Search results for: sustainable tourism models

Authors: Yahaya Salihu Emeje, Amuchie Austine Anthony

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The topic examined the prospects of entrepreneurship as an emerging dynamic and strategic tool in the upliftment of human and non-human resources in the Nigerian university system, with a view of showcasing the abundant positive impact, on the Nigerian University system in particular and Nigerian economy at large. It is end at bringing out the benefits of entrepreneurship in the university system which includes, namely cultivating the culture of enterprise in University system; improvement in the quality and quantity of both human and non-human resources; innovative and creative methods of production; new employment strategies in the University system; improved sources of internal generated revenue; entrepreneurship as the culture of sustainability within and outside the university system. Secondary data was used in analyzing entrepreneurship as a productivity tool in the Nigeria University system. From the findings, the university system could be enriched through innovative ideas and technical revenue and employment generation; sustainable financial and economic base; university autonomy and improved international ranking of Nigerian Universities system; therefore, recommended that entrepreneurship is necessary therapy for reviving the ailing, Nigerian universities system.

Keywords: entrepreneurship, strategic, productivity, universities

Procedia PDF Downloads 390

Authors: Danielle Klassen, Reiko Yeap, Margo Schmitt-Boshnick, Scott Oddie

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The development of the 7-week Alberta Happiness Basics program was initiated in 2010 in response to the need for community mental health programming. This provincial wide program aims to increase overall happiness and reduce negative thoughts and feelings through a positive psychology intervention. While the 7-week program has proven effective, a shortened 4-week program has additionally been developed to address client needs. In this study, participants were interviewed to determine if the 4- and 7-week programs had similar success of producing lasting behavior change at 3, 6, and 9 months post-program. A health quality of life (HQOL) measure was also used to compare the two programs and examine patient outcomes. Quantitative and qualitative analysis showed significant improvements in HQOL and sustainable behavior change for both programs. Findings indicate that the shorter, patient-centered program was effective in increasing happiness and reducing negative thoughts and feelings.

Keywords: primary care, mental health, depression, short duration

Procedia PDF Downloads 267

Authors: Abd Latif Abdul Rahman, Zuraidah Arif, Muhammad Faizal Iylia, Mohd Ghazali, Asmadi Mohammed Ghazali

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Mobile information is a significant access point for human information activities. Theories and models of human information behavior have developed over several decades but have not yet considered the role of the user’s computing device in digital information interactions. This paper reviews the literature that leads to developing a conceptual framework of a study on the managers mobile information behavior. Based on the literature review, dimensions of mobile information behavior are identified, namely, dimension information needs, dimension information access, information retrieval and dimension of information use. The study is significant to understand the nature of librarians’ behavior in searching, retrieving and using information via the mobile device. Secondly, the study would provide suggestions about various kinds of mobile applications which organization can provide for their staff to improve their services.

Keywords: mobile information behavior, information behavior, mobile information, mobile devices

