Search results for: performance framework

Authors: Natalia Efremova, Sergey Tarasenko

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We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

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Authors: A. El-S. Makled, M. K. Al-Tamimi

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A mathematical model to predict the performance parameters (thrusts, chamber pressures, fuel mass flow rates, mixture ratios, and regression rates during firing time) of hybrid rocket motor (HRM) is evaluated. The internal ballistic (IB) hybrid combustion model assumes that the solid fuel surface regression rate is controlled only by heat transfer (convective and radiative) from flame zone to solid fuel burning surface. A laboratory HRM is designed, manufactured, and tested for low thrust profile space missions (10-15 N) and for validating the mathematical model (computer program). The polymer material and gaseous oxidizer which are selected for this experimental work are polymethyle-methacrylate (PMMA) and polyethylene (PE) as solid fuel grain and gaseous oxygen (GO₂) as oxidizer. The variation of various operational parameters with time is determined systematically and experimentally in firing of up to 20 seconds, and an average combustion efficiency of 95% of theory is achieved, which was the goal of these experiments. The comparison between recording fire data and predicting analytical parameters shows good agreement with the error that does not exceed 4.5% during all firing time. The current mathematical (computer) code can be used as a powerful tool for HRM analytical design parameters.

Keywords: hybrid combustion, internal ballistics, hybrid rocket motor, performance parameters

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Authors: Anurag Saxena, Alkesh Agrawal, Dinesh Kumar

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The next generation mobile communication systems i.e. fourth generation (4G) was developed to accommodate the quality of service and required data rate. This project focuses on multiple access technique proposed in 4G communication systems. It is attempted to demonstrate the IDMA (Interleave Division Multiple Access) technology. The basic principle of IDMA is that interleaver is different for each user whereas CDMA employs different signatures. IDMA inherits many advantages of CDMA such as robust against fading, easy cell planning; dynamic channel sharing and IDMA increase the spectral efficiency and reduce the receiver complexity. In this, performance of IDMA is analyzed using QC-LDPC coding scheme further it is compared with LDPC coding and at last BER is calculated and plotted in MATLAB.

Keywords: 4G, QC-LDPC, CDMA, IDMA

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Authors: B.J. Khoza, B. Kembo

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Global socioeconomic developments and ever-growing technological advancements of the art and design industry indicate the pivotal importance of lifelong learning. There exists a discrepancy between competencies, personal ambition, and workplace requirements. There are few , if at all, institutions of higher learning in South Africa which offer Short Learning Programmes (SLP) in Art and Design Education. Traditionally, Art and Design education is delivered face to face via a hands-on approach. In this way the enduring perception among educators is that art and design education does not lend itself to online delivery. Short Learning programmes (SLP) are a concentrated approach to make revenue and lure potential prospective students to embark on further education study, this is often of weighted value to both students and employers. SLPs are used by Higher Education institutions to generate income in support of the core academic programmes. However, there is a gap in terms of the translation of art and design studio pedagogy into SLPs which provide quality education, are adaptable and delivered via a blended mode. In our paper, we propose a conceptual framework drawing on secondary research to analyse existing research to SLPs for arts and design education. We aim to indicate a new dimension to the process of using a design-based research approach for short learning programmes in art and design education. The study draws on a conceptual framework, a qualitative analysis through the lenses of Herrington, McKenney, Reeves and Oliver (2005) principles of the design-based research approach. The results of this study indicate that design-based research is not only an effective methodological approach for developing and deploying arts and design education curriculum for 1st years in Higher Education context but it also has the potential to guide future research. The findings of this study propose that the design-based research approach could bring theory and praxis together regarding a common purpose to design context-based solutions to educational problems.

Keywords: design education, design-based research, digital literacies, multi-literacies, short learning programme

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Authors: Maria Jose Granero Paris, Ana Isabel Jimenez Zarco, Agustin Pablo Alvarez Herranz

