Search results for: fuzzy multi-objective linear programming problems

Authors: Zohreh Khojasteh-Ghamari, Takashi Irohara

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One of the efficient ways in supply chain risk management is avoiding the interruption in Supply Chain (SC) before it occurs. Although the majority of the organizations focus on their first-tier suppliers to avoid risk in the SC, studies show that in only 60 percent of the disruption cases the reason is first tier suppliers. In the 40 percent of the SC disruptions, the reason is downstream SC, which is the second tier and lower. Due to the increasing complexity and interrelation of modern supply chains, the SC elements have become difficult to trace. Moreover, studies show that there is a vital need to better understand the integration of risk and visibility, especially in the context of multiple objectives. In this study, we propose a multi-objective programming model to avoid disruption in SC. The objective of this study is evaluating the effect of downstream SCV on managing supply chain risk. We propose a multi-objective mathematical programming model with the objective functions of minimizing the total cost and maximizing the downstream supply chain visibility (SCV). The decision variable is supplier selection. We assume there are several manufacturers and several candidate suppliers. For each manufacturer, our model proposes the best suppliers with the lowest cost and maximum visibility in downstream supply chain. We examine the applicability of the model by numerical examples. We also define several scenarios for datasets and observe the tendency. The results show that minimum visibility in downstream SC is needed to have a safe SC network.

Keywords: downstream supply chain, optimization, supply chain risk, supply chain visibility

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Authors: Sabrine Ammar, Mohamed Tahar Bhiri

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Automatic planning has a de facto standard language called Planning Domain Definition Language (PDDL) for describing planning problems. It aims to formalize the planning problems described by the concept of state space. PDDL-related dynamic analysis tools, namely planners and validators, are insufficient for verifying and validating PDDL descriptions. Indeed, these tools made it possible to detect errors a posteriori by means of test activity. In this paper, we recommend a formal approach coupling the two languages Event-B and PDDL, for automatic planning. Event-B is used for formal modeling by stepwise refinement with mathematical proofs of planning problems. Thus, this paper proposes a refinement strategy allowing to obtain reliable PDDL descriptions from an ultimate Event-B model correct by construction. The ultimate Event-B model, correct by construction which is supposed to be translatable into PDDL, is automatically translated into PDDL using our MDE Event-B2PDDL tool.

Keywords: code generation, event-b, PDDL, refinement strategy, translation rules

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Authors: Royia Soliman, Salma ElAnsary, Akram Amin Abdellatif, Florian Holzapfel

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Model-Based Safety Analysis (MBSA) is an approach in which the system and safety engineers share a common system model created using a model-based development process. The model can also be extended by the failure modes of the system components. There are two famous approaches for the addition of fault behaviors to system models. The first one is to enclose the failure into the system design directly. The second approach is to develop a fault model separately from the system model, thus combining both independent models for safety analysis. This paper introduces a hybrid approach of MBSA. The approach tries to use informal abstracted models to investigate failure behaviors. The approach will combine various concepts such as directed graph traversal, event lists and Constraint Satisfaction Problems (CSP). The approach is implemented using an Object Oriented programming language. The components are abstracted to its failure logic and relationships of connected components. The implemented approach is tested on various flight control systems, including electrical and multi-domain examples. The various tests are analyzed, and a comparison to different approaches is represented.

Keywords: flight control systems, model based safety analysis, safety assessment analysis, system modelling

