Search results for: weight vector

Authors: Lebari B. Gboeloh

Abstract:

Ficus exasperata is a plant used in the traditional management of malaria in south-south Nigeria. An investigation into the effects of the ethanolic extract of the leaf of the plant on some biochemical indices in albino mice infected with Plasmodium berghei (NK 65) was conducted. 48 mice with weight range of 13-23 g were grouped into six (A, B, C, D, E, and F). Each group contained 8 mice. Groups A, B, C, D and E were infected with blood containing the parasite. Group F was not infected and served as the normal control. On the 6^th day after infection, 4 mice from each group were sacrificed and blood samples are collected for investigation. The remaining mice in each group were treated. Mice in Groups A, B and C were administered orally with 200, 300 and 500 mg/kg body weight of Ficus exasperata respectively for six days. Group D was not treated while Group F was given distilled water. Group E was treated with 5 mg/kg body weight of chloroquine. On the 6^th day post treatment, these mice were sacrificed and blood samples were collected for biochemical analysis. The results indicated that on the 6^th day post inoculation, the levels of aspartate aminotransferase (AST), alkaline phosphatase (ALP) and alanine aminotransferase (ALT) in all the mice infected with the parasite were significantly (p < 0.05) elevated. However, on the 6^th day post administration of extract, the increased levels of AST, ALP and ALT were significantly (p < 0.05) reduced in groups administered with 300 and 500 mg/kg body weight of the extract compared with groups D and F. The reduction in the levels of these enzymes is an indication that F. exasperata have no hepatotoxic effect on the mice at the dose levels administered.

Keywords: Ficus exasperata, albino mice, Plasmodium berghei, biochemical parameters.

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Authors: Paitoon Kraipornsak

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The recent global financial problem urges government to play role in stimulating the economy due to the fact that private sector has little ability to purchase during the recession. A concerned question is whether the increased government spending crowds out private consumption and whether it helps stimulate the economy. If the government spending policy is effective; the private consumption is expected to increase and can compensate the recent extra government expense. In this study, the government spending is categorized into government consumption spending and government capital spending. The study firstly examines consumer consumption along the line with the demand function in microeconomic theory. Three categories of private consumption are used in the study. Those are food consumption, non food consumption, and services consumption. The dynamic Almost Ideal Demand System of the three categories of the private consumption is estimated using the Vector Error Correction Mechanism model. The estimated model indicates the substituting effects (negative impacts) of the government consumption spending on budget shares of private non food consumption and of the government capital spending on budget share of private food consumption, respectively. Nevertheless the result does not necessarily indicate whether the negative effects of changes in the budget shares of the non food and the food consumption means fallen total private consumption. Microeconomic consumer demand analysis clearly indicates changes in component structure of aggregate expenditure in the economy as a result of the government spending policy. The macroeconomic concept of aggregate demand comprising consumption, investment, government spending (the government consumption spending and the government capital spending), export, and import are used to estimate for their relationship using the Vector Error Correction Mechanism model. The macroeconomic study found no effect of the government capital spending on either the private consumption or the growth of GDP while the government consumption spending has negative effect on the growth of GDP. Therefore no crowding out effect of the government spending is found on the private consumption but it is ineffective and even inefficient expenditure as found reducing growth of the GDP in the context of Thailand.

Keywords: government consumption spending, governmentcapital spending, private consumption on food, non food, andservices, Vector Error Correction Mechanism, Almost Ideal DemandSystem, substitution effect, complementary effect, consumer demand, aggregate demand

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Authors: Tzyy Rong Jinn, Nguyen Tiep Khac, Tzong Yuan Wu

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Highly pathogenic avian influenza (HPAI) H5N1 viruses have created demand for a cost-effective vaccine to prevent a pandemic of the disease. Here, we report that Trichoplusia ni (T. ni) larvae can act as a cost-effective bioreactor to produce recombinant HA5 (rH5HA) proteins as an potential effective vaccine for chickens. To facilitate the recombinant virus identification, virus titer determination and access the infected larvae, we employed the internal ribosome entry site (IRES) derived from Perina nuda virus (PnV, belongs to insect picorna like Iflavirus genus) to construct a bi-cistronic baculovirus expression vector that can express the rH5HA protein and enhanced green fluorescent protein (EGFP) simultaneously. Western blot analysis revealed that the 70 kDa rH5HA protein and partially cleaved products (40 kDa H5HA1) were generated in T. ni larvae infected with recombinant baculovirus carrying the H5HA gene. These data suggest that the baculovirus-larvae recombinant protein expression system could be a cost-effective platform for H5N1 vaccine production.

