Search results for: sustainable business model

Authors: Parisa Moghaddam

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The significance of this study lies in its comprehensive exploration of renewable energy integration in poultry farming, a highly energy-intensive sector, to address pressing global food and energy crisis. As population growth amplifies these issues, innovative solutions are crucial for sustainable food production and energy security. This research investigated the potential of renewable energy sources, particularly anaerobic digestion and solar photovoltaics, to reduce energy consumption, mitigate greenhouse gas emissions, promote circular economy principles in agriculture, and reduce reliance on fossil fuels. By examining case studies from various countries and analyzing the economic and environmental benefits of these technologies, the study aimed to provide practical insights for farmers, stakeholders, and policymakers. Ultimately, this research developed a conceptual tool and framework to facilitate the transition towards more sustainable and circular agricultural practices, addressing critical gaps in renewable energy integration within agricultural systems, and aiming to attract potential investors and gain traction for sustainable practices. The study employed a mixed-methods approach, combining quantitative and qualitative analyses to provide a comprehensive evaluation framework for renewable energy integration in agriculture. Key components included a case study analysis utilizing data from a poultry operation in Armenia, an anaerobic digestion plant in Pakistan, and a solar photovoltaic project in Lebanon. A comprehensive literature review was conducted to understand the current state of renewable energy adoption, challenges, and opportunities in poultry farming. For quantitative analysis, the study used Cost-Benefit Analysis (CBA) to assign monetary values to costs and benefits of renewable energy investment projects, including economic valuation, financial budgeting, and cash flow considerations to compare two modes of renewable energy sources. The qualitative approach utilized Multi-Criteria Decision-Making (MCDM) to evaluate and prioritize alternatives based on multiple criteria, incorporating both objective and subjective factors beyond economic viability. Additionally, sensitivity analysis was conducted for more accurate modeling. Key findings revealed that on-farm anaerobic digester plants focusing on biogas and digestate production, rather than electricity generation, demonstrated economic viability with a Net Present Value of $621,386.3 and an Internal Rate of Return of 149%. Solar PV implementation showed moderate economic potential. The Multi-Criteria Decision-Making analysis, incorporating economic, technical, environmental, and social criteria, ranked anaerobic digesters (0.91) higher than solar PV (0.64) for agricultural applications. The findings suggest that small-scale anaerobic digesters offer the most promising pathway for agricultural waste valorization and renewable energy generation. However, successful implementation requires addressing limitations such as financial uncertainties, lack of accurate data, industry collaboration, and policy support. This research contributes to the growing body of knowledge on circular economy implementation in agriculture, offering practical insights for sustainable development in similar economic contexts.

Keywords: circular economy, renewable energy integration, sustainable poultry farming, anaerobic digestion, solar photovoltaics, sustainability, cost-benefit analysis, multi-criteria decision making, economic modeling

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Authors: Guanhua Zhou, Zhongqi Ma

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Submerged aquatic vegetation (SAV) in wetlands can absorb nitrogen and phosphorus effectively to prevent the eutrophication of water. It is feasible to monitor the distribution of SAV through remote sensing, but for the reason of weak vegetation signals affected by water body, traditional terrestrial vegetation indices are not applicable. This paper aims at constructing SAV index to enhance the vegetation signals and distinguish SAV from water body. The methodology is as follows: (1) select the bands sensitive to the vegetation parameters based on global sensitivity analysis of SAV canopy radiative transfer model; (2) take the soil line concept as reference, analyze the distribution of SAV and water reflectance simulated by SAV canopy model and semi-analytical water model in the two-dimensional space built by different sensitive bands; (3)select the band combinations which have better separation performance between SAV and water, and use them to build the SAVI indices in the form of normalized difference vegetation index(NDVI); (4)analyze the sensitivity of indices to the water and vegetation parameters, choose the one more sensitive to vegetation parameters. It is proved that index formed of the bands with central wavelengths in 705nm and 842nm has high sensitivity to chlorophyll content in leaves while it is less affected by water constituents. The model simulation shows a general negative, little correlation of SAV index with increasing water depth. Moreover, the index enhances capabilities in separating SAV from water compared to NDVI. The SAV index is expected to have potential in parameter inversion of wetland remote sensing.

