Search results for: demand and lead time randomness

Authors: Yehuda Roth

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In quantum theory, a system’s time evolution is predictable unless an observer performs measurement, as the measurement process can randomize the system. This randomness appears when the measuring device does not accurately describe the measured item, i.e., when the states characterizing the measuring device appear as a superposition of those being measured. When such a mismatch occurs, the measured data randomly collapse into a single eigenstate of the measuring device. This scenario resembles the interpretation process in which the observer does not experience an objective reality but interprets it based on preliminary descriptions initially ingrained into his/her mind. This distinction is the motivation for the present study in which the collapse scenario is regarded as part of the interpretation process of the observer. By adopting the formalism of the quantum theory, we present a complete mathematical approach that describes the interpretation process. We demonstrate this process by applying the proposed interpretation formalism to the ambiguous image "My wife and mother-in-law" to identify whether a woman in the picture is young or old.

Keywords: quantum-like interpretation, ambiguous image, determination, quantum-like collapse, classified representation

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Authors: Jungyeol Hong, Dongjoo Park

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The primary purpose of this study is to develop a methodological framework to predict daily subway ridership at a station-level and to examine the association between subway ridership and bus demand incorporating commercial business facility in the vicinity of each subway station. The socio-economic characteristics, land-use, and built environment as factors may have an impact on subway ridership. However, it should be considered not only the endogenous relationship between bus and subway demand but also the characteristics of commercial business within a subway station’s sphere of influence, and integrated transit network topology. Regarding a statistical approach to estimate subway ridership at a station level, therefore it should be considered endogeneity and heteroscedastic issues which might have in the subway ridership prediction model. This study focused on both discovering the impacts of bus demand, commercial business characteristics, and network topology on subway ridership and developing more precise subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers entire Seoul city in South Korea and includes 243 stations with the temporal scope set at twenty-four hours with one-hour interval time panels each. The data for subway and bus ridership was collected Seoul Smart Card data from 2015 and 2016. Three-Stage Least Square(3SLS) approach was applied to develop daily subway ridership model as capturing the endogeneity and heteroscedasticity between bus and subway demand. Independent variables incorporating in the modeling process were commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. As a result, it was found that bus ridership and subway ridership were endogenous each other and they had a significantly positive sign of coefficients which means one transit mode could increase another transportation mode’s ridership. In other words, two transit modes of subway and bus have a mutual relationship instead of the competitive relationship. The commercial business characteristics are the most critical dimension among the independent variables. The variables of commercial business facility rate in the paper containing six types; medical, educational, recreational, financial, food service, and shopping. From the model result, a higher rate in medical, financial buildings, shopping, and food service facility lead to increment of subway ridership at a station, while recreational and educational facility shows lower subway ridership. The complex network theory was applied for estimating integrated network topology measures that cover the entire Seoul transit network system, and a framework for seeking an impact on subway ridership. The centrality measures were found to be significant and showed a positive sign indicating higher centrality led to more subway ridership at a station level. The results of model accuracy tests by out of samples provided that 3SLS model has less mean square error rather than OLS and showed the methodological approach for the 3SLS model was plausible to estimate more accurate subway ridership. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT (2017R1C1B2010175).

Keywords: subway ridership, bus ridership, commercial business characteristic, endogeneity, network topology

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Authors: K. Menad, A. Feddag, M. A. Hassnaoui

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We are living in a time and in a world heavily polluted. In the list of the great dangers awaiting the man can be placed on top of the list pollution by heavy metals: lead, mercury, cadmium, etc. Fatigue, Depression, Thyroid disorder, Alzheimer's, Parkinson's, Cancer, are some of the health problems caused by heavy metal pollution. The environmental protection has long since become a major political and economic issue. Among the priorities, include safeguarding water resources. All countries of the world are concerned either because they lack water or because they pollute it. There are several ways to remove these heavy metals; ion exchange by zeolites is one of these ways, which our work is based on. Zeolites were among the main clean up materials by either adsorption, ion exchange and catalysis. Lead and cadmium, heavy metals, is one of the main dangers fulminate the flora and fauna of our small planet, so many resources are deployed to remedy them. The elimination of lead and cadmium by ion exchange has been extensively studied. However, exchange capacity of more and larger formed a major challenge for researchers and industry.

