Search results for: Kernel density estimate

Authors: Amir Hajian, Sepehr Damavandinejadmonfared

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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

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Authors: Ya-Mei Chang

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This research is intended to apply spatio-temporal point process methods to the dengue fever data in Tainan. The spatio-temporal intensity function of the dataset is assumed to be separable. The kernel estimation is a widely used approach to estimate intensity functions. The intensity function is very helpful to study the relation of the spatio-temporal point process and some covariates. The covariate effects might be nonlinear. An nonparametric smoothing estimator is used to detect the nonlinearity of the covariate effects. A fitted parametric model could describe the influence of the covariates to the dengue fever. The correlation between the data points is detected by the K-function. The result of this research could provide useful information to help the government or the stakeholders making decisions.

Keywords: dengue fever, spatial point process, kernel estimation, covariate effect

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Authors: P. S. Jagadeesh Kumar, Mingmin Pan, Yang Yung, Tracy Lin Huan

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Glaucoma is a group of visual maladies represented by the scheduled optic nerve neuropathy; means to the increasing dwindling in vision ground, resulting in loss of sight. In this paper, a novel support vector machine based retinal therapeutic for glaucoma using machine learning algorithm is conservative. The algorithm has fitting pragmatism; subsequently sustained on correlation clustering mode, it visualizes perfect computations in the multi-dimensional space. Support vector clustering turns out to be comparable to the scale-space advance that investigates the cluster organization by means of a kernel density estimation of the likelihood distribution, where cluster midpoints are idiosyncratic by the neighborhood maxima of the concreteness. The predicted planning has 91% attainment rate on data set deterrent on a consolidation of 500 realistic images of resolute and glaucoma retina; therefore, the computational benefit of depending on the cluster overlapping system pedestal on machine learning algorithm has complete performance in glaucoma therapeutic.

Keywords: machine learning algorithm, correlation clustering mode, cluster overlapping system, glaucoma, kernel density estimation, retinal therapeutic

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Authors: Hung-Sheng Lin, Cheng-Hsuan Li

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Over the past few years, kernel-based algorithms have been widely used to extend some linear feature extraction methods such as principal component analysis (PCA), linear discriminate analysis (LDA), and nonparametric weighted feature extraction (NWFE) to their nonlinear versions, kernel principal component analysis (KPCA), generalized discriminate analysis (GDA), and kernel nonparametric weighted feature extraction (KNWFE), respectively. These nonlinear feature extraction methods can detect nonlinear directions with the largest nonlinear variance or the largest class separability based on the given kernel function. Moreover, they have been applied to improve the target detection or the image classification of hyperspectral images. The double nearest proportion feature extraction (DNP) can effectively reduce the overlap effect and have good performance in hyperspectral image classification. The DNP structure is an extension of the k-nearest neighbor technique. For each sample, there are two corresponding nearest proportions of samples, the self-class nearest proportion and the other-class nearest proportion. The term “nearest proportion” used here consider both the local information and other more global information. With these settings, the effect of the overlap between the sample distributions can be reduced. Usually, the maximum likelihood estimator and the related unbiased estimator are not ideal estimators in high dimensional inference problems, particularly in small data-size situation. Hence, an improved estimator by shrinkage estimation (regularization) is proposed. Based on the DNP structure, LDA is included as a special case. In this paper, the kernel method is applied to extend DNP to kernel-based DNP (KDNP). In addition to the advantages of DNP, KDNP surpasses DNP in the experimental results. According to the experiments on the real hyperspectral image data sets, the classification performance of KDNP is better than that of PCA, LDA, NWFE, and their kernel versions, KPCA, GDA, and KNWFE.