Procedia PDF Downloads 343

Authors: S. C. Lin, M. S. Wu

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Japanese Scholar Manabu Sato has been advocating the Learning Community, which changed Japanese fundamental education during the last three decades. It was also called a “Quiet Revolution.” Manabu Sato criticized that traditional education only focused on individual competition, exams, teacher-centered instruction, and memorization. The students lacked leaning motivation. Therefore, Manabu Sato proclaimed that learning should be a sustainable process of “constantly weaving the relationship and the meanings” by having dialogues with learning materials, with peers, and with oneself. For a long time, secondary school education in Taiwan has been focused on exams and emphasized reciting and memorizing. The incident of “giving up learning” happened to some students. Manabu Sato’s learning community program has been implemented very successfully in Japan. It is worth exploring if learning community can resolve the issue of “Escape from learning” phenomenon among secondary school students in Taiwan. This study was the first year of a two-year project. This project applied a program theory-driven approach to evaluating the impact of teachers’ professional development interventions on students’ learning by using a mix of methods, qualitative inquiry, and quasi-experimental design. The current study was to show the results of using the method of theory-driven approach to program planning to design and evaluate a teachers’ professional development program (TPDP). The Manabu Sato’s learning community theory was applied to structure all components of a 54-hour workshop. The participants consisted of seven secondary school science teachers from two schools. The research procedure was comprised of: 1) Defining the problem and assessing participants’ needs; 2) Selecting the Theoretical Framework; 3) Determining theory-based goals and objectives; 4) Designing the TPDP intervention; 5) Implementing the TPDP intervention; 6) Evaluating the TPDP intervention. Data was collected from a number of different sources, including TPDP checklist, activity responses of workshop, LC subject matter test, teachers’ e-portfolio, course design documents, and teachers’ belief survey. The major findings indicated that program design was suitable to participants. More than 70% of the participants were satisfied with program implementation. They revealed that TPDP was beneficial to their instruction and promoted their professional capacities. However, due to heavy teaching loadings during the project some participants were unable to attend all workshops. To resolve this problem, the author provided options to them by watching DVD or reading articles offered by the research team. This study also established a communication platform for participants to share their thoughts and learning experiences. The TPDP had marked impacts on participants’ teaching beliefs. They believe that learning should be a sustainable process of “constantly weaving the relationship and the meanings” by having dialogues with learning materials, with peers, and with oneself. Having learned from TPDP, they applied a “learner-centered” approach and instructional strategies to design their courses, such as learning by doing, collaborative learning, and reflective learning. To conclude, participants’ beliefs, knowledge, and skills were promoted by the program instructions.

Keywords: program theory-driven approach, learning community, teacher professional development program, program evaluation

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Authors: Tarek Litim, Ouahiba Taamallah

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The present paper is an investigation of the effect of burnishing on the surface integrity of a component made of 15NiCr6 steel. This work shows a statistical study based on regression, and Taguchi's design has allowed the development of mathematical models to predict the output responses as a function of the technological parameters studied. The response surface methodology (RSM) showed a simultaneous influence of the burnishing parameters and observe the optimal processing parameters. ANOVA analysis of the results resulted in the validation of the prediction model with a determination coefficient R=90.60% and 92.41% for roughness and hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=10kgf, i=3passes, and f=0.074mm/rev, which favours minimum roughness and maximum hardness. The result was validated by the desirability of D= (0.99 and 0.95) for roughness and hardness, respectively.

Keywords: 15NiCr6 steel, burnishing, surface integrity, Taguchi, RSM, ANOVA

Procedia PDF Downloads 187

Authors: Ilaria Lucrezia Amerise

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Electricity markets throughout the world have undergone substantial changes. Accurate, reliable, clear and comprehensible modeling and forecasting of different variables (loads and prices in the first instance) have achieved increasing importance. In this paper, we describe the actual state of the art focusing on reg-SARMA methods, which have proven to be flexible enough to accommodate the electricity price/load behavior satisfactory. More specifically, we will discuss: 1) The dichotomy between point and interval forecasts; 2) The difficult choice between stochastic (e.g. climatic variation) and non-deterministic predictors (e.g. calendar variables); 3) The confrontation between modelling a single aggregate time series or creating separated and potentially different models of sub-series. The noteworthy point that we would like to make it emerge is that prices and loads require different approaches that appear irreconcilable even though must be made reconcilable for the interests and activities of energy companies.

Keywords: interval forecasts, time series, electricity prices, reg-SARIMA methods

Procedia PDF Downloads 128

Authors: Ehab AbdulRazzaq Hussein

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Quantum cryptography (QC) is an emerging technology for secure key distribution with single-photon transmissions. In contrast to classical cryptographic schemes, the security of QC schemes is guaranteed by the fundamental laws of nature. Their security stems from the impossibility to distinguish non-orthogonal quantum states with certainty. A potential eavesdropper introduces errors in the transmissions, which can later be discovered by the legitimate participants of the communication. In this paper, the modeling approach is proposed for QC protocol BB84 using polarization coding. The single-photon system is assumed to be used in the designed models. Thus, Eve cannot use beam-splitting strategy to eavesdrop on the quantum channel transmission. The only eavesdropping strategy possible to Eve is the intercept/resend strategy. After quantum transmission of the QC protocol, the quantum bit error rate (QBER) is estimated and compared with a threshold value. If it is above this value the procedure must be stopped and performed later again.