Keywords: Avian Influenza, baculovirus, hemagglutinin, Trichoplusia ni larvae

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Authors: S. Nandagopalan, N. Pradeep

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The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: Active Contour, Bayesian, Echocardiographic image, Feature vector.

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Authors: Smita Jauhari, Bhupendra Mistry

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Schiff base (E)-2-methyl-N-(tetrazolo[1,5-a]quinolin-4-ylmethylene)aniline (QMA) was synthesized, and its inhibitive effect for mild steel in 1N HCl solution was investigated by weight loss measurement and electrochemical tests. From the weight loss measurements and electrochemical tests, it was observed that the inhibition efficiency increases with the increase in the Schiff base concentration and reaches a maximum at the optimum concentration. This is further confirmed by the decrease in corrosion rate. It is found that the system follows Langmuir adsorption isotherm.

Keywords: Schiff base, acid corrosion, electrochemical impedance spectroscopy, polarization.

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Authors: G. B. Singh, S. Srivastava, N. Gupta

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In the present work we report a gram negative bacterial isolate, from soil of a dye industry, with promising biorefining and bioremediation potential. This isolate (GBS.5) could utilize carbazole (nitrogen containing polycyclic aromatic hydrocarbon) as the sole source of nitrogen and carbon and utilize almost 98% of 3mM carbazole in 100 hours. The specific activity of our GBS.5 isolate for carbazole degradation at 30°C and pH 7.0 was found to be 11.36 μmol/min/g dry cell weight as compared to 10.4 μmol/min/g dry cell weight, the highest reported specific activity till date. The presence of car genes (the genes involved in denitrogenation of carbazole) was confirmed through PCR amplification.

Keywords: Biodenitrogenation, Biorefining, Carbazoledegradation, Crude oil.

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Authors: Eu Tteum Ha, Kwang Ryel Ryu

Abstract:

As smartphones are equipped with various sensors, there have been many studies focused on using these sensors to create valuable applications. Human activity recognition is one such application motivated by various welfare applications, such as the support for the elderly, measurement of calorie consumption, lifestyle and exercise patterns analyses, and so on. One of the challenges one faces when using smartphone sensors for activity recognition is that the number of sensors should be minimized to save battery power. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we adopt to deal with this twelve-class problem uses various methods. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point, but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window. The experiments compared the performance of four kinds of basic multi-class classifiers and the performance of four kinds of ensemble learning methods based on three kinds of basic multi-class classifiers. The results show that while the method with the highest accuracy is ECOC based on Random forest.

Keywords: Ensemble learning, activity recognition, smartphone accelerometer.

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Authors: Şehri Çınar, Aydın Akın

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This study was conducted Razakı grape variety (Vitis vinifera L.) and its vine which was aged 19 was grown on 5 BB rootstock in a vegetation period of 2014 in Afyon province in Turkey. In this research, it was investigated whether the applications of Control (C), 1/3 Cluster Tip Reduction (1/3 CTR), Shoot Tip Reduction (STR), 1/3 CTR + STR, Boric Acid (BA), 1/3 CTR + BA, STR + BA, 1/3 CTR + STR + BA on yield and yield components of Razakı grape variety. The results were obtained as the highest fresh grape yield (7.74 kg/vine) with C application; as the highest cluster weight (244.62 g) with STR application; as the highest 100 berry weight (504.08 g) with C application; as the highest maturity index (36.89) with BA application; as the highest must yield (695.00 ml) with BA and (695.00 ml) with 1/3 CTR + STR + BA applications; as the highest intensity of L* color (46.93) with STR and (46.10) with 1/3 CTR + STR + BA applications; as the highest intensity of a* color (-5.37) with 1/3 CTR + STR and (-5.01) with STR, as the highest intensity of b* color (12.59) with STR application. The shoot tip reduction to increase cluster weight and boric acid application to increase maturity index of Razakı grape variety can be recommended.

Keywords: Razakı, 1/3 cluster tip reduction, shoot tip reduction, boric acid, yield and yield components.

