56 research outputs found
Seroprevalence of contagious caprine pleuropneumonia in Kefta Humera, Alamata (Tigray) and Aba-‘ala (Afar), Northern Ethiopia
No full textA cross sectional study was conducted to determine the sero-prevalence of contagious caprine pleuroneumonia in three districts of Tigray and Afar regions of Ethiopia namely; Kefta Humera, Alamata and Aba-‘alla. Proportions and chi-square test statistics were used to analyze the data. From a total of 863 goats and 137 sheep tested, 282 (32.68%) and 25 (18.25%) were positive for antibodies of Mycoplasma capricolum subsp. capripneumoniae respectively using complement fixation test (CFT). The seroprevalence of CCPP in goats among the three districts was statistically significant (x2 = 76.00, p < 0.001). In this study there was no statistical significant variation in the seroprevalence of CCPP in both sexes (x2 = 3.619, p = 0.0571) and age (x2 = 0.990, p = 0.095) groups. The finding of high seroprevalence of CCPP in sheep (18.25%) could indicate that sheep are potential carriers of Mccp.Ethiopian Science and Technology Agency (ESTA
Skull stripping using traditional and soft-computing approaches for magnetic resonance images : a semi-systematic meta-analysis
No full textMRI scanner captures the skull along with the brain and the skull needs to be removed for enhanced reliability and validity of medical diagnostic practices. Skull Stripping from Brain MR Images is significantly a core area in medical applications. It is a complicated task to segment an image for skull stripping manually. It is not only time consuming but expensive as well. An automated skull stripping method with good efficiency and effectiveness is required. Currently, a number of skull stripping methods are used in practice. In this review paper, many soft-computing segmentation techniques have been discussed. The purpose of this research study is to review the existing literature to compare the existing traditional and modern methods used for skull stripping from Brain MR images along with their merits and demerits. The semi-systematic review of existing literature has been carried out using the meta-synthesis approach. Broadly, analyses are bifurcated into traditional and modern, i.e. soft-computing methods proposed, experimented with, or applied in practice for effective skull stripping. Popular databases with desired data of Brain MR Images have also been identified, categorized and discussed. Moreover, CPU and GPU based computer systems and their specifications used by different researchers for skull stripping have also been discussed. In the end, the research gap has been identified along with the proposed lead for future research work
A Quantum based Evolutionary Algorithm for Stock Index and Bitcoin Price Forecasting
No full textQuantum computing has emerged as a new dimension with various applications in different fields like robotic, cryptography, uncertainty modeling etc. On the other hand, nature inspired techniques are playing vital role in solving complex problems through evolutionary approach. While evolutionary approaches are good to solve stochastic problems in unbounded search space, predicting uncertain and ambiguous problems in real life is of immense importance. With improved forecasting accuracy many unforeseen events can be managed well. In this paper a novel algorithm for Fuzzy Time Series (FTS) prediction by using Quantum concepts is proposed in this paper. Quantum Evolutionary Algorithm (QEA) is used along with fuzzy logic for prediction of time series data. QEA is applied on interval lengths for finding out optimized lengths of intervals producing best forecasting accuracy. The algorithm is applied for forecasting Taiwan Futures Exchange (TIAFEX) index as well as for Bitcoin crypto currency time series data as a new approach. Model results were compared with many preceding algorithms
An Insight for Cursive Context-Specific Printed Script Recognition
No full textThe greatest challenge of machine learning problems is to select suitable techniques and resources such as tools and datasets. Despite the existence of millions of speakers around the globe and the rich literary history of more than a thousand years, it is expensive to find the computational linguistic work related to Punjabi Shahmukhi script, a member of the Perso-Arabic context-specific script low-resource language family. This paper presents a deep insight into the related work with summary statistics, advocating the popularity and success of artificial neural networks and related techniques. The paper includes support from recent trends from the authentic sources based on the top-level researchers' feedback including the machine learning frameworks. A comprehensive comparison of the most popular deep learning techniques convolutional neural network and the recursive neural network has been presented for the cursive context-specific scripts of Perso-Arabic nature. The overview of the available benchmark datasets for machine learning problems, especially for the Perso-Arabic group, is added. This paper incorporates essential knowledge contents for the researchers in machine learning and natural language processing disciplines on the selection of algorithms, architectures, and resources
Impact of Islamic Microfinance on Borrower’s Income in Pakistan- A Case Study of Akhuwat
