Search results for: demand forecast

Authors: Avinash Kumar Ranjan, Akash Anand

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The Land Surface Temperature (LST) is an essential factor accompanying to rise urban heat and climate warming within a city in micro level. It is also playing crucial role in global change study as well as radiation budgets measuring in heat balance studies. The information of LST is very substantial to recognize the urban climatology, ecological changes, anthropological and environmental interactions etc. The Chief motivation of present study focus on time series of ANN model that taken a sequence of LST values of 2000, 2008 and 2016, realize the pattern of variation within the data set and predict the LST values for 2024 and 2032. The novelty of this study centers on evaluation of LST using series of multi-temporal MODIS (MOD 11A2) satellite data by Maximum Value Composite (MVC) techniques. The results derived from this study endorse the proficiency of Geoinformatics Technology with integration of ANN to gain knowledge, understanding and building of precise forecast from the complex physical world database. This study will also focus on influence of Land Use/ Land Cover (LU/LC) variation on Land Surface Temperature.

Keywords: LST, geoinformatics technology, ANN, MODIS satellite imagery, MVC

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Authors: Ammani K., Glory M.

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Demands of traditional herbal medicines are increasing day by day over the world. Considering the growing demand of medicinal plants in curative treatments and the role of VAM fungi in augmentation of the production of active secondary metabolites by the medicinal plants, the present work has been undertaken to survey the mycorrhizal status in 30 different medicinal plants belonging to various families from Krishna district, Andhra Pradesh. The roots were collected carefully and stained by the Phillips & Hayman technique. Basing on the occurrence of vesicles and arbuscules, categorized into four grades; Excellent: mycelia, vesicles or arbuscules present more than 75% of root bits, Good: mycelia, vesicles or arbuscules present 50-75% in surface of root bits, moderate: mycelia, vesicles or arbuscules present 25-50% in surface of root bits, and poor: mycelia, vesicles or arbuscules present 1-25% in surface of root bits. The study reveals that the roots of all plants were colonized by AM fungi. Percentage of root colonization by AM fungi was more in Aloe vera, Phylanthus emblica, Azadiracta indica and least in plants such as Aerva lanata, Vinca rosea, Crotalaria verrucosa among the 30 medicinal plants in present study. The enhancement of growth and vigour and increased production of bioactive compounds of the medicinal plants is desirable which may be achieved by inoculation of the roots with Arbuscular mycorrhizal fungi. There is a steady increase in the cultivation of medicinal plants to maintain a steady supply to support the increasing demand but corresponding researches of VAM fungi and their association in medicinal plants have received very little attention as compared to the studies on forest species and field crops. So a vast research on this field is necessary for a better tomorrow.

Keywords: Arbuscular mycorrhizae, colonization, categories, medicinal plants

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Authors: Peng Hao Wang, Garam Kim, Ronald Sterkenburg

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In composite manufacturing, the fabrication of tooling and tooling maintenance contributes to a large portion of the total cost. However, as the applications of composite materials continue to increase, there is also a growing demand for more tooling. The demand for more tooling places heavy emphasis on the industry’s ability to fabricate high quality tools while maintaining the tool’s cost effectiveness. One of the popular techniques of tool fabrication currently being developed utilizes additive manufacturing technology known as 3D printing. The popularity of 3D printing is due to 3D printing’s ability to maintain low material waste, low cost, and quick fabrication time. In this study, a team of Purdue University School of Aviation and Transportation Technology (SATT) faculty and students investigated the effectiveness of a 3D printed composite mold. A steel valve cover from an aircraft reciprocating engine was modeled utilizing 3D scanning and computer-aided design (CAD) to create a 3D printed composite mold. The mold was used to fabricate carbon fiber versions of the aircraft reciprocating engine valve cover. The carbon fiber valve covers were evaluated for dimensional accuracy and quality while the 3D printed composite mold was evaluated for durability and dimensional stability. The data collected from this study provided valuable information in the understanding of 3D printed composite molds, potential improvements for the molds, and considerations for future tooling design.

Keywords: additive manufacturing, carbon fiber, composite tooling, molds

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Authors: Yakubu Abdulai, Kenichi Matsui

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The agricultural industry has faced a variety of challenges in meeting the expanding income demand of the rural population. As a result, rural households must diversify their income sources to meet their income demand. Although income diversification strategies help rural households, it contributes to total household income, and the socio-demographic determinants are not known in the Upper East Region of Ghana. For these reasons, the purpose of this study was to determine the contribution of income diversification strategies to household income and the socio-demographic factors influencing it. We conducted a questionnaire survey among 360 rural households in the Upper East Region of Ghana. We asked about their socio-demographic information, their choice of income diversification strategies, and their remittances through rural-city migration. The questionnaire survey findings demonstrate that the main livelihood income source contributes 22%, and on-farm income diversification contributes the most to household total income (47%), followed by non-farm diversification income (16%) and off-farm diversification income (15%). Calculations from the income diversity index showed that the average income diversification strategy was 0.5 out of 1. The calculation of the income dependence index also showed that the average dependent on a particular source of income was 0.2 out of 1. All the respondents said household members temporarily migrate to contribute to household income through remittances. The results further reveal that their choice of income diversification is influenced by their age, educational background, experience, and farm size. The paper recommends the promotion of rural development policies that increase income-generating activities and educate rural households on how to increase returns from their investment.

