Search results for: improve efficiency

Authors: Hafsa Chergui

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Malnutrition is a very common problem for hospitalized patients in general but it happens most to those who have a chronic disease such as cancer. Learned food aversions are defined as aversions which form toward foods after their ingestion has been temporally paired with illness (nausea or emesis). Learned food aversion may exert a negative impact on nutritional status and quality of life. The present review evaluates the literature derived both from laboratory animals and humans. Also, a questionnaire has been filled by patients under chemotherapy to assess the level of food aversions. This study evaluated the current research for avoiding the formation of aversions to dietary items in 200 cancer patients treated with chemotherapy. A scapegoat food or beverage can be used just before treatment to reduce the incidence of treatment-related aversions to foods in the individual s usual diet. The goal of this work is to inform the nurses and dieticians because they play a vital role in the daily assessment of the patients' nutritional status. Being aware of all the causes of malnutrition may help to suggest solutions to improve the health condition of the patient and avoid severe malnutrition.

Keywords: chemotherapy, oncology, food aversion, taste aversion

Procedia PDF Downloads 299

Authors: Dehini Rachid, Ferdi Brahim

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The shunt active power filter (SAPF) is not destined only to improve the power factor, but also to compensate the unwanted harmonic currents produced by nonlinear loads. This paper presents a SAPF with identification and control method based on artificial neural network (ANN). To identify harmonics, many techniques are used, among them the conventional p-q theory and the relatively recent one the artificial neural network method. It is difficult to get satisfied identification and control characteristics by using a normal (ANN) due to the nonlinearity of the system (SAPF + fast nonlinear load variations). This work is an attempt to undertake a systematic study of the problem to equip the (SAPF) with the harmonics identification and DC link voltage control method based on (ANN). The latter has been applied to the (SAPF) with fast nonlinear load variations. The results of computer simulations and experiments are given, which can confirm the feasibility of the proposed active power filter.

Keywords: artificial neural networks (ANN), p-q theory, harmonics, total harmonic distortion

Procedia PDF Downloads 386

Authors: M. Merabet-Khelassi, Z. Houiene, L. Aribi-Zouioueche, O. Riant

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Lipases (EC.3.1.1.3) are efficient biotools widely used for their remarkable chemo-, regio- and enantio-selectivity, especially, in kinetic resolution of racemates. They offer access to a large panel of enantiopure building blocks, such as secondary benzylic alcohols, commonly used as synthetic intermediates in pharmaceutical and agrochemical industries. Due to the stability of lipases in both water and organic solvents poor in water, they are able to catalyze both transesterifications of arylalkylcarbinols and hydrolysis of their corresponding acetates. The use of enzymatic hydrolysis in aqueous media still limited. In this presentation, we expose a practical methodology for the preparation of optically enriched acetates using a Candida antarctica lipase B-catalyzed hydrolysis in non-aqueous media in the presence of alkaline carbonate salts. The influence of several parameters which can intervene on the enzymatic efficiency such as the impact of the introduction of the carbonates salts, its amount and the nature of the alkaline earth metal are discussed. The obtained results show that the use of sodium carbonate with CAL-B enhances drastically both reactivity and selectivity of this immobilized lipase. In all cases, the resulting alcohols and remaining acetates are obtained in high ee values (up to > 99 %), and the selectivities reach (E > 500).

Keywords: alkaline-hydrolysis, enzymatic kinetic resolution, lipases, arylalkylcarbinol, non-aqueous media

Procedia PDF Downloads 162

Authors: Awatef Chniguir, Tarek Farah, Zouhair Ben Jemaa, Safya Belguith

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Optimal routing allows minimizing energy consumption in wireless sensor networks (WSN). Clustering has proven its effectiveness in organizing WSN by reducing channel contention and packet collision and enhancing network throughput under heavy load. Therefore, nowadays, with the emergence of the Internet of Things, heterogeneity is essential. Stable election protocol (SEP) that has increased the network stability period and lifetime is the first clustering protocol for heterogeneous WSN. SEP and its descendants, namely SEP, Threshold Sensitive SEP (TSEP), Enhanced TSEP (ETSSEP) and Current Energy Allotted TSEP (CEATSEP), were studied. These algorithms’ performance was evaluated based on different metrics, especially first node death (FND), to compare their stability. Simulations were conducted on the MATLAB tool considering two scenarios: The first one demonstrates the fraction variation of advanced nodes by setting the number of total nodes. The second considers the interpretation of the number of nodes while keeping the number of advanced nodes permanent. CEATSEP outperforms its antecedents by increasing stability and, at the same time, keeping a low throughput. It also operates very well in a large-scale network. Consequently, CEATSEP has a useful lifespan and energy efficiency compared to the other routing protocol for heterogeneous WSN.

