Search results for: externality cost

Authors: Mosaad Attia Elkasaby

Abstract:

The crude oil contains paraffines, aromatics, and asphaltenes in addition to some organic impurities, with increasing demands to reduce the cost of crude oil production, the uses of a pour point depressant is mandatory to maintain good flow rate. The wax materials cause many problems during production, storage, and transport, especially at low temperature, as these waxes tend, at low temperatures, to precipitate on the wall lines, thus leads to the high viscosity of crude oil and impede the flow rate, which represents an additional burden for crude oil pumping system from the place of production to the refinery. There are many ways to solve this problem, including, but not limited to, heat the crude and the use of organic solvents. But one of the most important disadvantages of these methods is the high economic cost. The aim of this innovation is to manufacture some polymeric materials (polymers based on aniline) that are processed locally that can be used as a pour point depressant of crude oil. For the first time, polymer based on aniline is modified and used with a number of organic solvents and tested with solvent (Styrene). It was found that the polymer based on aniline, when modified, had full solubility in styrene, unlike other organic solvent that was used in the past, such as chloroform and toluene. We also used a new solvent (PONA) that is obtained from the process of hydrotreating and separation of straight run naphtha to dissolve polymer based on aniline as a pour point depressant of crude oil. This innovative include studies conducted on highly paraffinic crude oil (C.O.1 and C.O.2). On using concentration (2500 ppm) of polymer based on aniline, the pour point of crude oil has decreased from +33 to - 9°C in case of crude oil (C.O.1) and from + 42 to – 6°C in case crude oil (C.O.2) at the same concentration.

Keywords: PPD, aniline, paraffinic crude oils, polymers

Procedia PDF Downloads 78

Authors: Xiao-Hua Zhu, Xin Yuan, Yi-Ran Zhao

Abstract:

High-cadmium pollution in rice is a serious problem in many parts of China. Many kinds of remediation technologies have been tested and applied in many farmlands. Because of the productive function of the farmland, most technologies are inappropriate due to their destruction to the tillage soil layer. And the large labours and expensive fees of many technologies are also the restrictive factors for their applications. The conception of 'Root Micro-Geochemical Barrier' was proposed to reduce cadmium (Cd) bioavailability and the concentration of the cadmium in rice. Remediation and mitigation techniques were demonstrated on contaminated farmland in the downstream of some mine. According to the rule of rice growth, Cd would be absorbed by the crops in every growth stage, and the plant-absorb efficiency in the first stage of the tillering stage is almost the highest. We should create a method to protect the crops from heavy metal pollution, which could begin to work from the early growth stage. Many materials with repair property get our attention. The materials will create a barrier preventing Cd from being absorbed by the crops during all the growing process because the material has the ability to adsorb soil-Cd and making it losing its migration activity. And we should choose a good chance to put the materials into the crop-growing system cheaply as soon as early. Per plant, rice has a little root system scope, which makes the roots reach about 15cm deep and 15cm wide. So small root radiation area makes it possible for all the Cd approaching the roots to be adsorbed with a small amount of adsorbent. Mixing the remediation materials with the seed-raising soli and adding them to the tillage soil in the process of transplanting seedlings, we can control the soil-Cd activity in the range of roots to reduce the Cd-amount absorbed by the crops. Of course, the mineral materials must have enough adsorptive capacity and no additional pollution. More than 3000 square meters farmlands have been remediated. And on the application of root micro-geochemical barrier, the Cd-concentration in rice and the remediation-cost have been decreased by 90% and 80%, respectively, with little extra labour brought to the farmers. The Cd-concentrations in rice from remediated farmland have been controlled below 0.1 ppm. The remediation of one acre of contaminated cropland costs less than $100. The concept has its advantage in the remediation of paddy field contaminated by Cd, especially for the field with outside pollution sources.

