Search results for: specific factors model

Authors: M. Moeinaddini, Z. Asadi-Shekari, Z. Sultan, M. Zaly Shah

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Happiness can be related to everything that can provide a feeling of satisfaction or pleasure. This study tries to consider the relationship between land use factors and feeling of happiness at the neighbourhood level. Land use variables (beautiful and attractive neighbourhood design, availability and quality of shopping centres, sufficient recreational spaces and facilities, and sufficient daily service centres) are used as independent variables and the happiness score is used as the dependent variable in this study. In addition to the land use variables, socio-economic factors (gender, race, marital status, employment status, education, and income) are also considered as independent variables. This study uses the Oxford happiness questionnaire to estimate happiness score of more than 300 people living in six neighbourhoods. The neighbourhoods are selected randomly from Skudai neighbourhoods in Johor, Malaysia. The land use data were obtained by adding related questions to the Oxford happiness questionnaire. The strength of the relationship in this study is found using generalised linear modelling (GLM). The findings of this research indicate that increase in happiness feeling is correlated with an increasing income, more beautiful and attractive neighbourhood design, sufficient shopping centres, recreational spaces, and daily service centres. The results show that all land use factors in this study have significant relationship with happiness but only income, among socio-economic factors, can affect happiness significantly. Therefore, land use factors can affect happiness in Skudai more than socio-economic factors.

Keywords: neighbourhood land use, neighbourhood design, happiness, socio-economic factors, generalised linear modelling

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Authors: Yulina E. Riany, Divna Haslam, Matthew Sanders

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This cross-cultural study aims to compare the level of parental depression and stress, parenting style use, and child emotional and behavioural problems between parents in Australia as an example of a Western country and parents in Indonesia as an example of Asian culture. A series of hierarchical regressions were undertaken to determine two models examining the factors that predict child problems residing in Australia (Model 1) and in Indonesia (Model 2). The online survey was completed by 179 parents in Australia and 448 parents in Indonesia. Results indicated that Australian parents reported higher levels of depression, authoritative parenting and higher levels of child misbehaviours compared to Indonesian parents. In comparison, Indonesian parents reported higher authoritarian parenting. Analyses performed to examine Model 1 and 2 revealed that parental negative emotional states and parenting style predicted child emotional and behavioural problems in both countries.

Keywords: cross-cutural study, parental stress, parenting, child misbehaviour

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Authors: Adedayo Jeremiah Adeyekun, Samuel Oluwagbemiga Ishola,

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This paper is an assessment of factors influencing the cost and time performance of subcontractors and the need for effective performance of subcontractors at the project sites. The factors influencing the performance of subcontractors are grouped, similar to those identified with the project or an organization and on another hand, there are significant factors influencing the performance of the subcontractors. These factors incorporate management level leadership, time required to complete the project, profit, staff capability/expertise, reputation, installment method, organization history, and project procurement method strategy, security, bidding technique, insurance, bond and relationship with the major contractors. The factors influencing the management of subcontractors in building development projects includes performance of significant past projects, standard of workmanship, consistence with guidelines, regular payment to labourers, adherence to program, regularity and viability of communication with main contractor, adherence to subcontract necessities. Other factors comprise adherence to statutory environmental regulations, number of experienced sites administrative staff, inspection and maintenance of good workplace, number of artisans and workers, quality of as-built and shop drawings and ability to carry out the quantity of work and so on. This study also aimed to suggest a way forward to improve the performance of subcontractors which is the reason for exceeding budget at the project sites. To carry out this study, a questionnaire was drafted to derive information on the causes of low performance of subcontractors and the implication to cost.

Keywords: performance, contractor, subcontractors, construction

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Authors: Vera Sovkova, Andrea Mickova, Matej Buzgo, Karolina Vocetkova, Eva Filova, Evzen Amler

