Archives-July 2019

Ease of use is one of the main criteria that customers consider when making a purchase decision. In order to provide a pleasant experience to the customers, offering products or services consisting of advanced features and functions is no longer enough, due to the existing competition in the global market. In reality the ease of use of any product is influenced by the conditions of the product and the familiarity of the user. This study examines the influence of the familiarity and the product conditions on the ease of use of a product and the results would be a valuable guidance to the manufacturers in order to identify how the ease of use level of a product deviates from the standard level, when the usage hours of the product would increase.

The automatic identification of the modulation type of a signal at the receiver is a major task of an intelligent receiver, such as software defined radio (SDR), which is used in different communication systems. With no knowledge of the transmitted data, recognition of the modulation type is a difficult task. A communication system, in which receiver is designed based on Machine learning is trained to detect the message using statistical parameters. In this work, machine learning algorithm is developed for identifying 6 different modulated signal types at the receiving end. MATLAB tool is used to generate different modulated signals. Identification of modulation type is done by analyzing different statistical features such as normalized PSD, kurtosis and sum-fft which are calculated using the sampled version of received signal. The algorithm is tested for different frequency and amplitude signals at the receiving end and results are tested for correctness.

The present work has been done to emphasize the place of palm oil zomi in people diet at south of Benin. It has consisted in evaluating consumers’ perception and to record utilization of this oil in households of South Benin. On the basis of an inquiry questionnaire, 200 consumers (consumer’s producers (CP) and consumers non producers (CNP)) have been interviewed in six departments of South-Benin. Results have revealed flavored palm oil zomi was characterized by a deep red color (80%), a pronounced odor (10%), a good fluidity (67.14%) and an unsalted taste (93.55%). According to 99.14% of consumers, vegetable with tomatoes sauces were in their majority cooked with zomi oil. Beans according to 95.71% of consumers and boiled yam according to 89.15% of consumers represented foods largely consumed with zomi oil. Zomi oil supplying was frequently done in markets according to 50.7% of consumers. Totally, flavored palm oil zomi occupied an important place in Benin people gastronomy.

Adverse birth outcomes, comprising low birth weight, maternal mortality, infant mortality, premature births, and stillbirth continue to pose a serious challenge in Kenya. Although a number of factors influencing adverse birth outcomes have been documented, not much is known on the factors contributing to adverse birth outcomes in Kibra. The main objective of this study was to assess the factors influencing adverse birth outcomes in Kibra. The specific objectives were: to identify the socio-demographic; obstetric emergencies that contribute to adverse birth outcomes; and to determine the health facility factors that contribute to women’s vulnerability to adverse birth outcomes. The study used a cross sectional research design and targeted women of reproductive age (15-49). Purposive sampling was used to select the study site and simple random sampling was used to select the 384 study participants in households. Data from the households was collected using questionnaires. Key informant interviews on health facility in-charges was used to provide additional information. Data was presented using tables, graphs and cross tabulations. Chi-Square and logistic regression was used to assess the statistical association between variables. Findings showed that casual laborer’s had significant association with adverse birth outcomes (still births) [OR= .159, 95% CI (.031, .816), p<0.05] (Pre-term births) [OR= 2.789, 95% CI (1.37, 5.67), p<0.05. Self-employment had significant association with adverse birth outcomes (still births) [OR=.169, 95% CI (.031, .929), p<0.05], (Pre-term births) [OR= 2.163, 95% CI (1.11, 4.22), p<0.05]. Respondents without education were associated with high adverse birth outcomes [pre-term births] [OR=.235, 95% CI (.069, .831), p= 0.021]. The respondents who had miscarriage in previous pregnancies were more likely to experience adverse birth outcomes [Preterm births] [OR=3.89, 95% CI (2.06, 7.39) p=0.000] still births [OR=2.09, 95% CI (1.44, 5.84) p=0.000], low birth weight [OR=3.24, 95% CI (1.74, 6.05) p=0.000] and neonatal death [OR=3.39, 95% CI (1.63, 7.03) p=0.000]. Respondents who attended the public health facility had higher risk of experiencing adverse birth outcomes [Still births] [OR= 3.500, 95%CI (1.24, 9.86), p-value =0.018]. Findings from the study will be used to inform local interventions to reduce adverse birth outcomes.

In many modern computer applications such as Market Analysis, Critical Care, Speech Recognition, Physical Plant Monitoring, Sleep Stage Classification, Biological Population Tracking, data is captured over the course of time, constituting a Time-Series. Time-Series data often contain temporal information dependencies that cause two otherwise identical points of time to belong to different classes or predict different behavior. This inherent characteristic increases the difficulty of processing such data. Deep Machine Learning (DML) techniques possess the inherent ability for analyzing and making predictions about such data. By its nature, DML requires extensive provision of resources key amongst which is the model computation time. Several optimization algorithms have been invented in the recent past and compare differently in terms of their resource needs. The most popular class of optimization algorithms is based on the classical stochastic gradient descent (SGD) algorithm due to its ability to converge within reasonable time bounds. This paper is part of a larger project investigating optimization procedures for deep learning tasks based on the SGD. Specifically, we report on the comparative performance capabilities of the most popular SGD based algorithms for task of Time Series prediction namely. From our analysis of the six of these algorithms, we noted that ADAMAX is most appropriate for online learning while RMSPROP is the least affected by over-fitting for long training cycles.