Keywords: clustering, heterogeneous, stability, scalability, IoT, WSN

Procedia PDF Downloads 131

Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun

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In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distribution

Keywords: multi-objective optimization, random drift particle swarm optimization, crowding distance sorting, pareto optimal solution

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Authors: M. Zake, I. Barmina, R. Valdmanis, A. Kolmickovs

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Experimental investigations of the DC electric field effect on thermal decomposition of biomass, formation of the axial flow of volatiles (CO, H2, CxHy), mixing of volatiles with swirling airflow at low swirl intensity (S ≈ 0.2-0.35), their ignition and on formation of combustion dynamics are carried out with the aim to understand the mechanism of electric field influence on biomass gasification, combustion of volatiles and heat energy production. The DC electric field effect on combustion dynamics was studied by varying the positive bias voltage of the central electrode from 0.6 kV to 3 kV, whereas the ion current was limited to 2 mA. The results of experimental investigations confirm the field-enhanced biomass gasification with enhanced release of volatiles and the development of endothermic processes at the primary stage of thermochemical conversion of biomass determining the field-enhanced heat energy consumption with the correlating decrease of the flame temperature and heat energy production at this stage of flame formation. Further, the field-enhanced radial expansion of the flame reaction zone correlates with a more complete combustion of volatiles increasing the combustion efficiency by 3 % and decreasing the mass fraction of CO, H2 and CxHy in the products, whereas by 10 % increases the average volume fraction of CO2 and the heat energy production downstream the combustor increases by 5-10 %

Keywords: biomass, combustion, electrodynamic control, gasification

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Authors: Mahdi Motahari, Mojtaba Farzaneh, Ebrahim Sepidbar

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Tracking of moving and flying targets is one of the most important issues in image processing topic. Estimating of trajectory of desired object in short-term and long-term scale is more important than tracking of moving and flying targets. In this paper, a new way of identifying and estimating of future trajectory of a moving ball in long-term scale is estimated by using synthesis and interaction of image processing algorithms including noise removal and image segmentation, Kalman filter algorithm in order to estimating of trajectory of ball in football game in short-term scale and intelligent adaptive neuro-fuzzy algorithm based on time series of traverse distance. The proposed system attain more than 96% identify accuracy by using aforesaid methods and relaying on aforesaid algorithms and data base video in format of synthesis and interaction. Although the present method has high precision, it is time consuming. By comparing this method with other methods we realize the accuracy and efficiency of that.

Keywords: tracking, signal processing, moving targets and flying, artificial intelligent systems, estimating of trajectory, Kalman filter

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Authors: Peter Ugbedeojo Nelson

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Despite the tremendous advancements and knowledge acquisition around entrepreneurship orientation (EO) research, there may still be more to learn on how environmental dynamics would permute organizational processes and determine the extent to which success would be achieved. Using the contingency theory, we test a model that proposes a moderating influence of external relational capital and environmental hostility on the EO-performance effect of 423 managers/owners of small and medium scale enterprises. The hypotheses were tested using Hayes simultaneous regression, and the results showed that all EO dimensions (risk-taking, innovation, and performance) had a main effect on performance while the moderating variables interacted well with risk-taking (more than other EO dimensions) to improve performance. However, external relational capital, more than environmental hostility, influences the EO-performance relationship. Our findings highlight the differential ways that EO dimensions interact with environmental contingencies to influence performance. Further studies can examine how competitive aggressiveness and autonomy are moderated by external relational capital and environmental hostility.