Keywords: security, key distribution, cryptography, quantum protocols, Quantum Cryptography (QC), Quantum Key Distribution (QKD).

Procedia PDF Downloads 397

Authors: Mir Jalil Razavi, Tianming Liu, Xianqiao Wang

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Cortical folding, characterized by convex gyri and concave sulci, has an intrinsic relationship to the brain’s functional organization. Understanding the mechanism of the brain’s convoluted patterns can provide useful clues into normal and pathological brain function. During the development, the cerebral cortex experiences a noticeable expansion in volume and surface area accompanied by tremendous tissue folding which may be attributed to many possible factors. Despite decades of endeavors, the fundamental mechanism and key regulators of this crucial process remain incompletely understood. Therefore, to taking even a small role in unraveling of brain folding mystery, we present a mechanical model to find mechanism of 3-hinges formation in a growing brain that it has not been addressed before. A 3-hinge is defined as a gyral region where three gyral crests (hinge-lines) join. The reasons that how and why brain prefers to develop 3-hinges have not been answered very well. Therefore, we offer a theoretical and computational explanation to mechanism of 3-hinges formation in a growing brain and validate it by experimental observations. In theoretical approach, the dynamic behavior of brain tissue is examined and described with the aid of a large strain and nonlinear constitutive model. Derived constitute model is used in the computational model to define material behavior. Since the theoretical approach cannot predict the evolution of cortical complex convolution after instability, non-linear finite element models are employed to study the 3-hinges formation and secondary morphological folds of the developing brain. Three-dimensional (3D) finite element analyses on a multi-layer soft tissue model which mimics a small piece of the brain are performed to investigate the fundamental mechanism of consistent hinge formation in the cortical folding. Results show that after certain amount growth of cortex, mechanical model starts to be unstable and then by formation of creases enters to a new configuration with lower strain energy. By further growth of the model, formed shallow creases start to form convoluted patterns and then develop 3-hinge patterns. Simulation results related to 3-hinges in models show good agreement with experimental observations from macaque, chimpanzee and human brain images. These results have great potential to reveal fundamental principles of brain architecture and to produce a unified theoretical framework that convincingly explains the intrinsic relationship between cortical folding and 3-hinges formation. This achieved fundamental understanding of the intrinsic relationship between cortical folding and 3-hinges formation would potentially shed new insights into the diagnosis of many brain disorders such as schizophrenia, autism, lissencephaly and polymicrogyria.

Keywords: brain, cortical folding, finite element, three hinge

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Authors: Frank Kuebler, Rolf Steinhilper

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Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process

Procedia PDF Downloads 518

Authors: Shashikant Kumar, Chandraraj K.

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Perennial grasses have presented interesting choices in the current demand for renewable and sustainable energy sources to alleviate the load of the global energy problem. The perennial grass Napier grass (Pennisetum purpureum Schumach) is a promising feedstock for the production of cellulosic ethanol. The conversion of biomass into glucose and xylose is a crucial stage in the production of bioethanol, and it necessitates optimal pretreatment. Alkali treatment, among the several pretreatments available, effectively reduces lignin concentration and crystallinity of cellulose. Response surface methodology was used to optimize the alkali pretreatment of Napier grass for maximal reducing sugar production. The combined effects of three independent variables, viz. sodium hydroxide concentration, temperature, and reaction time, were studied. A second-order polynomial equation was used to fit the observed data. Maximum reducing sugar (590.54 mg/g) was obtained under the following conditions: 1.6 % sodium hydroxide, a reaction period of 30 min., and 120˚C. The results showed that Napier grass is a desirable feedstock for bioethanol production.

Keywords: Napier grass, optimization, pretreatment, sodium hydroxide

Procedia PDF Downloads 497

Authors: Kamel Al-Khaled

Abstract:

Reaction-diffusion equations are commonly used in population biology to model the spread of biological species. In this paper, we propose a fractional reaction-diffusion equation, where the classical second derivative diffusion term is replaced by a fractional derivative of order less than two. Based on the symbolic computation system Mathematica, Adomian decomposition method, developed for fractional differential equations, is directly extended to derive explicit and numerical solutions of space fractional reaction-diffusion equations. The fractional derivative is described in the Caputo sense. Finally, the recent appearance of fractional reaction-diffusion equations as models in some fields such as cell biology, chemistry, physics, and finance, makes it necessary to apply the results reported here to some numerical examples.