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Authors: Leslie M. Gutman

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Conduct problems (CP) represent a major dilemma, with wide-ranging and long-lasting individual and societal impacts. Children experience heterogeneous patterns of conduct problems; based on the age of onset, developmental course and related risk factors from around age 3. Early childhood represents a potential window for intervention efforts aimed at changing the trajectory of early starting conduct problems. Using the UK Millennium Cohort Study (n = 17,206 children), this study (a) identifies trajectories of conduct problems from ages 3 to 14 years and (b) assesses the cumulative and interactive effects of individual, family and socioeconomic risk factors from ages 9 months to 14 years. The same factors according to three domains were assessed, including child (i.e., low verbal ability, hyperactivity/inattention, peer problems, emotional problems), family (i.e., single families, parental poor physical and mental health, large family size) and socioeconomic (i.e., low family income, low parental education, unemployment, social housing). A cumulative risk score for the child, family, and socioeconomic domains at each age was calculated. It was then examined how the cumulative risk scores explain variation in the trajectories of conduct problems. Lastly, interactive effects among the different domains of cumulative risk were tested. Using group-based trajectory modeling, four distinct trajectories were found including a ‘low’ problem group and three groups showing childhood-onset conduct problems: ‘school-age onset’; ‘early-onset, desisting’; and ‘early-onset, persisting’. The ‘low’ group (57% of the sample) showed a low probability of conducts problems, close to zero, from 3 to 14 years. The ‘early-onset, desisting’ group (23% of the sample) demonstrated a moderate probability of CP in early childhood, with a decline from 3 to 5 years and a low probability thereafter. The ‘early-onset, persistent’ group (8%) followed a high probability of conduct problems, which declined from 11 years but was close to 70% at 14 years. In the ‘school-age onset’ group, 12% of the sample showed a moderate probability of conduct problems from 3 and 5 years, with a sharp increase by 7 years, increasing to 50% at 14 years. In terms of individual risk, all factors increased the likelihood of being in the childhood-onset groups compared to the ‘low’ group. For cumulative risk, the socioeconomic domain at 9 months and 3 years, the family domain at all ages except 14 years and child domain at all ages were found to differentiate childhood-onset groups from the ‘low’ group. Cumulative risk at 9 months and 3 years did not differentiate between the ‘school-onset’ group and ‘low’ group. Significant interactions were found between the domains for the ‘early-onset, desisting group’ suggesting that low levels of risk in one domain may buffer the effects of high risk in another domain. The implications of these findings for preventive interventions will be highlighted.

Keywords: conduct problems, cumulative risk, developmental trajectories, early childhood, adolescence

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Authors: Wen Li, Zhengyu Bai, Qi Zhang

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The demand for smart scheduling platform in agriculture, particularly in the scheduling process of machinery equipment, is high. With the continuous development of agricultural machinery equipment technology, a large number of agricultural machinery equipment and agricultural machinery cooperative service organizations continue to appear in China. The large area of cultivated land and a large number of agricultural activities in the central and western regions of China have made the demand for smart and efficient agricultural machinery equipment scheduling platforms more intense. In this study, we design and implement a platform for agricultural machinery equipment scheduling to allocate agricultural machinery equipment resources reasonably. With agricultural machinery equipment scheduling platform taken as the research object, we discuss its research significance and value, use the service blueprint technology to analyze and characterize the agricultural machinery equipment schedule workflow, the network analytic method to obtain the demand platform function requirements, and divide the platform functions through the platform function division diagram. Simultaneously, based on the case-based reasoning (CBR) algorithm, the equipment scheduling module of the agricultural machinery equipment scheduling platform is realized; finally, a design scheme of the agricultural machinery equipment scheduling platform architecture is provided, and the visualization interface of the platform is established via VB programming language. It provides design ideas and theoretical support for the construction of a modern agricultural equipment information scheduling platform.

Keywords: case-based reasoning, service blueprint, system design, ANP, VB programming language

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Authors: Paul Toprac, Branden Heng, Harsheni Siddharthan, Allison Tseng, Sarah Abraham, Etienne Vouga

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The goal of this project was to evaluate and document the capabilities and limitations of AI tools for empowering small teams to create high budget, high profile (AAA) 3D games typically developed by large studios. Two teams of novice game developers attempted to create two different games using AI and Unreal Engine 5.3. First, the teams evaluated 60 AI art, design, sound, and programming tools by considering their capability, ease of use, cost, and license restrictions. Then, the teams used a shortlist of 13 AI tools for game development. During this process, the following tools were found to be the most productive: (1) ChatGPT 4.0 for both game and narrative concepting and documentation; (2) Dall-E 3 and OpenArt for concept art; (3) Beatoven for music drafting; (4) Epic PCG for level design; and (5) ChatGPT 4.0 and Github Copilot for generating simple code and to complement human-made tutorials as an additional learning resource. While current generative AI may appear impressive at first glance, the assets they produce fall short of AAA industry standards. Generative AI tools are helpful when brainstorming ideas such as concept art and basic storylines, but they still cannot replace human input or creativity at this time. Regarding programming, AI can only effectively generate simple code and act as an additional learning resource. Thus, generative AI tools are at best tools to enhance developer productivity rather than as a system to replace developers.

Keywords: AAA games, AI, automation tools, game development

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Authors: Min Wei

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The traditional prediction methods of the forecast for tourism market are paid more attention to the accuracy of the forecasts, ignoring the results of the feasibility of forecasting and predicting operability, which had made it difficult to predict the results of scientific testing. With the application of Linear Regression Model, this paper attempts to construct a scientific evaluation system for predictive value, both to ensure the accuracy, stability of the predicted value, and to ensure the feasibility of forecasting and predicting the results of operation. The findings show is that a scientific evaluation system can implement the scientific concept of development, the harmonious development of man and nature co-ordinate.

