Search results for: travel cost

Authors: Mohammad Nehal Hasnine, Md Kamrul Hasan Chayon, Md Mobasswer Rahman

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Organizational tendencies towards computer-based information processing have been observed noticeably in the third-world countries. Many enterprises are taking major initiatives towards computerized working environment because of massive benefits of computer-based information processing. However, designing and developing information resource management software for small and mid-size enterprises under budget costs and strict deadline is always challenging for software engineers. Therefore, we introduced an approach to design mid-size enterprise software by using the Waterfall model, which is one of the SDLC (Software Development Life Cycles), in a cost effective way. To fulfill research objectives, in this study, we developed mid-sized enterprise software named “BSK Management System” that assists enterprise software clients with information resource management and perform complex organizational tasks. Waterfall model phases have been applied to ensure that all functions, user requirements, strategic goals, and objectives are met. In addition, Rich Picture, Structured English, and Data Dictionary have been implemented and investigated properly in engineering manner. Furthermore, an assessment survey with 20 participants has been conducted to investigate the usability and performance of the proposed software. The survey results indicated that our system featured simple interfaces, easy operation and maintenance, quick processing, and reliable and accurate transactions.

Keywords: end-user application development, enterprise software design, information resource management, usability

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Authors: Jae Hyun Park, Sangmi Chai, Minkyun Kim

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As users spend more time on the Internet, the probability of their personal information being exposed has been growing. This research has a main purpose of investigating factors and examining relationships when Internet users recognize their value of private information with a perspective of an economic asset. The study is targeted on Internet users, and the value of their private information will be converted into economic figures. Moreover, how economic value changes in relation with individual attributes, dealer’s traits, circumstantial properties will be studied. In this research, the changes in factors on private information value responding to different situations will be analyzed in an economic perspective. Additionally, this study examines the associations between users’ perceived risk and value of their personal information. By using the cost-benefit analysis framework, the hypothesis that the user’s sense in private information value can be influenced by individual attributes and situational properties will be tested. Therefore, this research will attempt to provide answers for three research objectives. First, this research will identify factors that affect value recognition of users’ personal information. Second, it provides evidences that there are differences on information system users’ economic value of information responding to personal, trade opponent, and situational attributes. Third, it investigates the impact of those attributes on individuals’ perceived risk. Based on the assumption that personal, trade opponent and situation attributes make an impact on the users’ value recognition on private information, this research will present the understandings on the different impacts of those attributes in recognizing the value of information with the economic perspective and prove the associative relationships between perceived risk and decision on the value of users’ personal information. In order to validate our research model, this research used the regression methodology. Our research results support that information breach experience and information security systems is associated with users’ perceived risk. Information control and uncertainty are also related to users’ perceived risk. Therefore, users’ perceived risk is considered as a significant factor on evaluating the value of personal information. It can be differentiated by trade opponent and situational attributes. This research presents new perspective on evaluating the value of users’ personal information in the context of perceived risk, personal, trade opponent and situational attributes. It fills the gap in the literature by providing how users’ perceived risk are associated with personal, trade opponent and situation attitudes in conducting business transactions with providing personal information. It adds to previous literature that the relationship exists between perceived risk and the value of users’ private information in the economic perspective. It also provides meaningful insights to the managers that in order to minimize the cost of information breach, managers need to recognize the value of individuals’ personal information and decide the proper amount of investments on protecting users’ online information privacy.

Keywords: private information, value, users, perceived risk, online information privacy, attributes

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Authors: Mohamed Abdelwahed

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We propose an optimization algorithm for the geometric control of fluid flow. The used approach is based on the topological sensitivity analysis method. It consists in studying the variation of a cost function with respect to the insertion of a small obstacle in the domain. Some theoretical and numerical results are presented in 2D and 3D.

Keywords: sensitivity analysis, topological gradient, shape optimization, stokes equations

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Authors: Lucia Rozumová, Ivo Šafařík, Jana Seidlerová, Pavel Kůs

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Biosorption by biological waste materials from agriculture industry could be a cost-effective technique for removing metal ions from wastewater. The performance of new biosorbent systems, consisting of the waste matrixes which were magnetically modified by iron oxide nanoparticles, for the removal of lead ions from an aqueous solution was tested. The use of low-cost and eco-friendly adsorbents has been investigated as an ideal alternative to the current expensive methods. This article deals with the removal of metal ions from aqueous solutions by modified waste products - orange peels, sawdust, peanuts husks, used tea leaves and ground coffee sediment. Magnetically modified waste materials were suspended in methanol and then was added ferrofluid (magnetic iron oxide nanoparticles). This modification process gives the predictions for the formation of the smart materials with new properties. Prepared material was characterized by using scanning electron microscopy, specific surface area and pore size analyzer. Studies were focused on the sorption and desorption properties. The changes of iron content in magnetically modified materials after treatment were observed as well. Adsorption process has been modelled by adsorption isotherms. The results show that magnetically modified materials during the dynamic sorption and desorption are stable at the high adsorbed amount of lead ions. The results of this study indicate that the biological waste materials as sorbent with new properties are highly effective for the treatment of wastewater.