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In the industrial sector the collaboration along the supply chain is key especially in order to develop product, production methods or process innovations. The access to resources and knowledge not being available inside the company, the achievement of cost competitive solutions, the reduction of the time required to innovate are some of the benefits linked with the collaboration with suppliers. The big industrial manufacturers have a long tradition to collaborate with their suppliers to develop new products in the developed countries. Since they have increased their global supply chains and global sourcing activities, the objective of the research is to analyse if the same best practices, way of working, experiences, information technology tools, governance methodologies are applied when collaborating with suppliers in the developed world or in developing countries. Most of the current research focuses to analyse the Supply Chain Collaboration in the developed countries and in recent years the number of publications related to the Supply Chain Collaboration in developing countries has increased, but there is still a lack of research comparing both and analysing the similarities, differences and key success factors among the Supply Chain Collaboration practices in developed and developing countries. With this gap in mind, the research under preparation will focus on the following goals: -Identify the most important elements required for a successful supply chain collaboration in the developed and developing countries. -Set up the optimal governance framework to manage the supply chain collaboration in the developed and developing countries. -Define some recommendations about required improvements in the current supply chain collaboration business relationship practices in place. Following the case methodology we will analyze the way manufacturers and suppliers collaborate in the development of new products, production methods or process innovations and in the set up of new global supply chains in two industries with different level of technology intensity and collaboration history being the automotive and aerospace industries.

Keywords: global supply chain networks, Supply Chain Collaboration, supply chain governance, supply chain performance

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Authors: Ellis D. Cooper

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“Circularchy” is supposed to be an adjustable formal framework with enough expressive power to articulate biological theory about Earthly Life in the sense of multi-scale biological autonomy constrained by non-equilibrium thermodynamics. “Formal framework” means specifically a multi-sorted first-order-theorywithequality (for each sort). Philosophically, such a theory is one kind of “microlect,” which means a “way of speaking” (or, more generally, a “way of behaving”) for overtly expressing a “mental model” of some “referent.” Other kinds of microlect include “natural microlect,” “diagrammatic microlect,” and “behavioral microlect,” with examples such as “political theory,” “Euclidean geometry,” and “dance choreography,” respectively. These are all describable in terms of a vocabulary conforming to grammar. As aspects of human culture, they are possibly reminiscent of Ernst Cassirer’s idea of “symbolic form;” as vocabularies, they are akin to Richard Rorty’s idea of “final vocabulary” for expressing a mental model of one’s life. A formal microlect is presented by stipulating sorts, variables, calculations, predicates, and postulates. Calculations (a.k.a., “terms”) may be composed to form more complicated calculations; predicates (a.k.a., “relations”) may be logically combined to form more complicated predicates; and statements (a.k.a., “sentences”) are grammatically correct expressions which are true or false. Conclusions are statements derived using logical rules of deduction from postulates, other assumed statements, or previously derived conclusions. A circularchy is a formal microlect constituted by two or more sub-microlects, each with its distinct stipulations of sorts, variables, calculations, predicates, and postulates. Within a sub-microlect some postulates or conclusions are equations which are statements that declare equality of specified calculations. An equational bond between an equation in one sub-microlect and an equation in either the same sub-microlect or in another sub-microlect is a predicate that declares equality of symbols occurring in a side of one equation with symbols occurring in a side of the other equation. Briefly, a circularchy is a network of equational bonds between sub-microlects. A circularchy is solvable if there exist solutions for all equations that satisfy all equational bonds. If a circularchy is not solvable, then a challenge would be to discover the obstruction to solvability and then conjecture what adjustments might remove the obstruction. Adjustment means changes in stipulated ingredients (sorts, etc.) of sub-microlects, or changes in equational bonds between sub-microlects, or introduction of new sub-microlects and new equational bonds. A circularchy is modular insofar as each sub-microlect is a node in a network of equation bonds. Solvability of a circularchy may be conjectured. Efforts to prove solvability may be thwarted by a counter-example or may lead to the construction of a solution. An automated theorem-proof assistant would likely be necessary for investigating a substantial circularchy, such as one purported to represent Earthly Life. Such investigations (chains of statements) would be concurrent with and no substitute for simulations (chains of numbers).

Keywords: autonomy, first-order theory, mathematics, thermodynamics

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Authors: Eiman Kattan

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This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

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Authors: Yongjiang Zhang, Kallol Barai, Umesh R. Hodeghatta, Trang Tran, Vikas Dhiman

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Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using a handheld spectroradiometer and leaf water potential data using a pressure chamber were collected from wild blueberry plants. Machine learning techniques, including multiple regression analysis and random forest models, were employed to predict leaf water potential (MPa). We explored the optimal wavelength bands for simple differences (RY1-R Y2), simple ratios (RY1/RY2), and normalized differences (|RY1-R Y2|/ (RY1-R Y2)). NDWI ((R857 - R1241)/(R857 + R1241)), SD (R2188 – R2245), and SR (R1752 / R1756) emerged as top predictors for predicting leaf water potential, significantly contributing to the highest model performance. The base learner models achieved an R-squared value of approximately 0.81, indicating their capacity to explain 81% of the variance. Research is underway to develop a neural vegetation index (NVI) that automates the process of index development by searching for specific wavelengths in the space ratio of linear functions of reflectance. The NVI framework could work across species and predict different physiological parameters.

