Search results for: supply chain models

Authors: Moyosooore A. Babalola, Ayodeji S. Ogunleye

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The main focus of the study was to determine the profitability of investment in the Oil Palm value chain of Osun State, Nigeria in 2015. The specific objectives were to describe the socio-economic characteristics of Oil Palm investors (producers, processors and marketers), to determine the profitability of the investment to investors in the Oil Palm value chain, and to determine the factors affecting the profitability of the investment of the oil palm investors in Osun state. A sample of 100 respondents was selected in this cross-sectional survey. Multiple stage sampling procedure was used for data collection of producers and processors while purposive sampling was used for marketers. Data collected was analyzed using the following analytical tools: descriptive statistics, budgetary analysis and regression analysis. The results of the gross margin showed that the producers and processors were more profitable than the marketers in the oil palm value chain with their benefit-cost ratios as 1.93, 1.82 and 1.11 respectively. The multiple regression analysis showed that education and years of experience were significant among marketers and producers while age and years of experience had significant influence on the gross margin of processors. Based on these findings, improvement on the level of education of oil palm investors is recommended in order to address the relatively low access to post-primary education among the oil palm investors in Osun State. In addition to this, it is important that training be made available to oil palm investors. This will improve the quality of their years of experience, ensuring that it has a positive influence on their gross margin. Low access to credit among processors and producer could be corrected by making extension services available to them. Marketers would also greatly benefit from subsidized prices on oil palm products to increase their gross margin, as the huge percentage of their total cost comes from acquiring palm oil.

Keywords: oil palm, profitability analysis, regression analysis, value chain

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Authors: Tareq Oshan

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Facility location and size decisions are important to any company because they affect profitability and success. However, warehouses are exposed to various risks of failure that affect their activity. This paper presents a mixed-integer non-linear mathematical model that can be used to determine optimal warehouse locations and sizes, which warehouses to fortify, and which branches should be assigned to specific warehouses when there is a risk of warehouse failure. Every branch is assigned to a fortified primary warehouse or a nonfortified primary warehouse and a fortified backup warehouse. The standard method and an introduced method, based on the average probabilities, for linearizing this mathematical model were used. A Canadian case study was used to demonstrate the developed mathematical model, followed by some sensitivity analysis.

Keywords: supply chain network design, fortified warehouse, mixed-integer mathematical model, warehouse failure risk

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Authors: José M Martín-Moreno, Rafaela Pérez, Jesús Ruiz

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In this paper we use a small open economy Dynamic Stochastic General Equilibrium Model (DSGE) for the Spanish economy to search for a deeper characterization of the determinants of Spain’s macroeconomic fluctuations throughout the period 1970-2008. In order to do this, we distinguish between tradable and non-tradable goods to take into account the fact that the presence of non-tradable goods in this economy is one of the largest in the world. We estimate a DSGE model with supply and demand shocks (sectorial productivity, public spending, international real interest rate and preferences) using Kalman Filter techniques. We find the following results. First of all, our variance decomposition analysis suggests that 1) the preference shock basically accounts for private consumption volatility, 2) the idiosyncratic productivity shock accounts for non-tradable output volatility, and 3) the sectorial productivity shock along with the international interest rate both greatly account for tradable output. Secondly, the model closely replicates the time path observed in the data for the Spanish economy and finally, the model captures the main cyclical qualitative features of this economy reasonably well.

Keywords: business cycle, DSGE models, Kalman filter estimation, small open economy

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Authors: Thomas Weber, Nina Strobel, Thomas Kohne, Eberhard Abele

