Search results for: supply chain optimization

Authors: Satwik Majumder, Dongyun Jung, Jennifer Ronholm, Saji George

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Bovine mastitis is the most common infectious disease in dairy cattle, with major economic implications for the dairy industry worldwide. Continuous monitoring for the emergence of antimicrobial resistance (AMR) among bacterial isolates from dairy farms is vital not only for animal husbandry but also for public health. In this study, the prevalence of AMR in 113 Escherichia coli isolates from cases of bovine clinical mastitis in Canada was investigated. Kirby-Bauer disk diffusion test with 18 antibiotics and microdilution method with three heavy metals (copper, zinc, and silver) was performed to determine the antibiotic and heavy-metal susceptibility. Resistant strains were assessed for efflux and ß-lactamase activities besides assessing biofilm formation and hemolysis. Whole-genome sequences for each of the isolates were examined to detect the presence of genes corresponding to the observed AMR and virulence factors. Phenotypic analysis revealed that 32 isolates were resistant to one or more antibiotics, and 107 showed resistance against at least one heavy metal. Quinolones and silver were the most efficient against the tested isolates. Among the AMR isolates, AcrAB-TolC efflux activity and ß-lactamase enzyme activities were detected in 13 and 14 isolates, respectively. All isolates produced biofilm but with different capacities, and 33 isolates showed α-hemolysin activity. A positive correlation (Pearson r = +0.89) between efflux pump activity and quantity of biofilm was observed. Genes associated with aggregation, adhesion, cyclic di-GMP, quorum sensing were detected in the AMR isolates, corroborating phenotype observations. This investigation showed the prevalence of AMR in E. coli isolates from bovine clinical mastitis. The results also suggest the inadequacy of antimicrobials with a single mode of action to curtail AMR bacteria with multiple mechanisms of resistance and virulence factors. Therefore, it calls for combinatorial therapy for the effective management of AMR infections in dairy farms and combats its potential transmission to the food supply chain through milk and dairy products.

Keywords: antimicrobial resistance, E. coli, bovine mastitis, antibiotics, heavy-metals, efflux pump, ß-lactamase enzyme, biofilm, whole-genome sequencing

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Authors: Bruna C. Brasileiro, José Alberto S. Sá, Brigida R. P. Rocha

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The Amazon region development was related to large-scale projects associated with economic cycles. Economic cycles were originated from policies implemented by successive governments that exploited the resources and have not yet been able to improve the local population's quality of life. These implanted development strategies were based on vertical planning centered on State that didn’t know and showed no interest in know the local needs and potentialities. The future of this region is a challenge that depends on a model of development based on human progress associated to intelligent, selective and environmentally safe exploitation of natural resources settled in renewable and no-polluting energy generation sources – a differential factor of attraction of new investments in a context of global energy and environmental crisis. In this process the planning and support of Brazilian State, local government, and selective international partnership are essential. Residual biomass utilization allows the sustainable development by the integration of production chain and energy generation process which could improve employment condition and income of riversides. Therefore, this research discourses how the use of local residual biomass (açaí lumps) could be an important instrument of sustainable development for isolated communities located at Alcobaça Sustainable Development Reserve (SDR), Tucuruí, Pará State, since in this region the energy source more accessible for who can pay are the fossil fuels that reaches about 54% of final energy consumption by the integration between the açaí productive chain and the use of renewable energy source besides it can promote less environmental impact and decrease the use of fossil fuels and carbon dioxide emissions.

Keywords: Amazon, biomass, renewable energy, sustainability

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Authors: Bib Paruhum Silalahi, Djihad Wungguli, Sugi Guritman

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Steepest descent method is a simple gradient method for optimization. This method has a slow convergence in heading to the optimal solution, which occurs because of the zigzag form of the steps. Barzilai and Borwein modified this algorithm so that it performs well for problems with large dimensions. Barzilai and Borwein method results have sparked a lot of research on the method of steepest descent, including alternate minimization gradient method and Yuan method. Inspired by previous works, we modified the step size of the steepest descent method. We then compare the modification results against the Barzilai and Borwein method, alternate minimization gradient method and Yuan method for quadratic function cases in terms of the iterations number and the running time. The average results indicate that the steepest descent method with the new step sizes provide good results for small dimensions and able to compete with the results of Barzilai and Borwein method and the alternate minimization gradient method for large dimensions. The new step sizes have faster convergence compared to the other methods, especially for cases with large dimensions.

Keywords: steepest descent, line search, iteration, running time, unconstrained optimization, convergence

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Authors: Sopheak Sorn, Kwok Yip Szeto

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Reliability is one of the important measures of how well the system meets its design objective, and mathematically is the probability that a complex system will perform satisfactorily. When the system is described by a network of N components (nodes) and their L connection (links), the reliability of the system becomes a network design problem that is an NP-hard combinatorial optimization problem. In this paper, we address the network design problem for a random point set’s pattern in two dimensions. We make use of a Voronoi construction with each cell containing exactly one point in the point pattern and compute the reliability of the Voronoi’s dual, i.e. the Delaunay graph. We further investigate the communicability of the Delaunay network. We find that there is a positive correlation and a negative correlation between the homogeneity of a Delaunay's degree distribution with its reliability and its communicability respectively. Based on the correlations, we alter the communicability and the reliability by performing random edge flips, which preserve the number of links and nodes in the network but can increase the communicability in a Delaunay network at the cost of its reliability. This transformation is later used to optimize a Delaunay network with the optimum geometric mean between communicability and reliability. We also discuss the importance of the edge flips in the evolution of real soap froth in two dimensions.