Keywords: global sensitivity analysis, radiative transfer model, submerged aquatic vegetation, vegetation indices

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Authors: S. Khamtree, T. Ratanawilai, C. Nuntadusit

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Rubberwood is a crucial commercial timber in Southern Thailand. All processes in a rubberwood production depend on the knowledge and expertise of the technicians, especially the drying process. This research aims to develop an empirical model for drying kinetics in rubberwood. During the experiment, the temperature of the hot air and the average air flow velocity were kept at 80-100 °C and 1.75 m/s, respectively. The moisture content in the samples was determined less than 12% in the achievement of drying basis. The drying kinetic was simulated using an empirical solver. The experimental results illustrated that the moisture content was reduced whereas the drying temperature and time were increased. The coefficient of the moisture ratio between the empirical and the experimental model was tested with three statistical parameters, R-square (R²), Root Mean Square Error (RMSE) and Chi-square (χ²) to predict the accuracy of the parameters. The experimental moisture ratio had a good fit with the empirical model. Additionally, the results indicated that the drying of rubberwood using the Henderson and Pabis model revealed the suitable level of agreement. The result presented an excellent estimation (R² = 0.9963) for the moisture movement compared to the other models. Therefore, the empirical results were valid and can be implemented in the future experiments.

Keywords: empirical models, rubberwood, moisture ratio, hot air drying

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Authors: Farnaz Farzin, Julie C. Thomson, Rob Dekkers, Geoff Whittam

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Research has shown that techno-entrepreneurship is economically significant. Therefore, it is suggested that teaching techno-entrepreneurship may be important because such programmes would prepare current and future generations of learners to recognize and act on high-technology opportunities. Education in techno-entrepreneurship may increase the knowledge of how to start one’s own enterprise and recognize the technological opportunities for commercialisation to improve decision-making about starting a new venture; also it influence decisions about capturing the business opportunities and turning them into successful ventures. Universities can play a main role in connecting and networking techno-entrepreneurship students towards a cooperative attitude with real business practice and industry knowledge. To investigate and answer whether education for techno-entrepreneurs really helps, this paper chooses a comparison of literature reviews as its method of research. Then, 6 different studies were selected. These particular papers were selected based on a keywords search and as their aim, objectives, and gaps were close to the current research. In addition, they were all based on the influence of techno-entrepreneurship education in self-employment and intention of students to start new ventures. The findings showed that teaching techno-entrepreneurship education may have an influence on students’ intention and their future self-employment, but which courses should be covered and the duration of programmes needs further investigation.

Keywords: techno entrepreneurship education, training, higher education, intention, self-employment

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Authors: Cagri Baris Kasap

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In this study, how interface designers can be viewed as producers of culture in the current era will be interrogated from a critical theory perspective. Walter Benjamin was a German Jewish literary critical theorist who, during 1930s, was engaged in opposing and criticizing the Nazi use of art and media. ‘The Author as Producer’ is an essay that Benjamin has read at the Communist Institute for the Study of Fascism in Paris. In this article, Benjamin relates directly to the dialectics between base and superstructure and argues that authors, normally placed within the superstructure should consider how writing and publishing is production and directly related to the base. Through it, he discusses what it could mean to see author as producer of his own text, as a producer of writing, understood as an ideological construct that rests on the apparatus of production and distribution. So Benjamin concludes that the author must write in ways that relate to the conditions of production, he must do so in order to prepare his readers to become writers and even make this possible for them by engineering an ‘improved apparatus’ and must work toward turning consumers to producers and collaborators. In today’s world, it has become a leading business model within Web 2.0 services of multinational Internet technologies and culture industries like Amazon, Apple and Google, to transform readers, spectators, consumers or users into collaborators and co-producers through platforms such as Facebook, YouTube and Amazon’s CreateSpace Kindle Direct Publishing print-on-demand, e-book and publishing platforms. However, the way this transformation happens is tightly controlled and monitored by combinations of software and hardware. In these global-market monopolies, it has become increasingly difficult to get insight into how one’s writing and collaboration is used, captured, and capitalized as a user of Facebook or Google. In the lens of this study, it could be argued that this criticism could very well be considered by digital producers or even by the mass of collaborators in contemporary social networking software. How do software and design incorporate users and their collaboration? Are they truly empowered, are they put in a position where they are able to understand the apparatus and how their collaboration is part of it? Or has the apparatus become a means against the producers? Thus, when using corporate systems like Google and Facebook, iPhone and Kindle without any control over the means of production, which is closed off by opaque interfaces and licenses that limit our rights of use and ownership, we are already the collaborators that Benjamin calls for. For example, the iPhone and the Kindle combine a specific use of technology to distribute the relations between the ‘authors’ and the ‘prodUsers’ in ways that secure their monopolistic business models by limiting the potential of the technology.

