Search results for: ultra-high performance concrete

Authors: E. Fereydouni, Laleh Maleknia , M. E. Olya

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The present research, nylon fabric dyed by pressure method with nano-Si, nano-Ti particles and SiO2-TiO2 nancomposite. The influence of the amount of Si, Ti and SiO2-TiO2 on the performance of nylon fabric was investigated by the use of Fourier transform infrared spectrophotometer (FTIR), horizontal flammability apparatus (HFA), scanning electron microscope (SEM), electron dispersive X-ray spectroscope (EDX), water contact angle tester (WCA) and CIE LAB colorimetric system. The possible interactions between particles and nylon fiber were elucidated by the FTIR spectroscopy. Results indicated that the stabilized nanoparticles and nanocomposite enhances flame retardancy of nylon fabrics. Also, the prominet features of nanoparticles and nanocomposite treatment can note increase of adsorption and fixation of dye.

Keywords: nano-Si, nano- Ti, SiO2-TiO2 nancomposite, nylon fabric, flame retardant nylon

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Authors: A. M. Sagir

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The aim of this paper is to investigate the performance of the developed linear multistep block method for solving first order initial value problem of Ordinary Differential Equations (ODEs). The method calculates the numerical solution at three points simultaneously and produces three new equally spaced solution values within a block. The continuous formulations enable us to differentiate and evaluate at some selected points to obtain three discrete schemes, which were used in block form for parallel or sequential solutions of the problems. A stability analysis and efficiency of the block method are tested on ordinary differential equations involving practical applications, and the results obtained compared favorably with the exact solution. Furthermore, comparison of error analysis has been developed with the help of computer software.

Keywords: block method, first order ordinary differential equations, linear multistep, self-starting

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Authors: Abdalla Mohamed Eblabla

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Due to the high increase and demand for a wide assortment of applications that require low-cost, high-efficiency, and compact systems, RF power amplifiers are considered the most critical design blocks and power consuming components in wireless communication, TV transmission, radar, and RF heating. Therefore, much research has been carried out in order to improve the performance of power amplifiers. Classes-A, B, C, D, E, and F are the main techniques for realizing power amplifiers. An implementation of high efficiency class-F power amplifier with Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT) was realized in this paper. The simulation and optimization of the class-F power amplifier circuit model was undertaken using Agilent’s Advanced Design system (ADS). The circuit was designed using lumped elements.

Keywords: Power Amplifier (PA), gallium nitride (GaN), Agilent’s Advanced Design System (ADS), lumped elements

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Authors: Jam Harley

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The COVID-19 epidemic accelerated the speed of change in the workplace. Overnight, several individuals shifted from co-location in an office to hybrid or remote work. The pandemic also expedited and intensified the need to address persistent leadership and management concerns, including digital transformation, remote management, leading through fast change, anxiety, and uncertainty. Nonetheless, many leaders have failed to address the problems left behind by the epidemic. In a fundamental work devoted to comprehending what constitutes a human need, Maslow reiterates similar descriptors in his explanation of belongingness as the human need to be accepted, acknowledged, respected, and appreciated by a community of other individuals. This study aims to investigate the lived experiences of dispersed hybrid team members in order to find leadership best practices that improve team performance and retention through an increased individual’s sense of belonging.

Keywords: organizational change, belonging, diversity, equity

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Authors: Nnadi Ezekiel Oluwaseun Ejiofor