Keywords: hyperspectral reflectance, water potential, spectral indices, machine learning, wild blueberries, optimal bands

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Authors: Mark Archei O. Javier

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The Fourth Industrial Revolution (FIR) is a major industrial era characterized by the fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. Since this era teaches us how to thrive in the fast-paced developing world, it is important to be able to adapt. With this, there is a need to make learning and teaching in the bioscience laboratory more challenging and engaging. The goal of the research is to find out if using in silico and in vitro laboratory activities compared to the conventional conduct laboratory activities would have positive impacts on the academic performance of the learners. The potential contribution of the research is that it would improve the teachers’ methods in delivering the content to the students when it comes to topics that need laboratory activities. This study will develop a method by which teachers can provide learning materials to the students. A one-tailed t-Test for independent samples was used to determine the significant difference in the pre- and post-test scores of students. The tests of hypotheses were done at a 0.05 level of significance. Based on the results of the study, the gain scores of the experimental group are greater than the gain scores of the control group. This implies that using in silico and in vitro labs for the experimental group is more effective than the conventional method of doing laboratory activities.

Keywords: academic performance, general biology, in silico laboratory, in vivo laboratory, virtual laboratory

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Authors: Saadia Izzeldin Malik

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Lack of ethics is the crisis of the 21-century. Today’s global world is filled with economic, political, environmental, media/communication, and social crises that all generated by the eroding fabric of ethics and moral values that guide human’s decisions in all aspects of live. Our global world is guided by liberal western democratic principles and liberal capitalist economic principles that define and reinforce each other. In economic terms, capitalism has turned world economic systems into one market place of ideas and products controlled by big multinational corporations that not only determine the conditions and terms of commodity production and commodity exchange between countries, but also transform the political economy of media systems around the globe. The citizen (read the consumer) today is the target of persuasion by all types of media at a time when her/his interests should be, ethically and in principle, the basic significant factor in the selection of media content. It is very important in this juncture of clashing media values –professional and commercial- and wide spread ethical lapses of media organizations and media professionals to think of a perspective to theorize these conflicting values within a broader framework of media ethics. Thus, the aim of this paper is to, epistemologically, bring to the center a perspective on media ethics as a basis for reconciliation of clashing values of the media. The paper focuses on conflicting ethical values in current media debate; namely ownership of media vs. press freedom, individual right for privacy vs. public right to know, and global western consumerism values vs. media values. The paper concludes that a framework to reconcile conflicting values of media ethics should focus on the “individual” journalist and his/her moral development as well as focus on maintaining ethical principles of the media as an institution with a primary social responsibility for the “public” it serves.

Keywords: ethics, media, journalism, social responsibility, conflicting values, global

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Authors: A. Sohouli, A. Suleman

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This study focuses on reliability analysis of variable stiffness composite laminate structures to investigate the potential structural improvement compared to conventional (straight fibers) composite laminate structures. A computational framework was developed which it consists of a deterministic design step and reliability analysis. The optimization part is Discrete Material Optimization (DMO) and the reliability of the structure is computed by Monte Carlo Simulation (MCS) after using Stochastic Response Surface Method (SRSM). The design driver in deterministic optimization is the maximum stiffness, while optimization method concerns certain manufacturing constraints to attain industrial relevance. These manufacturing constraints are the change of orientation between adjacent patches cannot be too large and the maximum number of successive plies of a particular fiber orientation should not be too high. Variable stiffness composites may be manufactured by Automated Fiber Machines (AFP) which provides consistent quality with good production rates. However, laps and gaps are the most important challenges to steer fibers that effect on the performance of the structures. In this study, the optimal curved fiber paths at each layer of composites are designed in the first step by DMO, and then the reliability analysis is applied to investigate the sensitivity of the structure with different standard deviations compared to the straight fiber angle composites. The random variables are material properties and loads on the structures. The results show that the variable stiffness composite laminate structures are much more reliable, even for high standard deviation of material properties, than the conventional composite laminate structures. The reason is that the variable stiffness composite laminates allow tailoring stiffness and provide the possibility of adjusting stress and strain distribution favorably in the structures.