Keywords: interface designer, cultural producer, Walter Benjamin, materialist aesthetics, dialectical thinking

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Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

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Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion process, trends functions, bi-parameters weibull density function

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Authors: Bruno Pinto Vieira, Marco Antonio Calijorne Soares, Armando Sérgio de Aguiar Filho

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Nowadays, a massive amount of information has been produced by different data sources, including mobile devices and transactional systems. In this scenario, concerns arise on how to maintain or establish data quality, which is now treated as a product to be defined, measured, analyzed, and improved to meet consumers' needs, which is the one who uses these data in decision making and companies strategies. Information that reaches low levels of quality can lead to issues that can consume time and money, such as missed business opportunities, inadequate decisions, and bad risk management actions. The step of selecting, identifying, evaluating, and selecting data sources with significant quality according to the need has become a costly task for users since the sources do not provide information about their quality. Traditional data quality control methods are based on user experience or business rules limiting performance and slowing down the process with less than desirable accuracy. Using advanced machine learning algorithms, it is possible to take advantage of computational resources to overcome challenges and add value to companies and users. In this study, machine learning is applied to data quality analysis on different datasets, seeking to compare the performance of the techniques according to the dimensions of quality assessment. As a result, we could create a ranking of approaches used, besides a system that is able to carry out automatically, data quality assessment.

Keywords: machine learning, data quality, quality dimension, quality assessment

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Authors: Elham Taghizadeh, Mostafa Abedzadeh, Mostafa Setak

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Logistics network is expected that opened facilities work continuously for a long time horizon without any failure; but in real world problems, facilities may face disruptions. This paper studies a reliable joint inventory location problem to optimize cost of facility locations, customers’ assignment, and inventory management decisions when facilities face failure risks and doesn’t work. In our model we assume when a facility is out of work, its customers may be reassigned to other operational facilities otherwise they must endure high penalty costs associated with losing service. For defining the model closer to real world problems, the model is proposed based on p-median problem and the facilities are considered to have limited capacities. We define a new binary variable (Z_is) for showing that customers are not assigned to any facilities. Our problem involve a bi-objective model; the first one minimizes the sum of facility construction costs and expected inventory holding costs, the second one function that mention for the first one is minimizes maximum expected customer costs under normal and failure scenarios. For solving this model we use NSGAII and MOSS algorithms have been applied to find the pareto- archive solution. Also Response Surface Methodology (RSM) is applied for optimizing the NSGAII Algorithm Parameters. We compare performance of two algorithms with three metrics and the results show NSGAII is more suitable for our model.

Keywords: joint inventory-location problem, facility location, NSGAII, MOSS

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Authors: Azeez Balogun

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Inexperienced building score practices are continually evolving and vary across areas. Yet, a few middle ideas stay steady, such as website selection, design, energy efficiency, water and material conservation, indoor environmental great, operational optimization, and waste discount. The essence of green building lies inside the optimization of 1 or more of those standards. This paper conducts a comparative analysis of 7 extensively recognized sustainable score structures—BREEAM, CASBEE, green GLOBES, inexperienced superstar, HK-BEAM, IGBC green homes, and LEED—based totally on the perceptions and opinions of stakeholders in Nigeria certified in green constructing rating systems. The purpose is to pick out and adopt an appropriate green building rating device for Nigeria. Numerous components of those systems had been tested to determine the high-quality health of the Nigerian built environment. The findings imply that LEED, the important machine within the USA and Canada, is the most suitable for Nigeria due to its sturdy basis, extensive funding, and confirmed blessings. LEED obtained the highest rating of eighty out of one hundred points on this assessment.

