Search results for: Kriging techniques

Authors: Arun C. O., Shrijith M. B., Thakur Rajesh Singh

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The study aims to analyze and understand the biomechanical stability of the atlantoaxial complex under different posterior fixation techniques using the finite element method in the Indian context. The conventional cadaveric studies performed show heterogeneity in biomechanical properties. The finite element method being a versatile numerical tool, is being wisely used for biomechanics analysis of atlantoaxial complex. However, the biomechanics of posterior fixation techniques for an Indian subject is missing in the literature. It is essential to study in this context as the bone density and geometry of vertebrae vary from region to region, thereby requiring different screw lengths and it can affect the range of motion(ROM), stresses generated. The current study uses CT images for developing a 3D finite element model with C1-C2 geometry without ligaments. Instrumentation is added to this geometry to develop four models for four fixation techniques, namely C1-C2 TA, C1LM-C2PS, C1LM-C2Pars, C1LM-C2TL. To simulate Flexion, extension, lateral bending, axial rotation, 1.5 Nm is applied to C1 while the bottom nodes of C2 are fixed. Then Range of Motion (ROM) is compared with the unstable model(without ligaments). All the fixation techniques showed more than 97 percent reduction in the Range of Motion. The von-mises stresses developed in the screw constructs are obtained. From the studies, it is observed that Transarticular technique is most stable in Lateral Bending, C1LM-C2 Translaminar is found most stable in Flexion/extension. The Von-Mises stresses developed minimum in Trasarticular technique in lateral bending and axial rotation, whereas stress developed in C2 pars construct minimum in Flexion/ Extension. On average, the TA technique is stable in all motions and also stresses in constructs are less in TA. Tarnsarticular technique is found to be the best fixation technique for Indian subjects among the 4 methods.

Keywords: biomechanics, cervical spine, finite element model, posterior fixation

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Authors: Ghada Elshafei, A. Elazim Negm

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Recently, Green architecture becomes a significant way to a sustainable future. Green building designs involve finding the balance between comfortable homebuilding and sustainable environment. Moreover, the utilization of the new technologies such as artificial intelligence techniques are used to complement current practices in creating greener structures to keep the built environment more sustainable. The most common objectives are green buildings should be designed to minimize the overall impact of the built environment on ecosystems in general and particularly on human health and on the natural environment. This will lead to protecting occupant health, improving employee productivity, reducing pollution and sustaining the environmental. In green building design, multiple parameters which may be interrelated, contradicting, vague and of qualitative/quantitative nature are broaden to use. This paper presents a comprehensive critical state of art review of current practices based on fuzzy and its combination techniques. Also, presented how green architecture/building can be improved using the technologies that been used for analysis to seek optimal green solutions strategies and models to assist in making the best possible decision out of different alternatives.

Keywords: green architecture/building, technologies, optimization, strategies, fuzzy techniques, models

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Authors: Alhassan Dahiru

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Value management is widely accepted technique of eliminating unnecessary cost at different stages of project development that maximizes the functional value of a project by managing its evolution and development from concept to completion. Many construction industry practitioners are not aware of Value Management practice, and its use is less widespread in Nigeria. The aim of this research is to identify the level of awareness on value management practice amongst construction practitioners with a view to contribute to the improvement of the implementation of value management practice in the Nigerian construction industry. In this study, construction practitioners have been chosen as respondents from the 6 geopolitical zones of the federation including FCT Abuja. Through the survey, a total number of 360 semi-structured questionnaires were administered and 284 were returned and remained good for the analysis. The results indicate that most of the respondents were aware of the value management concept and issues surrounding construction industry in Nigeria, while about 32% of the respondents were not aware of its potential benefits. Therefore, organisations should review their techniques and processes from time to time for improvement on effective service delivery. Additionally, a change management strategy should also be part of every organization to ease the introduction of new techniques such as value management. There is also the need for more value management training workshops and seminars in order to enlighten the participants of the construction industry on the principles, concept, and techniques involved in the value management process.

