Search results for: pedestrian target selection

Authors: Roberta Martino, Viviana Ventre

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Intertemporal choices are choices under conditions of uncertainty in which the consequences are distributed over time. The Discounted Utility Model is the essential reference for describing the individual in the context of intertemporal choice. The model is based on the idea that the individual selects the alternative with the highest utility, which is calculated by multiplying the cardinal utility of the outcome, as if the reception were instantaneous, by the discount function that determines a decrease in the utility value according to how the actual reception of the outcome is far away from the moment the choice is made. Initially, the discount function was assumed to have an exponential trend, whose decrease over time is constant, in line with a profile of a rational investor described by classical economics. Instead, empirical evidence called for the formulation of alternative, hyperbolic models that better represented the actual actions of the investor. Attitudes that do not comply with the principles of classical rationality are termed anomalous, i.e., difficult to rationalize and describe through normative models. The development of behavioral finance, which describes investor behavior through cognitive psychology, has shown that deviations from rationality are due to the limited rationality condition of human beings. What this means is that when a choice is made in a very difficult and information-rich environment, the brain does a compromise job between the cognitive effort required and the selection of an alternative. Moreover, the evaluation and selection phase of the alternative, the collection and processing of information, are dynamics conditioned by systematic distortions of the decision-making process that are the behavioral biases involving the individual's emotional and cognitive system. In this paper we present an original decomposition of the discount function to investigate the psychological principles of hyperbolic discounting. It is possible to decompose the curve into two components: the first component is responsible for the smaller decrease in the outcome as time increases and is related to the individual's impatience; the second component relates to the change in the direction of the tangent vector to the curve and indicates how much the individual perceives the indeterminacy of the future indicating his or her aversion to uncertainty. This decomposition allows interesting conclusions to be drawn with respect to the concept of impatience and the emotional drives involved in decision-making. The contribution that neuroscience can make to decision theory and inter-temporal choice theory is vast as it would allow the description of the decision-making process as the relationship between the individual's emotional and cognitive factors. Neurofinance is a discipline that uses a multidisciplinary approach to investigate how the brain influences decision-making. Indeed, considering that the decision-making process is linked to the activity of the prefrontal cortex and amygdala, neurofinance can help determine the extent to which abnormal attitudes respect the principles of rationality.

Keywords: impatience, intertemporal choice, neurofinance, rationality, uncertainty

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Authors: L. Pigon, S. Kot, J. K. Grabara

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Nowadays, with organizations facing the challenges of increasing competitiveness, human capital accumulated by the organization is one of the elements that strongly differentiate between companies. Efficient management in the competition area requires to manage the competencies of their employees to be suitable to the market fluctuations. The aim of the paper was to determine how employee training to improve their competencies is verified. The survey was conducted among 37 respondents involved in selection of training providers and training programs in their enterprises. The results showed that all organizations use training survey as a basic method for evaluation of training effectiveness. Depending on the training contents and organization, the questionnaires contain various questions. Most of these surveys are composed of the three basic blocks: the trainer's assessment, the evaluation of the training contents, the assessment of the materials and the place of the organisation. None of the organization surveys conducted regular job-related observations or examined the attitudes of the training participants.

Keywords: human capital, competencies, training effectiveness, sale department

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez, Mehdi Mrad

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We investigate the large scale of networks in the context of network survivability under attack. We use appropriate techniques to evaluate and the attacker-based- and the defender-based-network survivability. The attacker is unaware of the operated links by the defender. Each attacked link has some pre-specified probability to be disconnected. The defender choice is so that to maximize the chance of successfully sending the flow to the destination node. The attacker however will select the cut-set with the highest chance to be disabled in order to partition the network. Moreover, we extend the problem to the case of selecting the best p paths to operate by the defender and the best k cut-sets to target by the attacker, for arbitrary integers p,k > 1. We investigate some variations of the problem and suggest polynomial-time solutions.