Keywords: linear regression model, tourism market, forecast, tourism economics

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Authors: J. Cabral, C. Barreto Carvalho, C. da Motta, M. Sousa

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Community integration is a construct that an increasing body of research has shown to have a significant impact in well-being and recovery of people with psychiatric problems. However, there are few studies that explore which factors can be associated and predict community integration. Moreover, community integration has been mostly studied in minority groups, and currently literature on the definition and manifestation of community integration in the more general population is scarce. Thus, the current study aims to characterize community integration and explore possible predictor variables in a sample of participants with psychiatric problems (PP, N=183) and a sample of participants from the general population (GP, N=211). Results show that people with psychiatric problems present above average values of community integration, but are significantly lower than their healthy counterparts. It was also possible to observe that community integration does not vary in terms of the socio-demographic characteristics of both groups in this study. Correlation and multiple regression showed that, among several variables that literature present as relevant in the community integration process, only three variables emerged as having the most explanatory value in community integration of both groups: sense of community, basic needs satisfaction and submission. These results also shown that those variables have increased explanatory power in the PP sample, which leads us to emphasize the need to address this issue in future studies and increase the understanding of the factors that can be involved in the promotion of community integration, in order to devise more effective interventions in this field.

Keywords: community integration, mental illness, predictors, psychiatric problems

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Authors: Othmane Boughazi, Abdelmadjid Boumedienne, Hachemi Glaoui

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This work treats the modeling and simulation of non-linear system behavior of an induction motor using backstepping sliding mode control. First, the direct field oriented control IM is derived. Then, a sliding for direct field oriented control is proposed to compensate the uncertainties, which occur in the control.Finally, the study of Backstepping sliding controls strategy of the induction motor drive. Our non linear system is simulated in MATLAB SIMULINK environment, the results obtained illustrate the efficiency of the proposed control with no overshoot, and the rising time is improved with good disturbances rejections comparing with the classical control law.

Keywords: induction motor, proportional-integral, sliding mode control, backstepping sliding mode control

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Authors: W. Baumgartner, M. Welti, N. Hild, S. C. Hess, W. J. Stark, G. Meier Bürgisser, P. Giovanoli, J. Buschmann

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Perfusion bioreactors are used to solve problems in tissue engineering in terms of sufficient nutrient and oxygen supply. Such problems especially occur in critical size grafts because vascularization is often too slow after implantation ending up in necrotic cores. Biominerizable and biocompatible nanocomposite materials are attractive and suitable scaffold materials for bone tissue engineering because they offer mineral components in organic carriers – mimicking natural bone tissue. In addition, human adipose derived stem cells (ASCs) can potentially be used to increase bone healing as they are capable of differentiating towards osteoblasts or endothelial cells among others. In the present study, electrospun nanocomposite disks of poly-lactic-co-glycolic acid and amorphous calcium phosphate nanoparticles (PLGA/a-CaP) were seeded with human ASCs and eight disks were stacked in a bioreactor running with normal culture medium (no differentiation supplements). Under continuous perfusion and uniaxial cyclic compression, load-displacement curves as a function of time were assessed. Stiffness and energy dissipation were recorded. Moreover, stem cell densities in the layers of the piled scaffold were determined as well as their morphologies and differentiation status (endothelial cell differentiation, chondrogenesis and osteogenesis). While the stiffness of the cell free constructs increased over time caused by the transformation of the a-CaP nanoparticles into flake-like apatite, ASC-seeded constructs showed a constant stiffness. Stem cell density gradients were histologically determined with a linear increase in the flow direction from the bottom to the top of the 3.5 mm high pile (r2 > 0.95). Cell morphology was influenced by the flow rate, with stem cells getting more roundish at higher flow rates. Less than 1 % osteogenesis was found upon osteopontin immunostaining at the end of the experiment (9 days), while no endothelial cell differentiation and no chondrogenesis was triggered under these conditions. All ASCs had mainly remained in their original pluripotent status within this time frame. In summary, we have fabricated a critical size bone graft based on a biominerizable bone-biomimetic nanocomposite with preserved stiffness when seeded with human ASCs. The special feature of this bone graft was that ASC densities inside the piled construct varied with a linear gradient, which is a good starting point for tissue engineering interfaces such as bone-cartilage where the bone tissue is cell rich while the cartilage exhibits low cell densities. As such, this tissue-engineered graft may act as a bone-cartilage interface after the corresponding differentiation of the ASCs.

