Search results for: food system model

Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli

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Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.

Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models

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Authors: Xiaoxian Zhang

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Guidelines of ecological risk assessment (ERA) and food safety assessment (FSA) used nowadays, based on an S-shaped threshold dose-response curve (SDR), fail to consider hormesis, a reproducible biphasic dose-response model represented as a J-shaped or an inverted U-shaped curve, that occurs in the real-life environment across multitudinous compounds on cells, organisms, populations, and even the ecosystem. Specifically, in SDR-based ERA and FSA practice, predicted no effect concentration (PNEC) is calculated separately for individual substances from no observed effect concentration (NOEC, usually equivalent to 10% effect concentration (EC10) of a contaminant or food condiment) over an assessment coefficient that is bigger than 1. Experienced researchers doubted that hormesis in the real-life environment might lead to a waste of limited human and material resources in ERA and FSA practice, but related data are scarce. In this study, hormetic effects on bioluminescence of Aliivibrio fischeri (A. f) induced by sulfachloropyridazine (SCP) under 40 conditions to simulate the real-life scenario were investigated, and hormetic effects on growth of human MCF-7 cells caused by brown sugar and mascavado sugar were found likewise. After comparison of related parameters, it has for the first time been proved that there is a 50% probability for safe concentration (SC) of contaminants and food condiments to fall within the hormetic-stimulatory range (HSR) or left to HSR, revealing the unreliability of traditional parameters in standardized (eco)toxicological studies, and supporting qualitatively and quantitatively the over-strictness of ERA and FSA resulted from misuse of SDR. This study provides a novel perspective for ERA and FSA practitioners that hormesis should dominate and conditions where SDR works should only be singled out on a specific basis.

Keywords: dose-response relationship, food safety, ecological risk assessment, hormesis

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Authors: Sofia N. Gonçalves, Duarte M. S. Albuquerque, José C. F. Pereira

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The energy transition is spurred by structural changes in energy demand, supply, and prices. Microwave technology was first proposed as a faster alternative for cooking food. It was found that food heated instantly when interacting with high-frequency electromagnetic waves. The dielectric properties account for a material’s ability to absorb electromagnetic energy and dissipate this energy in the form of heat. Many energy-intense industries could benefit from electromagnetic heating since many of the raw materials are dielectric at high temperatures. Limestone sedimentary rock is a dielectric material intensively used in the cement industry to produce unslaked lime. A numerical 3D model was implemented in COMSOL Multiphysics to study the limestone continuous processing under microwave heating. The model solves the two-way coupling between the Energy equation and Maxwell’s equations as well as the coupling between heat transfer and chemical interfaces. Complementary, a controller was implemented to optimize the overall heating efficiency and control the numerical model stability. This was done by continuously matching the cavity impedance and predicting the required energy for the system, avoiding energy inefficiencies. This controller was developed in MATLAB and successfully fulfilled all these goals. The limestone load influence on thermal decomposition and overall process efficiency was the main object of this study. The procedure considered the Verification and Validation of the chemical kinetics model separately from the coupled model. The chemical model was found to correctly describe the chosen kinetic equation, and the coupled model successfully solved the equations describing the numerical model. The interaction between flow of material and electric field Poynting vector revealed to influence limestone decomposition, as a result from the low dielectric properties of limestone. The numerical model considered this effect and took advantage from this interaction. The model was demonstrated to be highly unstable when solving non-linear temperature distributions. Limestone has a dielectric loss response that increases with temperature and has low thermal conductivity. For this reason, limestone is prone to produce thermal runaway under electromagnetic heating, as well as numerical model instabilities. Five different scenarios were tested by considering a material fill ratio of 30%, 50%, 65%, 80%, and 100%. Simulating the tube rotation for mixing enhancement was proven to be beneficial and crucial for all loads considered. When uniform temperature distribution is accomplished, the electromagnetic field and material interaction is facilitated. The results pointed out the inefficient development of the electric field within the bed for 30% fill ratio. The thermal efficiency showed the propensity to stabilize around 90%for loads higher than 50%. The process accomplished a maximum microwave efficiency of 75% for the 80% fill ratio, sustaining that the tube has an optimal fill of material. Electric field peak detachment was observed for the case with 100% fill ratio, justifying the lower efficiencies compared to 80%. Microwave technology has been demonstrated to be an important ally for the decarbonization of the cement industry.