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PCL (poly-ε-caprolactone) nanofibrous scaffolds with adhered liposomes were prepared and tested as a possible drug delivery system for various synthetic growth factors. TGFβ, bFGF, and IGF-I have been shown to increase hMSC (human mesenchymal stem cells) proliferation and to induce hMSC differentiation. Functionalized PCL nanofibers were prepared with synthetic growth factors encapsulated in liposomes adhered to them in three different concentrations. Other samples contained PCL nanofibers with adhered, free synthetic growth factors. The synthetic growth factors free medium served as a control. The interaction of liposomes with the PCL nanofibers was visualized by SEM, and the release kinetics were determined by ELISA testing. The potential of liposomes, immobilized on the biodegradable scaffolds, as a delivery system for synthetic growth factors, and as a suitable system for MSCs adhesion, proliferation and differentiation in vitro was evaluated by MTS assay, dsDNA amount determination, confocal microscopy, flow cytometry and real-time PCR. The results showed that the growth factors adhered to the PCL nanofibers stimulated cell proliferation mainly up to day 11 and that subsequently their effect was lower. By contrast, the release of the lowest concentration of growth factors from liposomes resulted in gradual proliferation of MSCs throughout the experiment. Moreover, liposomes, as well as free growth factors, stimulated type II collagen production, which was confirmed by immunohistochemical staining using monoclonal antibody against type II collagen. The results of this study indicate that growth factors enriched liposomes adhered to surface of PCL nanofibers could be useful as a drug delivery instrument for application in short timescales, be combined with nanofiber scaffolds to promote local and persistent delivery while mimicking the local microenvironment. This work was supported by project LO1508 from the Ministry of Education, Youth and Sports of the Czech Republic

Keywords: drug delivery, growth factors, hMSC, liposomes, nanofibres

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Authors: Jyh-Yi Shih, Chie-Bein Chen, Kuang-Yi Lin, Yu-Wei Huang

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Because of the trend toward globalization, Taiwanese companies have gradually focused more on overseas market operations. Overseas market performance has gradually increased as a proportion of Taiwanese companies’ total business revenues. Existing international investment theories cannot explain numerous new phenomena in this domain. Opinions are inconsistent, and contradictory positions exist regarding the antecedents of multinational enterprise (MNE) performance. This study applied contemporary internalization theory to establish and extend approaches adopted by previous relevant studies. In the context of the overseas market, the influence that MNE investment in research and development (R&D) and marketing has on enterprise performance was investigated from the firm-specific advantages (FSAs) and country-specific advantages (CSAs) perspectives. CSAs and internationalization speed were addressed as moderators, and hypotheses regarding how internationalization and performance were achieved through MNE overseas market operation were explored to ensure the completeness of the investigation. The list of enterprises was sourced from the Taiwan Economic Journal. After examining the relevant data, the following conclusions were obtained: (a) The relationship between the level of FSAs in R&D and enterprise performance exhibited an S-shaped curve. (b) The relationship between the level of FSAs in marketing and enterprise performance displayed a U-shaped curve. (c) The extent to which potential CFAs were obtained positively moderated the relationship between enterprise investment in R&D to gain FSAs and MNE performance. (d) Internationalization speed positively moderated the relationship between MNEs and enterprise investment in R&D and marketing to gain FSAs.

Keywords: multinational corporation, firm-specific advantages, country-specific advantages, international speed

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Authors: Hung Lin-Zin, Lai Mei-Yen

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Prostate cancer is the most commonly diagnosed male cancer in the U.S. The prevalence is around 1 in 8. The etiology of prostate cancer is still unknown, but some predisposing factors, such as age, black race, family history, and obesity, may increase the risk of the disease. In 2020, a total of 7,178 Taiwanese people were nearly diagnosed with prostate cancer, accounting for 5.88% of all cancer cases, and the incidence rate ranked fifth among men. In that year, the total number of deaths from prostate cancer was 1,730, accounting for 3.45% of all cancer deaths, and the death rate ranked 6th among men, accounting for 94.34% of the cases of male reproductive organs. Looking for domestic and foreign literature on the use of OMOP (Observational Medical Outcomes Partnership, hereinafter referred to as OMOP) database analysis, there are currently nearly a hundred literature published related to nursing-related health problems and nursing measures built in the OMOP general data model database of medical institutions are extremely rare. The OMOP common data model construction analysis platform is a system developed by the FDA in 2007, using a common data model (common data model, CDM) to analyze and monitor healthcare data. It is important to build up relevant nursing information from the OMOP- CDM database to assist our daily practice. Therefore, we choose prostate cancer patients who are our popular care objects and use the OMOP- CDM database to explore the common associated health problems. With the assistance of OMOP-CDM database analysis, we can expect early diagnosis and prevention of prostate cancer patients' comorbidities to improve patient care.