Keywords: income diversification, poverty alleviation, rural households, upper east region

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Authors: Cyrillus Prabandana

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Supply chain optimisation requires multiple factors as consideration or constraints. These factors are including but not limited to demand forecasting, raw material fulfilment, production capacity, inventory level, facilities locations, transportation means, and manpower availability. By knowing all manageable factors involved and assuming the uncertainty with pre-defined percentage factors, an integrated supply chain model could be developed to manage various business scenarios. This paper analyse the utilisation of geographical point of view to develop an integrated supply chain network model to optimise the distribution of finished product appropriately according to forecasted demand and available supply. The supply chain optimisation model shows that small change in one supply chain constraint is possible to largely impact other constraints, and the new information from the model should be able to support the decision making process. The model was focused on three areas, i.e. raw material fulfilment, production capacity and finished products transportation. To validate the model suitability, it was implemented in a project aimed to optimise the concrete supply chain in a mining location. The high level of operations complexity and involvement of multiple stakeholders in the concrete supply chain is believed to be sufficient to give the illustration of the larger scope. The implementation of this geographical supply chain network modeling resulted an optimised concrete supply chain from raw material fulfilment until finished products distribution to each customer, which indicated by lower percentage of missed concrete order fulfilment to customer.

Keywords: decision making, geographical supply chain modeling, supply chain optimisation, supply chain

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Authors: Abel Sichinava

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The need for organ transplantation is vigorously increasing worldwide. The numbers on the waiting lists grow, but the number of donors is not keeping up with the demand even though there is a legal possibility of decreasing the gap between the demand and supply. Most countries around the globe are facing an organ donation problem (living or deceased); however, the extent of the problem differs based on how well developed a country is. The determining issues seem to be centered on how aware the society is about the concept of organ donation, as well as cultural and religious factors. Even if people are aware of the benefits of organ donation, they may still have fears that keep them from being in complete agreement with the idea. Some believe that in the case of deceased organ donation: “the brain dead human body may recover from its injuries” or “the sick might get less appropriate treatment if doctors know they are potential donors.” In the case of living organ donations, people sometimes fear that after the donation, “it might reduce work efficiency, cause health deterioration or even death.” Another major obstacle in the organ shortage is a lack of a well developed ethical framework. In reality, there are truly an immense number of people on the waiting list, and they have only two options in order to receive a suitable organ. First is the legal way, which is to wait until their turn. Sadly, numerous patients die while on the waiting list before an appropriate organ becomes available for transplant. The second option is an illegal way: seeking an organ in a country where they can possibly get. To tell the truth, in people’s desire to live, they may choose the second option if their resources are sufficient. This process automatically involves “organ brokers.” These are people who get organs from vulnerable poor people by force or betrayal. As mentioned earlier, the high demand and low supply leads to human trafficking. The subject of the study was the large number of society from different backgrounds of their belief, culture, nationality, level of education, socio-economic status. The great majority of them interviewed online used “Google Drive Survey” and others in person. All statistics and information gathered from trusted sources annotated in the reference list and above mentioned considerable testimonies shared by the respondents are the fundamental evidence of a lack of the well developed ethical framework. In conclusion, the continuously increasing number of people on the waiting list and an irrelevant ethical framework, lead people to commit to atrocious, dehumanizing crimes. Therefore, world society should be equally obligated to think carefully and make vital decisions together for the advancement of an organ donations and its ethical framework.

Keywords: donation, ethical framwork, organ, transplant

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Authors: Shailja Thakur

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In this paper it is shown that how farmers are suffering from all sides including vagaries of weather then price fluctuations, demand supply constraints, poor soil health etc. Also the ICT can prove to be of great help if incorporated rightly into Indian agriculture. Some innovative ways to reward farmers and distribution of subsidies to them can improve the current scenario.

Keywords: cost of farming, information and communication technology, innovative steps, roof gardening, vermicomposting

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Authors: Usman A. Usman

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Undeniably, unlike the Classical side, the Keynesian perspective of the aggregate demand side indeed has a significant position in the policy, growth, and welfare of Nigeria due to government involvement and ineffective demand of the population living with poor per capita income. This study seeks to investigate the effect of Government Final Consumption Expenditure, Financial Deepening on Households, and NPISHs Final consumption expenditure using data on Nigeria from 1981 to 2019. This study employed the ADF stationarity test, Johansen Cointegration test, and Vector Error Correction Model. The results of the study revealed that the coefficient of Government final consumption expenditure has a positive effect on household consumption expenditure in the long run. There is a long-run and short-run relationship between gross fixed capital formation and household consumption expenditure. The coefficients cpsgdp financial deepening and gross fixed capital formation posit a negative impact on household final consumption expenditure. The coefficients money supply lm2gdp, which is another proxy for financial deepening, and the coefficient FDI have a positive effect on household final consumption expenditure in the long run. Therefore, this study recommends that Gross fixed capital formation stimulates household consumption expenditure; a legal framework to support investment is a panacea to increasing hoodmold income and consumption and reducing poverty in Nigeria. Therefore, this should be a key central component of policy.