Keywords: CFD numerical simulations, efficiency optimization, electromagnetic heating, impedance matching, limestone continuous processing

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Authors: Abdullah Al. Morshed, Mohammad Nahid Mia

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Introduction: Food security refers to the availability of food and a person’s access to it. It is a complex sustainable development issue, which is closely related to under-nutrition. Food security, in turn, can widely affect the living standard, and is rooted in poverty and leads to poor health, low productivity, low income, food shortage, and hunger. The study's aim was to identify the most vulnerable women who are in insecure positions. Method: 17,842 married women were selected for analysis from the Bangladesh Demographic and Health Survey 2011. Food security defined as dichotomous variables of skipped meals and eaten less food at least once in the last year. The outcome variables were cross-tabulated with women's socio-demographic characteristics and chi2 test was applied to see the significance. Logistic regression models were applied to identify the most vulnerable groups in terms of food security. Result: Only 18.5% of women said that they ever had to skip meals in the last year. 45.7% women from low socioeconomic status had skip meal for at least once whereas only 3.6% were from women with highest socioeconomic status. Women meal skipping was ranged from 1.4% to 34.2% by their educational status. 22% of women were eaten less food during the last year. The rate was higher among the poorest (51.6%), illiterate (39.9%) and household have no electricity connection (38.1) in compared with richest (4.4%), higher educated (2.0%), and household has electricity connection (14.0%). The logistic regression analysis indicated that household socioeconomic status, and women education show strong gradients to skip meals. Poorest have had higher odds (20.9) than richest and illiterate women had 7.7 higher odds than higher educated. In terms of religion, Christianity was 2.3 times more likely to skip their meals than Islam. On the other hand, a similar trend was observed in our other outcome variable eat less food. Conclusion: In this study we able to identify women with lower economics status and women with no education were mostly suffered group from starvation.

Keywords: food security, hunger, under-nutrition, women

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Authors: Hafizan Junoh, Kumaran Palanisamy, Yip Chan Heng, Pua Fei Ling

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This study investigates the influence of low temperature thermo-chemical pretreatment of organic food waste on the performance of COD solubilisation. Both temperature and alkaline agent were reported to have an effect on solubilizing any possible biomass including organic food waste. The three independent variables considered in this pretreatment were temperature (50-90oC), pretreatment time (30-120 minutes) and alkaline concentration, sodium hydroxide, NaOH (0.7-15 g/L). The optimal condition obtained were 90oC, 15 g/L NaOH for 2 hours. Solubilisation has potential in enhancing methane production by providing a high amount of soluble components at an early stage during anaerobic digestion.

Keywords: food waste, pretreatments, respond surface methodology, ANOVA, anaerobic digestion

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Authors: Kavitha Thamadharan, Nurazean Maarop

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The implementation of e-assessment as tool to support the process of teaching and learning in university has become a popular technological means in universities. E-Assessment provides many advantages to the users especially the flexibility in teaching and learning. The e-assessment system has the capability to improve its quality of delivering education. However, there still exists a drawback in terms of security which limits the user acceptance of the online learning system. Even though there are studies providing solutions for identified security threats in e-learning usage, there is no particular model which addresses the factors that influences the acceptance of e-assessment system by lecturers from security perspective. The aim of this study is to explore security aspects of e-assessment in regard to the acceptance of the technology. As a result a conceptual model of secure acceptance of e-assessment is proposed. Both human and security factors are considered in formulation of this conceptual model. In order to increase understanding of critical issues related to the subject of this study, interpretive approach involving convergent mixed method research method is proposed to be used to execute the research. This study will be useful in providing more insightful understanding regarding the factors that influence the user acceptance of e-assessment system from security perspective.

Keywords: secure technology acceptance, e-assessment security, e-assessment, education technology

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Authors: Israa Al-Neami, Ali J. Al-Askery, Martin Johnston, Charalampos Tsimenidis

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In this paper, we focus on the design of a multi-line copper wire (MLCW) communication system. First, we construct our proposed MLCW channel and verify its characteristics based on the Kolmogorov-Smirnov test. In addition, we apply Middleton class A impulsive noise (IN) to the copper channel for further investigation. Second, the MIMO G.fast system is adopted utilizing the proposed MLCW channel model and is compared to a single line G-fast system. Second, the performance of the coded system is obtained utilizing concatenated interleaved Reed-Solomon (RS) code with four-dimensional trellis-coded modulation (4D TCM), and compared to the single line G-fast system. Simulations are obtained for high quadrature amplitude modulation (QAM) constellations that are commonly used with G-fast communications, the results demonstrate that the bit error rate (BER) performance of the coded MLCW system shows an improvement compared to the single line G-fast systems.