Keywords: structure, built surroundings, inexperienced building score gadget, Nigeria Inexperienced Constructing Council, sustainability

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Hamidrza Joodaki

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The most complex issue in urban land use planning is site selection that needs to assess the verity of elements and factors. Multi Criteria Decision Making (MCDM) methods are the best approach to deal with complex problems. In this paper, combination of the analytical hierarchy process (AHP) model and FUZZY logic was used as MCDM methods to select the best site for gas station in the 4th gas zone of Tehran. The first and the most important step in FUZZY-AHP model is selection of criteria and sub-criteria. Population, accessibility, proximity and natural disasters were considered as the main criteria in this study. After choosing the criteria, they were weighted based on AHP by EXPERT CHOICE software, and FUZZY logic was used to enhance accuracy and to approach the reality. After these steps, criteria layers were produced and weighted based on FUZZY-AHP model in GIS. Finally, through ARC GIS software, the layers were integrated and the 4th gas zone in TEHRAN was selected as the best site to locate gas station.

Keywords: multiple criteria decision making (MCDM), analytic hierarchy process (AHP), FUZZY logic, geographic information system (GIS)

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Authors: Sankar Majumder

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Development of Rural Entrepreneurs requires a holistic approach involving social, economic, political, technical, and environmental and many other issues. It needs a thorough understanding of the economy and society. It's true that agricultural development, rural development and many other social and right based development programmes have resulted in the growth of income in the rural sector. The development of rural entrepreneurs is necessary to utilise these opportunities. Many programmes and policies in the spheres of organisational, financial, infrastructural and technical supports have been taken to promote rural industries. But if one looks at the growth and development of rural industrial units, especially the manufacturing units, the picture is not promising. This paper aims at analysing the possible causes and its solutions in terms of (1) Mind set of the society towards business as a livelihood; (2) Sufficiency and appropriateness of the existing organisational, financial, infrastructural and technical supports. The paper is based on secondary data on various aspects of rural enterprises and the author’s experiences in the course of his work as a practitioner in this field. Growth of units and employment in the rural industries shows that the entrepreneurs are more inclined towards trading units than towards manufacturing ventures. The growth of rural industries is constrained not by the insufficiency of the supply of finance but by the insufficient demand for finance. The task is to increase the supply of entrepreneurs by creating an entrepreneurial environment. Incubation for rural entrepreneurs is the need of the hour.

Keywords: business mind set, entrepreneurial environment, supply of finance, technical support

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Authors: Rania Sherif Abd El-Azim

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The role of corporate social responsibility (CSR) in business has evolved and led to an era where industry leaders can no longer overlook the importance of being participative corporate citizens. This is not only because of the media’s skeptical attitude toward whether or not companies’ CSR efforts are sincere but also due to key stakeholders’ ability to hold companies to a higher standard than ever before as companies can gain competitive advantage through CSR. These programs result in addressing global challenges, such as climate, and poverty, or simply improving employee retention, so it has become increasingly clear that CSR is not just the new trend for companies but a necessary tool that organizations must integrate into their overall business strategies to build a stronger reputation as well as to also increase credibility among their key audience and enhance customers’ willingness to repurchase, pay premium price and enhancing positive word of mouth. According to the literature review, the link between CSR and competitive advantage at the firm level has long been an important topic for both CSR researchers and practitioners. Thus CSR can play an important role in enhancing the firm's competitive advantage, which seems an attractive area to investigate specially in Egypt. So, this paper will investigate the role of corporate social responsibility in enhancing the firm competitive advantage.

Keywords: corporate social responsibility, competitive advantage, corporate reputation, customers' willingness to repurchase, willingness to pay premium price, positive word of mouth

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Authors: Pedram Saadati, Zahra Nazari

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In the last decade, the role and importance of knowledge-based technological businesses in the insurance industry has greatly increased, and due to the weakness of previous studies in Iran, the current research deals with the design of the InsurTech empowerment model. In order to obtain the conceptual model of the research, a hybrid framework has been used. The statistical population of the research in the qualitative part were experts, and in the quantitative part, the InsurTech activists. The tools of data collection in the qualitative part were in-depth and semi-structured interviews and structured self-interaction matrix, and in the quantitative part, a researcher-made questionnaire. In the qualitative part, 55 indicators, 20 components and 8 concepts (dimensions) were obtained by the content analysis method, then the relationships of the concepts with each other and the levels of the components were investigated. In the quantitative part, the information was analyzed using the descriptive analytical method in the way of path analysis and confirmatory factor analysis. The proposed model consists of eight dimensions of supporter capability, supervisor of insurance innovation ecosystem, managerial, financial, technological, marketing, opportunity identification, innovative InsurTech capabilities. The results of statistical tests in identifying the relationships of the concepts with each other have been examined in detail and suggestions have been presented in the conclusion section.