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This research investigates the effects of poor cost estimation, material cost variations, and payment punctuality on the financial health and execution of construction projects in Nigeria. To achieve the objectives of the study, a quantitative research approach was employed, and data was gathered through an online survey of 74 construction industry professionals consisting of quantity surveyors, contractors, and other professionals. The study surveyed input on cost estimation errors, price fluctuations, and payment delays, among other factors. The responses of the respondents were analyzed using a five-point Likert scale and the Relative Importance Index (RII). The findings demonstrated that the errors in cost estimating in the Bill of Quantity (BOQ) have a high degree of negative impact on the reputation and image of the participants in the projects. The greatest effect was experienced on the likelihood of obtaining future endeavors for contractors (mean value = 3.42), followed by the likelihood of obtaining new commissions by quantity surveyors (mean value = 3.40). The level of inaccuracy in costing that undershoots exposes them to risks was most serious in terms of easement of construction and effects of shortage of funds to pursue bankruptcy (hence fears of mean value = 3.78). There was also considerable financial damage as a result of cost underestimation, whereby contractors suffered the worst loss in profit (mean value = 3.88). Every expense comes with its own peculiar risk and uncertainty. Pressure on the cost of materials and every other expense attributed to the building and completion of a structure adds risks to the performance figures of a project. The greatest weight (mean importance score = 4.92) was attributed to issues like market inflation in building materials, while the second greatest weight (mean importance score = 4.76) was due to increased transportation charges. On the other hand, delays in payments arising from issues of the clients like poor availability of funds (RII=0.71) and contracting issues such as disagreements on the valuation of works done (RII=0.72) or other reasons were also found to lead to project delays and additional costs. The results affirm the importance of proper cost estimation on the health of organization finances and project risks and finishes within set time limits. As for the suggestions, it is proposed to progress on the methods of costing, engender better communications with the stakeholders, and manage the delays by way of contracting and financial control. This study enhances the existing literature on construction project management by suggesting ways to deal with adverse cost inaccuracies and availability of materials due to delays in payments which, if addressed, would greatly improve the economic performance of the construction business.

Keywords: cost estimation, construction project management, material price fluctuations, payment delays, financial impact

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Authors: Loai Abdallah, Malik Yousef

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A domain space for the data should reflect the actual similarity between objects. Since objects belonging to the same cluster usually share some common traits even though their geometric distance might be relatively large. In general, the Euclidean distance of data points that represented by large number of features is not capturing the actual relation between those points. In this study, we propose a new method to construct a different space that is based on clustering to form a new distance metric. The new distance space is based on ensemble clustering (EC). The EC distance space is defined by tracking the membership of the points over multiple runs of clustering algorithm metric. Over this distance, we train the decision trees classifier (DT-EC). The results obtained by applying DT-EC on 10 datasets confirm our hypotheses that embedding the EC space as a distance metric would improve the performance.

Keywords: ensemble clustering, decision trees, classification, K nearest neighbors

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Authors: Alexander Cramer, Kenneth Cramer

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Since the inauguration of President George Washington in 1789, the United States of America has seen the governance of some 44 individual presidents. Although such presidents share a variety of attributes, they still differ from one another on many others. Significantly, these traits may be used to construct distinct sets of 'families' of presidents throughout American history. By comparatively analyzing data from experts on the U.S. presidency – in this case, the C-SPAN Presidential Historians Surveys from 2000, 2009, and 2017 – this article identifies a consistent set of six presidential families: the All Stars; the Conservative Visionaries; the Postwar Progressives; the Average Joes; the Forgettables; and the Regrettables. In situating these categories in history, this article argues that U.S. presidents can be accurately organized into cohesive, like-performing families whose constituents share a common set of criteria.

Keywords: C-SPAN, POTUS presidential performance, presidential ranking, presidential studies, presidential surveys, United States

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Authors: Gilbert O. Osayemwenre, Meyer L. Edson

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Ethylene vinyl acetate (EVA) encapsulation degradation affects the performance of photovoltaic (PV) module. Hotspot formation causes the EVA encapsulation to undergo photothermal deterioration and molecular breakdown by UV radiation. This leads to diffusion of chemical particles into other layers. During outdoor deployment, the EVA encapsulation in the affect region loses its adhesive strength, when this happen the affected region layer undergoes rapid delamination. The presence of photo-thermal degradation is detrimental to PV modules as it causes both optical and thermal degradation. Also, it enables the encapsulant to be more susceptible to chemicals substance and moisture. Our findings show a high concentration of Sodium, Phosphorus and Aluminium which originate from the glass substrate, cell emitter and back contact respectively.