Keywords: material optimization, Monte Carlo simulation, reliability analysis, response surface method, variable stiffness composite structures

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Authors: Xiao Zhang, Wensheng Xiao, Junguo Cui, Hongmin Wang

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Submersible permanent magnet linear synchronous motors (SPMLSMs) are electromagnetic devices, which can directly drive plunger pump to obtain the crude oil. Those motors have been gradually applied in oil fields due to high thrust force density and high efficiency. Since the force performance closely depends on the concrete structural parameters, the seven different structural parameters are investigated in detail. This paper presents an optimum design of an SPMLSM to minimize the detent force and maximize the thrust by using design of experiment (DOE) and genetic algorithm (GA). The three significant structural parameters (air-gap length, slot width, pole-arc coefficient) are separately screened using 27 1/16 fractional factorial design (FFD) to investigate the significant effect of seven parameters used in this research on the force performance. Response surface methodology (RSM) is well adapted to make analytical model of thrust and detent force with constraints of corresponding significant parameters and enable objective function to be easily created, respectively. GA is performed as a searching tool to search for the Pareto-optimal solutions. By finite element analysis, the proposed PMLSM shows merits in improving thrust and reducing the detent force dramatically.

Keywords: optimization, force performance, design of experiment (DOE), genetic algorithm (GA)

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Authors: Dogan Ciloglu, Abdurrahim Bolukbasi, Harun Cifci

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In this study, the experiments were carried out to determine the best coolant for the quenching process among water-based silica, alumina, titania and copper oxide nanofluids (0.1 vol%). A sphere made up off brass material was used in the experiments. After the spherical test specimen was heated at high temperatures, it was suddenly plunged into the nanofluid suspensions. All experiments were performed at saturated conditions and under atmospheric pressure. Using the temperature-time data of the specimen, the cooling curves were obtained. The experimental results showed that the cooling performance of test specimen depended on the type of nanofluids. The silica nanoparticles enhanced the performance of boiling heat transfer and it is the best coolant for the quenching among other nanoparticles.

Keywords: quenching, nanofluid, pool boiling, heat transfer

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Authors: S. J. Yune, S. Y. Lee, S. J. Im, B. S. Kam, S. Y. Baek

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This study aimed to determine the reliability of clinical performance assessments, having been emphasized by ability-based education, and professors overall assessment methods. We addressed the following problems: First, we try to find out whether there is a difference in what we consider to be the main variables affecting the clinical performance test according to the evaluator’s working period and the number of evaluation experience. Second, we examined the relationship among the global rating score (G), analytic global rating score (Gc), and the sum of the analytical checklists (C). What are the main factors affecting clinical performance assessments in relation to the numbers of times the evaluator had administered evaluations and the length of their working period service? What is the relationship between overall assessment score and analytic checklist score? How does analytic global rating with 6 components in OSCE and 4 components in sub-domains (Gc) CPX: aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude overall assessment score and task-specific analytic checklist score sum (C) affect the professor’s overall global rating assessment score (G)? We studied 75 professors who attended a 2016 Bugyeoung Consortium clinical skills performances test evaluating third and fourth year medical students at the Pusan National University Medical school in South Korea (39 prof. in OSCE, 36 prof. in CPX; all consented to participate in our study). Each evaluator used 3 forms; a task-specific analytic checklist, subsequent analytic global rating scale with sub-6 domains, and overall global scale. After the evaluation, the professors responded to the questionnaire on the important factors of clinical performance assessment. The data were analyzed by frequency analysis, correlation analysis, and hierarchical regression analysis using SPSS 21.0. Their understanding of overall assessment was analyzed by dividing the subjects into groups based on experiences. As a result, they considered ‘precision’ most important in overall OSCE assessment, and ‘precise accuracy physical examination’, ‘systemic approaches to taking patient history’, and ‘diagnostic skill capability’ in overall CPX assessment. For OSCE, there was no clear difference of opinion about the main factors, but there was for CPX. Analytic global rating scale score, overall rating scale score, and analytic checklist score had meaningful mutual correlations. According to the regression analysis results, task-specific checklist score sum had the greatest effect on overall global rating. professors regarded task-specific analytic checklist total score sum as best reflecting overall OSCE test score, followed by aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude on a subsequent analytic global rating scale. For CPX, subsequent analytic global rating scale score, overall global rating scale score, and task-specific checklist score had meaningful mutual correlations. These findings support explanations for validity of professors’ global rating in clinical performance assessment.