Keywords: sustainability, value management, construction practitioners, Nigeria

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Authors: Emin Gundogar, Burak Erkayman, Nusret Sazak

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Providing effective management performance through the whole supply chain is critical issue and hard to applicate. The proper evaluation of integrated data may conclude with accurate information. Analysing the supply chain data through OLAP (On-Line Analytical Processing) technologies may provide multi-angle view of the work and consolidation. In this study, association rules and classification techniques are applied to measure the supply chain performance metrics of an automotive manufacturer in Turkey. Main criteria and important rules are determined. The comparison of the results of the algorithms is presented.

Keywords: supply chain performance, performance measurement, data mining, automotive

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Authors: Hosam Mohamed Darwish

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In 2008, the Egyptian Ministry of Education introduced a new national coursebook ‘Hello for Secondary Schools, which recommends a shift in EFL teachers’ instructional practices. Since then, very little attention has been paid to teachers’ techniques in EFL writing classes. Hence, this study aimed at investigating teaching writing practices in secondary schools and exploring the teachers’ attitudes towards EFL writing skill in addition to exploring the difficulties that teachers encountered in EFL writing lessons. The study depended on data triangulation through administering two questionnaires: one to 44 teachers and the other to 24 students, and conducting semi-structured interviews with 11 teachers. Both teachers and students were asked to describe teaching practices in EFL writing classes while the open-ended questions and interviews collected data about the teachers’ difficulties in writing lessons. The questionnaires indicate that teachers have negative attitudes towards teaching writing, and most of their practices are still traditional. Five factors have influenced teachers’ practices: backwash of the test, teachers’ professional development, students’ culture of reading and large classes. The study recommends there has to be a necessary change in the students’ examination system, and ongoing teachers’ professional development should be considered. Finally, a teaching model and implications are suggested.

Keywords: EFL writing, Egyptian secondary schools, teachers’ attitudes, teachers’ techniques

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Authors: Mei-Yi Wu, Shang-Ming Huang

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The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system.

Keywords: mobile image retrieval, text mining, product information service system, online marketing

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Authors: Soner Güler, Mustafa Gülen, Eylem Güzel

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Masonry buildings constitute major part of building stock in Turkey. Masonry buildings were built up especially in rural areas and underdeveloped regions due to economic reasons. Almost all of these masonry buildings are not designed and detailed according to any design guidelines by designers. As a result of this, masonry buildings were totally collapsed or heavily damaged when subjected to destructive earthquake effects. Thus, these masonry buildings that were built up in our country must be retrofitted to improve their seismic performance. In this study, new seismic retrofitting techniques that is easy to apply and low-cost are summarized and the importance of seismic retrofitting is also emphasized for existing masonry buildings in Turkey.

Keywords: masonry buildings, earthquake effects, seismic retrofitting techniques, seismic performance

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Authors: Joseph George, Anne Kotteswara Roa

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Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

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Authors: H. E. Keshta, A. A. Ali

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Three phase grid-tied inverters are widely employed in micro-grids (MGs) as interphase between DC and AC systems. These inverters are usually controlled through standard decoupled d–q vector control strategy based on proportional integral (PI) controllers. Recently, advanced meta-heuristic optimization techniques have been used instead of deterministic methods to obtain optimum PI controller parameters. This paper provides a comparative study between the performance of the global Porcellio Scaber algorithm (GPSA) based PI controller and Manta Ray foraging optimization (MRFO) based PI controller.