Keywords: ethylene vinyl acetate (EVA), encapsulation, photo-thermal degradation, thermogravimetric analysis (TGA), scanning probe microscope (SPM)

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Authors: T. Niracharapa, W. Angkana

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Since information and communication technology (ICT) plays a critical role in enhancing national competitiveness, it is a driving force for social and economic growth and prosperity. The ASEAN Economic Community (AEC) will integrate this into ASEAN countries as a new mechanism and a measure that will improve economic performance as a global economy. Government policies may support or impede such harmonization. This study was to investigate, analyze the status of Thai IT entrepreneurs and define key strategies to enhance their competitive advantage. Data were collected based on in-depth interviews, questionnaires, focus groups, seminars and fieldwork on information technology excluding communication. SWOT was used as a tool to analyze the study. The results of this study can be used to enable the government to guide policy, measures and strategies for creating a competitive advantage for Thailand’s IT entrepreneurs in the global market.

Keywords: AEC, ASEAN, competitive advantage, IT entrepreneurs

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Authors: Shilpi Tyagi, D. K. Nauriyal

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This study investigates the firm level determinants of profitability of Indian drug and pharmaceutical industry. The study uses inflation adjusted panel data for a period 2000-2013 and applies OLS regression model with Driscoll-Kraay standard errors. It has been found that export intensity, A&M intensity, firm’s market power and stronger patent regime dummy have exercised positive influence on profitability. The negative and statistically significant influence of R&D intensity and raw material import intensity points to the need for firms to adopt suitable investment strategies. The study suggests that firms are required to pay far more attention to optimize their operating expenditures, advertisement and marketing expenditures and improve their export orientation, as part of the long term strategy.

Keywords: Indian pharmaceutical industry, profits, TRIPS, performance

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Authors: El Asnaoui Khalid, Chawki Youness, Aksasse Brahim, Ouanan Mohammed

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In these recent decades, the important and fast growth in the development and demand of multimedia products is contributing to an insufficient in the bandwidth of device and network storage memory. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossless and the near-lossless compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab's SVD function. The experimental results show that the proposed algorithm has a better compression performance compared with the existing compression algorithms that use the Matlab's SVD function. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression.

Keywords: image compression, SVD, block SVD power method, lossless compression, near lossless

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Authors: R. K. Saket, K. S. Anand Kumar

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This paper presents an innovative 3-wire capacitor circuit system used to increase the efficiency and comfort improvement of permanent split-capacitor ceiling fan. In this innovative circuit, current has been reduced to save electrical power. The system could be used to replace standard single phase motor 2-wire capacitor configuration by cost effective split value X rated of optimized AC capacitors with the auxiliary winding to provide reliable ceiling fan operation and improved machine performance to save power. In basic system operations, comparisons with conventional ceiling fan are described.

Keywords: permanent split-capacitor motor, innovative 3-wire capacitor circuit system, standard 2-wire capacitor circuit system, metalized film X-rated capacitor

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Authors: Éva Pintér, Péter Bagó, Nikolett Deutsch, Miklós Hetényi

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The process of digital transformation has a profound influence on all sectors of the worldwide economy and the business environment. The influence of blockchain technology can be observed in the digital economy and e-government, rendering it an essential element of a nation's growth strategy. The banking industry is experiencing significant expansion and development of financial technology firms. Utilizing developing technologies such as artificial intelligence (AI), machine learning (ML), and big data (BD), these entrants are offering more streamlined financial solutions, promptly addressing client demands, and presenting a challenge to incumbent institutions. The advantages of digital transformation are evident in the corporate realm, and firms that resist its adoption put their survival at risk. The advent of digital technologies has revolutionized the business environment, streamlining processes and creating opportunities for enhanced communication and collaboration. Thanks to the aid of digital technologies, businesses can now swiftly and effortlessly retrieve vast quantities of information, all the while accelerating the process of creating new and improved products and services. Big data analytics is generally recognized as a transformative force in business, considered the fourth paradigm of science, and seen as the next frontier for innovation, competition, and productivity. Big data, an emerging technology that is shaping the future of the banking sector, offers numerous advantages to banks. It enables them to effectively track consumer behavior and make informed decisions, thereby enhancing their operational efficiency. Banks may embrace big data technologies to promptly and efficiently identify fraud, as well as gain insights into client preferences, which can then be leveraged to create better-tailored products and services. Moreover, the utilization of big data technology empowers banks to develop more intelligent and streamlined models for accurately recognizing and focusing on the suitable clientele with pertinent offers. There is a scarcity of research on big data analytics in the banking industry, with the majority of existing studies only examining the advantages and prospects associated with big data. Although big data technologies are crucial, there is a dearth of empirical evidence about the role of big data analytics (BDA) capabilities in bank performance. This research addresses a gap in the existing literature by introducing a model that combines the resource-based view (RBV), the technical organization environment framework (TOE), and dynamic capability theory (DC). This study investigates the influence of Big Data Analytics (BDA) utilization on the performance of market and risk management. This is supported by a comparative examination of Hungarian mobile banking services.