Keywords: global rating, clinical performance assessment, medical education, analytic checklist

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Authors: Qiuying Li

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It is a shared opinion that sustainable development requires a system discontinuity, meaning that radical changes in the way we produce and consume are needed. Within this framework there is an emerging understanding that an important contribution to this change can be directly linked to decisions taken in the design phase of products, services and systems. Design schools have therefore to be able to provide design students with a broad knowledge and effective Design for Sustainability tools, in order to enable a new generation of designers in playing an active role in reorienting our consumption and production patterns.

Keywords: design for sustainability, services, systems, materials, ecomaterials

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Authors: Zouari Ezzeddine, Ghraieb Ikram

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From the results of the academic literature which evokes the limitations of previous studies, this article shows the reasons for multidimensionality Prediction of financial bubbles. A new framework for modeling study predicting financial bubbles by linking a set of variable presented on several dimensions dictating its multidimensional character. It takes into account the preferences of financial actors. A multicriteria anticipation of the appearance of bubbles in international financial markets helps to fight against a possible crisis.

Keywords: classical measures, predictions, financial bubbles, multidimensional, artificial neural networks

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Authors: Perry Ayi Mankattah

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Introduction: Africa, which should lead the world in honey production, is importing three times the honey it produces even though it has a healthy, industrious and large population of bees. This is due to the mechanism of honey harvesting that destroys the combs and thereby reducing honey production and rate of harvesting. For Africa to take its place in the world of honey production, Africa should adopt a method that enables a higher rate of honey harvesting. The Advance Top Bar is, therefore, a simplified framework that provides that answer. It can be made of wood, plastic and metal that can be fabricated by tin/metal smiths, wielders and carpenters at the village level without any very sophisticated machines. Material and Methods: ATB is a top bar-like hollow framework of dimension 3.2*48 cm that can be made of wood, plastic and metal. It is made up of three parts of a constant hollow top bar, a variable grooved bottom bar with both bars being joined through synchronized holes (that align both the top and bottom bars ) by either metal or plastic rods of length 22cm and diameter of 5 mm with rounded balls at both ends It could be used with foundation combs or without and also other accessories to have about ten (10) function which includes commercial propolis harvesting queen rearing etc. The variable bottom bar length depends on the width of the hive, as most African beehives are somehow not standardized. Results: Foundation combs are placed within the Advance Top Bar for the bees to form their combs over its mesh to prevent comb breakage during honey harvesting. Similarly, honeycombs on top bars will produce natural foundation combs when also placed in the Advance top bar system just as they are re-used in the Langstroth Frames. Discussions and Conclusions: Any modification that will promote non-comb destruction during honey harvesting in Top bars shall cause Africa to increase honey production by over 100% as beekeepers adopt the mechanism. Honey-laden combs from the current normal top bars could be placed in the Advance Top Bar to harvest without comb destruction; hence the same system could be used as a transition to the adoption of the Advance Top Bar with less cost.

Keywords: honey, harvest, increase, production

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Authors: Bagher Aziz Kalantari, Javad Rafiei, Mohamad Reza Talei Bavil Olyai

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Disclosed is a method of preparing a pigmentary chromium oxide nano particles having 50 percent particle size less than about 100nm. According to the disclosed method, a substantially dry solid composition of potassium dichromate and carbon active is heated in CO2 atmosphere to a temperature of about 600ºc for 1hr. Thereafter, the solid Cr2O3 product was washed twice with distilled water. The other aim of this study is to assess both the colouring performance and the potential of nano-pigments in the ceramic tile decoration. The rationable consists in nano-pigment application in several ceramics, including a comparison of colour performance with conventional micro-pigments.