Keywords: Communicability, Delaunay triangulation, Edge Flip, Reliability, Two dimensional network, Voronio

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Authors: M. J. Davidson, N. Selvaraj, L. Venugopal

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The elevated temperature forming studies on the expansion of thin walled tubes have been studied in the present work. The influence of process parameters namely the die angle, the die ratio and the operating temperatures on the expansion of tube ends at elevated temperatures is carried out. The range of operating parameters have been identified by perfoming extensive simulation studies. The hot forming parameters have been evaluated for AA2014 alloy for performing the simulation studies. Experimental matrix has been developed from the feasible range got from the simulation results. The design of experiments is used for the optimization of process parameters. Response Surface Method’s (RSM) and Box-Behenken design (BBD) is used for developing the mathematical model for expansion. Analysis of variance (ANOVA) is used to analyze the influence of process parameters on the expansion of tube ends. The effect of various process combinations of expansion are analyzed through graphical representations. The developed model is found to be appropriate as the coefficient of determination value is very high and is equal to 0.9726. The predicted values are found to coincide well with the experimental results, within acceptable error limits.

Keywords: expansion, optimization, Response Surface Method (RSM), ANOVA, bbd, residuals, regression, tube

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Authors: Ghada Elshafei, A. Elazim Negm

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Recently, Green architecture becomes a significant way to a sustainable future. Green building designs involve finding the balance between comfortable homebuilding and sustainable environment. Moreover, the utilization of the new technologies such as artificial intelligence techniques are used to complement current practices in creating greener structures to keep the built environment more sustainable. The most common objectives are green buildings should be designed to minimize the overall impact of the built environment on ecosystems in general and particularly on human health and on the natural environment. This will lead to protecting occupant health, improving employee productivity, reducing pollution and sustaining the environmental. In green building design, multiple parameters which may be interrelated, contradicting, vague and of qualitative/quantitative nature are broaden to use. This paper presents a comprehensive critical state of art review of current practices based on fuzzy and its combination techniques. Also, presented how green architecture/building can be improved using the technologies that been used for analysis to seek optimal green solutions strategies and models to assist in making the best possible decision out of different alternatives.

Keywords: green architecture/building, technologies, optimization, strategies, fuzzy techniques, models

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Authors: Yepeng Cheng, Yasuhiko Morimoto

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Customer relationship analysis is vital for retail stores, especially for supermarkets. The point of sale (POS) systems make it possible to record the daily purchasing behaviors of customers as an identification point of sale (ID-POS) database, which can be used to analyze customer behaviors of a supermarket. The customer value is an indicator based on ID-POS database for detecting the customer loyalty of a store. In general, there are many supermarkets in a city, and other nearby competitor supermarkets significantly affect the customer value of customers of a supermarket. However, it is impossible to get detailed ID-POS databases of competitor supermarkets. This study firstly focused on the customer value and distance between a customer's home and supermarkets in a city, and then constructed the models based on logistic regression analysis to analyze correlations between distance and purchasing behaviors only from a POS database of a supermarket chain. During the modeling process, there are three primary problems existed, including the incomparable problem of customer values, the multicollinearity problem among customer value and distance data, and the number of valid partial regression coefficients. The improved customer value, Huff’s gravity model, and inverse attractiveness frequency are considered to solve these problems. This paper presents three types of models based on these three methods for loyal customer classification and competitors’ influence analysis. In numerical experiments, all types of models are useful for loyal customer classification. The type of model, including all three methods, is the most superior one for evaluating the influence of the other nearby supermarkets on customers' purchasing of a supermarket chain from the viewpoint of valid partial regression coefficients and accuracy.

Keywords: customer value, Huff's Gravity Model, POS, Retailer

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Authors: Kanokon Chaicom, Chitima Sirijerachai, Kanchana Chansung, Pinsuda Klangsang, Boonpeng Palaeng, Prajuab Chaimanee, Pimjai Ananta

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Chronic myeloid leukemia (CML) is characterized by the consistent involvement of the Philadelphia chromosome (Ph), which is derived from a reciprocal translocation between chromosome 9 and 22, the main product of the t(9;22) (q34;q11) translocation, is found in the leukemic clone of at least 95% of CML patients. There are two major forms of the BCR/ABL fusion gene, involving ABL exon 2, but including different exons of BCR gene. The transcripts b2a2 (e13a2) or b3a2 (e14a2) code for a p210 protein. Another fusion gene leads to the expression of an e1a2 transcript, which codes for a p190 protein. Other less common fusion genes are b3a3 or b2a3, which codes for a p203 protein and e19a2 (c3a2) transcript, which codes for a p230 protein. Its frequency varies in different populations. In this study, we aimed to report the frequency of BCR-ABL fusion transcript types with CML by multiplex PCR (polymerase chain reaction) in Srinagarind Hospital, Khon Kaen, Thailand. Multiplex PCR for BCR-ABL was performed on 58 patients, to detect different types of BCR-ABL transcripts of the t (9; 22). All patients examined were positive for some type of BCR/ABL rearrangement. The majority of the patients (93.10%) expressed one of the p210 BCR-ABL transcripts, b3a2 and b2a2 transcripts were detected in 53.45% and 39.65% respectively. The expression of an e1a2 transcript showed 3.75%. Co-expression of p210/p230 was detected in 3.45%. Co-expression of p210/p190 was not detected. Multiplex PCR is useful, saves time and reliable in the detection of BCR-ABL transcript types. The frequency of one or other rearrangement in CML varies in different population.