Keywords: fractional partial differential equations, reaction-diffusion equations, adomian decomposition, biological species

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Authors: Aly Elshafei, Daniela Romano

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With the development of autonomous vehicles, a human-machine interaction (HMI) system is needed for a safe transition of control when a takeover request (TOR) is required. An important part of the HMI system is the ability to monitor the level of situational awareness (SA) of any driver in real-time, in different scenarios, and without any pre-calibration. Presenting state-of-the-art machine learning models used to measure SA is the purpose of this systematic review. Investigating the limitations of each type of sensor, the gaps, and the most suited sensor and computational model that can be used in driving applications. To the author’s best knowledge this is the first literature review identifying online and offline classification methods used to measure SA, explaining which measurements are subject or session-specific, and how many classifications can be done with each classification model. This information can be very useful for researchers measuring SA to identify the most suited model to measure SA for different applications.

Keywords: situational awareness, autonomous driving, gaze metrics, EEG, ECG

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Authors: Sonal H. Singh, Bhaskar Bhowmick

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The research hypothesis formulated in this paper examines the importance of microfinance provision for entrepreneurship development by engendering a high level of entrepreneurial orientation among the grassroots entrepreneurs. A theoretically well supported empirical framework is proposed to identify the influence of financial services and non-financial services provided by microfinance institutes in strengthening the impact of grassroots innovation on entrepreneurial orientation under resource constraints. In this paper, Grassroots innovation is perceived in three dimensions: new learning practice, localized solution, and network development. The study analyzes the moderating effect of microfinance provision on the relationship between grassroots innovation and entrepreneurial orientation. The paper employed structural equation modelling on 400 data entries from the grassroots entrepreneurs in India. The research intends to help policymakers, entrepreneurs and microfinance providers to promote the innovative design of microfinance services for the well-being of grassroots entrepreneurs and to foster sustainable entrepreneurship development.

Keywords: entrepreneurship development, grassroots innovation, India, structural equation model

Procedia PDF Downloads 261

Authors: Dimitrios Binas, Marianna Konidari, Charis Bourgioti, Lia Angela Moulopoulou, Theodore Economopoulos, George Matsopoulos

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High grade ovarian epithelial cancer (OEC) is fatal gynecological cancer and the poor prognosis of this entity is closely related to considerable intratumoral genetic heterogeneity. By examining imaging data, it is possible to assess the heterogeneity of tumorous tissue. This study proposes a methodology for aligning, segmenting and finally visualizing information from various magnetic resonance imaging series in order to construct 3D models of heterogeneity maps from the same tumor in OEC patients. The proposed system may be used as an adjunct digital tool by health professionals for personalized medicine, as it allows for an easy visual assessment of the heterogeneity of the examined tumor.

Keywords: image segmentation, ovarian epithelial cancer, quantitative characteristics, image registration, tumor visualization

Procedia PDF Downloads 203

Authors: Perpetual Nwakaego Ibe

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The Millennium Development Goals (MDGs), were an integrated project formed to eradicate many unnatural situations the citizens of the third world country may found themselves in. The MDGs, to be a sustainable project for the future depends 100% on the actions of governments, multilateral institutions and civil society. This paper first looks at the political views on the MDGs and relates it to the current electoral situations around the country by underlining the drastic changes over the few months. The second part of the paper presents ICT in tertiary institutions as one of the solutions in terms of the success of the MDGs. ICT is vital in all phases of educational process and development of the cloud connectivity is an added advantage of Information and Communication Technology (ICT) for sharing a common data bank for research purposes among UNICEF, RED CROSS, NPS, INEC, NMIC, and WHO. Finally, the paper concludes with areas that needs twigging and recommendations for the tertiary institutions committed to delivering an ambitious set of goals. A combination of observation, and document materials for data gathering was employed as the methodology for carrying out this research.