Keywords: micro-grids, optimization techniques, grid-tied inverter control, PI controller

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Authors: Charles St. Geste, Michael Neumann, Catherine Twohig

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Our primary aim is to examine farmer-centered participatory action learning as a tool to improve agricultural production, build resilience to climate shocks and, more broadly, advance community-driven solutions for sustainable development in rural communities across Haiti. For over six years, sixty plus farmers from Deslandes, Haiti, organized in three traditional work groups called konbits, have designed and tested low-input agroecology techniques as part of the Konbit Vanyan Kapab Pwoje Agroekoloji. The project utilizes a participatory action learning approach, emphasizing social inclusion, building on local knowledge, experiential learning, active farmer participation in trial design and evaluation, and cross-community sharing. Mixed methods were used to evaluate changes in knowledge and adoption of agroecology techniques, confidence in advancing agroecology locally, and innovation among Konbit Vanyan Kapab farmers. While skill and knowledge in application of agroecology techniques varied among individual farmers, a majority of farmers successfully adopted techniques outside of the trial farms. The use of agroecology techniques on trial and individual farms has doubled crop production in many cases. Farm income has also increased, and farmers report less damage to crops and property caused by extreme weather events. Furthermore, participatory action strategies have led to greater local self-determination and greater capacity for sustainable community development. With increased self-confidence and the knowledge and skills acquired from participating in the project, farmers prioritized sharing their successful techniques with other farmers and have developed a farmer-to-farmer training program that incorporates participatory action learning. Using adult education methods, farmers, trained as agroecology educators, are currently providing training in sustainable farming practices to farmers from five villages in three departments across Haiti. Konbit Vanyan Kapab farmers have also begun testing production of value-added food products, including a dried soup mix and tea. Key factors for success include: opportunities for farmers to actively participate in all phases of the project, group diversity, resources for application of agroecology techniques, focus on group processes and overcoming local barriers to inclusive decision-making.

Keywords: agroecology, participatory action learning, rural Haiti, sustainable community development

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Authors: Maryam Khazaei Pool, Lori Lewis

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This is a summary of articles based on higher order B-splines methods and the variation of B-spline methods such as Quadratic B-spline Finite Elements Method, Exponential Cubic B-Spline Method, Septic B-spline Technique, Quintic B-spline Galerkin Method, and B-spline Galerkin Method based on the Quadratic B-spline Galerkin method (QBGM) and Cubic B-spline Galerkin method (CBGM). In this paper, we study the B-spline methods and variations of B-spline techniques to find a numerical solution to the Burgers’ equation. A set of fundamental definitions, including Burgers equation, spline functions, and B-spline functions, are provided. For each method, the main technique is discussed as well as the discretization and stability analysis. A summary of the numerical results is provided, and the efficiency of each method presented is discussed. A general conclusion is provided where we look at a comparison between the computational results of all the presented schemes. We describe the effectiveness and advantages of these methods.

Keywords: Burgers’ equation, Septic B-spline, modified cubic B-spline differential quadrature method, exponential cubic B-spline technique, B-spline Galerkin method, quintic B-spline Galerkin method

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Authors: John O. Akindoyo, M. D. H. Beg, Suriati Binti Ghazali, Nitthiyah Jeyaratnam

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Regeneration of bone due to the many health challenges arising from traumatic effects of bone loss, bone tumours and other bone infections is fast becoming indispensable. Over the period of time, some approaches have been undertaken to mitigate this challenge. This includes but not limited to xenografts, allografts, autografts as well as artificial substitutions like bioceramics, synthetic cements and metals. However, most of these techniques often come along with peculiar limitation and problems such as morbidity, availability, disease transmission, collateral site damage or absolute rejection by the body as the case may be. Hydroxyapatite (HA) is very compatible and suitable for this application. However, most of the common methods for HA synthesis are expensive and environmentally unfriendly. Extraction of HA from bio-wastes have been perceived not only to be cost effective, but also environment-friendly. In this research, HA was produced from bio-waste: namely bovine bones through a combination of hydrothermal chemical processes and ordinary calcination techniques. Structure and property of the HA was carried out through different characterization techniques (such as TGA, FTIR, DSC, XRD and BET). The synthesized HA was found to possess similar properties to stoichiometric HA with highly desirable thermal, degradation, structural and porous properties. This material is unique for its potential minimal cost, environmental friendliness and property controllability. It is also perceived to be suitable for tissue and bone engineering applications.

