Abstract: Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.
Abstract: The purchase impulsiveness is preceded by a lack of self-control: consequently, it is legitimate to believe that a consumer with a low level of self-control can result in a higher probability of cognitive dissonance. Moreover, the process of purchase is influenced by the pre-existing affective state in a considerable way. With reference to on-line purchases, digital behavior cannot be merely ascribed to the rational sphere, given the speed and ease of transactions and the hedonistic dimension of purchases. To our knowledge, this research is among the first cases of verification of the effect of moderation exerted by the positive affective state in the on-line impulse purchase of products with a high expressive value such as a smartphone on the occurrence of cognitive dissonance. To this aim, a moderation analysis was conducted on a sample of 212 impulsive millennials buyers. Three scales were adopted to measure the constructs of interest: IBTS for impulsivity, PANAS for the affective state, Sweeney for cognitive dissonance. The analysis revealed that positive affective state does not affect the onset of cognitive dissonance.
Abstract: Shear displacement along bedding defects is a well-recognised behaviour when tunnelling and mining in stratified rock. This deformation can affect the durability and integrity of installed rock bolts. In-situ monitoring of rock bolt deformation under bedding shear cannot be accurately derived from traditional strain gauge bolts as sensors are too large and spaced too far apart to accurately assess concentrated displacement along discrete defects. A possible solution to this is the use of fiber optic technologies developed for precision monitoring. Distributed Optic Sensor (DOS) embedded rock bolts were installed in a tunnel project with the aim of measuring the bolt deformation profile under significant shear displacements. This technology successfully measured the 3D strain distribution along the bolts when subjected to bedding shear and resolved the axial and lateral strain constituents in order to determine the deformational geometry of the bolts. The results are compared well with the current visual method for monitoring shear displacement using borescope holes, considering this method as suitable.
Abstract: This work is intended to study the post-failure characteristic behaviour of rocks and the techniques of controlling the post-failure regime based on the mechanism of rocks deformation process. It is impossible to determine the post-failure regime of rocks using conventional laboratory testing equipment. This is because most testing machines are soft and therefore no information can be obtained after the peak load. Stress-strain deformation tests were conducted using both conventional and unconventional method (i.e. the closed loop servo-controlled testing machine) in accordance to ISRM standard. Normalised pre-failure curves were constructed to show the stages in the deformation process. The first type contains the Class I and progress to Class II with low strength soft brittle rocks. The second type shows entirely Class II characteristic behaviour. The third type is extremely brittle under axial loading, resulted in explosive failure, so its class could not be determined. The difficulty in obtaining the post-failure curves increases as the total volumetric strain approaches a positive value. The author’s use of normalised pre-failure curves enables identification of additional type of deformation process with very brittle response under axial loading. Testing the third type without confinement could cause equipment damage. Identification of the deformation process with the rock classes using conventional test could guide the personnel conducting tests using closed-loop servo-controlled system, to avoid equipment damage when testing rocks with third type deformation process so that testing is performed safely. It has also improved our understanding on total specimen failure and brittleness of rocks (e.g. brittle for Class II and less brittle or ductile for Class I).
Abstract: This work is carried out to evaluate the possibility of using to-be-wasted steel as reinforcement after welding together pieces of reinforcing steel bars, left over during construction activities. Tests were performed on a total of nine samples. These were made by welding pieces of reinforcing steel bars purchased from the local scrap steel market. The samples were tested in uniaxial tension using a universal testing machine (UTM). It was found that the failure of the welded bars is governed by the thickness of the weld. It is concluded that suitable design of the weld is essential for achieving the desired level of ductility/elongation of these bars, if they are to be used as conventional reinforcement in reinforced concrete members.