Keywords: external relational capital, entrepreneurial orientation, risk-taking, innovation, proactiveness

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Authors: Andrew R. Winters, Gregor J. Gassner

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A high-order numerical magentohydrodynamics (MHD) solver built upon a non-linear entropy stable numerical flux function that supports eight traveling wave solutions will be described. The method is designed to treat the divergence-free constraint on the magnetic field in a similar fashion to a hyperbolic divergence cleaning technique. The solver is especially well-suited for flows involving strong discontinuities due to its strong stability without the need to enforce artificial low density or energy limits. Furthermore, a new formulation of the numerical algorithm to guarantee positivity of the pressure during the simulation is described and presented. By construction, the solver conserves mass, momentum, and energy and is entropy stable. High spatial order is obtained through the use of a third order limiting technique. High temporal order is achieved by utilizing the family of strong stability preserving (SSP) Runge-Kutta methods. Main attributes of the solver are presented as well as details on an implementation of the new solver into the multi-physics, multi-scale simulation code FLASH. The accuracy, robustness, and computational efficiency is demonstrated with a variety of numerical tests. Comparisons are also made between the new solver and existing methods already present in FLASH framework.

Keywords: entropy stability, finite volume scheme, magnetohydrodynamics, pressure positivity

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Authors: Wu Defu, Kiefer Chiam, Yang Kin Seng

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The planning of geological survey works is an iterative process which involves planner, geologist, civil engineer and other stakeholders, who perform different roles and have different points of view. Traditionally, the team used paper maps or CAD drawings to present the proposal which is not an efficient way to present and share idea on the site investigation proposal such as sitting of borehole location or seismic survey lines. This paper focuses on how a GIS approach can be utilised to develop a web-based system to support decision making process in the planning of geological survey works and also to plan site activities carried out by Singapore Geological Office (SGO). The authors design a framework of building an interactive web-based GIS system, and develop a prototype, which enables the users to obtain rapidly existing geological information and also to plan interactively borehole locations and seismic survey lines via a web browser. This prototype system is used daily by SGO and has shown to be effective in increasing efficiency and productivity as the time taken in the planning of geological survey works is shortened. The prototype system has been developed using the ESRI ArcGIS API 3.7 for Flex which is based on the ArcGIS 10.2.1 platform.

Keywords: engineering geology, flex, geological survey planning, geoscience, GIS, site investigation, WebGIS

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Authors: Myeong Hee Jeong, Man Young Kim

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The use of perforated plate and tubes is common in applications such as vehicle exhaust silencers, attenuators in air moving ducts and duct linings in jet engines. Also, perforated plate flow conditioners designed to improve flow distribution upstream of an orifice plate flow meter typically have 50–60% free area but these generally employ a non-uniform distribution of holes of several sizes to encourage the formation of a fully developed pipe flow velocity distribution. In this study, therefore, numerical investigations on the flow characteristics with the various perforated plates have been performed and then compared to the case without a perforated plate. Three different models are adopted such as a flat perforated plate, a convex perforated plate in the direction of the inlet, and a convex perforated plate in the direction of the outlet. Simulation results show that the pressure drop with and without perforated plates are similar each other. However, it can be found that that the different shaped perforated plates influence the velocity contour, flow uniformity index, and location of the fully developed fluid flow. These results can be used as a practical guide to the best design of pipe with the perforated plate.

Keywords: perforated plate, flow uniformity, pipe turbulent flow, CFD (Computational Fluid Dynamics)

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Authors: K. N. Kipreou, E. Efthmiadou, G. Kordas

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Biofouling represents one of the most crucial problems in the present maritime industries when its control still challenges the researchers all over the world. The present work is referred to the synthesis and characterization CeMo and Cu2O nanocontainers by using a wide range of techniques including scanning electron microscopy (SEM), X-ray diffraction (XRD) and thermogravimetric analysis (TGA) for marine applications. The above nanosystems will be loaded with active monomers and corrosion rendering healing ability to marine paints. The objective of this project is their ability for self-healing, self-polishing and finally for anti-corrosion activity. One of the driving forces for the exploration of CeMo, is the unique anticorrosive behavior, which will be confirmed by the electrochemistry methodology. It has be highlighted that the nanocontainers of Cu2O with the appropriate antibacterial inhibitor will improve the hydrophobicity and the morphology of the coating surfaces reducing the water friction. In summary, both novel nanoc will increase the lifetime of the paints releasing the antifouling agent in a control manner.