Keywords: MDG, ICT, data bank, database

Procedia PDF Downloads 197

Authors: Mergleda Hodo

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All national governments aim to achieve economic equilibrium to build sustainable welfare, political stability, and economic equilibrium. There are various instruments to stimulate economic development and growth and achieve macroeconomic objectives. After the collapse of the political and economic system in the 1990s, some countries faced the complex challenge of economic development. This study aims to determine, based on empirical research, whether and to what extent tax revenue has an impact on the economic development of Albania. Furthermore, it gives an overview of the ways in which high tax burdens on the western Balkan countries have negatively affected foreign investment and reduced economic growth. This analysis is important for these selected countries, as the financial system has changed significantly over the years and has been affected significantly by a period of economic transition. The analysis is performed based on secondary data possessed by the World Bank and the central bank of each participating country between 2005 and 2018. The research findings indicate that tax policy affects, to a significant extent, the economic development of Albania. An efficient tax system is when individuals are willing to pay tax liability which will help in improving the economic well-being of a country.

Keywords: tax, development, economic growth, tax revenue

Procedia PDF Downloads 72

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 120

Authors: Rui Xing, Baolin Ye, Nan Zhou, Guohong Wang

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Drawing upon a perspective of cognitive interaction, this study explores the relationship between team cognitive heterogeneity and team strategic decision-making flexibility, treating the transactive memory system as a mediator and task complexity as a moderator. The hypotheses were tested in linear regression models by using data gathered from 67 strategic decision-making teams in the new-energy vehicle industry. It is found that team cognitive heterogeneity has a positive impact on strategic decision-making flexibility through the mediation of specialization and coordination of the transactive memory system, which is positively moderated by task complexity.

Keywords: strategic decision-making flexibility, team cognitive heterogeneity, transactive memory system, task complexity

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Authors: Dhananjoy Dutta

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Field studies in lower Gangetic plains of India reveal that over-abstraction of groundwater for irrigation to paddy leads to a substantial depletion of groundwater over the decades, resulting in negative effects on lowering of the water table, drying up of surface water sources and aquifer pollution with leached-out arsenic. The aggravating arsenic toxicity in drinking water is manifested in health problems and ‘arsenicosis’ of people. A social conflict arises between farmers, who intend to grow paddy for livelihoods, and the groundwater authority, which enacts the ‘Regulation Laws’ by putting a check on the excessive installation of private tube-wells for irrigation. Hence, considering the challenges of resource sustainability, health issues, and food security, the study calls for a paradigm shift in policy from further groundwater development to sustainable water resources management and evaluates some strategies integrating supply and demand side management for mitigating the problems.

Keywords: groundwater, irrigation, paddy farming, water table depletion, arsenic pollution, gangetic plains

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Authors: Sayedramin Hashemianesfehani, Seyed Hossein Hosseinilargani

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In this study, we attempt to realize that to what extent the increase in selected commodities in Iran Market is originated from the implementation of the targeted subsidies law. Hence, an econometric model based on existing theories of increasing and transferring prices in order to transferring inflation is developed. In other words, world price index and virtual variables defined for targeted subsidies has significant and positive impact on the producer price index. The obtained results indicated that the targeted subsidies act in Iran has influential long and short-term impacts on producer price indexes. Finally, world prices of dairy products and dairy price with respect to major parameters is carried out to obtain some managerial ‎results.

Keywords: econometric models, targeted subsidies, consumer price index (CPI), producer price index (PPI)

Procedia PDF Downloads 356

Authors: Gurjinder Singh, Ankur Gill, Amardeep Singh Kang

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In the present work an effort has been made to study the influence of the welding parameters on tensile strength of friction stir welding of aluminum. Three process parameters tool rotation speed, welding speed, and shoulder diameter were selected for the study. Two level factorial design of eight runs was selected for conducting the experiments. The mathematical model was developed from the data obtained. The significance of coefficients and adequacy of developed models were tested by ‘t’ test and ‘F’ test respectively. The effects of process parameters on mechanical properties have been represented in the form of graphs for better understanding.

