Search results for: low cost of mud formulation

Authors: Sathish Kumar Jayaraj

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The study of urban traffic dynamics, underpinned by the principles of fluid dynamics, offers a distinct perspective to comprehend and enhance the efficiency of traffic flow within bustling cityscapes. Leveraging the concept of the Traffic Flow Factor (TFF) as an analog to the Reynolds number, this research delves into the intricate interplay between traffic density, velocity, and road category, drawing compelling parallels to fluid dynamics phenomena. By introducing the notion of Vehicle Shearing Resistance (VSR) as an analogy to dynamic viscosity, the study sheds light on the multifaceted influence of traffic regulations, lane management, and road infrastructure on the smoothness and resilience of traffic flow. The TFF equation serves as a comprehensive metric for quantifying traffic dynamics, enabling the identification of congestion hotspots, the optimization of traffic signal timings, and the formulation of data-driven traffic management strategies. The study underscores the critical significance of integrating fluid dynamics principles into the domain of urban traffic management, fostering sustainable transportation practices, and paving the way for a more seamless and resilient urban mobility ecosystem.

Keywords: traffic flow factor (TFF), urban traffic dynamics, fluid dynamics principles, vehicle shearing resistance (VSR), traffic congestion management, sustainable urban mobility

Procedia PDF Downloads 62

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

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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 750

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

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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 186

Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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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 125

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

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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 291

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

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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 135

Authors: Haider M. Alsaeq

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The present research is an attempt to figure out the best configuration of composite cylindrical shells of the sandwich type, i.e. the lightest design of such shells required to sustain a certain load over a certain area. The optimization is based on elastic-plastic geometrically nonlinear incremental-iterative finite element analysis. The nine-node degenerated curved shell element is used in which five degrees of freedom are specified at each nodal point, with a layered model. The formulation of the geometrical nonlinearity problem is carried out using the well-known total Lagrangian principle. For the structural optimization problem, which is dealt with as a constrained nonlinear optimization, the so-called Modified Hooke and Jeeves method is employed by considering the weight of the shell as the objective function with stress and geometrical constraints. It was concluded that the optimum design of composite sandwich cylindrical shell that have a rigid polyurethane foam core and steel facing occurs when the area covered by the shell becomes almost square with a ratio of core thickness to facing thickness lies between 45 and 49, while the optimum height to length ration varies from 0.03 to 0.08 depending on the aspect ratio of the shell and its boundary conditions.

Keywords: composite structure, cylindrical shell, optimization, non-linear analysis, finite element

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Authors: Nasir Khalid, S. Thirumalaichelvam

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In most buildings, according to US Department of Energy Data Book, the electrical consumption attributable to centralized heating and ventilation of air- condition (HVAC) component can be as high as 40-60% of the total electricity consumption for an entire building. To provide efficient energy management for the market today, researchers are finding new ways to develop a system that can save electrical consumption of buildings even more. In this concept paper, a system known as Intelligent Chiller Energy Efficiency (iCEE) System is being developed that is capable of saving up to 25% from the chiller’s existing electrical energy consumption. In variable frequency drives (VFDs), research has found significant savings up to 30% of electrical energy consumption. Together with the VFDs at specific Air Handling Unit (AHU) of HVAC component, this system will save even more electrical energy consumption. The iCEE System is compatible with any make, model or age of centrifugal, rotary or reciprocating chiller air-conditioning systems which are electrically driven. The iCEE system uses engineering principles of efficiency analysis, enthalpy analysis, heat transfer, mathematical prediction, modified genetic algorithm, psychometrics analysis, and optimization formulation to achieve true and tangible energy savings for consumers.