Keywords: composite, ion excahnge, zeolite LTA, zeolite x

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Authors: Chongtham Jiten, K. Chandramani Singh, Radhapiyari Laishram

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Nanocrystalline powders of the lead-free piezoelectric material, tantalum-substituted potassium sodium niobate (K0.5Na0.5)(Nb0.9Ta0.1)O3 (KNNT), were produced using a Retsch PM100 planetary ball mill by setting the milling time to 15h, 20h, 25h, 30h, 35h and 40h, at a fixed speed of 250rpm. The average particle size of the milled powders was found to decrease from 12nm to 3nm as the milling time increases from 15h to 25h, which is in agreement with the existing theoretical model. An anomalous increase to 98nm and then a drop to 3nm in the particle size were observed as the milling time further increases to 30h and 40h respectively. Various sizes of these starting KNNT powders were used to investigate the effect of milling time on the microstructure, dielectric properties, phase transitions and piezoelectric properties of the resulting KNNT ceramics. The particle size of starting KNNT was somewhat proportional to the grain size. As the milling time increases from 15h to 25h, the resulting ceramics exhibit enhancement in the values of relative density from 94.8% to 95.8%, room temperature dielectric constant (εRT) from 878 to 1213, and piezoelectric charge coefficient (d33) from 108pC/N to 128pC/N. For this range of ceramic samples, grain size refinement suppresses the maximum dielectric constant (εmax), shifts the Curie temperature (Tc) to a lower temperature and the orthorhombic-tetragonal phase transition (Tot) to a higher temperature. Further increase of milling time from 25h to 40h produces a gradual degradation in the values of relative density, εRT, and d33 of the resulting ceramics.

Keywords: perovskite, dielectric, ceramics, high-energy milling

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Authors: Ashenafi Sileshi Etefa, Bezawit Worku Yenealem

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Micro-insurance is a relatively new concept that is just being introduced in Ethiopia. For an agrarian economy dominated by small holder farming and vulnerable to natural disasters, mainly drought, the need for an Index-Based Micro Insurance (IBMI) is crucial. Since IBMI solves moral hazard, adverse selection, and access issues to poor clients, it is preferable over traditional insurance products. IBMI is being piloted in drought prone areas of Ethiopia with the aim of learning and expanding the service across the country. This article analyses the demand of IBMI and the barriers to demand and finds that the demand for IBMI has so far been constrained by lack of awareness, trust issues, costliness, and the level of basis risk; and recommends reducing the basis risk and increasing the role of government and farmer cooperatives.

Keywords: agriculture, index based micro-insurance (IBMI), drought, micro-finance institution (MFI)

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Authors: Shabnam Najafi, Metin Turkay

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Network design problem (NDP) is used to determine the set of optimal values for certain pre-specified decision variables such as capacity expansion of nodes and links by optimizing various system performance measures including safety, congestion, and accessibility. The designed transportation network should improve objective functions defined for the system by considering the route choice behaviors of network users at the same time. The NDP studies mostly investigated the random demand and route selection constraints separately due to computational challenges. In this work, we consider both random demand and route selection constraints simultaneously. This work presents a nonlinear stochastic model for land use and road network design problem to address the development of different functional zones in urban areas by considering both cost function and air pollution. This model minimizes cost function and air pollution simultaneously with random demand and stochastic route selection constraint that aims to optimize network performance via road capacity expansion. The Bureau of Public Roads (BPR) link impedance function is used to determine the travel time function in each link. We consider a city with origin and destination nodes which can be residential or employment or both. There are set of existing paths between origin-destination (O-D) pairs. Case of increasing employed population is analyzed to determine amount of roads and origin zones simultaneously. Minimizing travel and expansion cost of routes and origin zones in one side and minimizing CO emission in the other side is considered in this analysis at the same time. In this work demand between O-D pairs is random and also the network flow pattern is subject to stochastic user equilibrium, specifically logit route choice model. Considering both demand and route choice, random is more applicable to design urban network programs. Epsilon-constraint is one of the methods to solve both linear and nonlinear multi-objective problems. In this work epsilon-constraint method is used to solve the problem. The problem was solved by keeping first objective (cost function) as the objective function of the problem and second objective as a constraint that should be less than an epsilon, where epsilon is an upper bound of the emission function. The value of epsilon should change from the worst to the best value of the emission function to generate the family of solutions representing Pareto set. A numerical example with 2 origin zones and 2 destination zones and 7 links is solved by GAMS and the set of Pareto points is obtained. There are 15 efficient solutions. According to these solutions as cost function value increases, emission function value decreases and vice versa.