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In context of the energy transition in Germany, the importance of so-called virtual power plants in the energy supply continues to increase. The progressive dismantling of the large power plants and the ongoing construction of many new decentralized plants result in great potential for optimization through synergies between the individual plants. These potentials can be exploited by mathematical optimization algorithms to calculate the optimal application planning of decentralized power and heat generators and storage systems. This also includes linear or linear mixed integer optimization. In this paper, procedures for reducing the number of decision variables to be calculated are explained and validated. On the one hand, this includes combining n similar installation types into one aggregated unit. This aggregated unit is described by the same constraints and target function terms as a single plant. This reduces the number of decision variables per time step and the complexity of the problem to be solved by a factor of n. The exact operating mode of the individual plants can then be calculated in a second optimization in such a way that the output of the individual plants corresponds to the calculated output of the aggregated unit. Another way to reduce the number of decision variables in an optimization problem is to reduce the number of time steps to be calculated. This is useful if a high temporal resolution is not necessary for all time steps. For example, the volatility or the forecast quality of environmental parameters may justify a high or low temporal resolution of the optimization. Both approaches are examined for the resulting calculation time as well as for optimality. Several optimization models for virtual power plants (combined heat and power plants, heat storage, power storage, gas turbine) with different numbers of plants are used as a reference for the investigation of both processes with regard to calculation duration and optimality.

Keywords: CHP, Energy 4.0, energy storage, MILP, optimization, virtual power plant

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Authors: Shunichi Ohmori, Sirawadee Arunyanart, Kazuho Yoshimoto

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We consider a periodic review inventory control problem of minimizing production cost, inventory cost, and lost-sales under demand uncertainty, in which product demands are not specified exactly and it is only known to belong to a given uncertainty set, yet the constraints must hold for possible values of the data from the uncertainty set. We propose a robust optimization formulation for obtaining lowest cost possible and guaranteeing the feasibility with respect to range of order quantity and inventory level under demand uncertainty. Our formulation is based on the adaptive robust counterpart, which suppose order quantity is affine function of past demands. We derive certainty equivalent problem via second-order cone programming, which gives 'not too pessimistic' worst-case.

Keywords: robust optimization, inventory control, supply chain managment, second-order programming

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Authors: B. Van Kessel, P. T. Kockelkorn, T. R. Speelman, T. C. Wierikx, C. Mai Van, T. A. Bogaard

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Saltwater intrusion is a common problem in estuaries around the world, as it could hinder the freshwater supply of coastal zones. This problem is likely to grow due to climate change and sea-level rise. The influence of these factors on the saltwater intrusion was investigated for the Cai River in the Khanh Hoa province in Vietnam. In addition, the Cai River has high seasonal fluctuations in discharge, leading to increased saltwater intrusion during the dry season. Sea level rise, river discharge changes, river mouth widening and a proposed saltwater intrusion prevention dam can have influences on the saltwater intrusion but have not been quantified for the Cai River estuary. This research used both an analytical and numerical model to investigate the effect of the aforementioned factors. The analytical model was based on a model proposed by Savenije and was calibrated using limited in situ data. The numerical model was a 3D hydrodynamic model made using the Delft3D4 software. The analytical model and numerical model agreed with in situ data, mostly for tidally average data. Both models indicated a roughly similar dependence on discharge, also agreeing that this parameter had the most severe influence on the modeled saltwater intrusion. Especially for discharges below 10 m/s3, the saltwater was predicted to reach further than 10 km. In the models, both sea-level rise and river widening mainly resulted in salinity increments up to 3 kg/m3 in the middle part of the river. The predicted sea-level rise in 2070 was simulated to lead to an increase of 0.5 km in saltwater intrusion length. Furthermore, the effect of the saltwater intrusion dam seemed significant in the model used, but only for the highest position of the gate.

Keywords: Cai River, hydraulic models, river discharge, saltwater intrusion, tidal barriers

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Authors: Changiz Valmohammadi

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The main purpose of this study is to explore the perception of Iranian experts and executive managers of sample organizations on the benefits and barriers of Internet of Things (IoT) solutions implementation. Based on the review of the related literature and web sites, benefits and barriers of successful implementation to IoT solutions were identified. Through a self-administered questionnaire which was collected from 67 Iranian organizations the ranking and importance of benefits and barriers of IoT solutions implementation were determined based on the perception of the experts of the surveyed organizations. Analysis of data and the obtained results revealed that “improved customer experience” and “Supply chain optimization and responsiveness” are the most important benefits that the survey organizations expect to reap as a result of IoT solutions implementation. Also,” Integration challenges" and “cannot find right suppliers” were ranked as the most challenging barriers to IoT solutions implementation.