Keywords: defense/attack strategies, large scale, networks, partitioning a network

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Authors: Shahram Nanekarani, Majid Goodarzi, Majid Khosravi

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The present study aimed at analyzing of ovine major histocompatibility complex class II (Ovar II) DRB1 gene second exon in Lori Sheep breed. The MHC plays a central role in the control of disease resistance and immunological response. Genomic DNA from blood samples of 124 sheep was extracted and a 296 bp MHC exon 2 fragment was amplified using polymerase chain reaction. PCR products were characterized by the restriction fragment length polymorphism technique using Hin1I restriction enzyme. The PCRRFLP patterns showed three genotypes, AA, AB and BB with frequency of 0.282, 0.573 and 0.145, respectively. There was no significant (P > 0.05) deviation from Hardy–Weinberg equilibrium for this locus in this population. The results of the present study indicate that exon 2 of the Ovar-DRB1 gene is highly polymorphic in Lori sheep and could be considered as an important marker assisted selection, for improvement of immunity in sheep.

Keywords: MHC-DRB1 gene, polymorphism, PCR-RFLP, lori sheep

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Authors: Sobia Rana

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The study intends to explain the problems of English collocational use faced by college students in Rawalpindi, Pakistan and recommends some authentic ways that will help in removing the learning barriers in light of the concerning methodological issues. It will not only help the students to improve their knowledge of the phenomena but will also enlighten the target teachers about the significance of authentic collocational use and how it naturalizes both written and spoken expressions. Data from both the students and teachers have been collected with the help of open/close-ended questionnaires to unearth the genuine cause/s and supplement them with the required solutions rooted in the actual problems. The students fail to use authentic collocations owing to multiple reasons: lack of awareness about English collocational use, improper teaching methodologies, and inexpert teachers.

Keywords: English collocational use, teaching methodologies, English learning barriers, vocabulary acquisition, college students of Rawalpindi

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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This study considers the selection of the most suitable in silico molecular descriptors that could be used for s-triazine pesticides characterization. Suitable descriptors among topological, geometrical and physicochemical are used for quantitative structure-retention relationships (QSRR) model establishment. Established models were obtained using linear regression (LR) and multiple linear regression (MLR) analysis. In this paper, MLR models were established avoiding multicollinearity among the selected molecular descriptors. Statistical quality of established models was evaluated by standard and cross-validation statistical parameters. For detection of similarity or dissimilarity among investigated s-triazine pesticides and their classification, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used and gave similar grouping. This study is financially supported by COST action TD1305.

Keywords: chemometrics, classification analysis, molecular descriptors, pesticides, regression analysis

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Authors: Thomas Q. Pan, Anika Basu, Chamith S. Rajapakse

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Machine learning requires data that is categorized into features that models train on. This topic is important to the field of sports medicine due to the many tools it provides to physicians such as diagnosis support and risk assessment. Physician note that healthcare professionals take are usually unclean and not suitable for model training. The objective of this study was to develop and evaluate an advanced approach for extracting key features from sports medicine data without the need for extensive model training or data labeling. An LLM (Large Language Model) was given a narrative (Physician’s Notes) and prompted to extract four features (details about the patient). The narrative was found in a datasheet that contained six columns: Case Number, Validation Age, Validation Gender, Validation Diagnosis, Validation Body Part, and Narrative. The validation columns represent the accurate responses that the LLM attempts to output. With the given narrative, the LLM would output its response and extract the age, gender, diagnosis, and injured body part with each category taking up one line. The output would then be cleaned, matched, and added to new columns containing the extracted responses. Five ways of checking the accuracy were used: unclear count, substring comparison, LLM comparison, LLM re-check, and hand-evaluation. The unclear count essentially represented the extractions the LLM missed. This can be also understood as the recall score ([total - false negatives] over total). The rest of these correspond to the precision score ([total - false positives] over total). Substring comparison evaluated the validation (X) and extracted (Y) columns’ likeness by checking if X’s results were a substring of Y's findings and vice versa. LLM comparison directly asked an LLM if the X and Y’s results were similar. LLM Re-check prompted the LLM to see if the extracted results can be found in the narrative. Lastly, A selection of 1,000 random narratives was also selected and hand-evaluated to give an estimate of how well the LLM-based feature extraction model performed. With a selection of 10,000 narratives, the LLM-based approach had a recall score of roughly 98%. However, the precision scores of the substring comparison and LLM comparison models were around 72% and 76% respectively. The reason for these low figures is due to the minute differences between answers. For example, the ‘chest’ is a part of the ‘upper trunk’ however, these models cannot detect that. On the other hand, the LLM re-check and subset of hand-tested narratives showed a precision score of 96% and 95%. If this subset is used to extrapolate the possible outcome of the whole 10,000 narratives, the LLM-based approach would be strong in both precision and recall. These results indicated that an LLM-based feature extraction model could be a useful way for medical data in sports to be collected and analyzed by machine learning models. Wide use of this method could potentially increase the availability of data thus improving machine learning algorithms and supporting doctors with more enhanced tools.