Keywords: OMOP, nursing diagnosis, health problem, prostate cancer

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Authors: Valentina Narvaez Gaitan, Laura Valentina Rodriguez Leguizamon, Ruben Dario Hernandez B.

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This work describes a physiological signal emulation system that uses electromyography (EMG) signals obtained from muscle sensors in the first instance. These signals are used to extract their characteristics to model and emulate specific arm movements. The main objective of this effort is to develop a new biomedical software system capable of generating physiological signals through the use of embedded systems by establishing the characteristics of the acquired signals. The acquisition system used was Biosignals, which contains two EMG electrodes used to acquire signals from the forearm muscles placed on the extensor and flexor muscles. Processing algorithms were implemented to classify the signals generated by the arm muscles when performing specific movements such as wrist flexion extension, palmar grip, and wrist pronation-supination. Matlab software was used to condition and preprocess the signals for subsequent classification. Subsequently, the mathematical modeling of each signal is performed to be generated by the embedded system, with a validation of the accuracy of the obtained signal using the percentage of cross-correlation, obtaining a precision of 96%. The equations are then discretized to be emulated in the embedded system, obtaining a system capable of generating physiological signals according to the characteristics of medical analysis.

Keywords: classification, electromyography, embedded system, emulation, physiological signals

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Authors: Hafiz Haseeb Nisar, Maryam Bilal

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This qualitative study was conducted to investigate the underlying dynamics, key success factors and characteristics of Pakistani business leaders. The sample included 5 top businessmen from different business sectors. They were approached through the magazine “Manager Today” office in Lahore. Semi-structured interview technique was used to understand their experiences, attitudes, styles of management and key factors in their business success. Grounded theory was employed to analyze data. The following themes emerged as characteristics of business leaders: optimism, assertiveness, professionalism, effective management style, business knowledge/ excellence, supportive family and strong faith in God. It was noted that all these were interlinked, which leads the businessmen to become a successful business tycoon of this country. The importance of this study rests in its eastern contribution to the theoretical framework of the psychology of business leaders and particularly these findings will help to realize the basic key factors of success behind a business leader in Pakistan.

Keywords: business psychology, characteristics, key personality factors, leadership

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Authors: K. Khanafer

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The aim of this investigation was to validate the fluid-structure interaction (FSI) model of type B aortic dissection with our experimental results from a bench-top-model. Another objective was to study the relationship between the size of a septectomy that increases the outflow of the false lumen and its effect on the values of the differential of pressure between true lumen and false lumen. FSI analysis based on Galerkin’s formulation was used in this investigation to study flow pattern and hemodynamics within a flexible type B aortic dissection model using boundary conditions from our experimental data. The numerical results of our model were verified against the experimental data for various tear size and location. Thus, CFD tools have a potential role in evaluating different scenarios and aortic dissection configurations.

Keywords: aortic dissection, fluid-structure interaction, in vitro model, numerical

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Authors: Antoni Wibowo, Harry Pujianto, Dewi Retno Sari Saputro

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The stock market can provide huge profits in a relatively short time in financial sector; however, it also has a high risk for investors and traders if they are not careful to look the factors that affect the stock market. Therefore, they should give attention to the dynamic fluctuations and movements of the stock market to optimize profits from their investment. In this paper, we present a nonlinear autoregressive exogenous model (NARX) to predict the movements of stock market; especially, the movements of the closing price index. As case study, we consider to predict the movement of the closing price in Indonesia composite index (IHSG) and choose the best structures of NARX for IHSG’s prediction.

Keywords: NARX (Nonlinear Autoregressive Exogenous Model), prediction, stock market, time series

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Authors: Zanjbeel Tabassum, Cahit Ali Bayraktar, Asfa Muhammad Din, Murat Durucu

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Six Sigma is a widely adapted quality improvement methodology applied throughout the world. Through this paper, an attempt has been made to identify Critical Success Factors (CSF) for successful implementation of Six Sigma in Pakistani Small and Medium-sized Enterprises (SMEs). A survey methodology was used to collect the data from SMEs in Pakistan. The results of this exploratory empirical research reflect the importance of different CSFs of Six Sigma implementation in SMEs in Pakistan. On the basis of extracted factors, a framework has been proposed for successful Six Sigma implementation in Pakistani SMEs. This study will provide a base for Pakistani SMEs and future researchers working in Six Sigma implementation and help them to prepare a road map to eradicate the hurdles in Six Sigma implementation.