Keywords: biomaterial, biopolymer, bone, hydroxyapatite

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Authors: John Kabuba

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The study investigated the implementation of the Neural Network (NN) techniques for prediction of the loading of Cu ions onto clinoptilolite. The experimental design using analysis of variance (ANOVA) was chosen for testing the adequacy of the Neural Network and for optimizing of the effective input parameters (pH, temperature and initial concentration). Feed forward, multi-layer perceptron (MLP) NN successfully tracked the non-linear behavior of the adsorption process versus the input parameters with mean squared error (MSE), correlation coefficient (R) and minimum squared error (MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed that NN modeling techniques could effectively predict and simulate the highly complex system and non-linear process such as ion-exchange.

Keywords: clinoptilolite, loading, modeling, neural network

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Authors: Abdallah A. Hlayel

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Operations research science (OR) deals with good success in developing and applying scientific methods for problem solving and decision-making. However, by using OR techniques, we can enhance the use of computer decision support systems to achieve optimal management for institutions. OR applies comprehensive analysis including all factors that affect on it and builds mathematical modeling to solve business or organizational problems. In addition, it improves decision-making and uses available resources efficiently. The adoption of OR by universities would definitely contributes to the development and enhancement of the performance of OR techniques. This paper provides an understanding of the structures, approaches and models of OR in problem solving and decision-making.

Keywords: best candidates' method, decision making, decision support system, operations research

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Authors: Mustafa Dogru, Ruveyda Komurlu

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Companies and professionals in the construction sector face various risks in every project depending on the characteristics, size, complexity, the location of the projects and the techniques used. Some risks’ effects may increase as the project progresses whereas new risks may emerge. Because of the ever-changing nature of the risks, risk management is a cyclical process that needs to be repeated throughout the project. Since the risks threaten the success of the project, risk management is an important part of the entire project management process. The aims of this study are to emphasize the importance of risk management in construction projects, summarize the risk identification process, and introduce a number of methods for preventing risks such as alternative design, checklists, prototyping and test-analysis-correction technique etc. Following the literature review conducted to list the techniques for preventing risks, case studies has been performed to compare and evaluate the success of the techniques in a number of completed projects with the same typology, performed domestic and international. Findings of the study suggest that controlling and minimizing the level of the risks in construction projects, taking optimal precautions for different risks, and mitigating or eliminating the effects of risks are important in order to prevent additional costs for the project. Additionally, focusing on the risks that have highest impact is the most rational way to minimize the effects of the risks on projects.

Keywords: construction projects, construction management, project management, risk management

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Authors: A. Vaidya-Soocheta, K. M. Wong-Hon-Lang

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Craft and fashion have always been interlinked. The combination of both often gives stunning results. The present study introduces ‘Paper Cutting Craft Techniques’ like the Japanese –Kirigami, Mexican –PapelPicado, German –Scherenschnitte, Polish –Wycinankito in textiles to develop innovative and novel design structures as embellishments and ornamentation. The project studies various ways of using these paper cutting techniques to obtain interesting features and delicate design patterns on fabrics. While paper has its advantages and related uses, it is fragile rigid and thus not appropriate for clothing. Fabric is sturdy, flexible, dimensionally stable and washable. In the present study, the cut out techniques develop creative design motifs and patterns to give an inventive and unique appeal to the fabrics. The beauty and fascination of lace in garments have always given them a nostalgic charm. Laces with their intricate and delicate complexity in combination with other materials add a feminine touch to a garment and give it a romantic, mysterious appeal. Various textured and decorative effects through fabric manipulation are experimented along with the use of paper cutting craft skills as an innovative substitute for developing lace or “Broderie Anglaise” effects on textiles. A number of assorted fabric types with varied textures were selected for the study. Techniques to avoid fraying and unraveling of the design cut fabrics were introduced. Fabrics were further manipulated by use of interesting prints with embossed effects on cut outs. Fabric layering in combination with assorted techniques such as cutting of folded fabric, printing, appliqué, embroidery, crochet, braiding, weaving added a novel exclusivity to the fabrics. The fabrics developed by these innovative methods were then tailored into garments. The study thus tested the feasibility and practicability of using these fabrics by designing a collection of evening wear garments based on the theme ‘Nostalgia’. The prototypes developed were complemented by designing fashion accessories with the crafted fabrics. Prototypes of accessories add interesting features to the study. The adaptation and application of this novel technique of paper cutting craft on textiles can be an innovative start for a new trend in textile and fashion industry. The study anticipates that this technique will open new avenues in the world of fashion to incorporate its use commercially.

