Search results for: oil palm kernel shell
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 997

Search results for: oil palm kernel shell

307 Alternate Furrow Irrigation and Potassium Fertilizer on Seed Yield, Water Use Efficiency and Fatty Acids of Rapeseed

Authors: A. Bahrani

Abstract:

In order to study the effect of restricted irrigation systems and different potassium fertilizer on water use efficiency and yield of rapeseed (Brassica napus L.), an experiment was conducted in an arid area in Khuzestan, Iran in 2013. The main plots consisted of three irrigation methods: FI (full irrigation), alternate furrow irrigation (AFI) and fixed furrow irrigation (FFI). Each subplot received three rates of K fertiliser application: 0, 150 or 300 kg ha-1. The results showed that the plots receiving the full irrigation resulted in significantly higher grain yields, 1000-kernel weight and grain number per pod than both alternate treatments. However, the highest WUE were obtained in alternate furrow irrigation and 300 kg K ha-1 and the lowest one was found in the FI treatment and 0 kg K ha-1. Potassium application increased RWC in alternate furrow irrigation and fixed furrow irrigation than FI treatment. Maximum oil content was observed in those treatments where full irrigation was applied while minimum oil content was produced in FFI irrigated treatments. Potassium fertilizer also increased grain oil by 15 % than control. Deficit irrigation reduced oleic acid and erucic acid. However, oleic acid and linoleic acid increased with increasing of potassium.

Keywords: erucic acid, irrigation methods, linoleic acid, oil percent, oleic acid

Procedia PDF Downloads 259
306 Development of a Three-Dimensional-Flywheel Robotic System

Authors: Chung-Chun Hsiao, Yu-Kai, Ting, Kai-Yuan Liu, Pang-Wei Yen, Jia-Ying Tu

Abstract:

In this paper, a new design of spherical robotic system based on the concepts of gimbal structure and gyro dynamics is presented. Robots equipped with multiple wheels and complex steering mechanics may increase the weight and degrade the energy transmission efficiency. In addition, the wheeled and legged robots are relatively vulnerable to lateral impact and lack of lateral mobility. Therefore, the proposed robotic design uses a spherical shell as the main body for ground locomotion, instead of using wheel devices. Three spherical shells are structured in a similar way to a gimbal device and rotate like a gyro system. The design and mechanism of the proposed robotic system is introduced. In addition, preliminary results of the dynamic model based on the principles of planar rigid body kinematics and Lagrangian equation are included. Simulation results and rig construction are presented to verify the concepts.

Keywords: gyro, gimbal, lagrange equation, spherical robots

Procedia PDF Downloads 288
305 Effect of Liquid Additive on Dry Grinding for Desired Surface Structure of CaO Catalyst

Authors: Wiyanti Fransisca Simanullang, Shinya Yamanaka

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Grinding method was used to control the active site and to improve the specific surface area (SSA) of calcium oxide (CaO) derived from scallop shell as a sustainable resource. The dry grinding of CaO with acetone and tertiary butanol as a liquid additive was carried out using a planetary ball mill with a laboratory scale. The experiments were operated by stepwise addition with time variations to determine the grinding limit. The active site of CaO was measured by X-Ray Diffraction and FT-IR. The SSA variations of products with grinding time were measured by BET method. The morphology structure of CaO was observed by SEM. The use of liquid additive was effective for increasing the SSA and controlling the active site of CaO. SSA of CaO was increased in proportion to the amount of the liquid additive and the grinding time. The performance of CaO as a solid base catalyst for biodiesel production was tested in the transesterification reaction of used cooking oil to produce fatty acid methyl ester (FAME).

Keywords: active site, calcium oxide, grinding, specific surface area

Procedia PDF Downloads 268
304 Correction Requirement to AISC Design Guide 31: Case Study of Web Post Buckling Design for Castellated Beams

Authors: Kitjapat Phuvoravan, Phattaraphong Ponsorn

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In the design of Castellated beams (CB), the web post buckling acted by horizontal shear force is one of the important failure modes that have to be considered. It is also a dominant governing mode when design following the AISC 31 design guideline which is just published. However, the equation of the web post buckling given by the guideline is still questionable for most of the engineers. So the purpose of this paper is to study and provide a proposed equation for design the web post buckling with more simplified and convenient to use. The study is also including the improper of the safety factor given by the guideline. The proposed design equation is acquired by regression method based on the results of finite element analysis. An amount of Cellular beam simulated to study is modelled by using shell element, analysis with both geometric and material nonlinearity. The results of the study show that the use of the proposed equation to design the web post buckling in Castellated beams is more simple and precise for computation than the equations provided from the guideline.