Keywords: green chromium oxide, nano particles, colour performances, particle size

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Authors: Abilio Pires Zacarias

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Analyzing company boards of directors is a relevant and timely topic. As the representative of shareholders, the board is the most senior management body of this type of company. Therefore, ascertaining the best kind of candidates to nominate, namely the most appropriate characteristics for leading the board to achieve better levels of performance, is certainly of great interest. The companies selected for this study were the 1,000 largest non-financial companies and the 100 largest financial companies in Portugal according to the Instituto Nacional de Estatística for 2010. The information stemmed from a questionnaire addressed to the person in charge of daily company management and then processed through STATA 17 with the multivariate analysis of variables - MANOVA. The study may correspondingly report that the vast majority of boards in the sample operate a dual leadership structure. By in terms of its prevalence, unitary leadership represents only a minority. Agency theory and stewardship theory postulate different characteristics for the ideal chairman but neither receive confirmation from our results. On the other hand, our findings do validate the behavioral theory of firms (BToF), concluding that experience is associated with organizational performance. This study is also relevant due to its analysis of companies not listed on the financial markets not only because of their weighting in the economy but also because they remain only very poorly studied in this field and thus also correspondingly contributing to deepening the literature.

Keywords: agency theory, behavioral theory of the firm, board of directors, corporate governance, stewardship theory

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Authors: Ola I. S. El Dardery, Ismail Gomaa, Adel R.M. Rayan, Ghada El Khayat, Sara H. Sabry

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Continuous improvement activities are becoming a key factor of the success of any organization, those improvement activities include but not limited to kaizen, six sigma, lean projects, and continuous improvement projects. Kaizen is a Japanese philosophy of continuous improvement by making small incremental changes to improve an organization’s performance, reduce costs, reduce delay time, reduce waste in production, etc. This study aims at proposing a new measuring technique for kaizen activities using a Sustainable balanced scorecard structure. A survey questionnaire was developed and introduced to kaizen participants in both Egypt and Japan with the purpose of allocating key performance indicators for both kaizen process (critical success factors) and result (kaizen benefits) into the five perspectives of sustainable balanced scorecard. The study contributes to the literature by presenting a new kaizen measurement of both kaizen process and results, that will illuminate the benefits of using kaizen. Also, the presented measurement can help in the sustainability of kaizen implementation. Determining the combination of the proper kaizen measures could be used by any industry whether service or manufacturing to better measure kaizen activates. The comparison between Japanese measures, as the leaders of kaizen philosophy, and Egyptian measures will help recommending better practices of kaizen in Egypt, and contributing to the 2030 sustainable development goals.

Keywords: continuous improvements, kaizen, performance, sustainable balanced scorecard

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Authors: Dilek Saritas Atalar, Cansu Alsancak Akbulut, İrem Metin Orta, Feyza Yön, Zeynep Yenen, Joan Grusec

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Objective: The aim of this study was to develop semi-structured Domains of Socialization Interview and its coding manual and to test their psychometric properties. Domains of Socialization Interview was designed to assess maternal awareness regarding effective parenting in five socialization domains (protection, mutual reciprocity, control, guided learning, and group participation) within the framework of the domains-of-socialization approach. Method: A series of two studies were conducted to develop and validate the interview and its coding manual. The pilot study, sampled 13 mothers of preschool-aged children, was conducted to develop the assessment tools and to test their function and clarity. Participants of the main study were 82 Turkish mothers (Xage = 34.25, SD = 3.53) who have children aged between 35-76 months (Xage = 50.75, SD = 11.24). Mothers filled in a questionnaire package including Coping with Children’s Negative Emotions Questionnaire, Social Competence and Behavior Evaluation-30, Child Rearing Questionnaire, and Two Dimensional Social Desirability Questionnaire. Afterward, interviews were conducted online by a single interviewer. Interviews were rated independently by two graduate students based on the coding manual. Results: The relationships of the awareness of effective parenting scores to the other measures demonstrate convergent, discriminant, and predictive validity of the coding manual. Intra-class correlation coefficient estimates were ranged between 0.82 and 0.90, showing high interrater reliability of the coding manual. Conclusion: Taken as a whole, the results of these studies demonstrate the validity and reliability of a new and useful interview to measure maternal awareness regarding effective parenting within the framework of the domains-of-socialization approach.