Keywords: household, government expenditures, vector error correction model, johansen test

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Authors: Abhinav Chaturvedi, Joohi Chaturvedi, Renu Chaturvedi

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With rapid urbanization and growth of population, more buildings are require to be constructed to meet the increasing demand of the shelter. 80 % of the world population is living in developing countries, but the adequate energy supplied to only 30% of it. In India situation get little more difficult as majority of the villages of India are still deprived of energy. 1/3 of the Indian household does not have energy supply. So there is big gap between energy demand and supply. Moreover India is producing around 65 % of the energy from Non – Renewable sources and 25 % of the Energy is imported in the form of oil and gas and only 10% of the total, is generated from other sources like solar power, wind power etc. Present modern structures are big energy consumers as they are consuming 40 % of the total energy in providing comfort conditions to the users, in from of heating and cooling,5 % in Building Construction, 20 % in transportation and 20 % in industrial process and 10 % in other processes. If we minimize this Heating and Cooling and lighting load of the building we can conserve huge amount of energy for the future. In history, buildings do not have artificial systems of cooling or heating. These buildings, especially in Hadoti Region which have Semi Arid Climatic conditions, are provided with Solar Passive Design Techniques that is the reason of comfort inside the buildings. So if we use some appropriate elements of these heritage structures, in our present age building design we can find some certain solution to energy crises. Present paper describes Various Solar Passive design techniques used in past, and the same could be used in present to reduce the consumption of energy.

Keywords: energy conservation, Hadoti region, solar passive design techniques , semi - arid climatic condition

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Authors: Marjan Golmaryami, Marzieh Behzadi

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Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.

Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange

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Authors: J. Julius Adebayo

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The objective of this paper is to assess the agro-climatic condition of Ibadan in the rain forest ecological zone of Nigeria, using rainfall pattern and temperature between 1978-2018. Data on rainfall and temperature in Ibadan, Oyo State for a period of 40 years were obtained from Meteorological Section of Forestry Research Institute of Nigeria, Ibadan and Oyo State Meteorology Centre. Time series analysis was employed to analyze the data. The trend revealed that rainfall is decreasing slowly and temperature is averagely increasing year after year. The model for rainfall and temperature are Yₜ = 1454.11-8*t and Yₜ = 31.5995 + 2.54 E-02*t respectively, where t is the time. On this basis, a forecast of 20 years (2019-2038) was generated, and the results showed a further downward trend on rainfall and upward trend in temperature, this indicates persistence rainfall shortage and very hot weather for agricultural practices in the southwest rain forest ecological zone. Suggestions on possible solutions to avert climate change crisis and also promote climate-smart agriculture for sustainable food and nutrition security were also discussed.

Keywords: climate change, rainfall pattern, temperature, time series analysis, food and nutrition security

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Authors: A. Porshnev, A. Zaporozhtchuk

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Motivation regarded as a key factor of labor turnover, is especially important for volunteers working on an altruistic basis in NGO. Despite the motivational letter, candidate selection depends on the impression of the selection committee, which can be subject to human bias. We expect that structured and unstructured information provided in motivation letters could be used to improve candidate selection procedures. In our paper, we perform qualitative and quantitative analysis of 2280 motivation letters, create logistic regression, and build a decision tree to improve selection procedures. Our analysis showed that motivation factors are significant and enable human resources department to forecast labor turnover and provide extra information to demographic, professional and timing questions. In spite of the average level of accuracy the model demonstrates the selection procedures of company of under consideration can be improved. We also discuss interrelation between answers to open and closed motivation questions, recommend changes in motivational letter templates to ensure more relevant information about applicants and further steps to create more accurate model.

Keywords: decision trees, logistic regression, model, motivational letter, non-governmental organization, retention, turnover

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Authors: Chiranjit Das, Sanjay Jharkharia