Keywords: marinepaints, nanocontainer, antifouling, anticorrosion, copper, electrochemistry, coating, biofouling, inhibitors, copper oxide, coating, SEM

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Authors: Hamnah Nisar

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As food is something which is particularly important for survival, in fact, it improves the quality of life and promotes health. Quality food is a key to a healthy life. Consumption of food depends on the knowledge we have regarding the nutrients it contains. Moreover, the awareness and knowledge about something is an initial stage for its improvement. We cannot work on anything unless we have knowledge about it. The pros and cons, effects, causes, dos, and don'ts, especially for an important things like food, are a necessity to learn. That is why my research would be all about analyzing what difference awareness makes on people and how making people more aware about a certain thing can help them improve their lifestyles and bring a positive change for them. The research would be done through questionnaires and interviews among two classes, one would be the upper class and the other would-be lower class. Because the upper class can easily access learning facilities and can know about the new things than the lower class. The questions would be related to what kind of food do they consume, what health issues they face, or what health issues are common among their regions. The results of the research would be helpful to know firstly the effects of awareness and education regarding food on health, how a basic thing like knowledge can have a significant effect on health and can be the cause of several diseases.

Keywords: nutrition, awareness, quality food, knowledge

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Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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Authors: Aurelija Burinskiene

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This paper presents the study for an e-commerce warehouse. The study is aiming to improve order fulfillment activity by identifying the strategy presenting the best performance. A simulation model was proposed to reach the target of this research. This model enables various scenario tests in an e-commerce warehouse, allowing them to find out for the best order fulfillment strategy. By using simulation, model authors investigated customers’ orders representing on-line purchases for one month. Experiments were designed to evaluate various order picking methods applicable to the fulfillment of customers’ orders. The research uses cost components analysis and helps to identify the best possible order picking method improving the overall performance of e-commerce warehouse and fulfillment service to the customers. The results presented show that the application of order batching strategy is the most applicable because it brings distance savings of around 6.7 percentage. This result could be improved by taking an assortment clustering action until 8.34 percentage. So, the recommendations were given to apply the method for future e-commerce warehouse operations.

Keywords: e-commerce, order, fulfilment, strategy, simulation

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Authors: Hee Soo Kim, Ha Young Kyung

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Happiness and pleasure are a result of dopamine, oxytocin, serotonin, and endorphin levels in the body. In order to increase the four neurochemical levels, it is important to associate daily activities with its corresponding neurochemical releases. This includes setting goals, maintaining social relationships, laughing frequently, and exercising regularly. The likelihood of experiencing happiness increases when all four neurochemicals are released at the optimal level. The achievement of happiness is important because it increases healthiness, productivity, and the ability to overcome adversity. To process emotions, electrical brain waves, brain structure, and neurochemicals must be analyzed. This research uses Chemcraft and Avogadro to determine the theoretical and chemical properties of the four neurochemical molecules. Each neurochemical molecule’s thermodynamic stability is calculated to observe the efficiency of the molecules. The study found that among dopamine, oxytocin, serotonin, alpha-, beta-, and gamma-endorphin, beta-endorphin has the lowest optimized energy of 388.510 kJ/mol. Beta-endorphin, a neurotransmitter involved in mitigating pain and stress, is the most thermodynamically stable and efficient molecule that is involved in the process of happiness. Through examining such properties of happiness neurotransmitters, the science of happiness is better understood.

Keywords: happiness, neurotransmitters, positive psychology, dopamine, oxytocin, serotonin, endorphins

Procedia PDF Downloads 154

Authors: Farid Benkaci-Alia, Abdelhamid Neggada, Sophie Laurentb

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A new extraction method of polyphenols from honey using a biodegradable resin was developed and compared with the common commercial resin amberlite XAD2. For this purpose, three honey samples of Algerian origin were selected for the different physico-chemical and biochemical parameters study. After extraction of the target compounds by both resins, the polyphenol content was determined, the antioxidant activity was tested, and LC-MS analyses were performed for identification and quantification. The results showed that physico-chemical and biochemical parameters meet the norms of the International Honey commission, and the H1 sample seemed to be of high quality. The optimal conditions of extraction by biodegradable resin were a pH of 3, an adsorption dose of 40 g/L, a contact time of 50 min, an extraction temperature of 60°C and no stirring. The regeneration and reuse number of both resins was three cycles. The polyphenol contents demonstrated a higher extraction efficiency of biosorbent than of XAD2, especially in H1. LC-MS analyses allowed for the identification and quantification of fifteen compounds in the different honey samples extracted using both resins and the most abundant compound was 3,4,5-trimethoxybenzoic acid. In addition, the biosorbent extracts showed stronger antioxidant activities than the XAD2 extracts.