Keywords: G.fast, Middleton Class A impulsive noise, mitigation techniques, Copper channel model

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Authors: Nasiruddin Khan, Saud Iqbal

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Arabian Gulf region has undergone enormous development due to oil boom resulting in overwhelming changes in the lifestyle of the population over the past few decades. This study focused on food consumption patterns of Omani university students. Information, on anthropometric measurements, dietary intakes (measured by a food frequency questionnaire) of students was recorded. Anthropometric data revealed 62.5% of the subjects to be of normal weight and approximately 25% being overweight. Female students appeared to be more weight conscious than males. Dietary intakes in terms of servings (Mean ± S.D) per day among normal weight (BMI 18.5 – 24.9) males vs. females were approximately; cereals (7.5 ± 5.9 vs. 4.9 ± 2.9 servings), meat and alternatives (1.9 ± 0.9 vs. 1.5 ± 0.9 servings), dairy foods (0.9 ± 0.8 vs. 1.1 ± 0.9 servings) per day, respectively. Overall 55.3% of both males (average 1.9 servings) as well as females (average 1.7 servings) had severely inadequate intakes of vegetables on a daily basis as per the food guide pyramid recommendations. Only the fruit group intakes were adequate in about 70% of the population. Adequate intakes of dairy and meat and alternatives group were found in only 22% and 32% of the subjects, respectively. These results indicate a significant influence of a modern lifestyle on dietary habits and food selection of the target population.

Keywords: dietary pattern, food guide pyramid, lifestyle, Oman

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Authors: Baye Berihun Getahun, Mulugeta Atnaf Tiruneh, Richard G. F. Visser

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Resource-poor farmers practice low-input farming systems, and yet, most breeding programs give less attention to this huge farming system, which serves as a source of food and income for several people in developing countries. The high-input conventional breeding system appears to have failed to adequately meet the needs and requirements of 'difficult' environments operating under this system. Moreover, the unavailability of resources for crop production is getting for their peaks, the environment is maltreated by excessive use of agrochemicals, crop productivity reaches its plateau stage, particularly in the developed nations, the world population is increasing, and food shortage sustained to persist for poor societies. In various parts of the world, genetic gain at the farmers' level remains low which could be associated with low adoption of crop varieties, which have been developed under high input systems. Farmers usually use their local varieties and apply minimum inputs as a risk-avoiding and cost-minimizing strategy. This evidence indicates that the conventional high-input plant breeding system has failed to feed the world population, and the world is moving further away from the United Nations' goals of ending hunger, food insecurity, and malnutrition. In this review, we discussed the rationality of focused breeding programs for low-input farming systems and, the technical aspect of crop breeding that accommodates future food needs and its significance for developing countries in the decreasing scenario of resources required for crop production. To this end, the application of exotic introgression techniques like polyploidization, pan-genomics, comparative genomics, and De novo domestication as a pre-breeding technique has been discussed in the review to exploit the untapped genetic diversity of the crop wild relatives (CWRs). Desired recombinants developed at the pre-breeding stage are exploited through appropriate breeding approaches such as evolutionary plant breeding (EPB), rhizosphere-related traits breeding, and participatory plant breeding approaches. Populations advanced through evolutionary breeding like composite cross populations (CCPs) and rhizosphere-associated traits breeding approach that provides opportunities for improving abiotic and biotic soil stress, nutrient acquisition capacity, and crop microbe interaction in improved varieties have been reviewed. Overall, we conclude that low input farming system is a huge farming system that requires distinctive breeding approaches, and the exotic pre-breeding introgression techniques and the appropriate breeding approaches which deploy the skills and knowledge of both breeders and farmers are vital to develop heterogeneous landrace populations, which are effective for farmers practicing low input farming across the world.