Keywords: biological waste, sorption, metal ions, ferrofluid

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Authors: Harshan Tee Pee

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Climate elements include surface temperatures, rainfall patterns, humidity, type and amount of cloudiness, air pressure and wind speed and direction. Change in one element can have an impact on the regional climate. The scientific predictions indicate that global climate change will increase the number of extreme events, leading to more frequent natural hazards. Global warming is likely to intensify the risk of drought in certain parts and also leading to increased rainfall in some other parts. Drought is a slow advancing disaster and creeping phenomenon– which accumulate slowly over a long period of time. Droughts are naturally linked with aridity. But droughts occur over most parts of the world (both wet and humid regions) and create severe impacts on agriculture, basic household welfare and ecosystems. Drought condition occurs at least every three years in India. India is one among the most vulnerable drought prone countries in the world. The economic impacts resulting from extreme environmental events and disasters are huge as a result of disruption in many economic activities. The focus of this paper is to develop a comprehensive understanding about the distributional impacts of disaster, especially impact of drought on agricultural production and income through a panel study (drought year and one year after the drought) in Raikhel village, Maharashtra, India. The major findings of the study indicate that cultivating area as well as the number of cultivating households reduced after the drought, indicating a shift in the livelihood- households moved from agriculture to non-agriculture. Decline in the gross cropped area and production of various crops depended on the negative income from these crops in the previous agriculture season. All the landholding categories of households except landlords had negative income in the drought year and also the income disparities between the households were higher in that year. In the drought year, the cost of cultivation was higher for all the landholding categories due to the increased cost for irrigation and input cost. In the drought year, agriculture products (50 per cent of the total products) were used for household consumption rather than selling in the market. It is evident from the study that livelihood which was based on natural resources became less attractive to the people to due to the risk involved in it and people were moving to less risk livelihood for their sustenance.

Keywords: climate change, drought, agriculture economics, disaster impact

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Authors: Saron Adisu Gezahegn

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Commercial cosmetic has been affecting human health due to their contents and dosage composition. Chemical base cosmetics exposes users to unnecessary health problems and financial cost. Some of the cosmetics' interaction with the environment has negative impacts on health such as burning, cracking, coloring, and so on. The users are looking for a temporary service without evaluating the side effects of cosmetics that contain chemical compositions that result in irritation, burning, allergies, cracking, and the nature of the face. Every cosmetic contains a heavy metal such as lead, zinc, cadmium, silicon, and other heavy cosmetics materials. The users may expose at the end of the day to untreatable diseases like cancer. The objective of the research is to study the effects of indigenous biological face treatment without any additives like chemicals. In ancient times this thought was highly tremendous in the world but things were changing bit by bit and reached chemical base cosmetics to maintain the beauty of hair, skin, and faces. The side effects of the treatment on the face were minimum and the side effects with the interaction of the environment were almost nil. But this thought is changed and replaces the indigenous substances with chemical substances by adding additives like heavy chemical lead and cadmium in the sense of preservation, pigments, dye, and shining. Various studies indicated that cosmetics have dangerous side effects that expose users to health problems and expensive financial loss. This study focuses on a local indigenous plant called Kulkual. Kulkual is available everywhere in a study area and sustainable products can harvest to use as indigenous face treatment materials.25 men and 25 women were selected as a sample population randomly to conduct the study effectively.The plant is harvested from the guard in the productive season. The plant was exposed to the sun dry for a week. Then the peel was removed from the plant fruit and the peels were taken to a bath filled with water to soak for three days. Then the flesh of the peel was avoided from the fruit and ready to use as a face treatment. The fleshy peel was smeared on each sample for almost a week and continued for a week. The result indicated that the effects of the treatment were a positive response with minimum cost and minimum side effects due to the environment. The beauty shines, smoothness, and color are better than chemical base cosmetics. Finally, the study is recommended that all users prefer a biological method of treatment with minimum cost and minimums side effects on health with the interaction of the environment.

Keywords: cosmetic, indigneous, heavymetals, toxic

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Authors: Saem Lee, Thanh Nguyen, Hio-Jung Shin, Thomas Koellner