Keywords: cadmium pollution, growth stage, cost, root micro-geochemistry barrier

Procedia PDF Downloads 69

Authors: Kamran Baksh Soomro, Amin Talei, Sina Alaghmand

Abstract:

Due to the declining freshwater availability to agriculture in many areas, the utilization of saline irrigation requires more consideration. For this purpose, the effects of saline irrigation on the economics of crop yield and soil salinity should be understood. A two-year field experiment was carried out during 2017-18 with three replications to investigate the effect of saline groundwater on the economics of bitter gourd production and soil salinity status after harvesting the crop. Two irrigation treatments, i.e., fresh quality irrigation water (IT₁ EC 0.56 dS.m⁻¹ (control) and other is saline groundwater ( IT₂ EC 2.56 dS.m⁻¹) were used under drip system of irrigation. Cost-benefit analysis is often used to assess adaptation approaches. In this study, it has been observed that the salts under IT₁ (fresh quality water) and IT₂ (saline groundwater) did not accumulate in the wetted zone. However, the salts were observed deposited at wetted periphery under both the treatments after the crop end at all the three sampling depths under drip system of irrigation. Moreover, the costs and benefits associated with different irrigation treatments for two consecutive seasons for bitter-gourd cultivation were also investigated, and it was found that the average gross returns per hectare in season 1 were USD 5008.22 and 4454.78 under irrigation treatment IT₁ and IT₂ respectively. Whereas in season 2 the average gross returns per hectare were 3713.47 and 3140.51 under IT₁ and IT₂ respectively.

Keywords: ground-water, soil salinity, drip irrigation, wetted zone, wetted periphery, cost benefit analysis

Procedia PDF Downloads 135

Authors: Udeh Nneka Evelyn

Abstract:

The shortcoming of traditional costing system in terms of validity, accuracy, consistency, and Relevance increased the need for modern management accounting system. Activity –Based Costing (ABC) can be used as a modern tool for planning, Control and decision making for management. Past studies on ABC system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing technique in service oriented business organizations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on ABC. Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry and government organization. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: identification the most profitable customers: more accurate product and service pricing: increase product profitability: Well organized process costs.

Keywords: business, costing, organizations, planning, techniques

Procedia PDF Downloads 227

Authors: Elham Dehghan, A. Shirzadi Javid, Mohsen Tadayon

Abstract:

Labor productivity is very important and gained special concerns among professionals in the construction industry, worldwide. Productivity improvements on labors achieve higher cost savings with minimal investment. Due to the fact that profit margins are small on construction projects, cost savings associated with productivity are crucial to become a successful contractor. This research program studies and highlights the factors affecting labor productivity in Iranian construction industry. A questionnaire was used to gather the relevant data from respondents who involve in managing various types of projects in wide areas in Iran. It involved ranking 57 predefined factors divided into 5 categories: Human/Labor; Financial; Management; Equipments/Materials and Environmental. Total 62 feedbacks were analyzed through the Relative Importance Index (RII) technique. The top ten factors affecting construction labor productivity in Iran are: 1) Professional capability of contractor project manager, 2) skills of contractor’s project management team, 3) professional capability of owner project manager, 4) professional capability of Consulting Project manager, 5) discipline working, 6) delay payments by the owner, 7) material shortages, 8) delays in delivery of materials, 9) turnover power of the owner, 10) poor site management. Recommendations have been made in the study to address these factors. The research has direct benefits to key stakeholders in Iranian construction industry.

Keywords: Iranian construction projects, labor, productivity, relative importance index

Procedia PDF Downloads 255

Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

Abstract:

The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

Procedia PDF Downloads 300

Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

Abstract:

This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

Procedia PDF Downloads 14

Authors: Karoline Reis de Sena

Abstract:

Endocrine disruptors are unregulated or not fully regulated compounds, even in the most developed countries, and which can be a danger to the environment and human health. They pass untreated through the secondary stage of conventional wastewater treatment plants, then the effluent from the wastewater treatment plants is discharged into the rivers, upstream and downstream from the drinking water treatment plants that use the same river water as the tributary. Long-term consumption of drinking water containing low concentrations of these compounds can cause health problems; these are persistent in nature and difficult to remove. In this way, research on emerging pollutants is expanding and is fueled by progress in finding the appropriate method for treating wastewater. Adsorption is the most common separation process, it is a simple and low-cost operation, but it is not eco-efficient. Concomitant to this, biosorption arises, which is a subcategory of adsorption where the biosorbent is biomass and which presents numerous advantages when compared to conventional treatment methods, such as low cost, high efficiency, minimization of the use of chemicals, absence of need for additional nutrients, biosorbent regeneration capacity and the biomass used in the production of biosorbents are found in abundance in nature. Thus, the use of alternative materials, such as sewage sludge, for the synthesis of adsorbents has proved to be an economically viable alternative, together with the importance of valuing the generated by-product flows, as well as managing the problem of their correct disposal. In this work, an alternative for the management of sewage sludge is proposed, transforming it into activated carbon and using it in the adsorption process of 17a-ethinylestradiol.

Keywords: 17α-ethinylestradiol, adsorption, activated carbon, sewage sludge, micropollutants

Procedia PDF Downloads 82

Authors: Syed Muhammad Awais Tahir, Syed Hossein Raza Hamdani

Abstract:

In the last two years, there has been a substantial increase in the rate of satellite launches. To keep up with the technology, it is imperative that the launch cost must be made affordable, especially in developing and underdeveloped countries. Launch cost is directly affected by the launch vehicle’s aerodynamic performance. Pegasus-XL SLV (Satellite Launch Vehicle) has been serving as a commercial SLV for the last 26 years, commencing its commercial flight operation from the six operational sites all around the US and Europe, and the Marshal Islands. Aerodynamic heating and drag contribute largely to Pegasus’s flight performance. The objective of this study is to reduce the aerodynamic heating and drag on Pegasus’s body significantly for supersonic and hypersonic flight regimes. Aerodynamic data for Pegasus’s first flight has been validated through CFD (Computational Fluid Dynamics), and then drag and aerodynamic heating is reduced by using a combination of a forward-facing cylindrical spike and a conical aero-disk at the actual operational flight conditions. CFD analysis using ANSYS fluent will be carried out for Mach no. ranges from 0.83 to 7.8, and AoA (Angle of Attack) ranges from -4 to +24 degrees for both simple and spiked-configuration, and then the comparison will be drawn using a variety of graphs and contours. Expected drag reduction for supersonic flight is to be around 15% to 25%, and for hypersonic flight is to be around 30% to 50%, especially for AoA < 15⁰. A 5% to 10% reduction in aerodynamic heating is expected to be achieved for hypersonic regions. In conclusion, the aerodynamic performance of air-launched Pegasus-XL SLV can be further enhanced, leading to its optimal fuel usage to achieve a more economical orbital flight.

Keywords: aerodynamics, pegasus-XL, drag reduction, aerodynamic heating, satellite launch vehicle, SLV, spike, aero-disk

Procedia PDF Downloads 86

Authors: Jaeun Park, Daekyoung Kim, Ho Kyoon Chung, Heeyeop Chae

Abstract:

Quantum dots light-emitting diodes (QD-LEDs) have been considered as the next generation display and lighting devices due to their excellent color purity, photo-stability solution process possibility and good device stability. Currently typical quantum dot light emitting diodes contain organic layers such as PEDOT:PSS and PVK for charge transport layers. To make quantum dot light emitting diodes (QD-LED) more stable, it is required to replace those acidic and relatively unstable organic charge transport layers with inorganic materials. Therefore all inorganic and solution processed quantum dot light emitting diodes can potentially be a solution to stable and cost-effective display devices. We studied solution processed NiO films to replace organic charge transport layers that are required for stable all-inorganic based light emitting diodes. The transition metal oxides can be made by various vacuum and solution processes, but the solution processes are considered more cost-effective than vacuum processes. In this work we investigated solution processed NiOx for a hole transport layer (HTL). NiOx, has valence band energy levels of 5.3eV and they are easy to make sol-gel solutions. Water vapor oxidation process was developed and applied to solution processed all-inorganic QD-LED. Turn-on voltage, luminance and current efficiency of QD in this work were 5V, 1800Cd/m2 and 0.5Cd/A, respectively.