Keywords: internet of things (IoT), exploratory study, benefits, barriers, Iran

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Authors: Gerard R. Lekhema, Willie A Cronje, Ian Korir

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The objective of this research work is to investigate the use of a micro-grid system to improve the reliability and availability of emergency electrical power in a nuclear facility. The nuclear facility is a safety-critical application that requires reliable electrical power for safe startup, operation and normal or emergency shutdown conditions. The majority of the nuclear facilities around the world utilize diesel generators as emergency power supply during loss of offsite power events. This study proposes the micro-grid system with distributed energy sources and energy storage systems for use as emergency power supply. The systems analyzed include renewable energy sources, decay heat recovery system and large scale energy storage system. The configuration of the micro-grid system is realized with guidelines of nuclear safety standards and requirements. The investigation results presented include performance analysis of the micro-grid system in terms of reliability and availability.

Keywords: emergency power supply, micro-grid, nuclear facility, renewable energy sources

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Authors: Elvira Mustikawati P.H., Iis Dewi Ratih, Dita Amelia

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Bojonegoro has proclaimed a policy of zero malnutrition. Therefore, as an effort to solve the cases of malnutrition children in Bojonegoro, this study used the approach geographically Mixed Weighted Regression (MGWR) to determine the factors that influence the percentage of malnourished children under five in which factors can be divided into locally influential factor in each district and global factors that influence throughout the district. Based on the test of goodness of fit models, R2 and AIC values in GWR models are better than MGWR models. R2 and AIC values in MGWR models are 84.37% and 14.28, while the GWR models respectively are 91.04% and -62.04. Based on the analysis with GWR models, District Sekar, Bubulan, Gondang, and Dander is a district with three predictor variables (percentage of vitamin A, the percentage of births assisted health personnel, and the percentage of clean water) that significantly influence the percentage of malnourished children under five.

Keywords: GWR, MGWR, R2, AIC

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Authors: Panpan Fan, Bo Ming, Niels P. R. Anten, Jochem B. Evers, Yaoyao Li, Shaokun Li, Ruizhi Xie

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The reallocation of dry matter (DM) and nitrogen (N) from vegetative tissues to the grain sinks are critical for grain yield. The objective of this study was to quantify the DM and N accumulation, partition, and reallocation at the single-leaf, different-organ, and individual-plant scales and clarify the responses to different levels of N availabilities. A two-year field experiment was conducted in Jinlin province, Northeast China, with three N fertilizer rates to create the different N availability levels: N0 (N deficiency), N1(low supply), and N2 (high supply). The results showed that grain N depends more on reallocations of vegetative organs compared with grain DM. Besides, vegetative organs reallocated more DM and N to grain under lower N availability, whereas more grain DM and grain N were derived from post-silking leaf photosynthesis and post-silking N uptake from the soil under high N availability. Furthermore, the reallocation amount and reallocation efficiency of leaf DM and leaf N content differed among leaf ranks and were regulated by N availability; specifically, the DM reallocation occurs mainly on senesced leaves, whereas the leaf N reallocation was in live leaves. These results provide a theoretical basis for deriving parameters in crop models for the simulation of the demand, uptake, partition, and reallocation processes of DM and N.

Keywords: dry matter, leaf N content, leaf rank, N availability, reallocation efficiency

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Authors: Abhishek Kumar Gupta

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Atomistic Molecular Dynamics (MD) Simulations have been performed to study the effect of monovalent salt i.e. NaCl concentration (Cs) and chain degree of neutralization (f) on the structure and dynamics of anionic poly(methacrylic acid) (PMA) in dilute aqueous solutions. In the present study, the attention is to unveil the conformational structure, hydrogen-bonding, local polyion-counterion structure, h-bond dynamics, chain dynamics and thermodynamic enthalpy of solvation of a-PMA in dilute aqueous solutions as a function of salt concentration, Cs and f. The results have revealed that at low salt concentration, the conformational radius of gyration (Rg) increases and then decreases reaching a maximum in agreement with the reported light scattering experimental results. The Rg at f = 1 shows a continual decrease and acquire a plateau value at higher salt concentration in agreement with results obtained by light scattering experiments. The radial distribution functions between PMA, salt and water atoms has been computed with respect to atom and centre-of-mass to understand the intermolecular structure in detail. The results pertaining to PMA chain conformations and hydrogen bond autocorrelation function showcasing the h-bond dynamics will be presented. The results pertaining to chain dynamics will be presented. The results pertaining to counterion condensation on the PMA chain shows greater condensation of Na+ ions on to the carboxylate ions with increase in salt concentration. Moreover, the solvation enthalpy of the system as a function of salt concentration will be presented.

