Open Access Short Research Article

A Study on Two Special Ternary Quadratic Diophantine Equations

Shreemathi Adiga, M. A. Gopalan

Current Journal of Applied Science and Technology, Page 1-5
DOI: 10.9734/CJAST/2018/42693

Hyperbolic paraboloids represented by the ternary quadratic diophantine equations given by (k+1)2x2 - k2y2=2z and k2ay2 – (a -k +1)x2 = ((k2 – 1)a+k – 1)z , a>k-1>0 are respectively considered. Employing matrix method, generation formula for integer solutions to each of the above hyperbolic paraboloids is constructed in the present study.

Open Access Original Research Article

Effect of Different Shade Levels on Growth, Physiology and Biochemical Characteristics of Small Cardamom (Elettaria cardamomum Maton)

M. Alagupalamuthirsolai, S. J. Ankegowda, K. S. Krishnamurthy

Current Journal of Applied Science and Technology, Page 1-9
DOI: 10.9734/CJAST/2018/42040

Elettaria cardamomum was grown under shade levels (75% shade, 50% shade and open irradiance) to evaluate its photosynthetic characteristics, physiology and biochemical characters. The highest net photosynthetic rates and stomatal conductance were observed under 75% shade, followed in descending order by 50% and open condition. The highest quantum yield of photosystem II was observed under 50% shade. As shade level increased, Chl a,Chl b and total Chl contents also increased significantly. The total number of opened stomata generally displayed the best activity in leaves subjected to 75% shade. The highest total phenol and epicuticular wax contents were observed in open irradiance treatment and highest proline level was observed in plants subjected to the 50% shade treatment.  The results indicate that increased plant height, chlorophyll and proline contents and higher quantum yield of Photosystem II and stomatal activity may play an essential role in shade adapting mechanism in small cardamom.

Open Access Original Research Article

Analysis of Milk and Biometric Traits of Brown Swiss Cattle in High Arid Climate

Oludayo Michael Akinsola, Dorcas John Jirgi, Amos Adedamola Ogundeji Ogundeji, Madaki Omammeh Shuaib, Adebayo Waheed Ismail, Louis Ugwu

Current Journal of Applied Science and Technology, Page 1-7
DOI: 10.9734/CJAST/2018/42150

The aim of the research was to estimate the genetic parameters for milk and conformation traits in Brown Swiss cattle breed. The data comprised 2,059 daily milk yield records of 404 Brown Swiss cattle that calved between 2001 and 2015. The total number of sires, dams and animal record extracted from the pedigree file were 98, 356 and 809 respectively. Heritability estimates was 0.22 for milk yield while body type traits ranged from 0.10 in central ligament through 0.48 in chest width. Repeatability estimates were low to high between milk yield and conformational traits. Overall the heritabilities of all traits were moderate to high except body condition score and chest ligament, these indicated that most traits in this herd can be improved by selective breeding.

Open Access Original Research Article

A Machine Learning Algorithm Based on Inverse Problems for Cyber Anomaly Detection

Ali Sever

Current Journal of Applied Science and Technology, Page 1-14
DOI: 10.9734/CJAST/2018/42730

With the rapid rate of technological advance, digital communications have become an integral part of our lives in e-commerce, healthcare, education, and government. As the cyber world has expanded and become more complex, it has also generated severe threats to cyber security. Adversarial attacks such as anomalies and misuses are hard to detect with conventional methods as these cyber activities look very similar to genuine ones.  There are many problems in anomaly and misuse detection of cybersecurity which can be considered as an inverse problem. In this paper, we have modeled anomaly detection system, Inverse Machine Learning Algorithm (IMLA), based on an inverse model approach with Riesz kernel and applying software system development concepts at each phase. For evaluation, the proposed approach IMLA have been compared with other state of the art supervised learning models. The experiments show the effectiveness of the proposed model IMLA.

Open Access Original Research Article

Assessment of Radiological Health Risks from Gamma Radiation Levels in Selected Oil Spill Communities of Bayelsa State, Nigeria

S. I. Ovuomarie-kevin, C. P. Ononugbo, G. O. Avwiri

Current Journal of Applied Science and Technology, Page 1-12
DOI: 10.9734/CJAST/2018/42601

