Search results for: trained graphic designers

Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

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In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: ANPR, CS, CNN, deep learning, NPL

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Authors: Z. Zerdoumi, D. Benatia, , D. Chicouche

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This paper investigates the application of artificial neural network to the problem of nonlinear channel equalization. The difficulties caused by channel distortions such as inter symbol interference (ISI) and nonlinearity can overcome by nonlinear equalizers employing neural networks. It has been shown that multilayer perceptron based equalizer outperform significantly linear equalizers. We present a multilayer perceptron based equalizer with decision feedback (MLP-DFE) trained with the back propagation algorithm. The capacity of the MLP-DFE to deal with nonlinear channels is evaluated. From simulation results it can be noted that the MLP based DFE improves significantly the restored signal quality, the steady state mean square error (MSE), and minimum Bit Error Rate (BER), when comparing with its conventional counterpart.

Keywords: Artificial Neural Network, signal restoration, Nonlinear Channel equalization, equalization

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Authors: Olivia A. Kjorlien, Maryam Asghari, Farshid Alizadeh-Shabdiz

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The goal of this paper is to investigate the impact of mosaic augmentation on the performance of object detection solutions. To carry out the study, YOLOv4 and YOLOv4-Tiny models have been selected, which are popular, advanced object detection models. These models are also representatives of two classes of complex and simple models. The study also has been carried out on two categories of objects, simple and complex. For this study, YOLOv4 and YOLOv4 Tiny are trained with and without mosaic augmentation for two sets of objects. While mosaic augmentation improves the performance of simple object detection, it deteriorates the performance of complex object detection, specifically having the largest negative impact on the false positive rate in a complex object detection case.

Keywords: accuracy, false positives, mosaic augmentation, object detection, YOLOV4, YOLOV4-Tiny

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Authors: Lara F. Horani

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Design is one of the most important stages in the process of product development. Product design has experienced significant changes over the years ranging from concentrating on cost and performance to combining economic, environmental and social considerations in customer requirements. Its evolution is in accordance with rapidly changing technology, economic situations, and climate change and environmental issues, as well as social context. Within product design, sustainability is a concept that balances economic, social and environmental aspects. This research aims to express changes in customer requirements over time from the viewpoint of sustainable design. It does so by systematically reviewing a broad scope of sustainable design literature. There is a need for a model to consider the changes that take place in customer requirements over time to build a successful relationship with customers which has been presented. Today’s literature does very little to even mention it, let alone present any progress in it. Systematic literature reviews are conducted primarily to: summarize the existing literature around a subject, highlight commonalities to build consensus, illuminate differences, identify gaps that can be filled, provide a background to position future research, and build a framework that can help designers meet the challenges of sustainable design.

Keywords: sustainable design, customer requirements for sustainable design, systematic literature reviews, changing customer requirements

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Authors: Aidan J. Bowes, Reaz Hasan

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The automotive industry is continually aiming to develop the aerodynamics of car body design. This may be for a variety of beneficial reasons such as to increase speed or fuel efficiency by reducing drag. However recently there has been a greater amount of focus on wind noise produced while driving. Designers in this industry seek a combination of both simplicity of approach and overall effectiveness. This combined with the growing availability of commercial CFD (Computational Fluid Dynamics) packages is likely to lead to an increase in the use of RANS (Reynolds Averaged Navier-Stokes) based CFD methods. This is due to these methods often being simpler than other CFD methods, having a lower demand on time and computing power. In this investigation the effectiveness of turbulent flow and acoustic noise prediction using RANS based methods has been assessed for different wing mirror geometries. Three different RANS based models were used, standard k-ε, realizable k-ε and k-ω SST. The merits and limitations of these methods are then discussed, by comparing with both experimental and numerical results found in literature. In general, flow prediction is fairly comparable to more complex LES (Large Eddy Simulation) based methods; in particular for the k-ω SST model. However acoustic noise prediction still leaves opportunities for more improvement using RANS based methods.