Keywords: critical success factors, small medium enterprises (SMEs), six sigma, Pakistan

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Authors: Md Yeasin, Ranjit Kumar Paul

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In recent years, recommendation systems have become indispensable tools for agricultural system. The accurate and timely recommendations can significantly impact crop yield and overall productivity. Causal inference modeling aims to establish cause-and-effect relationships by identifying the impact of variables or factors on outcomes, enabling more accurate and reliable recommendations. New advancements in causal inference models have been found in the literature. With the advent of the modern era, deep learning and machine learning models have emerged as efficient tools for modeling. This study proposed an innovative approach to enhance recommendation systems-based machine learning based casual inference model. By considering the causal effect and opportunity cost of covariates, the proposed system can provide more reliable and actionable recommendations for cereal farmers. To validate the effectiveness of the proposed approach, experiments are conducted using cereal cultivation data of eastern India. Comparative evaluations are performed against existing correlation-based recommendation systems, demonstrating the superiority of the advanced causal inference modeling approach in terms of recommendation accuracy and impact on crop yield. Overall, it empowers farmers with personalized recommendations tailored to their specific circumstances, leading to optimized decision-making and increased crop productivity.

Keywords: agriculture, casual inference, machine learning, recommendation system

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Authors: Guenther Schuh, Michael Riesener, Frederic Diels

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Nowadays, manufacturing companies are faced with the challenge of meeting heterogeneous customer requirements in short product life cycles with a variety of product functions. So far, some of the functional requirements remain unknown until late stages of the product development. A way to handle these uncertainties is the highly iterative product development (HIP) approach. By structuring the development project as a highly iterative process, this method provides customer oriented and marketable products. There are first approaches for combined, hybrid models comprising deterministic-normative methods like the Stage-Gate process and empirical-adaptive development methods like SCRUM on a project management level. However, almost unconsidered is the question, which development scopes can preferably be realized with either empirical-adaptive or deterministic-normative approaches. In this context, a development scope constitutes a self-contained section of the overall development objective. Therefore, this paper focuses on a methodology that deals with the uncertainty of requirements within the early development stages and the corresponding selection of the most appropriate development approach. For this purpose, internal influencing factors like a company’s technology ability, the prototype manufacturability and the potential solution space as well as external factors like the market accuracy, relevance and volatility will be analyzed and combined into an Agile-Indicator. The Agile-Indicator is derived in three steps. First of all, it is necessary to rate each internal and external factor in terms of the importance for the overall development task. Secondly, each requirement has to be evaluated for every single internal and external factor appropriate to their suitability for empirical-adaptive development. Finally, the total sums of internal and external side are composed in the Agile-Indicator. Thus, the Agile-Indicator constitutes a company-specific and application-related criterion, on which the allocation of empirical-adaptive and deterministic-normative development scopes can be made. In a last step, this indicator will be used for a specific clustering of development scopes by application of the fuzzy c-means (FCM) clustering algorithm. The FCM-method determines sub-clusters within functional clusters based on the empirical-adaptive environmental impact of the Agile-Indicator. By means of the methodology presented in this paper, it is possible to classify requirements, which are uncertainly carried out by the market, into empirical-adaptive or deterministic-normative development scopes.

Keywords: agile, highly iterative development, agile-indicator, product development

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Authors: Stefan Peters, Phillip Roetman