Measurement of terrestrial background ionizing radiation of oil spilled communities of Bayelsa State, Nigeria was carried out using well-calibrated radalert-100 and 200 meters and a Global Positioning System (Garmin 765). The average exposure rate of the four communities 0.009±0.001, 0.010±0.002, 0.009±0.002 and 0.010±0.002 mRh-1 respectively. The mean of absorbed dose rates estimated in Otuasega, Ibelebiri, Imiringi and Otuegwe are 82.17, 86.13, 73.95 and 83.52 nGy/hr respectively. Estimated values of the annual effective dose equivalent (AEDE) for outdoor exposures 0.13 mSv/yr was obtained in Otuasega, and Ibelebiri while at Imiringi AEDE was 0.15 mSvy-1 and  0.11 mSv/yr was obtained in Otuegwe II respectively. The mean excess lifetime cancer risk calculated for the oil spill values are (0.44, 0.46, 0.40 and 0.45) x10-3 respectively. The obtained values for background ionizing radiation in Ibelebiri and Imiringi oil spill sites was below the recommended standard limits by ICRP  while the absorbed dose (D) and AEDE calculated in the entire oil spill sites are within safe values but the excess lifetime cancer risk (ELCR) estimated were higher than their world permissible values of 0.29x10-3 respectively. The calculated dose to organs showed that the testes have the highest organ dose of 0.085 mSvy-1while the liver has the lowest organ dose of 0.048 mSvy-1. The contour map of Fig. 5 showed low level of BIR sparsely distributed and also the result showed that the oil spilled had little or no impact on the background radiation of the area. 

Open Access Original Research Article

Design and Execution of Wood-concrete Deck Bridge

Julio César Pigozzo, Felipe Nascimento Arroyo, André Luis Christoforo, Diego Henrique de Almeida, Carlito Calil Junior, Francisco Antonio Rocco Lahr

Current Journal of Applied Science and Technology, Page 1-10
DOI: 10.9734/CJAST/2018/42784

In Brazil is growing demand of short and medium span bridges not only in the new agriculture borders but also in the secondary roads in advanced regions. Traditional timber bridge not always meet the requirements of quality, they demand continuing maintenance and adequacy to actual heavy traffic. Mixed wood-concrete deck bridge arises as a viable alternative, because of its low construction cost, low maintenance and its high strength and stiffness. This paper presents the studies, design, execution and results from static load tests on wood-concrete deck bridge build with Corymbia citriodora wood specie logs, treated with CCA against xylophages organisms, reinforced medium strength concrete and steel bar connection bonde-in wood with epoxy resin, as shear connectors, were all used in construction system. Loaded tests were performed six months after the release of traffic. Results of the load tests indicate that the bridge performance is satisfactory.

Open Access Original Research Article

Curvelet Transform-Local Binary Pattern Feature Extraction Technique for Mass Detection and Classification in Digital Mammogram

Adeyemo Temitope Tosin, Adepoju Temilola Morufat, Oladele Matthias Omotayo, Wahab Wajeed Bolanle, Omidiora Elijah Olusayo, Olabiyisi Stephen Olatunde

Current Journal of Applied Science and Technology, Page 1-15
DOI: 10.9734/CJAST/2018/42579

Aim: To develop a Curvelet Transform (CT)-Local Binary Pattern (LBP) feature extraction technique for mass detection and classification in digital mammograms.

Study Design: A feature extraction technique.

Place and Duration of Study: Sample: Department of Computer Science and Engineering LAUTECH, Ogbomoso, Nigeria 2016.

Methodology: Three hundred (300) mammograms were acquired from the public available Mammographic Image Analysis Society (MIAS). One hundred and eighty images were used for training while the remaining 120 images out were used for testing purposes. The images were used pre-processed and segmented into Region of Interests (ROIs) using Histogram Normalization and Active Contour algorithms, respectively. CT algorithm was used to extract shape features from the ROIs while texture features were extracted using the LBP algorithm. K-Nearest Neighbor (KNN) algorithm was employed to classify the extracted features into normal and abnormal mammograms. The abnormal mammograms were further classified into benign (non-cancerous) and Malignant (cancerous) masses using KNN algorithm as well. The technique was implemented using Matrix Laboratory 8.2.0 (R2013b). The performance of the developed technique in classifying mammograms into normal/abnormal was investigated by comparing it with the existing CT-based and LBP-based techniques using sensitivity, specificity, and accuracy.

Results: The results of the evaluation showed that the sensitivity, specificity and overall performance for CT-based and LBP-based technique techniques are 72.0, 73.7 and 75.83%; 84.0%, 83.2% and 80.83% while sensitivity, specificity and overall performance of the developed CT-LBP technique are 96.0%, 93.7 and 94.17% respectively. The developed system improved detection of abnormality and the classification rate of mammogram in term of sensitivity, specificity and overall performance, which could be adopted in clinical practices for better detection and classification of breast cancer.