Keywords: AI, LLM, ML, sports

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Authors: Gülşah Çelik Gül, Figen Kurtuluş

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Magnesium containing boron compounds with hexagonal structure have been drawn much attention due to their superconductive nature. The main target of this work is new modified microwave oven by on our own has an ability about passing through a gas in the oven medium for attainment of oxygen-free compounds such as c-BN.  Mg containing boride was synthesized by modified-microwave method under nitrogen atmosphere using amorphous boron and magnesium source in appropriate molar ratio. Microwave oven with oxygen free environment has been modified to aimed to obtain magnesium boride without oxygen. Characterizations were done by powder X-ray diffraction (XRD), and Fourier transform infrared (FTIR) spectroscopy. Mg containing boride, generally named magnesium boride, with amorphous character without oxygen is obtained via designed microwave oven system.

Keywords: magnesium containing boron compounds, modified microwave synthesis, powder X-ray diffraction, FTIR

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Authors: Dora Martins, Susana Silva, Cândida Silva

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Human Resources Management (HRM) has been recognized by academics and practitioners as an important element in organizations. Therefore, this paper explores the best practices of HRM and seeks to understand the level of participation in the development of these practices by human resources managers in the hospitality industry and compare it with other industries. Thus, the study compared the HRM practices of companies in the hospitality sector with HRM practices of companies in other sectors, and identifies the main differences between their HRM practices. The results show that the most frequent HRM practices in all companies, independently of its sector of activity, are hiring and training. When comparing hospitality sector with other sectors of activity, some differences were noticed, namely in the adoption of the practices of communication and information sharing, and of recruitment and selection. According to these results, the paper discusses the major theoretical and practical implications. Suggestions for future research are also presented.

Keywords: exploratory study, human resources management practices, human resources manager, hospitality companies, Portuguese companies

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Authors: Yasser Abo El-Magd, Wael Fawzy Mohamed

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Due to the great development in construction and building field, there are many projects and huge works appeared which consume many construction materials. Accordingly, that causes difficulty in handling traditional transportation means (ordinary cranes) due to their limited capacity; there is an urgent need to use high capacity cranes such as tower cranes. However, with regard to their high expense, we have to take into consideration selecting what type of cranes to be utilized which has been discussed by many researchers. In this research, a proposed technique was created to select the suitable type of crane and the best place for crane erection, in addition to minimum radius for requested crane in order to minimize cost. To fulfill that target, a computer program is designed to numerate these problems, demonstrating an example explaining how to apply program and the result donated the best place.

Keywords: tower crane, jib length, operating time, location, feasible area

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Authors: Seyed-Ali Sadegh-Zadeh, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Saeed Shiry Ghidary, Amir M. Hajiyavand

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Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications.

Keywords: evaluation metrics, performance measurement, supervised learning, unsupervised learning, reinforcement learning, model robustness and stability, comparative analysis

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Authors: P. Halder, A. Zaman

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It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

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Authors: Hamed Saremi

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One of the challenges in manufacturing and service companies to provide a product or service is recognized Brand to consumers in target markets. They provide most of their processes under the same capacity. But the constant threat of devastating internal and external resources to prevent a rise Brands and more companies are recognizing the stages are bankrupt. This paper has tried to identify and analyze effective indicators of brand equity and focuses on indicators and presents a model of intelligent create a model to prevent possible damage. In this study identified indicators of brand equity based on literature study and according to expert opinions, set of indicators By techniques DEMATEL Then to used Multi-Step Adaptive Neural-Fuzzy Inference system (ANFIS) to design a multi-stage intelligent system for assessment of brand equity.

