National issues facing collaborative mobile money service provision

Recently, the developing countries are considering the development of mobile money ecosystems that supports more inclusive financial systems to overcome the high financial exclusion of their population.Such ecosystems can be enabled by facilitating the collaboration between diverse stakeholders from different sectors: financial, telecommunication, regulatory bodies and IT service providers.This development of mobile money ecosystem emphasized on considering existing issues of main stakeholders’ and their conflicting interests.The aim of this paper is to understand the existing issues that government needs to resolve when participating in collaborative mobile money ecosystem.The Sudanese national mobile money project was used as case study in this research. Qualitative interpretive interviews were conducted to collect data from different stakeholders in different sectors in Sudan. The data was analyzed using qualitative data analysis approach.The results of the analysis focus on representing the multiple perspectives of stakeholders on each identified government’s issue.Findings contribute toward a better understanding of mobile money ecosystem in Sudan from government’s perspective.This understanding can facilitate building successful value propositions between mobile money stakeholders which can result in better financial services

The relationship between phenolics and flavonoids production with total non structural carbohydrate and photosynthetic rate in labisia pumila benth. under high CO2 and nitrogen fertilization.

A factorial split plot 4 × 3 experiment was designed to examine and characterize the relationship among production of secondary metabolites (total phenolics, TP; total flavonoids, TF), carbohydrate content and photosynthesis of three varieties of the Malaysian medicinal herb Labisia pumila Benth. namely the varieties alata, pumila and lanceolata under CO2 enrichment (1,200 μmol mol-1) combined with four levels of nitrogen fertilization (0, 90, 180 and 270 kg N ha-1). No varietal differences were observed, however, as the levels of nitrogen increased from 0 to 270 kg N ha-1, the production of TP and TF decreased in the order leaves>roots>stems. The production of TP and TF was related to increased total non structural carbohydrate (TNC), where the increase in starch content was larger than that in sugar concentration. Nevertheless, the regression analysis exhibited a higher influence of soluble sugar concentration (r² = 0.88) than starch on TP and TF biosynthesis. Photosynthesis, on the other hand, displayed a significant negative relationship with TP and TF production (r² = -0.87). A decrease in photosynthetic rate with increasing secondary metabolites might be due to an increase in the shikimic acid pathway that results in enhanced production of TP and TF. Chlorophyll content exhibited very significant negative relationships with total soluble sugar, starch and total non structural carbohydrate

National issues facing collaborative mobile money service provision

Recently, the developing countries are considering the development of mobile money ecosystems that supports more inclusive financial systems to overcome the high financial exclusion of their population.Such ecosystems can be enabled by facilitating the collaboration between diverse stakeholders from different sectors: financial, telecommunication, regulatory bodies and IT service providers.This development of mobile money ecosystem emphasized on considering existing issues of main stakeholders’ and their conflicting interests.The aim of this paper is to understand the existing issues that government needs to resolve when participating in collaborative mobile money ecosystem.The Sudanese national mobile money project was used as case study in this research. Qualitative interpretive interviews were conducted to collect data from different stakeholders in different sectors in Sudan. The data was analyzed using qualitative data analysis approach.The results of the analysis focus on representing the multiple perspectives of stakeholders on each identified government’s issue.Findings contribute toward a better understanding of mobile money ecosystem in Sudan from government’s perspective.This understanding can facilitate building successful value propositions between mobile money stakeholders which can result in better financial services

An experimental study of welded bar sleeve wall panel connection under tensile, shear, and flexural loads

This paper presents an experimental study of a new grouted splice connection for wall panels, called Welded Bar Sleeve (WBS). The connections were made from steel pipes and tested with incremental tensile, shear and flexural loads until failure. The aim is to determine the behaviour of the connection under the three load cases. For this, the connections are evaluated in terms of the load–displacement responses, ultimate capacities, ductility responses and some feasibility assessment criteria. WBS was found to provide sufficient strength at the bar embedded length of 8, 8 and 11 times the bar diameter under tensile, shear and flexural loads, respectively. It is effective under tension, but could only service up to 1/3 of its ultimate shear capacity. Flexural load is the most critical load case for the connection. For this, further enhancements are required when subjected to shear and flexural loads

Assessment of variability pattern of flesh color in ‘Harumanis’ mango (Mangifera indica L.) from diverse Perlis geographical origin