Keywords: acoustics, aerodynamics, RANS models, turbulent flow

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Authors: Ijaz Ahmed, Anwar Zada, Muhammad Waqas, M. U. Ashraf

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We demonstrate the performance of a very efficient tagger applies on hadronically decaying top quark pairs as signal based on deep neural network algorithms and compares with the QCD multi-jet background events. A significant enhancement of performance in boosted top quark events is observed with our limited computing resources. We also compare modern machine learning approaches and perform a multivariate analysis of boosted top-pair as well as single top quark production through weak interaction at √s = 14 TeV proton-proton Collider. The most relevant known background processes are incorporated. Through the techniques of Boosted Decision Tree (BDT), likelihood and Multlayer Perceptron (MLP) the analysis is trained to observe the performance in comparison with the conventional cut based and count approach

Keywords: top tagger, multivariate, deep learning, LHC, single top

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Authors: Christian Andrä, Pauline Hähner, Sebastian Ludyga

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Introduction: In the recent past, discussions on the importance of physical activity for child development have contributed to a growing interest in executive functions, which refer to cognitive processes. By controlling, modulating and coordinating sub-processes, they make it possible to achieve superior goals. Major components include working memory, inhibition and cognitive flexibility. While executive functions can be trained easily in school children, there are still research deficits regarding the trainability during preschool age. Methodology: This quasi-experimental study with pre- and post-design analyzes 23 children [age: 5.0 (mean value) ± 0.7 (standard deviation)] from four different sports groups. The intervention group was made up of 13 children (IG: 4.9 ± 0.6), while the control group consisted of ten children (CG: 5.1 ± 0.9). Between pre-test and post-test, children from the intervention group participated special games that train executive functions (i.e., changing rules of the game, introduction of new stimuli in familiar games) for ten units of their weekly sports program. The sports program of the control group was not modified. A computer-based version of the Eriksen Flanker Task was employed in order to analyze the participants’ inhibition ability. In two rounds, the participants had to respond 50 times and as fast as possible to a certain target (direction of sight of a fish; the target was always placed in a central position between five fish). Congruent (all fish have the same direction of sight) and incongruent (central fish faces opposite direction) stimuli were used. Relevant parameters were response time and accuracy. The main objective was to investigate whether children from the intervention group show more improvement in the two parameters than the children from the control group. Major findings: The intervention group revealed significant improvements in congruent response time (pre: 1.34 s, post: 1.12 s, p<.01), while the control group did not show any statistically relevant difference (pre: 1.31 s, post: 1.24 s). Likewise, the comparison of incongruent response times indicates a comparable result (IG: pre: 1.44 s, post: 1.25 s, p<.05 vs. CG: pre: 1.38 s, post: 1.38 s). In terms of accuracy for congruent stimuli, the intervention group showed significant improvements (pre: 90.1 %, post: 95.9 %, p<.01). In contrast, no significant improvement was found for the control group (pre: 88.8 %, post: 92.9 %). Vice versa, the intervention group did not display any significant results for incongruent stimuli (pre: 74.9 %, post: 83.5 %), while the control group revealed a significant difference (pre: 68.9 %, post: 80.3 %, p<.01). The analysis of three out of four criteria demonstrates that children who took part in a special sports program improved more than children who did not. The contrary results for the last criterion could be caused by the control group’s low results from the pre-test. Conclusion: The findings illustrate that inhibition can be trained as early as in preschool age. The combination of familiar games with increased requirements for attention and control processes appears to be particularly suitable.