Keywords: collection, fabric cutouts, nostalgia, prototypes

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Authors: Daphne Alroy-Thiberge

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Trauma-impacted individuals present unique treatment challenges that include high reactivity, hyper-and hypo-arousal, poor adherence to therapy, as well as powerful transference and counter-transference experiences in therapy. This work provides an overview of the clinical tenets most often encountered in trauma-impacted individuals. Further, it provides readily applicable clinical techniques to optimize therapeutic rapport and facilitate accelerated positive mental health outcomes. Finally, integrated neuroscience and clinical evidence-based data are discussed to shed new light on crisis states in trauma-impacted individuals. This knowledge is utilized to provide effective and concrete interventions towards rapid and successful de-escalation of the impacted individual. A highly interactive, adult-learning-principles-based modality is utilized to provide an organic learning experience for participants. The information and techniques learned aim to increase clinical effectiveness, reduce staff injuries and burnout, and significantly enhance positive mental health outcomes and self-determination for the trauma-impacted individuals treated.

Keywords: clinical competencies, crisis interventions, psychotherapy techniques, trauma informed care

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Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: biological ontology, linked data, semantic data integration, semantic web

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Authors: V. B. Bastos, M. P. Lima, P. R. G. Kurka

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This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.

Keywords: simulation, visual navigation, mobile robot, data visualization

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Authors: Nuray Yılmaz Baran

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The conjugated Schiff base polymers which are also called as polyazomethines are promising materials for various applications due to their good thermal resistance semiconductive, liquid crystal, fiber forming, nonlinear optical outstanding photo- and electroluminescence and antimicrobial properties. In recent years, polyazomethines have attracted intense attention of researchers especially due to optoelectronic properties which have made its usage possible in organic light emitting diodes (OLEDs), solar cells (SCs), organic field effect transistors (OFETs), and photorefractive holographic materials (PRHMs). In this study, N-(pyridin-2-ylmethylidene)pyridin-2-amine Schiff base was synthesized from condensation reaction of 2-aminopyridine with 2-pyridine carbaldehyde. Polymerization of Schiff base was achieved by polycondensation reaction using NaOCl oxidant in methanol medium at various time and temperatures. The synthesized Schiff base monomer and polymer (Poly(N-(pyridin-2-ylmethylidene)pyridin-2-amine)) was characterized by UV-vis, FT-IR, 1H-NMR, XRD techniques. Molecular weight distribution and the surface morphology of the polymer was determined by GPC and SEM-EDAX techniques. Thermal behaviour of the monomer and polymer was investigated by TG/DTG, DTA and DSC techniques.

Keywords: polyazomethines, polycondensation reaction, Schiff base polymers, thermal stability

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Authors: Saif Al-Qaisi, Alif Saba