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This study is focused on transport mode selection under lead time variability and emissions constraint. In order to reduce the carbon emissions generation due to transportation, organization has often faced a dilemmatic choice of transport mode selection since logistic cost and emissions reduction are complementary with each other. Another important aspect of transportation decision is lead-time variability which is least considered in transport mode selection problem. Thus, in this study, we provide a comprehensive mathematical based analytical model to decide transport mode selection under emissions constraint. We also extend our work through analysing the effect of lead time variability in the transport mode selection by a sensitivity analysis. In order to account lead time variability into the model, two identically normally distributed random variables are incorporated in this study including unit lead time variability and lead time demand variability. Therefore, in this study, we are addressing following questions: How the decisions of transport mode selection will be affected by lead time variability? How lead time variability will impact on total supply chain cost under carbon emissions? To accomplish these objectives, a total transportation cost function is developed including unit purchasing cost, unit transportation cost, emissions cost, holding cost during lead time, and penalty cost for stock out due to lead time variability. A set of modes is available to transport each node, in this paper, we consider only four transport modes such as air, road, rail, and water. Transportation cost, distance, emissions level for each transport mode is considered as deterministic and static in this paper. Each mode is having different emissions level depending on the distance and product characteristics. Emissions cost is indirectly affected by the lead time variability if there is any switching of transport mode from lower emissions prone transport mode to higher emissions prone transport mode in order to reduce penalty cost. We provide a numerical analysis in order to study the effectiveness of the mathematical model. We found that chances of stock out during lead time will be higher due to the higher variability of lead time and lad time demand. Numerical results show that penalty cost of air transport mode is negative that means chances of stock out zero, but, having higher holding and emissions cost. Therefore, air transport mode is only selected when there is any emergency order to reduce penalty cost, otherwise, rail and road transport is the most preferred mode of transportation. Thus, this paper is contributing to the literature by a novel approach to decide transport mode under emissions cost and lead time variability. This model can be extended by studying the effect of lead time variability under some other strategic transportation issues such as modal split option, full truck load strategy, and demand consolidation strategy etc.

Keywords: carbon emissions, inventory theoretic model, lead time variability, transport mode selection

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Authors: Louise Ödlund, Danica Djuric Ilic

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From a system perspective, there are several benefits of DH. A possibility to utilize the excess heat from waste incineration and biomass-based combined heat and power (CHP) production (e.g. possibility to utilize the excess heat from electricity production) are two examples. However, in a future sustainable society, the benefits of DH may be less obvious. Due to the climate changes and increased energy efficiency of buildings, the demand for space heating is expected to decrease. Due to the society´s development towards circular economy, a larger amount of the waste will be material recycled, and the possibility for DH production by the energy recovery through waste incineration will be reduced. Furthermore, the benefits of biomass-based CHP production will be less obvious since the marginal electricity production will no longer be linked to high greenhouse gas emissions due to an increased share of renewable electricity capacity in the electricity system. The purpose of the study is (1) to provide an overview of the possible development of other sectors which may influence the DH in the future and (2) to detect new business strategies which would enable for DH to adapt to the future conditions and remain competitive to alternative heat production in the future. A system approach was applied where DH is seen as a part of an integrated system which consists of other sectors as well. The possible future development of other sectors and the possible business strategies for DH producers were searched through a systematic literature review In order to remain competitive to the alternative heat production in the future, DH producers need to develop new business strategies. While the demand for space heating is expected to decrease, the space cooling demand will probably increase due to the climate changes, but also due to the better insulation of buildings in the cases where the home appliances are the heat sources. This opens up a possibility for applying DH-driven absorption cooling, which would increase the annual capacity utilization of the DH plants. The benefits of the DH related to the energy recovery from the waste incineration will exist in the future since there will always be a need to take care of materials and waste that cannot be recycled (e.g. waste containing organic toxins, bacteria, such as diapers and hospital waste). Furthermore, by operating central controlled heat pumps, CHP plants, and heat storage depending on the intermittent electricity production variation, the DH companies may enable an increased share of intermittent electricity production in the national electricity grid. DH producers can also enable development of local biofuel supply chains and reduce biofuel production costs by integrating biofuel and DH production in local DH systems.

Keywords: district heating, sustainable business strategies, sustainable development, system approach

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Authors: Khalid M. Albarkoly, Kenneth S. Park

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The substantial development of the construction industry has forced the cement industry, its major support, to focus on achieving maximum productivity to meet the growing demand for this material. Statistics indicate that the demand for cement rose from 1.6 billion metric tons (bmt) in 2000 to 4bmt in 2013. This means that the reliability of a production system needs to be at the highest level that can be achieved by good maintenance. This paper studies the extent to which the implementation of RCM is needed as a strategy for increasing the reliability of the production systems component can be increased, thus ensuring continuous productivity. In a case study of four Libyan cement factories, 80 employees were surveyed and 12 top and middle managers interviewed. It is evident that these factories usually breakdown more often than once per month which has led to a decline in productivity, they cannot produce more than 50% of their designed capacity. This has resulted from the poor reliability of their production systems as a result of poor or insufficient maintenance. It has been found that most of the factories’ employees misunderstand maintenance and its importance. The main cause of this problem is the lack of qualified and trained staff, but in addition, it has been found that most employees are not found to be motivated as a result of a lack of management support and interest. In response to these findings, it has been suggested that the RCM strategy should be implemented in the four factories. The paper shows the importance of considering the development of maintenance strategies through the implementation of RCM in these factories. The purpose of it would be to overcome the problems that could reduce the level of reliability of the production systems. This study could be a useful source of information for academic researchers and the industrial organisations which are still experiencing problems in maintenance practices.