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Land-use management has an influence on the provision of ecosystem service in dynamic, agricultural landscapes. Agricultural land use is important for maintaining the productivity and sustainability of agricultural ecosystems. However, in Korea, intensive farming activities in this highland agricultural zone, the upper stream of Soyang has led to contaminated soil caused by over-use pesticides and fertilizers. This has led to decrease in water and soil quality, which has consequences for ecosystem services and human wellbeing. Conventional farming has still high percentage in this area and there is no special measure to prevent low water quality caused by farming activities. Therefore, the adoption of environmentally friendly farming has been considered one of the alternatives that lead to improved water quality and increase in biomass production. Concurrently, farm households with environmentally friendly farming have occupied still low rates. Therefore, our research involved a farm household survey spanning conventional farming, the farm in transition and organic farming in Soyang watershed. Another purpose of our research was to compare economic advantage of the farmers adopting environmentally friendly farming and non-adaptors and to investigate the different factors by logistic regression analysis with socio-economic and benefit-cost ratio variables. The results found that farmers with environmentally friendly farming tended to be younger than conventional farming and farmer in transition. They are similar in terms of gender which was predominately male. Farmers with environmentally friendly farming were more educated and had less farming experience than conventional farming and farmer in transition. Based on the benefit-cost analysis, total costs that farm in transition farmers spent for one year are about two times as much as the sum of costs in environmentally friendly farming. The benefit of organic farmers was assessed with 2,800 KRW per household per year. In logistic regression, the factors having statistical significance are subsidy and district, residence period and benefit-cost ratio. And district and residence period have the negative impact on the practice of environmentally friendly farming techniques. The results of our research make a valuable contribution to provide important information to describe Korean policy-making for agricultural and water management and to consider potential approaches to policy that would substantiate ways beneficial for sustainable resource management.

Keywords: organic farming, logistic regression, profitability, agricultural land-use

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Gubiani Rino, Nicola Zucchiatti, Da Broi Ugo, Bietresato Marco

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The problem of vibrations in agriculture is very important due to the different types of machinery used for the different types of soil in which work is carried out. One of the most commonly used machines is the tractor, where the phenomenon has been studied for a long time by measuring the whole body and placing the sensor on the seat. However, this measurement system does not take into account the characteristics of the drivers, such as their body index (BMI), their gender (male, female) or the muscle fatigue they are subjected to, which is highly dependent on their age for example. The aim of the research was therefore to place sensors not only on the seat but along the spinal column to check the transmission of vibration on drivers with different BMI on different tractors and at different travel speeds and of different genders. The test was also done using wearable sensors such as a dynamometer applied to the muscles, the data of which was correlated with the vibrations produced by the tractor. Initial data show that even on new tractors with pneumatic seats, the vibrations attenuate little and are still correlated with the roughness of the track travelled and the forward speed. Another important piece of data are the root-mean square values referred to 8 hours (A(8)x,y,z) and the maximum transient vibration values (MTVVx,y,z) and, the latter, the MTVVz values were problematic (limiting factor in most cases) and always aggravated by the speed. The MTVVx values can be lowered by having a tyre-pressure adjustment system, able to properly adjust the tire pressure according to the specific situation (ground, speed) in which a tractor is operating.

Keywords: fatigue, effect vibration on health, tractor driver vibrations, vibration, muscle skeleton disorders

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Authors: Raja Ezman Raja Shariff

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Acute kidney injury (AKI) is commonly seen in inpatients, and places a great cost on the NHS and patients. Timely and appropriate management is both nephron sparing and potentially life-saving. Ultrasound scanning (USS) is a well-recognised method for stratifying patients. Subsequently, the NICE AKI guidance has defined groups in whom scanning is recommended within 6 hours of request (pyonephrosis), within 24 hours (obstruction/cause unknown), and in whom routine scanning isn't recommended (cause for AKI identified). The audit looks into whether Stockport NHS Trust USS practice was in line with such recommendations. The audit evaluated 92 patients with AKI who had USS, between 01/01/14 to 30/04/14. Data collection was divided into 2 parts. Firstly, radiology request cards and the online imaging software (PACS) were evaluated. Then, the electronic case notes (ADVANTIS) was evaluated further. Based on request cards, 10% of requests were for pyonephrosis. Only 33% were scanned within 6hours and a further 33% within 24hours. 75% were requested for possible obstructions and unknown cause collectively. Of those due to possible obstruction, 71% of patients were scanned within 24 hours. Of those with unknown cause, 50% were scanned within 24 hours. 15% of requests had a cause declared and so potentially did not require scanning. Evaluation of the patients’ notes suggested further interesting findings. Firstly, potentially 39% of patients had a known cause for AKI, therefore, did not need USS. Subsequently, the cohort of unknown cause and possible obstruction was collectively reduced to 45%. Alarmingly the patient cohort with possible pyonephrosis went up to 16%, suggesting an under-recognition of this life-threatening condition. We plan to highlight these findings within our institution and make changes to encourage more appropriate requesting and timely scanning. Time will tell if we manage to save or increase our costs in this cost-conscious NHS. Patient benefits, though, seem to be guaranteed.