Keywords: QD-LED, metal oxide solution, NiO, all-inorganic QD-LED device

Procedia PDF Downloads 733

Authors: B. Tiseo, V. Quaranta, G. Bruno, G. Sisinni

Abstract:

There is an increasing demand of nano-satellite development among universities, small companies, and emerging countries. Low-cost and fast-delivery are the main advantages of such class of satellites achieved by the extensive use of commercial-off-the-shelf components. On the other side, the loss of reliability and the poor success rate are limiting the use of nano-satellite to educational and technology demonstration and not to the commercial purpose. Standardization of nano-satellite environmental testing by tailoring the existing test standard for medium/large satellites is then a crucial step for their market growth. Thus, it is fundamental to find the right trade-off between the improvement of reliability and the need to keep their low-cost/fast-delivery advantages. This is particularly even more essential for satellites of CubeSat family. Such miniaturized and standardized satellites have 10 cm cubic form and mass no more than 1.33 kilograms per 1 unit (1U). For this class of nano-satellites, the qualification process is mandatory to reduce the risk of failure during a space mission. This paper reports the description and results of the space qualification test campaign performed on Endurosat’s CubeSat nano-satellite and modules. Mechanical and environmental tests have been carried out step by step: from the testing of the single subsystem up to the assembled CubeSat nano-satellite. Functional tests have been performed during all the test campaign to verify the functionalities of the systems. The test duration and levels have been selected by tailoring the European Space Agency standard ECSS-E-ST-10-03C and GEVS: GSFC-STD-7000A.

Keywords: CubeSat, nano-satellite, shock, testing, vibration

Procedia PDF Downloads 165

Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

Abstract:

In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

Procedia PDF Downloads 111

Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

Abstract:

Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

Procedia PDF Downloads 276

Authors: Cecile Meier, Drago Diaz Aleman, Itahisa Perez Conesa, Jose Luis Saorin Perez, Jorge De La Torre Cantero

Abstract:

In this work, two ways of creating small-sized metal sculptures are proposed: the first by means of microcasting and the second by electroforming from models printed in 3D using an FDM (Fused Deposition Modeling‎) printer or using a DLP (Digital Light Processing) printer. It is viable to replace the wax in the processes of the artistic foundry with 3D printed objects. In this technique, the digital models are manufactured with resin using a low-cost 3D FDM printer in polylactic acid (PLA). This material is used, because its properties make it a viable substitute to wax, within the processes of artistic casting with the technique of lost wax through Ceramic Shell casting. This technique consists of covering a sculpture of wax or in this case PLA with several layers of thermoresistant material. This material is heated to melt the PLA, obtaining an empty mold that is later filled with the molten metal. It is verified that the PLA models reduce the cost and time compared with the hand modeling of the wax. In addition, one can manufacture parts with 3D printing that are not possible to create with manual techniques. However, the sculptures created with this technique have a size limit. The problem is that when printed pieces with PLA are very small, they lose detail, and the laminar texture hides the shape of the piece. DLP type printer allows obtaining more detailed and smaller pieces than the FDM. Such small models are quite difficult and complex to melt using the lost wax technique of Ceramic Shell casting. But, as an alternative, there are microcasting and electroforming, which are specialized in creating small metal pieces such as jewelry ones. The microcasting is a variant of the lost wax that consists of introducing the model in a cylinder in which the refractory material is also poured. The molds are heated in an oven to melt the model and cook them. Finally, the metal is poured into the still hot cylinders that rotate in a machine at high speed to properly distribute all the metal. Because microcasting requires expensive material and machinery to melt a piece of metal, electroforming is an alternative for this process. The electroforming uses models in different materials; for this study, micro-sculptures printed in 3D are used. These are subjected to an electroforming bath that covers the pieces with a very thin layer of metal. This work will investigate the recommended size to use 3D printers, both with PLA and resin and first tests are being done to validate use the electroforming process of microsculptures, which are printed in resin using a DLP printer.