Keywords: bioreactor, bone, cartilage, nanocomposite, stem cell gradient

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Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

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This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

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Authors: Jill Villarreal, Kristalyn Cooksey, Kai Lloyd, Daniel Ha

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Little research has been conducted to examine college students' reading attitudes, including students' perceptions of reading behaviors and reading abilities. This is problematic, as reading assigned course material is a critical component to an undergraduate student's academic success. For this study, flyers were electronically disseminated to instructors at 24 public and 10 private U.S. institutions in “Reading-Intensive Departments” including Psychology, Sociology, Education, Business, and Communications. We requested the online survey be completed as an in-class activity during the fall 2019 and spring 2020 semesters. All participants voluntarily completed the questionnaire anonymously. Of the participants, 280 self-identified their race as Black and 280 self-identified their race as White. Of the participants, 177 self-identified their gender as Male and 383 self-identified their Gender as Female. Participants ranged in age from 18-24. Factor analysis found four dimensions resulting from the questions regarding reading. The first we interpret as “Reading Proficiency”, accounted for 19% of the variability. The second dimension was “Reading Anxiety” (15%), the third was “Textbook Reading Ability” (9%), and the fourth was “Reading Enjoyment” (8%). Linear models on each of these dimensions revealed no effect of Age, Gender, Race, or Income on “Reading proficiency”. The linear model of “Reading Anxiety” showed a significant effect of race (p = 0.02), with higher anxiety in white students, as well as higher reading anxiety in female students (p < 0.001). The model of “Textbook Reading Ability” found a significant effect of race (p < 0.001), with higher textbook problems in white students. The model of “Reading Enjoyment” showed significant effects of race (p = 0.013) with more enjoyment for white students, gender (p = 0.001) with higher enjoyment for female students, and age (p = 0.033) with older students showing higher enjoyment. These findings suggest that gender, age, and race are important factors in many aspects of college students' reading attitudes. Further research will investigate possible causes for these differences. In addition, the effectiveness of college-level programs to reduce reading anxiety, promote the reading of textbooks, and foster a love of reading will be assessed.

Keywords: age, college, gender, race, reading

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Authors: Phan Thi Song Thuong

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This paper uses data from a survey on the green consumption behavior of Hanoi residents in October 2022. Data was gathered from a survey conducted in ten districts in the center of Hanoi, with 393 respondents. The hypothesis focuses on understanding the factors that may affect green consumption behavior, such as demographic characteristics, concerns about the environment and health, people living around, self-efficiency, and mass media. A number of methods, such as the T-test, exploratory factor analysis, and a linear regression model, are used to prove the hypotheses. Accordingly, the results show that gender, age, and education level have separate effects on the green consumption behavior of respondents.

Keywords: green consumption, urban residents, environment, sustainable, linear regression

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Authors: M. Sirhan, S. Bekhor, A. Sidess

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In-service pavements deteriorate with time due to traffic wheel loads, environment, and climate conditions. Pavement deterioration leads to a reduction in their serviceability and structural behavior. Consequently, proper maintenance and rehabilitation (M&R) are necessary actions to keep the in-service pavement network at the desired level of serviceability. Due to resource and financial constraints, the pavement management system (PMS) prioritizes roads most in need of maintenance and rehabilitation action. It recommends a suitable action for each pavement based on the performance and surface condition of each road in the network. The pavement performance and condition are usually quantified and evaluated by different types of roughness-based and stress-based indices. Examples of such indices are Pavement Serviceability Index (PSI), Pavement Serviceability Ratio (PSR), Mean Panel Rating (MPR), Pavement Condition Rating (PCR), Ride Number (RN), Profile Index (PI), International Roughness Index (IRI), and Pavement Condition Index (PCI). PCI is commonly used in PMS as an indicator of the extent of the distresses on the pavement surface. PCI values range between 0 and 100; where 0 and 100 represent a highly deteriorated pavement and a newly constructed pavement, respectively. The PCI value is a function of distress type, severity, and density (measured as a percentage of the total pavement area). PCI is usually calculated iteratively using the 'Paver' program developed by the US Army Corps. The use of soft computing techniques, especially Artificial Neural Network (ANN), has become increasingly popular in the modeling of engineering problems. ANN techniques have successfully modeled the performance of the in-service pavements, due to its efficiency in predicting and solving non-linear relationships and dealing with an uncertain large amount of data. Typical regression models, which require a pre-defined relationship, can be replaced by ANN, which was found to be an appropriate tool for predicting the different pavement performance indices versus different factors as well. Subsequently, the objective of the presented study is to develop and train an ANN model that predicts the PCI values. The model’s input consists of percentage areas of 11 different damage types; alligator cracking, swelling, rutting, block cracking, longitudinal/transverse cracking, edge cracking, shoving, raveling, potholes, patching, and lane drop off, at three severity levels (low, medium, high) for each. The developed model was trained using 536,000 samples and tested on 134,000 samples. The samples were collected and prepared by The National Transport Infrastructure Company. The predicted results yielded satisfactory compliance with field measurements. The proposed model predicted PCI values with relatively low standard deviations, suggesting that it could be incorporated into the PMS for PCI determination. It is worth mentioning that the most influencing variables for PCI prediction are damages related to alligator cracking, swelling, rutting, and potholes.