Keywords: feature extraction, kernel method, double nearest proportion feature extraction, kernel double nearest feature extraction

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Authors: U. Thisara G. Perera, C. M. Kanchana N. K. Chandrasekara

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Dengue is an epidemic which is spread by Aedes Egyptai and Aedes Albopictus mosquitoes. The cases of dengue show a dramatic growth rate of the epidemic in urban and semi urban areas spatially in tropical and sub-tropical regions of the world. Incidence of dengue has become a prominent reason for hospitalization and deaths in Asian countries, including Sri Lanka. During the last decade the dengue epidemic began to spread from urban to semi-urban and then to rural settings of the country. The highest number of dengue infected patients was recorded in Sri Lanka in the year 2016 and the highest number of patients was identified in Colombo district. Together with the commercial, industrial, and other supporting services, the district suffers from rapid urbanization and high population density. Thus, drainage and waste disposal patterns of the people in this area exert an additional pressure to the environment. The district is situated in the wet zone and thus low lying lands constitute the largest portion of the district. This situation additionally facilitates mosquito breeding sites. Therefore, the purpose of the present study was to assess the spatial and temporal distribution patterns of dengue epidemic in Kolonnawa MOH area (Medical Officer of Health) in the district of Colombo. The study was carried out using 615 recorded dengue cases in Kollonnawa MOH area during the south east monsoon season from May to September 2016. The Moran’s I and Kernel density estimation were used as analytical methods. The analysis of data was accomplished through the integrated use of ArcGIS 10.1 software packages along with Microsoft Excel analytical tool. Field observation was also carried out for verification purposes during the study period. Results of the Moran’s I index indicates that the spatial distribution of dengue cases showed a cluster distribution pattern across the area. Kernel density estimation emphasis that dengue cases are high where the population has gathered, especially in areas comprising housing schemes. Results of the Kernel Density estimation further discloses that hot spots of dengue epidemic are located in the western half of the Kolonnawa MOH area, which is close to the Colombo municipal boundary and there is a significant relationship with high population density and unplanned urban land use practices. Results of the field observation confirm that the drainage systems in these areas function poorly and careless waste disposal methods of the people further encourage mosquito breeding sites. This situation has evolved harmfully from a public health issue to a social problem, which ultimately impacts on the economy and social lives of the country.

Keywords: Dengue epidemic, health hazards, Kernel density, Moran’s I, Sri Lanka

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Authors: Vijaya Subramaniam, Loh Soh Kheang, Astimar Abdul Aziz

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Water footprint (WFP) has gained importance due to the increase in water scarcity in the world. This study analyses the WFP for an agriculture sector, i.e., the oil palm supply chain, which produces oil palm fresh fruit bunch (FFB), crude palm oil, palm kernel, and crude palm kernel oil. The water accounting and vulnerability evaluation (WAVE) method was used. This method analyses the water depletion index (WDI) based on the local blue water scarcity. The main contribution towards the WFP at the plantation was the production of FFB from the crop itself at 0.23m³/tonne FFB. At the mill, the burden shifts to the water added during the process, which consists of the boiler and process water, which accounted for 6.91m³/tonne crude palm oil. There was a 33% reduction in the WFP when there was no dilution or water addition after the screw press at the mill. When allocation was performed, the WFP reduced by 42% as the burden was shared with the palm kernel and palm kernel shell. At the kernel crushing plant (KCP), the main contributor towards the WFP 4.96 m³/tonne crude palm kernel oil which came from the palm kernel which carried the burden from upstream followed by electricity, 0.33 m³/tonne crude palm kernel oil used for the process and 0.08 m³/tonne crude palm kernel oil for transportation of the palm kernel. A comparison was carried out for mills with biogas capture versus no biogas capture, and the WFP had no difference for both scenarios. The comparison when the KCPs operate in the proximity of mills as compared to those operating in the proximity of ports only gave a reduction of 6% for the WFP. Both these scenarios showed no difference and insignificant difference, which differed from previous life cycle assessment studies on the carbon footprint, which showed significant differences. This shows that findings change when only certain impact categories are focused on. It can be concluded that the impact from the water used by the oil palm tree is low due to the practice of no irrigation at the plantations and the high availability of water from rainfall in Malaysia. This reiterates the importance of planting oil palm trees in regions with high rainfall all year long, like the tropics. The milling stage had the most significant impact on the WFP. Mills should avoid dilution to reduce this impact.

