Hidden Object Game, educational videos, the Shadow Matching technique, Find the Differences exercises, and color-coded methodologies. These identified techniques hold potential for application within ML2 classes for adult learners. Consequently, this study not only provides insights into optimizing language learning through specific visual culture strategies but also furnishes practical recommendations for enhancing language competencies and skills.

Keywords: visual culture, right-brain strategies, second language acquisition, maltese as a second language, visual aids, language-based activities

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Authors: Christoph Opperer

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Space syntax is a theory and method for analyzing the spatial layout of buildings and urban environments to understand how they can influence patterns of human movement, social interaction, and behavior. While direct visibility is a key factor in space syntax research, important visual information such as light, color, texture, etc., are typically not considered, even though psychological studies have shown a strong correlation to the human perceptual experience within physical space – with light and color, for example, playing a crucial role in shaping the perception of spaciousness. Furthermore, these surface properties are often the visual features that are most salient and responsible for drawing attention to certain elements within the environment. This paper explores the potential of integrating these factors into general space syntax methods and visibility-based analysis of space, particularly for architectural spatial layouts. To this end, we use a combination of geometric (isovist) and topological (visibility graph) approaches together with image-based methods, allowing a comprehensive exploration of the relationship between spatial geometry, visual aesthetics, and human experience. Custom-coded ray-tracing techniques are employed to generate spherical panorama images, encoding three-dimensional spatial data in the form of two-dimensional images. These images are then processed through computer vision algorithms to generate saliency-maps, which serve as a visual representation of areas most likely to attract human attention based on their visual properties. The maps are subsequently used to weight the vertices of isovists and the visibility graph, placing greater emphasis on areas with high saliency. Compared to traditional methods, our weighted visibility analysis introduces an additional layer of information density by assigning different weights or importance levels to various aspects within the field of view. This extends general space syntax measures to provide a more nuanced understanding of visibility patterns that better reflect the dynamics of human attention and perception. Furthermore, by drawing parallels to traditional isovist and VGA analysis, our weighted approach emphasizes a crucial distinction, which has been pointed out by Ervin and Steinitz: the difference between what is possible to see and what is likely to be seen. Therefore, this paper emphasizes the importance of including surface properties in visibility-based analysis to gain deeper insights into how people interact with their surroundings and to establish a stronger connection with human attention and perception.

Keywords: space syntax, visibility analysis, isovist, visibility graph, visual features, human perception, saliency detection, raytracing, spherical images

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Authors: Khairil I. Othman, Mahfuzah Mahayaddin, Zarina Bibi Ibrahim

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We develop and demonstrate a computationally efficient numerical technique to solve first order stiff differential equations. This technique is based on block method whereby three approximate points are calculated. The Cholistani of varied step sizes are presented in divided difference form. Stability regions of the formulae are briefly discussed in this paper. Numerical results show that this block method perform very well compared to existing methods.

Keywords: block method, divided difference, stiff, computational

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Authors: C. M. Nur Syazwani, M. K. Ahmad Imran, Rizal E. M. Nasir

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The study on BWB UV begins in UiTM since 2005 and three designs have been studied and published. The latest designs are Baseline-III and inspired by birds that have features and aerodynamics behaviour of cruising birds without flapping capability. The aircraft featuring planform and configuration are similar to the bird. Baseline-III has major flaws particularly in its low lift-to-drag ratio, stability and issues regarding limited controllability. New design known as Baseline-IV replaces straight, swept wing to delta wing and have a broader tail compares to the Baseline-III’s. The objective of the study is to investigate aerodynamics of Baseline-IV bird-inspired BWB aircraft. This will be achieved by theoretical calculation and wind tunnel experiments. The result shows that both theoretical and wind tunnel experiments of Baseline-IV graph of CL and CD versus alpha are quite similar to each other in term of pattern of graph slopes and values. Baseline-IV has higher lift coefficient values at wide range of angle of attack compares to Baseline-III. Baseline-IV also has higher maximum lift coefficient, higher maximum lift-to-drag and lower parasite drag. It has stable pitch moment versus lift slope but negative moment at zero lift for zero angle-of-attack tail setting. At high angle of attack, Baseline-IV does not have stability reversal as shown in Baseline-III. Baseline-IV is proven to have improvements over Baseline-III in terms of lift, lift-to-drag ratio and pitch moment stability at high angle-of-attack.