Keywords: Libyan cement industry, reliability centred maintenance, maintenance, production, reliability

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Authors: Liliana Villavicencio, Yohn Garcia, Pallavi Singh, Luis Fernando Cruz, Wilfrido Moreno

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Psychophysiological adaptive automation is a concept that combines human physiological data and computer algorithms to create personalized interfaces and experiences for users. This approach aims to enhance human learning by adapting to individual needs and preferences and optimizing the interaction between humans and machines. According to neurosciences, the working memory demand during the student learning process is modified when the student is learning a new subject or topic, managing and/or fulfilling a specific task goal. A sudden increase in working memory demand modifies the level of students’ attention, engagement, and cognitive load. The proposed psychophysiological adaptive automation system will adapt the task requirements to optimize cognitive load, the process output variable, by monitoring the student's brain activity. Cognitive load changes according to the student’s previous knowledge, the type of task, the difficulty level of the task, and the overall psychophysiological state of the student. Scaling the measured cognitive load as low, medium, or high; the system will assign a task difficulty level to the next task according to the ratio between the previous-task difficulty level and student stress. For instance, if a student becomes stressed or overwhelmed during a particular task, the system detects this through signal measurements such as brain waves, heart rate variability, or any other psychophysiological variables analyzed to adjust the task difficulty level. The control of engagement and stress are considered internal variables for the hypermedia system which selects between three different types of instructional material. This work assesses the feasibility of a fuzzy controller to track a student's physiological responses and adjust the learning content and pace accordingly. Using an industrial automation approach, the proposed fuzzy logic controller is based on linguistic rules that complement the instrumentation of the system to monitor and control the delivery of instructional material to the students. From the test results, it can be proved that the implemented fuzzy controller can satisfactorily regulate the delivery of academic content based on the working memory demand without compromising students’ health. This work has a potential application in the instructional design of virtual reality environments for training and education.

Keywords: fuzzy logic controller, hypermedia control system, personalized education, psychophysiological adaptive automation

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Authors: Shreesh Sinha, Alexander B. Barker, Megan Parkin, Emma Wilson, Rachael L. Murray

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Background and Objectives: Exposure to HFSS imagery is associated with the consumption of foods high in fat, sugar or salt (HFSS), and subsequently obesity, among young people. We report and compare the results of two content analyses, one of two popular terrestrial children's television channels in the UK and the other of a selection of children's programmes available on video-on-demand (VOD) streaming sites. Methods: Content analysis of three days' worth of programmes (including advertisements) on two popular children's television channels broadcast on UK television (CBeebies and Milkshake) as well as a sample of 40 highest-rated children's programmes available on the VOD platforms, Netflix and Amazon Prime, using 1-minute interval coding. Results: HFSS content was seen in 181 broadcasts (36%) and in 417 intervals (13%) on terrestrial television, 'Milkshake' had a significantly higher proportion of programmes/adverts which contained HFSS content than 'CBeebies'. In VOD platforms, HFSS content was seen in 82 episodes (72% of the total number of episodes), across 459 intervals (19% of the total number of intervals), with no significant difference in the proportion of programmes containing HFSS content between Netflix and Amazon Prime. Conclusions: This study demonstrates that HFSS content is common in both popular UK children's television channels and children's programmes on VOD services. Since previous research has shown that HFSS content in the media has an effect on HFSS consumption, children's television programmes broadcast either on TV or VOD services are likely to have an effect on HFSS consumption in children, and legislative opportunities to prevent this exposure are being missed.

Keywords: public health, junk food, children's TV, HFSS

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Authors: Salahaeddine Sbai

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Air quality analysis using machine learning models is a method employed to assess and predict air pollution levels. This approach leverages the capabilities of machine learning algorithms to analyze vast amounts of air quality data and extract valuable insights. By training these models on historical air quality data, they can learn patterns and relationships between various factors such as weather conditions, pollutant emissions, and geographical features. The trained models can then be used to predict air quality levels in real-time or forecast future pollution levels. This application of machine learning in air quality analysis enables policymakers, environmental agencies, and the general public to make informed decisions regarding health, environmental impact, and mitigation strategies. By understanding the factors influencing air quality, interventions can be implemented to reduce pollution levels, mitigate health risks, and enhance overall air quality management. Climate change is having significant impacts on Morocco, affecting various aspects of the country's environment, economy, and society. In this study, we use some machine learning models under python environment to predict and analysis air quality change over North of Morocco to evaluate the climate change impact on agriculture.

Keywords: air quality, machine learning models, pollution, pollutant emissions

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Authors: Mar Cañada Soriano, Rafael Royo-Pastor, Carolina Aparicio-Fernández, Jose-Luis Vivancos

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The lack of insulation, along with the existence of air leakages, constitute a meaningful impact on the energy performance of buildings. Both of them lead to increases in the energy demand through additional heating and/or cooling loads. Additionally, they cause thermal discomfort. In order to quantify these uncontrolled air currents, pressurization and depressurization tests can be performed. Among them, the Blower Door test is a standardized procedure to determine the airtightness of a space which characterizes the rate of air leakages through the envelope surface, calculating to this purpose an air flow rate indicator. In this sense, the low-energy buildings complying with the Passive House design criteria are required to achieve high levels of airtightness. Due to the invisible nature of air leakages, additional tools are often considered to identify where the infiltrations take place. Among them, the infrared thermography entails a valuable technique to this purpose since it enables their detection. The aim of this study is to assess the airtightness of a typical Mediterranean dwelling house located in the Valencian orchad (Spain) restored under the Passive House standard using to this purpose the blower-door test. Moreover, the building energy performance modelling tools TRNSYS (TRaNsient System Simulation program) and TRNFlow (TRaNsient Flow) have been used to determine its energy performance, and the infiltrations’ identification was carried out by means of infrared thermography. The low levels of infiltrations obtained suggest that this house may comply with the Passive House standard.