Keywords: life cycle assessment, water footprint, crude palm oil, crude palm kernel oil, WAVE method

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Authors: Olatundun Bukola Ezekiel, Adejumo Olusoji

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A feeding trial was conducted with 100 two-weeks old broiler chicken to evaluate the influence of inclusion in broiler diets at 0, 2.5, 5, 7.5 and 10% neem kernel (used to replace equal quantity of maize) on their performance, organ weight and gut morphometry. The birds were randomly allotted to five dietary treatments, each treatment having four replicates consisting of five broilers in a completely randomized design. The diets were formulated to be iso-nitrogenous (23% CP). Weekly feed intake and changes in body weight were calculated and feed efficiency determined. At the end of the 28-day feeding trial, four broilers per treatment were selected and sacrificed for carcass evaluation. Results were subjected to statistical analysis using the analysis of variance procedures of Statistical Analysis Software The treatment means were presented with group standard errors of means and where significant, were compared using the Duncan multiple range test of the same software. The results showed that broilers fed 2.5% neem kernel inclusion diets had growth performance statistically comparable to those fed the control diet. Birds on 5, 7.5 and 10% neem kernel diets showed significant (P<0.05) increase in relative weight of liver. The absolute weight of spleen also increased significantly (P<0.05) in birds on 10 % neem kernel diet. More than 5 % neem kernel diets gave significant (P<0.05) increase in the relative weight of the kidney. The length of the small intestine significantly increased in birds fed 7.5 and 10% neem kernel diets. Significant differences (P<0.05) did not occur in the length of the large intestine, right and left caeca. It is recommended that neem kernel can be included up to 2.5% in broiler chicken diet without any deleterious effects on the performance and physiological status of the birds.

Keywords: broiler chicken, growth performance, gut morphometry, neem kernel, organ weight

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Authors: Mahdi Golriz

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The aim of this work is to estimate the change in molecular structure of linear low-density polyethylene (LLDPE) during peroxide modification can be detected by a simple rheological method. For this purpose a commercial grade LLDPE (Exxon MobileTM LL4004EL) was reacted with different doses of dicumyl peroxide (DCP). The samples were analyzed by size-exclusion chromatography coupled with a light scattering detector. The dynamic shear oscillatory measurements showed a deviation of the δ-׀G ׀٭curve from that of the linear LLDPE, which can be attributed to the presence of long-chain branching (LCB). By the use of a simple rheological method that utilizes melt rheology, transformations in molecular architecture induced on an originally linear low density polyethylene during the early stages of reactive modification were indicated. Reasonable and consistent estimates are obtained, concerning the degree of LCB, the volume fraction of the various molecular species produced in peroxide modification of LLDPE.

Keywords: linear low-density polyethylene, peroxide modification, long-chain branching, rheological method

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Authors: A. Schirru, A. Irimescu, S. Merola, A. d’Adamo, S. Fontanesi

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One of the aspects that are usually neglected during the design phase of an engine is the effect of the spark plug on the flow field inside the combustion chamber. Because of the difficulties in the experimental investigation of the mutual interaction between flow alteration and early flame kernel convection effect inside the engine combustion chamber, CFD-3D simulation is usually exploited in such cases. Experimentally speaking, a particular type of engine has to be used in order to directly observe the flame propagation process. In this study, a double electrode spark plug was fitted into an optically accessible engine and a high-speed camera was used to capture the initial stages of the combustion process. Both the arc and the kernel phases were observed. Then, a morphologic analysis was carried out and the position of the center of mass of the flame, relative to the spark plug position, was calculated. The crossflow orientation was chosen for the spark plug and the kernel growth process was observed for different air-fuel ratios. It was observed that during a normal cycle the flow field between the electrodes tends to transport the arc deforming it. Because of that, the kernel growth phase takes place away from the electrodes and the flame propagates with a preferential direction dictated by the flow field.