Keywords: AKI, ARF, kidney, renal

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Authors: Milica Karadžić, Lidija Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Anamarija Mandić, Aleksandar Oklješa, Andrea Nikolić, Marija Sakač, Katarina Penov Gaši

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Using chemometric approach, the relationships between the chromatographic lipophilicity and in silico molecular descriptors for twenty-nine selected steroid derivatives were studied. The chromatographic lipophilicity was predicted using artificial neural networks (ANNs) method. The most important in silico molecular descriptors were selected applying stepwise selection (SS) paired with partial least squares (PLS) method. Molecular descriptors with satisfactory variable importance in projection (VIP) values were selected for ANN modeling. The usefulness of generated models was confirmed by detailed statistical validation. High agreement between experimental and predicted values indicated that obtained models have good quality and high predictive ability. Global sensitivity analysis (GSA) confirmed the importance of each molecular descriptor used as an input variable. High-quality networks indicate a strong non-linear relationship between chromatographic lipophilicity and used in silico molecular descriptors. Applying selected molecular descriptors and generated ANNs the good prediction of chromatographic lipophilicity of the studied steroid derivatives can be obtained. This article is based upon work from COST Actions (CM1306 and CA15222), supported by COST (European Cooperation and Science and Technology).

Keywords: artificial neural networks, chemometrics, global sensitivity analysis, liquid chromatography, steroids

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Authors: Geeta Gahlawat, Sanjeev Kumar Soni

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An imprudent use of environmentally hazardous petrochemical-based plastics and limited availability of fossil fuels have provoked research interests towards production of biodegradable plastics - polyhydroxyalkanoate (PHAs). However, the industrial application of PHAs based products is primarily restricted by their high cost of recovery and extraction protocols. Moreover, solvents used for the extraction and purification are toxic and volatile which causes adverse environmental hazards. Development of efficient downstream recovery strategies along with utilization of non-toxic solvents will accelerate their commercialization. In this study, various extraction strategies were designed for sustainable and cost-effective recovery of PHAs from Cupriavidus necator using non-toxic environment friendly solvents viz. 1,2-propylene carbonate, ethyl acetate, isoamyl alcohol, butyl acetate. The effect of incubation time i.e. 10, 30 and 50 min and temperature i.e. 60, 80, 100, 120°C was tested to identify the most suitable solvent. PHAs extraction using a recyclable solvent, 1,2 propylene carbonate, showed the highest recovery yield (90%) and purity (93%) at 120°C and 30 min incubation. Ethyl acetate showed the better capacity to recover PHAs from cells than butyl acetate. Extraction with ethyl acetate exhibited high recovery yield and purity of 96% and 92%, respectively at 100°C. Effect of non-toxic surfactant such as linear alkylbenzene sulfonic acid (LAS) was also studied at 40, 60 and 80°C, and detergent pH range of 3.0, 5.0, 7.0 and 9.0 for the extraction of PHAs from the cells. LAS gave highest yield of 86% and purity of 88% at temperature 80°C and 5.0 pH.

Keywords: polyhydroxyalkanoates, Cupriavidus necator, extraction, recovery yield

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Authors: R. Tajau, R. Rohani, M. S. Alias, N. H. Mudri, K. A. Abdul Halim, M. H. Harun, N. Mat Isa, R. Che Ismail, S. Muhammad Faisal, M. Talib, M. R. Mohamed Zin

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Bio-based polymeric materials are increasingly used for a variety of applications, including surface coating, drug delivery systems, and tissue engineering. These polymeric materials are ideal for the aforementioned applications because they are derived from natural resources, non-toxic, low-cost, biocompatible, and biodegradable, and have promising thermal and mechanical properties. The nature of hydrocarbon chains, carbon double bonds, and ester bonds allows various sources of oil (edible), such as soy, sunflower, olive, and oil palm, to fine-tune their particular structures in the development of innovative materials. Palm oil can be the most eminent raw material used for manufacturing new and advanced natural polymeric materials involving radiation techniques, such as coating resins, nanoparticles, scaffold, nanotubes, nanocomposites, and lithography for different branches of the industry in countries where oil palm is abundant. The radiation technique is among the most versatile, cost-effective, simple, and effective methods. Crosslinking, reversible addition-fragmentation chain transfer (RAFT), polymerisation, grafting, and degradation are among the radiation mechanisms. Exposure to gamma, EB, UV, or laser irradiation, which are commonly used in the development of polymeric materials, is used in these mechanisms. Therefore, this review focuses on current radiation processing technologies for the development of various radiation-curable bio-based polymeric materials with a promising future in biomedical and industrial applications. The key focus of this review is on radiation curable palm oil-based products, which have been published frequently in recent studies.

Keywords: palm oil, radiation processing, surface coatings, VOC

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Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

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Authors: Adel Nikfarjam, Hamed Tayebi, Sadoullah Ebrahimnejad

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This paper considers a two-echelon inventory system with a number of warehouses and a single retailer. The retailer replenishes its required items from warehouses, and assembles them into a single final product. We assume that each warehouse supplies only one kind of the raw material for the retailer. The demand process of the final product is assumed to be Poissson, and unsatisfied demand of the final product will be lost. The retailer applies one-for-one-period ordering policy which is also known as (1, T) ordering policy. In this policy the retailer orders to each warehouse a fixed quantity of each item at fixed time intervals, which the fixed quantity is equal to the utilization of the item in the final product. Since, this policy eliminates all demand uncertainties at the upstream echelon, the standard lot sizing model can be applied at all warehouses. In this paper, we calculate the total cost function of the inventory system. Then, based on this function, we present a procedure to obtain the optimal time interval between two consecutive order placements from retailer to the warehouses, and the optimal order quantities of warehouses (assuming that there are positive ordering costs at warehouses). Finally, we present some numerical examples, and conduct numerical sensitivity analysis for cost parameters.