Keywords: airtightness, blower door, trnflow, infrared thermography

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Authors: Neeraj Sahu, Ahmad Saadiq

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Anaerobic sulphate reduction has the potential for being effective and economically viable over conventional treatment methods for the treatment of sulphate-rich wastewater. However, a major challenge in anaerobic sulphate reduction is the diversion of a fraction of organic carbon towards methane production and some minor problem such as odour problems, corrosion, and increase of effluent chemical oxygen demand. A high-rate anaerobic technology has encouraged researchers to extend its application to the treatment of complex wastewaters with relatively low cost and energy consumption compared to physicochemical methods. Therefore, the aim of this study was to investigate the effects of COD/SO₄²⁻ ratio on the performance of lab scale UASB reactor. A lab-scale upflow anaerobic sludge blanket (UASB) reactor was operated for 170 days. In which first 60 days, for successful start-up with acclimation under methanogenesis and sulphidogenesis at COD/SO₄²⁻ of 18 and were operated at COD/SO₄²⁻ ratios of 12, 8, 4 and 1 to evaluate the effects of the presence of sulfate on the reactor performance. The reactor achieved maximum COD removal efficiency and biogas evolution at the end of acclimation (control). This phase lasted 53 days with 89.5% efficiency. The biogas was 0.6 L/d at (OLR) of 1.0 kg COD/m³d when it was treating synthetic wastewater with effective volume of reactor as 2.8 L. When COD/SO₄²⁻ ratio changed from 12 to 1, slight decrease in COD removal efficiencies (76.8–87.4%) was observed, biogas production decreased from 0.58 to 0.32 L/d, while the sulfate removal efficiency increased from 42.5% to 72.7%.

Keywords: anaerobic, chemical oxygen demand, organic loading rate, sulphate, up-flow anaerobic sludge blanket reactor

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Authors: Esther M. Folarin, Evans Osabuohien, Ademola Onabote

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Agriculture constitutes an important part of development and poverty mitigation in lower-middle-income countries, like Nigeria. The level of agricultural productivity in the Nigerian economy in line with the level of demand necessary to meet the desired expectation of the Nigerian populace is threatening to meeting the standard of the United Nations (UN) Sustainable Development Goals (SDGs); This includes the SDG-2 (achieve food security through agricultural productivity). The overall objective of the study is to reveal the performance of the interaction variable in the model among other factors that help in the achievement of greater Nigerian agricultural productivity. The study makes use of Wave 4 (2018/2019) of the Living Standard Measurement Studies, Integrated Survey on Agriculture (LSMS-ISA). Qualitative analysis of the information was also used to provide complimentary answers to the quantitative analysis done in the study. The study employed human capital theory and Grossman’s theory of health Demand in explaining the relationships that exist between the variables within the model of the study. The study engages the Instrumental Variable Regression technique in achieving the broad objectives among other techniques for the other specific objectives. The estimation results show that there exists a positive relationship between female healthcare and the level of female agricultural productivity in Nigeria. In conclusion, the study emphasises the need for more provision and empowerment for greater female access to healthcare and educational attainment levels that aids higher female agricultural productivity and consequently an improvement in the total agricultural productivity of the Nigerian economy.

Keywords: agricultural productivity, education, female, healthcare, investment

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Authors: A. Almaneea, N. Kapur, J. L. Summers, H. M. Thompson

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Meeting the growth in demand for digital services such as social media, telecommunications, and business and cloud services requires large scale data centres, which has led to an increase in their end use energy demand. Generally, over 30% of data centre power is consumed by the necessary cooling overhead. Thus energy can be reduced by improving the cooling efficiency. Air and liquid can both be used as cooling media for the data centre. Traditional data centre cooling systems use air, however liquid is recognised as a promising method that can handle the more densely packed data centres. Liquid cooling can be classified into three methods; rack heat exchanger, on-chip heat exchanger and full immersion of the microelectronics. This study quantifies the improvements of heat transfer specifically for the case of immersed microelectronics by varying the CPU and heat sink location. Immersion of the server is achieved by filling the gap between the microelectronics and a water jacket with a dielectric liquid which convects the heat from the CPU to the water jacket on the opposite side. Heat transfer is governed by two physical mechanisms, which is natural convection for the fixed enclosure filled with dielectric liquid and forced convection for the water that is pumped through the water jacket. The model in this study is validated with published numerical and experimental work and shows good agreement with previous work. The results show that the heat transfer performance and Nusselt number (Nu) is improved by 89% by placing the CPU and heat sink on the bottom of the microelectronics enclosure.