Keywords: anfis, dematel, brand, cosmetic product, brand value

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Authors: E. Botchway, C. Godfrey, V. Anderson, C. Catroppa

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Introduction: Sleep disturbances are common after childhood traumatic brain injury (TBI). This systematic review aimed to assess the prevalence, types, and predictors of sleep disturbances in childhood TBI. Methods: Medline, Pubmed, PsychInfo, Web of Science, and EMBASE databases were searched. Out of the 547 articles assessed, 15 met selection criteria for this review. Results: Sleep disturbances were common in children and adolescents with TBI, irrespective of injury severity. Excessive daytime sleepiness and insomnia were the most common sleep disturbances reported. Sleep disturbance was predicted by sex, injury severity, pre-existing sleep disturbances, younger age, pain, and high body mass index. Conclusions: Sleep disturbances are highly prevalent in childhood TBI, regardless of the injury severity. Routine assessment of sleep in survivors of childhood TBI is recommended.

Keywords: traumatic brain injury, sleep diatiurbances, childhood, systematic review

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Authors: Mohamed Barbary, Mohamed H. Abd El-Azeem

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Maneuvering extended object tracking (M-EOT) using high-resolution inverse synthetic aperture radar (ISAR) observations has been gaining momentum recently. This work presents a new robust implementation of the multiple models (MM) multi-Bernoulli (MB) filter for M-EOT, where the M-EOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, MM-MB-TBD filter

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Authors: Naim Karasekreter, Ugur Fidan, Fatih Basciftci

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Wireless sensor networks are networks in which more than one sensor node is organized among themselves. The working principle is based on the transfer of the sensed data over the other nodes in the network to the central station. Wireless sensor networks concentrate on routing algorithms, energy efficiency and clustering algorithms. In the clustering method, the nodes in the network are divided into clusters using different parameters and the most suitable cluster head is selected from among them. The data to be sent to the center is sent per cluster, and the cluster head is transmitted to the center. With this method, the network traffic is reduced and the energy efficiency of the nodes is increased. In this study, clustering algorithms were examined in terms of clustering performances and cluster head selection characteristics to try to identify weak and strong sides. This work is supported by the Project 17.Kariyer.123 of Afyon Kocatepe University BAP Commission.

Keywords: wireless sensor networks (WSN), clustering algorithm, cluster head, clustering

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Authors: Kajingulu Malandala, Ranganai Edmore

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The asymmetric Laplace distribution (ADL) is commonly used as the likelihood function of the Bayesian quantile regression, and it offers different families of likelihood method for quantile regression. Notwithstanding their popularity and practicality, ADL is not smooth and thus making it difficult to maximize its likelihood. Furthermore, Bayesian inference is time consuming and the selection of likelihood may mislead the inference, as the Bayes theorem does not automatically establish the posterior inference. Furthermore, ADL does not account for greater skewness and Kurtosis. This paper develops a new aspect of quantile regression approach for count data based on inverse of the cumulative density function of the Poisson, binomial and Delaporte distributions using the integrated nested Laplace Approximations. Our result validates the benefit of using the integrated nested Laplace Approximations and support the approach for count data.

Keywords: quantile regression, Delaporte distribution, count data, integrated nested Laplace approximation

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Authors: Xia Chen, Hua-Quan Yang, Shi-Hua Zhou

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Alkali-active sandstone aggregate was ground by vertical and ball mill into particles with residue over 45 μm less than 12%, and investigations have been launched on particles distribution and characterization of ground sandstone powder, fluidity, heat of hydration, strength as well as hydration products morphology of pastes with incorporation of ground sandstone powder. Results indicated that ground alkali-active sandstone powder with residue over 45 μm less than 8% was easily obtainable, and specific surface area was more sensitive to characterize its fineness with extension of grinding length. Incorporation of sandstone powder resulted in higher water demand and lower strength, advanced hydration of C₃A and C₂S within 3days and refined pore structure. Based on its manufacturing, characteristics and influence on properties of pastes, it was concluded that sandstone powder was a good selection for use in concrete as mineral admixture.

