Search results for: supply chain delivery models

Authors: Petra Buzkova, Milos Kopa

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Reliability of the credit default swap market had been questioned repeatedly during the EMU debt crisis. The article examines whether this development influenced sovereign EMU CDS prices in general. We regress the CDS market price on a model risk neutral CDS price obtained from an adopted reduced form valuation model in the 2009-2013 period. We look for a break point in the single-equation and multi-equation econometric models in order to show the changes in relations between CDS market and model prices. Our results differ according to the risk profile of a country. We find that in the case of riskier countries, the relationship between the market and model price changed when market participants started to question the ability of CDS contracts to protect their buyers. Specifically, it weakened after the change. In the case of less risky countries, the change happened earlier and the effect of a weakened relationship is not observed.

Keywords: chow stability test, credit default swap, debt crisis, reduced form valuation model, seemingly unrelated regression

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Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

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Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

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Authors: Kopal Verma, Umesh C. Kulshrestha

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The mountainous regions are very crucial for a country because of their importance for weather, water supply, forests, and various other socio-economic benefits. But the increasing population and its demand for energy and infrastructure have contributed very high loadings of air pollution. Various activities such as cooking, heating, manufacturing, transport, etc. contribute various particulate and gaseous pollutants in the atmosphere. This study was focused upon indoor air pollution and was carried out in four rural households of the Baggi village located in the Hamirpur District of the Himachal Pradesh state. The residents of Baggi village use biomass as fuel for cooking on traditional stove (Chullah). The biomass types include wood (mainly Beul, Grewia Optiva), crop residue and dung cakes. This study aimed to determine the organic carbon (OC), elemental carbon (EC), major cations and anions in the indoor air of each household. During non-cooking hours, it was found that the indoor air contained OC and EC as low as 21µg/m³ and 17µg/m³ respectively. But during cooking hours (with biomass burning), the levels of OC and EC were raised significantly by 91.2% and 85.4% respectively. Then the residents were advised to switch over as per our soft approach options. In the first approach change, they were asked to prepare the meal partially on Chullah using biomass and partially with liquefied petroleum gas (LPG). By doing this change, a considerable reduction in OC (53.1%) and in EC (41.8%) was noticed. The second change of approach included the cooking of entire meal by using LPG. This resulted in the reduction of OC (84.1%) and EC (73.3%) as compared to the values obtained during cooking entirely with biomass. The carbonaceous aerosol levels were higher in the morning hours than in the evening hours because of more biomass burning activity in the morning. According to a general survey done with the residents, the study provided them an awareness about the air pollution and the harmful effects of biomass burning. Some of them correlated their ailments like weakened eyesight, fatigue and respiratory problems with indoor air pollution. This study demonstrated that by replacing biomass with clean fuel such as LPG, the indoor concentrations of EC and OC can be reduced substantially.

Keywords: biomass burning, carbonaceous aerosol, elemental carbon, organic carbon, LPG

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Authors: Aura Alejandra Burbano Patino, Mariela Agotegaray, Veronica Lassalle, Fernanda Horst

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Water pollution is of worldwide concern due to its importance as an essential resource for life. Industrial and urbanistic growth are anthropogenic activities that have caused an increase of undesirable compounds in water. In the last decade, emerging pollutants have become of great interest since, at very low concentrations (µg/L and ng/L), they exhibit a hazardous effect on wildlife, aquatic ecosystems, and human organisms. One group of emerging pollutants that are a matter of study are pharmaceuticals. Their high consumption rate and their inappropriate disposal have led to their detection in wastewater treatment plant influent, effluent, surface water, and drinking water. In consequence, numerous technologies have been developed to efficiently treat these pollutants. Adsorption appears like an easy and cost-effective technology. One of the most used adsorbents of emerging pollutants removal is carbon-based materials such as hydrochars. This study aims to use a magnetic hydrochar nanocomposite to be employed as an adsorbent for diclofenac removal. Kinetics models and the adsorption efficiency in real water samples were analyzed. For this purpose, a magnetic hydrochar nanocomposite was synthesized through the hydrothermal carbonization (HTC) technique hybridized to co-precipitation to add the magnetic component into the hydrochar, based on iron oxide nanoparticles. The hydrochar was obtained from sunflower husk residue as the precursor. TEM, TGA, FTIR, Zeta potential as a function of pH, DLS, BET technique, and elemental analysis were employed to characterize the material in terms of composition and chemical structure. Adsorption kinetics were carried out in distilled water and real water at room temperature, pH of 5.5 for distilled water and natural pH for real water samples, 1:1 adsorbent: adsorbate dosage ratio, contact times from 10-120 minutes, and 50% dosage concentration of DCF. Results have demonstrated that magnetic hydrochar presents superparamagnetic properties with a saturation magnetization value of 55.28 emu/g. Besides, it is mesoporous with a surface area of 55.52 m²/g. It is composed of magnetite nanoparticles incorporated into the hydrochar matrix, as can be proven by TEM micrographs, FTIR spectra, and zeta potential. On the other hand, kinetic studies were carried out using DCF models, finding percent removal efficiencies up to 85.34% after 80 minutes of contact time. In addition, after 120 minutes of contact time, desorption of emerging pollutants from active sites took place, which indicated that the material got saturated after that t time. In real water samples, percent removal efficiencies decrease up to 57.39%, ascribable to a possible mechanism of competitive adsorption of organic or inorganic compounds, ions for active sites of the magnetic hydrochar. The main suggested adsorption mechanism between the magnetic hydrochar and diclofenac include hydrophobic and electrostatic interactions as well as hydrogen bonds. It can be concluded that the magnetic hydrochar nanocomposite could be valorized into a by-product which appears as an efficient adsorbent for DCF removal as a model emerging pollutant. These results are being complemented by modifying experimental variables such as pollutant’s initial concentration, adsorbent: adsorbate dosage ratio, and temperature. Currently, adsorption assays of other emerging pollutants are being been carried out.