Keywords: conformations, molecular dynamics simulations, NaCl concentration, radial distribution functions

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

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Many quality models have been used to measure e-government portals quality. However, the absence of an international consensus for e-government portals quality models results in many differences in terms of quality attributes and measures. The aim of this paper is to compare and analyze the existing e-government quality models proposed in literature (those that are based on ISO standards and those that are not) in order to propose guidelines to build a good and useful e-government portals quality model. Our findings show that, there is no e-government portal quality model based on the new international standard ISO 25010. Besides that, the quality models are not based on a best practice model to allow agencies to both; measure e-government portals quality and identify missing best practices for those portals.

Keywords: e-government, portal, best practices, quality model, ISO, standard, ISO 25010, ISO 9126

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Authors: Keith Dominic T. Li

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The soaring prices of residential properties in Hong Kong has become a social problem that even the middle class is having dif?iculties in purchasing homes. In making policies to curb the prices, it is important to determine the factors that contribute to the property in?lation. Many researches attribute this in?lation to macroeconomic factors especially the interest rate. However, it is important to remember that Hong Kong is under a Currency Board system which makes its interest rate exogenously determined. This research aims to show the signi?icance of the money supply on Hong Kong residential property prices in post-1997 Asian Financial Crisis period. Using money supply data, macroeconomic fundamentals, and demographic variables from 2000Q1 to 2013Q2, the factors contributed to residential property price in?lation are estimated to calculate the share of each explanatory variable in disparity. It is found that the Hong Kong property market is mainly driven by investment and that the in?lation on Hong Kong residential property prices can explained by the increase in the Hang Seng Index and in the money supply M2.

Keywords: real estate, Hong Kong, property market, monetary economics, monetary policy

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Authors: Salah Gariani, Islam Shyha, Fawad Inam, Dehong Huo

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A controlled cutting fluid impinging supply system (CUT-LIST) was developed to deliver an accurate amount of cutting fluid into the machining zone via well-positioned coherent nozzles based on a calculation of the heat generated. The performance of the CUT-LIST was evaluated against a conventional flood cutting fluid supply system during step shoulder milling of Ti-6Al-4V using vegetable oil-based cutting fluid. In this paper, the micro-hardness of the machined surface was used as the main criterion to compare the two systems. CUT-LIST provided significant reductions in cutting fluid consumption (up to 42%). Both systems caused increased micro-hardness value at 100 µm from the machined surface, whereas a slight reduction in micro-hardness of 4.5% was measured when using CUL-LIST. It was noted that the first 50 µm is the soft sub-surface promoted by thermal softening, whereas down to 100 µm is the hard sub-surface caused by the cyclic internal work hardening and then gradually decreased until it reached the base material nominal hardness. It can be concluded that the CUT-LIST has always given lower micro-hardness values near the machined surfaces in all conditions investigated.

Keywords: impinging supply system, micro-hardness, shoulder milling, Ti-6Al-4V, vegetable oil-based cutting fluid

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Authors: Nina Miklavčič, Urška Kugovnik, Natalia Galkina, Primož Ribarič, Rudi Vončina

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Today, the need for weather predictions is deeply rooted in the everyday life of people as well as it is in industry. The forecasts influence final decision-making processes in multiple areas, from agriculture and prevention of natural disasters to air traffic regulations and solutions on a national level for health, security, and economic problems. Namely, in Slovenia, alongside other existing forms of application, weather forecasts are adopted for the prognosis of electrical current transmission through powerlines. Meteorological parameters are one of the key factors which need to be considered in estimations of the reliable supply of electrical energy to consumers. And like for any other measured value, the knowledge about measurement uncertainty is also critical for the secure and reliable supply of energy. The estimation of measurement uncertainty grants us a more accurate interpretation of data, a better quality of the end results, and even a possibility of improvement of weather forecast models. In the article, we focused on the estimation of measurement uncertainty of the diagnostic microscale meteorological model CALMET. For the purposes of our research, we used a network of meteorological stations spread in the area of our interest, which enables a side-by-side comparison of measured meteorological values with the values calculated with the help of CALMET and the measurement uncertainty estimation as a final result.