Keywords: blended wing-body, bird-inspired blended wing-body, aerodynamic, stability

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Wenjun Hou, Marek Perkowski

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The Traveling Salesman problem is famous in computing and graph theory. In short, it asks for the Hamiltonian cycle of the least total weight in a given graph with N nodes. All variations on this problem, such as those with K-bounded-degree nodes, are classified as NP-complete in classical computing. Although several papers propose theoretical high-level designs of quantum algorithms for the Traveling Salesman Problem, no quantum circuit implementation of these algorithms has been created up to our best knowledge. In contrast to previous papers, the goal of this paper is not to optimize some abstract complexity measures based on the number of oracle iterations, but to be able to evaluate the real circuit and time costs of the quantum computer. Using the emerging quantum programming language Q# developed by Microsoft, which runs quantum circuits in a quantum computer simulation, an implementation of the bounded-degree problem and its respective quantum circuit were created. To apply Grover’s algorithm to this problem, a quantum oracle was designed, evaluating the cost of a particular set of edges in the graph as well as its validity as a Hamiltonian cycle. Repeating the Grover algorithm with an oracle that finds successively lower cost each time allows to transform the decision problem to an optimization problem, finding the minimum cost of Hamiltonian cycles. N log₂ K qubits are put into an equiprobablistic superposition by applying the Hadamard gate on each qubit. Within these N log₂ K qubits, the method uses an encoding in which every node is mapped to a set of its encoded edges. The oracle consists of several blocks of circuits: a custom-written edge weight adder, node index calculator, uniqueness checker, and comparator, which were all created using only quantum Toffoli gates, including its special forms, which are Feynman and Pauli X. The oracle begins by using the edge encodings specified by the qubits to calculate each node that this path visits and adding up the edge weights along the way. Next, the oracle uses the calculated nodes from the previous step and check that all the nodes are unique. Finally, the oracle checks that the calculated cost is less than the previously-calculated cost. By performing the oracle an optimal number of times, a correct answer can be generated with very high probability. The oracle of the Grover Algorithm is modified using the recalculated minimum cost value, and this procedure is repeated until the cost cannot be further reduced. This algorithm and circuit design have been verified, using several datasets, to generate correct outputs.

Keywords: quantum computing, quantum circuit optimization, quantum algorithms, hybrid quantum algorithms, quantum programming, Grover’s algorithm, traveling salesman problem, bounded-degree TSP, minimal cost, Q# language

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Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

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Authors: Anthony John Walker, Glen Bright

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The challenge faced by manufactures, when producing custom products, is that each product needs exact components. This can cause work-in-process instability due to component matching constraints imposed on assembly cells. Clearing type flow control policies have been used extensively in mediating server access between multiple arrival processes. Although the stability and performance of clearing policies has been well formulated and studied in the literature, the growth in arrival to departure sequence disorder for each arriving job, across a serving resource, is still an area for further analysis. In this paper, a closed form industrial model has been formulated that characterizes arrival-to-departure sequence disorder through stable manufacturing systems under clearing type flow control policy. Specifically addressed are the effects of sequence disorder imposed on a downstream assembly cell in terms of work-in-process instability induced through component matching constraints. Results from a simulated manufacturing system show that steady state average sequence disorder in parallel upstream processing cells can be balanced in order to decrease downstream assembly system instability. Simulation results also show that the closed form model accurately describes the growth and limiting behavior of average sequence disorder between parts arriving and departing from a manufacturing system flow controlled via clearing policy.

Keywords: assembly system constraint, custom products, discrete sequence disorder, flow control

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Authors: Chun-Wei Huang, Jyh-Cherng Gu, Ming-Ta Yang

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Non-synchronous breakage or line failure in power systems with light or no loads can lead to core saturation in transformers or potential transformers. This can cause component and capacitance matching resulting in the formation of resonant circuits, which trigger ferroresonance. This study employed a wavelet transform for the detection of ferroresonance. Simulation results demonstrate the efficacy of the proposed method.

Keywords: ferroresonance, wavelet transform, intelligent electronic device, transformer

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Authors: Ziqu Ouyang, Kun Su

Abstract:

A novel efficient and clean coal combustion system, namely the purification-combustion system, was designed by the Institute of Engineering Thermal Physics, Chinese Academy of Science, in 2022. Among them, the purification system was composed of a mesothermal activating unit and a hyperthermal reductive unit, and the combustion system was composed of a mild combustion system. In the purification-combustion system, the deep in-situ removal of coal-N could be realized by matching the temperature and atmosphere in each unit, and thus the NOx emission was controlled effectively. To acquire the methods for realizing the efficient and clean coal combustion, this study investigated the effect of the activating temperature (including 822 °C, 858 °C, 933 °C, 991 °C), which was the key factor affecting the system operation, on combustion and NOx emission characteristics of pulverized coal in a 30 kW purification-combustion test bench. The research result turned out that the activating temperature affected the combustion and NOx emission characteristics significantly. As the activating temperature increased, the temperature increased first and then decreased in the mild combustion unit, and the temperature change in the lower part was much higher than that in the upper part. Moreover, the main combustion region was always located at the top of the unit under different activating temperatures, and the combustion intensity along the unit was weakened gradually. Increasing the activating temperature excessively could destroy the reductive atmosphere early in the upper part of the unit, which wasn’t conducive to the full removal of coal-N in the reductive coal char. As the activating temperature increased, the combustion efficiency increased first and then decreased, while the NOx emission decreased first and then increased, illustrating that increasing the activating temperature properly promoted the efficient and clean coal combustion, but there was a limit to its growth. In this study, the optimal activating temperature was 858 °C. Hence, this research illustrated that increasing the activating temperature properly could realize the mutual matching of improving the combustion efficiency and reducing the NOx emission, and thus guaranteed the clean and efficient coal combustion well.