Keywords: Combustion, Optically Accessible Engine, Spark-Ignition Engine, Sparl Orientation, Kernel Growth

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Authors: Shahin Mirshekari, Mohammadreza Moradi, Hossein Jafari, Mehdi Jafari, Mohammad Ensaf

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This research employs Gaussian Process Regression (GPR) with an ensemble kernel, integrating Exponential Squared, Revised Matern, and Rational Quadratic kernels to analyze pharmaceutical sales data. Bayesian optimization was used to identify optimal kernel weights: 0.76 for Exponential Squared, 0.21 for Revised Matern, and 0.13 for Rational Quadratic. The ensemble kernel demonstrated superior performance in predictive accuracy, achieving an R² score near 1.0, and significantly lower values in MSE, MAE, and RMSE. These findings highlight the efficacy of ensemble kernels in GPR for predictive analytics in complex pharmaceutical sales datasets.

Keywords: Gaussian process regression, ensemble kernels, bayesian optimization, pharmaceutical sales analysis, time series forecasting, data analysis

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Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

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Authors: Kazeem K. Adewole, Ismail A. Yahya

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In the published literature, Palm Kernel Shell (PKS), an agricultural waste has largely been used as a large aggregate in PKS concrete production. In this paper, the development of Crushed Palm Kernel Shell Fine Aggregate Concrete (CPKSFAC) with crushed PKS (CPKS) as the fine aggregate and granite as the coarse aggregate is presented. 100mm x 100mm x 100mm 1:11/2:3 and 1:2:4 CPKSFAC and River Sand Fine Aggregate Concrete (RSFAC) cubes were molded, cured for 28 days and subjected to a compressive strength test. The average wet densities of the 1:11/2:3 and 1:2:4 CPKSFAC cubes are 2240kg/m3 and 2335kg/m3 respectively. The average wet densities of the 1:11/2:3 and 1:2:4 RSFAC cubes are 2606kg/m3 and 2553kg/m3 respectively. The average compressive strengths of the 1:11/2:3 and 1:2:4 CPKSFAC cubes are 15.40MPa and 14.30MPa respectively. This study demonstrates that CPKSFA is suitable for the production of non-structural C8/10 and C12/15 concrete specified in BS EN 206-1:2000.

Keywords: crushed palm kernel shell, fine aggregate, lightweight concrete, non-structural concrete

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Authors: K. Asemave, D. O. Abakpa, T. T. Ligom

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The ability of bacteria to develop resistance to many antibiotics cannot be undermined, given the multifaceted health challenges in the present times. For this reason, a lot of attention is on botanicals and their products in search of new antibacterial agents. On the other hand, mango kernel oils (MKO) can be heavily valorized by taking advantage of the myriads bioactive phytochemicals it contains. Herein, we validated the use of MKO as bioactive agent against bacteria. The MKOs for the study were extracted by soxhlet means with ethanol and hexane for 4 h from 3 different mango kernels, namely; 'local' (sample A), 'julie' (sample B), and 'john' (sample C). Prior to the extraction, ground fine particles of the kernels were obtained from the seed kernels dried in oven at 100 °C for 8 h. Hexane gave higher yield of the oils than ethanol. It was also qualitatively confirmed that the mango kernel oils contain some phytochemicals such as phenol, quinone, saponin, and terpenoid. The results of the antibacterial activities of the MKO against both gram positive (Staphylococcus aureus) and gram negative (Pseudomonas aeruginosa) at different concentrations showed that the oils extracted with ethanol gave better antibacterial properties than those of the hexane. More so, the bioactivities were best with the local mango kernel oil. Indeed this work has completely validated the previous claim that MKOs are effective antibacterial agents. Thus, these oils (especially the ethanol-derived ones) can be used as bacteriostatic and antibacterial agents in say food, cosmetics, and allied industries.

Keywords: bacteria, mango, kernel, oil, phytochemicals

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Authors: A. Elsariti, T. Evans

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An understanding of the interaction between acoustic waves and cancellous bone is needed in order to realize the full clinical potential of ultrasonic bone measurements. Scattering is likely to be of central importance but has received little attention to date. Few theoretical approaches have been described to explain scattering of ultrasound from bone. In this study, a scattering model based on velocity and density fluctuations in a binary mixture (marrow fat and cortical matrix) was used to estimate the ultrasonic attenuation in cancellous bone as a function of volume fraction. Predicted attenuation and backscatter coefficient were obtained for a range of porosities and scatterer size. At 600 kHZ and for different scatterer size the effect of velocity and density fluctuations in the predicted attenuation was approximately 60% higher than velocity fluctuations.