Keywords: low input farming, evolutionary plant breeding, composite cross population, participatory plant breeding

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Authors: M. Draman, S. Z. Muhamad Yassin, M. S. Alias, Z. Lambak, M. I. Zulkifli, S. N. Padhi, K. N. Baharim, F. Maskuriy, A. I. A. Rahim

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The performance of Malay automatic speech recognition (ASR) system for the call centre environment is presented. The system utilizes Kaldi toolkit as the platform to the entire library and algorithm used in performing the ASR task. The acoustic model implemented in this system uses a deep neural network (DNN) method to model the acoustic signal and the standard (n-gram) model for language modelling. With 80 hours of training data from the call centre recordings, the ASR system can achieve 72% of accuracy that corresponds to 28% of word error rate (WER). The testing was done using 20 hours of audio data. Despite the implementation of DNN, the system shows a low accuracy owing to the varieties of noises, accent and dialect that typically occurs in Malaysian call centre environment. This significant variation of speakers is reflected by the large standard deviation of the average word error rate (WERav) (i.e., ~ 10%). It is observed that the lowest WER (13.8%) was obtained from recording sample with a standard Malay dialect (central Malaysia) of native speaker as compared to 49% of the sample with the highest WER that contains conversation of the speaker that uses non-standard Malay dialect.

Keywords: conversational speech recognition, deep neural network, Malay language, speech recognition

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Authors: Dnyandip K. Bhamare, Manish K Rathod, Jyotirmay Banerjee

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This paper aims to study performance of a thermosiphon solar water heating system with the help of the proposed analytical model. This proposed model predicts the temperature and mass flow rate in a thermosiphon solar water heating system depending on radiation intensity and ambient temperature. The performance of the thermosiphon solar water heating system is evaluated in the Indian context. For this, eight cities in India are selected considering radiation intensity and geographical positions. Predicted performance at various cities reveals the potential for thermosiphon solar water in India.

Keywords: solar water heater, collector outlet temperature, thermosyphon, India

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Authors: Hajara Abdulkarim Aliyu, Abdulbasid Ismail Isa

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This research paper studies electrohydraulic system for its role in position and motion control system and develops as mathematical model describing the behaviour of the system. The research further proposes Fuzzy logic and conventional PID controllers in order to achieve both accurate positioning of the payload and overall improvement of the system performance. The simulation result shows Fuzzy logic controller has a superior tracking performance and high disturbance rejection efficiency for its shorter settling time, less overshoot, smaller values of integral of absolute and deviation errors over the conventional PID controller at all the testing conditions.

Keywords: electrohydraulic, fuzzy logic, modelling, NZ-PID

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Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Giovanni Cuciniello

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: flapping dynamics, flight dynamics, system identification, tilt-rotor modeling and simulation

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Authors: Nahid Banihashemi

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An emerging important area of the life sciences is systems biology, which involves understanding the integrated behavior of large numbers of components interacting via non-linear reaction terms. A centrally important problem in this area is an understanding of the co-metabolism of protein and carbohydrate, as it has been clearly demonstrated that the ratio of these metabolites in diet is a major determinant of obesity and related chronic disease. In this regard, we have considered a systems biology model for the co-metabolism of carbon and nitrogen in colonies of the fungus Mucor mucedo. Oscillations are an important diagnostic of underlying dynamical processes of this model. The maintenance of specific patterns of oscillation and its relation to the robustness of this system are the important issues which have been targeted in this paper. In this regard, parametric sensitivity approach as a theoretical approach has been considered for the analysis of the robustness of this model. As a result, the parameters of the model which produce the largest sensitivities have been identified. Furthermore, the largest changes that can be made in each parameter of the model without losing the oscillations in biomass production have been computed. The results are obtained from the implementation of parametric sensitivity analysis in Matlab.

Keywords: system biology, parametric sensitivity analysis, robustness, carbon and nitrogen co-metabolism, Mucor mucedo

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Authors: Widari

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This study aims to determine the relationship of fast food consumption preferences with macro and micro nutrient adequacy students of SMP Negeri 5 Padang. This study used a cross sectional study conducted on 100 students of SMP Negeri 5 Padang. The variables studied were fast food preferences, nutrition adequacy macronutrients (carbohydrate, protein, fat, fiber) and micro nutrients (sodium, calcium, iron). Confounding factor in this study was the physical activity level because it was considered quite affecting food consumption of students. Data collected by using a questionnaire food recall as many as 2 x 24 hours to see the history of the respondents eat at school day and on holidays. Then, data processed using software Nutrisurvey and Microsoft Excel 2010. The analysis was performed on samples that have low and medium category on physical activity. The physical activity was not analyzed with another variable to see the strength of the relationship between independent and dependent variables. So that, do restrictions on physical activity variables in an attempt to get rid of confounding in design. Univariate and bivariate analyzes performed using SPSS 16.0 for Windows with Kolmogrov-Smirnov statistical tests, confidence level = 95% (α = 0,05). Results of univariate analysis showed that more than 70% of respondents liked fast food. On average, respondents were malnourished macro; malnourished fiber (100%), carbohydrates (72%), and protein (56%), whereas for fat, excess intake of the respondents (41%). Furthermor, many respondents who have micronutrient deficiencies; 98% for sodium, 96% for iron, and 91% for calcium. The results of the bivariate analysis showed no significant association between fast food consumption preferences with macro and micro nutrient adequacy (p > 0,05). This happens because in the fact not all students who have a preference for fast food actually eat them. To study better in the future, it is expected sampling really like and eat fast food in order to obtain better analysis results.