Keywords: uncertancy, meteorological model, meteorological measurment, CALMET

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Authors: Ayman Aboelkassem, Mahmoud Ali

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Introduction: The models of soul houses have appeared in the prehistory, old kingdom and middle kingdom period. These soul houses represented the imagination of the deceased about his house in the afterlife, some of these soul houses were two floors and the study will examine five models of soul houses which were discovered near Saqqara site by an Egyptian mission. These models had been transferred to The Grand Egyptian Museum (GEM) to be ready to display at the new museum. We focus on models of soul houses (GEM Numbers, 1276, 1280, 1281, 1282, 8711) these models of soul houses were related to the old kingdom period. These models were all made of pottery, the five models have an oval shape and were decorated with relief. Methodology: The study will focus on the development of soul houses during the different periods in ancient Egypt, the function of soul houses, the kind of offerings which were put in it and the symbolism of the offerings colors in ancient Egyptian believe. Conclusion: This study is useful for the heritage and ancient civilizations especially when we talk about opening new museums like The Grand Egyptian Museum which will display a new collection of soul houses. The study of soul houses and The kinds of offerings which put in it reflect the economic situation in the Egyptian society and kinds of oils which were famous in ancient Egypt.

Keywords: archaeology study, Grand Egyptian Museum, relief, soul houses

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

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Authors: Karolin Bauer, Anna Brinkmann

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Vulnerabilities in critical infrastructure can cause significant difficulties for the affected population during crises. Securing the food supply as part of the critical infrastructure in crisis situations is an essential part of public services and a ground stone for a successful concept of civil protection. In most industrialized countries, there are currently no comparative studies regarding the food supply of the population during crisis and disaster events. In order to mitigate the potential impact in case of major disasters in Germany, it is absolutely necessary to investigate how the food supply can be secured. The research project aims to provide in-depth research on the experiences gathered during past large-scale disasters in the 34 OECD member countries in order to discover alternatives for an updated civil protection system in Germany. The basic research question is: "Which international approaches and structures of civil protection have been proven and would be useful to modernize the German civil protection with regards to the critical infrastructure and food supply?" Research findings should be extracted from an extensive literature review covering the entire research period as well as from personal and online-based interviews with experts and responsible persons from involved institutions. The capability of the research project insists on the deliberate choice to investigate previous large-scale disasters to formulate important and practical approaches to modernize civil protection in Germany.

Keywords: food supply, vulnerabilty, critical infratstructure, large-scale disaster

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Authors: E. Chakwizira, D. J. Moot, M. Andrews, E. Teixeira