Keywords: executive functions, flanker task, inhibition, preschool children

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

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Authors: Ching Louis Liu, Edmund Kazmierczak, Tim Miller

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Safety analysis for multi-agent systems is complicated by the, potentially nonlinear, interactions between agents. This paper proposes a method for analyzing the safety of multi-agent systems by explicitly focusing on interactions and the accident data of systems that are similar in structure and function to the system being analyzed. The method creates a Bayesian network using the accident data from similar systems. A feature of our method is that the events in accident data are labeled with HAZOP guide words. Our method uses an Ontology to abstract away from the details of a multi-agent implementation. Using the ontology, our methods then constructs an “Interaction Map,” a graphical representation of the patterns of interactions between agents and other artifacts. Interaction maps combined with statistical data from accidents and the HAZOP classifications of events can be converted into a Bayesian Network. Bayesian networks allow designers to explore “what it” scenarios and make design trade-offs that maintain safety. We show how to use the Bayesian networks, and the interaction maps to improve multi-agent system designs.

Keywords: multi-agent system, safety analysis, safety model, integration map

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Authors: Smita Lahkar

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Sattriya, the youngest of the eight principal Classical Indian dance traditions, has undergone too many changes and modifications to arrive at its present stage of performing art form extracting itself from age-old religious confinement. Although some of the other traditions have been revived in the recent past, Sattriya has a living tradition since its inception in the 15th century by Srimanta Sankardeva, the great Vaishnavite saint, poet, playwright, lyricist, painter, singer and dancer of Assam, a primary north-eastern state of India. This living dance tradition from the Sattras, the Vaishnavite monasteries, has been practiced for over five hundred years by celibate male monks, as a powerful medium for propagating the Vaishnava religious faith. Sankardeva realised the potential of the vocalised word integrated with the visual image as a powerful medium of expression and communication. So he used this principal medium for propagating his newly found message of devotion among the people of his time. Earlier, Sattriya was performed by male monks alone in monasteries (Sattras) as a part of daily rituals. The females were not even allowed to learn this art form. But, in present time, Sattriya has come out from the Sattras to proscenium stage, performed mostly by female as well as few male dancers also. The technique of performing movements, costumes, ornaments, music and style of performance too have experienced too many changes and modifications. For example, earlier and even today in Sattra, the ‘Pataka’ hand gesture is depicted in conformity with the original context (religious) of creation of the dance form. But, today stage-performers prefer the instructions of the scripture ‘Srihastamuktavali’ and depict the ‘Pataka’ in a sophisticated manner affecting decontextualisation to a certain extent. This adds aesthetic beauty to the dance form as an art distancing it from its context of being a vehicle for propagating Vaishnava religion. The Sattriya dance today stands at the crossroads of past and future, tradition and modernity, devotion and display, spirituality and secularism. The traditional exponents trained under the tutelage of Sattra maestros and imbibing a devotionally inspired rigour of the religion, try to retain the traditional nuances; while the young artists being trained outside the monasteries are more interested in taking up the discipline purely from the perspective of ‘performing arts’ bereft of the philosophy of religion or its sacred associations. Hence, this paper will be an endeavor to establish the hypothesis that the Sattriya, whose origin was for propagating Vaishnava faith, has now entered the world of performing arts with highly aesthetical components. And as a transformed art form, Sattriya may be expected to carve a niche in world dance arena. This will be done with the help of historical evidences, observations from the recorded past and expert rendezvous.

Keywords: dance, performing art, religion, Sattriya

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Authors: Mohamed Othmani, Yassine Khlifi

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This paper presents a technique for compact three dimensional (3D) object model reconstruction using wavelet networks. It consists to transform an input surface vertices into signals,and uses wavelet network parameters for signal approximations. To prove this, we use a wavelet network architecture founded on several mother wavelet families. POLYnomials WindOwed with Gaussians (POLYWOG) wavelet families are used to maximize the probability to select the best wavelets which ensure the good generalization of the network. To achieve a better reconstruction, the network is trained several iterations to optimize the wavelet network parameters until the error criterion is small enough. Experimental results will shown that our proposed technique can effectively reconstruct an irregular 3D object models when using the optimized wavelet network parameters. We will prove that an accurateness reconstruction depends on the best choice of the mother wavelets.