Keywords: extraction, polyphénols, biosorbent, resin amberlite, HPLC-MS

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Authors: Erkihun Zelalem

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Ethiopian’s sheep population, estimated to be 25.5 million heads, is found widely distributed across the diverse agro-ecological zones of the country. In the past, there were many projects that done to improve production of meat, milk and productivity of sheep breed. However, no significance research has been done so far on production of wool fiber in Ethiopia which could be taken as a potential fiber next to cotton. The measurement of the sheep wool fiber physical properties is critically important, technical, commercial and certification point of view. A total of 24 sheep from different breeds (Menz, Tikur, Farta and Washera) were used in this study. Samples of fiber were analyzed using standard measurements for wool fiber length (WFL), mean fiber diameter (MFD), coefficient of variation of wool fiber diameter (FDCV), breaking strength, elongation, crimp, cleanness and moisture content. Based on the result all parameters shows that there is a great potential of getting of wool fiber from the skin of sheep and according to the standards of its property and grading system based on wool fiber fineness is medium to course. These types of fibers can be making carpets, blankets, rugs, coverings and other products.

Keywords: Fiber, Fineness, Carpet, Fleece, Raw Wool

Procedia PDF Downloads 164

Authors: Reynaldo Esquivel, Pedro Hernandez, Aaron Martinez-Higareda, Sergio Tena-Cano, Enrique Alvarez-Ramos, Armando Lucero-Acuna

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Stimuli-responsive nanomaterials play an essential role in loading, transporting and well-distribution of anti-cancer compounds in the cellular surroundings. The outstanding properties as the Lower Critical Solution Temperature (LCST), hydrolytic cleavage and protonation/deprotonation cycle, govern the release and delivery mechanisms of payloads. In this contribution, we experimentally determine the load efficiency and release of antineoplastic Vincristine Sulfate into PNIPAM-Interpenetrated-Chitosan (PIntC) nanoparticles. Structural analysis was performed by Fourier Transform Infrared Spectroscopy (FT-IR) and Proton Nuclear Magnetic Resonance (1HNMR). ζ-Potential (ζ) and Hydrodynamic diameter (DH) measurements were monitored by Electrophoretic Mobility (EM) and Dynamic Light scattering (DLS) respectively. Mathematical analysis of the release pharmacokinetics reveals a three-phase model above LCST, while a monophasic of Vincristine release model was observed at 32 °C. Cytotoxic essays reveal a noticeable enhancement of Vincristine effectiveness at low drug concentration on HeLa cervix cancer and MDA-MB-231 breast cancer.

Keywords: nanoparticles, vincristine, drug delivery, PNIPAM

Procedia PDF Downloads 156

Authors: Mohsin Ali Shaikh, Song Weiguo, Muhammad Kashan Surahio, Usman Shahid, Rehmat Karim

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This study investigated a catastrophic arson fire incident that occurred at a textile garment building in Karachi, Pakistan. Unfortunately, a catastrophic event led to the loss of 262 lives and caused 55 severe injuries. The primary objective is to analyze the aspects of the fire incident and understand the causes of arson fire disasters. The study utilized Fire Dynamic Simulation (F.D.S) was employed to simulate fire propagation, visibility, harmful gas concentration, fire temperature, and numerical results. The analysis report has determined the specific circumstances that created the unpleasant incident in the present study. The significance of the current findings lies in their potential to prevent arson fires, improve fire safety measures, and the development of safety plans in building design. The fire dynamic simulation findings can serve as a theoretical basis for the investigation of arson fires and evacuation planning in textile garment buildings.

Keywords: investigation, fire arson incident, textile garment, fire dynamic simulation (FDS)

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Authors: Farzad Vakili-Farahani, Joern Lungershausen, Kilian Wasmer

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Wobbled laser beam welding, fast oscillations of a tiny laser beam within a designed path (weld geometry) during the laser pulse illumination, opens new possibilities to improve the marco-to micro-manufacturing process. The present work introduces the wobbled laser beam welding as a robust welding strategy for improving macro-to micro-fabrication process, e.g., the laser processing for gap-bridging and packaging industry. The typical requisites and relevant equipment for the development of a wobbled laser processing unit are addressed, including a suitable laser source, light delivery system, optics, proper beam deflection system and the design geometry. In addition, experiments have been carried out on titanium plate to compare the results of wobbled laser welding with conventional pulsed laser welding. As compared to the pulsed laser welding, the wobbled laser welding offers a much greater fusion area (i.e. additional molten material) while minimizing the HAZ and provides a better confinement of the material microstructural changes.