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Authors: Hyunchul Ahn, Kyoung-Jae Kim

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Corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has been one of the attractive research topics in the literature. In recent years, multiclass classification models such as artificial neural network (ANN) or multiclass support vector machine (MSVM) have become a very appealing machine learning approaches due to their good performance. However, most of them have only focused on classifying samples into nominal categories, thus the unique characteristic of the credit rating - ordinality - has been seldom considered in their approaches. This study proposes new types of ANN and MSVM classifiers, which are named OMANN and OMSVM respectively. OMANN and OMSVM are designed to extend binary ANN or SVM classifiers by applying ordinal pairwise partitioning (OPP) strategy. These models can handle ordinal multiple classes efficiently and effectively. To validate the usefulness of these two models, we applied them to the real-world bond rating case. We compared the results of our models to those of conventional approaches. The experimental results showed that our proposed models improve classification accuracy in comparison to typical multiclass classification techniques with the reduced computation resource.

Keywords: Artificial neural network, Corporate credit rating, Support vector machines, Ordinal pairwise partitioning

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Authors: Hui-Yu Huang, Shih-Hang Hsu

Abstract:

In this paper, we propose a robust scheme to work face alignment and recognition under various influences. For face representation, illumination influence and variable expressions are the important factors, especially the accuracy of facial localization and face recognition. In order to solve those of factors, we propose a robust approach to overcome these problems. This approach consists of two phases. One phase is preprocessed for face images by means of the proposed illumination normalization method. The location of facial features can fit more efficient and fast based on the proposed image blending. On the other hand, based on template matching, we further improve the active shape models (called as IASM) to locate the face shape more precise which can gain the recognized rate in the next phase. The other phase is to process feature extraction by using principal component analysis and face recognition by using support vector machine classifiers. The results show that this proposed method can obtain good facial localization and face recognition with varied illumination and local distortion.

Keywords: Gabor filter, improved active shape model (IASM), principal component analysis (PCA), face alignment, face recognition, support vector machine (SVM)

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Authors: Achut Manandhar, Kenneth D. Morton, Peter A. Torrione, Leslie M. Collins

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The current trends in affect recognition research are to consider continuous observations from spontaneous natural interactions in people using multiple feature modalities, and to represent affect in terms of continuous dimensions, incorporate spatio-temporal correlation among affect dimensions, and provide fast affect predictions. These research efforts have been propelled by a growing effort to develop affect recognition system that can be implemented to enable seamless real-time human-computer interaction in a wide variety of applications. Motivated by these desired attributes of an affect recognition system, in this work a multi-dimensional affect prediction approach is proposed by integrating multivariate Relevance Vector Machine (MVRVM) with a recently developed Output-associative Relevance Vector Machine (OARVM) approach. The resulting approach can provide fast continuous affect predictions by jointly modeling the multiple affect dimensions and their correlations. Experiments on the RECOLA database show that the proposed approach performs competitively with the OARVM while providing faster predictions during testing.

Keywords: Dimensional affect prediction, Output-associative RVM, Multivariate regression.

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Authors: Leila Azadbakht, Maedeh Moradi, Mohammad Reza Merasi, Farzaneh Jahangir

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Maternal dietary intake during lactation might affect the growth rate of an exclusive breastfed infant. The present study was conducted to evaluate the effect of maternal dietary patterns and quality during lactation on the growth of the exclusive breastfed infant. Methods: 484 healthy lactating mothers with their infant were enrolled in this study. Only exclusive breastfed infants were included in this study which was conducted in Iran. Dietary intake of lactating mothers was assessed using a validated and reliable semi-quantitative food frequency questionnaire. Diet quality indices such as alternative Healthy eating index (HEI), Dietary energy density (DED), and adherence to Mediterranean dietary pattern score, Nordic and dietary approaches to stop hypertension (DASH) eating pattern were created. Anthropometric features of infant (weight, height, and head circumference) were recorded at birth, two and four months. Results: Weight, length, weight for height and head circumference of infants at two months and four months age were mostly in the normal range among those that mothers adhered more to the HEI in lactation period (normal weight: 61%; normal height: 59%). The prevalence of stunting at four months of age among those whose mothers adhered more to the HEI was 31% lower than those with the least adherence to HEI. Mothers in the top tertiles of HEI score had the lowest frequency of having underweight infants (18% vs. 33%; P=0.03). Odds ratio of being overweight or obese at four months age was the lowest among those infants whose mothers adhered more to the HEI (OR: 0.67 vs 0.91; Ptrend=0.03). However, there was not any significant association between adherence of mothers to Mediterranean diet as well as DASH diet and Nordic eating pattern and the growth of infants (none of weight, height or head circumference). Infant weight, length, weight for height and head circumference at two months and four months did not show significant differences among different tertile categories of mothers’ DED. Conclusions: Higher diet quality indices and more adherence of lactating mother to HEI (as an indicator of diet quality) may be associated with better growth indices of the breastfed infant. However, it seems that DED of the lactating mother does not affect the growth of the breastfed infant. Adherence to the different dietary patterns such as Mediterranean, DASH or Nordic among mothers had no different effect on the growth indices of the infants. However, higher diet quality indices and more adherence of lactating mother to HEI may be associated with better growth indices of the breastfed infant. Breastfeeding is a complete way that is not affected much by the dietary patterns of the mother. However, better diet quality might be associated with better growth.