Keywords: chronic myeloid leukemia, BCR-ABL fusion transcript types, multiplex PCR, frequency of BCR-ABL fusion

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Authors: P. Singh, R. M. Banik

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Artificial neural network (ANN) was employed to optimize assay parameters viz., time, temperature, pH of reaction mixture, enzyme volume and substrate concentration of L-glutaminase from Bacillus cereus MTCC 1305. ANN model showed high value of coefficient of determination (0.9999), low value of root mean square error (0.6697) and low value of absolute average deviation. A multilayer perceptron neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model and its topology was obtained as 5-3-1 after applying Levenberg Marquardt (LM) training algorithm. The predicted activity of L-glutaminase was obtained as 633.7349 U/l by considering optimum assay parameters, viz., pH of reaction mixture (7.5), reaction time (20 minutes), incubation temperature (35˚C), substrate concentration (40mM), and enzyme volume (0.5ml). The predicted data was verified by running experiment at simulated optimum assay condition and activity was obtained as 634.00 U/l. The application of ANN model for optimization of assay conditions improved the activity of L-glutaminase by 1.499 fold.

Keywords: Bacillus cereus, L-glutaminase, assay parameters, artificial neural network

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Authors: Noriyuki Suyama

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This paper looked into consumer behavioral changes by analyzing the data collected by ASMARKS Co., one of a research companies in Japan. The purpose of the paper is to understand the two differences of before vs. after COVID-19 pandemic and Japanese living in Japan. Subsequently, examining the analysis results helped obtain useful insights into new business models for business parties in Japan as a microlevel perspective. The paper also tried to explore future conditions of globalization by taking into consideration nation’s political and economic changes as a macro-level perspective. The COVID-19 has been continuing its spread across the world with more than 60 million confirmed cases in 190 countries. This pandemic with restricted scopes of behavior mandates have disrupted the consumer habits of their lifestyles. Consumers have tendency to learn new ways when they have trouble in taking routine action. For example, the government forces people to refrain from going out, they try to telecommute at home. If the situation come back to normal, people still change their lifestyles to fit in the best. Some of data show typical effects of COVID-19; forceful exposure to digitalized work-life styles; more flexible time at home; importance of trustful and useful information gathering between what's good and bad;etc. in comparison with before vs. after COVID-19 pandemic. In addition, Japanese have less changed their lifestyles than Expatriates living in Japan. For example, while 94% of the expatriates have decreased their outgo because of self-quarantine, only 55% of the Japanese have done. There are more differences in both comparisons in the analysis results. The economic downtrend resulting from COVID-19 is supposed to be at least as devastating if not more so than that of the financial crisis. With unemployment levels in the US taking two weeks to reach what took 6 months in the 2008 crisis, there is no doubt of a global recession some predict could reach 10% or above of GDP. As a result, globalization in the global supply chain of goods and services will end up with negative impact. A lot of governmental financial and economic policies are supposed to focus on their own profits and interests, exclusing other countries interests as is the case with the Recovery Act just after the global financial crisis from 2007 to 2008. Both micro- and macro-levels analysis successfully reveal important connotations and managerial implications of business in Japan for Japanese consumers as well as after COVID-19 global business.

Keywords: COVID-19, lifestyle in Japan, expatriates, consumer behavior

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Authors: Ridoy Das, Myriam Neaimeh, Yue Wang, Ghanim Putrus

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Electric vehicles are a popular transportation medium renowned for potential environmental benefits. However, large and uncontrolled charging volumes can impact distribution networks negatively. Smart charging is widely recognized as an efficient solution to achieve both improved renewable energy integration and grid relief. Nevertheless, different decision-makers may pursue diverse and conflicting objectives. In this context, this paper proposes a multi-objective optimization framework to control electric vehicle charging to achieve both energy cost reduction and peak shaving. A weighted-sum method is developed due to its intuitiveness and efficiency. Monte Carlo simulations are implemented to investigate the impact of uncertain electric vehicle driving patterns and provide decision-makers with a robust outcome in terms of prospective cost and network loading. The results demonstrate that there is a conflict between energy cost efficiency and peak shaving, with the decision-makers needing to make a collaborative decision.

Keywords: electric vehicles, multi-objective optimization, uncertainty, mixed integer linear programming

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Authors: Derssie Mebratu

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As a large variety of micro services, web services, social graphic applications, and media applications are continuously developed, it is substantially vital to design and build a reliable, efficient, and faster memory tiering system. Despite limited design, implementation, and deployment in the last few years, several techniques are currently developed to improve a memory tiering system in a cloud. Some of these techniques are to develop an optimal scanning frequency; improve and track pages movement; identify pages that recently accessed; store pages across each tiering, and then identify pages as a hot, warm, and cold so that hot pages can store in the first tiering Dynamic Random Access Memory (DRAM) and warm pages store in the second tiering Compute Express Link(CXL) and cold pages store in the third tiering Non-Volatile Memory (NVM). Apart from the current proposal and implementation, we also develop a new technique based on a machine learning algorithm in that the throughput produced 25% improved performance compared to the performance produced by the baseline as well as the latency produced 95% improved performance compared to the performance produced by the baseline.

Keywords: machine learning, bayesian optimization, memory tiering, CXL, DRAM

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Authors: Maxwell Henderson, Tristan Cook, Justin Chan Jin Le, Mark Hodson, YoungJung Chang, John Novak, Daniel Padilha, Nishan Kulatilaka, Ansu Bagchi, Sanjoy Ray, John Kelly