Keywords: castellated beam, web opening, web post buckling, design equation

Procedia PDF Downloads 277
303 Properties of Bio-Phenol Formaldehyde Composites Filled with Empty Fruit Bunch Fiber

Authors: Sharifah Nabihah Syed Jaafar, Umar Adli Amran, Rasidi Roslan, Chia Chin Hua, Sarani Zakaria

Abstract:

Bio-composites derived from plant fiber and bio-derived polymer, are likely more ecofriendly and demonstrate competitive performance with petroleum based. In this research, the green phenolic resin was used as a matrix and oil palm empty fruit bunch fiber (EFB) was used as filler. The matrix was synthesized from soda lignin, phenol and hydrochloric acid as a catalyst. The phenolic resin was synthesized via liquefaction and condensation to enhance the combination of phenol during the process. Later, the phenolic resin was mixed with EFB by using mechanical stirrer and was molded with hot press at 180 oC. In this research, the composites were prepared with EFB content of 5%, 10%, 15% and 20%. The samples that viewed under scanning electron microscopy (SEM) showed that the EFB filler remained embedded in the resin. From impact and hardness testing, samples 10% of EFB showed the optimum properties meanwhile sample 15% showed the optimum properties for flexural testing. Thermal stability of the composites was investigated using thermogravimetric (TGA) analysis and found that the weight loss and the activation energy (Ea) of the composites samples were decreased as the filler content increased.

Keywords: EFB, liquefaction, phenol formaldehyde, lignin

Procedia PDF Downloads 563
302 Three Dimensional Vibration Analysis of Carbon Nanotubes Embedded in Elastic Medium

Authors: M. Shaban, A. Alibeigloo

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This paper studies free vibration behavior of single-walled carbon nanotubes (SWCNTs) embedded on elastic medium based on three-dimensional theory of elasticity. To accounting the size effect of carbon nanotubes, nonlocal theory is adopted to shell model. The nonlocal parameter is incorporated into all constitutive equations in three dimensions. The surrounding medium is modeled as two-parameter elastic foundation. By using Fourier series expansion in axial and circumferential direction, the set of coupled governing equations are reduced to the ordinary differential equations in thickness direction. Then, the state-space method as an efficient and accurate method is used to solve the resulting equations analytically. Comprehensive parametric studies are carried out to show the influences of the nonlocal parameter, radial and shear elastic stiffness, thickness-to-radius ratio and radius-to-length ratio.

Keywords: carbon nanotubes, embedded, nonlocal, free vibration

Procedia PDF Downloads 422
301 Silver-Doped Magnetite Titanium Oxide Nanoparticles for Photocatalytic Degradation of Organic Pollutants

Authors: Hanna Abbo, Siyasanga Noganta, Salam Titinchi

Abstract:

The global lack of clean water for human sanitation and other purposes has become an emerging dilemma for human beings. The presence of organic pollutants in wastewater produced by textile industries, leather manufacturing and chemical industries is an alarming matter for a safe environment and human health. For the last decades, conventional methods have been applied for the purification of water but due to industrialization these methods fall short. Advanced oxidation processes and their reliable application in degradation of many contaminants have been reported as a potential method to reduce and/or alleviate this problem. Lately it has been assumed that incorporation of some metal nanoparticles such as magnetite nanoparticles as photocatalyst for Fenton reaction which could improve the degradation efficiency of contaminants. Core/shell nanoparticles, are extensively studied because of their wide applications in the biomedical, drug delivery, electronics fields and water treatment. The current study is centred on the synthesis of silver-doped Fe3O4/SiO2/TiO2 photocatalyst. Magnetically separable Fe3O4@SiO2@TiO2 composite with core–shell structure were synthesized by the deposition of uniform anatase TiO2 NPs on Fe3O4@SiO2 by using titanium butoxide (TBOT) as titanium source. Then, the silver is doped on SiO2 layer by hydrothermal method. Integration of magnetic nanoparticles was suggested to avoid the post separation difficulties associated with the powder form of the TiO2 catalyst, increase of the surface area and adsorption properties. The morphology, structure, composition, and magnetism of the resulting composites were characterized and their photocatalytic activities were also evaluated. The results demonstrate that TiO2 NPs were uniformly deposited on the Fe3O4@SiO2 surface. The silver nanoparticles were also uniformly distributed on the surface of TiO2 nanoparticles. The aim of this work is to study the suitability of photocatalysis for the treatment of aqueous streams containing organic pollutants such as methylene blue which is selected as a model compound to represent one of the pollutants existing in wastewaters. Various factors such as initial pollutant concentration, photocatalyst dose and wastewater matrix were studied for their effect on the photocatalytic degradation of the organic model pollutants using the as synthesized catalysts and compared with the commercial titanium dioxide (Aeroxide P25). Photocatalysis was found to be a potential purification method for the studied pollutant also in an industrial wastewater matrix with the removal percentages of over 81 % within 15 minutes. Methylene blue was removed most efficiently and its removal consumed the least of energy in terms of the specific applied energy. The magnetic Ag/SiO2/TiO2 composites show high photocatalytic performance and can be recycled three times by magnetic separation without major loss of activity, which meant that they can be used as efficient and conveniently renewable photocatalyst.