Keywords: concrete, mineral admixture, hydration, structure

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Authors: Ben Levenger

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Social life revolves around a central meeting place or gathering space. It is where the community integrates, earns social skills, and ultimately becomes part of the community. Following this premise, public spaces are one of the most important spaces that downtowns offer, providing locations for people to be witnessed, heard, and most importantly, seamlessly integrate into the downtown as part of the community. To facilitate this, these local spaces must be envisioned and designed to meet the changing needs of a downtown, offering a space and purpose for everyone. This paper will dive deep into analyzing, designing, and implementing public space design for small plazas or gathering spaces. These spaces often require a detailed level of study, followed by a broad stroke of design implementation, allowing for adaptability. This paper will highlight how to assess needs, define needed types of spaces, outline a program for spaces, detail elements of design to meet the needs, assess your new space, and plan for change. This study will provide participants with the necessary framework for conducting a grass-roots-level assessment of public space and programming, including short-term and long-term improvements. Participants will also receive assessment tools, sheets, and visual representation diagrams. Urbanism, for the sake of urbanism, is an exercise in aesthetic beauty. An economic improvement or benefit must be attained to solidify these efforts' purpose further and justify the infrastructure or construction costs. We will deep dive into case studies highlighting economic impacts to ground this work in quantitative impacts. These case studies will highlight the financial impact on an area, measuring the following metrics: rental rates (per sq meter), tax revenue generation (sales and property), foot traffic generation, increased property valuations, currency expenditure by tenure, clustered development improvements, cost/valuation benefits of increased density in housing. The economic impact results will be targeted by community size, measuring in three tiers: Sub 10,000 in population, 10,001 to 75,000 in population, and 75,000+ in population. Through this classification breakdown, the participants can gauge the impact in communities similar to their work or for which they are responsible. Finally, a detailed analysis of specific urbanism enhancements, such as plazas, on-street dining, pedestrian malls, etc., will be discussed. Metrics that document the economic impact of each enhancement will be presented, aiding in the prioritization of improvements for each community. All materials, documents, and information will be available to participants via Google Drive. They are welcome to download the data and use it for their purposes.

Keywords: downtown, economic development, planning, strategic

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Authors: Mehdi Brahimi, Kamal Medjaher, Noureddine Zerhouni, Mohammed Leouatni

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The Prognostics and Health Management is a system engineering discipline which provides solutions and models to the implantation of a predictive maintenance. The approach is based on extracting useful information from monitoring data to assess the “health” state of an industrial equipment or an asset. In this paper, we examine multiple extracted features from Pantograph-Catenary contact force in order to select the most relevant ones to achieve a diagnostics function. The feature extraction methodology is based on simulation data generated thanks to a Pantograph-Catenary simulation software called INPAC and measurement data. The feature extraction method is based on both statistical and signal processing analyses. The feature selection method is based on statistical criteria.

Keywords: catenary/pantograph interaction, diagnostics, Prognostics and Health Management (PHM), quality of current collection

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Authors: Changgil Lee, Junkyeong Kim, Jihwan Park, Seunghee Park

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In this study, bridge weigh-in-motion (BWIM) system was simulated under various environmental conditions such as temperature, humidity, wind and so on to improve the performance of the BWIM system. The environmental conditions can make difficult to analyze measured data and hence those factors should be compensated. Various conditions were considered as input parameters for ANN (Artificial Neural Network). The number of hidden layers for ANN was decided so that nonlinearity could be sufficiently reflected in the BWIM results. The weight of vehicles and axle weight were more accurately estimated by applying ANN approach. Additionally, the type of bridge which was a target structure was considered as an input parameter for the ANN.

Keywords: bridge weigh-in-motion (BWIM) system, environmental conditions, artificial neural network, type of bridges

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Authors: Dení Stincer Gómez, Zuraya Monroy Nasr

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Pedagogy of science historically has given priority to teaching strategies that mobilize the cognitive mechanisms leaving out emotional. Modern epistemology, cognitive psychology and psychoanalysis begin to argue and prove that emotions are relevant epistemological functions. They are 1) the selection function: that allows the perception and reason choose, to multiple alternative explanation of a particular fact, those are relevant and discard those that are not, 2) heuristic function: that is related to the activation cognitive processes that are effective in the process of knowing; and 3) the function that called carrier content: on the latter it arises that emotions give the material reasoning that later transformed into linguistic propositions. According to these hypotheses, scientific knowledge seems to come from emotions that meet these functions. In this paper I argue that science education should start from the presence of certain emotions in the learner if it is to form citizens with scientific or cultural future scientists.