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We present a method of using adiabatic quantum optimization (AQO) to solve a mixed integer nonlinear programming (MINLP) problem instance. The MINLP problem is a general form of a set of NP-hard optimization problems that are critical to many business applications. It requires optimizing a set of discrete and continuous variables with nonlinear and potentially nonconvex constraints. Obtaining an exact, optimal solution for MINLP problem instances of non-trivial size using classical computation methods is currently intractable. Current leading algorithms leverage heuristic and divide-and-conquer methods to determine approximate solutions. Creating more accurate and efficient algorithms is an active area of research. Quantum computing (QC) has several theoretical benefits compared to classical computing, through which QC algorithms could obtain MINLP solutions that are superior to current algorithms. AQO is a particular form of QC that could offer more near-term benefits compared to other forms of QC, as hardware development is in a more mature state and devices are currently commercially available from D-Wave Systems Inc. It is also designed for optimization problems: it uses an effect called quantum tunneling to explore all lowest points of an energy landscape where classical approaches could become stuck in local minima. Our work used a novel algorithm formulated for AQO to solve a special type of MINLP problem. The research focused on determining: 1) if the problem is possible to solve using AQO, 2) if it can be solved by current hardware, 3) what the currently achievable performance is, 4) what the performance will be on projected future hardware, and 5) when AQO is likely to provide a benefit over classical computing methods. Two different methods, integer range and 1-hot encoding, were investigated for transforming the MINLP problem instance constraints into a mathematical structure that can be embedded directly onto the current D-Wave architecture. For testing and validation a D-Wave 2X device was used, as well as QxBranch’s QxLib software library, which includes a QC simulator based on simulated annealing. Our results indicate that it is mathematically possible to formulate the MINLP problem for AQO, but that currently available hardware is unable to solve problems of useful size. Classical general-purpose simulated annealing is currently able to solve larger problem sizes, but does not scale well and such methods would likely be outperformed in the future by improved AQO hardware with higher qubit connectivity and lower temperatures. If larger AQO devices are able to show improvements that trend in this direction, commercially viable solutions to the MINLP for particular applications could be implemented on hardware projected to be available in 5-10 years. Continued investigation into optimal AQO hardware architectures and novel methods for embedding MINLP problem constraints on to those architectures is needed to realize those commercial benefits.

Keywords: adiabatic quantum optimization, mixed integer nonlinear programming, quantum computing, NP-hard

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Authors: Piotr Muzyk, Beata Morawiec, Mariusz Opara, Andrzej Tomasik, Brygida Przywara-Chowaniec, Wojciech Jachec, Ewa Nowalany-Kozielska, Damian Kawecki

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Background: Coronary bifurcation is one of the most complex lesion in patients with coronary ar-tery disease. Provisional T-stenting is currently one of the recommended techniques. The aim was to assess optimal methods of treatment in the era of drug-eluting stents (DES). Methods: The regis-try consisted of data from 1916 patients treated with coronary percutaneous interventions (PCI) using either first- or second-generation DES. Patients with bifurcation lesion entered the analysis. Major adverse cardiac and cardiovascular events (MACCE) were assessed at one year of follow-up and comprised of death, acute myocardial infarction (AMI), repeated PCI (re-PCI) of target ves-sel and stroke. Results: Of 1916 registry patients, 204 patients (11%) were diagnosed with bifurcation lesion >50% and entered the analysis. The most commonly used technique was provi-sional T-stenting (141 patients, 69%). Optimization with kissing-balloons technique was performed in 45 patients (22%). In 59 patients (29%) second-generation DES was implanted, while in 112 pa-tients (55%), first-generation DES was used. In 33 patients (16%) both types of DES were used. The procedure success rate (TIMI 3 flow) was achieved in 98% of patients. In one-year follow-up, there were 39 MACCE (19%) (9 deaths, 17 AMI, 16 re-PCI and 5 strokes). Provisional T-stenting resulted in similar rate of MACCE to other techniques (16% vs. 5%, p=0.27) and similar occurrence of re-PCI (6% vs. 2%, p=0.78). The results of post-PCI kissing-balloon technique gave equal out-comes with 3% vs. 16% of MACCE in patients in whom no optimization technique was used (p=0.39). The type of implanted DES (second- vs. first-generation) had no influence on MACCE (4% vs 14%, respectively, p=0.12) and re-PCI (1.7% vs. 51% patients, respectively, p=0.28). Con-clusions: The treatment of bifurcation lesions with PCI represent high-risk procedures with high rate of MACCE. Stenting technique, optimization of PCI and the generation of implanted stent should be personalized for each case to balance risk of the procedure. In this setting, the operator experience might be the factor of better outcome, which should be further investigated.

Keywords: coronary bifurcation, drug eluting stents, long-term follow-up, percutaneous coronary interventions

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Authors: Lie-Fen Lin, Tzu-Hsuan Lin, Ching-Heng Lin

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Hospice care for terminally ill patients provides not only a better quality of life but also cost-saving benefits. However, the utilization of home-based hospice care (HBH care) remains low even for countries covered by National Health Insurance (NHI) programs in Taiwan. In the current commercial insurance policy, only hospital-based hospice benefits were covered. It may have an influence on the insureds chosen to receive end-of-life care in a hospitalized manner. Thus, how to propose a feasible method to advocate HBH care utilization rate of public health policies is an important issue. A total of 130,219 cancer decedents in the year 2011-2013 from the National Health Insurance Research Database (NHIRD) in Taiwan were included in this study. By adding a day volume pays benefits of HBH care as a commercial insurance rider, will provide alternative benefits for the insureds. A multiple-state Markov chain model was incorporated to estimate the transition intensities of patients in different states at the end of their lives (Non-hospice, HBH, hospital-based hospice), and the premiums were estimated. HBH care insurance benefits provide financial support and reduce the burden of care for patients. The rate-making of this product is very sensitive while the utilization rate is rising, especially for high ages. The proposed HBH care insurance is a feasible way to reduce the financial burden, enhance the care quality and family satisfaction of insureds. Meanwhile, insurance companies can participate in advocating a good medical policy to enhance the social image. In addition, the medical costs of NHI can reduce effectively.