Keywords: Breastfeeding, growth, infant, maternal diet.

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Authors: Rong Zhou, Shun’ich Kaneko, Fumio Tanaka, Miyuki Kayamori, Motoshige Shimizu

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In this paper, we propose a robust disease detection method, called adaptive orientation code matching (Adaptive OCM), which is developed from a robust image registration algorithm: orientation code matching (OCM), to achieve continuous and site-specific detection of changes in plant disease. We use two-stage framework for realizing our research purpose; in the first stage, adaptive OCM was employed which could not only realize the continuous and site-specific observation of disease development, but also shows its excellent robustness for non-rigid plant object searching in scene illumination, translation, small rotation and occlusion changes and then in the second stage, a machine learning method of support vector machine (SVM) based on a feature of two dimensional (2D) xy-color histogram is further utilized for pixel-wise disease classification and quantification. The indoor experiment results demonstrate the feasibility and potential of our proposed algorithm, which could be implemented in real field situation for better observation of plant disease development.

Keywords: Cercospora Leaf Spot (CLS), Disease detection, Image processing, Orientation Code Matching (OCM), Support Vector Machine (SVM).

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Authors: Sahar Y. Al-Okbi, Doha A. Mohamed, Thanaa E. Hamed, Ahmed Ms Hussein

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In the present research, two nutraceuticals made from red grape and walnut that showed previously to improve kidney dysfunction were incorporated separately into functional foods' bread made from barley and rice bran. The functional foods were evaluated in rats in which chronic renal failure was induced through feeding diet rich in adenine and phosphate (APD). The evaluation based on assessing kidney function, oxidative stress, inflammatory biomarkers and body weight gain. Results showed induction of chronic kidney failure reflected in significant increase in plasma urea, creatinine, malondialdehyde, tumor necrosis factor- α and low density lipoprotein cholesterol along with significant reduction of plasma albumin, and total antioxidant and creatinine clearance and body weight gain on feeding APD compared to control healthy group. Feeding the functional foods produced amelioration in the different biochemical parameters and body weight gain indicating improvement in kidney function.

Keywords: Functional food, kidney dysfunction, rats.

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Authors: Jatinderkumar R. Saini, Apurva A. Desai

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e-mail has become an important means of electronic communication but the viability of its usage is marred by Unsolicited Bulk e-mail (UBE) messages. UBE consists of many types like pornographic, virus infected and 'cry-for-help' messages as well as fake and fraudulent offers for jobs, winnings and medicines. UBE poses technical and socio-economic challenges to usage of e-mails. To meet this challenge and combat this menace, we need to understand UBE. Towards this end, the current paper presents a content-based textual analysis of nearly 3000 winnings-announcing UBE. Technically, this is an application of Text Parsing and Tokenization for an un-structured textual document and we approach it using Bag Of Words (BOW) and Vector Space Document Model techniques. We have attempted to identify the most frequently occurring lexis in the winnings-announcing UBE documents. The analysis of such top 100 lexis is also presented. We exhibit the relationship between occurrence of a word from the identified lexisset in the given UBE and the probability that the given UBE will be the one announcing fake winnings. To the best of our knowledge and survey of related literature, this is the first formal attempt for identification of most frequently occurring lexis in winningsannouncing UBE by its textual analysis. Finally, this is a sincere attempt to bring about alertness against and mitigate the threat of such luring but fake UBE.