Keywords: 3d object, optimization, parametrization, polywog wavelets, reconstruction, wavelet networks

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

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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

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Authors: Davies Obaromi, Qin Yongsong, James Ndege

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To interpolate scattered or regularly distributed data, there are imprecise or exact methods. However, there are some of these methods that could be used for interpolating data in a regular grid and others in an irregular grid. In spatial epidemiology, it is important to examine how a disease prevalence rates are distributed in space, and how they relate with each other within a defined distance and direction. In this study, for the geographic and graphic representation of the disease prevalence, linear and biharmonic spline methods were implemented in MATLAB, and used to identify, localize and compare for smoothing in the distribution patterns of tuberculosis (TB) in Eastern Cape Province. The aim of this study is to produce a more “smooth” graphical disease map for TB prevalence patterns by a 3-D curve fitting techniques, especially the biharmonic splines that can suppress noise easily, by seeking a least-squares fit rather than exact interpolation. The datasets are represented generally as a 3D or XYZ triplets, where X and Y are the spatial coordinates and Z is the variable of interest and in this case, TB counts in the province. This smoothing spline is a method of fitting a smooth curve to a set of noisy observations using a spline function, and it has also become the conventional method for its high precision, simplicity and flexibility. Surface and contour plots are produced for the TB prevalence at the provincial level for 2012 – 2015. From the results, the general outlook of all the fittings showed a systematic pattern in the distribution of TB cases in the province and this is consistent with some spatial statistical analyses carried out in the province. This new method is rarely used in disease mapping applications, but it has a superior advantage to be assessed at subjective locations rather than only on a rectangular grid as seen in most traditional GIS methods of geospatial analyses.

Keywords: linear, biharmonic splines, tuberculosis, South Africa

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Authors: John Lorenzo Bautista, Yoon-Joong Kim

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This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.

Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition

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Authors: Hanan M. Taleb

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Energy consumption associated with buildings has a significant impact on the environment. To that end, and as a transaction between the inside and outside and between the building and urban space, the building skin plays an especially important role. It provides protection from the elements; demarcates private property and creates privacy. More importantly, it controls the admission of solar radiation. Therefore, designing the building skin sustainably will help to achieve optimal performance in terms of both energy consumption and thermal comfort. Unfortunately, with accelerating construction expansion, many recent buildings do not pay attention to the importance of the envelope design. This piece of research will highlight the importance of this part of the creation of buildings by providing evidence of a significant reduction in energy consumption if the envelopes are redesigned. Consequently, the aim of this paper is to enhance the performance of the hospital envelope in order to achieve sustainable performance. A hospital building sited in Abu Dhabi, in the UAE, has been chosen to act as a case study. A detailed analysis of the annual energy performance of the case study will be performed with the use of a computerised simulation; this is in order to explore their energy performance shortcomings. The energy consumption of the base case will then be compared with that resulting from the new proposed building skin. The results will inform architects and designers of the savings potential from various strategies.

Keywords: ASHREA, building skin, building envelopes, hospitals, Abu Dhabi, UAE, IES software

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Authors: Veena Easvaradoss, Ebenezer Joseph, Sumathi Chandrasekaran, Sweta Jain, Aparna Anna Mathai, Senta Christy