Keywords: epsilon-constraint, multi-objective, network design, stochastic

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Authors: Lydia Andrade, Kumar M. R. Bhat

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Heavy metals, especially lead, is considered to be a multi-organ toxicant. However, such heavy metals, are used in the preparation of traditional medicines. Nagabhasma is one of the traditional medicines. Lead is the metal used in its preparation. Lead is converted into a health beneficial, organometallic compound, when subjected to various traditional methods of purification. Therefore, this study is designed to evaluate the effect of such processed lead in various stages of traditionally prepared Nagabhasma on the histological structure of kidneys. Using the human equivalent doses of Nagabhasma, various stages of its preparation were fed orally for 30 days and 60 days (short term and long term). The treated and untreated rats were then sacrificed for the collection of kidneys. The kidneys were processed for histopathological study. The results show severe changes in the histological structure of kidneys. The animals treated with lead acetate showed changes in the epithelial cells lining the bowman’s capsule. The proximal and distal convoluted tubules were dilated leading to atrophy of their epithelial cells. The amount of inflammatory infiltrates was more in this group. A few groups also showed pockets of inter-tubular hemorrhage. These changes, however, were minimized as the stages progressed form stages 1 to 4 of Nagabhasma preparation. Therefore, it is necessary to stringently monitor the processing of lead acetate during the preparation of Nagabhasma.

Keywords: heavy metals, kidneys, lead acetate, Nagabhasma

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Authors: Josip Visković, Ana Rimac Smiljanić, Ines Ivić

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Housing loans play an important role in CEE countries’ economies. This fact is based on their share in total loans to households and their importance for economic activity and growth in CEE countries. Therefore, it is important to find out key determinants of housing loans demand in these countries. The aim of this study is to research and analyze the determinants of the demand for housing loans in Croatia. In this regard, the effect of economic activity, loan terms and real estate prices were analyzed. Also, the aim of this study is to find out what motivates people to take housing loans. Therefore, primarily empirical study was conducted among the Croatian residents. The results show that demand for housing loans is positively affected by economic growth, higher personal income and flexible loan terms, while it is negatively affected by interest rate rise.

Keywords: CEE countries, Croatia, demand determinants, housing loans

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Authors: Jacky Hau

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The prevalence of emerging technologies disrupts various industries as well as consumer behavior. Data collection has been in the fingertip and inherited through enabled Internet-of-things (IOT) devices. Big data analytics (BDA) becomes possible and allows real-time demand network management (DNM) through leagile supply chain. To enhance further on its resilience and predictability, governance is going to be examined to promote supply chain transparency and trust in an efficient manner. Leagility combines lean thinking and agile techniques in supply chain management. It aims at reducing costs and waste, as well as maintaining responsiveness to any volatile consumer demand by means of adjusting the decoupling point where the product flow changes from push to pull. Leagility would only be successful when collaborative planning, forecasting, and replenishment (CPFR) process or alike is in place throughout the supply chain business entities. Governance and procurement of the supply chain, however, is crucial and challenging for the execution of CPFR as every entity has to walk-the-talk generously for the sake of overall benefits of supply chain performance, not to mention the complexity of exercising the polices at both of within across various supply chain business entities on account of organizational behavior and mutual trust. Empirical survey results showed that the effective timespan on demand forecasting had been drastically shortening in the magnitude of months to weeks planning horizon, thus agility shall come first and preferably following by lean approach in a timely manner.

Keywords: governance, leagility, procure-to-pay, source-to-contract

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Authors: Lei Zhao, Zhe Yuan, Wenyue Kuang

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This paper studies two-warehouse inventory models for a deteriorating item considering that the demand is influenced by inventory levels. The problem mainly focuses on the optimal order policy and the optimal order cycle with inventory-level-dependent demand in two-warehouse system for retailers. It considers the different deterioration rates and the inventory holding costs in owned warehouse (OW) and rented warehouse (RW), and the conditions of transportation cost, allowed shortage and partial backlogging. Two inventory models are formulated: last-in first-out (LIFO) model and first-in-first-out (FIFO) model based on the policy choices of LIFO and FIFO, and a comparative analysis of LIFO model and FIFO model is made. The study finds that the FIFO policy is more in line with realistic operating conditions. Especially when the inventory holding cost of OW is high, and there is no difference or big difference between deterioration rates of OW and RW, the FIFO policy has better applicability. Meanwhile, this paper considers the differences between the effects of warehouse and shelf inventory levels on demand, and then builds retailers’ inventory decision model and studies the factors of the optimal order quantity, the optimal order cycle and the average inventory cost per unit time. To minimize the average total cost, the optimal dispatching policies are provided for retailers’ decisions.

Keywords: FIFO model, inventory-level-dependent, LIFO model, two-warehouse inventory

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Authors: Khalid Elbadawi Elshafea, Mahmoud Hassan Onsa

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This paper presents the results of the experiments to measure the impact of pasteurization cows dung on important parameter of anaerobic digestion (retention time) and measure the effect in daily production rate of biogas, were used local materials in these experiments, two experiments were carried out in two bio-digesters (1 and 2) (18.0 L), volume of the mixture 16.0-litre and the mass of dry matter in the mixture 4.0 Kg of cow dung. Pasteurization process has been conducted on the mixture into the digester 2, and put two digesters under room temperature. Digester (1) produced 268.5 liter of methane in period of 49 days with daily methane production rate 1.37L/Kg/day, and digester (2) produced 302.7-liter of methane in period of 26 days with daily methane production rate 2.91 L/Kg/day. This study concluded that the use of system pasteurization cows dung speed up hydrolysis in anaerobic process, because heat to certain temperature in certain time lead to speed up chemical reactions (transfer Protein to Amino acids, Carbohydrate to Sugars and Fat to Long chain fatty acids), this lead to reduce the retention time an therefore increase the daily methane production rate with 212%.