Keywords: Lexis, Unsolicited Bulk e-mail (UBE), Vector SpaceDocument Model, Winnings, Lottery

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Authors: Madi Rafik, Guenfoud Mohamed

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In recent years, rehabilitation has been the subject of extensive research due to increased spending on building work and repair of built works. In all cases, it is absolutely essential to carry out methods of strengthening or repair of structural elements, and that following an inspection analysis and methodology of a correct diagnosis. The reinforced concrete columns are important elements in building structures. They support the vertical loads and provide bracing against the horizontal loads. This research about the behavior of reinforced concrete rectangular columns, rehabilitated by concrete liner, confinement FRP fabric, steel liner or cage formed by metal corners. It allows comparing the contributions of different processes used perspective section resistance elements rehabilitated compared to that is not reinforced or repaired. The different results obtained revealed a considerable gain in bearing capacity failure of reinforced sections cladding concrete, metal bracket, steel plates and a slight improvement to the section reinforced with fabric FRP. The use of FRP does not affect the weight of the structures, but the use of different techniques cladding increases the weight of elements rehabilitated and therefore the weight of the building which requires resizing foundations.

Keywords: cladding, Rehabilitation, reinforced concrete columns, confinement, composite materials.

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Authors: D. Abdul Budan, T.S. Manjunatha

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This paper demonstrates the feasibility of replacing the metal coil spring with the composite coil spring. Three different types of springs were made using glass fiber, carbon fiber and combination of glass fiber and carbon fiber. The objective of the study is to reduce the weight of the spring. According to the experimental results the spring rate of the carbon fiber spring is 34% more than the glass fiber spring and 45% more than the glass fiber/carbon fiber spring. The weight of the carbon fiber spring is 18% less than the glass fiber spring, 15% less than the Glass fiber/carbon fiber spring and 80% less than the steel spring.

Keywords: Carbon fiber, Glass fiber, Helical composite spring, spring rate.

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Authors: Sarma. M.V.R.K, Saharan. K, Prakash. A, Bisaria. V. S, Sahai.V

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Vermiculite was used to develop inorganic carrier-based formulations of fluorescent pseudomonad strains R62 and R81. The effect of bio-inoculation of fluorescent pseudomonad strains R62 and R81 (plant growth promoting and biocontrol agent) on growth responses of Vigna-mungo under field condition was enumerated. The combined bioinoculation of these two organisms in a formuation increased the pods yield by 300% in comparison to the control crop. There was also significant increment in the other plant growth responses such as dry root weight, dry shoot weight, shoot length and number of branches per plant.

Keywords: Bio-inoculants formulation, Fluorescent pseudomonad, Plant growth promotion activity.

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Authors: Makan Cheraghpour, Seyed Ahmad Hosseini, Damoon Ashtary-Larky, Saeed Shirali, Matin Ghanavati, Meysam Alipour

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Background: In addition to reducing body weight, the low-calorie diets can reduce the lean body mass. It is hypothesized that in addition to reducing the body weight, the low-calorie diets can maintain the lean body mass. So, the current study aimed at evaluating the effects of high-protein diet with calorie restriction on body composition in overweight and obese individuals. Methods: 36 obese and overweight subjects were divided randomly into two groups. The first group received a normal-protein, low-energy diet (RDA), and the second group received a high-protein, low-energy diet (2×RDA). The anthropometric indices including height, weight, body mass index, body fat mass, fat free mass, and body fat percentage were evaluated before and after the study. Results: A significant reduction was observed in anthropometric indices in both groups (high-protein, low-energy diets and normal-protein, low-energy diets). In addition, more reduction in fat free mass was observed in the normal-protein, low-energy diet group compared to the high -protein, low-energy diet group. In other the anthropometric indices, significant differences were not observed between the two groups. Conclusion: Independently of the type of diet, low-calorie diet can improve the anthropometric indices, but during a weight loss, high-protein diet can help the fat free mass to be maintained.

Keywords: Diet, high-protein, body mass index, body fat percentage.

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Authors: Elena Ezhova, Vadim Mottl, Olga Krasotkina

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The problem of estimating time-varying regression is inevitably concerned with the necessity to choose the appropriate level of model volatility - ranging from the full stationarity of instant regression models to their absolute independence of each other. In the stationary case the number of regression coefficients to be estimated equals that of regressors, whereas the absence of any smoothness assumptions augments the dimension of the unknown vector by the factor of the time-series length. The Akaike Information Criterion is a commonly adopted means of adjusting a model to the given data set within a succession of nested parametric model classes, but its crucial restriction is that the classes are rigidly defined by the growing integer-valued dimension of the unknown vector. To make the Kullback information maximization principle underlying the classical AIC applicable to the problem of time-varying regression estimation, we extend it onto a wider class of data models in which the dimension of the parameter is fixed, but the freedom of its values is softly constrained by a family of continuously nested a priori probability distributions.