Keywords: wobbled laser beam welding, wobbling function, beam oscillation, micro welding

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Authors: Nayden Chivarov, Denis Chikurtev, Kaloyan Yovchev, Nedko Shivarov

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This paper represents methods for improving the efficiency and precision of service mobile robot. This robot is used for increasing the quality of life of elderly and disabled people. The key concept of the proposed Intelligent Service Mobile Robot is its easier adaptability to achieve services for a wide range of Elderly or Disabled Person’s needs, by performing different tasks for supporting Elderly or Disabled Persons care. We developed robot autonomous navigation and computer vision systems in order to recognize different objects and bring them to the people. Web based user interface is developed to provide easy access and tele-control of the robot by any device through the internet. In this study algorithms for object recognition and localization are proposed for providing successful object recognition and accuracy in the positioning. Different methods for sending movement commands to the mobile robot system are proposed and evaluated. After executing some experiments to show the results of the research, we can summarize that these systems and algorithms provide good control of the service mobile robot and it will be more useful to help the elderly and disabled persons.

Keywords: service robot, mobile robot, autonomous navigation, computer vision, web user interface, ROS

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Authors: H. M. Wang, C. J. Chang

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As the threat of global climate change is more seriously, "net zero emissions by 2050" has become a common global goal. In order to reduce the consumption of petrochemical raw materials and reduce carbon emissions, low-carbon fiber materials have become key materials in the future global textile supply chain. This project uses polyolefin raw materials to modify through synthesis and amination to develop low-temperature dyeable polypropylene fibers, endow them with low-temperature dyeability and high color fastness that can be combined with acid dyes, and improve the problem of low coloring strength. The color fastness to washing can reach the requirement of commerce with 3.5 level or more. Therefore, we realize the entry of polypropylene fiber into the clothing textile supply chain, replace existing fiber raw materials, solve the problem of domestic chemical fiber, textile, and clothing industry's plight of no low-carbon alternative new material sources, and provide the textile industry with a solution to achieve the goal of net zero emissions in 2050.

Keywords: acid dyes, dyeing, low-temperature, polypropylene fiber

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Authors: Muhammad Raqib Rasul, Tavga Sulaiman Rashid

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Fertilization increases efficiency and obtains better quality of product recovery in agricultural activities. However, fertilizer consumption increased exponentially throughout the world, causing severe environmental problems. Biofertilizers can be a practical approach to minimize chemical fertilizer sources and ultimately develop soil fertility. This study was carried out to isolate, identify and characterize bacteria from medicinal plant (Rumex tuberosus L. and Verbascum sp.) rhizosphere for in vivo screening. 25 bacterial isolates were isolated and several biochemical tests were performed. Two isolates that were positive for most biochemical tests were chosen for the field experiment. The isolates were identified as Go1 Alcaligenes faecalis (Accession No. OP001725) and T11 (Bacillus sp.) based on the 16S rRNA sequence analysis that was compared with related bacteria in GenBank database using MEGA 6.1. For the field trial isolate GO1 and T11 (separately and mixed), NPK as a positive control was used. Both isolates increased plant height, chlorophyll content, number of tubers, and tuber’s weight. The results demonstrated that these two isolates of bacteria can potentially replace with chemical fertilizers for potato production.