Keywords: home-based hospice care, commercial insurance, Markov chain model, the day volume pays

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Authors: Xiang Zheng, Zhaoping Zhong

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In this study, Aspen Plus was used to simulate the whole process of biomass conversion to liquid fuel in different ways, and the main results of material and energy flow were obtained. The process optimization and evaluation were carried out on the four routes of cellulosic biomass pyrolysis gasification low-carbon olefin synthesis olefin oligomerization, biomass water pyrolysis and polymerization to jet fuel, biomass fermentation to ethanol, and biomass pyrolysis to liquid fuel. The environmental impacts of three biomass species (poplar wood, corn stover, and rice husk) were compared by the gasification synthesis pathway. The global warming potential, acidification potential, and eutrophication potential of the three biomasses were the same as those of rice husk > poplar wood > corn stover. In terms of human health hazard potential and solid waste potential, the results were poplar > rice husk > corn stover. In the popular pathway, 100 kg of poplar biomass was input to obtain 11.9 kg of aviation coal fraction and 6.3 kg of gasoline fraction. The energy conversion rate of the system was 31.6% when the output product energy included only the aviation coal product. In the basic process of hydrothermal depolymerization process, 14.41 kg aviation kerosene was produced per 100 kg biomass. The energy conversion rate of the basic process was 33.09%, which can be increased to 38.47% after the optimal utilization of lignin gasification and steam reforming for hydrogen production. The total exergy efficiency of the system increased from 30.48% to 34.43% after optimization, and the exergy loss mainly came from the concentration of precursor dilute solution. Global warming potential in environmental impact is mostly affected by the production process. Poplar wood was used as raw material in the process of ethanol production from cellulosic biomass. The simulation results showed that 827.4 kg of pretreatment mixture, 450.6 kg of fermentation broth, and 24.8 kg of ethanol were produced per 100 kg of biomass. The power output of boiler combustion reached 94.1 MJ, the unit power consumption in the process was 174.9 MJ, and the energy conversion rate was 33.5%. The environmental impact was mainly concentrated in the production process and agricultural processes. On the basis of the original biomass pyrolysis to liquid fuel, the enzymatic hydrolysis lignin residue produced by cellulose fermentation to produce ethanol was used as the pyrolysis raw material, and the fermentation and pyrolysis processes were coupled. In the coupled process, 24.8 kg ethanol and 4.78 kg upgraded liquid fuel were produced per 100 kg biomass with an energy conversion rate of 35.13%.

Keywords: biomass conversion, biofuel, process optimization, life cycle assessment

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Authors: Mohammadjavad Mahdavinejad, Hadi Yazdi

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The greatest influence we have from the world is shaped through the visual form, thus light is an inseparable element in human life. The use of daylight in visual perception and environment readability is an important issue for users. With regard to the hazards of greenhouse gas emissions from fossil fuels, and in line with the attitudes on the reduction of energy consumption, the correct use of daylight results in lower levels of energy consumed by artificial lighting, heating and cooling systems. Windows are usually the starting points for analysis and simulations to achieve visual comfort and energy optimization; therefore, attention should be paid to the orientation of buildings to minimize electrical energy and maximize the use of daylight. In this paper, by using the Design Builder Software, the effect of the orientation of an 18m²(3m*6m) room with 3m height in city of Tehran has been investigated considering the design constraint limitations. In these simulations, the dimensions of the building have been changed with one degree and the window is located on the smaller face (3m*3m) of the building with 80% ratio. The results indicate that the orientation of building has a lot to do with energy efficiency to meet high-performance architecture and planning goals and objectives.

Keywords: daylight, window, orientation, energy consumption, design builder

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Authors: Aydin Teymourifar, Gurkan Ozturk, Ozan Bahadir

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In this paper, a new neural network based variable neighborhood search is proposed for the multi-objective dynamic, flexible job shop scheduling problems. The neural network controls the problems' constraints to prevent infeasible solutions, while the Variable Neighborhood Search (VNS) applies moves, based on the critical block concept to improve the solutions. Two approaches are used for managing the constraints, in the first approach, infeasible solutions are modified according to the constraints, after the moves application, while in the second one, infeasible moves are prevented. Several neighborhood structures from the literature with some modifications, also new structures are used in the VNS. The suggested neighborhoods are more systematically defined and easy to implement. Comparison is done based on a multi-objective flexible job shop scheduling problem that is dynamic because of the jobs different release time and machines breakdowns. The results show that the presented method has better performance than the compared VNSs selected from the literature.

Keywords: constrained optimization, neural network, variable neighborhood search, flexible job shop scheduling, dynamic multi-objective optimization

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Authors: Amela Ajanovic, Reinhard Haas

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Electric vehicles (EVs) are considered as an important means to cope with current environmental problems in transport. However, their high capital costs and limited driving ranges state major barriers to a broader market penetration. The core objective of this paper is to investigate the future market prospects of various types of EVs from an economic and ecological point of view. Our method of approach is based on the calculation of total cost of ownership of EVs in comparison to conventional cars and a life-cycle approach to assess the environmental benignity. The most crucial parameters in this context are km driven per year, depreciation time of the car and interest rate. The analysis of future prospects it is based on technological learning regarding investment costs of batteries. The major results are the major disadvantages of battery electric vehicles (BEVs) are the high capital costs, mainly due to the battery, and a low driving range in comparison to conventional vehicles. These problems could be reduced with plug-in hybrids (PHEV) and range extenders (REXs). However, these technologies have lower CO₂ emissions in the whole energy supply chain than conventional vehicles, but unlike BEV they are not zero-emission vehicles at the point of use. The number of km driven has a higher impact on total mobility costs than the learning rate. Hence, the use of EVs as taxis and in car-sharing leads to the best economic performance. The most popular EVs are currently full hybrid EVs. They have only slightly higher costs and similar operating ranges as conventional vehicles. But since they are dependent on fossil fuels, they can only be seen as energy efficiency measure. However, they can serve as a bridging technology, as long as BEVs and fuel cell vehicle do not gain high popularity, and together with PHEVs and REX contribute to faster technological learning and reduction in battery costs. Regarding the promotion of EVs, the best results could be reached with a combination of monetary and non-monetary incentives, as in Norway for example. The major conclusion is that to harvest the full environmental benefits of EVs a very important aspect is the introduction of CO₂-based fuel taxes. This should ensure that the electricity for EVs is generated from renewable energy sources; otherwise, total CO₂ emissions are likely higher than those of conventional cars.