Keywords: Magnetite nanoparticles, Titanium, Photocatalyst, Organic pollutant, Water treatment

Procedia PDF Downloads 245
300 Predictive Analytics of Student Performance Determinants

Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

Procedia PDF Downloads 96
299 Hot Spot Stress Analysis and Parametric Study on Rib-To-Deck Welded Connections in Orthotropic Steel Bridge Decks

Authors: Dibu Dave Mbako, Bin Cheng

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This paper study the stress variation of the welded joints in the rib-to-deck connection structure, the influence stress of the deck plate and u-rib thickness at different positions. A Finite-element model of orthotropic steel deck structure using solid element and shell element was established in ABAQUS. Under a single wheel load, the static response was analyzed to understand the structural behaviors and examine stress distribution. A parametric study showed that the geometric parameters have a significant effect on the hot spot stress at the weld toe, but has little impact on the stress concentration factor. The increase of the thickness of the deck plate will lead to the decrease of the hot spot stress at the weld toe and the maximum deflection of the deck plate. The surface stresses of the deck plate are significantly larger than those of the rib near the joint in the 80% weld penetration into the u-rib.

Keywords: orthotropic steel bridge deck, rib-to-deck connection, hot spot stress, finite element method, stress distribution

Procedia PDF Downloads 198
298 Globally Attractive Mild Solutions for Non-Local in Time Subdiffusion Equations of Neutral Type

Authors: Jorge Gonzalez Camus, Carlos Lizama

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In this work is proved the existence of at least one globally attractive mild solution to the Cauchy problem, for fractional evolution equation of neutral type, involving the fractional derivate in Caputo sense. An almost sectorial operator on a Banach space X and a kernel belonging to a large class appears in the equation, which covers many relevant cases from physics applications, in particular, the important case of time - fractional evolution equations of neutral type. The main tool used in this work was the Hausdorff measure of noncompactness and fixed point theorems, specifically Darbo-type. Initially, the equation is a Cauchy problem, involving a fractional derivate in Caputo sense. Then, is formulated the equivalent integral version, and defining a convenient functional, using the analytic integral resolvent operator, and verifying the hypothesis of the fixed point theorem of Darbo type, give us the existence of mild solution for the initial problem. Furthermore, each mild solution is globally attractive, a property that is desired in asymptotic behavior for that solution.

Keywords: attractive mild solutions, integral Volterra equations, neutral type equations, non-local in time equations

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297 Robust Medical Image Watermarking based on Contourlet and Extraction Using ICA

Authors: S. Saju, G. Thirugnanam

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In this paper, a medical image watermarking algorithm based on contourlet is proposed. Medical image watermarking is a special subcategory of image watermarking in the sense that images have special requirements. Watermarked medical images should not differ perceptually from their original counterparts because clinical reading of images must not be affected. Watermarking techniques based on wavelet transform are reported in many literatures but robustness and security using contourlet are better when compared to wavelet transform. The main challenge in exploring geometry in images comes from the discrete nature of the data. In this paper, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image. To extract the watermark, Kernel ICA is used and it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that proposed scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with Discrete Wavelet Transform (DWT) to prove the robustness of the scheme. Simulations are carried out using Matlab Software.

Keywords: digital watermarking, independent component analysis, wavelet transform, contourlet

Procedia PDF Downloads 508
296 Image Segmentation Using Active Contours Based on Anisotropic Diffusion

Authors: Shafiullah Soomro

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Active contour is one of the image segmentation techniques and its goal is to capture required object boundaries within an image. In this paper, we propose a novel image segmentation method by using an active contour method based on anisotropic diffusion feature enhancement technique. The traditional active contour methods use only pixel information to perform segmentation, which produces inaccurate results when an image has some noise or complex background. We use Perona and Malik diffusion scheme for feature enhancement, which sharpens the object boundaries and blurs the background variations. Our main contribution is the formulation of a new SPF (signed pressure force) function, which uses global intensity information across the regions. By minimizing an energy function using partial differential framework the proposed method captures semantically meaningful boundaries instead of catching uninterested regions. Finally, we use a Gaussian kernel which eliminates the problem of reinitialization in level set function. We use several synthetic and real images from different modalities to validate the performance of the proposed method. In the experimental section, we have found the proposed method performance is better qualitatively and quantitatively and yield results with higher accuracy compared to other state-of-the-art methods.