Keywords: Time varying regression, time-volatility of regression coefficients, Akaike Information Criterion (AIC), Kullback information maximization principle.

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Authors: Ahmed M. Hemeida, Wael A. Farag, Osama A. Mahgoub

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This paper focuses on developing an integrated reliable and sophisticated model for ultra large wind turbines And to study the performance and analysis of vector control on large wind turbines. With the advance of power electronics technology, direct driven multi-pole radial flux PMSG (Permanent Magnet Synchronous Generator) has proven to be a good choice for wind turbines manufacturers. To study the wind energy conversion systems, it is important to develop a wind turbine simulator that is able to produce realistic and validated conditions that occur in real ultra MW wind turbines. Three different packages are used to simulate this model, namely, Turbsim, FAST and Simulink. Turbsim is a Full field wind simulator developed by National Renewable Energy Laboratory (NREL). The wind turbine mechanical parts are modeled by FAST (Fatigue, Aerodynamics, Structures and Turbulence) code which is also developed by NREL. Simulink is used to model the PMSG, full scale back to back IGBT converters, and the grid.

Keywords: FAST, Permanent Magnet Synchronous Generator(PMSG), TurbSim, Vector Control and Pitch Control

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Authors: O. A. Anjola, M. A. Adejobi, L. A Tijani

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This study was conducted to investigate the effects of brewer spent grain (BSG) on growth performance and serum biochemistry characteristics of blood of broilers chickens. Three hundred and fifteen (4 weeks old) Oba – Marshall Broilers were used for the experiment. Five experimental diets were formulated with diet 1 (T1) containing 100% soya bean meal as the control, Diet 2, 3, 4 and 5 had BSG as replacement for soya bean meal at 0%, 36%, 57%, 76% and 100% respectively. The birds were allocated into each dietary group in a completely randomized design with 63 chicks in 3 replicates of 21 chicks each. The birds were offered these diets ad libitum from four weeks old to nine weeks old (35 days). Feed intake, body weight, weight gain, and feed conversion ratio (FCR) were assessed. Blood samples were also collected to examine the effect of BSG waste on hematology and serum biochemistry of broilers. Result indicated that BSG did not significantly (P>0.05) affect feed intake and weight gain. However, FCR and final weight of finishing broilers differs significantly (P<0.05) among treatments. The blood hematology and serum biochemistry indices did not follow a particular trend. Cholesterol concentration reduced with increasing level of BSG in the diet. Hb, RBC, WBC, neutrophils, lymphocytes, heterophiles and MCHC were significant (P<0.05) while MHC and MVC were not significantly (P>0.05) affected by BSG in diets. serum total protein, albumin, and cholesterol concentration also showed significance (P<0.05) difference. Thus, BSG can replace soya bean meal up to 14% in the broiler finisher diet without deleterious effect on the growth, hematology and the serum biochemistry of broiler chicken.

Keywords: Broilers, growth performance, hematology, serum biochemistry.

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Authors: Andreas Theissler, Ian Dear

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In the automotive industry test drives are being conducted during the development of new vehicle models or as a part of quality assurance of series-production vehicles. The communication on the in-vehicle network, data from external sensors, or internal data from the electronic control units is recorded by automotive data loggers during the test drives. The recordings are used for fault analysis. Since the resulting data volume is tremendous, manually analysing each recording in great detail is not feasible. This paper proposes to use machine learning to support domainexperts by preventing them from contemplating irrelevant data and rather pointing them to the relevant parts in the recordings. The underlying idea is to learn the normal behaviour from available recordings, i.e. a training set, and then to autonomously detect unexpected deviations and report them as anomalies. The one-class support vector machine “support vector data description” is utilised to calculate distances of feature vectors. SVDDSUBSEQ is proposed as a novel approach, allowing to classify subsequences in multivariate time series data. The approach allows to detect unexpected faults without modelling effort as is shown with experimental results on recordings from test drives.

Keywords: Anomaly detection, fault detection, test drive analysis, machine learning.