Keywords: big data, digital transformation, dynamic capabilities, mobile banking

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Authors: S. Hatamikia, A. Biguri, H. Furtado, G. Kronreif, J. Kettenbach, W. Birkfellner

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Nowadays, three dimensional Cone Beam CT (CBCT) has turned into a widespread clinical routine imaging modality for interventional radiology. In conventional CBCT, a circular sourcedetector trajectory is used to acquire a high number of 2D projections in order to reconstruct a 3D volume. However, the accumulated radiation dose due to the repetitive use of CBCT needed for the intraoperative procedure as well as daily pretreatment patient alignment for radiotherapy has become a concern. It is of great importance for both health care providers and patients to decrease the amount of radiation dose required for these interventional images. Thus, it is desirable to find some optimized source-detector trajectories with the reduced number of projections which could therefore lead to dose reduction. In this study we investigate some source-detector trajectories with the optimal arbitrary orientation in the way to maximize performance of the reconstructed image at particular regions of interest. To achieve this approach, we developed a box phantom consisting several small target polytetrafluoroethylene spheres at regular distances through the entire phantom. Each of these spheres serves as a target inside a particular region of interest. We use the 3D Point Spread Function (PSF) as a measure to evaluate the performance of the reconstructed image. We measured the spatial variance in terms of Full-Width-Half-Maximum (FWHM) of the local PSFs each related to a particular target. The lower value of FWHM shows the better spatial resolution of reconstruction results at the target area. One important feature of interventional radiology is that we have very well-known imaging targets as a prior knowledge of patient anatomy (e.g. preoperative CT) is usually available for interventional imaging. Therefore, we use a CT scan from the box phantom as the prior knowledge and consider that as the digital phantom in our simulations to find the optimal trajectory for a specific target. Based on the simulation phase we have the optimal trajectory which can be then applied on the device in real situation. We consider a Philips Allura FD20 Xper C-arm geometry to perform the simulations and real data acquisition. Our experimental results based on both simulation and real data show our proposed optimization scheme has the capacity to find optimized trajectories with minimal number of projections in order to localize the targets. Our results show the proposed optimized trajectories are able to localize the targets as good as a standard circular trajectory while using just 1/3 number of projections. Conclusion: We demonstrate that applying a minimal dedicated set of projections with optimized orientations is sufficient to localize targets, may minimize radiation.

Keywords: CBCT, C-arm, reconstruction, trajectory optimization

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Authors: Luis Javier Serrano Tamayo

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This research on technology makes a first approach to the selection of an amphibious landing ship with strategic capabilities, through the implementation of a multi-criteria model using Analytical Hierarchical Process (AHP), in which a significant group of alternatives of latest technology has been considered. The variables were grouped at different levels to match design and performance characteristics, which affect the lifecycle as well as the acquisition, maintenance and operational costs. The model yielded an overall measure of effectiveness and an overall measure of cost of each kind of ship that was compared each other inside the model and showed in a Pareto chart. The modeling was developed using the Expert Choice software, based on AHP method.

Keywords: analytic hierarchy process, multi-criteria decision-making, Pareto analysis, Colombian Marine Corps, projection operations, expert choice, amphibious landing ship

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Authors: Najam Aziz, Nasru Minallah, Ahmad Junaid, Kashaf Gul

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Landcover classification using automated classification techniques, while employing remotely sensed multi-spectral imagery, is one of the promising areas of research. Different land conditions at different time are captured through satellite and monitored by applying different classification algorithms in specific environment. In this paper, a SPOT-5 image provided by SUPARCO has been studied and classified in Environment for Visual Interpretation (ENVI), a tool widely used in remote sensing. Then, Artificial Neural Network (ANN) classification technique is used to detect the land cover changes in Abbottabad district. Obtained results are compared with a pixel based Distance classifier. The results show that ANN gives the better overall accuracy of 99.20% and Kappa coefficient value of 0.98 over the Mahalanobis Distance Classifier.