Keywords: environmental remediation, emerging pollutants, hydrochar, magnetite nanoparticles

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Authors: Yehia Manawi, Ahmad Kayvanifard

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Membrane distillation is an emerging technology which has been used to produce freshwater and purify different types of aqueous mixtures. Qatar is an arid country where almost 100% of its freshwater demand is supplied through the energy-intensive thermal desalination process. The country’s need for water has reached an all-time high which stipulates finding an alternative way to augment freshwater without adding any drastic affect to the environment. The objective of this paper was to investigate the potential of using the industrial low grade waste heat to produce freshwater using membrane distillation. The main part of this work was conducting a heat audit on selected Qatari chemical industries to estimate the amounts of freshwater produced if such industrial waste heat were to be recovered. By the end of this work, the main objective was met and the heat audit conducted on the Qatari chemical industries enabled us to estimate both the amounts of waste heat which can be potentially recovered in addition to the amounts of freshwater which can be produced if such waste heat were to be recovered. By the end, the heat audit showed that around 605 Mega Watts of waste heat can be recovered from the studied Qatari chemical industries which resulted in a total daily production of 5078.7 cubic meter of freshwater. This water can be used in a wide variety of applications such as human consumption or industry. The amount of produced freshwater may look small when compared to that produced through thermal desalination plants; however, one must bear in mind that this water comes from waste and can be used to supply water for small cities or remote areas which are not connected to the water grid. The idea of producing freshwater from the two widely-available wastes (thermal rejected brine and waste heat) seems promising as less environmental and economic impacts will be associated with freshwater production which may in the near future augment the conventional way of producing freshwater currently being thermal desalination. This work has shown that low grade waste heat in the chemical industries in Qatar and perhaps the rest of the world can contribute to additional production of freshwater using membrane distillation without significantly adding to the environmental impact.

Keywords: membrane distillation, desalination, heat recovery, environment

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Authors: Varsha Pandurang Nagargoje, K. S. James

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Background: Social participation is considered as one of the central components of successful and healthy aging. This study aimed to examine the moderating role of marital status and living arrangement in the relationship between social participation and life satisfaction and other potential factors associated with life satisfaction of Indian older adults. Method: For analyses, the nationally representative study sample of 31,464 adults aged ≥60 years old was extracted from the Longitudinal Ageing Study in India (LASI) wave 1, 2017-18. Descriptive statistics and bivariate analysis have been performed to determine the proportion of life satisfaction. The first set of multivariable linear regression analyses examined Diener’s Satisfaction with Life Scale and its association with various predictor variables, including social participation, marital status, living arrangements, socio-demographic, economic, and health-related variables. Further, the second and third sets of regression investigated the moderating role of marital status and living arrangements respectively in the association of social participation and level of life satisfaction among Indian older adults. Results: Overall, the proportion of life satisfaction among older men was relatively higher than women counterparts in most background characteristics. Regression results stressed the importance of older adults’ involvement in social participation [β = 0.39, p < 0.05], being in marital union [β = 0.68, p < 0.001] and co-residential living arrangements either only with spouse [β = 1.73, p < 0.001] or with other family members [β = 2.18, p < 0.001] for the improvement of life satisfaction. Results also showed that some factors were significant for life satisfaction: in particular, increased age, having a higher level of educational status, MPCE quintile, and caste category. Higher risk of life dissatisfaction found among Indian older adults who were exposed to vulnerabilities like consuming tobacco, poor self-rated health, having difficulty in performing ADL and IADL were of major concern. The interaction effect of social participation with marital status or with living arrangements explained that currently married older individuals, and those older adults who were either co-residing with their spouse only or with other family members irrespective of their involvement in social participation remained an important modifiable factor for life satisfaction. Conclusion: It would be crucial for policymakers and practitioners to advocate social policy programs and service delivery oriented towards meaningful social connections, especially for those Indian older adults who were staying alone or currently not in the marital union to enhance their overall life satisfaction.