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Partitioning of macro-nutrients in wheat (Triticum aestivum L.) plant organs have not been extensively studied, particularly for modern genotypes grown under contrasting N supply. Nutrient accumulation and partitioning of phosphorus, potassium, calcium, magnesium and sulphur (P, K, Ca, Mg and S) were determined for six wheat genotypes [12S2-2021, 12S3-3019, 13S3-2026, Discovery, Duchess and Reliance] grown with (200 kg/ha) or without (0 kg/ha) nitrogen (N), in a fully irrigated field experiment in 2017-18 season at Lincoln, New Zealand. Data were collected at three growth stages (GS): tillering (GS21), anthesis (GS60) and grain maturity (GS92). Grain yield varied with both N and genotype; from 6-7.5 t/ha for the 0 kg N/ha crops and 8.1-9.3 t/ha for the 200 kg N/ha treatments. Plant nutrient uptake at maturity responded to both N supply and genotype for all nutrients, except S which did not differ among the genotypes. For example, total P uptake averaged 13.5 (12.4-14.3) kg/ha for the 0 kg N/ha treatments and 17.8 (15.1-19.7) kg/ha when 200 kg N/ha was applied. Similarly, K uptake increased from an average of 23 (21.6-25.3) for the 0 kg N/ha treatments to 34.3 (32.4-40.8) kg/ha when 200 kg N/ha was applied. Similar trends were observed for Ca and Mg. The S content only responded to N supply but not to genotype, increasing from 7.9 kg/ha for the 0 kg N treatments to 12.8 kg/ha when 200 kg N was applied. Relative nutrient content at anthesis compared with those at maturity were 30% for P, 100% for both K and Ca and 34% of Mg. Sulphur content at anthesis decreased 29% with N supply and was highest for genotypes 12S2-2021 compared with the other five genotype. At grain maturity, the ratio of nutrients in grain to total plant nutrient, defined as the nutrient harvest index (NHI) varied with both N supply and genotype. Averaged across treatments, the NHI was 0.96 for P, 0.53 for K, 0.58 for Ca, 0.90 for Mg and 0.85 for S. These results suggest that Ca and K should be provided earlier in the season as there is limited or no uptake after anthesis. These results also show that Ca and K are important for structural functions, while P, Mg and S are remobilised to the grains and become important for quality.

Keywords: anthesis, genotype, nutrient harvests index, NHI, Triticum aestivum L.

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Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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Authors: Ezekiel Olukayode Akintunde

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There is a high level of inadequate methods at all levels of food supply in the global food industry. The inadequacies have led to vast wastages of food. Hence there is a need to curb the wastages that can later affect natural resources, water resources, and energy to avoid negative impacts on the climate and the environment. There is a need to engage multifaceted engineering packaging approaches for a sustainable food chain to ensure active packaging, intelligent packaging, new packaging materials, and a sustainable packaging system. Packaging can be regarded as an indispensable component approach that can be applied to solve major problems of sustainable food consumption globally; this is about controlling the environmental impact of packed food. The creative innovation will ensure that packaged foods are free from food-borne diseases and food chemical pollution. This paper evaluates the key shortcomings that must be addressed by innovative food packaging to ensure a safe, natural environment that will preserve energy and sustain water resources. Certain solutions, including fabricating microbial biodegradable chemical compounds/polymers from agro-food waste remnants, appear a bright path to ensure a strong and innovative waste-based food packaging system. Over the years, depletion in the petroleum reserves has brought about the emergence of biodegradable polymers as a proper replacement for traditional plastics; moreover, the increase in the production of traditional plastics has raised serious concerns about environmental threats. Biodegradable polymers have proven to be biocompatible, which can also be processed for other useful applications. Therefore, this study will showcase a workable guiding framework for designing a sustainable food packaging system that will not constitute a danger to our present society and that will surely preserve natural water resources. Various assessment methods will be deployed at different stages of the packaging design to enhance the package's sustainability. Every decision that will be made must be facilitated with methods that will be engaged per stage to allow for corrective measures throughout the cycle of the design process. Basic performance appraisal of packaging innovations. Food wastage can result in inimical environmental impacts, and ethical practices must be carried out for food loss at home. An examination in West Africa quantified preventable food wastage over the entire food value chain at almost 180kg per person per year. That is preventable food wastage, 35% of which originated at the household level. Many food losses reported, which happened at the harvesting, storage, transportation, and processing stages, are not preventable and are without much environmental impact because such wastage can be used for feeding. Other surveys have shown that 15%-20% of household food losses can be traced to food packaging. Therefore, new innovative packaging systems can lessen the environmental effect of food wastage to extend shelf‐life to lower food loss in the process distribution chain and at the household level.

