Search results for: improve efficiency

Authors: C. G. Jinimole, A. Harsha

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One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.

Keywords: computed tomography, enhancement techniques, increasing contrast, PSNR and MSE

Procedia PDF Downloads 294

Authors: Abdull Halim Abdull, Nasiman Sapari, Mohammad Haikal Asyraf Bin Anuar

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Although soil thermal properties are required in many areas to improve oil recovery, they are seldom measured on a routine basis. Reasons for this are unclear, but may be related to a lack of suitable instrumentation and entropy theory. We integrate single probe thermal gradient for the radial conduction of a short-duration heat pulse away from a single electrode source, and compared it with the theory for an instantaneously heated line source. By measuring the temperature response at a short distance from the line source, and applying short-duration heat-pulse theory, we can extract all the entropy properties, the thermal diffusivity, heat capacity, and conductivity, from a single heat-pulse measurement. Results of initial experiments carried out on air-dry sand and clay materials indicate that this heat-pulse method yields soil thermal properties that compare well with thermal properties measured by single electrode.

Keywords: entropy, single probe thermal gradient, soil thermal, probe heat

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Authors: Mitra Ghiasi, Roghayeh Ghorbani Bousari

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Nowadays, the aim of the organizations is to gain sustainable competitive. So, developing their intellectual capital, encouraging innovation, increasing suitable performance can be done by knowledge management. Knowledge turns into science if knowledge is used to improve decision making, decision quality and make effective decisions. The current research intends to investigate the relationship between cybernetics and knowledge management from the perspective of users who are members of electronic discussion groups (ALA, ALIA). The research methodology is survey method, and it is a type of correlation research. Cybernetics and knowledge management questionnaires used for collecting data. The questionnaire that was designed in electronic format, distributed among two electronic discussion groups during 30 days and completed by 100 members of each electronic discussion groups. The finding of this research showed that although cybernetics has an impact on knowledge management, there is no significant difference between the ALA and ALIA user's view regard to effect of cybernetics on knowledge management. The results also indicated that this conceptual model is consistent with the data collected from the sample.

Keywords: ALA discussion group, ALIA discussion group, cybernetics, knowledge management

Procedia PDF Downloads 227

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

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Authors: Ibrahim Watad, Ibrahim Abdulhalim

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Conventional spectroscopic surface plasmon resonance (SPR) sensors are widely used, both in fundamental research and environmental monitoring as well as healthcare diagnostics. However, they still lack the low limit of detection (LOD) and there still a place for improvement. SPR conventional sensors are based on the detection of a dip in the reflectivity spectrum which is relatively wide. To improve the performance of these sensors, many techniques and methods proposed either to reduce the width of the dip or to increase the sensitivity. Together with that, profiting from the sharp jump in the phase spectrum under SPR, several works suggested the extraction of the phase of the reflected wave. However, existing phase measurement setups are in general more complicated compared to the conventional setups, require more stability and are very sensitive to external vibrations and noises. In this study, a simple polarimetric technique for phase extraction under SPR is presented, followed by a theoretical error analysis and an experimental verification. The advantages of the proposed technique upon existing techniques will be elaborated, together with conclusions regarding the best polarimetric function, and its corresponding optimal metal layer range of thicknesses to use under the conventional Kretschmann-Raether configuration.

Keywords: plasmonics, polarimetry, thin films, optical sensors

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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

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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: 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: Vivian Guo, Yan Qu

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Online marketplaces are not only digital places where consumers buy and sell merchandise, and they are also destinations for brands to connect with real consumers at the moment when customers are in the shopping mindset. For many marketplaces, brands have been important partners through advertising. There can be, however, a risk of advertising impacting a consumer’s shopping journey if it hurts the use experience or takes the user away from the site. Both could lead to the loss of transaction revenue for the marketplace. In this paper, we present user-based methods for cannibalization control by selectively turning off ads to users who are likely to be cannibalized by ads subject to business objectives. We present ways of measuring cannibalization of advertising in the context of an online marketplace and propose novel ways of measuring cannibalization through purchase propensity and uplift modeling. A/B testing has shown that our methods can significantly improve user purchase and engagement metrics while operating within business objectives. To our knowledge, this is the first paper that addresses cannibalization mitigation at the user-level in the context of advertising.

Keywords: cannibalization, machine learning, online marketplace, revenue optimization, yield optimization

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Authors: Laatra Zemmouri, Said Boukhechem, Samia Haffaf, Mohamed Lafri

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A study was conducted in order to determine the prevalence and risk factors associated with abortion in ewes in the region of M’sila, located in central-eastern Algeria. A questionnaire was carried out to obtain information about the occurrence of abortion, sheep housing conditions, vaccination, feeding and management practices, and whether the farmers kept other livestock. This cross-sectional study was conducted for 36 months (between 2016 and 2019). A total of 71 sheep flocks were visited. Among 8168 ewes, we recorded 734 (8.99%) abortions and 3861 lambings. The risk factor analysis using multivariable logistic regression showed an association between abortion and vaccination against brucellosis (CI 95%= 2,76-1,35; p<0,001). Abortion decreased when dogs are owned (CI 95%= 0,36-0,84; p= 0.006), however, abortion increased with the presence of cats in farms (CI 95%= 1,24-2,8; p=0.003). There was a significant association between abortion and keeping goats (CI 95%= 1,18-2,40; p= 0.004), bovins (CI 95%= 0,3-0,68; p<0,001) and poultry CI 95%= 0,39-0,77; p= 0.001) in farms. Through this study, it is noticed that a strong association between the occurrence of abortion and estrus synchronization, stillbirth occurrence, and feed supplementation (p<0.05). Identification of the causes of abortion is an important task to reduce foetal losses and to improve livestock productivity.