Keywords: Indian, older adults, social participation, life satisfaction, marital status, living arrangement

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Authors: Carolina Cuéllar, Paz González

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Research has shown that school leadership has a significant indirect effect on students’ achievements. In Chile, evidence has also revealed that this impact is stronger in vulnerable schools. With the aim of strengthening school leadership, public policy has taken up the challenge of enhancing capabilities of novice principals through the implementation of induction programs, which include a mentoring component, entrusting the task of delivering these programs to universities. The importance of using mentoring or coaching models in the preparation of novice school leaders has been emphasized in the international literature. Thus, it can be affirmed that building leadership capacity through partnership is crucial to facilitate cognitive and affective support required in the initial phase of the principal career, gain role clarification and socialization in context, stimulate reflective leadership practice, among others. In Chile, mentoring is a recent phenomenon in the field of school leadership and it is even more new in the preparation of new principals who work in public schools. This study, funded by the Chilean Ministry of Education, sought to explore the challenges and lessons arising from the design and implementation of mentoring processes which are part of the induction programs, according to the perception of the different actors involved: ministerial agents, university coordinators, mentors and novice principals. The investigation used a qualitative design, based on a study of three cases (three induction programs). The sources of information were 46 semi-structured interviews, applied in two moments (at the beginning and end of mentoring). Content analysis technique was employed. Data focused on the uniqueness of each case and the commonalities within the cases. Five main challenges and lessons emerged in the design and implementation of mentoring within the induction programs for new principals from Chilean public schools. They comprised the need of (i) developing a shared conceptual framework on mentoring among the institutions and actors involved, which helps align the expectations for the mentoring component within the induction programs, along with assisting in establishing a theory of action of mentoring that is relevant to the public school context; (ii) recognizing trough actions and decisions at different levels that the role of a mentor differs from the role of a principal, which challenge the idea that an effective principal will always be an effective mentor; iii) improving mentors’ selection and preparation processes trough the definition of common guiding criteria to ensure that a mentor takes responsibility for developing critical judgment of novice principals, which implies not limiting the mentor’s actions to assist in the compliance of prescriptive practices and standards; (iv) generating common evaluative models with goals, instruments and indicators consistent with the characteristics of mentoring processes, which helps to assess expected results and impact; and (v) including the design of a mentoring structure as an outcome of the induction programs, which helps sustain mentoring within schools as a collective professional development practice. Results showcased interwoven elements that entail continuous negotiations at different levels. Taking action will contribute to policy efforts aimed at professionalizing the leadership role in public schools.

Keywords: induction programs, mentoring, novice principals, school leadership preparation

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Authors: Jia-Ling Ho, Xiu-Ru Zhang, Zwe-Ling Kong

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Diabetes mellitus (DM) is a major health problem that affects patients’ life quality throughout the world due to its many complications. It characterized by chronic hyperglycemia with oxidative stress, which impaired male reproductive function. Fibroblast growth factor 21 (FGF21) is a metabolic regulator that is required for normal spermatogenesis and protects against diabetes-induced germ cell apoptosis. Echinacea purpurea ethanol extract (EE), which contain phenolic acid and isobutylamide, had been proven to have antidiabetic property. Silica-chitosan nanoparticles (Nano-CS) has drug delivery and controlled release properties. This study aims to investigate whether silica-chitosan nanoparticles encapsulated EE (Nano-EE) had more ameliorating male infertility by analyzing the effect of testicular FGF21. The Nano-EE was characterized before used to treatment the diabetic rat model. Male Sprague-Dawley (SD) rats were obtained and divided into seven groups. A group was no induced Streptozotocin (STZ), marked as normal group. Diabetic rats were induced into diabetes by STZ (33 mg/kg). A diabetic group was no treatment with sample (diabetic control group), and other groups were treatment by Nano-CS (465 mg/kg), Nano-EE (93, 279, 465 mg/kg), and metformin (Met) (200 mg/kg) used as reference drug for 7 weeks. Our results indicated that the average nanoparticle size and zeta potential of Nano-EE were 2630 nm and -21.3 mV, respectively. The encapsulation ratio of Nano-EE was about 70%. It also confirmed the antioxidative activity was unchanged by comparing the DPPH and ABTS scavenging of Nano-EE and EE. In vivo test, Nano-EE can improve the STZ induced hyperglycemia, insulin resistance, and plasma FGF21 levels. Nano-EE has increased sperm motility, mitochondria membrane potential (MMP), plasma testosterone level, and reduction of abnormal sperm, nitric oxide (NO), superoxide production as well as reactive oxygen species (ROS). In addition, in plasma antioxidant enzymes glutathione peroxidase (GPx) and superoxide dismutase (SOD) was increased whereas pro-inflammatory cytokines TNF-α, and IL-1β were decreased. Further, in testis, protein content of FGF21, PGC-1α, and SIRT1 were improved. Nano-EE might improve diabetes-induced down-regulation of testicular FGF21 and SIRT1/PGC-1α signaling hence maintain spermatogenesis.