Keywords: epistemic emotions, science education, formation of citizens and scientists., philosophy of emotions

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Authors: Amir Azaron

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In this research, a stochastic programming approach is developed for designing supply chains with uncertain parameters. Demands and selling prices of products at markets are considered as the uncertain parameters. The proposed mathematical model will be multi-period two-stage stochastic programming, which takes into account the selection of retailer sites, suppliers, production levels, inventory levels, transportation modes to be used for shipping goods, and shipping quantities among the entities of the supply chain network. The objective function is to maximize the chain’s net present value. In order to maximize the chain’s NPV, the sum of first-stage investment costs on retailers, and the expected second-stage processing, inventory-holding and transportation costs should be kept as low as possible over multiple periods. The effects of supply uncertainty where suppliers are unreliable will also be investigated on the efficiency of the supply chain.

Keywords: supply chain management, stochastic programming, multiobjective programming, inventory control

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Authors: K. Raghuwaiya, S. Singh, B. Sharma, J. Vanualailai

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This paper presents a set of artificial potential field functions that improves upon; in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of 3-trailer systems in a priori known environment. We basically design and inject two new concepts; ghost walls and the Distance Optimization Technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dynamical model. This new combination of techniques emerges as a convenient mechanism for obtaining feasible orientations at the target positions with an overall reduction in the complexity of the navigation laws. The effectiveness of the proposed control laws were demonstrated via simulations of two traffic scenarios.

Keywords: artificial potential fields, 3-trailer systems, motion planning, posture, parking and collision, free trajectories

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Authors: Haga Abdelrahman Elimam

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This paper investigates the connotation, and some of the realistic implications, of the economic reform of health sector in under developed countries. The paper investigates the issues that economic reforms have to address, and the policy targets they are considered to accomplish. The work argues that the development of economic reform is not connected only with understanding the priorities and refining them, furthermore with reformation and restructuring the organizations through which health policies are employed. Considering various organizational values, that are likely to be regular to all economic reform programs, a regulatory approach to institutional reform is unsuitable. The paper further investigates the selection of economic reform that may as well influence via technical suggestions and analysis, but the verdict to continue, and the consequent success of execution, eventually depends on the progressive political sustainability. The paper concludes by giving examples of institutional reforms from various underdeveloped countries and includes recommendation of the responsibility and control of donor organizations.

Keywords: economic reform, health sector, underdeveloped countries, technical suggestions

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Authors: Sarah J. C. Slabbert

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The uptake of research as part of the diffusion or adoption of innovation by practitioners, whether individuals or organisations, has been a popular topic in agricultural development studies for many decades. In the classical, linear model of innovation theory, the innovation originates from an expert source such as a state-supported research organisation or academic institution. The changing context of agriculture led to the development of the agricultural innovation systems model, which recognizes innovation as a complex interaction between individuals and organisations, which include private industry and collective action organisations. In terms of this model, an innovation can be developed and adopted without any input or intervention from a state or parastatal research organisation. This evolution in the diffusion of agricultural innovation has put forward new challenges for state or parastatal research organisations, which have to demonstrate the impact of their research to the legislature or a regulatory authority: Unless the organisation and the research it produces cross the knowledge paths of the intended audience, there will be no awareness, no uptake and certainly no impact. It is therefore critical for such a research organisation to base its communication strategy on a thorough understanding of the knowledge needs, information sources and knowledge networks of the intended target audience. In 2016, the South African Water Research Commission (WRC) commissioned a study to investigate the knowledge needs, information sources and knowledge networks of Water User Associations and commercial irrigators with the aim of improving uptake of its research on efficient water use in irrigation. The first phase of the study comprised face-to-face interviews with the CEOs and Board Chairs of four Water User Associations along the Orange River in South Africa, and 36 commercial irrigation farmers from the same four irrigation schemes. Intermediaries who act as knowledge conduits to the Water User Associations and the irrigators were identified and 20 of them were subsequently interviewed telephonically. The study found that irrigators interact regularly with grower organisations such as SATI (South African Table Grape Industry) and SAPPA (South African Pecan Nut Association) and that they perceive these organisations as credible, trustworthy and reliable, within their limitations. State and parastatal research institutions, on the other hand, are associated with a range of negative attributes. As a result, the awareness of, and interest in, the WRC and its research on water use efficiency in irrigated agriculture are low. The findings suggest that a communication strategy that involves collaboration with these grower organisations would empower the WRC to participate much more efficiently and with greater impact in agricultural innovation networks. The paper will elaborate on the findings and discuss partnering frameworks and opportunities to manage perceptions and uptake.