Abstract: Magnetic susceptibility (χ) is operational to identify of late quaternary glacial-interglacial cycles in loess-paleosol sequences. It is well accepted that many loess-paleosol sequences bear witness to cold-dry/warm-humid periods, well known as glacial-interglacial cycles, respectively. For this study, loess-paleosol sequence of north-east of Iran was magnetically investigated. The study area is situated at about 8 km away of Neka city, on the main road of Sari-Behshahr, in Mazandaran Province, north of Iran. The youngest deposits of study area are the late Quaternary wind-blown accumulations. In this study, the total number of 117 samples was collected from loess-paleosols units. After that, the natural remnant magnetization (NRM) and magnetic susceptibility (MS) of the samples were measured. Variation of MS of more than 110 loess samples was plotted to reveal the correlation of the MS and paleoclimatic changes. This study aims reconstruction of climatic changes (glacial-interglacial and stadials-interstadials cycles). To confirm our results we compared MS (χ) and the curves of other investigations in paleoclimatology. This correspondence abled us to recognize worldly events in the study area such as: Younger Dryas, the Last Glacial Maximum (LGM), deglaciation of Northern Hemisphere etc. The obtained magnetic data indicate that during almost 50 ka, at least two glacial-interglacial periods occurred in north-east of Iran. Further, variation of χ values revealed short period of climatically cycles known as stadials-interstadials. We recognized 4 stadials and a single stadial as colder sub-periods for S0 (recently soil-paleosol) and S2 (lower paleosol), respectively, Moreover, we recognized 6 warmer sub-periods (interstadials) for L1 (upper loess) and one interstadial L2 (lower loess).
Abstract: The purpose of this quantitative study is to identify the impact of the destination attributes of Negombo on the coastal tourists’ visitor experience. As an island nation, Sri Lanka is identified and well renowned for its gold sandy beaches and natural scenic beauty. Among many tourist attractions, Negombo is identified as a developed beach centric tourist destination in the country. Yet, it is identified that there are low positive reviews on the internet for Negombo compared to other beach centric tourist attractions in Sri Lanka. Therefore, this study would help the policymakers and tourism service providers to identify the impact of destination attributes on international visitor satisfaction and to understand the visitors comprehensively so as to develop Negombo as a stable tourist destination while offering a memorable and satisfying experience for its visitors. In support, a self-administered questionnaire survey study was performed with 150 respondents (international tourists) in Negombo. The questions were designed based on the selected dimensions of destination attributes such as tourism service quality, infrastructure and superstructure developments, tourist information facilities and destination aesthetics and developments. The results showed that the overall satisfaction level of the international tourists who visit Sri Lanka is significantly affected by the destination attributes of Negombo. Yet, the dimensions of destination aesthetics and developments and tourist information facilities indicated a low level of mean satisfaction, paving the critique that Negombo as a beach centric tourist attraction is not serving well with its natural beauty and its destination management. Further, it is advocated that the policymakers and tourism service providers have a significant role in leading the way to attract more potential visitors to enhance their destination satisfaction and to encourage them to revisit Sri Lanka while recommending it to others. The survey was done during the off-peak season of the industry and it is suggested that the survey would have been conducted throughout a complete year.
Abstract: Since China has entered an era of mass tourism, there has been a fundamental change in the way Chinese people approach and perceive the image of other countries. With the advent of the new media era, social networking sites such as Sina Weibo have become a tool for many foreign governmental organizations to spread and promote their national image. Among them, the Japan National Tourism Organization (JNTO) was one of the first foreign official tourism agencies to register with Sina Weibo and actively implement communication activities. Due to historical and political reasons, cognition of Japan's national image by the Chinese has always been complicated and contradictory. However, since 2015, China has become the largest source of tourists visiting Japan. This clearly indicates that the broadening of Japan's national image in China has been effective and has value worthy of reference in promoting a positive Chinese perception of Japan and encouraging Japanese tourism. Within this context and using the method of content analysis in media studies through content mining software, this study analyzed how JNTO’s Sina Weibo accounts have constructed and spread Japan's national image. This study also summarized the characteristics of its content and form, and finally revealed the strategy of JNTO in building its international image. The findings of this study not only add a tourism-based perspective to traditional national image communications research, but also provide some reference for the effective international dissemination of national image in the future.