Keywords: diabetes mellitus, Echinacea purpurea, reproductive dysfunction, silica-chitosan nanoparticles

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Authors: Maftunakhon Latipova, Feruza Khaydarova

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Obesity is considered a chronic metabolic disease that occurs at any age. Regulation of body weight in the body is carried out through complex interaction of a complex of interrelated systems that control the body's energy system. Energy imbalance is the cause of obesity and overweight, in which the supply of energy from food exceeds the energy needs of the body. Obesity is closely related to impaired appetite regulation, and a hypothalamus is a key place for neural regulation of food consumption. The nucleus of the hypothalamus is connected and interdependent on receiving, integrating and sending hunger signals to regulate appetite. Purpose of the study: to identify markers of food behavior. Materials and methods: The screening was carried out to identify eating disorders in 200 men and women aged 18 to 35 years with overweight and obesity and to check the effects of Orexin A and Neuropeptide Y markers. A questionnaire and questionnaires were conducted with over 200 people aged 18 to 35 years. Questionnaires were for eating disorders and hidden depression (on the Zang scale). Anthropometry is measured by OT, OB, BMI, Weight, and Height. Based on the results of the collected data, 3 groups were divided: People with obesity, People with overweight, Control Group of Healthy People. Results: Of the 200 analysed persons, 86% had eating disorders. Of these, 60% of eating disorders were associated with childhood. According to the Zang test result: Normal condition was about 37%, mild depressive disorder 20%, moderate depressive disorder 25% and 18% of people suffered from severe depressive disorder without knowing it. One group of people with obesity had eating disorders and moderate and severe depressive disorder, and group 2 was overweight with mild depressive disorder. According to laboratory data, the first group had the lowest concentration of Orexin A and Neuropeptide U in blood serum. Conclusions: Being overweight and obese are the first signal of many diseases, and prevention and detection of these disorders will prevent various diseases, including type 2 diabetes. Obesity etiology is associated with eating disorders and signal transmission of the orexinorghetic system of the hypothalamus.

Keywords: obesity, endocrinology, hypothalamus, overweight

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi

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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.

Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition

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Authors: Nasser Almonawer

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Timely reaction to an evolving global business environment and volatile market conditions necessitates system and process flexibility, which in turn demands agile and adaptable architecture and a steady infusion of affordable new technologies. On the contrary, a large number of organizations utilize systems characterized by inflexible and obsolete legacy architectures. To effectively respond to the dynamic contemporary business environments, such architectures must be migrated to robust and modular open architectures. To this end, this paper proposes an integrated decision support system for a seamless migration to open systems. The proposed decision support system (DSS) integrates three well-established quantitative and qualitative decision-making models—namely, the Delphi method, Analytic Hierarchy Process (AHP) and Goal Programming (GP) to (1) assess risks and establish evaluation criteria; (2) formulate migration strategy and rank candidate systems; and (3) allocate resources among the selected systems.

Keywords: decision support systems, open systems architecture, analytic hierarchy process (AHP), goal programming (GP), delphi method

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Authors: Manasse Elusma, Thung-Hong Lin, Chun-yin Lee

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The relationship between hunger and war or conflict remains to be discussed. Do wars or conflicts cause hunger and food scarcity, or is the reverse relationship is true? As the world becomes more peaceful and wealthier, some countries are still suffered from hunger and food shortage. So, eradicating hunger calls for a more comprehensive understanding of the relationship between conflict and hunger. Several studies are carried out to detect the importance of conflict or war on food security. Most of these studies, however, perform only descriptive analysis and largely use food security indicators instead of the global hunger index. Few studies have employed cross-country panel data to explicitly analyze the association between conflict and chronic hunger, including hidden hunger. Herein, this study addresses this issue and the knowledge gap. We combine global datasets to build a new panel dataset including 143 countries from 1989 to 2020. This study examines the effect of conflict on hunger with fixed effect models, and the results show that the increase of conflict frequency deteriorates hunger. Peacebuilding efforts and war prevention initiative are required to eradicate global hunger.

Keywords: armed conflict, food scarcity, hidden hunger, hunger, malnutrition

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Authors: A. Shafaghat, H. Khabbaz, S. Moravej, Ah. Shafaghat

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The bearing capacity of closely spaced shallow footings alters with their spacing and the shape of footing. In this study, the bearing capacity and settlement of two adjacent footings constructed on a sand layer are investigated. The effect of different footing shapes including square, circular, ring and strip on sandy soil is captured in the calculations. The investigations are carried out numerically using PLAXIS-3D software and analytically employing conventional settlement equations. For this purpose, foundations are modelled in the program with practical dimensions and various spacing ratios ranging from 1 to 5. The spacing ratio is defined as the centre-to-centre distance to the width of foundations (S/B). Overall, 24 models are analyzed; and the results are compared and discussed in detail. It can be concluded that the presence of adjacent foundation leads to the reduction in bearing capacity for round shape footings while it can increase the bearing capacity of rectangular footings in some specific distances.