Keywords: agricultural innovation systems, communication strategy, diffusion of innovation, irrigated agriculture, knowledge paths, research organisations, target audiences, water use efficiency

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Authors: Chantouch Wannathanom

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Research The study of elders’ needs in Bangkok metropolis for the options of health tourism. The objective is to study of elders’ needs in Bangkok Metropolis for the options of health tourism. The research her collected data using a questionnaire. The samples used in this research is elderly people living in the Dusit area. Of 400 people found the majority were female than male. Accounted for18 percent aged between 50-55 years, mostly undergraduate degree. Moreover, most seniors do not have underlying disease. The study found that 1. Elders’ needs in Bangkok Metropolis for the options of health tourism; 2. Tourism activity patterns that fit elderly was divided into 5 categories, including massage, massage, and herbal sauna. Practicing meditation and ascetic. The results showed that selection of elderly tourist activities by choosing healthy eating are the first. The hypothesis testing period: Elders’ needs in Bangkok Metropolis for the options of health tourism is different. The level of statistical significance .05 level.

Keywords: needs, elder, health tourism, Bangkok

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Authors: Reinhard Neck, Guido Schäfer

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In this paper, we explore the macroeconomic effects of the European Single Market on Austria by simulating the McKibbin-Sachs Global Model. Global interdependence and the impact of long-run effects on short-run adjustments are taken into account. We study the sensitivity of the results with respect to different assumptions concerning monetary and fiscal policies for the countries and regions of the world economy. The consequences of different assumptions about budgetary policies in Austria are also investigated. The simulation results are contrasted with ex-post evaluations of the actual impact of Austria’s membership in the Single Market. As a result, it can be concluded that the Austrian participation in the European Single Market entails considerable long-run gains for the Austrian economy with nearly no adverse side-effects on any macroeconomic target variable.

Keywords: macroeconomics, European Union, simulation, sensitivity analysis

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Authors: Jatinderkumar R. Saini

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E-mail has become a key mechanism of electronic communication. This is truer for professional organizations that like to communicate with their subjects online and are slowly shifting to paper-less office. The current paper focuses specifically on academic institutions offering Engineering course in Gujarat state and attempts for textual analysis of the usernames of the institutional e-mail addresses. We found that the institutions tend to design the username segment of their e-mail addresses by choosing words or combination of words from specific categories. The paper also highlights the use of special characters, digits and random words in designing the usernames. On the sidelines, the paper lists the style of employing department names and designations for the design process. To the best of our knowledge, this is the first formal attempt to analyze the selection of words employed for designing username segment of e-mail addresses of Engineering institutions.

Keywords: e-mail address, institute, engineering, username

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Authors: Peter Schnell, Phillip Haag

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In the course of the structural transformation of the construction industry, the integration of industrialization and digitization has led to the development of construction methods with an increased degree of prefabrication, such as system or modular construction. Compared to conventional construction, these innovative construction methods are characterized by modified structural and procedural properties and expand the range of construction services. Faced with the supply side, it is possible to identify construction-specific customer types with different characteristics and certain preferences as far as the choice of construction method is concerned. The basis for this finding was qualitative expert interviews. By evaluating the stereotypical customer needs, a corresponding segmentation of the demand side can be made along with the basic orientation and decision behavior. This demarcation supports the target- and needs-oriented customer approach and contributes to cooperative and successful project management.

Keywords: differentiation of customer types, modular construction methods, conventional construction methods, stereotypical customer types

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