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The global loss of biodiversity is threatening the benefits nature provides to human populations and has become a more pressing issue than climate change and requires immediate attention. While there have been successful global agreements for environmental protection, such as the Montreal Protocol, these are rare, and we cannot rely on them solely. Thus, it is crucial to take national and local actions to support biodiversity. Australia is one of the 17 countries in the world with a high level of biodiversity, and its cities are vital habitats for endangered species, with more of them found in urban areas than in non-urban ones. However, the protection of biodiversity in metropolitan Adelaide has been inadequate, with over 130 species disappearing since European colonization in 1836. In this research project we conceptualized, developed and implemented a framework for wildlife Habitat Hotspots and Habitat Corridor modelling in an urban context using geographic data and GIS modelling and analysis. We used detailed topographic and other geographic data provided by a local council, including spatial and attributive properties of trees, parcels, water features, vegetated areas, roads, verges, traffic, and census data. Weighted factors considered in our raster-based Habitat Hotspot model include parcel size, parcel shape, population density, canopy cover, habitat quality and proximity to habitats and water features. Weighted factors considered in our raster-based Habitat Corridor model include habitat potential (resulting from the Habitat Hotspot model), verge size, road hierarchy, road widths, human density, and presence of remnant indigenous vegetation species. We developed a GIS model, using Python scripting and ArcGIS-Pro Model-Builder, to establish an automated reproducible and adjustable geoprocessing workflow, adaptable to any study area of interest. Our habitat hotspot and corridor modelling framework allow to determine and map existing habitat hotspots and wildlife habitat corridors. Our research had been applied to the study case of Burnside, a local council in Adelaide, Australia, which encompass an area of 30 km2. We applied end-user expertise-based category weightings to refine our models and optimize the use of our habitat map outputs towards informing local strategic decision-making.

Keywords: biodiversity, GIS modeling, habitat hotspot, wildlife corridor

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Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

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In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

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Authors: Vichada Chokesikarin

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The study aims to determine which factors account for customer satisfaction and to investigate the relationship between entrepreneurial orientation and business success, in particular, context of the information understanding of hostel business in Pranakorn district, Bangkok and the significant element of entrepreneurship in tourism industry. This study covers 352 hostels customers and 61 hostel owners/managers nearby Khao San Road. Data collection methods were used by survey questionnaire and a series of hypotheses were developed from services marketing literature. The findings suggest the customer satisfaction most influenced by image, service quality, room quality and price accordingly. Furthermore the findings revealed that significant relationships exist between entrepreneurial orientation and business success; while competitive aggressiveness was found unrelated. The ECSI model’s generic measuring customer satisfaction was found partially mediate the business success. A reconsideration of other variables applicable should be supported with the model of hostel business. The study provides context and overall view of hostel business while discussing from the entrepreneurial orientation to customer satisfaction, thereby reducing decision risk on hostel investment.

Keywords: customer satisfaction, ECSI model, entrepreneurial orientation, small hotel, hostel, business performance

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Authors: Christopher Reichstein, Ralf-Christian Härting, Martina Häußler

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With a continuously increasing speed of information exchange on the World Wide Web, retailers in the E-Commerce sector are faced with immense possibilities regarding different online purchase processes like dynamic price settings. By use of Dynamic Pricing, retailers are able to set short time price changes in order to optimize producer surplus. The empirical research illustrates the basics of Dynamic Pricing and identifies six influencing factors of Dynamic Pricing. The results of a structural equation modeling approach show five main drivers increasing the potential of dynamic price settings in the E-Commerce. Influencing factors are the knowledge of customers’ individual willingness to pay, rising sales, the possibility of customization, the data volume and the information about competitors’ pricing strategy.

Keywords: e-commerce, empirical research, experts, dynamic pricing (DP), influencing factors, potentials

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Authors: Saadia Drissi

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The cloud computing is an innovative paradigm that introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. As consequence, there is a need of risk assessment model adapted to cloud computing. This paper requires a new risk assessment model based on multi-agent system and AHP model as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.

Keywords: cloud computing, risk assessment model, multi-agent system, AHP model, cloud consumer

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Authors: R. M. Rajapaksa

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Construction industry is one of the key players in driving the economy of a country to achieve its prosperity. However, a dispute is one of the crucial factors which prevent the completion of construction contracts within the budgeted cost, scheduled time, and accepted quality. Disputes are inevitable in the construction contract. Accordingly, a study has been undertaken to identify the factors affecting contractual disputes in construction projects in Sri Lanka. The study was a mixed approach with major qualitative and minor quantitative. Qualitative study was set in the form of in-depth interviews with eighteen participants, and quantitative study was conducted using a questionnaire with twenty-four respondents from previously implemented projects by the National Water Supply & Drainage Board representing the employer, engineer and the Contractor to identify the factors affecting contractual disputes and to verify most critical factors respectively. Data analysis for qualitative and quantitative studies was carried out by means of transcribing, code & categorizeand average score methods, respectively. The study reveals that there are forty factors affecting the contractual disputes in construction contracts in Sri Lanka. The finding further illustrates that conflicting decisions by inexperience personnel in the higher position of the Employer, ambiguities resulting inadequate descriptions of the preliminary/general items in price schedule, unfair valuation and late confirmation of variations, unfair determination due to lack of experience of the Engineer/Consultant, under certification of progress payments, unfair grant of EOT & application of delay damages, unreasonable claims for variation of works, errors/discrepancies/ambiguities in the contract conditions and discrepancies & errors in designs & specifications are the most critical factors affecting contractual disputes. Finally, the study proposed remedial measures to most critical factors affecting contractual disputes.