Keywords: bearing capacity, finite element analysis, loose sand, settlement equations, shallow foundation

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Authors: Mark Lin, Periklis Papadopoulos

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This paper explores the aerodynamics of the formula racecar when a ‘halo’ driver-protection device is added to the chassis. The halo protection device was introduced at the start of the 2018 racing season as a safety measure against foreign object impacts that a driver may encounter when driving an open-wheel racecar. In the one-year since its introduction, the device has received wide acclaim for protecting the driver on two separate occasions. The benefit of such a safety device certainly cannot be disputed. However, by adding the halo device to a car, it changes the airflow around the vehicle, and most notably, to the engine air-intake and the rear wing. These negative effects in the air supply to the engine, and equally to the downforce created by the rear wing are studied in this paper using numerical technique, and the resulting CFD outputs are presented and discussed. Comparing racecar design prior to and after the introduction of the halo device, it is shown that the design of the air intake and the rear wing has not followed suit since the addition of the halo device. The reduction of engine intake mass flow due to the halo device is computed and presented for various speeds the car may be going. Because of the location of the halo device in relation to the air intake, airflow is directed away from the engine, making the engine perform less than optimal. The reduction is quantified in this paper to show the correspondence to reduce the engine output when compared to a similar car without the halo device. This paper shows that through aerodynamic arguments, the engine in a halo car will not receive unobstructed, clean airflow that a non-halo car does. Another negative effect is on the downforce created by the rear wing. Because the amount of downforce created by the rear wing is influenced by every component that comes before it, when a halo device is added upstream to the rear wing, airflow is obstructed, and less is available for making downforce. This reduction in downforce is especially dramatic as the speed is increased. This paper presents a graph of downforce over a range of speeds for a car with and without the halo device. Acknowledging that although driver safety is paramount, the negative effect of this safety device on the performance of the car should still be well understood so that any possible redesign to mitigate these negative effects can be taken into account in next year’s rules regulation.

Keywords: automotive aerodynamics, halo device, downforce. engine intake

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Authors: Nathi Ram, Saurabh K. Yadav

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In turbomachinery, the turbulent flow occurs due to the use of high velocity of low kinematic viscosity lubricants and used in many industrial applications. In the present work, the performance of symmetric slot-entry hybrid worn journal bearing under laminar and turbulent lubrication has been investigated. For turbulent lubrication, the Reynolds equation has been modified using Constantinescu turbulent model. This modified equation has been solved using the finite element method. The effect of turbulent lubrication on bearing’s performance has been presented for symmetric hybrid journal bearing. The slot-entry hybrid worn journal bearing under turbulent/laminar regimes have been investigated. It has been observed that the stiffness and damping coefficients are more for the bearing having slot width ratio (SWR) of 0.25 than the bearing with SWR of 0.5 and 0.75 under the turbulent regime. Further, it is also observed that for constant wear depth parameter, stability threshold speed gets increased for bearing operates at slot width ratio 0.25 under turbulent lubrication.

Keywords: hydrostatic bearings, journal bearings, restrictors, turbulent flow models, finite element technique

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Authors: Yanqun Li, Hong Geng

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The occurrence of Wenchuan earthquake in 2008 has led to severe damage to the rural areas of Chengdu city, such as the rupture of the social network, the stagnation of economic production and the rupture of living space. The post-disaster reconstruction has become a sustainable issue. As an important link to maintain the order of rural social development, social network should be an important content of post-disaster reconstruction. Therefore, this paper takes rural reconstruction communities in earthquake-stricken areas of Chengdu as the research object and adopts sociological research methods such as field survey, observation and interview to try to understand the transformation of rural social relations network under the influence of earthquake and its impact on rural space. It has found that rural societies under the earthquake generally experienced three phases: the break of stable social relations, the transition of temporary non-normal state, and the reorganization of social networks. The connotation of phased rural social relations also changed accordingly: turn to a new division of labor on the social orientation, turn to a capital flow and redistribution in new production mode on the capital orientation, and turn to relative decentralization after concentration on the spatial dimension. Along with such changes, rural areas have emerged some social issues such as the alienation of competition in the new industry division, the low social connection, the significant redistribution of capital, and the lack of public space. Based on a comprehensive review of these issues, this paper proposes the corresponding response mechanism. First of all, a reasonable division of labor should be established within the villages to realize diversified commodity supply. Secondly, the villages should adjust the industrial type to promote the equitable participation of capital allocation groups. Finally, external public spaces should be added to strengthen the field of social interaction within the communities.

Keywords: social relations, social support networks, industrial division, capital allocation, public space

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Authors: Chico Horacio Jose Sambo

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Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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Authors: Ljiljana Stojković, Manja Zec, Maja Zivkovic, Maja Bundalo, Marija Glibetić, Dragan Alavantić, Aleksandra Stankovic