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Working memory refers to a cognitive processing space where information is received, managed, transformed, and briefly stored. It is an operational process of transforming information for the execution of cognitive tasks in different and new ways. Many class room activities require children to remember information and mentally manipulate it. While the impact of chess training on intelligence and academic performance has been unequivocally established, its impact on working memory needs to be studied. This study, funded by the Cognitive Science Research Initiative, Department of Science & Technology, Government of India, analyzed the effect of one-year chess training on the working memory of children. A pretest–posttest with control group design was used, with 52 children in the experimental group and 50 children in the control group. The sample was selected from children studying in school (grades 3 to 9), which included both the genders. The experimental group underwent weekly chess training for one year, while the control group was involved in extracurricular activities. Working memory was measured by two subtests of WISC-IV INDIA. The Digit Span Subtest involves recalling a list of numbers of increasing length presented orally in forward and in reverse order, and the Letter–Number Sequencing Subtest involves rearranging jumbled alphabets and numbers presented orally following a given rule. Both tasks require the child to receive and briefly store information, manipulate it, and present it in a changed format. The Children were trained using Winning Moves curriculum, audio- visual learning method, hands-on- chess training and recording the games using score sheets, analyze their mistakes, thereby increasing their Meta-Analytical abilities. They were also trained in Opening theory, Checkmating techniques, End-game theory and Tactical principles. Pre equivalence of means was established. Analysis revealed that the experimental group had significant gains in working memory compared to the control group. The present study clearly establishes a link between chess training and working memory. The transfer of chess training to the improvement of working memory could be attributed to the fact that while playing chess, children evaluate positions, visualize new positions in their mind, analyze the pros and cons of each move, and choose moves based on the information stored in their mind. If working-memory’s capacity could be expanded or made to function more efficiently, it could result in the improvement of executive functions as well as the scholastic performance of the child.

Keywords: chess training, cognitive development, executive functions, school children, working memory

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Authors: Amic G. Ho

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Language usage and typography in Hong Kong are unique, as can be seen clearly on the streets of the city. In contrast to many other parts of the world, where there is only one language, in Hong Kong many signs and billboards display two languages: Chinese and English. The language usage on signage, fonts and types used, and the designs in magazines and advertisements all demonstrate the unique features of Hong Kong typographic design, which reflect the multicultural nature of Hong Kong society. This study is the first step in investigating the nature and development of Hong Kong typography. The preliminary research explored how the historical development of Hong Kong is reflected in its unique typography. Following a review of historical development, a quantitative study was designed: Local Hong Kong participants were invited to provide input on what makes the Hong Kong typographic style unique. Their input was collected and analyzed. This provided us with information about the characteristic criteria and features of Hong Kong typography, as recognized by the local people. The most significant typographic designs in Hong Kong were then investigated and the influence of Chinese and other cultures on Hong Kong typography was assessed. The research results provide an indication to local designers on how they can strengthen local design outcomes and promote the values and culture of their mother town.

Keywords: typography, Hong Kong, historical developments, multiple cultures

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: H. Nejadriahi

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A growing demand for sustainability makes sustainability as one of the significant debates of nowadays. Energy saving is one of the main criteria to be considered in the context of sustainability. Reducing energy use in buildings is one of the most important ways to reduce humans’ overall environmental impact. Taking this into consideration, study of different design strategies, which can assist in reducing energy use and subsequently improving the sustainability level of today's buildings would be an essential task. The sustainability level of a building is highly affected by the sustainability performance of its components. One of the main building components, which can have a great impact on energy saving and sustainability level of the building, is its facade. The aim of this study is to investigate on the role of facade in sustainability enhancement of the contemporary buildings of Iran. In this study, the concept of sustainability in architecture, the building facades, and their relationship to sustainability are explained briefly. Following that, a number of contemporary Iranian buildings are discussed and analyzed in terms of different design strategies used in their facades in accordance to the sustainability concepts. The methods used in this study are descriptive and analytic. The results of this paper would assist in generating a wider vision and a source of inspiration for the current designers to design and create environmental and sustainable buildings for the future.

Keywords: building facade, contemporary buildings, Iran, sustainability

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Authors: Lo Kar Yin, Law Ka Mei

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Architectural, engineering, construction and operations (AECO) industry practitioners have been well adapting to the dynamic construction market from the fundamental training of its discipline. As further triggered by the pandemic since 2019, great steps are taken in virtual environment and the best collaboration is strived with project teams without boundaries. With adoption of Building Information Modeling-based approach and qualitative analysis, this paper is to review quantity take-off and cost estimation process through modeling techniques in liaison with suppliers, fabricators, subcontractors, contractors, designers, consultants and services providers in the construction industry value chain for automatic project cost budgeting, project cost control and cost evaluation on design options of in-situ reinforced-concrete construction and Modular Integrated Construction (MiC) at design stage, variation of works and cash flow/spending analysis at construction stage as far as practicable, with a view to sharing the findings for enhancing mutual trust and co-operation among AECO industry practitioners. It is to foster development through a common prototype of design and build project delivery method in NEC Engineering and Construction Contract (ECC) Options A and C.