Keywords: costs, mobility, policy, sustainability,

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Authors: Panpan Fan, Bo Ming, Niels Anten, Jochem Evers, Yaoyao Li, Shaokun Li, Ruizhi xie

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Nitrogen (N) utilization for crop production under N deficiency conditions is subject to a trade-off between maintaining specific leaf N content (SLN), important for radiation-use efficiency (RUE), versus maintaining leaf area (LA) development, important for light capture. This paper aims to explore how maize deals with this trade-off through responses in SLN, LA and their underlying traits during the vegetative and reproductive growth stages. In a ten-year N fertilization trial in Jilin province, Northeast China, three N fertilizer levels have been maintained: N-deficiency (N0), low N supply (N1), and high N supply (N2). We analyzed data from years 8 and 10 of this experiment for two common hybrids. Under N deficiency, maize plants maintained LA and decreased SLN during vegetative stages, while both LA and SLN decreased comparably during reproductive stages. Canopy-average specific leaf area (SLA) decreased sharply during vegetative stages and slightly during reproductive stages, mainly because senesced leaves in the lower canopy had a higher SLA. In the vegetative stage, maize maintained leaf area at low N by maintaining leaf biomass (albeit hence having N content/mass) and slightly increasing SLA. These responses to N deficiency were stronger in maize hybrid XY335 than in ZD958. We conclude the main strategy of maize to cope with low N is to maintain plant growth, mainly by increasing SLA throughout the plant during early growth. N was too limiting for either strategy to be followed during later growth stages.

Keywords: leaf N content per unit leaf area, N deficiency, specific leaf area, maize strateg

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Authors: Salako Emmanuel Adekunle

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With numerous advantages of ICT in teaching such as using images to improve the retentive memory of students, academic staff is yet to deliver instructions adequately and effectively due to no power supply, lack of technical supports and non-availability of functional ICT tools. This study was conducted to investigate the attitudes of academic staff towards the use of information communication technology as a pedagogical tool for effective teaching in FCT College of Education, Zuba-Abuja, Nigeria. A sample of 200 academic staff from five schools/faculties was involved in the study. The respondents were selected by using simple random sampling technique (SRST). A questionnaire was developed and validated by the experts in Measurement and Evaluation, and reliability co-efficient of 0.85 was obtained. It was used to gather relevant data from the respondents. This study revealed that the respondents had positive attitudes towards the use of ICT as a pedagogical tool for effective teaching. Also, the uses of ICT by the academic staff included: to encourage closer relationship for attainment of higher academic, and to deliver instructions effectively. The study also revealed that there is a significant relationship between the attitudes and the uses of ICT by the academic staff. Based on these findings, some recommendations were made which include: power supply should be provided to operate ICT facilities for effective teaching, and technical assistance on ICT usage for effective delivery of instructions should be provided among other recommendations.

Keywords: academic staff, attitudes, information communication technology, pedagogical tool, teaching, use

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Authors: F. Murilo T. Luna, Vanessa F. Oliveira, Alysson Rocha, Expedito J. S. Parente, Andre V. Bueno, Matheus C. M. Farias, Celio L. Cavalcante Jr.

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Aviation jetfuel used in aircraft gas-turbine engines is customarily obtained from the kerosene distillation fraction of petroleum (150-275°C). Mineral jetfuel consists of a hydrocarbon mixture containing paraffins, naphthenes and aromatics, with low olefins content. In order to ensure their safety, several stringent requirements must be met by jetfuels, such as: high energy density, low risk of explosion, physicochemical stability and low pour point. In this context, aviation fuels eventually obtained from biofeedstocks (which have been coined as ‘biojetfuel’), must be used as ‘drop in’, since adaptations in aircraft engines are not desirable, to avoid problems with their operation reliability. Thus, potential aviation biofuels must present the same composition and physicochemical properties of conventional jetfuel. Among the potential feedtstocks for aviation biofuel, the babaçu oil, extracted from a palm tree extensively found in some regions of Brazil, contains expressive quantities of short chain saturated fatty acids and may be an interesting choice for biojetfuel production. In this study, biojetfuel was synthesized through homogeneous transesterification of babaçu oil using methanol and its properties were compared with petroleum-based jetfuel through measurements of oxidative stability, physicochemical properties and low temperature properties. The transesterification reactions were carried out using methanol and after decantation/wash procedures, the methyl esters were purified by molecular distillation under high vacuum at different temperatures. The results indicate significant improvement in oxidative stability and pour point of the products when compared to the fresh oil. After optimization of operational conditions, potential biojetfuel samples were obtained, consisting mainly of C8 esters, showing low pour point and high oxidative stability. Jet engine tests are being conducted in an automated test bed equipped with pollutant emissions analysers to study the operational performance of the biojetfuel that was obtained and compare with a mineral commercial jetfuel.