Keywords: dispute, contractual, factors, employer, engineer, contractor, construction projects

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Authors: Anyia Nduka, Aslan Bin Amad Senin

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Organizational culture, strategic leadership and organizational resilience have gained significant attention in recent years. This study aims to examine the relationship between these factors and their combined influence on an organization's ability to adapt and thrive in the face of challenges and disruptions. A mixed-methods approach, combining quantitative survey data and qualitative interviews with leaders and employees from cohort organizations within the industry. The quantitative phase involves measuring organizational culture, strategic leadership behaviours, and organizational resilience using standardized scales. This study highlighted the significance of organizational culture and strategic leadership in building and sustaining organizational resilience. Preliminary findings suggest a strong positive relationship between a resilient organizational culture and strategic leadership practices. Secondly, Organizations can enhance their capacity to respond to disruptions, exploit opportunities, and achieve long-term success in a rapidly changing business environment. Furthermore, the qualitative analysis reveals several key themes that elucidate the link between organizational culture, strategic leadership, and resilience. This study contributes to the growing body of knowledge on organizational resilience and strategic leadership, providing insights and practical implications for leaders and practitioners seeking to strengthen their organizations' resilience capabilities. Further research is needed to explore the specific mechanisms and contextual factors that influence the relationship between these variables in different organizational contexts and industries.

Keywords: organizational culture, strategic leadership, organizational resilience, leadership

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Authors: M. F. Wu, F. T. Cheng

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Leather industry is the most important traditional industry to provide the leather products in the world for thousand years. The fierce global competitive environment and common awareness of global carbon reduction make livestock supply quantities falling, salt and wet blue leather material reduces and the price skyrockets significantly. Exchange rate fluctuation led sales revenue decreasing which due to the differences of export exchanges and compresses the overall profitability of leather industry. This paper applies activity-based benefit assessment approach to build up fitness fur input mixed model, fur is Wet Blue, which concerned with four key factors: the output rate of wet blue, unit cost of wet blue, yield rate and grade level of Wet Blue to achieve the low cost strategy under given unit price of leather product condition of the company. The research findings indicate that applying this model may improve the input cost structure, decrease numbers of leather product inventories and to raise the competitive advantages of the enterprise in the future.

Keywords: activity-based benefit assessment approach, input mixed, output rate, wet blue

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Authors: Flavia Cordeiro, Fabio Silva, Alvaro Eiras, Jose Luiz Acebal

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Aedes aegypti is present in the tropical and subtropical regions of the world and is a vector of several diseases such as dengue fever, yellow fever, chikungunya, zika etc. The growth in the number of arboviruses cases in the last decades became a matter of great concern worldwide. Meteorological factors like mean temperature and precipitation are known to influence the infestation by the species through effects on physiology and ecology, altering the fecundity, mortality, lifespan, dispersion behaviour and abundance of the vector. Models able to describe the dynamics of the vector population size should then take into account the meteorological variables. The relationship between meteorological factors and the population dynamics of Ae. aegypti adult females are studied to provide a good set of predictors to model the dynamics of the mosquito population size. The time-series data of capture of adult females of a public health surveillance program from the city of Lavras, MG, Brazil had its association with precipitation, humidity and temperature analysed through a set of statistical methods for time series analysis commonly adopted in Signal Processing, Information Theory and Neuroscience. Cross-correlation, multicollinearity test and whitened cross-correlation were applied to determine in which time lags would occur the influence of meteorological variables on the dynamics of the mosquito abundance. Among the findings, the studied case indicated strong collinearity between humidity and precipitation, and precipitation was selected to form a pair of descriptors together with temperature. In the techniques used, there were observed significant associations between infestation indicators and both temperature and precipitation in short, mid and long terms, evincing that those variables should be considered in entomological models and as public health indicators. A descriptive model used to test the results exhibits a strong correlation to data.