Keywords: building information modeling, cost estimation, quantity take-off, modeling techniques

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Authors: Paolo Pilloni, Fabrizio Mulas, Salvatore Carta

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Nowadays, several research studies point up that an active lifestyle is essential for physical and mental health benefits. Mobile phones have greatly influenced people’s habits and attitudes also in the way they exercise. Our research work is mainly focused on investigating how to exploit mobile technologies to favour people’s exertion experience. To this end, we developed an exertion framework users can exploit through a real world mobile application, called BLINDED, designed to act as a virtual personal trainer to support runners during their trainings. In this work, inspired by both previous findings in the field of interaction design for people with visual impairments, feedback gathered from real users of our framework, and positive results obtained from two experimentations, we present some new interaction facilities we designed to enhance the interaction experience during a training. The positive obtained results helped us to derive some interaction design recommendations we believe will be a valid support for designers of future mobile systems conceived to be used in circumstances where there are limited possibilities of interaction.

Keywords: human computer interaction, interaction design guidelines, persuasive mobile technologies for sport and health

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Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

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Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

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Authors: In Hoi Lee, Seong Baeg Kim, Je Eung Jeon, Gwang Yong Choi, Joo Sub Lee, Ik Sang Kim

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Recently, the interest of globalization in the field of teacher education has increased. In the U.S., the government is trying to enhance the quality of education through a global approach in education. To do so, the schools in the U.S. are recruiting teachers with global capability from countries like Korea where competent teachers are being trained. Meanwhile, in the case of Korea, although excellent teachers have been cultivated every year, due to a low birth rate it is not easy to become a domestic teacher. To solve the trouble that the two countries are facing, the study first examines the demand and necessity of globalization in the field of teacher education between Korea and the U.S. Second, we propose a new project, called the ‘Global Teachers University (GTU)’ program to satisfy the demands of both countries. Finally, we provide its implications to build the future educational cooperation for teacher training in a global context.

Keywords: educational cooperation, globalization, teachers education program, teacher training institutions

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Authors: Nuran Bahar, Mehmet A. Akcayol

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In the aviation industry, many faults may occur frequently during the maintenance processes and assembly operations of complex structured aircrafts because of their high dependencies of components. These faults affect the quality of aircraft parts or developed modules adversely. Technical employee requires long time and high labor force while checking the correctness of each component. In addition, the person must be trained regularly because of the ever-growing and changing technology. Generally, the cost of this training is very high. Augmented Reality (AR) technology reduces the cost of training radically and improves the effectiveness of the training. In this study, the usage of AR technology in the aviation industry has been investigated and the effectiveness of AR with heads-up display glasses has been examined. An application has been developed for comparison of production process with AR and manual one.

Keywords: aerospace, assembly quality, augmented reality, heads-up display

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Authors: Meng-Tzu Cheng, Louisa Rosenheck, Chen-Yen Lin, Eric Klopfer

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The purpose of the research is to explore some of the ways in which gameplay data can be analyzed to yield results that feedback into the learning ecosystem. Back-end data for all users as they played an MMOG, The Radix Endeavor, was collected, and this study reports the analyses on a specific genetics quest by using the data mining techniques, including the decision tree method. In the study, different reasons for quest failure between participants who eventually succeeded and who never succeeded were revealed. Regarding the in-game tools use, trait examiner was a key tool in the quest completion process. Subsequently, the results of decision tree showed that a lack of trait examiner usage can be made up with additional Punnett square uses, displaying multiple pathways to success in this quest. The methods of analysis used in this study and the resulting usage patterns indicate some useful ways that gameplay data can provide insights in two main areas. The first is for game designers to know how players are interacting with and learning from their game. The second is for players themselves as well as their teachers to get information on how they are progressing through the game, and to provide help they may need based on strategies and misconceptions identified in the data.