Keywords: biojetfuel, babaçu oil, oxidative stability, engine tests

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Authors: Luis E. Zapata, Sergio Ruiz, María F. Mantilla, Jhon A. Villamizar

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Sand as fine aggregate for concrete production needs a feasible substitute due to several environmental issues. In this work, a study of the behavior of self-compacting concrete mixtures under replacement of sand by iron slag from 0.0% to 50.0% of weight and variations of water/cementitious material ratio between 0.3 and 0.5 is presented. Control fresh state tests of Slump flow, T500, J-ring and L-box were determined. In the hardened state, compressive strength was determined and optimization from response surface analysis was performed. The study of the variables in the hardened state was developed based on inferential statistical analyses using central composite design methodology and posterior analyses of variance (ANOVA). An increase in the compressive strength up to 50% higher than control mixtures at 7, 14, and 28 days of maturity was the most relevant result regarding the presence of iron slag as replacement of natural sand. Considering the obtained result, it is possible to infer that iron slag is an acceptable alternative replacement material of the natural fine aggregate to be used in structural concrete.

Keywords: ANOVA, iron slag, response surface analysis, self-compacting concrete

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Authors: Rayleigh Dada Abu, Halilu Ahmad Shaba

Abstract:

Siltation is a serious problem that affects public water supply infrastructures such as dams and reservoirs. It is a major problem which threatens the performance and sustainability of dams and reservoirs. It reduces the dam capacity for flood control, potable water supply, changes water stage, reduces water quality and recreational benefits. The focus of this study is the Lower Usuma reservoir. At completion the reservoir had a gross storage capacity of 100 × 106 m3 (100 million cubic metres), a maximum operational level of 587.440 m a.s.l., with a maximum depth of 49 m and a catchment area of 241 km2 at dam site with a daily designed production capacity of 10,000 cubic metres per hour. The reservoir is 1,300 m long and feeds the treatment plant mainly by gravity. The reservoir became operational in 1986 and no survey has been conducted to determine its current storage capacity and rate of siltation. Hydrographic survey of the reservoir by integrated acoustic echo-sounding technique was conducted in November 2012 to determine the level and rate of siltation. The result obtained shows that the reservoir has lost 12.0 meters depth to siltation in 26 years of its operation; indicating 24.5% loss in installed storage capacity. The present bathymetric survey provides baseline information for future work on siltation depth and annual rates of storage capacity loss for the Lower Usuma reservoir.

Keywords: sedimentation, lower Usuma reservoir, acoustic echo sounder, bathymetric survey

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Authors: Marzouk Benali, Jawad Jeaidi, Behrang Mansoornejad, Olumoye Ajao, Banafsheh Gilani, Nima Ghavidel Mehr

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Canadian forest industry is seeking to identify and implement transformational strategies for enhanced financial performance through the emerging bioeconomy or more specifically through the concept of the biorefinery. For example, processing forest residues or surplus of biomass available on the mill sites for the production of biofuels, biochemicals and/or biomaterials is one of the attractive strategies along with traditional wood and paper products and cogenerated energy. There are many possible process-product biorefinery pathways, each associated with specific product portfolios with different levels of risk. Thus, it is not obvious which unique strategy forest industry should select and implement. Therefore, there is a need for analytical and design tools that enable evaluating biorefinery strategies based on a set of criteria considering a perspective of sustainability over the short and long terms, while selecting the existing core products as well as selecting the new product portfolio. In addition, it is critical to assess the manufacturing flexibility to internalize the risk from market price volatility of each targeted bio-based product in the product portfolio, prior to invest heavily in any biorefinery strategy. The proposed paper will focus on introducing a systematic methodology for designing integrated biorefineries using process systems engineering tools as well as a multi-criteria decision making framework to put forward the most effective biorefinery strategies that fulfill the needs of the forest industry. Topics to be covered will include market analysis, techno-economic assessment, cost accounting, energy integration analysis, life cycle assessment and supply chain analysis. This will be followed by describing the vision as well as the key features and functionalities of the I-BIOREF software platform, developed by CanmetENERGY of Natural Resources Canada. Two industrial case studies will be presented to support the robustness and flexibility of I-BIOREF software platform: i) An integrated Canadian Kraft pulp mill with lignin recovery process (namely, LignoBoost™); ii) A standalone biorefinery based on ethanol-organosolv process.

Keywords: biorefinery strategies, bioproducts, co-production, multi-criteria decision making, tool

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Authors: Vethathirri Ramanujam Srinivasan, S. M. Shiva Nagendra

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Air quality management in urban areas is a serious concern in both developed and developing countries. In this regard, more number of air quality monitoring stations are planned to mitigate air pollution in urban areas. In India, Central Pollution Control Board has set up 574 air quality monitoring stations across the country and proposed to set up another 500 stations in the next few years. The number of monitoring stations for each city has been decided based on population data. The setting up of ambient air quality monitoring stations and their operation and maintenance are highly expensive. Therefore, there is a need to optimize monitoring networks for air quality management. The present paper discusses the various methods such as Indian Standards (IS) method, US EPA method and European Union (EU) method to arrive at the minimum number of air quality monitoring stations. In addition, optimization of rain-gauge method and Inverse Distance Weighted (IDW) method using Geographical Information System (GIS) are also explored in the present work for the design of air quality network in Chennai city. In summary, additionally 18 stations are required for Chennai city, and the potential monitoring locations with their corresponding land use patterns are ranked and identified from the 1km x 1km sized grids.

Keywords: air quality monitoring network, inverse distance weighted method, population based method, spatial variation

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Authors: Baljit Singh Khehra, Amar Partap Singh Pharwaha

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Clusters of Microcalcifications (MCCs) are most frequent symptoms of Ductal Carcinoma in Situ (DCIS) recognized by mammography. Least-Square Support Vector Machine (LS-SVM) is a variant of the standard SVM. In the paper, LS-SVM is proposed as a classifier for classifying MCCs as benign or malignant based on relevant extracted features from enhanced mammogram. To establish the credibility of LS-SVM classifier for classifying MCCs, a comparative evaluation of the relative performance of LS-SVM classifier for different kernel functions is made. For comparative evaluation, confusion matrix and ROC analysis are used. Experiments are performed on data extracted from mammogram images of DDSM database. A total of 380 suspicious areas are collected, which contain 235 malignant and 145 benign samples, from mammogram images of DDSM database. A set of 50 features is calculated for each suspicious area. After this, an optimal subset of 23 most suitable features is selected from 50 features by Particle Swarm Optimization (PSO). The results of proposed study are quite promising.