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Normalization of electromyography (EMG) data in ergonomics research is a prerequisite for interpreting the data. Normalizing accounts for variability in the data due to differences in participants’ physical characteristics, electrode placement protocols, time of day, and other nuisance factors. Typically, normalized data is reported as a percentage of the muscle’s isometric maximum voluntary contraction (%MVC). Various MVC techniques have been recommended in the literature for normalizing EMG activity of back muscles. This research tests and compares the recommended MVC techniques in the literature for three back muscles commonly used in ergonomics research, which are the lumbar erector spinae (LES), latissimus dorsi (LD), and thoracic erector spinae (TES). Six healthy males from a university population participated in this research. Five different MVC exercises were compared for each muscle using the Tringo wireless EMG system (Delsys Inc.). Since the LES and TES share similar functions in controlling trunk movements, their MVC exercises were the same, which included trunk extension at -60°, trunk extension at 0°, trunk extension while standing, hip extension, and the arch test. The MVC exercises identified in the literature for the LD were chest-supported shoulder extension, prone shoulder extension, lat-pull down, internal shoulder rotation, and abducted shoulder flexion. The maximum EMG signal was recorded during each MVC trial, and then the averages were computed across participants. A one-way analysis of variance (ANOVA) was utilized to determine the effect of MVC technique on muscle activity. Post-hoc analyses were performed using the Tukey test. The MVC technique effect was statistically significant for each of the muscles (p < 0.05); however, a larger sample of participants was needed to detect significant differences in the Tukey tests. The arch test was associated with the highest EMG average at the LES, and also it resulted in the maximum EMG activity more often than the other techniques (three out of six participants). For the TES, trunk extension at 0° was associated with the largest EMG average, and it resulted in the maximum EMG activity the most often (three out of six participants). For the LD, participants obtained their maximum EMG either from chest-supported shoulder extension (three out of six participants) or prone shoulder extension (three out of six participants). Chest-supported shoulder extension, however, had a larger average than prone shoulder extension (0.263 and 0.240, respectively). Although all the aforementioned techniques were superior in their averages, they did not always result in the maximum EMG activity. If an accurate estimate of the true MVC is desired, more than one technique may have to be performed. This research provides additional MVC techniques for each muscle that may elicit the maximum EMG activity.

Keywords: electromyography, maximum voluntary contraction, normalization, physical ergonomics

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Authors: Bhrugesh Radadiya, Jaydeep Shah

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In Indian foundry industry, there is a need of defect free casting with minimum production cost in short lead time. Casting defect is a very large issue in foundry shop which increases the rejection rate of casting and wastage of materials. The various parameters influences on casting process such as mold machine related parameters, green sand related parameters, cast metal related parameters, mold related parameters and shake out related parameters. The mold related parameters are most influences on casting defects in sand casting process. This paper review the casting produced by foundry with shrinkage and blow holes as a major defects was analyzed and identified that mold related parameters such as mold temperature, pouring temperature and runner size were not properly set in sand casting process. These parameters were optimized using different optimization techniques such as Taguchi method, Response surface methodology, Genetic algorithm and Teaching-learning based optimization algorithm. Finally, concluded that a Teaching-learning based optimization algorithm give better result than other optimization techniques.

Keywords: casting defects, genetic algorithm, parametric optimization, Taguchi method, TLBO algorithm

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Authors: Muhammad Saleem

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Background: The teaching of sports sciences encompasses a broad spectrum of disciplines, including biomechanics, physiology, psychology, and coaching. Effective pedagogical techniques are crucial in imparting both theoretical knowledge and practical skills necessary for students to excel in the field. The impact of these techniques on students’ learning outcomes, engagement, and professional preparedness remains a vital area of study. Objective: This study aims to evaluate the effectiveness of various pedagogical techniques used in the teaching of sports sciences. It seeks to identify which methods most significantly enhance student learning, retention, engagement, and practical application of knowledge. Methods: A mixed-methods approach was employed, including both quantitative and qualitative analyses. The study involved a comparative analysis of traditional lecture-based teaching, experiential learning, problem-based learning (PBL), and technology-enhanced learning (TEL). Data were collected through surveys, interviews, and academic performance assessments from students enrolled in sports sciences programs at multiple universities. Statistical analysis was used to evaluate academic performance, while thematic analysis was applied to qualitative data to capture student experiences and perceptions. Results: The findings indicate that experiential learning and PBL significantly improve students' understanding and retention of complex sports science concepts compared to traditional lectures. TEL was found to enhance engagement and provide students with flexible learning opportunities, but its impact on deep learning varied depending on the quality of the digital resources. Overall, a combination of experiential learning, PBL, and TEL was identified as the most effective pedagogical approach, leading to higher student satisfaction and better preparedness for real-world applications. Conclusion: The study underscores the importance of adopting diverse and student-centered pedagogical techniques in the teaching of sports sciences. While traditional lectures remain useful for foundational knowledge, integrating experiential learning, PBL, and TEL can substantially improve student outcomes. These findings suggest that educators should consider a blended approach to pedagogy to maximize the effectiveness of sports science education.