Keywords: Aedes aegypti, cross-correlation, multicollinearity, meteorological variables

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Authors: Khan R. Rahaman, Quazi K. Hassan

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Global changes in climate, environment, economies, populations, governments, institutions, and cultures converge in localities. Changes at a local scale, in turn, contribute to global changes as well as being affected by them. Our hypothesis is built on a consideration that temperature does vary at local level (i.e., termed as local warming) in comparison to the predicted models at the regional and/or global scale. To date, the bulk of the research relating local places to global climate change has been top-down, from the global toward the local, concentrating on methods of impact analysis that use as a starting point climate change scenarios derived from global models, even though these have little regional or local specificity. Thus, our focus is to understand such trends over the southern Alberta, which will enable decision makers, scientists, researcher community, and local people to adapt their policies based on local level temperature variations and to act accordingly. Specific objectives in this study are: (i) to understand the local warming (temperature in particular) trend in context of temperature normal during the period 1961-2010 at point locations using meteorological data; (ii) to validate the data by using specific yearly data, and (iii) to delineate the spatial extent of the local warming trends and understanding influential factors to adopt situation by local governments. Existing data has brought the evidence of such changes and future research emphasis will be given to validate this hypothesis based on remotely sensed data (i.e. MODIS product by NASA).

Keywords: local warming, climate change, urban area, Alberta, Canada

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Authors: Zunaira Asif, Zhi Chen

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The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM_2.5, PM₁₀, NO_x, and SO₂. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NO_x and SO₂ reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.

Keywords: air pollution, linear programming, mining, optimization, treatment technologies

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Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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Authors: Pronab Ganguly, Ahmed A. Moustafa

Abstract:

Holistic management of schizophrenia involves mainstream pharmacological intervention, complimentary medicine intervention, therapeutic intervention and other psychosocial factors such as accommodation, education, job training, employment, relationship, friendship, exercise, overall well-being, smoking, substance abuse, suicide prevention, stigmatisation, recreation, entertainment, violent behaviour, arrangement of public trusteeship and guardianship, day-day-living skill, integration with community, and management of overweight due to medications and other health complications related to medications amongst others. Our review shows that there is no integrated survey by combining all these factors. An international web-based survey was conducted to evaluate the significance of all these factors and present them in a unified manner. It is believed this investigation will contribute positively towards holistic management of schizophrenia. There will be two surveys. In the pharmacological intervention survey, five popular drugs for schizophrenia will be chosen and their efficacy as well as harmful side effects will be evaluated on a scale of 0 -10. This survey will be done by psychiatrists. In the second survey, each element of therapeutic intervention and psychosocial factors will be evaluated according to their significance on a scale of 0 - 10. This survey will be done by care givers, psychologists, case managers and case workers. For the first survey, professional bodies of psychiatrists in English speaking countries will be contacted to request them to ask their members to participate in the survey. For the second survey, professional bodies of clinical psychologist and care givers in English speaking countries will be contacted to request them to ask their members to participate in the survey. Additionally, for both the surveys, relevant professionals will be contacted through personal contact networks. For both the surveys, mean, mode, median, standard deviation and net promoter score will be calculated for each factor and then presented in a statistically significant manner. Subsequently each factor will be ranked according to their statistical significance. Additionally, country specific variation will be highlighted to identify the variation pattern. The results of these surveys will identify the relative significance of each type of pharmacological intervention, each type of therapeutic intervention and each type of psychosocial factor. The determination of this relative importance will definitely contribute to the improvement in quality of life for individuals with schizophrenia.

Keywords: schizophrenia, holistic management, antipsychotics, quality of life

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Authors: Eti Dwi Wiraningsih, Folashade Agusto, Lina Aryati, Syamsuddin Toaha, Suzanne Lenhart, Widodo, Willy Govaerts

Abstract:

This paper considers a deterministic model for the transmission dynamics of rabies virus in the wild dogs-domestic dogs-human zoonotic cycle. The effect of vaccination and culling in dogs is considered on the model, then the stability was analysed to get basic reproduction number. We use the next generation matrix method and Routh-Hurwitz test to analyze the stability of the Disease-Free Equilibrium and Endemic Equilibrium of this model.