Keywords: methane, cow dung, daily production, pasteurization, increase

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Authors: B. A. Adeniyi, S. A. Daud, O. Amao

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The study investigates consumer demand for meat products in Oyo West Local Government using linear approximate almost ideal demand system (LA/AIDS). Questions that were addressed by the study include: first, what is the type and quantity of meat products available to the household and their demand pattern? Second is the investigation of the factors that affect meat products demand pattern and proportion of income that is spent on them. For the above purpose cross-sectional data were collected from 156 households of the study area and analyzed to reveal the functional relationship between meat products consumption and some socio-economic variables of the household. Results indicated that per capita meat consumption increased as household income and education increased but decreased with age. It was also found that male tend to consume more meat products than their female counterparts and that increase in household size will first increased per caput meat consumption but later decreased it. Price also tends to greatly influence the demand pattern of meat products. The results of elasticity computed from the results of regression analysis revealed that own price elasticity for all meat products were negative which indicated that they were normal products while cross and expenditure elasticity were positive which further confirmed that meat products were normal and substitute products. This study therefore concludes that the relevance of these variables imposed a great challenge to the policy makers and the government, in the sense that more cost effective methods of meat production technology have to be devised in other to make consumption of meat products more affordable.

Keywords: meat products, consumption, animal production, technology

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Authors: Kalyani Mer

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Hydrogen peroxide (H₂O₂) is one of the most efficient and commonly used oxidants in in-situ chemical oxidation (ISCO) of organic contaminants. In the present study, we investigated the activation of H₂O₂ by heavy metal (nickel and lead metal ions) loaded biochar for phenol degradation in an aqueous solution (concentration = 100 mg/L). It was found that H₂O₂ can be effectively activated by biochar, which produces hydroxyl (•OH) radicals owing to an increase in the formation of persistent free radicals (PFRs) on biochar surface. Ultrasound treated (30s duration) biochar, chemically activated by 30% phosphoric acid and functionalized by diethanolamine (DEA) was used for the adsorption of heavy metal ions from aqueous solutions. It was found that modified biochar could remove almost 60% of nickel in eight hours; however, for lead, the removal efficiency reached up to 95% for the same time duration. The heavy metal loaded biochar was further used for the degradation of phenol in the absence and presence of H₂O₂ (20 mM), within 4 hours of reaction time. The removal efficiency values for phenol in the presence of H₂O₂ were 80.3% and 61.9%, respectively, by modified biochar loaded with nickel and lead metal ions. These results suggested that the biochar loaded with nickel exhibits a better removal capacity towards phenol than the lead loaded biochar when used in H₂O₂ based oxidation systems. Meanwhile, control experiments were set in the absence of any activating biochar, and the removal efficiency was found to be 19.1% when only H₂O₂ was added in the reaction solution. Overall, the proposed approach serves a dual purpose of using biochar for heavy metal ion removal and treatment of organic contaminants by further using the metal loaded biochar for H₂O₂ activation in ISCO processes.

Keywords: biochar, ultrasound, heavy metals, in-situ chemical oxidation, chemical activation

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Authors: Parisa Bagheri Tookanlou

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In this paper, we analyze a product line design problem faced by a manufacturing firm where the product line consists of a customized product in addition to a standard product and is offered in a market in which customers are heterogeneous on aesthetic attributes of the product. The customization level of a product is defined by the fraction of aesthetic attributes of the product that the manufacturer chooses to customize. In contrast to the existing literature on product line design that predominantly assumes deterministic demand, we consider the presence of demand uncertainty and frame the product line design problem in a single period (news vendor) setting. We examine the effect of demand uncertainty on product line decisions. Furthermore, we also examine how product line decisions are influenced by channel structure. While we use the centralized channel as a benchmark, we consider the decentralized dual channel where the customized product is sold through an online channel owned by the manufacturer and the standard product is sold through a retailer. We introduce a supply contract between the manufacturer and the retailer for improving channel efficiency and coordinate the distribution channel.