Keywords: two-echelon supply chain, multi-vendor-single-buyer inventory system, lost sales, Poisson demand, one-for-one-period policy, lot sizing model

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Authors: Maariyah Irfan

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Intro: Current cardiovascular (CV) care faces challenges such as low budgets and high hospital admission rates. This review aims to evaluate Big Data in CV healthcare management through the use of wearable devices in atrial fibrillation (AF) detection. AF may present intermittently, thus it is difficult for a healthcare professional to capture and diagnose a symptomatic rhythm. Methods: The iRhythm ZioPatch, AliveCor portable electrocardiogram (ECG), and Apple Watch were chosen for review due to their involvement in controlled clinical trials, and their integration with smartphones. The cost-effectiveness and AF detection of these devices were compared against the 12-lead ambulatory ECG (Holter monitor) that the NHS currently employs for the detection of AF. Results: The Zio patch was found to detect more arrhythmic events than the Holter monitor over a 2-week period. When patients presented to the emergency department with palpitations, AliveCor portable ECGs detected 6-fold more symptomatic events compared to the standard care group over 3-months. Based off preliminary results from the Apple Heart Study, only 0.5% of participants received irregular pulse notifications from the Apple Watch. Discussion: The Zio Patch and AliveCor devices have promising potential to be implemented into the standard duty of care offered by the NHS as they compare well to current routine measures. Nonetheless, companies must address the discrepancy between their target population and current consumers as those that could benefit the most from the innovation may be left out due to cost and access.

Keywords: atrial fibrillation, big data, cardiovascular healthcare management, wearable devices

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Authors: Neha Dimri, Varsha Gupta

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Purpose: Fast Fashion trend promotes consumption of low cost high fashion garments at a rapid rate. Frequent change in fashion trend results in higher disposability of Fast Fashion products. To cater for the Fast Fashion appetite of the present day consumer, fashion giants have ramped up production of garments, thus imposing a massive strain on the planet’s natural resources. Also, ethical issues related to cheaper methods of production are of concern. India being a large consumer base has a major role to play in proliferation of the Fast Fashion trend. This paper is an attempt to study the effect of fast fashion trends on the Indian consumer’s behaviour. It also attempts to ascertain the awareness of the consumer about the detrimental effect that the fast fashion trends manifest on the environment. Design /methodology/approach: The survey was conducted using a questionnaire targeted at a set of urban Indian consumers of varied age, profession and socio economic backgrounds. Trends regarding frequency of purchase, expenditure on clothing, disposal methods and awareness about environmental issues were analyzed using the obtained data. Findings: The result of the study indicates that urban Indian consumer has a strong affinity towards fast fashion trends, but is largely unaware of its detrimental effect on the environment and strain on natural resources. Research Limitation/implications: The sample size for survey was only of a hundred consumers, and the same could be expanded for a better estimate of trends. Also, the sample consumers were mostly urban. A big chunk of Indian fashion consumers reside in small towns and the same could be included in the survey. Practical implications: As the true cost of Fast Fashion in terms of environmental and ethical aspects is getting realized worldwide, a big market like India cannot remain isolated from this phenomenon. Globally there has been an increase in demand of ethically produced clothing. It is imperative that the Indian consumer be made aware about the unsustainable nature of Fast Fashion so that he can contribute towards conservation of natural resources and ethical production of garments. Originality/value The research attempts to ascertain consumption pattern of the Indian fashion consumer and also his awareness about the true cost and consequences of Fast Fashion. The inferences may be used by fashion giants to use ‘Green Marketing’ and ‘Social Marketing’ techniques to make the Indian consumer more aware about sustainable fashion and to market their own products as ‘Sustainable, Green and Ethical’.

Keywords: consumption, disposable, fast fashion, Indian consumer

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Authors: Krishna Nand, Mohammad Taufik