Keywords: CPU location, data centre cooling, heat sink in enclosures, immersed microelectronics, turbulent natural convection in enclosures

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Authors: M. R. Gholizadeh, N. Bhuiyan, M. Salari

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In the near future, companies will be increasingly forced to shift their activities along a new road in order to decrease the harmful effects of their design, production and after-life on our environment. Products must meet environmental standards to not only prevent penalties but to consider the sustainability for future generations. However, the most important factor that companies will face is selecting a reasonable strategy to maximize their profit. Thus, companies need to have precise forecast from their profit after design stage through Trade-off analysis. This paper is an attempt to introduce a mathematical model that considers effective factors that impact the total profit when products are designed for resource and energy efficiency or recyclability. The modification is according to different strategies based on a Cost-Volume-Profit model. Here, the cost structure consists of Recycling cost, Development cost, Ramp-up cost, Production cost, and Pollution cost. Also, the model shows the effect of implementation of design for recyclable on revenue structure through revenue of used parts and revenue of recycled materials. A numerical example is used to evaluate the proposed model. Results show that fulfillment of Green Product Development not only can reduce the environmental impact of products but also it will increase profit of company in long term.

Keywords: green product, design for environment, C-V-P model, trade-off analysis

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Authors: Elaine Wong Yee-Sing, Liaw Wee Tong

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Rapid transformations in demographic and socioeconomic shifts are leading to a growing global demand for health and beauty products and services that demands holistic concepts of well-being. In addition, technological breakthroughs such as internet of things make it convenient and offer innovative solutions for well-being and engage consumers to track their own health conditions and fitness goals. This 'new health economy' encompasses three key concepts: well-being, well-conditioned and well-shaped; which are shaped by wellness segments and goals that influence purchasing decisions of consumers. The research protocol aims to examine the feasibility, challenges, and capabilities in provision for each customer with an ecosystem, or platform, that organizes data and insights to create an individual health and fitness, nutrition, and beauty profile. Convenience sampling of 100 consumers residing in private housing within five major districts in Singapore will be selected to participate in the study. Statistical Package for Social Science 25 will be used to conduct descriptive statistics for quantitative data while qualitative data results using focus interviews, will be translated and transcribed to identify improvements in provision of these services. Rising income in emerging global markets is fuelling the demand for these general wellbeing products and services. Combined with technological advances, it is imperative to understand how these highly personalized services with integrated technology can be designed better to support consumer preferences; provide greater flexibility and high-quality service, and generate better health awareness among consumers.

Keywords: beauty, consumers, health, technology, wellness

Procedia PDF Downloads 131

Authors: Pierluigi Gallo, Francesco Randazzo, Ignazio Gallo

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

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

Procedia PDF Downloads 297

Authors: Sara Patricia Ibarra-Zavaleta, Rabindranarth Romero-Lopez, Rosario Langrave, Annie Poulin, Gerald Corzo, Mathias Glaus, Ricardo Vega-Azamar, Norma Angelica Oropeza

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The progressive change in climatic conditions worldwide has increased frequency and severity of extreme hydrometeorological events (EHE). Mexico is an example; this has been affected by the presence of EHE leaving economic, social and environmental losses. The objective of this research was to apply a Canadian distributed hydrological model (DHM) to tropical conditions and to evaluate its capacity to predict flows in a basin in the central Gulf of Mexico. In addition, the DHM (once calibrated and validated) was used to calculate the theoretical hydraulic power and the performance to predict streamflow before the presence of an EHE. The results of the DHM show that the goodness of fit indicators between the observed and simulated flows in the calibration process (NSE=0.83, RSR=0.021 and BIAS=-4.3) and validation: temporal was assessed at two points: point one (NSE=0.78, RSR=0.113 and BIAS=0.054) and point two (NSE=0.825, RSR=0.103 and BIAS=0.063) are satisfactory. The DHM showed its applicability in tropical environments and its ability to characterize the rainfall-runoff relationship in the study area. This work can serve as a tool for identifying vulnerabilities before floods and for the rational and sustainable management of water resources.

Keywords: HYDROTEL, hydraulic power, extreme hydrometeorological events, streamflow

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Authors: Alexander B. Barker, Megan Parkin, Shreesh Sinha, Emma Wilson, Rachael L. Murray

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Objectives: Exposure to HFSS imagery is associated with consumption of foods high in fat, sugar, or salt (HFSS), and subsequently obesity, among young people. We report and compare the results of two content analyses, one of two popular terrestrial children’s television channels in the UK and the other of a selection of children’s programs available on video-on-demand (VOD) streaming sites. Design: Content analysis of three days’ worth of programs (including advertisements) on two popular children’s television channels broadcast on UK television (CBeebies and Milkshake) as well as a sample of 40 highest-rated children’s programs available on the VOD platforms, Netflix and Amazon Prime, using 1-minute interval coding. Setting: United Kingdom, Participants: None. Results: HFSS content was seen in 181 broadcasts (36%) and in 417 intervals (13%) on terrestrial television, ‘Milkshake’ had a significantly higher proportion of programs/adverts which contained HFSS content than ‘CBeebies’. In VOD platforms, HFSS content was seen in 82 episodes (72% of the total number of episodes), across 459 intervals (19% of the total number of intervals), with no significant difference in the proportion of programs containing HFSS content between Netflix and Amazon Prime. Conclusions: This study demonstrates that HFSS content is common in both popular UK children’s television channels and children's programs on VOD services. Since previous research has shown that HFSS content in the media has an effect on HFSS consumption, children’s television programs broadcast either on TV or VOD services are likely having an effect on HFSS consumption in children and legislative opportunities to prevent this exposure are being missed.