Keywords: biofertilizer, Bacillus subtilis, Alcaligenes faecalis, potato tubers, in vivo screening

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Authors: Madhujit Deb, G. R. K. Sastry, R. S. Panua, Rahul Banerjee, P. K. Bose

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The present work attempts to investigate the combustion, performance and emission characteristics of an existing single-cylinder four-stroke compression-ignition engine operated in dual-fuel mode with hydrogen as an alternative fuel. Environmental concerns and limited amount of petroleum fuels have caused interests in the development of alternative fuels like hydrogen for internal combustion (IC) engines. In this experimental investigation, a diesel engine is made to run using hydrogen in dual fuel mode with diesel, where hydrogen is introduced into the intake manifold using an LPG-CNG injector and pilot diesel is injected using diesel injectors. A Timed Manifold Injection (TMI) system has been developed to vary the injection strategies. The optimized timing for the injection of hydrogen was 100 CA after top dead center (ATDC). From the study it was observed that with increasing hydrogen rate, enhancement in brake thermal efficiency (BTHE) of the engine has been observed with reduction in brake specific energy consumption (BSEC). Furthermore, Soot contents decrease with an increase in indicated specific NOx emissions with the enhancement of hydrogen flow rate.

Keywords: diesel engine, hydrogen, BTHE, BSEC, soot, NOx

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Authors: Samar Alkindy

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Purpose: The BIM model has been used to support the planning of different construction projects in the industry by showing the different stages of the construction process. The model has been instrumental in identifying some of the common errors in the construction process through the spatial arrangement. The continuous use of the BIM model in the construction industry has resulted in various radical changes such as virtual prototyping. Construction virtual prototyping is a highly advanced technology that incorporates a BIM model with realistic graphical simulations, and facilitates the simulation of the project before a product is built in the factory. The paper presents virtual prototyping in the construction industry by examining its application, challenges and benefits to a construction project. Methodology approach: A case study was conducted for this study in four major construction projects, which incorporate virtual construction prototyping in several stages of the construction project. Furthermore, there was the administration of interviews with the project manager and engineer and the planning manager. Findings: Data collected from the methodological approach shows a positive response for virtual construction prototyping in construction, especially concerning communication and visualization. Furthermore, the use of virtual prototyping has increased collaboration and efficiency between construction experts handling a project. During the planning stage, virtual prototyping has increased accuracy, reduced planning time, and reduced the amount of rework during the implementation stage. Irrespective of virtual prototyping being a new concept in the construction industry, the findings outline that the approach will benefit the management of construction projects.

Keywords: construction operations, construction planning, process simulation, virtual prototyping

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Authors: Sharad Singh, Ajay Kumar Sinha

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Coupled dampers like viscoelastic-frictional dampers for supplemental damping are a newer technique. In this paper, innovative Visco-frictional damping models have been presented and investigated. This paper attempts to couple frictional and fluid viscous dampers into a single unit of supplemental dampers. Visco-frictional damping model is developed by series and parallel coupling of frictional and fluid viscous dampers using Maxwell and Kelvin-Voigat models. The time analysis has been performed using numerical simulation on an SDOF system with varying fundamental periods, subject to a set of 12 ground motions. The simulation was performed using the direct time integration method. MATLAB programming tool was used to carry out the numerical simulation. The response behavior has been analyzed for the varying time period and added damping. This paper compares the response reduction behavior of the two modes of coupling. This paper highlights the performance efficiency of the suggested damping models. It also presents a mathematical modeling approach to visco-frictional dampers and simultaneously suggests the suitable mode of coupling between the two sub-units.

Keywords: hysteretic damping, Kelvin model, Maxwell model, parallel coupling, series coupling, viscous damping

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Authors: Ajay Kumar Choubey, Geeta Agnihotri, C. Sasikumar, Rashmi Dwivedi

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Deep-drawing operations are performed widely in industrial applications. It is very important for efficiency to achieve parts with no or minimum defects. Deep drawn parts are used in high performance, high strength and high reliability applications where tension, stress, load and human safety are critical considerations. Wrinkling is a kind of defect caused by stresses in the flange part of the blank during metal forming operations. To avoid wrinkling appropriate blank-holder pressure/force or drawbead can be applied. Now-a-day computer simulation plays a vital role in the field of manufacturing process. So computer simulation of manufacturing has much advantage over previous conventional process i.e. mass production, good quality of product, fast working etc. In this study, a two dimensional elasto-plastic Finite Element (F.E.) model for Mild Steel material blank has been developed to study the behavior of the flange wrinkling and deep drawing parameters under different Blank-Holder Pressure (B.H.P.). For this, commercially available Finite Element software ANSYS 14 has been used in this study. Simulation results are critically studied and salient conclusions have been drawn.

Keywords: ANSYS, deep drawing, BHP, finite element simulation, wrinkling

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Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

Abstract:

Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

Abstract:

Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

Procedia PDF Downloads 128