Keywords: activating temperature, combustion characteristics, nox emission, purification-combustion system

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Authors: Leonard Lipovich, Pattaraporn Thepsuwan, Anton-Scott Goustin, Juan Cai, Donghong Ju, James B. Brown

Abstract:

Two-thirds of human genes do not encode any known proteins. Aside from long non-coding RNA (lncRNA) genes with recently-discovered functions, the ~40,000 non-protein-coding human genes remain poorly understood, and a role for their transcripts as de-facto unconventional messenger RNAs has not been formally excluded. Ribosome profiling (Riboseq) predicts translational potential, but without independent evidence of proteins from lncRNA open reading frames (ORFs), ribosome binding of lncRNAs does not prove translation. Previously, we mass-spectrometrically documented translation of specific lncRNAs in human K562 and GM12878 cells. We now examined lncRNA translation in human MCF7 cells, integrating strand-specific Illumina RNAseq, Riboseq, and deep mass spectrometry in biological quadruplicates performed at two core facilities (BGI, China; City of Hope, USA). We excluded known-protein matches. UCSC Genome Browser-assisted manual annotation of imperfect (tryptic-digest-peptides)-to-(lncRNA-three-frame-translations) alignments revealed three peptides hypothetically explicable by 'stop-to-nonstop' in-frame replacement of stop codons by amino acids in two ORFs of the lncRNA MMP24-AS1. To search for this phenomenon genomewide, we designed and implemented a novel pipeline, matching tryptic-digest spectra to wildcard-instead-of-stop versions of repeat-masked, six-frame, whole-genome translations. Along with singleton putative stop-to-nonstop events affecting four other lncRNAs, we identified 24 additional peptides with stop-to-nonstop in-frame substitutions from multiple positive-strand MMP24-AS1 ORFs. Only UAG and UGA, never UAA, stop codons were impacted. All MMP24-AS1-matching spectra met the same significance thresholds as high-confidence known-protein signatures. Targeted resequencing of MMP24-AS1 genomic DNA and cDNA from the same samples did not reveal any mutations, polymorphisms, or sequencing-detectable RNA editing. This unprecedented apparent gene-specific violation of the genetic code highlights the importance of matching peptides to whole-genome, not known-genes-only, ORFs in mass-spectrometry workflows, and suggests a new mechanism enhancing the combinatorial complexity of the proteome. Funding: NIH Director’s New Innovator Award 1DP2-CA196375 to LL.

Keywords: genetic code, lncRNA, long non-coding RNA, mass spectrometry, proteogenomics, ribo-seq, ribosome, RNAseq

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Authors: Sofia N. Gonçalves, Duarte M. S. Albuquerque, José C. F. Pereira

Abstract:

Microwave technology has been gaining importance in contributing to decarbonization processes in high energy demand industries. Despite the several numerical models presented in the literature, a proper Verification and Validation exercise is still lacking. This is important and required to evaluate the physical process model accuracy and adequacy. Another issue addresses impedance matching, which is an important mechanism used in microwave experiments to increase electromagnetic efficiency. Such mechanism is not available in current computational tools, thus requiring an external numerical procedure. A numerical model was implemented to study the continuous processing of limestone with microwave heating. This process requires the material to be heated until a certain temperature that will prompt a highly endothermic reaction. Both a 2D and 3D model were built in COMSOL Multiphysics to solve the two-way coupling between Maxwell and Energy equations, along with the coupling between both heat transfer phenomena and limestone endothermic reaction. The 2D model was used to study and evaluate the required numerical procedure, being also a benchmark test, allowing other authors to implement impedance matching procedures. To achieve this goal, a controller built in MATLAB was used to continuously matching the cavity impedance and predicting the required energy for the system, thus successfully avoiding energy inefficiencies. The 3D model reproduces realistic results and therefore supports the main conclusions of this work. Limestone was modeled as a continuous flow under the transport of concentrated species, whose material and kinetics properties were taken from literature. Verification and Validation of the coupled model was taken separately from the chemical kinetic model. The chemical kinetic model was found to correctly describe the chosen kinetic equation by comparing numerical results with experimental data. A solution verification was made for the electromagnetic interface, where second order and fourth order accurate schemes were found for linear and quadratic elements, respectively, with numerical uncertainty lower than 0.03%. Regarding the coupled model, it was demonstrated that the numerical error would diverge for the heat transfer interface with the mapped mesh. Results showed numerical stability for the triangular mesh, and the numerical uncertainty was less than 0.1%. This study evaluated limestone velocity, heat transfer, and load influence on thermal decomposition and overall process efficiency. The velocity and heat transfer coefficient were studied with the 2D model, while different loads of material were studied with the 3D model. Both models demonstrated to be highly unstable when solving non-linear temperature distributions. High velocity flows exhibited propensity to thermal runways, and the thermal efficiency showed the tendency to stabilize for the higher velocities and higher filling ratio. Microwave efficiency denoted an optimal velocity for each heat transfer coefficient, pointing out that electromagnetic efficiency is a consequence of energy distribution uniformity. The 3D results indicated the inefficient development of the electric field for low filling ratios. Thermal efficiencies higher than 90% were found for the higher loads and microwave efficiencies up to 75% were accomplished. The 80% fill ratio was demonstrated to be the optimal load with an associated global efficiency of 70%.

Keywords: multiphysics modeling, microwave heating, verification and validation, endothermic reactions modeling, impedance matching, limestone continuous processing

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Authors: Thanusha D. Abeywickrama, Inoka C. Perera, Genji Kurisu

Abstract:

Tuberculosis, considered being as the ninth leading cause of death worldwide, cause from a single infectious agent M. tuberculosis and the drug resistance nature of this bacterium is a continuing threat to the world. Therefore TB preventing treatment is expanding, where this study designed to analyze the regulatory mechanism of GntR transcriptional regulator gene Rv0792c, which lie between several genes codes for some hypothetical proteins, a monooxygenase and an oxidoreductase. The gene encoding Rv0792c was cloned into pET28a and expressed protein was purified to near homogeneity by Nickel affinity chromatography. It was previously reported that the protein binds within the intergenic region (BS region) between Rv0792c gene and monooxygenase (Rv0793). This resulted in binding of three protein molecules with the BS region suggesting tight control of monooxygenase as well as its own gene. Since monooxygenase plays a key role in metabolism, this gene may have a global regulatory role. The natural ligand for this regulator is still under investigation. In relation to the Rv0792 protein structure, a Circular Dichroism (CD) spectrum was carried out to determine its secondary structure elements. Percentage-wise, 17.4% Helix, 21.8% Antiparallel, 5.1% Parallel, 12.3% turn and 43.5% other were revealed from CD spectrum data under room temperature. Differential Scanning Calorimetry (DSC) was conducted to assess the thermal stability of Rv0792, which the melting temperature of protein is 57.2 ± 0.6 °C. The graph of heat capacity (Cp) versus temperature for the best fit was obtained for non-two-state model, which concludes the folding of Rv0792 protein occurs through stable intermediates. Peak area (∆HCal ) and Peak shape (∆HVant ) was calculated from the graph and ∆HCal / ∆HVant was close to 0.5, suggesting dimeric nature of the protein.

Keywords: CD spectrum, DSC analysis, GntR transcriptional regulator, protein structure

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Authors: E. Al Daoud

Abstract:

In many cases, theoretical treatments are available for models for which there is no perfect physical realization. In this situation, the only possible test for an approximate theoretical solution is to compare with data generated from a computer simulation. In this paper, Monte Carlo tools are used to study and compare the elementary particles models. All the experiments are implemented using 10000 events, and the simulated energy is 13 TeV. The mean and the curves of several variables are calculated for each model using MadAnalysis 5. Anomalies in the results can be seen in the muons masses of the minimal supersymmetric standard model and the two Higgs doublet model.

Keywords: Feynman rules, hadrons, Lagrangian, Monte Carlo, simulation

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Authors: M. Nekri, A. Khelladi

Abstract:

The world wide web network is a network with a complex topology, the main properties of which are the distribution of degrees in power law, A low clustering coefficient and a weak average distance. Modeling the web as a graph allows locating the information in little time and consequently offering a help in the construction of the research engine. Here, we present a model based on the already existing probabilistic graphs with all the aforesaid characteristics. This work will consist in studying the web in order to know its structuring thus it will enable us to modelize it more easily and propose a possible algorithm for its exploration.

Keywords: clustering coefficient, preferential attachment, small world, web community

Procedia PDF Downloads 272