Keywords: stability analysis, rabies model, vaccination effect, culling in dogs

Procedia PDF Downloads 611

Authors: Pierluigi Gallo, Francesco Randazzo, Ignazio Gallo

Abstract:

In recent years, many new and interesting models of successful online business have been developed. Many of these are based on the competition between users, such as online auctions, where the product price is not fixed and tends to rise. Other models, including group-buying, are based on cooperation between users, characterized by a dynamic price of the product that tends to go down. There is not yet a business model in which both sellers and buyers are grouped in order to negotiate on a specific product or service. The present study investigates a new extension of the group-buying model, called fair, which allows aggregation of demand and supply for price optimization, in a cooperative manner. Additionally, our system also aggregates products and destinations for shipping optimization. We introduced the following new relevant input parameters in order to implement a double-side aggregation: (a) price-quantity curves provided by the seller; (b) waiting time, that is, the longer buyers wait, the greater discount they get; (c) payment time, which determines if the buyer pays before, during or after receiving the product; (d) the distance between the place where products are available and the place of shipment, provided in advance by the buyer or dynamically suggested by the system. To analyze the proposed model we implemented a system prototype and a simulator that allows studying effects of changing some input parameters. We analyzed the dynamic price model in fairs having one single seller and a combination of selected sellers. The results are very encouraging and motivate further investigation on this topic.

Keywords: auction, aggregation, fair, group buying, social buying

Procedia PDF Downloads 282

Authors: Reza Safari, Ali Rajabzadeh Ghatari, Raheleh Hossseinzadeh Mahabadi

Abstract:

In the present world, there are different pressures on firms such as competition, legislations, social etc. these pressures force the firms to follow “survival” as their primary goal and then growth. One of the main factors that helps firms to reach their goals is proper financial performance. To find out about the financial performance, a firm should monitors its financial performance. Financial performance affected by many factors. This research seeks to clear which financial performance indicators are most important according to Environmental situation of a firm and what are their priorities. To do so, environmental indicators specified as presented on OECD Key Environmental Indicators 2008 and so the financial performance indicators such as Profitability, Liquidity, Gearing, Investor ratios, and etc. At this stage, the affections questioned through questionnaires. After gaining the results, data analyzed using Promethee technique. By using decision matrixes extracted from those techniques an expert system designed. This expert system suggests the suitable financial performance indicators and their ranking by receiving the environment situation given environment indicators weight.

Keywords: environment indicators, financial performance indicators, promethee, expert system

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Authors: Bernard Kumi-Boateng, Issaka Yakubu

Abstract:

Forest fire, which is, an uncontrolled fire occurring in nature has become a major concern for the Forestry Commission of Ghana (FCG). The forest fires in Ghana usually result in massive destruction and take a long time for the firefighting crews to gain control over the situation. In order to assess the effect of forest fire at local scale, it is important to consider the role fire plays in vegetation composition, biodiversity, soil erosion, and the hydrological cycle. The occurrence, frequency and behaviour of forest fires vary over time and space, primarily as a result of the complicated influences of changes in land use, vegetation composition, fire suppression efforts, and other indigenous factors. One of the forest zones in Ghana with a high level of vegetation stress is the Goaso forest area. The area has experienced changes in its traditional land use such as hunting, charcoal production, inefficient logging practices and rural abandonment patterns. These factors which were identified as major causes of forest fire, have recently modified the incidence of fire in the Goaso area. In spite of the incidence of forest fires in the Goaso forest area, most of the forest services do not provide a cartographic representation of the burned areas. This has resulted in significant amount of information being required by the firefighting unit of the FCG to understand fire risk factors and its spatial effects. This study uses Remote Sensing and Geographic Information System techniques to develop a fire risk hazard model using the Goaso Forest Area (GFA) as a case study. From the results of the study, natural forest, agricultural lands and plantation cover types were identified as the major fuel contributing loads. However, water bodies, roads and settlements were identified as minor fuel contributing loads. Based on the major and minor fuel contributing loads, a forest fire risk hazard model with a reasonable accuracy has been developed for the GFA to assist decision making.

Keywords: forest, GIS, remote sensing, Goaso

Procedia PDF Downloads 435