Keywords: sport sciences, pedagogical techniques, health and physical education, problem-based learning, student engagement

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Authors: Said Benkaciali, Mourad Haddadi, Abdallah Khellaf, Kacem Gairaa, Mawloud Guermoui

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In this study, many experiments were carried out to assess the influence of the input parameters on the performance of multilayer perceptron which is one the configuration of the artificial neural networks. To estimate the daily global solar radiation on the horizontal surface, we have developed some models by using seven combinations of twelve meteorological and geographical input parameters collected from a radiometric station installed at Ghardaïa city (southern of Algeria). For selecting of best combination which provides a good accuracy, six statistical formulas (or statistical indicators) have been evaluated, such as the root mean square errors, mean absolute errors, correlation coefficient, and determination coefficient. We noted that multilayer perceptron techniques have the best performance, except when the sunshine duration parameter is not included in the input variables. The maximum of determination coefficient and correlation coefficient are equal to 98.20 and 99.11%. On the other hand, some empirical models were developed to compare their performances with those of multilayer perceptron neural networks. Results obtained show that the neural networks techniques give the best performance compared to the empirical models.

Keywords: empirical models, multilayer perceptron neural network, solar radiation, statistical formulas

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Authors: Ian Omung'a

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Breast cancer remains to be one of the deadliest cancers for women worldwide, with the risk of developing tumors being as high as 50 percent in Sub-Saharan African countries like Kenya. With as many as 42 percent of these cases set to be diagnosed late when cancer has metastasized and or the prognosis has become terminal, Full Field Digital [FFD] Mammography remains an effective screening technique that leads to early detection where in most cases, successful interventions can be made to control or eliminate the tumors altogether. FFD Mammograms have been proven to multiply more effective when used together with Computer-Aided Detection and Diagnosis [CADe] systems, relying on algorithmic implementations of Deep Learning techniques in Computer Vision to carry out deep pattern recognition that is comparable to the level of a human radiologist and decipher whether specific areas of interest in the mammogram scan image portray abnormalities if any and whether these abnormalities are indicative of a benign or malignant tumor. Within this paper, we review emergent Deep Learning techniques that will prove relevant to the development of State-of-The-Art FFD Mammogram CADe systems. These techniques will span self-supervised learning for context-encoded occlusion, self-supervised learning for pre-processing and labeling automation, as well as the creation of a standardized large-scale mammography dataset as a benchmark for CADe systems' evaluation. Finally, comparisons are drawn between existing practices that pre-date these techniques and how the development of CADe systems that incorporate them will be different.

Keywords: breast cancer diagnosis, computer aided detection and diagnosis, deep learning, whole mammogram classfication, ultrasound classification, computer vision

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Authors: Mustafa Ural, Can Bayseferogulari

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In this work, radio frequency (RF) coupling between two HF antennas on a shipboard platform is minimized by determining an optimal antenna placement. Unlike the other works, the coupling is minimized not only at single frequency but over the whole frequency band of operation. Similarly, GAO and PSO, are used in order to determine optimal antenna placement. Throughout this work, outputs of two optimization techniques are compared with each other in terms of antenna placements and coupling results. At the end of the work, far-field radiation pattern performances of the antennas at their optimal places are analyzed in terms of directivity and coverage in order to see that.