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Fused Filament Fabrication (FFF) is one of the most popular additive manufacturing (AM) technology. In FFF technology, a wire form material (filament) is fed inside a heated chamber, where it gets converted into semi-solid form and extruded out of a nozzle to be deposited on the build platform to fabricate the part. FFF technology is expanding and covering the market at a very rapid rate, so the need of raw materials for 3D printing is also increasing. The cost of 3D printing is directly affected by filament cost. To make 3D printing more economic, a compact and portable filament/wire extrusion system is needed. Wire extrusion systems to extrude ordinary wire/filament made of a single material are available in the market. However, extrusion system to make a composite wire/filament are not available. Hence, in this study, initial efforts have been made to develop a table-top composite wire extruder. The developed system is consisted of mechanical parts, electronics parts, and a control system. A multiple channel hopper, extrusion screw, melting chamber and nozzle, cooling zone, and spool winder are some mechanical parts. While motors, heater, temperature sensor, cooling fans are some electronics parts, which are used to develop this system. A control board has been used to control the various process parameters like – temperature and speed of motors. For the production of composite wire/filament, two different materials could be fed through two channels of hopper, which will be mixed and carried to the heated zone by extrusion screw. The extrusion screw is rotated by a motor, and the speed of this motor will be controlled by the controller as per the requirement of material extrusion rate. In the heated zone, the material will melt with the help of a heating element and extruded out of the nozzle in the form of wire. The developed system occupies less floor space due to the vertical orientation of its heating chamber. It is capable to extrude ordinary filament as well as composite filament, which are compatible with 3D printers available in the market. Further, the developed system could be employed in the research and development of materials, processing, and characterization for 3D printer. The developed system presented in this study could be a better choice for hobbyists and researchers dealing with the fused filament fabrication process to reduce the 3D printing cost significantly by recycling the waste material into 3D printer feed material. Further, it could also be explored as a better alternative for filament production at the commercial level.

Keywords: additive manufacturing, 3D Printing, filament extrusion, pellet extrusion

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Authors: Ihaddadene Thanina, Haraoubia Imane, Baouni Tahar

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Urban mobility is one of the first challenges of cities; it is becoming more and more problematic because it is perceived as the cause of many dysfunctions; it is not only to facilitate accessibility but also to ensure vast benefits. For this reason, several cities in the world have thought about alternatives to smart mobility and sustainable transport. Today, the sustainable city has many cards at its disposal, and a new mode is entering the urban scene: aerial cable transport; it has imposed itself as an effective mode of public transport and a real solution for the future. This electric mobility brings a new dimension, not only to collective daily travel but also to the urban space. It has an excellent capacity to redevelop the public space; it is a catalyst that allows one to appreciate the view from the sky and to discover different large-scale projects that bring an important attractiveness to the city. With regard to the cities in the world which use these systems of transport: Algeria does not escape this reality; it is the country which has the greatest number of devices of urban transport by cable in the world, with installations in many cities such as Tlemcen, Constantine, Blida, Oran, Tizi-Ouzou, Annaba, Skikda. The following study explores the role of cable transport in the transformation of the city of Algiers into a smart city. The methodology used in this work is based on the development of a set of indicators using a questionnaire survey. The main objective of this work is to shed light on cable transport as a key issue in designing the sustainable city of tomorrow, to evaluate its role in the city of Algiers, and its ability to integrate into the urban transport network.

Keywords: Algiers, cable transport, indicators, smart city

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Authors: Babak Mirbaha, Mahmoud Saffarzadeh, Fatemeh Mohajeri

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Road traffic accidents lead to a higher rate of death and injury, especially in vulnerable road users such as pedestrians. Improving the safety of facilities for pedestrians is a major concern for policymakers because of the high number of pedestrian fatalities and direct and indirect costs which are imposed to the society. This study focuses on the idea of determining the willingness to pay of pedestrians for increasing their safety while crossing the street. In this study, three different scenarios including crossing the street with zebra crossing facilities, crossing the street with zebra crossing facilities and installing a pedestrian traffic light and constructing a pedestrian bridge with escalator are presented. The research was conducted based on stated preferences method. The required data were collected from a questionnaire that consisted of three parts: pedestrian’s demographic characteristics, travel characteristics and scenarios. Four different payment amounts are presented for each scenario and a logit model has been built for each proposed payment. The results show that sex, age, education, average household income and individual salary have significant effect on choosing a scenario. Among the policies that have been mentioned through the questionnaire scenarios, the scenario of crossing the street with zebra crossing facilities and installing a traffic lights is the most frequent, with willingness to pay 10,000 Rials and the scenario of crossing the street with a zebra crossing with a willingness to pay 100,000 Rials having the least frequency. For all scenarios, as the payment is increasing, the willingness to pay decreases.

Keywords: pedestrians, willingness to pay, safety, immunization

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: Kyung Bae Park, Sung Ho Ha

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Online user-generated contents (UGC) significantly change the way customers behave (e.g., shop, travel), and a pressing need to handle the overwhelmingly plethora amount of various UGC is one of the paramount issues for management. However, a current approach (e.g., sentiment analysis) is often ineffective for leveraging textual information to detect the problems or issues that a certain management suffers from. In this paper, we employ text mining of Latent Dirichlet Allocation (LDA) on a popular online review site dedicated to complaint from users. We find that the employed LDA efficiently detects customer complaints, and a further inspection with the visualization technique is effective to categorize the problems or issues. As such, management can identify the issues at stake and prioritize them accordingly in a timely manner given the limited amount of resources. The findings provide managerial insights into how analytics on social media can help maintain and improve their reputation management. Our interdisciplinary approach also highlights several insights by applying machine learning techniques in marketing research domain. On a broader technical note, this paper illustrates the details of how to implement LDA in R program from a beginning (data collection in R) to an end (LDA analysis in R) since the instruction is still largely undocumented. In this regard, it will help lower the boundary for interdisciplinary researcher to conduct related research.