Abstract: A compact design of multi-sector patch antenna array for 60 GHz applications is presented and discussed in details. The proposed design combines five 1×8 linear patch antenna arrays, referred to as sectors, in a multi-sector configuration. The coaxial-fed radiation elements of the multi-sector array are designed on 0.2 mm Rogers RT5880 dielectrics. The array operates in the frequency range of 58-62 GHz and provides switchable directional/omnidirectional radiation beams with high gain and high directivity characteristics. The designed multi-sector array exhibits good performances and could be used in the fifth generation (5G) cellular networks.
Abstract: The present study aimed to evaluate the understanding of the students in Tehran universities (Iran) about the numerical representation of the average rate of change based on the Structure of Observed Learning Outcomes (SOLO). In the present descriptive-survey research, the statistical population included undergraduate students (basic sciences and engineering) in the universities of Tehran. The samples were 604 students selected by random multi-stage clustering. The measurement tool was a task whose face and content validity was confirmed by math and mathematics education professors. Using Cronbach's Alpha criterion, the reliability coefficient of the task was obtained 0.95, which verified its reliability. The collected data were analyzed by descriptive statistics and inferential statistics (chi-squared and independent t-tests) under SPSS-24 software. According to the SOLO model in the prestructural, unistructural, and multistructural levels, basic science students had a higher percentage of understanding than that of engineering students, although the outcome was inverse at the relational level. However, there was no significant difference in the average understanding of both groups. The results indicated that students failed to have a proper understanding of the numerical representation of the average rate of change, in addition to missconceptions when using physics formulas in solving the problem. In addition, multiple solutions were derived along with their dominant methods during the qualitative analysis. The current research proposed to focus on the context problems with approximate calculations and numerical representation, using software and connection common relations between math and physics in the teaching process of teachers and professors.
Abstract: This study investigated factors that influence mathematics achievement based on a sample of ninth-grade students (N = 21,444) from the High School Longitudinal Study of 2009 (HSLS09). Key aspects studied included efficacy in mathematics, interest and enjoyment of mathematics, identity with mathematics and future utility beliefs and how these influence mathematics achievement. The predictability of mathematics achievement based on these factors was assessed using correlation coefficients and multiple linear regression. Spearman rank correlations and multiple regression analyses indicated positive and statistically significant relationships between the explanatory variables: mathematics efficacy, identity with mathematics, interest in and future utility beliefs with the response variable, achievement in mathematics.
Abstract: With the birth of Islam, the definitions of paradise in Quran have spread across three continents since 7th century, showing itself in the palace gardens as a reflection of Islamic Culture. The design characteristics of Islamic gardens come forth with the influence of religious beliefs, as well as taking its form as per the cultural, climatic and soil characteristics of its geography, and showing its difference. It is possible to see these differences from the garden examples that survived to present time from the civilizations in the lands of Islamic proliferation. The main material of this research is the Islamic gardens in Iran and Spain. Field study was carried out in Alhambra Palace in Spain, Granada and Shah Goli garden in Iran, Tabriz. In this study, the birth of Islamic gardens, spatial perception of paradise, design principles, spatial structure, along with the structural/plantation materials used are examined. Also the characteristics and differentiation of the gardens examined in different cultures and geographies have been revealed. In the conclusion section, Iran and Spain Islamic garden samples were evaluated and their properties were determined.
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.
Abstract: Laboratory trial results of mixing crumb rubber produced from discarded tires with 60/70 pen grade Kuwaiti bitumen are presented on this paper. PG grading and multiple stress creep recovery tests were conducted on Kuwaiti bitumen blended with 15% and 18% crumb rubber at temperatures ranging from 40 to 70 °C. The results from elastic recovery and non-recoverable creep presented optimum performance at 18% rubber content. The optimum rubberized-bitumen mix was next transformed into a pelletized form (PelletPave®), and was used as a partial replacement to the conventional bitumen in the manufacture of continuously graded hot mix asphalts at a number of binder contents. The trialed PelletPave® contents were at 2.5%, 3.0%, and 3.5% by mass of asphalt mix. In this investigation, it was not possible to utilize the results of standard Marshall method of mix design (i.e. volumetric, stability and flow tests) and subsequently additional assessment of mix compactability was carried out using gyratory compactor in order to determine the optimum PelletPave® and total binder contents.