Keywords: artificial neural networks, computer programming, pavement condition index, pavement management, performance prediction

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Authors: Tapas Acharya, Monalisa Mitra

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Overlay modeling is the most widely used conventional analysis for spatial decision support system. Overlay modeling requires a set of themes with different weightage computed in varied manners, which gives a resultant input for further integrated analysis. In spite of the popularity and most widely used technique; it gives inconsistent and erroneous results for similar inputs while processed in various GIS overlay techniques. This study is an attempt to compare and analyse the differences in the outputs of different overlay methods using GIS platform with same set of themes of the Precambrian metamorphic to obtain groundwater prospecting in Precambrian metamorphic rocks. The objective of the study is to emphasize the most suitable overlay method for groundwater prospecting in older Precambrian metamorphics. Seven input thematic layers like slope, Digital Elevation Model (DEM), soil thickness, lineament intersection density, average groundwater table fluctuation, stream density and lithology have been used in the spatial overlay models of fuzzy overlay, weighted overlay and weighted sum overlay methods to yield the suitable groundwater prospective zones. Spatial concurrence analysis with high yielding wells of the study area and the statistical comparative studies among the outputs of various overlay models using RStudio reveal that the Weighted Overlay model is the most efficient GIS overlay model to delineate the groundwater prospecting zones in the Precambrian metamorphic rocks.

Keywords: fuzzy overlay, GIS overlay model, groundwater prospecting, Precambrian metamorphics, weighted overlay, weighted sum overlay

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Authors: P. Thepnarintra, S. Nikorn

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Agricultural machinery industry plays an important role in the industrial development especially the production industry of the country. There has been continuing development responding to the higher demand of the production. However, the problem in agricultural machinery production still exists. Thus, the purpose of this research is to investigate problems on fundamental factors of industry based on the entrepreneurs’ point of view. The focus was on the small and medium size industry receiving a factory license typed number 0660 from the Department of Industrial Works. The investigation was on the comparison between the management of the small and medium size agricultural industry in 3 provinces in the central region of Thailand. Population in this study consisted of 189 company managers or managing directors, of which 101 were from the small size and 88 were from the medium size industry. The data were analyzed to find percentage, arithmetic mean, and standard deviation with independent sample T-test at the statistical significance .05. The results showed that the small and medium size agricultural machinery manufacturers in the central region of Thailand reported high problems in every aspect. When compared the problems on basic factors in running the business, it was found that there was no difference statistically at .05 in managing of the small and medium size agricultural machinery manufacturers. However, there was a statistically significant difference between the small and medium size agricultural machinery manufacturers on the aspect of policy and services of the government. The problems reported by the small and medium size agricultural machinery manufacturers were the services on public tap water and the problem on politic and stability of the country.

Keywords: agricultural machinery, manufacturers, problems, on running the business

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Authors: Anna Kesoyan

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The present paper deals with the syntax-related problems of translation from English into Armenian. Although Syntax is a part of grammar, syntax-related problems of translation are studied separately during the process of translation. Translation from one language to another is widely accepted as a challenging problem. This becomes even more challenging when the source and target languages are widely different in structure and style, as is the case with English and Armenian. Syntax-related problems of translation from English into Armenian are mainly connected with the syntactical structures of these languages, and particularly, with the word order of the sentence. The word order of the sentence of the Armenian language, which is a synthetic language, is usually characterized as “rather free”, and the word order of the English language, which is an analytical language, is characterized “fixed”. The following research examines the main translation means, particularly, syntactical transformations as the translator has to take real steps while trying to solve certain syntax-related problems. Most of the means of translation are based on the transformation of grammatical components of the sentence, without changing the main information of the text. There are several transformations that occur during translation such as word order of the sentence, transformations of certain grammatical constructions like Infinitive participial construction, Nominative with the Infinitive and Elliptical constructions which have been covered in the following research.