Keywords: landcover classification, artificial neural network, remote sensing, SPOT 5

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Authors: Naseem M. Twaissi

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Medical professionals play an important role in society, and in general, they care more about their patients than about their personal well-being. They need to take a professional approach to maintain a work-life balance. Through a collection of primary data from 1020 medical professionals and the application of relevant statistical tools, this paper explores the pressures on medical professionals with reference to their work-life balance. This study highlights how hospital management, in addition to economic reasons, needs to identify variables to enhance the work-life balance of medical professionals so that quality healthcare facilities may be provided to the citizens of Jordan. Results indicate that formulation and implementation of policies for enhancing work-life balance together with career and retention plans for medical professionals would enhance the performance of hospitals and the quality of health care in Jordan, leading to greater societal well-being.

Keywords: work life balance, job environment, job satisfaction, employee well-being, stress, hospital industry

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Authors: Juraj Camaj, Martin Kendra, Jaroslav Masek

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The paper is focused to the evaluation railway tracks in the Slovakia by using Multi-Criteria method. Evaluation of railway tracks has important impacts for the assessment of investment in technical equipment. Evaluation of railway tracks also has an important impact for the allocation of marshalling yards. Marshalling yards are in transport model as centers for the operation assigned catchment area. This model is one of the effective ways to meet the development strategy of the European Community's railways. By applying this model in practice, a transport company can guarantee a higher quality of service and then expect an increase in performance. The model is also applicable to other rail networks. This model supplements a theoretical problem of train formation problem of new ways of looking at evaluation of factors affecting the organization of wagon flows.

Keywords: railway track, multi-criteria methods, evaluation, transportation model

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Authors: Bruna Luisa Ramos Prado Vasques, Mariane Rembold Petraglia, Antonio Petraglia

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This paper investigates MIMO (Multiple-Input Multiple-Output) adaptive filtering techniques for the application of supervised source separation in the context of convolutive mixtures. From the observation that there is correlation among the signals of the different mixtures, an improvement in the NSAF (Normalized Subband Adaptive Filter) algorithm is proposed in order to accelerate its convergence rate. Simulation results with mixtures of speech signals in reverberant environments show the superior performance of the proposed algorithm with respect to the performances of the NLMS (Normalized Least-Mean-Square) and conventional NSAF, considering both the convergence speed and SIR (Signal-to-Interference Ratio) after convergence.

Keywords: adaptive filtering, multi-rate processing, normalized subband adaptive filter, source separation

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Authors: Abdenour Achour, Kan Chen, Mike Reece, Zhaorong Huang

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Here we report the synthesis of pure and cost effective of BiCuSeO by a flux method in air, and the enhancement of the thermoelectric performance by Cs doping. The comparison between our synthesis and the usual vacuum furnace method has been studied for the pristine oxyselenides BiCuSeO. We report for very high Seebeck coefficients up to 516 μV K⁻¹ at room temperature with the electrical conductivity of 5.20 S cm⁻¹ which lead to a high power factor of 140 µWm⁻¹K⁻². We also report at the high temperatures the lowest thermal conductivity value of 0.42 µWm⁻¹K⁻¹. Upon doping with Cs, enhanced electrical conductivity coupled with a moderate Seebeck coefficient lead to a power factor of 338 µWm⁻¹K⁻² at 682 K. Moreover, it shows a very low thermal conductivity in the temperature range of 300 to 682 K (0.75 to 0.35 Wm⁻¹K⁻¹). By optimizing the power factor and reducing the thermal conductivity, this results in a high ZT of ~ 0.66 at 682 K for Bi0.995Cs0.005CuSeO.