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Cardiovascular disease (CVD) is associated with alterations in DNA methylation, the latter modulated by dietary polyphenols. The present pilot study (part of the original clinical study registered as NCT02800967 at www.clinicaltrials.gov) aimed to investigate the impact of 4-week daily consumption of polyphenol-rich Aronia melanocarpa juice on Long Interspersed Nucleotide Element-1 (LINE-1) methylation in peripheral blood leukocytes, in subjects (n=34, age of 41.1±6.6 years) at moderate CVD risk, including an increased body mass index, central obesity, high normal blood pressure and/or dyslipidemia. The goal was also to examine whether factors known to affect DNA methylation, such as folate intake levels, MTHFR C677T gene variant, as well as the anthropometric and metabolic parameters, modulated the LINE-1 methylation levels upon consumption of polyphenol-rich Aronia juice. The experimental analysis of LINE-1 methylation was done by the MethyLight method. MTHFR C677T genotypes were determined by the polymerase chain reaction-restriction fragment length polymorphism method. Folate intake was assessed by processing the data from the food frequency questionnaire and repeated 24-hour dietary recalls. Serum lipid profile was determined by using Roche Diagnostics kits. The statistical analyses were performed using the Statistica software package. In women, after vs. before the treatment period, a significant decrease in LINE-1 methylation levels was observed (97.54±1.50% vs. 98.39±0.86%, respectively; P=0.01). The change (after vs. before treatment) in LINE-1 methylation correlated directly with MTHFR 677T allele presence, average daily folate intake and the change in serum low-density lipoprotein cholesterol, while inversely with the change in serum triacylglycerols (R=0.72, R2=0.52, adjusted R2=0.36, P=0.03). The current results imply potential cardioprotective effects of habitual polyphenol-rich Aronia juice consumption achieved through the modifications of DNA methylation pattern in subjects at CVD risk, which should be further confirmed. Hence, the precision nutrition-driven modulations of DNA methylation may become targets for new approaches in the prevention and treatment of CVD.

Keywords: Aronia melanocarpa, cardiovascular risk, LINE-1, methylation, peripheral blood leukocytes, polyphenol

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Authors: Lethukuthula Ngobese, Abin Gupthar, Patrick Govender

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The ability of yeast cell wall-derived mannoproteins (glycoproteins) to positively contribute to oenological properties has been a key factor that stimulates research initiatives into these industrially important glycoproteins. In addition, and from a fundamental research perspective, yeast cell wall glycoproteins are involved in a wide range of biological interactions. To date, and to the best of our knowledge, our understanding of the fine molecular structure of these mannoproteins is fairly limited. Generally, the amino acid sequences of their protein moieties have been established from structural and functional analysis of the genomic sequence of these yeasts whilst far less information is available on the glycosyl moieties of these mannoproteins. A novel strategy was devised in this study that entails the genetic engineering of yeast strains that over-express and release cell wall-associated glycoproteins into the liquid growth medium. To this end, the Flo1p mannoprotein was overexpressed in Saccharomyces cerevisiae laboratory strains bearing a specific deletion in KNR4 and GPI7 genes involved in cell wall biosynthesis that have been previously shown to extracellularly hyper-secrete cell wall-associated glycoproteins. A polymerase chain reaction (PCR) -based cloning strategy was employed to generate transgenic yeast strains in which the native cell wall FLO1 glycoprotein-encoding gene is brought under transcriptional control of the constitutive PGK1 promoter. The modified Helm’s flocculation assay was employed to assess flocculation intensities of a Flo1p over-expressing wild type and deletion mutant as an indirect measure of their abilities to release the desired mannoprotein. The flocculation intensities of the transformed strains were assessed and all the strains showed similar intensities (>98% flocculation). To assess if mannoproteins were released into the growth medium, the supernatant of each strain was subjected to the BCA protein assay and the transformed Δknr4 strain showed a considerable increase in protein levels. This study has the potential to produce mannoproteins in sufficient quantities that may be employed in future investigations to understand their molecular structures and mechanisms of interaction to the benefit of both fundamental and industrial applications.

Keywords: glycoproteins, genetic engineering, flocculation, over-expression

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Authors: Scott Hollier, Ruchi Permvattana

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The purpose of this abstract is to share the findings of a recently completed disability-related Internet of Things (IoT) project undertaken at Curtin University in Australia. The project focused on identifying how IoT could support people with disabilities with their educational outcomes. To achieve this, the research consisted of an analysis of current literature and interviews conducted with students with vision, hearing, mobility and print disabilities. While the research acknowledged the ability to collect data with IoT is now a fairly common occurrence, its benefits and applicability still need to be grounded back into real-world applications. Furthermore, it is important to consider if there are sections of our society that may benefit from these developments and if those benefits are being fully realised in a rush by large companies to achieve IoT dominance for their particular product or digital ecosystem. In this context, it is important to consider a group which, to our knowledge, has had little specific mainstream focus in the IoT area –people with disabilities. For people with disabilities, the ability for every device to interact with us and with each other has the potential to yield significant benefits. In terms of engagement, the arrival of smart appliances is already offering benefits such as the ability for a person in a wheelchair to give verbal commands to an IoT-enabled washing machine if the buttons are out of reach, or for a blind person to receive a notification on a smartphone when dinner has finished cooking in an IoT-enabled microwave. With clear benefits of IoT being identified for people with disabilities, it is important to also identify what implications there are for education. With higher education being a critical pathway for many people with disabilities in finding employment, the question as to whether such technologies can support the educational outcomes of people with disabilities was what ultimately led to this research project. This research will discuss several significant findings that have emerged from the research in relation to how consumer-based IoT can be used in the classroom to support the learning needs of students with disabilities, how industrial-based IoT sensors and actuators can be used to monitor and improve the real-time learning outcomes for the delivery of lectures and student engagement, and a proposed method for students to gain more control over their learning environment. The findings shared in this presentation are likely to have significant implications for the use of IoT in the classroom through the implementation of affordable and accessible IoT solutions and will provide guidance as to how policies can be developed as the implications of both benefits and risks continue to be considered by educators.