Keywords: ultrasound scattering, sound speed, density fluctuations, attenuation coefficient

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Authors: Abdullah Alhomidan

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This study is conducted to identify the main factors affecting accuracy of pretender cost estimate in building construction projects in Saudi Arabia from owners’ perspective. 44 factors affecting pretender cost estimate were identified through literature review and discussion with some construction experts. The results show that the top important factors affecting pretender cost estimate accuracy are: level of competitors in the tendering, material price changes, communications with suppliers, communications with client, and estimating method used.

Keywords: cost estimate, accuracy, pretender, estimating, bid estimate

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Authors: Kazeem K. Adewole

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There need to construct building walls with lightweight masonry bricks/blocks and mortar to reduce the weight and cost of cooling/heating of buildings in hot/cold climates is growing partly due to legislations on energy use and global warming. In this paper, the development of Palm Kernel Shell masonry mortar (PKSMM) prepared with Portland cement and crushed PKS fine aggregate (an agricultural waste) is demonstrated. We show that PKSMM can be used as a lightweight mortar for the construction of lightweight masonry walls with good thermal insulation efficiency than the natural river sand commonly used for masonry mortar production.

Keywords: building walls, fine aggregate, lightweight masonry mortar, palm kernel shell, wall thermal insulation efficacy

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Authors: Abderrahmen Aloulou, Younes Boujelbene

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The current paper displays a new method of extracting information content from options prices by eliminating biases caused by daily variation of contract maturity. Based on Kernel regression tool, this non-parametric technique serves to obtain a spectrum of interpolated options with constant maturity horizons from negotiated optional contracts on the S&P TSX 60 index. This method makes it plausible to compare daily risk neutral densities from which extracting time continuous indicators allows the detection traders attitudes’ evolution, such as, belief homogeneity, asymmetry and extreme Risk Perception. Our findings indicate that the applied method contribute to develop effective trading strategies and to adjust monetary policies through controlling trader’s reactions to economic and monetary news.

Keywords: risk neutral densities, kernel, constant maturity horizons, homogeneity, asymmetry and extreme risk perception

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Authors: Saheed O. Akinwale, Olufemi A. Koya

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Based on the need to modify palm kernel shell (PKS) and coconut shell (CNS) for some engineering applications, the study evaluated some physical characteristics and fracture resistance, relevant in estimating energy requirements in comminution of the nutshells. The shells, obtained from local processing mills, were washed, sun-dried and sorted to remove kernels, nuts and other extraneous materials. Experiments were then conducted to determine the thickness, density, moisture content, and hardness of the shells. Fracture resistances were characterised by the average compressive load, stiffness and toughness at bio-yield point of specially prepared section of the shells, under quasi-static compression loading. The densities of the dried PKS at 7.12% and the CNS at 6.47% (wb) moisture contents were 1291.20 and 1247.40 kg/m3, respectively. The corresponding Brinnel Hardness Numbers were 58.40 ± 1.91 and 56.33 ± 4.33. Close shells thickness of both PKS and CNS exhibited identical physical properties although; CNS is relatively larger in physical dimensions than PKS. The findings further showed that both shell types exhibited higher resistance with compression along the longitudinal axes than the transverse axes. With compressions along the longitudinal axes, the fracture force were 1.41 ± 0.11 and 3.62 ± 0.09 kN; bio-stiffness; 934.70 ± 67.03 kN/m and 1980.74 ± 8.92 kN/m; and toughness, 2.17 ± 0.16 and 6.51 ± 0.15 KN mm for the PKS and CNS, respectively. With the estimated toughness of CNS higher than that of PKS, the study showed the requirement of higher comminution energy for CNS.