Keywords: fast food, nutritional adequacy, preferences, students

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Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

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An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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Authors: Ji-Seok Koo, Hee‑Yong Kwon, Hui-Young Yun, Kyung-Hui Wang, Youn-Seo Koo

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This paper presents a forecasting system for PM2.5 levels in Seoul, South Korea, leveraging a combination of chemical transport modeling and ConvLSTM-DNN machine learning technology. Exposure to PM2.5 has known detrimental impacts on public health, making its prediction crucial for establishing preventive measures. Existing forecasting models, like the Community Multiscale Air Quality (CMAQ) and Weather Research and Forecasting (WRF), are hindered by their reliance on uncertain input data, such as anthropogenic emissions and meteorological patterns, as well as certain intrinsic model limitations. The system we've developed specifically addresses these issues by integrating machine learning and using carefully selected input features that account for local and distant sources of PM2.5. In South Korea, the PM2.5 concentration is greatly influenced by both local emissions and long-range transport from China, and our model effectively captures these spatial and temporal dynamics. Our PM2.5 prediction system combines the strengths of advanced hybrid machine learning algorithms, convLSTM and DNN, to improve upon the limitations of the traditional CMAQ model. Data used in the system include forecasted information from CMAQ and WRF models, along with actual PM2.5 concentration and weather variable data from monitoring stations in China and South Korea. The system was implemented specifically for Seoul's PM2.5 forecasting.

Keywords: PM2.5 forecast, machine learning, convLSTM, DNN

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Authors: Pongsiri Kingkan

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This research aims to study the Readiness of Thai Restaurant in Bangkok in Applying for Certification of Halal Food Services Standard for Tourism. This research was conduct by using mix methodology; both quantitative and qualitative data were used. 420 questionnaires were used as tools to collected data from the samples, the restaurant employees. The results were divided into two parts, the demographic data and the Readiness of Thai Restaurant in Bangkok in Applying for Certification of Halal Food Services Standard for Tourism. The majority of samples are single female age between 18–30 years old, who earn about 282.40 US dollars a month. The result of Thai restaurant readiness study demonstrated that readiness in foods and restaurant operating processes were scored at the lowest level. Readiness in social responsibility, food contact persons and food materials were rated at the low level. The readiness of utensils and kitchen tools, waste management, environmental management, and the availability of space to implement the establishment of halal food were scored at the average level. Location readiness, foods service safety and the relationship with the local community were rated at high level. But interestingly there is none of them rated at the highest level.

Keywords: availability, Bangkok, halal, Thai restaurant, readiness

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Authors: Sh. Wafa, M. Alanoud, S. Liyakathunisa

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Online booking for a trip or hotel has become an indispensable traveling tool today, people tend to be more interested in selecting air flight travel as their first choice when going for a long trip. People's shopping behavior has greatly changed by the advent of social network. Traditional ticket booking methods are considered as outdated with the advancement in tools and technology. Web based booking framework is an 'absolute necessity to have' for any visit or movement business that is investing heaps of energy noting telephone calls, sending messages or considering employing more staff. In this paper, we propose a process model for online trip reservation for our designed web application. Our proposed system will be highly beneficial and helps in reduction in time and cost for customers.

Keywords: trip, hotel, reservation, process model, time, cost, web app

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Authors: Dana Alghool, Tarek ElMekkawy, Mohamed Haouari, Adel Elomari

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District cooling systems have captured the attentions of many researchers recently due to the enormous benefits offered by such system in comparison with traditional cooling technologies. It is considered a major component of urban cities due to the significant reduction of energy consumption. This paper aims to find the optimal design and operation of district cooling systems by developing a mixed integer linear programming model to minimize the annual total system cost and satisfy the end-user cooling demand. The proposed model is experimented with different cooling demand scenarios. The results of the very high cooling demand scenario are only presented in this paper. A sensitivity analysis on different parameters of the model was performed.