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Authors: I. Yakubu, D. Mireku-Gyimah, D. Asafo-Adjei

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The challenge for everyone involved in preserving the ecosystem is to find creative ways to protect and restore the remaining ecosystems while accommodating and enhancing the country social and economic well-being. Frequent fires of anthropogenic origin have been affecting the ecosystems in many countries adversely. Hence adopting ways of decision making such as Multicriteria Decision Making (MCDM) is appropriate since it will enhance the evaluation and analysis of fire risk and hazard of the ecosystem. In this paper, fire risk and hazard data from the West Gonja area of Ghana were used in some of the methods (Analytical Hierarchy Process, Compromise Programming, and Grey Relational Analysis (GRA) for MCDM evaluation and analysis to determine the optimal weight method for fire risk and hazard. Ranking of the land cover types was carried out using; Fire Hazard, Fire Fighting Capacity and Response Risk Criteria. Pairwise comparison under Analytic Hierarchy Process (AHP) was used to determine the weight of the various criteria. Weights for sub-criteria were also obtained by the pairwise comparison method. The results were optimised using GRA and Compromise Programming (CP). The results from each method, hybrid GRA and CP, were compared and it was established that all methods were satisfactory in terms of optimisation of weight. The most optimal method for spatial multicriteria evaluation was the hybrid GRA method. Thus, a hybrid AHP and GRA method is more effective method for ranking alternatives in MCDM than the hybrid AHP and CP method.

Keywords: Compromise programming, grey relational analysis, spatial multi-criteria, weight optimisation.

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Authors: S. Desouky, A. Al sabagh , M. Betiha, A. Badawi, A. Ghanem, S. Khalil

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Two Amphiphilic catalysts, iron (III) dodecylbenzene sulfonate and nickel (II) dodecylbenzene sulfonate, were synthesized and used in the catalytic aquathermolysis of heavy crude oil to reduce its viscosity. The prepared catalysts exhibited good performance in the aquathermolysis and the viscosity is reduced by ~ 78.9 % for Egyptian heavy crude oil. The chemical and physical properties of heavy oil both before and after reaction were investigated by FT-IR, dynamic viscosity, molecular weight and SARA analysis. The results indicated that the content of resin, asphaltene, average molecular weight and sulfur content of heavy oil is reduced after the catalytic aquathermolysis.

Keywords: Amphiphilic catalyst, Aquathermolysis, Heavy oil, Viscosity reduction.

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Authors: Jérôme Azé, Mathieu Roche, Yves Kodratoff, Michèle Sebag

Abstract:

Term Extraction, a key data preparation step in Text Mining, extracts the terms, i.e. relevant collocation of words, attached to specific concepts (e.g. genetic-algorithms and decisiontrees are terms associated to the concept “Machine Learning" ). In this paper, the task of extracting interesting collocations is achieved through a supervised learning algorithm, exploiting a few collocations manually labelled as interesting/not interesting. From these examples, the ROGER algorithm learns a numerical function, inducing some ranking on the collocations. This ranking is optimized using genetic algorithms, maximizing the trade-off between the false positive and true positive rates (Area Under the ROC curve). This approach uses a particular representation for the word collocations, namely the vector of values corresponding to the standard statistical interestingness measures attached to this collocation. As this representation is general (over corpora and natural languages), generality tests were performed by experimenting the ranking function learned from an English corpus in Biology, onto a French corpus of Curriculum Vitae, and vice versa, showing a good robustness of the approaches compared to the state-of-the-art Support Vector Machine (SVM).

Keywords: Text-mining, Terminology Extraction, Evolutionary algorithm, ROC Curve.

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Authors: Orkide Donma, Mustafa M. Donma

Abstract:

Chronologic age (CA) of individuals is closely related to obesity and generally affects the magnitude of obesity parameters. On the other hand, close association between basal metabolic rate (BMR) and metabolic age (MA) is also a matter of concern. It is suggested that MA higher than CA is the indicator of the need to improve the metabolic rate. In this study, the aim was to assess some commonly used obesity parameters, such as obesity degree, visceral adiposity, BMR, BMR-to-weight ratio, in several groups with varying differences between MA and CA values. The study comprises adults, whose ages vary between 18 and 79 years. Four groups were constituted. Group 1, 2, 3 and 4 were composed of 55, 33, 76 and 47 adults, respectively. The individuals exhibiting -1, 0 and +1 for their MA-CA values were involved in Group 1, which was considered as the control group. Those, whose MA-CA values varying between -5 and -10 participated in Group 2. Those, whose MAs above their real ages were divided into two groups [Group 3 (MA-CA; from +5 to + 10) and Group 4 (MA-CA; from +11 to + 12)]. Body mass index (BMI) values were calculated. TANITA body composition monitor using bioelectrical impedance analysis technology was used to obtain values for obesity degree, visceral adiposity, BMR and BMR-to-weight ratio. The compiled data were evaluated statistically using a statistical package program; SPSS. Mean ± SD values were determined. Correlation analyses were performed. The statistical significance degree was accepted as p < 0.05. The increase in BMR was positively correlated with obesity degree. MAs and CAs of the groups were 39.9 ± 16.8 vs 39.9 ± 16.7 years for Group 1, 45.0 ± 15.3 vs 51.4 ± 15.7 years for Group 2, 47.2 ± 12.7 vs 40.0 ± 12.7 years for Group 3, and 53.6 ± 14.8 vs 42 ± 14.8 years for Group 4. BMI values of the groups were 24.3 ± 3.6 kg/m², 23.2 ± 1.7 kg/m², 30.3 ± 3.8 kg/m², and 40.1 ± 5.1 kg/m² for Group 1, 2, 3 and 4, respectively. Values obtained for BMR were 1599 ± 328 kcal in Group 1, 1463 ± 198 kcal in Group 2, 1652 ± 350 kcal in Group 3, and 1890 ± 360 kcal in Group 4. A correlation was observed between BMR and MA-CA values in Group 1. No correlation was detected in other groups. On the other hand, statistically significant correlations between MA-CA values and obesity degree, BMI as well as BMR/weight were found in Group 3 and in Group 4. It was concluded that upon consideration of these findings in terms of MA-CA values, BMR-to-weight ratio was found to be much more useful indicator of the severe increase in obesity development than BMR. Also, the lack of associations between MA and BMR as well as BMR-to-weight ratio emphasize the importance of consideration of MA-CA values rather than MA.

Keywords: Basal metabolic rate, chronologic age, metabolic age, obesity degree.

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Authors: Nneka N. Uchegbu

Abstract:

Physical, sensory properties and hypoglycemic effect of crackers produced from sprouted pigeon pea, unripe plantain and brewers’ spent grain fed to diabetic rats were investigated. Different composite flours were used to produce crackers. Physical and sensory properties of the crackers, the blood serum of the rats and changes in the rat body weight were measured. Spread ratio and break strength of the crackers from different flour blends ranges from 7.01 g to 8.51 g and 1.87 g to 3.01 g respectively. The acceptability of the crackers revealed that Sample A (100% wheat crackers) was not significantly (p>0.05) different from Samples C and D. Feeding the rats with formulated crackers caused an increase in the body weight of the rats but a reduced body weight was observed in diabetic rats fed with normal rat feed. The result indicated that cracker produced from the formulated flour blends caused a significant hypoglycemic effect in diabetic rats and led to a reduction of measured biochemical indices. Therefore, this work showed that consumption of crackers from the above formulated flour blend was able to decrease hyperglycemia in diabetic rats.

Keywords: Hypoglycemia, hyperlipidemia, total lipid, triglyceride, total cholesterol.

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Authors: G. Settanni, A. Panarese, R. Vaira, A. Galiano

Abstract:

Nowadays, artificial intelligence is used successfully in the field of e-commerce for its ability to learn from a large amount of data. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them the most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Also, Long Short-Term Memory algorithms have been implemented and trained on historical data in order to predict customer scores of the different items. Items with the highest scores are recommended to customers.

Keywords: Deep Learning, Long Short-Term Memory, Machine Learning, Recommender Systems, Support Vector Machine.

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Authors: A. Khalique, T. Naseem, N. Haque, Z. Rasool

Abstract:

The objective of current study was to investigate the effect of Bacillus subtilis PB6 (CloSTAT) as a probiotic in broilers. The corn-soybean based diet was divided into four treatment groups; T1 (basal diet with no probiotic and no Clostridium perfringens); T2 (basal diet challenged with C. perfringens without probiotic); T3 (basal diet challenged with C. perfringens having 0.05% probiotic); T4 (basal diet challenged with C. perfringens having 0.1% probiotic). Every treatment group had four replicates with 24 birds each. Body weight and feed intake were measured on weekly basis, while ileal bacterial count was recorded on day-28 following Clostridium perfringens challenge. The 0.1% probiotic treatment showed 7.2% increase in average feed intake (P=0.05) and 8% increase in body weight compared to T2. In 0.1% treatment body weight was 5% higher than T3 (P=0.02). It was also observed that 0.1% treatment had improved feed conversion ratio (1.77) on 6^th week. No effect of treatment was observed on mortality and ileal bacterial count. The current study indicated that 0.1% use of probiotic had positive response in C. perfringens challenged broilers.

Keywords: Bacillus subtilis PB6, antibiotic growth promoters, Clostridium perfringens, CloSTAT, broilers.

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