Keywords: variable frequency drives, adjustable speed drives, ac drives, chiller energy system

Procedia PDF Downloads 558

Authors: Abrar Hussain, Kuen-Song Lin, Sayed Maeen Badshah, Jamshid Hussain

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The conversion of CO₂ into versatile, useful compounds such as fuels and other chemicals remains a challenging frontier in research, demanding the innovation of increasingly effective catalysts. In the present work, a catalyst-incorporating zirconium (Zr) modification within CuO–ZnO–Al₂O₃ (CZA) was synthesized via a co-precipitation method to convert CO₂ into methanol. Furthermore, bio-HZSM-5 was used to promote methanol dehydration to produce dimethyl ether (DME). We prepared the porous hierarchy bio-HZSM-5 with remarkable pore connectivity by utilizing an economical loofah sponge and rice husks as biotemplates. The synthesized catalysts were characterized using Field Emission Scanning Electron Microscopy (FE-SEM), X–ray diffraction (XRD), N₂ adsorption (BET), temperature-programmed desorption (NH₃-TPD) and thermogravimetric analysis (TGA). The Zr addition improved the performance of the CZZA catalyst as a structural promoter, leading to increased DME selectivity and total carbon conversion by enhancing active sites, surface area, and the synergistic interfaces between CuO and ZnO. The presence of silicon in the biomass, notably from the loofah sponge (0.016 wt %) and rice husks (8.3 wt %), also performed a pivotal role in the preparation of bio-HZSM-5. Furthermore, contrasted to the CZZA/com-ZSM-5 catalyst, the integration of CZZA with bio-HZSM-5-L bifunctional catalyst achieved the highest DME yield (12.1 %), DME selectivity (58.6%), CO₂ conversion (22.5%) at 280 °C and 30 bar. The payback time for 5 and 10-tons per day (5 and10-TPD) DME formation using the catalytic process of CO₂ from petrochemical refinery plant waste gas emissions was 2.98 and 2.44 years, respectively.

Keywords: Cost assessment, Dimethyl ether, low-cost bio-HZSM-5, CZZA catalyst, CO₂ hydrogenation

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

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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

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

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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 155

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: Merve Ozer, Tolga Gokkurt, Yasemen Gokkurt, Ezgi Bozbey

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In this study, we investigated the recovery of Polyethylene terephthalate/Polypropylene (PET/PP)-containing automotive textile waste from post-product and post-consumer phases in the automotive sector according to the upcycling technique and the methods of formulation and production that would allow these wastes to be substituted as PP/PET alloys instead of original PP raw materials used in plastic edge band production. The laminated structure of the stated wastes makes it impossible to separate the incompatible PP and PET phases in content and thus produce a quality raw material or product as a result of recycling. Within the scope of a two-stage production process, a comprehensive process was examined using block copolymers and maleic grafted copolymers with different features to ensure that these two incompatible phases are compatible. The mechanical, thermal, and morphological properties of the plastic raw materials, which will be referred to as PP/PET blends obtained as a result of the process, were examined in detail and discussed their substitutability instead of the original raw materials.

Keywords: mechanical recycling, melt blending, plastic blends, polyethylene, polypropylene, recycling of plastics, terephthalate, twin screw extruders

Procedia PDF Downloads 72

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

Procedia PDF Downloads 239

Authors: Lena Emamjomeh, Sohrab Imani

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Nowadays, the use of encapsulation technology of pesticides causes an increase in the efficiency and controlled release of these substances. Controlled release by nanoencapsulated formulations allows the essential oil to be used more effectively over a given time interval, suitability to the mode of application and minimization of environmental damage. The essential oil from Eucalyptus globulus exhibited an average yield of 1.19% and presented 1,8-cineol (59.08%) as the major component. Nanoemulsion essential oil was carried out by the method of gum - maltodextrin using homogenization and morphology and size were determined by TEM. Several concentrations were prepared, and then third instar larvae of E.kuehniella were introduced into each treatment. Then, repellent activity was determined after 1, 3 and 24 h from commencement. This study reveals that at a concentration of 1.5 ppm, the nanoemulsion of E. globulus essential oil on the flour disc was shown here to possess more repellent activity (85%) than E.kuehniella compared to natural essential oil (5%) before formulation after 24h. The repellent activity varied with application method concentrations and exposure time. The results showed higher repellent rates in nanoemulsion than in essential oil due to controlled-release formulations allowing smaller quantities of essential oil to be used more effectively over a given time interval. Findings led to the conclusion that encapsulated technology of essential oils can enhance their control release and persistence under controlled conditions.