Keywords: bio-stiffness, coconut shell, comminution, crushing strength, energy requirement, palm kernel shell, toughness

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Authors: Viney Dixit, Rohit R. Shahi, Ashish Bhatnagar, P. Jain, T. P. Yadav, O. N. Srivastava

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Carbons are being widely investigated as hydrogen storage material owing to their light weight, fast hydrogen absorption kinetics and low cost. However, these materials suffer from low hydrogen storage capacity at room temperature. The aim of the present study is to synthesize carbon based material which shows moderate hydrogen storage at room temperature. For this purpose, hydrogenation characteristics of natural precursor coconut kernel is studied in this work. The hydrogen storage measurement reveals that the as-synthesized materials have good hydrogen adsorption and desorption capacity with fast kinetics. The synthesized material absorbs 8 wt.% of hydrogen at liquid nitrogen temperature and 2.3 wt.% at room temperature. This could be due to the presence of certain elements (KCl, Mg, Ca) which are confirmed by TEM.

Keywords: coconut kernel, carbonization, hydrogenation, KCl, Mg, Ca

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Authors: Yose Rizal, Nuraini, Mirnawati, Maria Endo Mahata, Rio Darman, Dendi Kurniawan

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An experiment had been conducted to determine the effects of several levels of Neurospora crassa- fermented palm kernel cake in the diet on the production performance and egg-yolk quality of Arab laying-hens, and to obtain the appropriate level of this fermented palm kernel cake for reducing the utilization of concentrated feed in the diet. Three hundred Arab laying-hens of 72 weeks old were employed in this experiment, and randomly assigned to four treatments (0, 7.25, 10.15, and 13.05% fermented palm kernel cake in diets) in a completely randomized design with five replicates. Measured variables were production performance (feed consumption, egg-mass production, feed conversion, egg weight and hen-day egg production), and egg-yolk quality (ether extract and cholesterol contents, and egg-yolk color index). Results of experiment indicated that feed consumption, egg-mass production, feed conversion, egg weight, hen-day egg production and egg-yolk color index were not influenced (P>0.05) by diets. However, the ether extract and cholesterol contents of egg-yolk were very significantly reduced (P<0.01) by diets. In conclusion, Neurospora crassa-fermented palm kernel cake could be included up to 13.05% to effectively replace 45% concentrated feed in Arab laying-hens diet without adverse effect on the production performance.

Keywords: neurospora crassa-fermented palm kernel cake, Arab laying-hens, production performance, ether extract, cholesterol, egg-yolk color index

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Authors: Felix U. Asoiro, Daniel I. Eleazar, Peter O. Offor

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As a result of increasing energy demands, research in bioethanol has increased in recent years all through the world, in abide to partially or totally replace renewable energy supplies. The first and third generation feedstocks used for biofuel production have fundamental drawbacks. Waste rice straw and cake from second generation feedstock like Jatropha curcas l. kernel (JC) is seen as non-food feedstock and promising candidates for the industrial production of bioethanol. In this study, JC and rice husk (RH) wastes were characterized for proximate composition. Bioethanol was produced from the residual polysaccharides present in rice husk (RH) and Jatropha seed cake by sequential hydrolytic and fermentative processes at varying mixing proportions (50 g JC/50 g RH, 100 g JC/10 g RH, 100 g JC/20 g RH, 100 g JC/50 g RH, 100 g JC/100 g RH, 100 g JC/200 g RH and 200 g JC/100 g RH) and particle sizes (0.25, 0.5 and 1.00 mm). Mixing proportions and particle size significantly affected both bioethanol yield and some bioethanol properties. Bioethanol yield (%) increased with an increase in particle size. The highest bioethanol (8.67%) was produced at a mixing proportion of 100 g JC/50g RH at 0.25 mm particle size. The bioethanol had the lowest values of specific gravity and density of 1.25 and 0.92 g cm-3 and the highest values of 1.57 and 0.97 g cm-3 respectively. The highest values of viscosity (4.64 cSt) were obtained with 200 g JC/100 g RH, at 1.00 mm particle size. The maximum flash point and cloud point values were 139.9 oC and 23.7oC (100 g JC/200 g RH) at 1 mm and 0.5 mm particle sizes respectively. The maximum pour point value recorded was 3.85oC (100 g JC/50 g RH) at 1 mm particle size. The paper concludes that bioethanol can be recovered from JC and RH wastes. JC and RH blending proportions as well as particle sizes are important factors in bioethanol production.