Keywords: insurTech, knowledge-base, empowerment model, factor analysis, insurance

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Authors: Sara Mostofian

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The nuclear industry is a technology that can fulfill future energy needs but requires special attention to ensure safety and reliability while minimizing any environmental impact. To meet these expectations, the nuclear industry is exploring different reactor technologies for power production. Several designs are under development and the technical viability of these new designs is the subject of many ongoing studies. One of these studies considers the radioactive emissions and radioactive waste generated during the life of a nuclear power production plant to allow a successful license process. For all the modern technologies, a good understanding of the radioactivity generated in the process systems of the plant is essential. Some of that understanding may be gleaned from the performance of some prototype reactors of similar design that operated decades ago. This paper presents how, with that understanding, a model can be developed to estimate the emissions as well as the radioactive waste during the normal operation of a nuclear power plant. The model would predict the radioactive material concentrations in different waste streams. Using this information, the radioactive emission and waste generated during the life of these new technologies can be estimated during the early stages of the design of the plant.

Keywords: SMRs, activity transport, model, radioactive waste

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Authors: Eetedal Alanjem, Majedah Alnajem

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The importance of innovation in entrepreneurship can be seen in the invention of new ways to produce products or improved solutions. A service industry can expand with new or improved types of services to fulfill the ever changing needs of their clients. Manufacturers can come up with new products from raw materials and by-products. Innovation is vital for the durability of any business. Innovation usually begins with a need. Small businesses are generally directly involved in their communities and they know exactly what the communities need and strive to come up with solutions to fulfill those needs. They seize the opportunity to innovate to ease communal problems and make lives more comfortable. And then, these solutions keep getting better, easier and more useful as entrepreneurs and their small businesses come up with improved formulas and solutions. Keeping abreast with current trends and demands is an important factor for entrepreneurs to fuel their creativity and innovation. Manufacturers are constantly innovating to produce more without sacrificing quality. Small businesses should make innovation as a fundamental part of their organisational development since innovation creates business success. Entrepreneurs must not see just one solution to a need. They should come up with ideas for multiple solutions. It is imperative for small businesses to encourage growth of innovation among their employees. Competition is another factor that elevates the importance of innovation in entrepreneurship. It motivates entrepreneurs to come up with better, improved products and services than their competitors for a higher share of the market. In this paper will go in-depth for each factor and will discuss some of cases studies to know how innovation it’s important for entrepreneurs by facts & lessons?

Keywords: innovation, entrepreneurship, creativity, organisational development

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Authors: Chayanika Rout, Debjani Chakraborty, Adrijit Goswami

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Our work presents an inventory model which illustrates imperfect production and imperfect inspection processes for deteriorating items. A cost-minimizing model is studied considering two types of inspection errors, namely, Type I error of falsely screening out a proportion of non-defects, thereby passing them on for rework and Type II error of falsely not screening out a proportion of defects, thus selling those to customers which incurs a penalty cost. The screened items are reworked; however, no returns are entertained due to deteriorating nature of the items. In more practical situations, certain parameters such as the demand rate and the deterioration rate of inventory cannot be accurately determined, and therefore, they are assumed to be triangular fuzzy numbers in our model. We calculate the optimal lot size that must be produced in order to minimize the total inventory cost for both the crisp and the fuzzy models. A numerical example is also considered to exemplify the procedure which is followed by the analysis of sensitivity of various parameters on the decision variable and the objective function.

Keywords: deteriorating items, EPQ, imperfect quality, rework, type I and type II inspection errors

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Authors: Yogesh Shukla

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Many attempts have been made to study temperature distribution problem in human tissues under normal environmental and physiological conditions at constant arterial blood temperature. But very few attempts have been made to investigate temperature distribution in human tissues under different arterial blood temperature. In view of above, a finite element model has been developed to unsteady temperature distribution in dermal region in human body. The model has been developed for one dimension unsteady state case. The variation in parameters like thermal conductivity, blood mass flow and metabolic activity with respect to position and time has been incorporated in the model. Appropriate boundary conditions have been framed. The central difference approach has been used in space variable and trapezoidal rule has been employed a long time variable. Numerical results have been obtained to study relationship among temperature and time.