Keywords: nanoemulsion, eucalyptus globulus, ephestia kuehniella, TEM

Procedia PDF Downloads 50

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

Procedia PDF Downloads 537

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

Procedia PDF Downloads 118

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

Procedia PDF Downloads 108

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: Farzad Khajavi

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Recognition of the interaction between active pharmaceutical ingredients (API) and excipients is a pivotal factor in the development of all pharmaceutical dosage forms. By predicting the interaction between API and excipients, we will be able to prevent the advent of impurities or at least lessen their amount. In this study, we used principle component analysis (PCA) to predict the interaction between Gliclazide as a secondary amine with Lactose in pharmaceutical solid dosage forms. The infrared spectra of binary mixtures of Gliclazide with Lactose at different mole ratios were recorded, and the obtained matrix was analyzed with PCA. By plotting score columns of the analyzed matrix, the incompatibility between Gliclazide and Lactose was observed. This incompatibility was seen experimentally. We observed the appearance of the impurity originated from the Maillard reaction between Gliclazide and Lactose at the chromatogram of the manufactured tablets in room temperature and under accelerated stability conditions. This impurity increases at the stability months. By changing Lactose to Mannitol and using Calcium Dibasic Phosphate in the tablet formulation, the amount of the impurity decreased and was in the acceptance range defined by British pharmacopeia for Gliclazide Tablets. This method is a fast and simple way to predict the existence of incompatibility between excipients and active pharmaceutical ingredients.

Keywords: PCA, gliclazide, impurity, infrared spectroscopy, interaction

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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: Merrimi El Bekkaye, El Bikri Khalid, Benamar Rhali

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In the present paper, the problem of geometrically non-linear free vibration of symmetrically and asymmetrically laminated composite beams (LCB) resting on nonlinear Pasternak elastic Foundation with immovable ends is studied. A homogenization procedure has been performed to reduce the problem under consideration to that of the isotropic homogeneous beams with effective bending stiffness and axial stiffness parameters. This simple formulation is developed using the governing axial equation of the beam in which the axial inertia and damping are ignored. The theoretical model is based on Hamilton’s principle and spectral analysis. Iterative form solutions are presented to calculate the fundamental nonlinear frequency parameters which are found to be in a good agreement with the published results. On the other hand, the influence of the foundation parameters on the nonlinear frequency to the linear frequency ratio of the LCB has been studied. The non-dimensional curvatures associated to the fundamental mode are also given in the case of clamped-clamped symmetrically and asymmetrically laminated composite beams.

Keywords: large vibration amplitudes, laminated composite beam, Pasternak foundation, composite beams

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Authors: Anwesha Pathak

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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

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Authors: Mohammed Ibrahim Bu Haya, Abdelmoneim Bahyeldin Mohamed Metwally

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This paper examines the impact of Green Intellectual Capital (GIC) on Green Supply Chain Performance (GSCP). Further, the study examines the moderating role of external pressures (EP) on the relationship between GIC and GSCP. Data were collected from employees working in Egyptian hotels and tourism companies (N= 366). The collected data were analyzed using smart partial least squares (Smart-PLS) software. The current research indicated that there is a positive and significant impact of all GIC components on GSCP. The results also revealed that EP were found to moderate the relationship between GIC and GSCP. The study model was able to explain 63.1% of the variance in GSCP. The findings of this study serve as a pivotal yardstick for guiding corporate policy formulation, offering valuable insights to drive continuous improvements in supply chain management and performance. Furthermore, the research holds substantial implications for managerial strategies by shedding light on the potential of GIC and EP to elevate GSCP. Positioned as one of the initial studies to delve into the moderating role of EP in the relationship between GIC and GSCP, this research offers insights within an emerging market context.

Keywords: green intellectual capital, green supply chain, supply chain performance, external pressures, emerging economy, Egypt

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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

Procedia PDF Downloads 94