Keywords: active contours, anisotropic diffusion, level-set, partial differential equations

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295 Challenges Facing Farmers in the Governorate of Al-Baha, Saudi Arabia

Authors: Mohammed Alghamdi, Ghanem Al-Ghamdi

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The Governorate of Al-Baha is known for a history of farming that focused on plant products such as Date Palm, olives, figs, pomegranate and cereals as well as raising cattle, sheep, goats and to some extent camels for many decades. However, farmers have been facing with very significant natural and artificial challenges lately. The goal of this study was to determine the most significant challenges facing farmers in the Governorate of Al-Baha. Sixty farms were surveyed during the year of 2013. Farm survey focused on the farm management, farm financial status and governmental support. Our results showed that most farms were dedicated to farming with limited number of farms used parts of its premises for recreation. About 90% of farms were engaged in exclusively farming business. The financial status was good in most of the farms (80%), stable in 16% and hardly standing in less than 5%. Nearly 60% of the farms marketed 1-3 products and 23% marketed up to 6 products, 14% of the farms marketed up to 9 products and 4% marketed more than 9 products. Less than 14% had a chance to market their products over seven times per year while about 11% market their products and 32% of farms market 3-4 per year and 43% of farms market 1-2 per year. Our data showed that most farmers are in good financial status producing healthy food.

Keywords: farming system, Al-Baha, healthy food, Saudi Arabia

Procedia PDF Downloads 254
294 Survey of Methods for Solutions of Spatial Covariance Structures and Their Limitations

Authors: Joseph Thomas Eghwerido, Julian I. Mbegbu

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In modelling environment processes, we apply multidisciplinary knowledge to explain, explore and predict the Earth's response to natural human-induced environmental changes. Thus, the analysis of spatial-time ecological and environmental studies, the spatial parameters of interest are always heterogeneous. This often negates the assumption of stationarity. Hence, the dispersion of the transportation of atmospheric pollutants, landscape or topographic effect, weather patterns depends on a good estimate of spatial covariance. The generalized linear mixed model, although linear in the expected value parameters, its likelihood varies nonlinearly as a function of the covariance parameters. As a consequence, computing estimates for a linear mixed model requires the iterative solution of a system of simultaneous nonlinear equations. In other to predict the variables at unsampled locations, we need to know the estimate of the present sampled variables. The geostatistical methods for solving this spatial problem assume covariance stationarity (locally defined covariance) and uniform in space; which is not apparently valid because spatial processes often exhibit nonstationary covariance. Hence, they have globally defined covariance. We shall consider different existing methods of solutions of spatial covariance of a space-time processes at unsampled locations. This stationary covariance changes with locations for multiple time set with some asymptotic properties.

Keywords: parametric, nonstationary, Kernel, Kriging

Procedia PDF Downloads 233
293 Comparison of the Oxidative Stability of Chinese Vegetable Oils during Repeated Deep-Frying of French Fries

Authors: TranThi Ly, Ligang Yang, Hechun Liu, Dengfeng Xu, Haiteng Zhou, Shaokang Wang, Shiqing Chen, Guiju Sun

Abstract:

This study aims to evaluate the oxidative stability of Chinese vegetable oils during repeated deep-frying. For frying media, palm oil (PO), sunflower oil (SFO), soybean oil (SBO), and canola oil (CO) were used. French fries were fried in oils heated to 180 ± 50℃. The temperature was kept constant during the eight h of the frying process. The oil quality was measured according to the fatty acid (FA) content, trans fatty acid (TFA) compounds, and chemical properties such as peroxide value (PV), acid value (AV), anisidine value (AnV), and malondialdehyde (MDA). Additionally, the sensory characteristics such as color, flavor, greasiness, crispiness, and overall acceptability of the French fries were assessed. Results showed that the PV, AV, AnV, MDA, and TFA content of SFO, CO, and SBO significantly increased in conjunction with prolonged frying time. During the deep-frying process, the SBO showed the lowest oxidative stability at all indices, while PO retained oxidative stability and generated the lowest level of TFA. The French fries fried in PO also offered better sensory properties than the other oils. Therefore, results regarding oxidative stability and sensory attributes suggested that among the examined vegetable oils, PO appeared to be the best oil for frying food products.