Keywords: Annual Cooling Demand, Compression Chiller, Mathematical Modeling, District Cooling Systems, Optimization

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Authors: Markus Mazzola, Gunther Schaaf

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A vehicle driving with an Adaptive Cruise Control System (ACC) is usually controlled decentrally, based on the information of radar systems and in some publications based on C2X-Communication (CACC) to guarantee stable platoons. In this paper, we present a Model Predictive Control (MPC) design of a centralized, server-based ACC-System, whereby the vehicular platoon is modeled and controlled as a whole. It is then proven that the proposed MPC design guarantees asymptotic stability and hence string stability of the platoon. The Networked MPC design is chosen to be able to integrate system constraints optimally as well as to reduce the effects of communication delay and packet loss. The performance of the proposed controller is then simulated and analyzed in an LTE communication scenario using the LTE/EPC Network Simulator LENA, which is based on the ns-3 network simulator.

Keywords: adaptive cruise control, centralized server, networked model predictive control, string stability

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Authors: Tengqin Han

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Delinquency has been a crucial factor in economics throughout the years. Commonly seen in credit card and mortgage, it played one of the crucial roles in causing the most recent financial crisis in 2008. In each case, a delinquency is a sign of the loaner being unable to pay off the debt, and thus may cause a lost of property in the end. Individually, one case of delinquency seems unimportant compared to the entire credit system. China, as an emerging economic entity, the national strength and economic strength has grown rapidly, and the gross domestic product (GDP) growth rate has remained as high as 8% in the past decades. However, potential risks exist behind the appearance of prosperity. Among the risks, the credit system is the most significant one. Due to long term and a large amount of balance of the mortgage, it is critical to monitor the risk during the performance period. In this project, about 300,000 mortgage account data are analyzed in order to develop a predictive model to predict the probability of delinquency. Through univariate analysis, the data is cleaned up, and through bivariate analysis, the variables with strong predictive power are detected. The project is divided into two parts. In the first part, the analysis data of 2005 are split into 2 parts, 60% for model development, and 40% for in-time model validation. The KS of model development is 31, and the KS for in-time validation is 31, indicating the model is stable. In addition, the model is further validation by out-of-time validation, which uses 40% of 2006 data, and KS is 33. This indicates the model is still stable and robust. In the second part, the model is improved by the addition of macroeconomic economic indexes, including GDP, consumer price index, unemployment rate, inflation rate, etc. The data of 2005 to 2010 is used for model development and validation. Compared with the base model (without microeconomic variables), KS is increased from 41 to 44, indicating that the macroeconomic variables can be used to improve the separation power of the model, and make the prediction more accurate.

Keywords: delinquency, mortgage, model development, model validation

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Authors: Ming-Chien Su, Yi-Zih Chen, Nien-Hsin Kao, Hideaki Shibata

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The major component of the atmosphere is nitrogen, yet atmospheric nitrogen has limited availability for biological use. Human activities have produced different types of nitrogen related compounds such as nitrogen oxides from combustion, nitrogen fertilizers from farming, and the nitrogen compounds from waste and wastewater, all of which have impacted the environment. Many studies have indicated the N-footprint is dominated by food, followed by housing, transportation, and goods and services sectors. To solve the impact issues from agricultural land, nitrogen cycle research is one of the key solutions. The study site is located in Hualien County, Taiwan, a major rice and food production area of Taiwan. Importantly, environmentally friendly farming has been promoted for years, and an environmental indicator system has been established by previous authors based on the concept of resilience capacity index (RCI) and environmental performance index (EPI). Nitrogen management is required for food production, as excess N causes environmental pollution. Therefore it is very important to develop a roadmap of the nitrogen footprint, and to integrate it with environmental indicators. The key focus of the study thus addresses (1) understanding the environmental impact caused by the nitrogen cycle of food products and (2) uncovering the trend of the N-footprint of agricultural products in Hualien, Taiwan. The N-footprint model was applied, which included both crops and energy consumption in the area. All data were adapted from government statistics databases and crosschecked for consistency before modeling. The actions involved with agricultural production were evaluated and analyzed for nitrogen loss to the environment, as well as measuring the impacts to humans and the environment. The results showed that rice makes up the largest share of agricultural production by weight, at 80%. The dominant meat production is pork (52%) and poultry (40%); fish and seafood were at similar levels to pork production. The average per capita food consumption in Taiwan is 2643.38 kcal capita−1 d−1, primarily from rice (430.58 kcal), meats (184.93 kcal) and wheat (ca. 356.44 kcal). The average protein uptake is 87.34 g capita−1 d−1, and 51% is mainly from meat, milk, and eggs. The preliminary results showed that the nitrogen footprint of food production is 34 kg N per capita per year, congruent with the results of Shibata et al. (2014) for Japan. These results provide a better understanding of the nitrogen demand and loss in the environment, and the roadmap can furthermore support the establishment of nitrogen policy and strategy. Additionally, the results serve to develop a roadmap of the nitrogen cycle of an environmentally friendly farming area, thus illuminating the nitrogen demand and loss of such areas.