Keywords: friction stir welding, aluminium alloy, mathematical model, welding speed

Procedia PDF Downloads 437

Authors: Hülya Torun, Ondřej Novák, Jaromír Mikulík, Miroslav Strnad, Faik A. Ayaz

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World climate is changing. Millions of people in the world still face chronic undernourishment for conducting a healthy life and the world’s population is growing steadily. To meet this growing demand, agriculture and food systems must adapt to the adverse effects of climate change and become more resilient, productive and sustainable. From this perspective, to determine tolerant cultivars for undesirable environmental conditions will be necessary food production for sustainable development. Among abiotic stresses, soil salinity is one of the most detrimental global fact restricting plant sources. Development of salt-tolerant lines is required in order to increase the crop productivity and quality in salt-treated lands. Therefore, the objective of this study was to investigate the morphological and physiological responses of barley cultivars accessions to salinity stress by NaCl. For this purpose, it was aimed to determine the crosstalk between some endogenous phytohormones and exogenous salicylic acid (SA) in two different vegetative parts (leaves and roots) of barley (Hordeum vulgare L.; Poaceae; 2n=14; Ince-04) which is detected salt-tolerant. The effects of SA on growth parameters, leaf relative water content (RWC), endogenous phytohormones; including indole-3-acetic acid (IAA), cytokinins (CKs), abscisic acid (ABA), jasmonic acid (JA) and ethylene were investigated in barley cultivars under salinity stress. SA was applied to 17-day-old seedlings of barley in two different ways including before (pre-treated for 24 h) and simultaneously with NaCl stress treatment. NaCl (0, 150, 300 mM) exposure in the hydrophonic system was associated with a rapid decrease in growth parameters and RWC, which is an indicator of plant water status, resulted in a strong up-regulation of ABA as a stress indicator. Roots were more dramatically affected than leaves. Water conservation in 150 mM NaCl treated-barley plants did not change, but decreased in 300 mM NaCl treated plants. Pre- and simultaneously treatment of SA did not significantly alter growth parameters and RWC. ABA, JA and ethylene are known to be related with stress. In the present work, ethylene also increased, similarly to ABA, but not with the same intensity. While ABA and ethylene increased by the increment of salt concentrations, JA levels rapidly decreased especially in roots. Both pre- and simultaneously SA applications alleviated salt-induced decreases in 300 mM NaCl resulted in the increment of ABA levels. CKs and IAA are related to cell growth and development. At high salinity (300 mM NaCl), CKs (cZ+cZR) contents increased in both vegetative organs while IAA levels stayed at the same level with control groups. However, IAA increased and cZ+cZR rapidly decreased in leaves of barley plants with SA treatments before salt applications (in pre- SA treated groups). Simultaneously application of SA decreased CKs levels in both leaves and roots of the cultivar. Due to increasing concentrations of NaCl in association with decreasing ABA, JA and ethylene content and increments in CKs and IAA were recorded with SA treatments. As results of the study, in view of all the phytohormones that we tested, exogenous SA induced greater tolerance to salinity particularly when applied before salinity stress.

Keywords: Barley, Hordeum vulgare, phytohormones, salicylic acid, salinity

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Authors: Sherry Robinson, Hans Anton Stubberud

Abstract:

Entrepreneurship can take many forms. Traditional entrepreneurs seek profits and growth for the businesses they start themselves. Intrapreneurs act entrepreneurially within a business they do not own. Social entrepreneurs have goals other than (but not excluding) profit and growth as they seek to solve social problems or protect the environment. This type of entrepreneur often focuses on the triple bottom line, which includes a concern for people and the planet as well as profit. Ecopreneurs in particular are driven by their desire to create and promote environmentally sustainable products and processes. All of these entrepreneurs need an entrepreneurial orientation in order to survive and thrive. The three most common elements of an entrepreneurial orientation are (1) creativity and innovation, (2) the willingness to take risks and (3) the proactiveness to put ideas into action. This study describes an interdisciplinary entrepreneurship course integrating topics regarding the triple bottom line with those relevant to an entrepreneurial orientation. The results show that students significantly increased their skill levels in many areas, including soft skills such as communicating and working in teams, as well as designing innovative products and taking calculated risk.