Keywords: elliptical constructions, nominative with the infinitive constructions, fixed and free word order, syntactic structures

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Authors: Mohamad Saberi, Arash Sohrabi

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Tuned liquid damper is one the passive structural control ways which has been used since mid-1980 decade for seismic control in civil engineering. This system is made of one or many tanks filled with fluid, mostly water that installed on top of the high raised structure and used to prevent structure vibration. In this article we will show how to make seismic table contain TLD system and analysis the result of using this system in our structure. Results imply that when frequency ratio approaches 1 this system can perform its best in both dissipate energy and increasing structural damping. And also results of these serial experiments are proved compatible with Hunzer linear theory behaviour.

Keywords: TLD, seismic table, structural system, Hunzer linear behaviour

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: D. S. Naumann, B. J. Evans, O. Hassan

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This paper outlines the development of an automated aerodynamic optimisation algorithm using a novel method of parameterising a computational mesh by employing user–defined control nodes. The shape boundary movement is coupled to the movement of the novel concept of the control nodes via a quasi-1D-linear deformation. Additionally, a second order smoothing step has been integrated to act on the boundary during the mesh movement based on the change in its second derivative. This allows for both linear and non-linear shape transformations dependent on the preference of the user. The domain mesh movement is then coupled to the shape boundary movement via a Delaunay graph mapping. A Modified Cuckoo Search (MCS) algorithm is used for optimisation within the prescribed design space defined by the allowed range of control node displacement. A finite volume compressible NavierStokes solver is used for aerodynamic modelling to predict aerodynamic design fitness. The resulting coupled algorithm is applied to a range of test cases in two dimensions including the design of a subsonic, transonic and supersonic intake and the optimisation approach is compared with more conventional optimisation strategies. Ultimately, the algorithm is tested on a three dimensional wing optimisation case.

Keywords: mesh movement, aerodynamic shape optimization, cuckoo search, shape parameterisation

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Authors: Tahani Salman Alangari

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Student success can be impacted by internal factors such as their emotional well-being and external factors such as organizational support and instructional support in the classroom. This study is to identify at least one factor that forecasts student engagement. It is a cross-sectional, conducted on 6206 teachers and encompassed three years of data collection and observations of math instruction in approximately 50 schools and 300 classrooms. A multiple linear regression revealed that a model predicting student engagement from emotional support, classroom organization, and instructional support was significant. Four linear regression models were tested using hierarchical regression to examine the effects of independent variables: emotional support was the highest predictor of student engagement while instructional support was the lowest.

Keywords: student engagement, emotional support, organizational support, instructional support, well-being

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Authors: Muhammad Tayyab Sohail, Li Jiangfeng

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This study aimed at characterizing land cover dynamics for about three decades in capital city of Pakistan Islamabad. The specific objectives were identifying and map the major land cover types in 1993, 2002 and 2014 and check the reduction of greenery and urbanization rate and its some environments aspects. The study showed that overall grasslands decreased in the prescribed period. The key hotspots of these changes were distributed in all directions of the study area, but at different times. Urbanization is increasing every year in this city but the policies for this number of people are not sufficient to meet their living standard requirements. Apart from it, there is also an impact of urbanization on environmental related problems. Underground water is going down and down, traffic related issue and other associated problems are part of this research. Therefore, policies that integrate restoration and conservation of natural ecosystems with enhancement of agricultural productivity are strongly recommended. This will ensure environmental sustainability and socio-economic well-being in the area. Future research needs to address the problems related to urbanization and need to clarify the problems and solve it on high priority.

Keywords: land, Islamabad, water, urban

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Authors: Bekir O. Bartin, Kaan Ozbay, Sandeep Mudigonda, Hong Yang

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The use of microscopic traffic simulation in evaluating the operational and safety conditions at toll plazas is demonstrated. Two toll plazas in New Jersey are selected as case studies and were developed and validated in Paramics traffic simulation software. In order to simulate drivers’ lane selection behavior in Paramics, a utility-based lane selection approach is implemented in Paramics Application Programming Interface (API). For each vehicle approaching the toll plaza, a utility value is assigned to each toll lane by taking into account the factors that are likely to impact drivers’ lane selection behavior, such as approach lane, exit lane and queue lengths. The results demonstrate that similar operational conditions, such as lane-by-lane toll plaza traffic volume can be attained using this approach. In addition, assessment of safety at toll plazas is conducted via a surrogate safety measure. In particular, the crash index (CI), an improved surrogate measure of time-to-collision (TTC), which reflects the severity of a crash is used in the simulation analyses. The results indicate that the spatial and temporal frequency of observed crashes can be simulated using the proposed methodology. Further analyses can be conducted to evaluate and compare various different operational decisions and safety measures using microscopic simulation models.