Keywords: vegetable oils, French fries, oxidative stability, sensory properties, frying oil

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292 Forming Simulation of Thermoplastic Pre-Impregnated Textile Composite

Authors: Masato Nishi, Tetsushi Kaburagi, Masashi Kurose, Tei Hirashima, Tetsusei Kurasiki

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The process of thermoforming a carbon fiber reinforced thermoplastic (CFRTP) has increased its presence in the automotive industry for its wide applicability to the mass production car. A non-isothermal forming for CFRTP can shorten its cycle time to less than 1 minute. In this paper, the textile reinforcement FE model which the authors proposed in a previous work is extended to the CFRTP model for non-isothermal forming simulation. The effect of thermoplastic is given by adding shell elements which consider thermal effect to the textile reinforcement model. By applying Reuss model to the stress calculation of thermoplastic, the proposed model can accurately predict in-plane shear behavior, which is the key deformation mode during forming, in the range of the process temperature. Using the proposed model, thermoforming simulation was conducted and the results are in good agreement with the experimental results.

Keywords: carbon fiber reinforced thermoplastic, finite element analysis, pre-impregnated textile composite, non-isothermal forming

Procedia PDF Downloads 411
291 Atomic Clusters: A Unique Building Motif for Future Smart Nanomaterials

Authors: Debesh R. Roy

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The fundamental issue in understanding the origin and growth mechanism of nanomaterials, from a fundamental unit is a big challenging problem to the scientists. Recently, an immense attention is generated to the researchers for prediction of exceptionally stable atomic cluster units as the building units for future smart materials. The present study is a systematic investigation on the stability and electronic properties of a series of bimetallic (semiconductor-alkaline earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for exceptional and/ or unusual stable motifs. A very popular hybrid exchange-correlation functional, B3LYP as proposed by A. D. Becke along with a higher basis set, viz., 6-31+G[d,p] is employed for this purpose under the density functional formalism. The magic stability among the concerned clusters is explained using the jellium model. It is evident from the present study that the magic stability of B4Mg3 cluster arises due to the jellium shell closure.

Keywords: atomic clusters, density functional theory, jellium model, magic clusters, smart nanomaterials

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290 Arbitrarily Shaped Blur Kernel Estimation for Single Image Blind Deblurring

Authors: Aftab Khan, Ashfaq Khan

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The research paper focuses on an interesting challenge faced in Blind Image Deblurring (BID). It relates to the estimation of arbitrarily shaped or non-parametric Point Spread Functions (PSFs) of motion blur caused by camera handshake. These PSFs exhibit much more complex shapes than their parametric counterparts and deblurring in this case requires intricate ways to estimate the blur and effectively remove it. This research work introduces a novel blind deblurring scheme visualized for deblurring images corrupted by arbitrarily shaped PSFs. It is based on Genetic Algorithm (GA) and utilises the Blind/Reference-less Image Spatial QUality Evaluator (BRISQUE) measure as the fitness function for arbitrarily shaped PSF estimation. The proposed BID scheme has been compared with other single image motion deblurring schemes as benchmark. Validation has been carried out on various blurred images. Results of both benchmark and real images are presented. Non-reference image quality measures were used to quantify the deblurring results. For benchmark images, the proposed BID scheme using BRISQUE converges in close vicinity of the original blurring functions.

Keywords: blind deconvolution, blind image deblurring, genetic algorithm, image restoration, image quality measures

Procedia PDF Downloads 423
289 Ilorin Traditional Architecture as a Good Example of a Green Building Design

Authors: Olutola Funmilayo Adekeye

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Tradition African practice of architecture can be said to be deeply rooted in Green Architecture in concept, design and execution. A study into the ancient building techniques in Ilorin Emirate depicts prominent (eco-centric approach of) Green Architecture principles. In the Pre-colonial era before the introduction of modern architecture and Western building materials, the Nigeria traditional communities built their houses to meet their cultural, religious and social needs using mainly indigenous building materials such as mud (Amo), cowdung (Boto), straws (koriko), palm fronts (Imo-Ope) to mention a few. This research attempts to identify the various techniques of applying the traditional African principles of Green Architecture to Ilorin traditional buildings. It will examine and assess some case studies to understand the extent to which Green architecture principles have been applied to traditional building designs that are still preserved today in Ilorin, Nigeria. Furthermore, this study intends to answer many questions, which can be summarized into two basic questions which are: (1) What aspects of what today are recognized as important green architecture principles have been applied to Ilorin traditional buildings? (2) To what extent have the principles of green architecture applied to Ilorin traditional buildings been ways of demonstrating a cultural attachment to the earth as an expression of the African sense of human being as one with nature?