Keywords: domains of socialization, parenting, interview, assessment

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: biomarker discovery, cancer, feature selection, mass spectrometry

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Authors: Wangxu Xia

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BACKGROUND BI-RADS 4 lesions raise the possibility of malignancy that warrant further clinical and radiologic work-up. This study aimed to evaluate the predictive performance of diffusion-weighted imaging(DWI) and microcalcifications on mammography for predicting malignancy of BI-RADS 4 lesions. In addition, the predictive performance of DWI combined with microcalcifications was alsocompared with the Kaiser score. METHODS During January 2021 and June 2023, 144 patients with 178 BI-RADS 4 lesions underwent conventional MRI, DWI, and mammography were included. The lesions were dichotomized intobenign or malignant according to the pathological results from core needle biopsy or surgical mastectomy. DWI was performed with a b value of 0 and 800s/mm2 and analyzed using theapparent diffusion coefficient, and a Kaiser score > 4 was considered to suggest malignancy. Thediagnostic performances for various diagnostic tests were evaluated with the receiver-operatingcharacteristic (ROC) curve. RESULTS The area under the curve (AUC) for DWI was significantly higher than that of the of mammography (0.86 vs 0.71, P<0.001), but was comparable with that of the Kaiser score (0.86 vs 0.84, P=0.58). However, the AUC for DWI combined with mammography was significantly highthan that of the Kaiser score (0.93 vs 0.84, P=0.007). The sensitivity for discriminating malignant from benign BI-RADS 4 lesions was highest at 89% for Kaiser score, but the highest specificity of 83% can be achieved with DWI combined with mammography. CONCLUSION DWI combined with microcalcifications on mammography could discriminate malignant BI-RADS4 lesions from benign ones with a high AUC and specificity. However, Kaiser score had a better sensitivity for discrimination.

Keywords: MRI, DWI, mammography, breast disease

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Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

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In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Manal Bouasria, Mohammed-Hichem Benzaama, Valérie Pralong, Yassine El Mendili

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Reducing the quantity of cement in cementitious composites can help to reduce the environmental effect of construction materials. By-products such as ferronickel slags (FNS), fly ash (FA), and Crepidula fornicata (CR) are promising options for cement replacement. In this work, we investigated the relevance of substituting cement with FNS-CR and FA-CR on the mechanical properties of mortar and on the thermal properties of concrete. Foraging intervals ranging from 2 to 28 days, the mechanical properties are obtained by 3-point bending and compression tests. The chosen mix is used to construct a prototype in order to study the material’s hygrothermal performance. The data collected by the sensors placed on the prototype was utilized to build an artificial neural network.

Keywords: artificial neural network, cement, circular economy, concrete, by products

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Authors: Enrique Claver Cortés, Bartolomé Marco Lajara, Eduardo Sánchez García, Pedro Seva Larrosa, Encarnación Manresa Marhuenda, Lorena Ruiz Fernández, Esther Poveda Pareja

Abstract:

In recent decades, the analysis of the effects of clustering as an essential factor for the development of innovations and the competitiveness of enterprises has raised great interest in different areas. Nowadays, companies have access to almost all tangible and intangible resources located and/or developed in any country in the world. However, despite the obvious advantages that this situation entails for companies, their geographical location has shown itself, increasingly clearly, to be a fundamental factor that positively influences their innovative performance and competitiveness. Industrial clusters could represent a unique level of analysis, positioned between the individual company and the industry, which makes them an ideal unit of analysis to determine the effects derived from company membership of a cluster. Also, the absorptive capacity (hereinafter 'AC') can mediate the process of innovation development by companies located in a cluster. The transformation and exploitation of knowledge could have a mediating effect between knowledge acquisition and innovative performance. The main objective of this work is to determine the key factors that affect the degree of generation and use of knowledge from the environment by companies and, consequently, their innovative performance and competitiveness. The elements analyzed are the companies' membership of a cluster and the AC. To this end, 30 most relevant papers published on this subject in the "Web of Science" database have been reviewed. Our findings show that, within a cluster, the knowledge coming from the companies' environment can significantly influence their innovative performance and competitiveness, although in this relationship, the degree of access and exploitation of the companies to this knowledge plays a fundamental role, which depends on a series of elements both internal and external to the company.