Keywords: MMOG, decision tree, genetics, gaming-learning interaction

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Authors: Hatharasinghe Liyanage Saneetha Chathaurika, Shreenika De Silva Weliange

Abstract:

Background and Significance of the Study: Natural and human-induced disasters have become more common due to rapid development and climate change. Therefore hospitalization due to injuries has increased in the midst of advancement in medicine. Prehospital trauma care is critical in reducing morbidity and mortality following injury. Army soldiers are one of the first responder categories after a major disaster causing injury. Thus, basic life support measures taken by trained lay first responders is life-saving, it is important to build up their capacities by updating their knowledge and practices while cultivating positive attitudes toward it. Objective: To describe knowledge, attitudes and practices on prehospital trauma care among army soldiers in Matara District. Methodology: A descriptive cross sectional study was carried out among army soldiers in Matara district. The whole population was studied belonging to the above group during the study period. Self-administered questionnaire was used as the study instrument. Cross tabulations were done to identify the possible associations using chi square statistics. Knowledge and practices were categorized in to two groups as “Poor” and “Good” taking 50% as the cut off. Results: The study population consists of 266 participants (response rate 97.79%).The overall level of knowledge on prehospital trauma care is poor (78.6%) while knowledge on golden hour of trauma (77.1%), triage system (74.4%), cardio pulmonary resuscitation (92.5%) and transportation of patients with spinal cord injury (69.2%) was markedly poor. Good knowledge is significantly associated with advance age, higher income and higher level of education whereas it has no significant association with work duration. More than 80% of them had positive attitudes on most aspects of prehospital trauma care while majority thinks it is good to have knowledge on this topic and they would have performed better in disaster situations if they were trained on pre-hospital trauma care. With regard to the practice, majority (62.8%) is included in the group of poor level of practice. They lack practice on first-aid, cardiopulmonary resuscitation and safe transportation of the patients. Moreover, they had less opportunity to participate in drills/simulation programs done on disaster events. Good practice is significantly associated with advance age and higher level of education but not associated with level of income and working duration of army soldiers. Highly significant association was observed between the level of knowledge and level of practice on prehospital trauma care of army soldiers. It is observed that higher the knowledge practices become better. Conclusion: A higher proportion of army soldiers had poor knowledge and practice on prehospital trauma care while majority had positive attitudes regarding it. Majority lacks knowledge and practice in first-aid and cardiopulmonary resuscitation. Due to significant association observed between knowledge and practice it can be recommended to include a training session on prehospital trauma care in the basic military curriculum which will enhance the ability to act as first responders effectively. Further research is needed in this area of prehospital trauma care to enhance the qualitative outcome.

Keywords: disaster, prehospital trauma care, first responders, army soldiers

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Authors: Sergo Tsiramua, Sulkhan Sulkhanishvili, Elisabed Asabashvili, Lazare Kvirtia

Abstract:

The paper presents logical-probabilistic methods, models, and algorithms for reliability assessment of complex systems, based on which a web application for structural analysis and reliability assessment of systems was created. It is important to design systems based on structural analysis, research, and evaluation of efficiency indicators. One of the important efficiency criteria is the reliability of the system, which depends on the components of the structure. Quantifying the reliability of large-scale systems is a computationally complex process, and it is advisable to perform it with the help of a computer. Logical-probabilistic modeling is one of the effective means of describing the structure of a complex system and quantitatively evaluating its reliability, which was the basis of our application. The reliability assessment process included the following stages, which were reflected in the application: 1) Construction of a graphical scheme of the structural reliability of the system; 2) Transformation of the graphic scheme into a logical representation and modeling of the shortest ways of successful functioning of the system; 3) Description of system operability condition with logical function in the form of disjunctive normal form (DNF); 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical elements with probabilistic elements in ODNF, obtaining a reliability estimation polynomial and quantifying reliability; 6) Calculation of “weights” of elements of system. Using the logical-probabilistic methods, models and algorithms discussed in the paper, a special software was created, by means of which a quantitative assessment of the reliability of systems of a complex structure is produced. As a result, structural analysis of systems, research, and designing of optimal structure systems are carried out.