Keywords: green architecture, Ilorin, traditional buildings, design principles, ecocentric, application

Procedia PDF Downloads 517
288 Online Handwritten Character Recognition for South Indian Scripts Using Support Vector Machines

Authors: Steffy Maria Joseph, Abdu Rahiman V, Abdul Hameed K. M.

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Online handwritten character recognition is a challenging field in Artificial Intelligence. The classification success rate of current techniques decreases when the dataset involves similarity and complexity in stroke styles, number of strokes and stroke characteristics variations. Malayalam is a complex south indian language spoken by about 35 million people especially in Kerala and Lakshadweep islands. In this paper, we consider the significant feature extraction for the similar stroke styles of Malayalam. This extracted feature set are suitable for the recognition of other handwritten south indian languages like Tamil, Telugu and Kannada. A classification scheme based on support vector machines (SVM) is proposed to improve the accuracy in classification and recognition of online malayalam handwritten characters. SVM Classifiers are the best for real world applications. The contribution of various features towards the accuracy in recognition is analysed. Performance for different kernels of SVM are also studied. A graphical user interface has developed for reading and displaying the character. Different writing styles are taken for each of the 44 alphabets. Various features are extracted and used for classification after the preprocessing of input data samples. Highest recognition accuracy of 97% is obtained experimentally at the best feature combination with polynomial kernel in SVM.

Keywords: SVM, matlab, malayalam, South Indian scripts, onlinehandwritten character recognition

Procedia PDF Downloads 554
287 Production and Leftovers Usage Policies to Minimize Food Waste under Uncertain and Correlated Demand

Authors: Esma Birisci, Ronald McGarvey

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One of the common problems in food service industry is demand uncertainty. This research presents a multi-criteria optimization approach to identify the efficient frontier of points lying between the minimum-waste and minimum-shortfall solutions within uncertain demand environment. It also addresses correlation across demands for items (e.g., hamburgers are often demanded with french fries). Reducing overproduction food waste (and its corresponding environmental impacts) and an aversion to shortfalls (leave some customer hungry) need to consider as two contradictory objectives in an all-you-care-to-eat environment food service operation. We identify optimal production adjustments relative to demand forecasts, demand thresholds for utilization of leftovers, and percentages of demand to be satisfied by leftovers, considering two alternative metrics for overproduction waste: mass; and greenhouse gas emissions. Demand uncertainty and demand correlations are addressed using a kernel density estimation approach. A statistical analysis of the changes in decision variable values across each of the efficient frontiers can then be performed to identify the key variables that could be modified to reduce the amount of wasted food at minimal increase in shortfalls. We illustrate our approach with an application to empirical data from Campus Dining Services operations at the University of Missouri.

Keywords: environmental studies, food waste, production planning, uncertain and correlated demand

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286 Breeding Performance and Egg Quality of Red Jungle Fowl (Gallus Gallus L.) Mated with Native Hens (Gallus galus domesticus) in Selected Areas of Leyte under Confinement System

Authors: Francisco F. Buctot Jr.

Abstract:

This study was conducted to assess the breeding performance and egg quality traits of Red Jungle Fowls in selected areas of Leyte mated to Native hens under confinement system. A total of six Red Jungle Fowl roosters, two native roosters and 16 native hens were randomly assigned to four treatments with eight replications; each composed of one rooster and two hens randomly laid out in a Randomized Complete Block Design set up. Result on egg weight showed highly significant difference at p<0.01 and revealed heaviest weight (39.0 g) and lightest weight (35.75 g) on Native x Native and Baybay RJF x Native, respectively. While comparable number of eggs per clutch, fertility and hatchability rates, yolk and albumen weights, shell weight, egg length and width, egg shape index and yolk color score were obtained.

Keywords: egg clutch, egg shape index, native chicken, hatchability rate

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285 The Asymmetric Proximal Support Vector Machine Based on Multitask Learning for Classification

Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

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Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

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284 Physico-Chemical Characterization of Vegetable Oils from Oleaginous Seeds (Croton megalocarpus, Ricinus communis L., and Gossypium hirsutum L.)