Keywords: food packaging, biodegradable polymer, intelligent packaging, shelf-life

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Authors: Rocío González-Sánchez, Sara Alonso-Muñoz

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Food waste implies an inefficient management of the final stages in the food supply chain. Referring to Sustainable Development Goals (SDGs) by United Nations, the SDG 12.3 proposes to halve per capita food waste at the retail and consumer level and to reduce food losses. In the linear system, food waste is disposed and, to a lesser extent, recovery or reused after consumption. With the negative effect on stocks, the current food consumption system is based on ‘produce, take and dispose’ which put huge pressure on raw materials and energy resources. Therefore, greater focus on the circular management of food waste will mitigate the environmental, economic, and social impact, following a Triple Bottom Line (TBL) approach and consequently the SDGs fulfilment. A mixed methodology is used. A total sample of 311 publications from Web of Science database were retrieved. Firstly, it is performed a bibliometric analysis by SciMat and VOSviewer software to visualise scientific maps about co-occurrence analysis of keywords and co-citation analysis of journals. This allows for the understanding of the knowledge structure about this field, and to detect research issues. Secondly, a systematic literature review is conducted regarding the most influential articles in years 2020 and 2021, coinciding with the most representative period under study. Thirdly, to support the development of this field it is proposed an agenda according to the research gaps identified about circular economy and food waste management. Results reveal that the main topics are related to waste valorisation, the application of waste-to-energy circular model and the anaerobic digestion process towards fossil fuels replacement. It is underlined that the use of food as a source of clean energy is receiving greater attention in the literature. There is a lack of studies about stakeholders’ awareness and training. In addition, available data would facilitate the implementation of circular principles for food waste recovery, management, and valorisation. The research agenda suggests that circularity networks with suppliers and customers need to be deepened. Technological tools for the implementation of sustainable business models, and greater emphasis on social aspects through educational campaigns are also required. This paper contributes on the application of circularity to food waste management by abandoning inefficient linear models. Shedding light about trending topics in the field guiding to scholars for future research opportunities.

Keywords: bibliometric analysis, circular economy, food waste management, future research lines

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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Authors: Urszula Malaga-Toboła, Marek Gugała, Rafał Kornas, Robert Rusinek, Marek Gancarz

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The work focused on presenting the elements that determine the quality of fresh milk in the context of the quality of its transport. The quality of the raw material depends on the quality of transport. Milk transport involves many activities in which, apart from the temperature and sterility of the means of transport, it is important not to expose the raw material to shocks. Recently, there have been changes in the milk supply chain, thus affecting the logistics processes between its links. Based on the conducted research and analyses, it was found that the condition of the road surface on which milk is transported affects its quality. For the T1 milk transport route- gravel roads of very poor and poor quality, the lowest number of bacteria and the highest number of somatic cells, fat content, and temperature of the transported milk were obtained. A well-organized integrated transport system is a real need for most companies today. The analysis showed significant differences in the quality of milk delivered to the dairy.

Keywords: fresh milk, transport, milk quality, dairy

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Authors: I. Behroyan, P. Ganesan, S. He, S. Sivasankaran

Abstract:

This study compares the predictions of five types of Computational Fluid Dynamics (CFD) models, including two single-phase models (i.e. Newtonian and non-Newtonian) and three two-phase models (Eulerian-Eulerian, mixture and Eulerian-Lagrangian), to investigate turbulent forced convection of Cu-water nanofluid in a tube with a constant heat flux on the tube wall. The Reynolds (Re) number of the flow is between 10,000 and 25,000, while the volume fraction of Cu particles used is in the range of 0 to 2%. The commercial CFD package of ANSYS-Fluent is used. The results from the CFD models are compared with results from experimental investigations from literature. According to the results of this study, non-Newtonian single-phase model, in general, does not show a good agreement with Xuan and Li correlation in prediction of Nu number. Eulerian-Eulerian model gives inaccurate results expect for φ=0.5%. Mixture model gives a maximum error of 15%. Newtonian single-phase model and Eulerian-Lagrangian model, in overall, are the recommended models. This work can be used as a reference for selecting an appreciate model for future investigation. The study also gives a proper insight about the important factors such as Brownian motion, fluid behavior parameters and effective nanoparticle conductivity which should be considered or changed by the each model.