Keywords: product line design, demand uncertainty, customization level, distribution channel

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Authors: Evangelos Kaisar, Anika Tabassum, Taraneh Ardalan, Majed Al-Ghandour

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The economy of any country is dependent on its ability to accommodate the movement and delivery of goods. The demand for goods movement and services increases truck traffic on highways and inside the cities. The livability of most cities is directly affected by the congestion and environmental impacts of trucks, which are the backbone of the urban freight system. Better operation of heavy vehicles on highways and arterials could lead to the network’s efficiency and reliability. In many cases, roundabouts can respond better than at-level intersections to enable traffic operations with increased safety for both cars and heavy vehicles. Recently emerged, the concept of turbo-roundabout is a viable alternative to the two-lane roundabout aiming to improve traffic efficiency. The primary objective of this study is to evaluate the operation and performance level of an at-grade intersection, a conventional two-lane roundabout, and a basic turbo roundabout for freight movements. To analyze and evaluate the performances of the signalized intersections and the roundabouts, micro simulation models were developed PTV VISSIM. The networks chosen for this analysis in this study are to experiment and evaluate changes in the performance of the movement of vehicles with different geometric and flow scenarios. There are several scenarios that were examined when attempting to assess the impacts of various geometric designs on vehicle movements. The overall traffic efficiency depends on the geometric layout of the intersections, which consists of traffic congestion rate, hourly volume, frequency of heavy vehicles, type of road, and the ratio of major-street versus side-street traffic. The traffic performance was determined by evaluating the delay time, number of stops, and queue length of each intersection for varying truck percentages. The results indicate that turbo-roundabouts can replace signalized intersections and two-lane roundabouts only when the traffic demand is low, even with high truck volume. More specifically, it is clear that two-lane roundabouts are seen to have shorter queue lengths compared to signalized intersections and turbo-roundabouts. For instance, considering the scenario where the volume is highest, and the truck movement and left turn movement are maximum, the signalized intersection has 3 times, and the turbo-roundabout has 5 times longer queue length than a two-lane roundabout in major roads. Similarly, on minor roads, signalized intersections and turbo-roundabouts have 11 times longer queue lengths than two-lane roundabouts for the same scenario. As explained from all the developed scenarios, while the traffic demand lowers, the queue lengths of turbo-roundabouts shorten. This proves that turbo roundabouts perform well for low and medium traffic demand. The results indicate that turbo-roundabouts can replace signalized intersections and two-lane roundabouts only when the traffic demand is low, even with high truck volume. Finally, this study provides recommendations on the conditions under which different intersections perform better than each other.

Keywords: At-grade intersection, simulation, turbo-roundabout, two-lane roundabout

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Authors: Yu-Chun Lin

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This study examines whether the adoption of clawback provisions increases the demand for audit service. We use abnormal audit fees to proxy for the demand for audit service. Because firms’ voluntary adoption of the clawback provisions is endogenously determined, this study controls for this bias using the propensity-score matching technique. Based on 1,247 U.S. firms that voluntarily adopt clawback provisions during 2003-2013 and a matched sample, the empirical results show that clawback provisions adoption is associated with abnormal audit fees, especially by firms with higher likelihood of misstatements. When firm executives are overconfident, abnormal audit fees increase subsequent to clawback provisions adoption. Since regulators require listed firms to adopt recoupment policy after 2015 in U.S., the evidence about higher demand for audit service might provide political implications for mandatory clawback provisions.

Keywords: clawback provisions, audit service, audit fees, overconfidence

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Authors: M. Gil, R. Montalvo

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Business Intelligence (BI) has become a major source of competitive advantages for firms around the world. BI has been defined as the process of data visualization and reporting for understanding what happened and what is happening. Moreover, BI has been studied for its predictive capabilities in the context of trade and financial transactions. The current literature has identified that BI permits managers to identify market trends, understand customer relations, and predict demand for their products and services. This last capability of BI has been of special concern to academics. Specifically, due to its power to build predictive models adaptable to specific time horizons and geographical regions. However, the current literature of BI focuses on predicting specific markets and industries because the impact of such predictive models was relevant to specific industries or organizations. Currently, the existing literature has not developed a predictive model of BI that takes into consideration the whole economy of a geographical area. This paper seeks to create a predictive model of BI that would show the bigger picture of a geographical area. This paper uses a data set from the Secretary of Economic Development of the state of Jalisco, Mexico. Such data set includes data from all the commercial transactions that occurred in the state in the last years. By analyzing such data set, it will be possible to generate a BI model that predicts supply and demand from specific industries around the state of Jalisco. This research has at least three contributions. Firstly, a methodological contribution to the BI literature by generating the predictive supply and demand model. Secondly, a theoretical contribution to BI current understanding. The model presented in this paper incorporates the whole picture of the economic field instead of focusing on a specific industry. Lastly, a practical contribution might be relevant to local governments that seek to improve their economic performance by implementing BI in their policy planning.