Keywords: latent dirichlet allocation, R program, text mining, topic model, user generated contents, visualization

Procedia PDF Downloads 171

Authors: Zhehao Zhang

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Walking has become an indispensable and sustainable way of travel for college students in their daily lives; campus street is an important carrier for students to walk and take part in a variety of activities, improving the walkability of campus streets plays an important role in optimizing the quality of campus space environment, promoting the campus walking system and inducing multiple walking behaviors. The purpose of this paper is to explore the effect of campus layout, facility distribution, and location site selection on the walkability of campus streets, and assess the street design qualities from the elements of imageability, enclosure, complexity, transparency, and human scale, and further examines the relationship between street-level urban design perceptual qualities and walkability and its effect on walking behavior in the campus. Taking Tianjin University as the research object, this paper uses the optimized walk score method based on walking frequency, variety, and distance to evaluate the walkability of streets from a macro perspective and measures the urban design qualities in terms of the calculation of street physical environment characteristics, as well as uses behavior annotation and street image data to establish temporal and spatial behavior database to analyze walking activity from the microscopic view. In addition, based on the conclusions, the improvement and design strategy will be presented from the aspects of the built walking environment, street vitality, and walking behavior.

Keywords: walkability, streetscapes, pedestrian activity, walk score

Procedia PDF Downloads 131

Authors: J. M. Counsell, Y. Khalid, M. J. Stewart

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Achieving nearly zero carbon heating continues to be identified by UK government analysis as an important feature of any lowest cost pathway to reducing greenhouse gas emissions. Heat currently accounts for 48% of UK energy consumption and approximately one third of UK’s greenhouse gas emissions. Heat Networks are being promoted by UK investment policies as one means of supporting hybrid heat pump based solutions. To this effect the RISE (Renewable Integrated and Sustainable Electric) heating system project is investigating how an all-electric heating sourceshybrid configuration could play a key role in long-term decarbonisation of heat.  For the purposes of this study, hybrid systems are defined as systems combining the technologies of an electric driven air source heat pump, electric powered thermal storage, a thermal vessel and micro-heat network as an integrated system.  This hybrid strategy allows for the system to store up energy during periods of low electricity demand from the national grid, turning it into a dynamic supply of low cost heat which is utilized only when required. Currently a prototype of such a system is being tested in a modern house integrated with advanced controls and sensors. This paper presents the virtual performance analysis of the system and its design for a micro heat network with multiple dwelling units. The results show that the RISE system is controllable and can reduce carbon emissions whilst being competitive in running costs with a conventional gas boiler heating system.

Keywords: gas boilers, heat pumps, hybrid heating and thermal storage, renewable integrated and sustainable electric

Procedia PDF Downloads 402

Authors: Ran Etgar, Yuval Cohen, Erel Avineri

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One of the major challenges of transportation in medium sized inner-cities (such as Tel-Aviv) is the last-mile solution. Personal rapid transit (PRT) seems like an applicable candidate for this, as it combines the benefits of personal (car) travel with the operational benefits of transit. However, the investment required for large area PRT grid is significant and there is a need to economically justify such investment by correctly evaluating the grid capacity. PRT main elements are small automated vehicles (sometimes referred to as podcars) operating on a network of specially built guideways. The research is looking at a specific concept of elevated PRT system. Literature review has revealed the drawbacks PRT modelling and simulation approaches, mainly due to the lack of consideration of technical and operational features of the system (such as headways, acceleration, safety issues); the detailed design of infrastructure (guideways, stations, and docks); the stochastic and sessional characteristics of demand; and safety regulations – all of them have a strong effect on the system performance. A highly detailed model of the system, developed in this research, is applying a discrete event simulation combined with an agent-based approach, to represent the system elements and the podecars movement logic. Applying a case study approach, the simulation model is used to study the capacity of the system, the expected throughput of the system, the utilization, and the level of service (journey time, waiting time, etc.).

Keywords: capacity, productivity measurement, PRT, simulation, transportation

Procedia PDF Downloads 147

Authors: Samkeliso S. Ndzimandze, Welldone Moyo, Oranso T. Mahlangu, Adolph A. Muleja, Alex T. Kuvarega, Thabo T. I. Nkambule

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The high cost of precursor materials has hindered the commercialization of ceramic membrane technology in water treatment. In this work, a ceramic membrane disc (approximately 50 mm in diameter and 4 mm thick) was prepared from low-cost starting materials, kaolin, and fly ash by pressing at 200 bar and calcining at 900 °C. The fabricated membrane was characterized for various physicochemical properties, natural organic matter (NOM) removal as well as fouling propensity using several techniques. Further, the ceramic membrane was tested on samples collected from four drinking water treatment plants in KwaZulu-Natal, South Africa (named plants 1-4). The membrane achieved 48.6%, 54.6%, 57.4%, and 76.4% bulk UV254 reduction for raw water at plants 1, 2, 3, and 4, respectively. These removal rates were comparable to UV254 reduction achieved by coagulation/flocculation steps at the respective plants. Further, the membrane outperformed sand filtration steps in plants 1-4 in removing disinfection by-product precursors (8%-32%) through size exclusion. Fluorescence excitation-emission matrices (FEEM) studies showed the removal of fluorescent NOM fractions present in the water samples by the membrane. The membrane was fabricated using an up-scalable facile method, and it has the potential for application as a polishing step to complement conventional processes in water treatment for drinking purposes.