Keywords: rate of metabolism, blood mass flow rate, thermal conductivity, heat generation, finite element method

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Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

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In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

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Authors: Patraporn Kaewkhanitarak, Weerawan Marangkun

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The objective of this study was to explore the establishment and to investigate the relationship between the gender (male or female) of SME owner-managers/ entrepreneurs and their risk perception in business activity. The study examines the data by interviewing 76 SME owner-managers/entrepreneurs’ responses (37 males, 39 females) in manufacturing, finance, human resources and marketing sector in the economic regions of Songkhla province, Thailand. This study found that four tools which were operation, cash flow, staff, and new market were perceived by the SME owner-managers/entrepreneurs at high level. However, male and female SME owner-managers/entrepreneurs perceived some factors such as the age of SME owner-managers/entrepreneurs, the duration of firm operation, type of firm, and type of business without significant differences. In contrast, the gender affected the risk perception about increasing cost, fierce competition, leapfrog development of firm, substandard staff, namely that male and female perceived these factors with significant differences. According to the research, SME owner-managers/entrepreneurs should develop their risk management competency to deal with the risk efficiently. Secondly, SME firms should gather into groups. Furthermore, it was shown that the five key tools used to manage these risky situations were the use of managerial competencies and clustering.

Keywords: risk perception, owner-managers/entrepreneurs, SME, Songkhla, Thailand

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Authors: Nnadi Ezekiel Ejiofor

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In Enugu, Nigeria, this study investigates the connection between strategic leadership and project management sustainability, with an emphasis on building projects in the State. The study set out to accomplish two specific goals: first, it sought to establish a link between creative project management and resource efficiency in construction projects in Enugu State, Nigeria; and second, it sought to establish a link between innovative thinking and waste minimization in those same projects. A structured questionnaire was used to collect primary data from 45 registered construction enterprises in the study area as part of the study's descriptive research approach. Due to the nonparametric nature of the data, Spearman Rank Order Correlation was used to evaluate the acquired data. The findings demonstrate that creative project management had a significant positive impact on resource efficiency in construction projects carried out by architecture firms in Enugu State, Nigeria (r =.849; p.001), and that innovative thinking had a significant impact on waste reduction in those same projects (r =.849; p.001). It was determined that strategic leadership had a significant impact on the sustainability of project management, and it was thus advised that project managers should foresee, prepare for, and effectively communicate present and future developments to project staff in order to ensure that the objective of sustainable initiatives, such as recycling and reuse, is implemented in construction projects.

Keywords: construction, project management, strategic leadership, sustainability, waste reduction

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Authors: Silvio Carlos Anibal de Almeida

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Hydrogen stands out as a promising alternative to fossil fuels due to its significantly high energy density. The promise of a sustainable transportation system with fuel cell electric vehicles (FCEVs) depends on overcoming economic and infrastructure barriers. The high cost of hydrogen and the scarcity of refueling stations require innovative solutions for the widespread adoption of FCEVs. Although developments in fuel cell technology have reduced costs in recent years, FCEVs are still considerably more expensive than internal combustion vehicles. This study analyzes the prospects for cost reduction of FCEVs, hydrogen, and the investments needed to expand the hydrogen distribution network. Projections indicate that the cost of FCEVs will align with that of gasoline cars by 2050, driven by technological maturation and mass production. Reducing the production costs of green hydrogen by reducing renewable energy costs, developing more efficient electrolyzers, and leveraging economies of scale could bring the price down to less than $5/kgH₂ by 2030. Government investment and public-private partnerships are essential to build a robust infrastructure for production, transportation, storage, and refueling stations. The goal of a sustainable transportation future powered by FCEVs can only be achieved by converging these factors.

Keywords: alternative vehicles, fuel cell, fuel cell electric vehicles, green hydrogen

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Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

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Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

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Authors: Julia Wicker, Alexander Lang