Present paper is an important study for constructing magic squares of odd orders. This magic squares have been formed using the properties of Latin squares. Here, reduced Latin square is used and it is formulated by using the cyclic shifting method with the entries (????, ????,...., ????) (????(????- ????),.... ???? power ???? ).This work has been generalized for magic square of order ???? power ????, when ???? is odd and ???? by using the mathematical formula ?????????(???????????? ???? power ????): ????= ????, ????,..., ???? power ????. The method is tested for ????, ???? power ???? and ????.

The main objective of the study was to compare the Area Wise Socio-Economic Status and Emotional Fitness of Senior Citizens of Himachal Pradesh and Uttar Pradesh State of India. The present researcher used simple random sampling method for the selection of 2000 subjects (Senior Citizens) for the present study. 100 Male and 100 Female Senior Citizens were taken together from each five district taken for the present study of Himachal Pradesh and Uttar Pradesh State of India. Kuppuswamy’s Socio-Economic Standardized scale and Gross & John Emotion Regulation Questionnaire (ERQ) were used for data collection. The data collected was statistically analyzed by using Percentage and Chi Square was specially used to found the significance difference in between different socio-economic status and Emotional Fitness of Senior Citizens Himachal Pradesh and Uttar Pradesh State of India. Further Percentage, Average Percentage, Mean, Combined Mean, Average Mean and Chi Square were calculated. On the basis of above findings and conclusions it can be briefly concluded that senior citizens of Himachal Pradesh and Uttar Pradesh State of India differed significantly in respect to their socio-economic Status and Emotional Level.

According to the United Nations, there were approximately 4.854 million international students registered around the world in 2016. While the mentioned figure was equal to 3.961 million in 2011 [1]. Educational migration is an increasing trend, which brings various benefits to the host countries. Georgia began attracting foreign youth representatives as soon as it started experiencing optimistic economic trends. The growing number of foreign students has had a noticeable, positive impact on the economy and thus, has become a subject of discussion in the society. The present article is dedicated to discussing general characteristics of Georgian immigration profile (such as statistics concerning immigrants) and observing details of students' migration to the mentioned state. Additionally, the work examines diverse recommendations that could increase the number of prospective international students in the country. Analyzing some aspects of the youth immigration to Georgia is a safe mean of acknowledging the realities of Georgian educational sector and finding prospects of further development. Due to the importance of the theme, the article discusses some of the relevant recent researches and statistical data that have been published by various international and local, Georgian institutions.

In this work, a new algorithm is proposed and that can be used to construct strongly regular graphs from skew-Hadamard matrices. The proposed method is based on matrix manipulations and is similar to the construction given by Jayathilaka A.A.C.A. et al., where they considered Hadamard matrices. Two strongly regular graphs have been constructed by using skew-Hadamard matrices of order 2 and 4 and are drawn using a Java programme. Considering skew-Hadamard matrices of higher order, larger strongly regular graphs can be obtained and those can be used as networks with several nodes.

Terrestrial heating is so real in Mwea that it has significantly reduced water levels in the canal; a catastrophe complexed with uphazard and unscheduling of irrigation in the scheme to the detriment of crops at its termini. In that view therefore, an experiment was set out at KALRO-Mwea to investigate on the effect of irrigation scheduling on yield components and grain yield of two Nerica rice varieties. The experiment was laid out in a Randomized Complete Block Design in split-plot arrangement and replicated thrice. Four irrigation schedules (Daily (control), Every 3 days, Every 5 days and Weekly) formed main plots and two rice varieties (Nerica 4 and Nerica 11) formed the sub plots. Results indicated positive influence though not significant on filled grain number, shoot biomass, root biomass, unfilled grain number, productive tillers, panicle number, 1.5 m² plot grain weight, moisture content, and on grain yield in both seasons, while significant effect was exerted on 1000-grain weight, where highest and least 1000-grain weight of 55.92 g and 41.0 g in Nerica 4 on every 3 days and weekly schedules in season 1 were recorded respectively, while significant effect was elicited on unproductive tillers in season 2 where highest of 1.783 unproductive tillers in Nerica 11 on every 5 days’ schedule was recorded, while least of 0.75 unproductive tillers in Nerica 4 on weekly schedule was also recorded. Positive though insignificant effect was also observed in unproductive tillers in season 1, while the same was observed in 1000-grain weight in season 2. Grain yield (ton/ha) did not present any significant effect due to irrigation schedule treatments in both seasons, although variation in means of grain yield was observed, where highest grain yield of 1.003 tons / hectare was produced in Nerica 4 on weekly irrigation schedule in season 2, while least grain yield of 0.863 tons / hectare was produced in Nerica 11 on every 3 days’ irrigation schedule in both seasons. Nerica 4 outperformed Nerica 11 in productive tillers, 1.5 m² plot grain weight, 1000-grain –weight and on grain yield, while Nerica 11 outperformed it in unproductive tillers, filled grain yield, unfilled grain yield, shoot biomass, root biomass, panicle number, and on moisture content in yield. Nerica 4 on weekly schedule, while Nerica 11 on control, and on every 5 days’, and both on every 3 days’ schedule are recommended to farmers for adoption.