Keywords: crossflow filtration, drinking water treatment plants, fluorescence excitation-emission matrices, ultraviolet 254 (UV₂₅₄)

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Authors: Hanan A. Anwar

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This paper introduces green building construction in Egypt with different concepts and practices. The following study includes green building applied definition, guidelines, regulations and Standards. Evaluation of cost/benefit of green construction methods and green construction rating systems are presented. Relevant case studies will be reviewed. Four sites will be included.

Keywords: green construction, ecofreindly, self-sufficient town, carbon neutral atmosphere

Procedia PDF Downloads 634

Authors: Mahnaz Sanjari, Sedigheh Salemi, Mohammad Mirzabeigi

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Nowadays, the world is facing a crisis of workforce and one of the most striking examples is the shortage of nurses. Nursing workforce productivity is related by various factors such as absenteeism, professional effectiveness and quality care. This cross-sectional study was conducted in 700 nurses who work in government hospitals from 35 hospitals of 9 provinces in Iran. The study was approved by the Nursing Council and was carried out with the authorization of the Research Ethics Committee. The questionnaire included 33 questions and 4 sub categories such as human resource, education and management. The reliability was evaluated by Cronbach's alpha (α=0/85). Statistical analyzes were performed, using SPSS version 16. The result showed that nurses emphasized on "respect to nurse-to-bed ratio" and less importance item was "using less experienced nurse". In addition, another important factor in clinical productivity is "Proper physical structure and amenities","good communication with colleagues" and "having good facilities". Also, "human resources at all levels of standard", "promoting on merit" and "well defined relationship in health system" are another important factors in productivity from nurse` view. The main managerial factor is "justice between employees" and the main educational component of productivity is “updating nursing knowledge”. The results show that more than half of the participants emphasized on the management and educational factors. Productivity as one of the main part of the health care quality leads to appropriate use of human and organizational resources, reduce cost services, and organizational development.

Keywords: productivity, nursing services, workforce, cost services

Procedia PDF Downloads 333

Authors: Ali Jahanfar, Brajesh Dubey, Bahram Gharabaghi, Saber Bayat Movahed

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Ever increasing population growth of major urban centers and environmental challenges in siting new landfills have resulted in a growing trend in design of mega-landfills some with extraordinary heights and dangerously steep slopes. Landfill failure mobility risk analysis is one of the most uncertain types of dynamic rheology models due to very large inherent variabilities in the heterogeneous solid waste material shear strength properties. The waste flow of three historic dumpsite and two landfill failures were back-analyzed using run-out modeling with DAN-W model. The travel distances of the waste flow during landfill failures were calculated approach by taking into account variability in material shear strength properties. The probability distribution function for shear strength properties of the waste material were grouped into four major classed based on waste material compaction (landfills versus dumpsites) and composition (high versus low quantity) of high shear strength waste materials such as wood, metal, plastic, paper and cardboard in the waste. This paper presents a probabilistic method for estimation of the spatial extent of waste avalanches, after a potential landfill failure, to create maps of vulnerability scores to inform property owners and residents of the level of the risk.

Keywords: landfill failure, waste flow, Voellmy rheology, friction coefficient, waste compaction and type

Procedia PDF Downloads 273

Authors: Mohammad Amin Hamedirad, Seyed Javad Vaziri Kang Olyaei

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Project planning and control are one of the most critical issues in the management of construction projects. Traditional methods of project planning and control, such as the critical path method or Gantt chart, are not widely used for planning projects with discrete and repetitive activities, and one of the problems of project managers is planning the implementation process and optimal allocation of its resources. Massive concreting projects is also a project with discrete and repetitive activities. This study uses the concept of simulating discrete events to manage resources, which includes finding the optimal number of resources considering various limitations such as limitations of machinery, equipment, human resources and even technical, time and implementation limitations using analysis of resource consumption rate, project completion time and critical points analysis of the implementation process. For this purpose, the concept of discrete-event simulation has been used to model different stages of implementation. After reviewing the various scenarios, the optimal number of allocations for each resource is finally determined to reach the maximum utilization rate and also to reduce the project completion time or reduce its cost according to the existing constraints. The results showed that with the optimal allocation of resources, the project completion time could be reduced by 90%, and the resulting costs can be reduced by up to 49%. Thus, allocating the optimal number of project resources using this method will reduce its time and cost.

Keywords: simulation, massive concreting, discrete event simulation, resource management

Procedia PDF Downloads 131