Keywords: sculptures, DLP 3D printer, microcasting, electroforming, fused deposition modeling

Procedia PDF Downloads 117

Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

Abstract:

The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm

Procedia PDF Downloads 287

Authors: D. G. Badagha, C. D. Modhera, S. A. Vasanwala

Abstract:

There is a great challenge for civil engineering field to contribute in environment prevention by finding out alternatives of cement and natural aggregates. There is a problem of global warming due to cement utilization in concrete, so it is necessary to give sustainable solution to produce concrete containing waste. It is very difficult to produce designated grade of concrete containing different ingredient and water cement ratio including waste to achieve desired fresh and harden properties of concrete as per requirement and specifications. To achieve the desired grade of concrete, a number of trials have to be taken, and then after evaluating the different parameters at long time performance, the concrete can be finalized to use for different purposes. This research work is carried out to solve the problem of time, cost and serviceability in the field of construction. In this research work, artificial neural network introduced to fix proportion of concrete ingredient with 50% waste replacement for M20, M25, M30, M35, M40, M45, M50, M55 and M60 grades of concrete. By using the neural network, mix design of high performance concrete was finalized, and the main basic mechanical properties were predicted at 3 days, 7 days and 28 days. The predicted strength was compared with the actual experimental mix design and concrete cube strength after 3 days, 7 days and 28 days. This experimentally and neural network based mix design can be used practically in field to give cost effective, time saving, feasible and sustainable high performance concrete for different types of structures.

Keywords: artificial neural network, high performance concrete, rebound hammer, strength prediction

Procedia PDF Downloads 140

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

Abstract:

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

Procedia PDF Downloads 423

Authors: Jae Hyun Park, Sangmi Chai, Minkyun Kim

Abstract:

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

Procedia PDF Downloads 221

Authors: Mohamed Abdelwahed

Abstract:

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

Procedia PDF Downloads 524

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

Abstract:

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

Procedia PDF Downloads 126

Authors: Harshan Tee Pee

Abstract:

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

Procedia PDF Downloads 101

Authors: Saron Adisu Gezahegn

Abstract:

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

Procedia PDF Downloads 87

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

Abstract:

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

Procedia PDF Downloads 389

Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

Abstract:

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

Procedia PDF Downloads 46

Authors: Raja Ezman Raja Shariff

Abstract:

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

Procedia PDF Downloads 386

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

Abstract:

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

Procedia PDF Downloads 325

Authors: Geeta Gahlawat, Sanjeev Kumar Soni

Abstract:

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

Procedia PDF Downloads 495

Authors: Anwesha Pathak

Abstract:

Space law refers to all legal provisions that may regulate or apply to space travel, as well as to space-related activity. Although there is undoubtedly a core corpus of “space law,” rather than designating a conceptually distinct single kind of law, the phrase can be seen as a label applied to a bucket that includes a variety of different laws and regulations. Similar to ‘family law' or ‘environmental law' "space law" refers to a variety of laws that are identified by the subject matter they address rather than by the logical extension of a single legal concept. The word "space law" refers to the Law of Space, which can cover anything from the specifics of an insurance agreement for a specific space launch to the most general guidelines that direct state behaviour in space. Space debris, often referred to as space junk, space pollution, space waste, space trash, or space garbage, is a term used to describe abandoned human-made objects in space, primarily in Earth orbit. These include disused spacecraft, discarded launch vehicle stages, mission-related detritus, and fragmentation material from the destruction of disused rocket bodies and spacecraft, which is particularly prevalent in Earth orbit. Other types of space debris, besides abandoned human-made objects in orbit, include pieces left over from collisions, erosion, and disintegration, or even paint specks, solidified liquids ejected from spacecraft, and unburned components from solid rocket engines. The initial action of launching or using a spacecraft in near-Earth orbit imposes an external cost on others that is typically not taken into account or fully accounted for in the cost by the launcher or payload owner.

Keywords: space, outer space treaty, geostationary orbit, satellites, spacecrafts

Procedia PDF Downloads 72

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

Abstract:

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

Procedia PDF Downloads 170

Authors: Masood Varshosaz, Kamyar Hasanpour

Abstract:

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

Procedia PDF Downloads 76