Keywords: creativity, entrepreneurship education, sustainability, triple bottom line

Procedia PDF Downloads 468

Authors: Tayyab Ahmad, Gerard Healey

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The potential role of higher education institutes in sustainable development cannot be undermined. In this regard, it is important to investigate the established concept of sustainability in such institutes to explore the room for further improvement. In this paper, a case study of the University of Melbourne is conducted, and the institute’s commitments towards sustainability are examined by a detailed qualitative review of its policy and design standard documents. These documents are reviewed as through these; the institute portrays its vision of building environment facilities, which it aspires to procure and use. From detailed review, it is realized that these documents are updated at different times, creating the potential for mismatch between them. The occurrence of different goals and objectives in different documents is highlighted, and the interrelationships between different goals and operational objectives are explored. The role of the university aspired goals/objectives in terms of built environment sustainability is discussed, and the gaps in the articulation of goals and operational objectives are highlighted. Recommendations are provided for enhancing the built environment sustainability at the University of Melbourne.

Keywords: university, design standards, policy, sustainability, built environment

Procedia PDF Downloads 166

Authors: Diane Ghanem, Oscar Covarrubias, Michael Raad, Dawn LaPorte, Babar Shafiq

Abstract:

Introduction: Standardized exams have long been considered a cornerstone in measuring cognitive competency and academic achievement. Their fixed nature and predetermined scoring methods offer a consistent yardstick for gauging intellectual acumen across diverse demographics. Consequently, the performance of artificial intelligence (AI) in this context presents a rich, yet unexplored terrain for quantifying AI's understanding of complex cognitive tasks and simulating human-like problem-solving skills. Publicly available AI language models such as ChatGPT have demonstrated utility in text generation and even problem-solving when provided with clear instructions. Amidst this transformative shift, the aim of this study is to assess ChatGPT’s performance on the orthopaedic surgery in-training examination (OITE). Methods: All 213 OITE 2021 web-based questions were retrieved from the AAOS-ResStudy website. Two independent reviewers copied and pasted the questions and response options into ChatGPT Plus (version 4.0) and recorded the generated answers. All media-containing questions were flagged and carefully examined. Twelve OITE media-containing questions that relied purely on images (clinical pictures, radiographs, MRIs, CT scans) and could not be rationalized from the clinical presentation were excluded. Cohen’s Kappa coefficient was used to examine the agreement of ChatGPT-generated responses between reviewers. Descriptive statistics were used to summarize the performance (% correct) of ChatGPT Plus. The 2021 norm table was used to compare ChatGPT Plus’ performance on the OITE to national orthopaedic surgery residents in that same year. Results: A total of 201 were evaluated by ChatGPT Plus. Excellent agreement was observed between raters for the 201 ChatGPT-generated responses, with a Cohen’s Kappa coefficient of 0.947. 45.8% (92/201) were media-containing questions. ChatGPT had an average overall score of 61.2% (123/201). Its score was 64.2% (70/109) on non-media questions. When compared to the performance of all national orthopaedic surgery residents in 2021, ChatGPT Plus performed at the level of an average PGY3. Discussion: ChatGPT Plus is able to pass the OITE with a satisfactory overall score of 61.2%, ranking at the level of third-year orthopaedic surgery residents. More importantly, it provided logical reasoning and justifications that may help residents grasp evidence-based information and improve their understanding of OITE cases and general orthopaedic principles. With further improvements, AI language models, such as ChatGPT, may become valuable interactive learning tools in resident education, although further studies are still needed to examine their efficacy and impact on long-term learning and OITE/ABOS performance.

Keywords: artificial intelligence, ChatGPT, orthopaedic in-training examination, OITE, orthopedic surgery, standardized testing

Procedia PDF Downloads 81

Authors: Agnese Natali, Francesco Morelli, Walter Salvatore, José Humberto Matias de Paula Filho, Patrick Pol

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In the framework of the evaluation of the applicability of high strength steel to produce thin-walled elements to be used in Automated Rack Supported Warehouses, an experimental campaign is carried outto evaluate the structural performance of typical profile shapes adopted for such purposes and made of high strength steel. Numerical models are developed to fit the observed failure modes, stresses, and deformation patterns, and proper directions are proposed to simplify the numerical simulations to be used in further applications and to evaluate the mechanical behavior and performance of profiles.