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The shortage of skilled workers is no longer unique to Europe; Australia now faces similar challenges, particularly in the field of project management. Project managers, essential to the success of a wide range of industries, frequently operate under intense stress and, as a result, may choose to leave their positions before the completion of their projects. This trend poses significant risks to project continuity, budget stability, and the long-term success of organizations. Consequently, it is crucial to explore strategies aimed at improving the retention of project managers, with a specific focus on fostering intrinsic motivation -an essential factor for achieving sustained success and commitment within project-based roles. The aim of this paper is to investigate retention strategies from other industries to identify effective practices that could be adapted to the unique challenges faced by project managers. In particular, the paper draws inspiration from the volunteer sector, an industry also heavily reliant on intrinsic motivation to drive commitment and performance. By examining how the volunteer sector sustains retention through a focus on intrinsic motivation, this paper seeks to highlight potential parallels and offer actionable insights for improving the retention of project managers. The paper includes an overview of the current landscape of retention challenges in project management, highlighting key factors that contribute to early departures and their impacts on organizations. This is followed by an analysis of interviews conducted with both active volunteers and those who have left their roles, leading to the development of a model that categorizes different types of volunteers and explores their behaviours. The model identifies specific reasons for volunteer terminating their assignments and proposes strategies to mitigate these issues. The paper then adapts these volunteer retention strategies to address the challenges faced by project managers, concluding with actionable recommendations for fostering an intrinsically motivated and resilient project management workforce. Ultimately, this research aims to contribute to broader efforts in mitigating skilled workforce shortages by offering sustainable retention strategies.

Keywords: skilled workforce shortages, retention challenges in project management, retention strategies in the volunteering sector, retention strategies for project managers

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Authors: Mohamed Redha Menani

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The Northern Saharan aquifer system “SASS” shared by Algeria, Libya, and Tunisia, covers a surface of about 1 100 000 km². It is composed of superposed aquifers; the upper one is the “Continental terminal – CT” (Eocene calcareous formation) situated at 400 m depth in average, while the” Continental Intercalaire – CI”(clay sands from Albian to Lower Cretaceous) is generally at 1500 m depth. This aquifer system is situated in a dry zone with a very weak current recharge but with a non-renewable big volume stored, estimated between 20 000 and 31 000 km³. From 1970 to nowadays, the exploitation of the SASS has increased from 0.6 to more than 2.5 km³/year. This situation provoked risks of water salinisation, reduction of the artesianisme, an increase of drawdowns, etc. which seriously threaten the sustainable socioeconomic development engaged in the SASS zone. Face the water shortage induced by the alarming dryness noted these last years, particularly in the MENA region, the joint management of this system by the three concerned countries, engaged for many years, needs a long-term strategy of integrated water resources management to meet the expected socio-economic goals projected not only in the SASS zone but also in other places, by water transfers. The sustainable management of this extensive aquifer system, aiming to satisfy various needs not only in the areas covered by the SASS but also in other areas through hydraulic transfers, can only be considered if this management is genuinely coordinated, incorporating schemes that primarily address the major constraint of climate change, which has been observed worldwide over the past two decades and is intensifying. In this particular climate context, management schemes must necessarily target several aspects, including (i) Updating the state of water resource exploitation in the SASS. (ii) Guiding agricultural usage as the primary consumer to ensure significant water savings. (iii) Constant monitoring through a network of piezometers to control the physicochemical parameters of the exploited aquifers. (iv) Other aspects related to governance within the framework of integrated management must also be taken into consideration, particularly environmental aspects and conflict resolution. However, problems, especially political ones as currently seen in Libya, may limit or at least disrupt the prospects of coordinated and sustainable management of this aquifer system, which is vital for the three countries.

Keywords: transboundary water resources, SASS, governance, climatic changes

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Authors: Norazah Mohd Suki, Norbayah Mohd Suki

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This research aims to examine the influence of mediating effect of corporate social responsibility on the relationship between consumer awareness of green marketing and purchase intentions in the retail setting. Data from 200 valid questionnaires was analyzed using the partial least squares (PLS) approach for the analysis of structural equation models with SmartPLS computer program version 2.0 as research data does not necessarily have a multivariate normal distribution and is less sensitive to sample size than other covariance approaches. PLS results revealed that corporate social responsibility partially mediated the link between consumer awareness of green marketing and purchase intentions of the product in the retail setting. Marketing managers should allocate a sufficient portion of their budget to appropriate corporate social responsibility activities by engaging in voluntary programs for positive return on investment leading to increased business profitability and long run business sustainability. The outcomes of the mediating effects of corporate social responsibility add a new impetus to the growing literature and preceding discoveries on consumer green marketing awareness, which is inadequately researched in the Malaysian setting. Direction for future research is also presented.

