Abstract:Clustering is an essential unsupervised method in pattern recognition of data mining domains. The main challenge of cluster is how to evaluate the result based on the compactness and correctness of the clustering data points. There are two methods are used for evaluating the cluster validity that are internal validity index and external validity index. Internal indices determine the quality of a clustering solution using the underlying data. External indices compare the clustering results with respect to a pre-specified structure of the data points. Out of two methods of cluster validity, this research concentrates only the internal cluster evaluation indexes with different multivariate data sets. In this paper, the validity of the cluster evaluation can only be done after the detection of outliers in the multivariate data sets. The PIMA Indian datasets are taken from the UCI machine learning repository. In this paper, four internal cluster validity indexes (CVI) that are Calinski-Harabasz index (CH), Davies-Bouldin index (DB), Silhouette index, Dunn index , R-Squared index are used to evaluate results.
Abstract:Based on the cognitive dissonance theory, the empirical results on Vietnamese consumers in purchasing green vegetables indicate that greenwash is positively associated with green perceived risk while negatively related to both green perceived quality and green purchase intentions. Moreover, as consumers have a higher degree of information and knowledge about green product, the positive nexus between greenwash and green perceived risk will be weakened meanwhile the negative relationship between greenwash and green perceived quality will be strengthened. A noteworthy point is that green perceived risk and green perceived quality partially mediate the impacts of greenwash on green purchase intentions. The results offer new insights on how to make green marketing strategies to enhance green purchase intentions and avoid the potential consequences of greenwashing.
Abstract:Twenty-four male lambs (Rambouillet 23.5 kg ï¿½ 3.17 kg initial BW) were fed a basal diet with treatments which consisted of a control and oral doses of ruminally-protected choline (4 g/d RPC) and plant-based choline (4 g/d Biocholine) in a completely randomized design with initial weight as a covariate. The experiment was conducted for 42 days during which live weight, dry matter intake, carcass characteristics, blood metabolites and basic hemograms were measured. The daily gain in lambs was similar between treatments. Intake was higher in lambs given Biocholine (1.32 kg/d). The L value and mineral content in the meat were improved with both sources of choline. Blood triglycerides increased by RPC compared with the other treatments, and cholesterol was reduced by Biocholine. Alanine transaminase (ALT) and aspartate aminotransferase (AST) activity decreased by effect of choline. Hematological parameters were affected by choline supplementation regardless of the source; erythrocyte, monocytes and lymphocytes count decreased with both sources of choline in growing lambs.
Abstract:The aim of the present study was to evaluate the effect of copra meal on in vitro ruminal kinetic and greenhouse gases production and in vivo lamb performance. Twenty-eight male Rambouillet sheep (initial body weight 24.5± 3.9 kg) were randomly assigned to one of the following treatments: 0, 50, 100 and 150 g of copra meal per kg of diet (dry matter basis). Final weight, weight gain and feed intake were not affected (P > 0.05) by copra meal addition. Gas production volume decreased and gas production rate increased, in a linear trend (P<0.05) as copra meal was added to diet while methane and carbon dioxide production showed an opposite quadratic trend (P<0.05) with a high and low value at 100 g/kg DM copra meal, respectively. Copra meal addition in diet decreases volume gas production and is a strategy to decline methane and carbon dioxide production in sheep feeding, without affecting animal performance.
Abstract:In view of the problems that the early warning process of low frequency oscillation in \npower system is vulnerable to the influence of complex grid environment.The classification speed \nis slow due to the large amount of processing data in the classification process. A three-stage random \nforest based on a fuzzy matrix method is proposed in this paper to improve the accuracy and the \nclassification speed of low frequency oscillation early warning in power system. Firstly, the fuzzy \nmatrix comprehensive evaluation will be carried out by PMU data, and the evaluation score S will \nbe obtained to determine whether low-frequency oscillation occurs and makes a quick warning. \nThen, the data is processed by synchronous wavelet transform (SWT), and the damping ratio and \nattenuation factor of the data are obtained. Furthermore, RF 2 and RF 3 are used to judge the type \nof low frequency oscillation. Finally, simulation results show that the comprehensive fuzzy matrix \nimproves the accuracy of low-frequency oscillation early warning, and the three-stage classification \nmethod reduces the amount of data processing and improves the classification speed and stability.
Abstract:This study analyses the impact of profitability (ROA), leverage (LEV) and corporate governance (DUAL and BS) on value creation of Real estate companies listed in the Saudi financial market (Tadawul). The study is carried out for the period 2015 – 2022. The panel data regression method is used to examine the impact of the aforementioned factors on value creation. Data consisting of a sample of 10 companies for the entire eight-year period represent the database for this study. Results obtained showed a strong significant positive relationship between leverage and board size on the one hand and value creation of a firm on the other hand. However, Profitability and CEO duality have a significant negative impact on value creation. Finally, firm size, as a control variable, negatively and significantly affects value creation. The findings are expected to have practical implications for directors and shareholders of firms operating in real estate sector and can help them in their decisions regarding financial performance and value creation.