Keywords: agriculture productions, energy consumption, environmental indicator, nitrogen footprint

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Authors: Andy Sand, Naama Massad – Ivanir, Nadav Nitzan, Elisa Valderrama, Alfred Wegenberger, Koranit Shlosman, Rotem Shemesh, Ester Segal

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Microbial spoilage of food products is of great concern in the food industry due to the direct impact on the shelf life of foods and the risk of foodborne illness. Therefore, food packaging may serve as a crucial contribution to keep the food fresh and suitable for consumption. Active packaging solutions that have the ability to inhibit the development of microorganism in food products attract a lot of interest, and many efforts have been made to engineer and assimilate such solutions on various food products. NanoPack is an EU-funded international project aiming to develop state-of-the-art antimicrobial packaging systems for perishable foods. The project is based on natural essential oils which possess significant antimicrobial activity against many bacteria, yeasts and molds. The essential oils are encapsulated in natural aluminosilicate clays, halloysite nanotubes (HNT's), that serves as a carrier for the volatile essential oils and enable their incorporation into polymer films. During the course of the project, several polyethylene films with diverse essential oils combinations were designed based on the characteristics of their target food products. The antimicrobial activity of the produced films was examined in vitro on a broad spectrum of microorganisms including gram-positive and gram-negative bacteria, aerobic and anaerobic bacteria, yeasts and molds. The films that showed promising in vitro results were successfully assimilated on in vivo active packaging of several food products such as cheese, bread, fruits and raw meat. The results of the in vivo analyses showed significant inhibition of the microbial spoilage, indicating the strong contribution of the NanoPack packaging solutions on the extension of shelf life and reduction of food waste caused by early spoilage throughout the supply chain.

Keywords: food safety, food packaging, essential oils, nanotechnology

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Authors: Avan Al-Saffar, Eun-Jin Kim

Abstract:

Both the logistic growth model and the gompertz growth model are used to describe growth processes. Both models driven by perturbations in different cases are investigated using information theory as a useful measure of sustainability and the variability. Specifically, we study the effect of different oscillatory modulations in the system's parameters on the evolution of the system and Probability Density Function (PDF). We show the maintenance of the initial conditions for a long time. We offer Fisher information analysis in positive and/or negative feedback and explain its implications for the sustainability of population dynamics. We also display a finite amplitude solution due to the purely fluctuating growth rate whereas the periodic fluctuations in negative feedback can lead to break down the system's self-regulation with an exponentially growing solution. In the cases tested, the gompertz and logistic systems show similar behaviour in terms of information and sustainability although they develop differently in time.

Keywords: dynamical systems, fisher information, probability density function (pdf), sustainability

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Authors: Sheela Tiwari, R. Naresh, R. Jha

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The paper presents an investigation into the effect of neural network predictive control of UPFC on the transient stability performance of a multi-machine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers and an improved damping of the power oscillations as compared to the conventional PI controller.