Keywords: business intelligence, predictive model, supply and demand, Mexico

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Authors: Comfort Adeoye, Anthony Eneji

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Lead pollution by mining, industrial dumping, and other anthropogenic uses are corroding the environment. Efforts being made to control it include physical, chemical and biological methods. The failure of the aforementioned methods are largely due to the fact that they are cumbersome, expensive, and not eco-friendly. Some plant species can be used for remediation of these pollutants. The objective of this work is to investigate the abilities of two native weed species to remediate two lead-polluted soils: a) Battery dumpsite and, (b) Naturally occurring lead mine. Soil samples were taken from the two sites: a) Kumapayi in Ibadan, a battery dumpsite, (b) Zamfara, a natural lead mine. Screen house experiment in Complete Randomized Design (CRD) replicated three times was carried out at I.I.T.A. Unpolluted soils were collected and polluted with various rates of lead concentrations of 0, 0.1, 0.2, and 0.5%. These were planted with weed species. Plant growth parameters were monitored for twelve weeks, after which the plants were harvested. Dry weight and plant uptake of the lead were taken. Analysis of data was carried out using, Genstat, Excel and descriptive statistics. Relative concentration of lead (Pb) in the above and below ground parts of Gomphrena celusoides revealed that a higher amount of Pb is taken up in the root compared with the shoots at different levels of Pb pollution. However, lead uptake at 0.5% > 0.2% > 0.1% > Control. In essence, phytoremediation of Gomphrena is highest at soil pollution of 0.5% and its retention is greater in the root than the shoot.In S. pyramidalis, soil retention ranges from 0.1% > 0.5% > 0.2% > control. Uptake is highest at 0.5% > 0.1% > 0.2 in stem. Uptake in leaves is highest at 0.2%, but none in the 0.5% pollution. Therefore, different plant species exhibited different accumulative mode probably due to their physiological and rooting systems. Gomphrena spp. rooting system is tap root,while that of S.pyramidalis is fibrous.

Keywords: grass, lead, phytoremediation, pollution

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Authors: Y. Ghiassi-Farrokhfal

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The number of electric vehicles (EVs) is increasing worldwide. Replacing gas fueled cars with EVs reduces carbon emission. However, the extensive energy consumption of EVs stresses the energy systems, requiring non-green sources of energy (such as gas turbines) to compensate for the new energy demand caused by EVs in the energy systems. To make EVs even a greener solution for the future energy systems, new EV charging stations are equipped with solar PV panels and batteries. This will help serve the energy demand of EVs through the green energy of solar panels. To ensure energy availability, solar panels are combined with batteries. The energy surplus at any point is stored in batteries and is used when there is not enough solar energy to serve the demand. While EV charging stations equipped with solar panels and batteries are green and ecologically optimal, they might not be financially viable solutions, due to battery prices. To make the system viable, we should size the battery economically and operate the system optimally. This is, in general, a challenging problem because of the stochastic nature of the EV arrivals at the charging station, the available solar energy, and the battery operating system. In this work, we provide a mathematical model for this problem and we compute the return on investment (ROI) of such a system, which is designed to be ecologically and financially optimal. We also quantify the minimum required investment in terms of battery and solar panels along with the operating strategy to ensure that a charging station has enough energy to serve its EV demand at any time.

Keywords: solar energy, battery storage, electric vehicle, charging stations

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Authors: Riccardo Patriarca, Giulio Di Gravio, Francesco Costantino, Massimo Tronci

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An accurate inventory management policy acquires a crucial role in the several high-availability sectors. In these sectors, due to the high-cost of spares and backorders, an (S-1, S) replenishment policy is necessary for high-availability items. The policy enables the shipment of a substitute efficient item anytime the inventory size decreases by one. This policy can be modelled following the Multi-Echelon Technique for Recoverable Item Control (METRIC). The METRIC is a system-based technique that allows defining the optimum stock level in a multi-echelon network, adopting measures in line with the decision-maker’s perspective. The METRIC defines an availability-cost function with inventory costs and required service levels, using as inputs data about the demand trend, the supplying and maintenance characteristics of the network and the budget/availability constraints. The traditional METRIC relies on the hypothesis that a Poisson distribution well represents the demand distribution in case of items with a low failure rate. However, in this research, we will explore the effects of using a Poisson distribution to model the demand of low failure rate items characterized by an irregular demand trend. This characteristic of a demand is not included in the traditional METRIC formulation leading to the need of revising its traditional formulation. Using the CV (Coefficient of Variation) and ADI (Average inter-Demand Interval) classification, we will define the inherent flaws of Poisson-based METRIC for irregular demand items, defining an innovative ad hoc distribution which can better fit the irregular demands. This distribution will allow defining proper stock levels to reduce stocking and backorder costs due to the high irregularities in the demand trend. A case study in the aviation domain will clarify the benefits of this innovative METRIC approach.