Keywords: microscopic simulation, toll plaza, surrogate safety, application programming interface

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Authors: Shuang Luo, Er-Xiang Song

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Many problems in geotechnical engineering, such as foundation deformation, groundwater seepage, seismic wave propagation and geothermal transfer problems, may involve analysis in the ground which can be seen as extending to infinity. To that end, consideration has to be given regarding how to deal with the unbounded domain to be analyzed by using numerical methods, such as finite element method (FEM), finite difference method (FDM) or finite volume method (FVM). A simple artificial boundary approach derived from the analytical solutions for transient radial seepage problems, is introduced. It should be noted, however, that the analytical solutions used to derive the artificial boundary are particular solutions under certain boundary conditions, such as constant hydraulic head at the origin or constant pumping rate of the well. When dealing with unbounded domains with unsteady boundary conditions, a more sophisticated artificial boundary approach to deal with the infinity of the domain is presented. By applying Laplace transforms and introducing some specially defined auxiliary variables, the global artificial boundary conditions (ABCs) are simplified to local ones so that the computational efficiency is enhanced significantly. The introduced two local ABCs are implemented in a finite element computer program so that various seepage problems can be calculated. The two approaches are first verified by the computation of a one-dimensional radial flow problem, and then tentatively applied to more general two-dimensional cylindrical problems and plane problems. Numerical calculations show that the local ABCs can not only give good results for one-dimensional axisymmetric transient flow, but also applicable for more general problems, such as axisymmetric two-dimensional cylindrical problems, and even more general planar two-dimensional flow problems for well doublet and well groups. An important advantage of the latter local boundary is its applicability for seepage under rapidly changing unsteady boundary conditions, and even the computational results on the truncated boundary are usually quite satisfactory. In this aspect, it is superior over the former local boundary. Simulation of relatively long operational time demonstrates to certain extents the numerical stability of the local boundary. The solutions of the two local ABCs are compared with each other and with those obtained by using large element mesh, which proves the satisfactory performance and obvious superiority over the large mesh model.

Keywords: transient seepage, unbounded domain, artificial boundary condition, numerical simulation

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Authors: Hussein Moselhy, Islam Salam

Abstract:

There have been some challenges and problems which hinder the implementation of the e-marketing systems such as the high cost of information systems infrastructure and maintenance as well as their unavailability within the institution. Also, there is no system which supports all programming languages and different platforms. Another problem is the lack of integration between these systems on one hand and the operating systems and different web browsers on the other hand. No system for customer relationship management is established which recognizes their desires and puts them in consideration while performing e-marketing functions is available. Therefore, the service-oriented architecture emerged as one of the most important techniques and methodologies to build systems that integrate with various operating systems and different platforms and other technologies. This technology allows realizing the data exchange among different applications. The service-oriented architecture represents distributed computing concepts to demonstrate its success in achieving the requirements of systems through web services. It also reflects the appropriate design for the services to use different web services in supporting the requirements of business processes and software users. In a service-oriented environment, web services are deployed on the web in the form of independent services to be accessed without knowledge of the nature of the programs and systems with in. This Paper presents a proposal for a new model which contributes to the application of methods and means of e-marketing with the integration of marketing mix elements to improve marketing efficiency (E-MSOA). And apply it in the educational city of one of the Egyptian sector.

Keywords: service-oriented architecture, electronic commerce, virtual retailing, unified modeling language

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Authors: Ibrahim Ali, Adamu Danlami Ahmed

Abstract:

This study examines the impact of depreciation on taxable income and financial performance of consumer goods companies quoted on the Nigerian stock exchange. The study adopts ex-post factor research design. Data were collected using a secondary source. The findings of the study suggest that, method of depreciation adopted in any organization influence the taxable profit. Depreciation techniques can either be: depressive, accelerative and linear depreciation. It was also recommended that consumer goods should adjust their method of depreciation to make sure an appropriate method is adopted. This will go a long way to revitalize their taxable profit.