Keywords: electromagnetic compatibility, antenna placement, optimization, genetic algorithm optimization, particle swarm optimization

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Authors: Praneeth Puvvula

Abstract:

Autonomy in has become increasingly common in modern automotive cars. There are 5 levels of autonomy as defined by SAE. This paper focuses on a SAE level 2 feature which, by definition, is able to control the vehicle longitudinally and laterally at the same time. The system keeps the vehicle centred with in the lane by detecting the lane boundaries while maintaining the vehicle speed. As with the features from SAE level 1 to level 3, the primary responsibility of dynamic driving task lies with the driver. This will need monitoring techniques to ensure the driver is always engaged even while the feature is active. This paper focuses on the these techniques, which would help the safe usage of the feature and provide appropriate warnings to the driver.

Keywords: autonomous driving, safety, adas, automotive technology

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Authors: Ouafa Benaida, Abdelhamid Loukil, Adda Ali Pacha

Abstract:

In recent years, the growing interest of scientists in the field of image processing and analysis of underwater images and videos has been strengthened following the emergence of new underwater exploration techniques, such as the emergence of autonomous underwater vehicles and the use of underwater image sensors facilitating the exploration of underwater mineral resources as well as the search for new species of aquatic life by biologists. Indeed, underwater images and videos have several defects and must be preprocessed before their analysis. Underwater landscapes are usually darkened due to the interaction of light with the marine environment: light is absorbed as it travels through deep waters depending on its wavelength. Additionally, light does not follow a linear direction but is scattered due to its interaction with microparticles in water, resulting in low contrast, low brightness, color distortion, and restricted visibility. The improvement of the underwater image is, therefore, more than necessary in order to facilitate its analysis. The research presented in this paper aims to implement and evaluate a set of classical techniques used in the field of improving the quality of underwater images in several color representation spaces. These methods have the particularity of being simple to implement and do not require prior knowledge of the physical model at the origin of the degradation.

Keywords: underwater image enhancement, histogram normalization, histogram equalization, contrast limited adaptive histogram equalization, single-scale retinex

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Authors: Jennifer Leach, Umashanger Thayasivam

Abstract:

The use of technology has benefited society in more ways than one ever thought possible. Unfortunately, though, as society’s knowledge of technology has advanced, so has its knowledge of ways to use technology to manipulate people. This has led to a simultaneous advancement in the world of fraud. Machine learning techniques can offer a possible solution to help decrease this advancement. This research explores how the use of various machine learning techniques can aid in detecting fraudulent activity across two different types of fraudulent data, and the accuracy, precision, recall, and F1 were recorded for each method. Each machine learning model was also tested across five different training and testing splits in order to discover which testing split and technique would lead to the most optimal results.

Keywords: data science, fraud detection, machine learning, supervised learning

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Authors: Asma Ameur, Dhafer Malouche

Abstract:

Hotel competitiveness research is an essential phase of the marketing strategy for any hotel. Certainly, knowing the hotels' competitors helps the hotelier to grasp its position in the market and the citizen to make the right choice in picking a hotel. Thus, competitiveness is an important indicator that can be influenced by various factors. In fact, the issue of competitiveness, this ability to cope with competition, remains a difficult and complex concept to define and to exploit. Therefore, the purpose of this article is to make an exploratory study to calculate a competitiveness indicator for hotels. Further on, this paper makes it possible to determine the criteria of direct or indirect effect on the image and the perception of a hotel. The actual research is used to look into the right model for hotel ‘competitiveness. For this reason, we exploit different theoretical contributions in the field of machine learning. Thus, we use some statistical techniques such as the Principal Component Analysis (PCA) to reduce the dimensions, as well as other techniques of statistical modeling. This paper presents a survey covering of the techniques and methods in hotel competitiveness research. Furthermore, this study allows us to deduct the significant variables that influence the determination of hotel’s competitors. Lastly, the discussed experiences in this article found that the hotel competitors are influenced by several factors with different rates.

Keywords: competitiveness, e-reputation, hotels' competitors, online hotel’ review, principal component analysis, statistical modeling

Procedia PDF Downloads 119