No full textMicrofinance is a process of providing financial access in the form of micro-credits, and other services such as micro-insurance, savings, checking accounts and payment systems to the poor who do not have access to conventional banking. Lack of collateral and capital assets put limitations on the marginalized community to access the funds through the conventional banking system which leads to their financial exclusion. It is grasped that the objective of financial inclusion can be achieved at its full potential through redistributive instruments (Zakah, Awqaf, Qard al-hassan) of the Islamic microfinance industry. Pakistan Microfinance Review (2017) revealed that Akhuwat (A leading Islamic microfinance organization based on voluntarism and philanthropy) had maintained its outreach top spot in terms of Active Borrowers (820,000) during the year 2017. This study is conducted to analyze microfinance services provided by Akhuwat and its effects on borrowers’ income and consumption. The study adopted the qualitative research designed by applying questionnaires and interviewing techniques to collect data. The study finds that there was a reasonable increase in the income and consumption of the borrowers. Results indicate an average increase of 18 % in rural borrowers’ income and an average increase of 23% in urban borrowers’ income. The study recommends that vocational training should be provided to people in rural areas to enable them to engage in diverse business activities instead of solely relying on agriculture-related business
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Collecting Stories of Identity and Culture with Young people: The Synallactic Collective Image Technique
No full textThe leader of an arts-based workshop, Evangelia, has asked the young people involved to consider a time they translated or interpreted and to think about how they were feeling. One young man named Tariq looks unsure and mumbles, ‘I don’t got feelings’ and then asks the question more loudly: ‘do you have feelings when you translate, do you have feelings?’. A couple of his friends smile but no one replies. Throughout the workshop he casts sideways looks at the others’ drawings. In the end, with a black pen he draws an oval face, with two round circles for eyes that are blank in the middle. The face has a little bit of hair, a line for a nose and a round circle for the mouth. The only bit of colour is a red tongue in the mouth. It is a stark face, for its lack of detail. For his story Tariq writes: ‘don’t have any story about translating, mean I do but don’t really remember them’, and ‘don’t have any feelings while I am translating’, and on the back of his drawing he writes ‘#Nofeelings’ and, a little further down the page, ‘Concern’. This excerpt is drawn from an arts-based workshop which was part of an Arts and Humanities Research Council-funded project, based at the Thomas Coram Research Unit (TCRU) between 2014–17. The project focused on child language brokers; children and young people who translate and interpret for family members, peers and the local community. In this chapter, we focus on one of our arts-based workshops that employed the Synallactic Collective Image Technique (SCIT), a technique used for sharing personal and collective stories, memories and experiences. In this instance, we brought together a group of young language brokers (aged 13–16) who took part in a SCIT workshop. Through sharing individual drawings and narratives of personal experiences of language brokering, interpersonal transactions within the group unfold
A Comparative Study on User Interfaces of Interactive Genetic Algorithm
No full textAbstractThis paper provides a review on current developments in the Interactive Genetic Algorithm (IGA). The discussion includes graphical aspects of different applications of IGA. We have reviewed topics like visualization techniques, usage of different machine learning algorithms and mathematical methods in order to get the best solution from IGA. Examples of IGA in this review include the fashion design applications, tree modeling and 3D objects reconstruction. This paper concludes with the current problems and future directions of IGA
An insight into the evolution of rotation operator to quaternion’s. Computer graphics perspective
No full textRotations are an integral part of various computational techniques and mechanics. The objective in this paper is twofold: first to have a classical insight into the history of quaternions, a problem that Hamilton faced for over a decade and secondly to look at into its applications from computer graphics perspective. Thorough revision of quaternion algebra and its use case as a rotation operator has been presented. A quaternion simulation algorithm has been written and practiced to generate simulation results. Results show that though quaternions supersede Euler angles technically but are tricky to use and control for e.g. when same quaternion is applied on a different vector axis, the particle is not able to reach its initial position and an incomplete rotation effect has been recorded and observed
Topic Modeling of Quranic Verses using Latent Dirichlet Allocation with English Language: Topic Modeling using LDA
No full textThis study aims to assess the effectiveness of topic modeling in the English translation of the Holy Quran. Topic modeling is a popular text mining technique for uncovering latent semantic patterns in the collection of textual documents and helps to annotate the documents based on these topics. This study identifies the most significant topics in each document as well as grasping an understanding of the topic distribution throughout the document sets. Different steps are performed to acquire the dominant topics in each document and identify the distribution of topics across documents. In this context, the present research work chose to employ Latent Dirichlet Allocation as an unsupervised approach for topic modeling since there is no requirement for a training phase as hidden topics can be discovered throughout the topic modeling process. For this, the word cloud is generated to understand and interpret the results after pre-processing. A dictionary and corpus are created to extract the features from the dataset using the Bag of Words approach. The results are evaluated by calculating the perplexity and coherence score, where high coherence indicates the goodness of well-structured topic models and low perplexity score indicates the correctness of prediction made by the topic models. Lastly, the visualization step is performed
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