Abstract: The impact of metabolic syndrome (MetS) on cognition and functions of the brain is being investigated. Iron deficiency and deficiencies of B9 (folate) as well as B12 (cobalamin) vitamins are best-known nutritional anemias. They are associated with cognitive disorders and learning difficulties. The antidepressant effects of vitamin D are known and the deficiency state affects mental functions negatively. The aim of this study is to investigate possible correlations of MetS with serum brain-derived neurotrophic factor (BDNF), iron, folate, cobalamin and vitamin D in pediatric patients. 30 children, whose age- and sex-dependent body mass index (BMI) percentiles vary between 85 and 15, 60 morbid obese children with above 99th percentiles constituted the study population. Anthropometric measurements were taken. BMI values were calculated. Age- and sex-dependent BMI percentile values were obtained using the appropriate tables prepared by the World Health Organization (WHO). Obesity classification was performed according to WHO criteria. Those with MetS were evaluated according to MetS criteria. Serum BDNF was determined by enzyme-linked immunosorbent assay. Serum folate was analyzed by an immunoassay analyzer. Serum cobalamin concentrations were measured using electrochemiluminescence immunoassay. Vitamin D status was determined by the measurement of 25-hydroxycholecalciferol [25-hydroxy vitamin D3, 25(OH)D] using high performance liquid chromatography. Statistical evaluations were performed using SPSS for Windows, version 16. The p values less than 0.05 were accepted as statistically significant. Although statistically insignificant, lower folate and cobalamin values were found in MO children compared to those observed for children with normal BMI. For iron and BDNF values, no alterations were detected among the groups. Significantly decreased vitamin D concentrations were noted in MO children with MetS in comparison with those in children with normal BMI (p ≤ 0.05). The positive correlation observed between iron and BDNF in normal-BMI group was not found in two MO groups. In THE MetS group, the partial correlation among iron, BDNF, folate, cobalamin, vitamin D controlling for waist circumference and BMI was r = -0.501; p ≤ 0.05. None was calculated in MO and normal BMI groups. In conclusion, vitamin D should also be considered during the assessment of pediatric MetS. Waist circumference and BMI should collectively be evaluated during the evaluation of MetS in children. Within this context, BDNF appears to be a key biochemical parameter during the examination of obesity degree in terms of mental functions, cognition and learning capacity. The association observed between iron and BDNF in children with normal BMI was not detected in MO groups possibly due to development of inflammation and other obesity-related pathologies. It was suggested that this finding may contribute to mental function impairments commonly observed among obese children.
Abstract: Basal metabolic rate (BMR) is widely used and an accepted measure of energy expenditure. Its principal determinant is body mass. However, this parameter is also correlated with a variety of other factors. The objective of this study is to measure BMR and compare it with the values obtained from predictive equations in adults classified according to their body mass index (BMI) values. 276 adults were included into the scope of this study. Their age, height and weight values were recorded. Five groups were designed based on their BMI values. First group (n = 85) was composed of individuals with BMI values varying between 18.5 and 24.9 kg/m2. Those with BMI values varying from 25.0 to 29.9 kg/m2 constituted Group 2 (n = 90). Individuals with 30.0-34.9 kg/m2, 35.0-39.9 kg/m2, > 40.0 kg/m2 were included in Group 3 (n = 53), 4 (n = 28) and 5 (n = 20), respectively. The most commonly used equations to be compared with the measured BMR values were selected. For this purpose, the values were calculated by the use of four equations to predict BMR values, by name, introduced by Food and Agriculture Organization (FAO)/World Health Organization (WHO)/United Nations University (UNU), Harris and Benedict, Owen and Mifflin. Descriptive statistics, ANOVA, post-Hoc Tukey and Pearson’s correlation tests were performed by a statistical program designed for Windows (SPSS, version 16.0). p values smaller than 0.05 were accepted as statistically significant. Mean ± SD of groups 1, 2, 3, 4 and 5 for measured BMR in kcal were 1440.3 ± 210.0, 1618.8 ± 268.6, 1741.1 ± 345.2, 1853.1 ± 351.2 and 2028.0 ± 412.1, respectively. Upon evaluation of the comparison of means among groups, differences were highly significant between Group 1 and each of the remaining four groups. The values were increasing from Group 2 to Group 5. However, differences between Group 2 and Group 3, Group 3 and Group 4, Group 4 and Group 5 were not statistically