Keywords: BiCuSeO, Cs doping, thermoelectric, oxyselenide

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Authors: Christian Lauter, Corin Reuter, Shuang Wu, Thomas Troester

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Lightweight construction became more and more important over the last decades in several applications, e.g. in the automotive or aircraft sector. This is the result of economic and ecological constraints on the one hand and increasing safety and comfort requirements on the other hand. In the field of lightweight design, different approaches are used due to specific requirements towards the technical systems. The use of endless carbon fiber reinforced plastics (CFRP) offers the largest weight saving potential of sometimes more than 50% compared to conventional metal-constructions. However, there are very limited industrial applications because of the cost-intensive manufacturing of the fibers and production technologies. Other disadvantages of pure CFRP-structures affect the quality control or the damage resistance. One approach to meet these challenges is hybrid materials. This means CFRP and sheet metal are combined on a material level. Therefore, new opportunities for innovative process routes are realizable. Hybrid lightweight design results in lower costs due to an optimized material utilization and the possibility to integrate the structures in already existing production processes of automobile manufacturers. In recent and current research, the advantages of two-layered hybrid materials have been pointed out, i.e. the possibility to realize structures with tailored mechanical properties or to divide the curing cycle of the epoxy resin into two steps. Current research work at the Chair for Automotive Lightweight Design (LiA) at the Paderborn University focusses on production processes for fiber-metal-laminates. The aim of this work is the development and qualification of a large-scale production process for high-performance fiber-metal-laminates (FML) for industrial applications in the automotive or aircraft sector. Therefore, the prepreg-press-technology is used, in which pre-impregnated carbon fibers and sheet metals are formed and cured in a closed, heated mold. The investigations focus e.g. on the realization of short process chains and cycle times, on the reduction of time-consuming manual process steps, and the reduction of material costs. This paper gives an overview over the considerable steps of the production process in the beginning. Afterwards experimental results are discussed. This part concentrates on the influence of different process parameters on the mechanical properties, the laminate quality and the identification of process limits. Concluding the advantages of this technology compared to conventional FML-production-processes and other lightweight design approaches are carried out.

Keywords: composite material, fiber-metal-laminate, lightweight construction, prepreg-press-technology, large-series production

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Authors: Aleksandar Jovanovic, Katarina Kukic, Ana Uzelac, Dusan Teodorovic

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Wisdom of the Crowd (WoC) is a decentralized method that uses the collective intelligence of humans. Individual guesses may be far from the target, but when considered as a group, they converge on optimal solutions for a given problem. We will utilize WoC to address the challenge of controlling traffic lights within intersections from the streets of Kragujevac, Serbia. The problem at hand falls within the category of NP-hard problems. We will employ an algorithm that leverages the swarm intelligence of bees: Bee Colony Optimization (BCO). Data regarding traffic signal timing at a single intersection will be gathered from citizens through a survey. Results obtained in that manner will be compared to the BCO results for different traffic scenarios. We will use Vissim traffic simulation software as a tool to compare the performance of bees’ and humans’ collective intelligence.

Keywords: wisdom of the crowd, traffic signal control, combinatorial optimization, bee colony optimization

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Authors: Abbasali Abouei Mehrizi, Hao Wang, Leping Zhou

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Modification of surface wettability is one of the conventional approaches to manipulate the boiling heat transfer. Instead of direct surface modification, in the present study, the surface is decorated with free copper particles with different hydrophobicity. We used millimeter-sized copper particles with two different hydrophobicity. The surface is covered with untreated, hydrophilic, and a combination of hydrophobic and hydrophilic copper particles separately, and the heat flux and wall superheat temperature was measured experimentally and compared with the bare polished copper surface. The results show that the untreated copper particles can slightly improve the boiling heat transfer when the hydrophilic copper particles have better performance. Combining hydrophilic and hydrophobic copper particles reduces boiling heat transfer.

Keywords: boiling heat transfer, copper balls, hydrophobic, hydrophilic

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Authors: Ubu Isaiah, Gambo D.

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Haematological studies are an important diagnosis of nutritional studies. The study investigated the haematological parameters of West African Dwarf (WAD) goats fed a diet containing different levels of sodium humate. Twenty (20) WAD bucks weighing between 8.154 ± 0.340 kg were used for this study. The bucks were randomly allotted to four dietary treatments containing 0, 5, 10, and 15 g/kg diet of sodium humate laid out as a completely randomized design. Data on haematological parameters were obtained and statistically analysed using the generalized linear model (GLM) of the Statistical Package for Social Sciences (SPSS) (version 23). Results showed that sodium humate supplementation (p <0.05) has no significant effect on Neutrophils, Eosinophil, Basophils, and Monocytes, respectively. It was recommended up to 15 g/kg diet supplementation of sodium humate sufficiently enhance the performance of WAD goats as well the improving their haematological indices.