Keywords: identification, neural networks, predictive control, transient stability, UPFC

Procedia PDF Downloads 360

Authors: W. Kongnoo, J. Loysongkroa, S. Chotivichien, N. Viriyautsahakul, N. Saiwongse

Abstract:

Obesity, stunting and wasting problems among Thai school-aged children are increasing due to inappropriate food consumption behavior and poor environments for desirable nutritional behavior. Because of a low school lunch budget of only 0.40 USD per person per day, food quality is not up to nutritional standards. Therefore, the Health Department with the Education Ministry and the Thai Health Promotion Foundation have developed a quality school lunch project during 2009–2013. The program objectives were development and management of public policy to increase school lunch budget. The methods used a healthy public policy motivation process and movement in 241 local administrative organizations and 538 schools. The problem and solution research was organized to study school food and nutrition management, create a best practice policy mobilization model and hold a public hearing to motivate an increase of school meal funding. The results showed that local public policy has been motivated during 2009-2011 to increase school meal budget using local budgets. School children with best food consumption behavior and exercise increased from 13.2% in 2009 to 51.6% in 2013 and stunting decreased from 6.0% in 2009 to 4.7% in 2013. As the result of national policy motivation (2012-2013), the cabinet meeting on October 22, 2013 has approved an increase of school lunch budget from 0.40 USD to 0.62 USD per person per day. Thus, 5,800,469 school children nationwide have benefited from the budget increase.

Keywords: public policy, quality school lunch, Thailand, obesity

Procedia PDF Downloads 333

Authors: Miled Amel, Ben Maad Hatem, Askri Faouzi, Ben Nasrallah Sassi

Abstract:

Metal hydride water pumping system uses hydrogen as working fluid to pump water for low head and high discharge. The principal operation of this pump is based on the desorption of hydrogen at high pressure and its absorption at low pressure by a metal hydride. This work is devoted to study a concept of the dynamic behavior of a metal hydride pump using unsteady model and LaNi5 as hydriding alloy. This study shows that with MHP, it is possible to pump 340l/kg-cycle of water in 15 000s using 1 Kg of LaNi5 at a desorption temperature of 360 K, a pumping head equal to 5 m and a desorption gear ratio equal to 33. This study reveals also that the error given by the steady model, using LaNi5 is about 2%.A dimensional mathematical model and the governing equations of the pump were presented to predict the coupled heat and mass transfer within the MHP. Then, a numerical simulation is carried out to present the time evolution of the specific water discharge and to test the effect of different parameters (desorption temperature, absorption temperature, desorption gear ratio) on the performance of the water pumping system (specific water discharge, pumping efficiency and pumping time). In addition, a comparison between results obtained with steady and unsteady model is performed with different hydride mass. Finally, a geometric configuration of the reactor is simulated to optimize the pumping time.

Keywords: dynamic behavior, LaNi5, performance of water pumping system, unsteady model

Procedia PDF Downloads 185

Authors: Joon-Hoon Park

Abstract:

In this paper the rationalized Haar transform is applied for distributed parameter system identification and estimation. A distributed parameter system is a dynamical and mathematical model described by a partial differential equation. And system identification concerns the problem of determining mathematical models from observed data. The Haar function has some disadvantages of calculation because it contains irrational numbers, for these reasons the rationalized Haar function that has only rational numbers. The algorithm adopted in this paper is based on the transform and operational matrix of the rationalized Haar function. This approach provides more convenient and efficient computational results.

Keywords: distributed parameter system, rationalized Haar transform, operational matrix, system identification

Procedia PDF Downloads 490

Authors: Samuel Matylewicz, K. W. Goossen

Abstract:

The deployment of white or cool (high albedo) roofing is a common energy savings recommendation for a variety of buildings all over the world. Here, the effect of a white roof on the energy savings of an ice rink facility in the northeastern US is determined by measuring the effect of solar irradiance on the consumption of the rink's ice refrigeration system. The consumption of the refrigeration system was logged over a year, along with multiple weather vectors, and a statistical model was applied. The experimental model indicates that the expected savings of replacing the existing grey roof with a white roof on the consumption of the refrigeration system is only 4.7 %. This overall result of the statistical model is confirmed with isolated instances of otherwise similar weather days, but cloudy vs. sunny, where there was no measurable difference in refrigeration consumption up to the noise in the local data, which was a few percent. This compares with a simple theoretical calculation that indicates 30% savings. The difference is attributed to a lack of convective cooling of the roof in the theoretical model. The best experimental model shows a relative effect of the weather vectors dry bulb temperature, solar irradiance, wind speed, and relative humidity on refrigeration consumption of 1, 0.026, 0.163, and -0.056, respectively. This result can have an impact on decisions to apply white roofing to refrigerated buildings in general.

Keywords: cool roofs, solar cooling load, refrigerated buildings, energy-efficient building envelopes

Procedia PDF Downloads 114