Keywords: complex systems, logical-probabilistic methods, orthogonalization algorithm, reliability of systems, “weights” of elements

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Authors: Pei-Jun Xue, Ming-Yu Hsiao

Abstract:

Language is the emblem of a culture, representing the extension of cultural life. In addition, it is also an important tool for communication and message transmission. It carries not only information but also covers the self-conscious of the information constructor as well as the situational experiences of users from different backgrounds. Moreover, design can be regarded as a language, a dynamic process of coding and decoding. With the designers’ experiences in everyday life, they bring them into the products’ experiences. Considered from the aspects of atmosphere and the five senses, a designer should consider and reconsider how to communicate the messages effectively to suit the users’ needs. In the process of language learning, we should understand the construction behind it and the rules of the compositions of language codes. Regarding the understanding of the design of works or the form of product construction, it is necessary for us to understand the coding system during the process of product construction. The form (signifiers) and meanings (signified) of Chinese characters are closely related. At the same time, it is also a process of simplifying the complicated to the simple. This study discusses the chinese characters that used in the cultural symbols construction, and analysis of existing products by Peirce's semiotic triangles. Through people's cognition of Chinese characters and constitute method, help to understand the way of construction product symbol.

Keywords: cultural-creative product design, cultural product, cultural symbols, linguistic symbols

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Authors: Ezekiel Ejiofor Nnadi

Abstract:

Nigeria construction industry is known for its active construction activities. This has earmarked the industry to be the key to economic growth of the nation. It has largest employer of labour and gives sustenance to other industries like manufacturing industry. While this is a sign of growth and prosperity; the waste generated by the industry has always been a problem and a serious concern. It results in wastage of economic gain and has resultant health effect on the populace apart from injury being sustained on sites. This work provides a platform to learn more about construction waste, its management strategy and how to reduce waste production in Nigeria construction industry. Construction sites, waste management authority and public health institutions in Lagos as the centre of most construction activities in Nigeria were selected, and a set of questionnaire was administered to using the systematic sampling technique. Descriptive statistics and relative importance index (RII) technique were employed for the analysis of the data gathered. The findings of the analysis show that excessive wastes reduce contractors’ profit margin and also that some construction wastes contain hazardous and toxic elements such as lead, asbestos or radioactive materials which required proper handling and effective disposal. The conclusion was drawn that the check on waste on construction sites starts with the designers to the contractors who execute on site.

Keywords: construction cost, construction industry, economic growth, materials wastes

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Authors: Saeedeh Barzegar Khalilsaraei, Manoocheher Kelarestaghi, Farshad Eshghi

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The vehicle color, as a prominent and stable feature, helps to identify a vehicle more accurately. As a result, vehicle color recognition is of great importance in intelligent transportation systems. Unlike conventional methods which use only a single Convolutional Neural Network (CNN) for feature extraction or classification, in this paper, four CNNs, with different architectures well-performing in different classes, are trained to extract various features from the input image. To take advantage of the distinct capability of each network, the multiple outputs are combined using a stack generalization algorithm as an ensemble technique. As a result, the final model performs better than each CNN individually in vehicle color identification. The evaluation results in terms of overall average accuracy and accuracy variance show the proposed method’s outperformance compared to the state-of-the-art rivals.

Keywords: Vehicle Color Recognition, Ensemble Algorithm, Stack Generalization, Convolutional Neural Network

Procedia PDF Downloads 78