Keywords: absorptive capacity, clusters, innovation, knowledge

Procedia PDF Downloads 114

Authors: M. Bolacali

Abstract:

The aim of the study is to determine the effect of immunocastration vaccine administration at different doses on fattening performance of feedlot Holstein bulls. Bopriva® is a vaccine that stimulates the animals' own immune system to produce specific antibodies against gonadotropin releasing factor (GnRF). Ninety four Holstein male calves (309.5 ± 2.58 kg body live weight and 267 d-old) assigned to the 4 treatments. Control group; 1 mL of 0.9% saline solution was subcutaneously injected to intact bulls on 1st and 60th days of the feedlot as placebo. On the same days of the feedlot, Bopriva® at two doses of 1 mL and 1 mL for Trial-1 group, 1.5 mL, and 1.5 mL for Trial-2 group, 1.5 mL, and 1 mL for Trial-3 group were subcutaneously injected to bulls. The study was conducted in a private establishment in the Sirvan district of Siirt province and lasted 180 days. The animals were weighed at the beginning of fattening and at 30-day intervals to determine their live weights at various periods. The statistical analysis for normal distribution data of the treatment groups was carried out with the general linear model procedure of SPSS software. The fattening initial live weight in Control, Trial-1, Trial-2 and Trial-3 groups was respectively 309.21, 306.62, 312.11, and 315.39 kg. The fattening final live weight was respectively 560.88, 536.67, 548.56, and 548.25 kg. The daily live weight gain during the trial was respectively 1.40, 1.28, 1.31, and 1.29 kg/day. The cold carcass yield was respectively 51.59%, 50.32%, 50.85%, and 50.77%. Immunocastration vaccine administration at different doses did not affect the live weights and cold carcass yields of Holstein male calves reared under intensive conditions (P > 0.05). However, it was determined to reduce fattening performance between 61-120 days (P < 0.05) and 1-180 days (P < 0.01). In addition, it was determined that the best performance among the vaccine-treated groups occurred in the group administered a 1.5 mL of vaccine on the 1st and 60th study days. In animals, castration is used to control fertility, aggressive and sexual behaviors. As a result, the fact that stress is induced by physical castration in animals and active immunization against GnRF maintains performance by maximizing welfare in bulls improves carcass and meat quality and controls unwanted sexual and aggressive behavior. Considering such features, it may be suggested that immunocastration vaccine with Bopriva® can be administered as a 1.5 mL dose on the 1st and 60th days of the fattening period in Holstein bulls.

Keywords: anti-GnRF, fattening, growth, immunocastration

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Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

Abstract:

Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

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Authors: Thanapat Chaireongsirikul, Apichit Svang-Ariyaskul

Abstract:

An analysis of mass balance, energy performance, and environmental impact assessment were performed to evaluate bioethanol production in Thailand. Thailand is an agricultural country. Thai government plans to increase the use of alternative energy to 20 percent by 2022. One of the primary campaigns is to promote a bioethanol production from abundant biomass resources such as bitter cassava, molasses and sugarcane. The bioethanol production is composed of three stages: cultivation, pretreatment, and bioethanol conversion. All of mass, material, fuel, and energy were calculated to determine the environmental impact of three types of bioethanol production: bioethanol production from cassava (CBP), bioethanol production from molasses (MBP), and bioethanol production from rice straw (RBP). The results showed that bioethanol production from cassava has the best environmental performance. CBP contributes less impact when compared to the other processes.

Keywords: bioethanol production, biofuel, LCA, chemical engineering

Procedia PDF Downloads 349

Authors: Elisa Y. M. Ang, Teng Yong Ng, Jingjie Yeo, Rongming Lin, Zishun Liu, K. R. Geethalakshmi

Abstract:

By stacking carbon nanotubes (CNT) one on top of another, single layer CNT arrays can perform water-salt separation with ultra-high permeability and selectivity. Such outer-wall CNT slit membrane is named as the transverse flow CNT membrane. By adjusting the slit size between neighboring CNTs, the membrane can be configured to sieve out different solutes, right down to the separation of monovalent salt ions from water. Molecular dynamics (MD) simulation results show that the permeability of transverse flow CNT membrane is more than two times that of conventional axial-flow CNT membranes, and orders of magnitude higher than current reverse osmosis membrane. In addition, by carrying out MD simulations with different CNT size, it was observed that the variance in desalination performance with CNT size is small. This insensitivity of the transverse flow CNT membrane’s performance to CNT size is a distinct advantage over axial flow CNT membrane designs. Not only does the membrane operate well under constant pressure desalination operation, but MD simulations further indicate that oscillatory operation can further enhance the membrane’s desalination performance, making it suitable for operation such as electrodialysis reversal. While there are still challenges that need to be overcome, particularly on the physical fabrication of such membrane, it is hope that this versatile membrane design can bring the idea of using low dimensional structures for desalination closer to reality.

Keywords: carbon nanotubes, membrane desalination, transverse flow carbon nanotube membrane, molecular dynamics

Procedia PDF Downloads 178