Keywords: METRIC, inventory management, irregular demand, spare parts

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Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

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Authors: Esmeralda Hysenbelliu

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Over the last years, the demand for high bandwidth services, such as live (IPTV Service) and on-demand video streaming, steadily and rapidly increased. It has been predicted that video traffic (IPTV, VoD, and WEB TV) will account more than 90% of global Internet Protocol traffic that will cross the globe in 2016. Consequently, the importance and consideration on requirements and challenges of service providers faced today in supporting user’s requests for entertainment video across the various IPTV services through virtualization over Software Defined Networks (SDN), is tremendous in the highest stage of attention. What is necessarily required, is to deliver optimized live and on-demand services like Internet Protocol Service (IPTV Service) with low cost and good quality by strictly fulfill the essential requirements of Clients and ISP’s (Internet Service Provider’s) in the same time. The aim of this study is to present an overview of the important requirements and challenges of IPTV service with two network trends on solving challenges through virtualization (SDN and Network Function Virtualization). This paper provides an overview of researches published in the last five years.

Keywords: challenges, IPTV service, requirements, software defined networking (SDN)

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Authors: Rakesh Namdeti

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The liquid waste-wastewater- is essentially the water supply of the community after it has been used in a variety of applications. In recent years, heavy metal concentrations, besides other pollutants, have increased to reach dangerous levels for the living environment in many regions. Among the heavy metals, Lead has the most damaging effects on human health. It can enter the human body through the uptake of food (65%), water (20%), and air (15%). In this background, certain low-cost and easily available biosorbent was used and reported in this study. The scope of the present study is to remove Lead from its aqueous solution using Olea EuropaeaResin as biosorbent. The results showed that the biosorption capacity of Olea EuropaeaResin biosorbent was more for Lead removal. The Langmuir, Freundlich, Tempkin, and Dubinin-Radushkevich (D-R) models were used to describe the biosorption equilibrium of Lead Olea EuropaeaResin biosorbent, and the biosorption followed the Langmuir isotherm. The kinetic models showed that the pseudo-second-order rate expression was found to represent well the biosorption data for the biosorbent.

Keywords: novel biosorbent, central composite design, Lead, isotherms, kinetics

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Authors: A. Beril Tugrul

Abstract:

Demand on production and thereby the global need of energy is growing continuously. Each country has different trends on energy demand and supply according to their geopolitical and geographical locations, underground reserves, weather conditions and level of industrialization. Conventional energy resources such as oil, gas and coal –in other words fossil resources- remain dominant on primary energy supply in spite of causing of environmental problems. Energy supply and demand securities are essential within the energy importing and exporting countries. This concept affected all sectors, but especially impressed on political aspects of the countries and also global economic views.

Keywords: energy policy, energy economics, energy strategy, global trends, petro-dollar recycling

Procedia PDF Downloads 468

Authors: A. K. Paul, Vinod Kumar

Abstract:

Lead free magnetoelectric (ME) nanoparticulate (1−x) BNT-BKT-BMgT−x CFO (x = 0, 0.1, 0.2, 0.3) composite films were synthesized using chemical solution deposition method. The X-ray diffraction and transmission electron microscope (TEM) reveal that CFO nanoparticles were well distributed in the matrix of BNT-BKT-BMgT. The nanocomposite films exhibit both good magnetic and ferroelectric properties at room temperature (R-T). It is concluded that the modulation in compositions of piezomagnetic/piezoelectric components plays a fundamental role in the magnetoelectric coupling in these nanoparticulate composite films. These ME composites provide a great opportunity as potential lead-free systems for ME devices.

Keywords: lead free multiferroic, nanocomposite, ferroelectric, ferromagnetic and magneto-electric properties

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Authors: A. Benhadji, M. Taleb Ahmed

Abstract:

Among the various methods of treatment, advanced oxidation processes (AOP) are the most promising ones. In this study, Peroxi Electrocoagulation Process (PEP) was investigated for the treatment of detergent wastewater. The process was compared with electrooxidation treatment. The results showed that chemical oxygen demand (COD) was high 7584 mgO₂.L^-1, while the biochemical oxygen demand was low (250 mgO₂.L^-1). This wastewater was hardly biodegradable. Electrochemical process was carried out for the removal of detergent using a glass reactor with a volume of 1 L and fitted with three electrodes. A direct current (DC) supply was used. Samples were taken at various current density (0.0227 A/cm² to 0.0378 A/cm²) and reaction time (1-2-3-4 and 5 hour). Finally, the COD was determined. The results indicated that COD removal efficiency of PEP was observed to increase with current intensity and reached to 77% after 5 h. The highest removal efficiency was observed after 5 h of treatment.