Keywords: disability, higher education, internet of things, students

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Aleksandar Hatzivelkos

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The term ”compromise” is mostly used casually within the social choice theory. It is usually used as a mere result of the social choice function, and this omits its deeper meaning and ramifications. This paper is based on a mathematical model for the description of a compromise as a version of the Sorites paradox. It introduces a formal definition of d-measure of divergence from a compromise and models a notion of compromise that is often used only colloquially. Such a model for vagueness phenomenon, which lies at the core of the notion of compromise enables the introduction of new mathematical structures. In order to maximize compromise, different methods can be used. In this paper, we explore properties of a social welfare function TdM (from Total d-Measure), which is defined as a function which minimizes the total sum of d-measures of divergence over all possible linear orderings. We prove that TdM satisfy strict Pareto principle and behaves well asymptotically. Furthermore, we show that for certain domain restrictions, TdM satisfy positive responsiveness and IIIA (intense independence of irrelevant alternatives) thus being equivalent to Borda count on such domain restriction. This result gives new opportunities in social choice, especially when there is an emphasis on compromise in the decision-making process.

Keywords: borda count, compromise, measure of divergence, minimization

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Authors: Samantha A. Cintron, Janet Pierce, Mihaela E. Sardiu, Diane Mahoney, Jill Peltzer, Bhanu Gupta, Qiuhua Shen

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High output heart failure (HOHF) is characterized a high output state resulting from an underlying disease process and is commonly caused by obesity. As obesity levels increase, more individuals will be at risk for obesity-related HOHF. However, the underlying pathophysiologic mechanisms of obesity-related HOHF are not well understood and need further research. The aim of the study was to describe the differences in leukocyte transcriptomes of morbidly obese patients with HOHF and those with non-HOHF. In this cross-sectional study, the study team collected blood samples, demographics, and clinical data of six patients with morbid obesity and HOHF and six patients with morbid obesity and non-HOHF. The study team isolated the peripheral blood leukocyte RNA and applied stranded total RNA sequencing. Differential gene expression was calculated, and Ingenuity Pathway Analysis software was used to interpret the canonical pathways, functional changes, upstream regulators, and mechanistic and causal networks that were associated with the significantly different leukocyte transcriptomes. The study team identified 116 differentially expressed genes; 114 were upregulated, and 2 were downregulated in the HOHF group (Benjamini-Hochberg adjusted p-value ≤ 0.05 and log2(fold-change) of ±1). The differentially expressed genes were involved with cell proliferation, mitochondrial function, erythropoiesis, erythrocyte stability, and apoptosis. The top upregulated canonical pathways associated with differentially expressed genes were autophagy, adenosine monophosphate-activated protein kinase signaling, and senescence pathways. Upstream regulator GATA Binding Protein 1 (GATA1) and a network associated with nuclear factor kappa-light chain-enhancer of activated B cells (NF-kB) were also identified based on the different leukocyte transcriptomes of morbidly obese patients with HOHF and non-HOHF. To the author’s best knowledge, this is the first study that reported the differential gene expression in patients with obesity-related HOHF and demonstrated the unique pathophysiologic mechanisms underlying the disease. Further research is needed to determine the role of cellular function and maintenance, inflammation, and iron homeostasis in obesity-related HOHF.

Keywords: cardiac output, heart failure, obesity, transcriptomics

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Authors: Mohammad Reza Dahmardeh Ghaleno, Mohammad Nohtani, Saeedeh Khaledi

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Hydrological models are applied to simulation and prediction floods in watersheds. WetSpa is a distributed, continuous and physically model with daily or hourly time step that explains of precipitation, runoff and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave Equation which depend on the slope, velocity and flow route characteristics. Garmabrood watershed located in Mazandaran province in Iran and passing over coordinates 53° 10´ 55" to 53° 38´ 20" E and 36° 06´ 45" to 36° 25´ 30"N. The area of the catchment is about 1133 km2 and elevations in the catchment range from 213 to 3136 m at the outlet, with average slope of 25.77 %. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe Model Efficiency Coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 61% and 83.17 % respectively.

Keywords: watershed simulation, WetSpa, runoff, flood prediction

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Authors: Ahmed Mateen, Zhu Qingsheng, Faisal Shahzad

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Requirement Engineering (RE) is a part being created for programming structure during the software development lifecycle. Software product line development is a new topic area within the domain of software engineering. It also plays important role in decision making and it is ultimately helpful in rising business environment for productive programming headway. Decisions are central to engineering processes and they hold them together. It is argued that better decisions will lead to better engineering. To achieve better decisions requires that they are understood in detail. In order to address the issues, companies are moving towards Software Product Line Engineering (SPLE) which helps in providing large varieties of products with minimum development effort and cost. This paper proposed a new framework for software product line and compared with other models. The results can help to understand the needs in SPL testing, by identifying points that still require additional investigation. In our future scenario, we will combine this model in a controlled environment with industrial SPL projects which will be the new horizon for SPL process management testing strategies.