Authors: Patrizia Firmani, Sara Perucchini, Irene Rapone, Raffella Borrelli, Stefano Chiaberge, Manuela Grande, Rosamaria Marrazzo, Alberto Savoini, Andrea Siviero, Silvia Spera, Fabio Vago, Davide Deriu, Sergio Fanutti, Alessandro Oldani

Abstract:

According to the Renewable Energy Directive II, the use of palm oil in diesel will be gradually reduced from 2023 and should reach zero in 2030 due to the deforestation caused by its production. Eni aims at finding alternative feedstocks for its biorefineries to eliminate the use of palm oil by 2023. Therefore, the ideal vegetable oils to be used in bio-refineries are those obtainable from plants that grow in marginal lands and with low impact on food-and-feed chain; hence, Eni research is studying the possibility of using oleaginous seeds, such as castor, croton, and cotton, to extract the oils to be exploited as feedstock in bio-refineries. To verify their suitability for the upgrading processes, an analytical protocol for their characterization has been drawn up and applied. The analytical characterizations include a step of water and ashes content determination, elemental analysis (CHNS analysis, X-Ray Fluorescence, Inductively Coupled Plasma - Optical Emission Spectroscopy, ICP– Mass Spectrometry), and total acid number determination. Gas chromatography coupled to flame ionization detector (GC-FID) is used to quantify the lipid content in terms of free fatty acids, mono-, di- and triacylglycerols, and fatty acids composition. Eventually, Nuclear Magnetic Resonance and Fourier Transform-Infrared spectroscopies are exploited with GC-MS and Fourier Transform-Ion Cyclotron Resonance to study the composition of the oils. This work focuses on the GC-FID analysis of the lipid fraction of these oils, as the main constituent and of greatest interest for bio-refinery processes. Specifically, the lipid component of the extracted oil was quantified after sample silanization and transmethylation: silanization allows the elution of high-boiling compounds and is useful for determining the quantity of free acids and glycerides in oils, while transmethylation leads to a mixture of fatty acid esters and glycerol, thus allowing to evaluate the composition of glycerides in terms of Fatty Acids Methyl Esters (FAME). Cotton oil was extracted from cotton oilcake, croton oil was obtained by seeds pressing and seeds and oilcake ASE extraction, while castor oil comes from seed pressing (not performed in Eni laboratories). GC-FID analyses reported that the cotton oil is 90% constituted of triglycerides and about 6% diglycerides, while free fatty acids are about 2%. In terms of FAME, C18 acids make up 70% of the total and linoleic acid is the major constituent. Palmitic acid is present at 17.5%, while the other acids are in low concentration (<1%). Both analyzes show the presence of non-gas chromatographable compounds. Croton oils from seed pressing and extraction mainly contain triglycerides (98%). Concerning FAME, the main component is linoleic acid (approx. 80%). Oilcake croton oil shows higher abundance of diglycerides (6% vs ca 2%) and a lower content of triglycerides (38% vs 98%) compared to the previous oils. Eventually, castor oil is mostly constituted of triacylglycerols (about 69%), followed by diglycerides (about 10%). About 85.2% of total FAME is ricinoleic acid, as a constituent of triricinolein, the most abundant triglyceride of castor oil. Based on the analytical results, these oils represent feedstocks of interest for possible exploitation as advanced biofuels.

Keywords: analytical protocol, biofuels, biorefinery, gas chromatography, vegetable oil

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283 A Mechanical Diagnosis Method Based on Vibration Fault Signal down-Sampling and the Improved One-Dimensional Convolutional Neural Network

Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

Abstract:

Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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282 Modeling Continuous Flow in a Curved Channel Using Smoothed Particle Hydrodynamics

Authors: Indri Mahadiraka Rumamby, R. R. Dwinanti Rika Marthanty, Jessica Sjah

Abstract:

Smoothed particle hydrodynamics (SPH) was originally created to simulate nonaxisymmetric phenomena in astrophysics. However, this method still has several shortcomings, namely the high computational cost required to model values with high resolution and problems with boundary conditions. The difficulty of modeling boundary conditions occurs because the SPH method is influenced by particle deficiency due to the integral of the kernel function being truncated by boundary conditions. This research aims to answer if SPH modeling with a focus on boundary layer interactions and continuous flow can produce quantifiably accurate values with low computational cost. This research will combine algorithms and coding in the main program of meandering river, continuous flow algorithm, and solid-fluid algorithm with the aim of obtaining quantitatively accurate results on solid-fluid interactions with the continuous flow on a meandering channel using the SPH method. This study uses the Fortran programming language for modeling the SPH (Smoothed Particle Hydrodynamics) numerical method; the model is conducted in the form of a U-shaped meandering open channel in 3D, where the channel walls are soil particles and uses a continuous flow with a limited number of particles.