Keywords: heat transfer, nanofluid, single-phase models, two-phase models

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Authors: Amidu Owolabi Ayeni

Abstract:

Studies have shown that spatio-temporal distribution and variability of climatic variables, urban land use, and population have had substantial impact on water supply. It is based on these facts that the impacts of climate, urbanization, and population on water supply in Lagos State Nigeria remain the focus of this study. Population and water production data on Lagos State between 1963 and 2006 were collected, and used for time series and projection analyses. Multi-temporal land-sat images of 1975, 1995 and NigeriaSat-1 imagery of 2007 were used for land use change analysis. The population of Lagos State increased by about 557.1% between 1963 and 2006, correspondingly, safe water supply increased by 554%. Currently, 60% of domestic water use in urban areas of Lagos State is from groundwater while 75% of rural water is from unsafe surface water. Between 1975 and 2007, urban land use increased by about 235.9%. The 46years climatic records revealed that temperature and evaporation decreased slightly while rainfall and Relatively Humidity (RH) decreased consistently. Based on these trends, the Lagos State population and required water are expected to increase to about 19.8millions and 2418.9ML/D respectively by the year 2026. Rainfall is likely to decrease by -6.68mm while temperature will increase by 0.950C by 2026. Urban land use is expected to increase by 20% with expectation of serious congestion in the suburb areas. With these results, over 50% of the urban inhabitants will be highly water poor in future if the trends continue unabated.

Keywords: challenges, climate change, urbanization, water supply

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Authors: Charles Mothobiso

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This study attempts to identify the client’s main priority when delivering green projects. The aim is to compare whether clients’ interests are similar when delivering conventional buildings as compared to green buildings. Private clients invest more in green buildings as compared to government and parastatal entities. Private clients prioritize on maximizing a return on investment and they mainly invest in energy-saving buildings that have low life cycle costs. Private clients are perceived to be more knowledgeable about the benefits of green building projects as compared to government and parastatal clients. A shortage of expertise and managerial skill leads to the low adaptation of green buildings in government and parastatal projects. Other factors that seem to prevent the adoption of green buildings are the preparedness of the supply chain within the industry and inappropriate procurement strategies adopted by clients.

Keywords: construction clients, design team, green buildings, procurement

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Authors: Rahil Saeedi

Abstract:

The imbalance in truck parking supply and demand can create important safety issues for truck drivers and the public. Research has shown that breaks at specific intervals can increase drivers’ alertness by reducing the monotony of the task. However, if fatigued truck drivers are unable to find a safe parking spot for rest, they may continue to drive or choose to park at remote and insecure areas or undesignated locations. All of these situations pose serious safety and security risks to truck drivers and other roadway users. This study uses 5-year truck crash data in Ohio to develop and test a framework for identifying crashes that happen as a result of imbalances in truck parking supply and demand. The societal impacts of these crashes are then interpreted as monetary values, calculated using the costs associated with various crash severity levels.

Keywords: truck parking, road safety, crash data, geofencing, driver fatigue, undesignated parking

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Authors: Li Feng, Cheng Zhang, Chuanzhou Yuang

Abstract:

Understanding the macromolecular structure of low-rank coal is very important for its gasification and liquefaction. The pyrolysis is one of the methods of analyzing the macromolecular structure of coal. The gaseous products decomposed directly by the raw lignite at 500 °C and indirectly by tar products from raw lignite pyrolysis at 500 °C were investigated and compared by thermogravimetry, gas chromatography and mass spectrum coupled instrument system (TG/GC/MS) in this paper. The results show that 52 kinds of products were found from the raw lignite and 70 kinds of products from the tar. The pyrolysis products directly from the lignite appear more monocyclic aromatic hydrocarbons and less substituent groups or branch chain, compared with the products from the tar. There is less linear chain and double bonds structure in the tar, which can be speculated that linear chain and double bonds structure took part in the generation of condensed rings and other reactions. There are more kinds of phenol and furan in the tar, which indicate that these products may be generated from the secondary reaction. The formation process of phenol, phenol naphthalene, naphthene and furan are discussed.

Keywords: composition and structure, lignite, pyrolysis of coal, tar, TG/GC/MS

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Authors: Megha Gupta, Nupur Prakash

Abstract:

Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

Procedia PDF Downloads 195