Keywords: bioethanol, hydrolysis, Jatropha curcas l. kernel, rice husk, fermentation, proximate composition

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Authors: Kanit Manatura

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The combustion and pyrolysis behavior of Palm Kernel Shell (PKS) were investigated in a thermogravimetric analyzer. A 10 mg sample of each biomass was heated from 30 °C to 800 °C at four heating rates (within 5, 10, 15 and 30 °C/min) in nitrogen and dry air flow of 20 ml/min instead of pyrolysis and combustion process respectively. During pyrolysis, thermal decomposition occurred on three different stages include dehydration, hemicellulose-cellulose and lignin decomposition on each temperature range. The TG/DTG curves showed the degradation behavior and the pyrolysis/combustion characteristics of the PKS samples which led to apply in thermogravimetric analysis. The kinetic factors including activation energy and pre-exponential factor were determined by the Coats-Redfern method. The obtained kinetic factors are used to simulate the thermal decomposition and compare with experimental data. Rising heating rate leads to shift the mass loss towards higher temperature.

Keywords: combustion, palm kernel shell, pyrolysis, thermogravimetric analyzer

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Authors: I. Ruzaina, A. B. Rashid, M. S. Halimahton Zahrah, C. S. Cheow, M. S. Adi

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This study was conducted to determine the potential of palm stearin (PS) as edible coating materials for fruits. The palm stearin was blended with 20-80% palm kernel olein (PKOo) and the properties of the blends were evaluated in terms of the slip melting point (SMP), solid fat content (SFC), fatty acid and triacylglycerol compositions (TAG), and polymorphism. Blending of PS with PKOo reduced the SMP, SFC, altered the FAC and TAG composition and changed the crystal polymorphism from β to mixture of β and β′. The changes in the physicochemical properties of PS were due to the replacement of the high melting TAG in PS with medium chain TAG in PKOo. From the analysis, 1:1 and 3:2 were the better PSPKOo blend formulations in slowing down the weight loss, respiration gases and gave better appearance when compared to other PSPKOo blends formulations.

Keywords: guava, palm stearin, palm kernel olein, physicochemical

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Authors: Bing-Bing E. Goh

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Plant counting is a labour intensive and time-consuming task for the farmers. However, it is an important indicator for farmers to make decisions on subsequent field management. This study is to evaluate the potential of Sentinel-2 images using statistical analysis to retrieve information on plant density for monitoring, especially during critical period at the beginning of March. The model was calibrated with in-situ data from 19 winter wheat fields in Republic of Ireland during the crop growing season in 2019-2020. The model for plant density resulted in R2 = 0.77, RMSECV = 103 and NRMSE = 14%. This study has shown the potential of using Sentinel-2 to estimate plant density and quantify plant establishment to effectively monitor crop progress and to ensure proper field management.

Keywords: winter wheat, remote sensing, crop monitoring, multivariate analysis

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Authors: Virender Singh Gurau, Akash Deep, Sarbjot S. Sandhu

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Vegetable oils are produced from numerous oil seed crops. While all vegetable oils have high energy content, most require some processing to assure safe use in internal combustion engines. Some of these oils already have been evaluated as substitutes for diesel fuels. In the present research work Bitter Apricot kernel oil was employed as a feedstock for the production of biodiesel. The physicochemical properties of the Bitter Apricot kernel oil methyl ester were investigated as per ASTM D6751. From the series of engine testing, it is concluded that the brake thermal efficiency (BTE) with biodiesel blend was little lower than that of diesel. BSEC is slightly higher for Bitter apricot kernel oil methyl ester blends than neat diesel. For biodiesel blends, CO emission was lower than diesel fuel as B 20 reduced CO emissions by 18.75%. Approximately 11% increase in NOx emission was observed with 20% biodiesel blend. It is observed that HC emissions tend to decrease for biodiesel based fuels and Smoke opacity was found lower for biodiesel blends in comparison to diesel fuel.