Keywords: smoothed particle hydrodynamics, computational fluid dynamics, numerical simulation, fluid mechanics

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281 A Kernel-Based Method for MicroRNA Precursor Identification

Authors: Bin Liu

Abstract:

MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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280 Harmonization of Conflict Ahadith between Dissociation and Peaceful Co-Existence with Non-Muslims

Authors: Saheed Biodun Qaasim-Badmusi

Abstract:

A lot has been written on peaceful co-existence with non-Muslims in Islam, but little attention is paid to the conflict between Ahadith relating to dissociation from non-Muslims as a kernel of Islamic faith, and the one indicating peaceful co-existence with them. Undoubtedly, proper understanding of seemingly contradictory prophetic traditions is an antidote to the bane of pervasive extremism in our society. This is what calls for need to shed light on ‘Harmonization of Conflict Ahadith between Dissociation and Peaceful Co-existence with Non-Muslims. It is in view of the above that efforts are made in this paper to collate Ahadith pertaining to dissociation from non-Muslims as well as co-existence with them. Consequently, a critical study of their authenticity is briefly explained before proceeding to analysis of their linguistic and contextual meanings. To arrive at the accurate interpretation, harmonization is graphically applied. The result shows that dissociation from non –Muslims as a bedrock of Islamic faith could be explained in Sunnah by prohibition of participating or getting satisfaction from their religious matters, and anti-Islamic activities. Also, freedom of apostasy, ignoring da`wah with wisdom and seeking non-Muslims support against Muslims are frowned upon in Sunnah as phenomenon of dissociation from non –Muslims. All the aforementioned are strictly prohibited in Sunnah whether under the pretext of enhancing peaceful co-existence with non-Muslims or not. While peaceful co-existence with non-Muslims is evidenced in Sunnah by permissibility of visiting the sick among them, exchange of gift with them, forgiving the wrong among them, having good relationship with non-Muslim neighbours, ties of non-Muslim kinship, legal business transaction with them and the like. Finally, the degree of peaceful co-existence with non-Muslims is determined by their attitude towards Islam and Muslims.

Keywords: Ahadith, conflict, co-existence, non-Muslims

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279 Application of Rapid Eye Imagery in Crop Type Classification Using Vegetation Indices

Authors: Sunita Singh, Rajani Srivastava

Abstract:

For natural resource management and in other applications about earth observation revolutionary remote sensing technology plays a significant role. One of such application in monitoring and classification of crop types at spatial and temporal scale, as it provides latest, most precise and cost-effective information. Present study emphasizes the use of three different vegetation indices of Rapid Eye imagery on crop type classification. It also analyzed the effect of each indices on classification accuracy. Rapid Eye imagery is highly demanded and preferred for agricultural and forestry sectors as it has red-edge and NIR bands. The three indices used in this study were: the Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Normalized Difference Red Edge Index (NDRE) and all of these incorporated the Red Edge band. The study area is Varanasi district of Uttar Pradesh, India and Radial Basis Function (RBF) kernel was used here for the Support Vector Machines (SVMs) classification. Classification was performed with these three vegetation indices. The contribution of each indices on image classification accuracy was also tested with single band classification. Highest classification accuracy of 85% was obtained using three vegetation indices. The study concluded that NDRE has the highest contribution on classification accuracy compared to the other vegetation indices and the Rapid Eye imagery can get satisfactory results of classification accuracy without original bands.

Keywords: GNDVI, NDRE, NDVI, rapid eye, vegetation indices

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278 Structural Analysis of Multi-Pressure Integrated Vessel for Sport-Multi-Artificial Environment System

Authors: Joon-Ho Lee, Jeong-Hwan Yoon, Jung-Hwan Yoon, Sangmo Kang, Su-Yeon Hong, Hyun-Woo Jeong, Jaeick Chae

Abstract:

There are several dedicated individual chambers for sports that are supplied and used, but none of them are multi-pressured all-in-one chambers that can provide a sports multi-environment simultaneously. In this study, we design a multi-pressure (positive/atmospheric/negative pressure) integrated vessel that can be used for the sport-multi-artificial environment system. We presented additional vessel designs with enlarged space for the tall users; with reinforcement pads added to reduce the maximum stress in the joints of its shells, and then carried out numerical analysis for the structural analysis with maximum stress and structural safety. Under the targeted allowable pressure conditions, maximum stresses occurred at the joint of the shell, and the entrance, the safety of the structure was checked with the allowable stress of its material.

Keywords: structural analysis, multi-pressure, integrated vessel, sport-multi-artificial environment

Procedia PDF Downloads 505