Keywords: public health, epidemiology, obesity, content analysis

Procedia PDF Downloads 194

Authors: Kashif Hassan, M.A. Ahanger

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Floods have become more frequent and severe due to effects of global climate change and human alterations of the natural environment. Flood prediction/ forecasting and control is one of the greatest challenges facing the world today. The forecast of floods is achieved by the use of hydraulic models such as HEC-RAS, which are designed to simulate flow processes of the surface water. Extreme flood events in river Jhelum , lasting from a day to few are a major disaster in the State of Jammu and Kashmir, India. In the present study HEC-RAS model was applied to two different reaches of river Jhelum in order to estimate the flood levels corresponding to 25, 50 and 100 year return period flood events at important locations and to deduce flood vulnerability of important areas and structures. The flow rates for the two reaches were derived from flood-frequency analysis of 50 years of historic peak flow data. Manning's roughness coefficient n was selected using detailed analysis. Rating Curves were also generated to serve as base for determining the boundary conditions. Calibration and Validation procedures were applied in order to ensure the reliability of the model. Sensitivity analysis was also performed in order to ensure the accuracy of Manning's n in generating water surface profiles.

Keywords: flood plain, HEC-RAS, Jhelum, return period

Procedia PDF Downloads 429

Authors: Nana Segu Acquaah-Harrison, James Osei Mensah, Richard Aidoo, David Amponsah, Amy Buah, Gilbert Aboagye

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The study aimed at assessing the feasibility of commercial meat rabbit production in the Kumasi Metropolis of Ghana. Structured and unstructured questionnaires were utilized in obtaining information from two hundred meat consumers and 15 meat rabbit farmers. Data were analyzed using Net Present Value (NPV), Internal Rate of Return (IRR), Benefit Cost Ratio (BCR)/Profitability Index (PI) technique, percentages and chi-square contingency test. The study found that the current demand for rabbit meat is low (36%). The desirable nutritional attributes of rabbit meat and other socio economic factors of meat consumers make the potential demand for rabbit meat high (69%). It was estimated that GH¢5,292 (approximately $ 2672) was needed as a start-up capital for a 40-doe unit meat rabbit farm in Kumasi Metropolis. The cost of breeding animals, housing and equipment formed 12.47%, 53.97% and 24.87% respectively of the initial estimated capital. A Net Present Value of GH¢ 5,910.75 (approximately $ 2984) was obtained at the end of the fifth year, with an internal rate return and profitability index of 70% and 1.12 respectively. The major constraints identified in meat rabbit production were low price of rabbit meat, shortage of fodder, pest and diseases, high cost of capital, high cost of operating materials and veterinary care. Based on the analysis, it was concluded that meat rabbit production is feasible in the Kumasi Metropolis of Ghana. The study recommends embarking on mass advertisement; farmer association and adapting to new technologies in the production process will help to enhance productivity.

Keywords: feasibility, commercial meat rabbit, production, Kumasi, Ghana

Procedia PDF Downloads 137

Authors: A. Rong, P. B. Luh, R. Lahdelma

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High penetration of intermittent renewable energy sources (RES) such as solar power and wind power into the energy system has caused temporal and spatial imbalance between electric power supply and demand for some countries and regions. This brings about the critical need for coordinating power production and power exchange for different regions. As compared with the power-only systems, the combined heat and power (CHP) systems can provide additional flexibility of utilizing RES by exploiting the interdependence of power and heat production in the CHP plant. In the CHP system, power production can be influenced by adjusting heat production level and electric power can be used to satisfy heat demand by electric boiler or heat pump in conjunction with heat storage, which is much cheaper than electric storage. This paper addresses multi-site CHP systems without considering RES, which lay foundation for handling penetration of RES. The problem under study is the unit commitment (UC) of the transmission-constrained multi-site CHP systems. We solve the problem by combining linear relaxation of ON/OFF states and sequential dynamic programming (DP) techniques, where relaxed states are used to reduce the dimension of the UC problem and DP for improving the solution quality. Numerical results for daily scheduling with realistic models and data show that DP-based algorithm is from a few to a few hundred times faster than CPLEX (standard commercial optimization software) with good solution accuracy (less than 1% relative gap from the optimal solution on the average).

Keywords: dynamic programming, multi-site combined heat and power system, relaxed states, transmission-constrained generation unit commitment

Procedia PDF Downloads 369