Keywords: green marketing awareness, social responsibility, partial least squares, purchase intention

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Authors: Anuj Abraham, N. Pappa, Daniel Honc, Rahul Sharma

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In this paper, an analysis of some model order reduction techniques is presented. A new hybrid algorithm for model order reduction of linear time invariant systems is compared with the conventional techniques namely Balanced Truncation, Hankel Norm reduction and Dominant Pole Algorithm (DPA). The proposed hybrid algorithm is known as Clustering Dominant Pole Algorithm (CDPA) is able to compute the full set of dominant poles and its cluster center efficiently. The dominant poles of a transfer function are specific eigenvalues of the state space matrix of the corresponding dynamical system. The effectiveness of this novel technique is shown through the simulation results.

Keywords: balanced truncation, clustering, dominant pole, Hankel norm, model reduction

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Authors: Peter Adly Hamdy Fahmy

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The aim of the study was to examine the effects of a physical education program on student learning by combining the teaching of personal and social responsibility (TPSR) with a physical education model and TPSR with a traditional teaching model, these learning outcomes involving self-learning. -Study. Athletic performance, enthusiasm for sport, group cohesion, sense of responsibility and game performance. The participants were 3 secondary school physical education teachers and 6 physical education classes, 133 participants with students from the experimental group with 75 students and the control group with 58 students, and each teacher taught the experimental group and the control group for 16 weeks. The research methods used surveys, interviews and focus group meetings. Research instruments included the Personal and Social Responsibility Questionnaire, Sports Enthusiasm Scale, Group Cohesion Scale, Sports Self-Efficacy Scale, and Game Performance Assessment Tool. Multivariate analyzes of covariance and repeated measures ANOVA were used to examine differences in student learning outcomes between combining the TPSR with a physical education model and the TPSR with a traditional teaching model. The research findings are as follows: 1) The TPSR sports education model can improve students' learning outcomes, including sports self-efficacy, game performance, sports enthusiasm, team cohesion, group awareness and responsibility. 2) A traditional teaching model with TPSR could improve student learning outcomes, including sports self-efficacy, responsibility, and game performance. 3) The sports education model with TPSR could improve learning outcomes more than the traditional teaching model with TPSR, including sports self-efficacy, sports enthusiasm, responsibility and game performance. 4) Based on qualitative data on teachers' and students' learning experience, the physical education model with TPSR significantly improves learning motivation, group interaction and sense of play. The results suggest that physical education with TPSR could further improve learning outcomes in the physical education program. On the other hand, the hybrid model curriculum projects TPSR - Physical Education and TPSR - Traditional Education are good curriculum projects for moral character education that can be used in school physics.

Keywords: approach competencies, physical, education, teachers employment, graduate, physical education and sport sciences, SWOT analysis character education, sport season, game performance, sport competence

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Authors: Vishant Gahlaut, A Mercy Latha, Sanjay Kumar Ghosh

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Multi-stage depressed collectors (MDC) are used as an efficiency enhancement technique in traveling wave tubes the high-energy electron beam, after its interaction with the RF signal, gets velocity sorted and collected at various depressed electrodes of the MDC. The ultimate goal is to identify an optimum thermal management scheme (cooling mechanism) that could extract the heat efficiently from the electrodes. Careful thermal analysis, incorporating the cooling mechanism is required to ensure that the maximum temperature does not exceed the safe limits. A simple analytical model for quick prediction of the thermal has been developed. The model has been developed for the worst-case un-modulated DC condition, where all the thermal power is dissipated in the last electrode (typically, fourth electrode in the case of the four-stage depressed collector). It considers the thermal contact resistances at various braze joints accounting for the practical non-uniformities. Analytical results obtained from the model have been validated with simulated and experimental results.

Keywords: multi-stage depressed collector, TWTs, thermal contact resistance, thermal management

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Authors: Yong-Nam Kwon

Abstract:

In the present study, we have designed the hydro-mechanical forming in which AZ31 sheet was drawn to a kind of preform step following gas blow forming for accurate geometry. In order to judge a formability enhancement of AZ31 sheet, model geometry came from a practical automotive part which had quite depth with complicated curvatures, which was proven that a single sheet forming could not gave a successful part. Experimentally, we succeeded to make the model part with accurate dimension. The optimum forming conditions for respective forming steps were considered most important technical features of this hydro-mechanical and would be discussed in details. Also, the effort to avoid detrimental abnormal grain growth was given and discussed for a practical application.

Keywords: hydro-mechanical forming, AZ31, abnormal grain growth, model geometry

Procedia PDF Downloads 515