significant. These insignificances were lost in predictive equations proposed by Harris and Benedict, FAO/WHO/UNU and Owen. For Mifflin, the insignificance was limited only to Group 4 and Group 5. Upon evaluation of the correlations of measured BMR and the estimated values computed from prediction equations, the lowest correlations between measured BMR and estimated BMR values were observed among the individuals within normal BMI range. The highest correlations were detected in individuals with BMI values varying between 30.0 and 34.9 kg/m2. Correlations between measured BMR values and BMR values calculated by FAO/WHO/UNU as well as Owen were the same and the highest. In all groups, the highest correlations were observed between BMR values calculated from Mifflin and Harris and Benedict equations using age as an additional parameter. In conclusion, the unique resemblance of the FAO/WHO/UNU and Owen equations were pointed out. However, mean values obtained from FAO/WHO/UNU were much closer to the measured BMR values. Besides, the highest correlations were found between BMR calculated from FAO/WHO/UNU and measured BMR. These findings suggested that FAO/WHO/UNU was the most reliable equation, which may be used in conditions when the measured BMR values are not available.
Abstract: Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.
Abstract: Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.
Abstract: The biochemical industry is one of the most important modern industries. Biochemical reactors are crucial devices of the biochemical industry. The essential bioprocess carried out in bioreactors is the fermentation process. A thorough insight into the fermentation process and the knowledge how to control it are essential for effective use of bioreactors to produce high quality and quantitatively enough products. The development of the control system starts with the determination of a mathematical model that describes the steady state and dynamic properties of the controlled plant satisfactorily, and is suitable for the development of the control system. The paper analyses the fermentation process in bioreactors thoroughly, using existing mathematical models. Most existing mathematical models do not allow the design of a control system for controlling the fermentation process in batch bioreactors. Due to this, a mathematical model was developed and presented that allows the development of a control system for batch bioreactors. Based on the developed mathematical model, a control system was designed to ensure optimal response of the biochemical quantities in the fermentation process. Due to the time-varying and non-linear nature of the controlled plant, the conventional control system with a proportional-integral-differential controller with constant parameters does not provide the desired transient response. The improved adaptive control system was proposed to improve the dynamics of the fermentation. The use of the adaptive control is suggested because the parameters’ variations of the fermentation process are very slow. The developed control system was tested to produce dairy products in the laboratory bioreactor. A carbon dioxide concentration was chosen as the controlled variable. The carbon dioxide concentration correlates well with the other, for the quality of the fermentation process in significant quantities. The level of the carbon dioxide concentration gives important information about the fermentation process. The obtained results showed that the designed control system provides minimum error between reference and actual values of carbon dioxide concentration during a transient response and in a steady state. The recommended control system makes reference signal tracking much more efficient than the currently used conventional control systems which are based on linear control theory. The proposed control system represents a very effective solution for the improvement of the milk fermentation process.
Abstract: This paper presents wavelet based classification of various heart diseases. Electrocardiogram signals of different heart patients have been studied. Statistical natures of electrocardiogram signals for different heart diseases have been compared with the statistical nature of electrocardiograms for normal persons. Under this study four different heart diseases have been considered as follows: Myocardial Ischemia (MI), Congestive Heart Failure (CHF), Arrhythmia and Sleep Apnea. Statistical nature of electrocardiograms for each case has been considered in terms of kurtosis values of two types of wavelet coefficients: approximate and detail. Nine wavelet decomposition levels have been considered in each case. Kurtosis corresponding to both approximate and detail coefficients has been considered for decomposition level one to decomposition level nine. Based on significant difference, few decomposition levels have been chosen and then used for classification.