Keywords: accelerated, linear, depressive, depreciation

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Authors: Ana Clara Santos, Maria Manuela Portela, Bettina Schaefli

Abstract:

This work assesses the performance of an analytical model framework to generate daily flow duration curves, FDCs, based on climatic characteristics of the catchments and on their streamflow recession coefficients. According to the analytical model framework, precipitation is considered to be a stochastic process, modeled as a marked Poisson process, and recession is considered to be deterministic, with parameters that can be computed based on different models. The analytical model framework was tested for three case studies with different hydrological regimes located in Switzerland: pluvial, snow-dominated and glacier. For that purpose, five time intervals were analyzed (the four meteorological seasons and the civil year) and two developments of the model were tested: one considering a linear recession model and the other adopting a nonlinear recession model. Those developments were combined with recession coefficients obtained from two different approaches: forward and inverse estimation. The performance of the analytical framework when considering forward parameter estimation is poor in comparison with the inverse estimation for both, linear and nonlinear models. For the pluvial catchment, the inverse estimation shows exceptional good results, especially for the nonlinear model, clearing suggesting that the model has the ability to describe FDCs. For the snow-dominated and glacier catchments the seasonal results are better than the annual ones suggesting that the model can describe streamflows in those conditions and that future efforts should focus on improving and combining seasonal curves instead of considering single annual ones.

Keywords: analytical streamflow distribution, stochastic process, linear and non-linear recession, hydrological modelling, daily discharges

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Authors: Amir Reza Talaghat

Abstract:

Since 2015, a new approach and policy regarding energy resources protection and using renewable energies has been started in Iran which was developing new projects. Investigating about the feasibility study of these new projects helped to figure out five steps to prepare an executive feasibility study of the concerned projects, which are proper site selections, authorizations, design and simulation, economic study and programming, respectively. The results were interesting and essential for decision makers and investors to start implementing of these projects in reliable condition. The research is obtained through collection and study of the project's documents as well as recalculation to review conformity of the results with GIS data and the technical information of the bidders. In this paper, it is attempted to describe the result of the performed research by describing the five steps as an executive methodology, for preparing a feasible study of installing a 10 MW – solar farm project. The corresponding results of the research also help decision makers to start similar projects is explained in this paper as follows: selecting the best location for the concerned PV plant, reliable and safe conditions for investment and the required authorizations to start implementing the solar farm project in the concerned region, selecting suitable component to achieve the best possible performance for the plant, economic profit of the investment, proper programming to implement the project on time.

Keywords: solar farm, solar energy, execution of PV power plant PV power plant

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Authors: Koray U. Erbas

Abstract:

Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

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Authors: Olga Maksakova

Abstract:

A work with unconscious patients after acute brain damages besides special knowledge and practical skills of all the participants requires a very specific organization. A lot of said about team approach in neurorehabilitation, usually as for outpatient mode. Rehabilitologists deal with fixed patient problems or deficits (motion, speech, cognitive or emotional disorder). Team-building means superficial paradigm of management psychology. Linear mode of teamwork fits casual relationships there. Cases with deep altered states of consciousness (vegetative states, coma, and confusion) require non-linear mode of teamwork: recovery of consciousness might not be the goal due to phenomenon uncertainty. Rehabilitation team as Semi-open Complex System includes the patient as a part. Patient's response pattern becomes formed not only with brain deficits but questions-stimuli, context, and inquiring person. Teamwork is sourcing of phenomenology knowledge of patient's processes as Third-person approach is replaced with Second- and after First-person approaches. Here is a chance for real-time change. Patient’s contacts with his own body and outward things create a basement for restoration of consciousness. The most important condition is systematic feedbacks to any minimal movement or vegetative signal of the patient. Up to now, recovery work with the most severe contingent is carried out in the mode of passive physical interventions, while an effective rehabilitation team should include specially trained psychologists and psychotherapists. It is they who are able to create a network of feedbacks with the patient and inter-professional ones building up the team. Characteristics of ‘Team-Patient’ system (TPS) are energy, entropy, and complexity. Impairment of consciousness as the absence of linear contact appears together with a loss of essential functions (low energy), vegetative-visceral fits (excessive energy and low order), motor agitation (excessive energy and excessive order), etc. Techniques of teamwork are different in these cases for resulting optimization of the system condition. Directed regulation of the system complexity is one of the recovery tools. Different signs of awareness appear as a result of system self-organization. Joint meetings are an important part of teamwork. Regular or event-related discussions form the language of inter-professional communication, as well as the patient's shared mental model. Analysis of complex communication process in TPS may be useful for creation of the general theory of consciousness.

Keywords: rehabilitation team, urgent rehabilitation, severe brain damage, consciousness disorders, complex system theory

Procedia PDF Downloads 146