Keywords: AOP, COD, detergent, PEP, wastewater

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Authors: Sahar Sohrabi

Abstract:

The emergence of Cloud data centers has revolutionized the IT industry. Private Clouds in specific provide Cloud services for certain group of customers/businesses. In a real-time private Cloud each task that is given to the system has a deadline that desirably should not be violated. Scheduling tasks in a real-time private CLoud determine the way available resources in the system are shared among incoming tasks. The aim of the scheduling policy is to optimize the system outcome which for a real-time private Cloud can include: energy consumption, deadline violation, execution time and the number of host switches. Different scheduling policies can be used for scheduling. Each lead to a sub-optimal outcome in a certain settings of the system. A Bayesian Scheduling strategy is proposed for scheduling to further improve the system outcome. The Bayesian strategy showed to outperform all selected policies. It also has the flexibility in dealing with complex pattern of incoming task and has the ability to adapt.

Keywords: cloud computing, scheduling, real-time private cloud, bayesian

Procedia PDF Downloads 350

Authors: Chadel Meriem, Bensmaine Souhila, Chadel Asma, Bouchikhi Chaima

Abstract:

The Methylammonium Lead Iodide CH3NH3PbI3 is used in solar cell as an absorber layer since 2009. The efficiencies of these technologies have increased from 3.8% in 2009 to 29.15% in 2019. So, these technologies Methylammonium Lead Iodide is promising for the development of high-performance photovoltaic applications. Due to the high cost of the experimental of the solar cells, researchers have turned to other methods like numerical simulation. In this work, we evaluate and simulate the performance of a CH₃NH₃PbI₃ lead-based perovskite solar cell when the amount of materials of absorber layer is reduced. We show that the reducing of thickness the absorber layer influent on performance of the solar cell. For this study, the one-dimensional simulation program, SCAPS-1D, is used to investigate and analyze the performance of the perovskite solar cell. After optimization, maximum conversion efficiency was achieved with 300 nm in absorber layer.

Keywords: methylammonium lead Iodide, perovskite solar cell, caracteristic J-V, effeciency

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Authors: Mansouri Ouarda, Adbdennour Cherif, Boukarma Ziad

Abstract:

Environmental and biological monitoring are used for the evaluation of exposure to industrial chemicals, and provide a tool for assessing workers’ exposure to chemicals. The organs or tissues where the first biological effects can be observed with increasing amounts of lead toxicity. This study aims at evaluating the effect of the metal element-trace; lead, on the sex hormones in male workers, exposed to this metal on the level of the manufacturing plant of lead accumulators. The results indicate a significant reduction of the testosterone concentration in exposed workers compared to the control. However, the rate of LH was strongly increased at the individuals exposed to Pb. A significant difference concerning the rate of FSH, the hormone Prolactin and cortisol was recorded. The indicators of the lead poisoning indicate a very highly significant increase in the value of Pbs which vary between (142-796 µg/L) among which 50% of the workers present a high lead poisoning and the value of PPZ which vary between (43-554µg/L). The biochemical parameters show a significant increase in the rate of the créatinine, the urea and the acid urique. The hepatic results show no significant differentiation in the rate of TGO and TGP between both groups of study. However the rates of the enzyme phosphatase alkaline, triglyceride, and cholesterol a significant difference were registered.

Keywords: hormons, parameters, physilogical, Pbs, PPZ

Procedia PDF Downloads 371

Authors: R. T. Aggangan

Abstract:

Woodfuels continue to be a major component of the energy supply mix of the Philippines due to increasing demand for energy that are not adequately met by decreasing supply and increasing prices of fuel oil such as liquefied petroleum gas (LPG) and kerosene. The Development Academy of the Philippines projects the demand of woodfuels in 2016 as 28.3 million metric tons in the household sector and about 105.4 million metric tons combined supply potentials of both forest and non-forest lands. However, the Revised Master Plan for Forestry Development projects a demand of about 50 million cu meters of fuelwood in 2016 but the capability to supply from local sources is only about 28 million cu meters indicating a 44 % deficiency. Household demand constitutes 82% while industries demand is 18%. Domestic household demand for energy is for cooking needs while the industrial demand is for steam power generation, curing barns of tobacco: brick, ceramics and pot making; bakery; lime production; and small scale food processing. Factors that favour increased use of wood-based energy include the relatively low prices (increasing oil-based fuel prices), availability of efficient wood-based energy utilization technology, increasing supply, and increasing population that cannot afford conventional fuels. Moreover, innovations in combustion technology and cogeneration of heat and power from biomass for modern applications favour biomass energy development. This paper recommends policies and strategic directions for the development of the woodfuel industry with the twin goals of sustainably supplying the energy requirements of households and industry.

Keywords: biomass energy development, fuelwood, households and industry, innovations in combustion technology, supply and demand

Procedia PDF Downloads 320