Keywords: requirements engineering, software product lines, scoping, process structure, domain specific language

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Authors: Babak Kamrani, Nozar Kishi

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Stochastic catalog represents the events module of the earthquake loss estimation models. It includes series of events with different magnitudes and corresponding frequencies/probabilities. For the development of the stochastic catalog, random or uniform sampling methods are used to sample the events from the seismicity model. For covering all the Magnitude Frequency Distribution (MFD), a huge number of events should be generated for the above-mentioned methods. Characteristic Event (CE) method chooses the events based on the interest of the insurance industry. We divide the MFD of each source into bins. We have chosen the bins based on the probability of the interest by the insurance industry. First, we have collected the information for the available seismic sources. Sources are divided into Fault sources, subduction, and events without specific fault source. We have developed the MFD for each of the individual and areal source based on the seismicity of the sources. Afterward, we have calculated the CE magnitudes based on the desired probability. To develop the stochastic catalog, we have introduced uncertainty to the location of the events too.

Keywords: stochastic catalogue, earthquake loss, uncertainty, characteristic event

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Authors: Mustafa Kaya

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In this study, the effect of pre-stressed strand diameters, providing the beam-to-column connections, was investigated from both experimental, and analytical aspects. In the experimental studies, the strength, stiffness, and energy dissipation capacities of the precast specimens comprising two pre-stressed strand samples of 12.70 mm, and 15.24 mm diameters, were compared with the reference specimen. The precast specimen with strands of 15.24 mm reached 96% of the maximum strength of the reference specimen; the amount of energy dissipated by this specimen until end of the test reached 48% of the amount of energy dissipated by the reference sample, and the stiffness of the same specimen at a 1.5% drift of reached 77% of the stiffness of the reference specimen at this drift. Parallel results were obtained during the analytical studies from the aspects of strength, and behavior, but the initial stiffness of the analytical models was lower than that of the test specimen.

Keywords: precast beam to column connection, moment resisting connection, post tensioned connections, finite element method

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Authors: William Kelly, Sorelle Veigne, Xianhua Li, Zuyi Huang, Shyamsundar Subramanian, Eugene Schaefer

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The ambr15™ bioreactor is a single-use microbioreactor for cell line development and process optimization. The ambr system offers fully automatic liquid handling with the possibility of fed-batch operation and automatic control of pH and oxygen delivery. With operating conditions for large scale biopharmaceutical production properly scaled down, micro bioreactors such as the ambr15™ can potentially be used to predict the effect of process changes such as modified media or different cell lines. In this study, gassing rates and dilution rates were varied for a semi-continuous cell culture system in the ambr15™ bioreactor. The corresponding changes to metabolite production and consumption, as well as cell growth rate and therapeutic protein production were measured. Conditions were identified in the ambr15™ bioreactor that produced metabolic shifts and specific metabolic and protein production rates also seen in the corresponding larger (5 liter) scale perfusion process. A Dynamic Flux Balance model was employed to understand and predict the metabolic changes observed. The DFB model-predicted trends observed experimentally, including lower specific glucose consumption when CO₂ was maintained at higher levels (i.e. 100 mm Hg) in the broth. A Computational Fluid Dynamic (CFD) model of the ambr15™ was also developed, to understand transfer of O₂ and CO₂ to the liquid. This CFD model predicted gas-liquid flow in the bioreactor using the ANSYS software. The two-phase flow equations were solved via an Eulerian method, with population balance equations tracking the size of the gas bubbles resulting from breakage and coalescence. Reasonable results were obtained in that the Carbon Dioxide mass transfer coefficient (kLa) and the air hold up increased with higher gas flow rate. Volume-averaged kLa values at 500 RPM increased as the gas flow rate was doubled and matched experimentally determined values. These results form a solid basis for optimizing the ambr15™, using both CFD and FBA modelling approaches together, for use in microscale simulations of larger scale cell culture processes.

Keywords: cell culture, computational fluid dynamics, dynamic flux balance analysis, microbioreactor

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Authors: Mohanad Al-Behadili, Djamila Ouelhadj

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In this paper, a specific type of vehicle routing problem under stochastic demand (SVRP) is considered. This problem is of great importance because it models for many of the real world vehicle routing applications. This paper used a robust optimisation model to solve the problem along with the novel Simulation-Particle Swarm Optimisation (Sim-PSO) approach. The proposed Sim-PSO approach is based on the hybridization of the Monte Carlo simulation technique with the PSO algorithm. A comparative study between the proposed model and the Sim-PSO approach against other solution methods in the literature has been given in this paper. This comparison including the Analysis of Variance (ANOVA) to show the ability of the model and solution method in solving the complicated SVRP. The experimental results show that the proposed model and Sim-PSO approach has a significant impact on the obtained solution by providing better quality solutions comparing with well-known algorithms in the literature.

Keywords: stochastic vehicle routing problem, robust optimisation model, Monte Carlo simulation, particle swarm optimisation

Procedia PDF Downloads 273