Keywords: clusters of microcalcifications, ductal carcinoma in situ, least-square support vector machine, particle swarm optimization

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Authors: B. Adebayo, A. A. Adebayo

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Adequate power generation and supply are enormous challenges confronting Nigeria state today. This is a powerful mechanism that drives industrial development and socio-economy of any nation. The present level of power generation and supply have become national embarrassment to both government and the citizens of Nigeria, where over 60% of the population have no access to electricity. This paper is set to review the abundant clean energy alternative sources available in abundance that are capable of boosting power generation. The clean energy sources waiting to be exploited include: nuclear, solar and wind energy. The environmental benefits of these sources of power generation are identified. Nuclear energy is a powerful clean energy source. However, Africa accounted for 20% of known recoverable reserve and uranium produces heat of 500,000 MJ/kg. Moreover, Nigeria receives average daily solar radiation of over 5.249 kWh/m2/day. Researchers have shown that wind speed and power flux densities varied from 1.5 – 4.1 m/s and 5.7 – 22.5 W/m2 respectively. It is a fact that the cost of doing business in Nigeria is very high, leading to winding up of the multi-national companies and then led to increase unemployment level. More importantly, readily available vast quantity of energy will reduce cost of running industries. Hence, more industries will come on board, goods, services, and more job creation will be achieved. This clean source of power generation is devoid of production of green house gases, elimination of environmental pollution, and reduced waste disposal. Then Nigerians will live in harmony with the environment.

Keywords: power, generation, energy, mix, clean, industrial

Procedia PDF Downloads 311

Authors: Vahid Nademi

Abstract:

In response to widely used wearable medical devices equipped with a continuous glucose monitor (CGM) and insulin pump, the advanced control methods are still demanding to get the full benefit of these devices. Unlike costly clinical trials, implementing effective insulin-glucose control strategies can provide significant contributions to the patients suffering from chronic diseases such as diabetes. This study deals with a key role of two-layer insulin-glucose regulator based on model-predictive-control (MPC) scheme so that the patient’s predicted glucose profile is in compliance with the insulin level injected through insulin pump automatically. It is achieved by iterative optimization algorithm which is called an integrated perturbation analysis and sequential quadratic programming (IPA-SQP) solver for handling uncertainties due to unexpected variations in glucose-insulin values and body’s characteristics. The feasibility evaluation of the discussed control approach is also studied by means of numerical simulations of two case scenarios via measured data. The obtained results are presented to verify the superior and reliable performance of the proposed control scheme with no negative impact on patient safety.

Keywords: blood glucose monitoring, insulin pump, predictive control, optimization

Procedia PDF Downloads 136

Authors: Jeong-Hyun Hong, Wonsuk Choi, Hyungdal Park, Jinseok Kim, Junesun Kim

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Identifying the chronic functions of an implanted neural electrode is an important factor in acquiring neural signals through the electrode or restoring the nerve functions after peripheral nerve injury. The purpose of this study was to investigate the biocompatibility of the chronic implanted neural electrode into the sciatic nerve. To do this, a sieve-type neural electrode was implanted at proximal and distal ends of a transected sciatic nerve as an experimental group (Sieve group, n=6), and the end-to-end epineural repair was operated with the cut sciatic nerve as a control group (reconstruction group, n=6). All surgeries were performed on the sciatic nerve of the right leg in Sprague Dawley rats. Behavioral tests were performed before and 1, 4, 7, 10, 14, and weekly days until 5 months following surgery. Changes in sensory function were assessed by measuring paw withdrawal responses to mechanical and cold stimuli. Motor function was assessed by motion analysis using a Qualisys program, which showed a range of motion (ROM) related to the joints. Neurofilament-heavy chain and fibronectin expression were detected 5 months after surgery. In both groups, the paw withdrawal response to mechanical stimuli was slightly decreased from 3 weeks after surgery and then significantly decreased at 6 weeks after surgery. The paw withdrawal response to cold stimuli was increased from 4 days following surgery in both groups and began to decrease from 6 weeks after surgery. The ROM of the ankle joint was showed a similar pattern in both groups. There was significantly increased from 1 day after surgery and then decreased from 4 days after surgery. Neurofilament-heavy chain expression was observed throughout the entire sciatic nerve tissues in both groups. Especially, the sieve group was showed several neurofilaments that passed through the channels of the sieve-type neural electrode. In the reconstruction group, however, a suture line was seen through neurofilament-heavy chain expression up to 5 months following surgery. In the reconstruction group, fibronectin was detected throughout the sciatic nerve. However, in the sieve group, the fibronectin was observed only in the surrounding nervous tissues of an implanted neural electrode. The present results demonstrated that the implanted sieve-type neural electrode induced a focal inflammatory response. However, the chronic implanted sieve-type neural electrodes did not cause any further inflammatory response following peripheral nerve injury, suggesting the possibility of the chronic application of the sieve-type neural electrodes. This work was supported by the Basic Science Research Program funded by the Ministry of Science (2016R1D1A1B03933986), and by the convergence technology development program for bionic arm (2017M3C1B2085303).

Keywords: biocompatibility, motor functions, neural electrodes, peripheral nerve injury, sensory functions

Procedia PDF Downloads 151