Keywords: haematological indices, goat, sodium humate

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Authors: Kheira A. Bekhechi, Belkacem Khiat

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The goal of our study is to know if there is an influence of the regular sporting physical-activity on the school performances of Algerian children. An experimental group composed of 55 sporting pupils and a reference group of 55 non-sporting pupils between 6 to10 years old (boys and girls) of the primary schools in Oran (Algeria) were followed during 15 months (Five terms). The socio-demographic data was collected from a survey given to pupils of the two groups and the school results from the administration at the end of each term. The sporting pupils have a general school average significantly higher than those of the non- sporting pupils (p < 0.05). The practice of physical activity and regular sporting by the children would deserve to be largely encouraged based on the beneficial effects not only on health but also on the academic performance. The parents, teachers and health professionals should be strongly aware.

Keywords: cognitive capacities, physical activity and sport, school children, school performances

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Authors: Habtemariam Alemu

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It has been known that the performance of position and force control is highly affected by both robot dynamic and environment stiffness uncertainties. In this paper, joint space hybrid force and position control strategy with self-selecting matrix using artificial neural network compensator is proposed. The objective of the work is to improve controller robustness by applying a neural network technique in order to compensate the effect of uncertainties in the robot model. Simulation results for a 6 degree of freedom (6-DoF) manipulator and different types of environments showed the effectiveness of the suggested approach. 6-DoF Puma 560 family robot manipulator is chosen as industrial robot and its efficient dynamic model is designed using Matlab/SimMechanics library.

Keywords: robot manipulator, force/position control, artificial neural network, Matlab/Simulink

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Authors: Adeniran Adetunji, Babalola M. Florence, Akande Ademola

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In this paper, we made an overview on the concept of adaptive e-Learning system, enumerates the elements of adaptive learning concepts e.g. A pedagogical framework, multiple learning strategies and pathways, continuous monitoring and feedback on student performance, statistical inference to reach final learning strategy that works for an individual learner by “mass-customization”. Briefly highlights the motivation of this new system proposed for effective learning teaching. E-Review literature on the concept of adaptive e-learning system and emphasises on the Item Response Calibration, which is an important approach to developing an adaptive e-Learning system. This paper write-up is concluded on the justification of item response calibration/estimation towards designing a successful and effective adaptive e-Learning system.

Keywords: adaptive e-learning system, pedagogical framework, item response, computer applications

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Authors: Sadixa Sanjel, Ahmed Sadek, Naseef Mansoor, Zelalem Denekew

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Collegiate ice hockey (NCAA) sports analytics is different from the national level hockey (NHL). We apply and compare multiple machine learning models such as Linear Regression, Random Forest, and Neural Networks to predict the win ratio for a team based on their statistics. Data exploration helps determine which statistics are most useful in increasing the win ratio, which would be beneficial to coaches and team managers. We ran experiments to select the best model and chose Random Forest as the best performing. We conclude with how to bridge the gap between the college and national levels of sports analytics and the use of machine learning to enhance team performance despite not having a lot of metrics or budget for automatic tracking.

Keywords: NCAA, NHL, sports analytics, random forest, regression, neural networks, game predictions

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Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: P. Karimi, A. H. Khedmati Bazkiaei

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The main goal of this study is to test differential neural network as a controller of smart structure and is to enumerate its advantages and disadvantages in comparison with other controllers. In this study, the smart structure has been considered as a Euler Bernoulli cantilever beam and it has been tried that it be under control with the use of vibration neural network resulting from movement. Also, a linear observer has been considered as a reference controller and has been compared its results. The considered vibration charts and the controlled state have been recounted in the final part of this text. The obtained result show that neural observer has better performance in comparison to the implemented linear observer.

Keywords: smart material, on-line differential artificial neural network, active control, finite element method

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