Abstract:Siddha system of medicine is one of the Ayush systems of medicine, which is practiced widely in India, especially in the south. Pittu is one of the unexplored Siddha medicines, but it is a well-known carbohydrate diet in South India, especially in Tamil Nadu and Kerala. Pittu preparation is explained as the process of steaming moistened powder.This article explains the Pittu and form of Siddha medicine Perumpadukku Pittu (PP) indicated for Abnormal Uterine Bleeding (Natpatta perumpadu) which is present in the Siddha literature.Ingredients of the PP are Ilandhaipattai (Ziziphus mauritiania, Lam),Othiyampattai (Lannea coromandelia (houtt) Merr),Naavalpattai (Syzygium cumini,linn), Athipattai (Ficus racemose.linn), Arasampattai (Ficus religiosa.linn), Maampattai (Mangifera indica.linn), Veelampattai (Acacia nilotica.linn), Pacharasi (Oryza sativa), Panai vellam (Borassus flabellifer).Ingredients of the PP have Anti-inflammatory, Analgesic, Anti-spasmodic, and Thrombolytic action. Generally, Pittu is referred to the uterus-related problems. Hence, PP is also a good medicine for the menorrhagia. Pittu medicine is not currently available in the market due to its short shelf-life period and its frequent contamination. Due to the negligence of the Pittu like medicine, it becomes endangered. More research needs to be done to explore these types of unexplored pharmaceutical forms of medicine.
Abstract:Thalassemias, group of hereditary blood disorders with less synthesis of one or both globin chain of hemoglobin. Beta thalassemia major is linked with no formation of β-globin chain of hemoglobin and prevalent in the whole world, more affecting developing countries. The current research work was designed to investigate variations in hematological parameters due to iron overload in β-thalassemia patients. Hundred β-thalassemic male and female patients (Fifty each) were considered for this study. Blank blood sample was drawn from each patient. The t- and p-value of studied hematological parameters: red blood cells (0.781, p<0.436), platelet count (8.65, p<0.001), mean corpuscular volume (MCV) 1.27, p<0.204, mean corpuscular hemoglobin (MCH) 0.00, p<1, neutrophils (5.97, p<0.001), mean corpuscular hemoglobin concentration (MCHC) 1.44, p<0.150, hemoglobin (Hb) 15.76, p<0.001, monocytes (3.92, p<0.002), lymphocytes (11.46, p<0.001), Hematocrit (Hct) 13.49, p<0.001, total leukocyte count (TLC) 2.14, p<0.034, eiosinophils (19.95, p<0.001) red blood cell distribution width (RDW) 17.43p<0.001 and erythrocyte sedimentation rate (ESR) 12.93, p<0.001. The level of hemoglobin, Hct, RDW, lymphocytes, neutrophils, platelets, eiosinoplis, monocytes, ESR in β-thalassemic male were compared with β-thalassemic female and statistically highly significant (p<0.001) results were obtained. While non significant results were obtained when t-test was applied on RBCs, TLC, MCV, MCHC and MCH values of beta thalassemic males and females. Results of hematological parameters were significantly altered from standard values.
Abstract:In an iris recognition system, one of the main problems is the use of images with low quality, which affects the performance and effectiveness of the system. Errors in the identification process of these systems as the false acceptance and false rejection are the result of images without adequate quality. Progress in this area of research have increased, mainly supported by standards such as the ISO and NIST, which recommend the evaluation of some characteristics of iris images with the objective to assign a quality value, however, these standards are deficient by failing to establish clear criteria for assessing the quality of the images, so in this paper we propose an algorithm based on ISO / IEC 19794-6 which evaluates each requirement that the standard recommends using specifics methods, achieving classify iris images to use only those that have appropriate levels of quality, making to the iris recognition systems more efficient.
Abstract:This paper presents design and implementation of a boost converter with passive soft-switching feature to improve efficiency is presented. At first, operational principle of a Boost converter is introduced and then, a variety of soft-switching-cell topologies are discussed. In the passive soft-switching cells, an appropriate one is adopted to reduce switching loss of the DC-DC converter. For verification, a 1200 W boost converter with the soft-switching cell is studied and implemented. In addition, considerations in layout, parallel connection of MOSFETs, and resonant-component selection are also presented in detail. From hardware measurements, the boost converter can achieve high efficiency up to 95%, which also demonstrates that the soft-switching cell reduces switching loss significantly.