Keywords: abortion, ewes, questionnaire, risk factors

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Authors: Chutikarn Sriviboon

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The objectives of this research were to study the operation of the Labor Fund and to investigate the needs for money and assistance from Thai laborers both from within the system and out of the system and to compare between the assistance from domestic and international funds. The population of this study included three labor groups: group one was laborer in the system who were the members of saving cooperative, group two was laborer in the system who were not the members of saving cooperative, and group three was laborer who were not in the system. This was a mixed research of quantitative and qualitative methods. The findings can be categorized into four parts. First, the labor fund was beneficial to Thai laborers by giving access to government funds but the weakness was found to be poor public relations. Second, the labor funds should extend their assistance to laborer in the system who was not the members of saving cooperative. Third, the comparison between domestic labor funds and international labor funds revealed that there were no international funds which provided assistance the same way as Thai labor funds. Finally, there was a need to improve the management of labor funds and to provide long term assistance to Thai labors.

Keywords: effectiveness, quality, labor funds, service

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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: 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

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Authors: Riam Almaqrn, Abdulrahman Alshabeb

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The study aims to examine the attitudes of Saudi students of English towards proper pronunciation and towards podcasts as a facilitator for proper pronunciation. In order to fulfill the purpose of the study, twenty-three students participated in this study. The study used a questionnaire as the main data collection instrument. The questionnaire included two parts, one or proper pronunciation and the other for podcasts. Data analysis showed that the participants, in spite of the low rate of improvement in their pronunciation, had positive attitudes towards proper pronunciation of English. This outcome is compatible with previous studies` results that assert the fact that having a positive attitude towards a particular language and its speakers can improve pronunciation. As for podcasts, students received a total of five podcasts related to their listening and speaking textbook. At the end of the project, students showed high rate of acceptance for podcasts and positive attitudes towards them. The findings proved the usefulness of examining learners` attitudes towards new CALL applications before using them in a practical way. In the light of the findings, pedagogical implications and suggestions were presented for language instructors and academics.

Keywords: CALL, MALL, podcast, learning English

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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: 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

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Authors: Shaohua Li, Aihua Zhang, Kelly Zatopek, Saba Parvez, Andrew F. Gardner, Ivan R. Corrêa Jr., Christopher J. Noren, Ming-Qun Xu

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Covalent immobilization of enzymes on solid supports is an alternative approach to biocatalysis with the added benefits of simple enzyme removal, improved stability, and adaptability to automation and high-throughput applications. Nevertheless, immobilized enzymes generally suffer from reduced activities compared to their soluble counterparts. One major factor leading to activity loss is the intrinsic hydrophobic property of the supporting material surface, which could result in the conformational change/confinement of enzymes. We report a strategy of utilizing flexible poly (ethylene oxide) (PEO) moieties as to improve the surface hydrophilicity of solid supports used for enzyme immobilization. DNA modifying enzymes were covalently conjugated to PEO-coated magnetic-beads. Kinetics studies proved that the activities of the covalently-immobilized DNA modifying enzymes were greatly enhanced by the PEO modification on the bead surface.

Keywords: immobilized enzymes, biocatalysis, poly(ethylene oxide), surface modification

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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: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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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

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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: Bongsoo Jeon, Jayoung Kim, Jihong Lee

Abstract:

Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor (exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit (IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.

Keywords: inertial measurement unit, laser range finder, real-time recognition of the ground shape, proprioceptive sensor

Procedia PDF Downloads 276

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 113

Authors: Andres M. Tuates Jr., Ofero A. Caparino

Abstract:

Plastics have achieved a dominant position in agriculture because of their transparency, lightness in weight, impermeability to water and their resistance to microbial attack. However, this generates a higher quantity of wastes that are difficult to dispose of by farmers. To address these problems, the project aim to develop and evaluate the biodegradable film for mango fruit bag during development. The PBS and starch were melt-blended in a twin-screw extruder and then blown into film extrusion machine. The physic-chemical-mechanical properties of biodegradable fruit bag were done following standard methods of test. Field testing of fruit bag was also conducted to evaluate its durability and efficiency field condition. The PHilMech-FiC fruit bag is made of biodegradable material measuring 6 x 8 inches with a thickness of 150 microns. The tensile strength is within the range of LDPE while the elongation is within the range of HDPE. It is projected that after thirty-six (36) weeks, the film will be totally degraded. Results of field testing show that the quality of harvested fruits using PHilMech-FiC biodegradable fruit bag in terms of percent marketable, non-marketable and export, peel color at the ripe stage, flesh color, TSS, oBrix, percent edible portion is comparable with the existing bagging materials such as Chinese brown paper bag and old newspaper.

Keywords: cassava starch, PBS, biodegradable, chemical, mechanical properties

Procedia PDF Downloads 261