A Viewpoint of Tanzania E-Commerce and Implementation Barriers

The growing rate of ICT utilization particularly the Internet and mobile phones has influenced at an exponential rate online interaction and communication among the generality of the populace. However, with the enormity of businesses on the Internet, Tanzania is yet to harness the opportunities for optimal financial gains. This study is exploratory in nature as it attempts to unveil the prospects of e-commerce implementation, participation, motivation and opportunity to the developing countries like Tanzania where by the domestic market is very big to ensure the growth of agricultural sector. The paper proposes to investigate the ability of consumers to purchase online, the available motivation to do so, and the opportunities for Internet access. We argue the Government and central bank to encourage innovative new technological developments by pre-regulating electronic money to familiarize itself with electronic money schemes generally. Findings revealed that Tanzanians have the ability to participate in e-commerce, but there is need for improved national image to bring in the element of trust and discipline within, and before the international communities. Currently, consumers source for information online but make purchases the traditional way

An Improved Solar Low Energy Adaptive Clustering Hierarchy (IS-LEACH) Technique

in the recent years, the Wireless Sensor Networks (WSNs) has grown dramatically in many fields such as military applications, environmental applications, and health assistant applications. However, there are numerous problems associated with applying the WSNs. Such problems are related to power consumption, performance, reliability, installation cost, and hardware cost. Thus, many algorithms in the WSNs context have been considered to propose an improved solar Low Energy Adaptive Clustering Hierarchy (LEACH) technique for maximizing the lifetime, increasing the performance, increasing the reliability, and decreasing the costs. This proposed technique improves the selecting Cluster Heads (CHs) process and powering it with a renewable energy (solar cell). The OMNeT++ tool has been employed to simulate such technique. After many scenarios have taken place with different data sets, this study finds that the lifetime of WSNs has been maximized, the performance has been improved, the reliability has also been improved, and finally the cost has been decreased

A Viewpoint of Tanzania E-Commerce and Implementation Barriers

The growing rate of ICT utilization particularly the Internet and mobile phones has influenced at an exponential rate online interaction and communication among the generality of the populace. However, with the enormity of businesses on the Internet, Tanzania is yet to harness the opportunities for optimal financial gains. This study is exploratory in nature as it attempts to unveil the prospects of ecommerce implementation, participation, motivation and opportunity to the developing countries like Tanzania where by the domestic market is very big to ensure the growth of agricultural sector. The paper proposes to investigate the ability of consumers to purchase online, the available motivation to do so, and the opportunities for Internet access. We argue the Government and central bank to encourage innovative new technological developments by pre-regulating electronic money to familiarize itself with electronic money schemes generally. Findings revealed that Tanzanians have the ability to participate in e-commerce, but there is need for improved national image to bring in the element of trust and discipline within, and before the international communities. Currently, consumers source for information online but make purchases the traditional way

Prioritized Transaction Management for Mobile Computing Systems

Abstract I

Sociodemographic factors in Arab children with Autism Spectrum Disorders

Introduction: There is a critical gap in Autistic Spectrum Disorders (ASD) research with respect to manifestations of the condition in developing countries This study examined the influence of sociodemographic variables on the severity of autistic symptoms and behavioral profile in Arab children. Methods: The total study sample comprised of 60 Arab children (38 boys and 22 girls) from three Arab countries (22 Jordanians, 19 Saudis and 19 Egyptians). The diagnosis of Autism Spectrum Disorders (ASD) was based on DSM-IV criteria supplemented by direct observation according to the Indian Scale for Assessment of Autism (ISAA) and assessment of Intelligent Quotient (IQ). Finally, parents rated their child on the Achenbach Child Behavior Checklist (CBCL). Results: It was found that the housewives and Saudi parents described more autistic symptoms and externalizing behavior problems. A significant negative correlation was found between IQ and each of ISAA, CBCL Internalizing and Externalizing problems scores. Conclusion: The study concluded that the clinical presentation of ASD may be shaped by cultural factors that are likely to help to formulate specific diagnosis and intervention techniques in Arab children with ASD. Pan African Medical Journal 2012; 13:6

Deep face recognition using imperfect facial data

YesToday, computer based face recognition is a mature and reliable mechanism which is being practically utilised for many access control scenarios. As such, face recognition or authentication is predominantly performed using ‘perfect’ data of full frontal facial images. Though that may be the case, in reality, there are numerous situations where full frontal faces may not be available — the imperfect face images that often come from CCTV cameras do demonstrate the case in point. Hence, the problem of computer based face recognition using partial facial data as probes is still largely an unexplored area of research. Given that humans and computers perform face recognition and authentication inherently differently, it must be interesting as well as intriguing to understand how a computer favours various parts of the face when presented to the challenges of face recognition. In this work, we explore the question that surrounds the idea of face recognition using partial facial data. We explore it by applying novel experiments to test the performance of machine learning using partial faces and other manipulations on face images such as rotation and zooming, which we use as training and recognition cues. In particular, we study the rate of recognition subject to the various parts of the face such as the eyes, mouth, nose and the cheek. We also study the effect of face recognition subject to facial rotation as well as the effect of recognition subject to zooming out of the facial images. Our experiments are based on using the state of the art convolutional neural network based architecture along with the pre-trained VGG-Face model through which we extract features for machine learning. We then use two classifiers namely the cosine similarity and the linear support vector machines to test the recognition rates. We ran our experiments on two publicly available datasets namely, the controlled Brazilian FEI and the uncontrolled LFW dataset. Our results show that individual parts of the face such as the eyes, nose and the cheeks have low recognition rates though the rate of recognition quickly goes up when individual parts of the face in combined form are presented as probes

Modelling Access Control with Dynamic Role Binding

Non