Keywords: biodiesel, transesterification, bitter apricot kernel oil, performance and emission testing

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Authors: Nastaran Moosavi, Mohammad Mokhtari

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Seismic inversion is a technique which has been in use for years and its main goal is to estimate and to model physical characteristics of rocks and fluids. Generally, it is a combination of seismic and well-log data. Seismic inversion can be carried out through different methods; we have conducted and compared post-stack and pre- stack seismic inversion methods on real data in one of the fields in the Persian Gulf. Pre-stack seismic inversion can transform seismic data to rock physics such as P-impedance, S-impedance and density. While post- stack seismic inversion can just estimate P-impedance. Then these parameters can be used in reservoir identification. Based on the results of inverting seismic data, a gas reservoir was detected in one of Hydrocarbon oil fields in south of Iran (Persian Gulf). By comparing post stack and pre-stack seismic inversion it can be concluded that the pre-stack seismic inversion provides a more reliable and detailed information for identification and prediction of hydrocarbon reservoirs.

Keywords: density, p-impedance, s-impedance, post-stack seismic inversion, pre-stack seismic inversion

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Authors: Oscar Corredor, Alexander Guzman, Adan Leon

Abstract:

Density is a bulk physical property that indicates the quality of a petroleum fraction. It is also a useful property to estimate various physicochemical properties of fraction and petroleum fluids; however, the determination of density of extra heavy residual (EHR) fractions by standard methodologies, (ASTM D70) shows limitations for samples with higher densities than 1.0879 g/cm3. For this reason, a dilution methodology was developed in order to determinate density for those particular fractions, 87 (EHR) fractions were obtained as products of the fractionation of Colombian typical Vacuum Distillation Residual Fractions using molecular distillation (MD) and extraction with Solvent N-hexane in Supercritical Conditions (SFEF) pilot plants. The proposed methodology showed reliable results that can be demonstrated with the standard deviation of repeatability and reproducibility values of 0.0031 and 0.0061 g/ml respectively. In the same way, it was possible to determine densities in fractions EHR up to 1.1647g/cm3 and °API values obtained were ten times less than the water reference value.

Keywords: API, density, vacuum residual, molecular distillation, supercritical fluid extraction

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Authors: H. M. Al-Qassem, L. Cheng, Y. Pan

Abstract:

In this paper we establish sharp bounds for oscillatory singular integrals with an arbitrary real polynomial phase P. Our kernels are allowed to be rough both on the unit sphere and in the radial direction. We show that the bounds grow no faster than log(deg(P)), which is optimal and was first obtained by Parissis and Papadimitrakis for kernels without any radial roughness. Among key ingredients of our methods are an L¹→L² estimate and extrapolation.

Keywords: oscillatory singular integral, rough kernel, singular integral, Orlicz spaces, Block spaces, extrapolation, L^{p} boundedness

Procedia PDF Downloads 357

Authors: Aziz Sezgin

Abstract:

We consider the problem of stabilization of an unstable heat equation in a 2-D, 3-D and generally n-D domain by deriving a generalized backstepping boundary control design methodology. To stabilize the systems, we design boundary backstepping controllers inspired by the 1-D unstable heat equation stabilization procedure. We assume that one side of the boundary is hinged and the other side is controlled for each direction of the domain. Thus, controllers act on two boundaries for 2-D domain, three boundaries for 3-D domain and ”n” boundaries for n-D domain. The main idea of the design is to derive ”n” controllers for each of the dimensions by using ”n” kernel functions. Thus, we obtain ”n” controllers for the ”n” dimensional case. We use a transformation to change the system into an exponentially stable ”n” dimensional heat equation. The transformation used in this paper is a generalized Volterra/Fredholm type with ”n” kernel functions for n-D domain instead of the one kernel function of 1-D design.

Keywords: backstepping, boundary control, 2-D, 3-D, n-D heat equation, distributed parameter systems

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Authors: Jessada Tariboon

Abstract:

In this article, using distribution kernel, we study the nonlinear equations with n-dimensional telegraph operator iterated k-times.

Keywords: telegraph operator, elementary solution, distribution kernel, nonlinear equations

Procedia PDF Downloads 489