Keywords: Steel racks, Automated Rack Supported Warehouse, thin walled cold-formed elements, high strength steel.

Procedia PDF Downloads 174

Authors: Omar A. Shaneb, Adell S. Amer

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Reduction of CO2 emissions has become a priority for several countries due to increasing concerns about global warming and climate change, especially in the developed countries. Residential sector is considered one of the most important sectors for considerable reduction of CO2 emissions since it represents a significant amount of the total consumed energy in those countries. A significant CO2 reduction cannot be achieved unless some initiatives have been adopted in the policy of these countries. Introducing micro combined heat and power (µCHP) systems into residential energy systems is one of these initiatives, since such a technology offers several advantages. Moreover, µCHP technology has the opportunity to be operated not only by natural gas but it could also be operated by renewable fuels. However, this technology can be operated by different operation strategies. Each strategy has some advantages and disadvantages. This paper provides a review of different operation strategies of such a technology used for residential energy systems, especially for single dwellings. The review summarizes key points that outline the trend of previous research carried out in this field.

Keywords: energy management, µCHP systems, residential energy systems, sustainable houses, operation strategy.

Procedia PDF Downloads 423

Authors: Murat Sarı, Emin Gundogar, Mumtaz Ipek

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Nowadays, in a furniture sector, competition of market share (portion) and production variety and changeability enforce the firm to reengineer operations on manufacturing line to increase the productivity. In this study, spring mattress manufacturing line of the furniture manufacturing firm is analyzed analytically. It’s intended to search and find the bottlenecks of production to balance the semi-finished material flow. There are four base points required to investigate in bottleneck elimination process. These are bottlenecks of Method, Material, Machine and Man (work force) resources, respectively. Mentioned bottlenecks are investigated and varied scenarios are created for recruitment of manufacturing system. Probable near optimal alternatives are determined by system models built in Arena simulation software.

Keywords: bottleneck search, buffer stock, furniture sector, simulation

Procedia PDF Downloads 354

Authors: Hossein Arzani, Masoud Jafari Shalamzari, Z. Arzani

Abstract:

This paper follows FAO model of suitability analysis. Influential factors affecting extensive grazing were determined and converted into a model. Taleghan rangelands were examined for common types of grazing animals as an example. Advantages and limitations were elicited. All range ecosystems’ components affect range suitability but due to the time and money restrictions, the most important and feasible elements were investigated. From which three sub-models including water accessibility, forage production and erosion sensitivity were considered. Suitable areas in four levels of suitability were calculated using GIS. This suitability modeling approach was adopted due to its simplicity and the minimal time that is required for transforming and analyzing the data sets. Managers could be benefited from the model to devise the measures more wisely to cope with the limitations and enhance the rangelands health and condition.

Keywords: range suitability, land-use, extensive grazing, modeling, land evaluation

Procedia PDF Downloads 337

Authors: Sabina Ngodigha, Roland Gbarabe, Aiyebatonworio Austin

Abstract:

A study of fisher’s knowledge (FK) and community-based fisheries management practices in River Nun estuary was conducted to assess the contribution of FK to fisheries resources conservation. A total of 390 fishers operates in the area of which 221 were interviewed based on having a minimum of 10 years of experience. Community-based fisheries management programme was introduced and implemented by fishermen’s union in 2010 for the sustainable management and conservation of fisheries resources. Local law introduced were: band on the use of mesh size of less than 5cm and band on chemical fishing. Defaulters were made to pay monetary fines ranging from #2,000 to #6,000 while fishers caught using chemicals to fish were arrested and landed over to the police for prosecution. The management method has enhanced conservation of fisheries resources which is a major source of livelihood for the people. Landings increased tremendously resulting in positive increase in the finances of the fishers. It is, therefore, pertinent to introduce community-based laws to check over exploitation of fisheries resources in the Niger Delta.

Keywords: community, conservation, fishers knowledge, local laws, management

Procedia PDF Downloads 274