Harumanis’ (Mangifera indica L) is one of the mango cultivars which has high market value because of the excellent quality of the fruit which has attractive color, good aroma, delicious taste and high nutritive values. In this study, fifty accessions from five different collection sites which belonging to North (Paya Kelubi and Chelong Balik Bukit, Padang Besar), West (Santan, Kangar), East (Alor Ara Timur, Arau) and South (Simpang Empat, Kangar) region of Perlis were analyzed according to flesh color traits based on their region of origin. The analysis of variance using Kruskal-Wallis test resulted in significant differences among the geographical region for traits of fruit flesh color such as L*, a*, chroma and hue at (P<0.05). The correlation result shows that the intensity pattern of the orange color of the fruit samples mesocarp was associated by an increase in the values of a*, b* and C*, and a decrease in the values of L* and h. By performing Cluster analysis using Ward’s method and Euclidian distance, five distinct clusters were successfully identified. The finding shows a high distribution of ‘Harumanis’ accessions from different locations in each distinct group. This study also reveals the relationship of variability in fruit traits with their places of origin. However, these differences cannot be explained in firm via morphological characterization only. Other methods such as molecular characterization are strongly recommended

CTJ: Input-Output Based Relation Combinatorial Testing Strategy Using Jaya Algorithm

&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ويكاد يكون من المستحيل اختبار كل مجموعة من المدخلات نظرًا لأن تنفيذ حالات الاختبار يتطلب وقتا طويلا للغاية. الأختبار الاندماجي هو السبيل لتخطي عقبات الاختبار الشامل من خلال أختبار كل قيم المدخلات لكل المعاملات المركبة المتعددة طرق الترتيب. &nbsp; يمكن تقسيم الاختبار التجميعي إلى ثلاثة أنواع هي تفاعل القوة الموحد ، والتفاعل المتغير والقوة ، والعلاقة القائمة على المدخلات والمخرجات . ان الطريقة الاخيرة الانفة الذكر تختزل الفحص الاندماجي الى مجموعة ضمن اختيار الشخص الفاحص. معظم الابحاث في الاختبار الاندماجي طبقت في تفاعل القوة الموحدة وقوة التفاعل المتغيرة ، ومع ذلك ، هناك اهتمام قليل جدا بالعلاقة بين المدخلات والمخرجات. لذا تم اقتراح خوارزمية جايا في هذا البحث&nbsp; كخوارزمية مثلي لانشاء جدول الفحص الاندماجي باستراتيجية تعتمد على العلاقة بين المدخلات والمخرجات. نتيجة تطبيق خوارزمية جايا في الاختبار الاندماجي القائم على المدخلات والمخرجات مقبولة لأنها تنتج العدد الأمثل تقريبًا لحالات الاختبار في نطاق زمني مقبول.Software testing is a vital part of the software development life cycle. In many cases, the system under test has more than one input making the testing efforts for every exhaustive combination impossible (i.e. the time of execution of the test case can be outrageously long). Combinatorial testing offers an alternative to exhaustive testing via considering the interaction of input values for every t-way combination between parameters. Combinatorial testing can be divided into three types which are uniform strength interaction, variable strength interaction and input-output based relation (IOR). IOR combinatorial testing only tests for the important combinations selected by the tester. Most of the researches in combinatorial testing applied the uniform and the variable interaction strength, however, there is still a lack of work addressing IOR. In this paper, a Jaya algorithm is proposed as an optimization algorithm engine to construct a test list based on IOR in the proposed combinatorial test list generator strategy into a tool called CTJ. The result of applying the Jaya algorithm in input-output based combinatorial testing is acceptable since it produces a nearly optimum number of test cases in a satisfactory time range

Recognition of Radar-Based Deaf Sign Language Using Convolution Neural Network

The difficulties in the communication between the deaf and normal people through sign language can be overcome by implementing deep learning in the gestures signal recognition. The use of the Convolution Neural Network (CNN) in distinguishing radar-based gesture signals of deaf sign language has not been investigated. This paper describes the recognition of gestures of deaf sign language using radar and CNN. Six gestures of deaf sign language were acquired from normal subjects using a radar system and processed. Short-time Fourier Transform was performed to extract the gestures features and the classification was performed using CNN. The performance of CNN was examined using two types of inputs; segmented and non-segmented spectrograms. The accuracy of recognising the gestures is higher (92.31%) using the non-segmented spectrograms compared to the segmented spectrogram. The radar-based deaf sign language could be recognised accurately using CNN without segmentation

Recognition of Radar-Based Deaf Sign Language Using Convolution Neural Network

The difficulties in the communication between the deaf and normal people through sign language can be overcome by implementing deep learning in the gestures signal recognition. The use of the Convolution Neural Network (CNN) in distinguishing radar-based gesture signals of deaf sign language has not been investigated. This paper describes the recognition of gestures of deaf sign language using radar and CNN. Six gestures of deaf sign language were acquired from normal subjects using a radar system and processed. Short-time Fourier Transform was performed to extract the gestures features and the classification was performed using CNN. The performance of CNN was examined using two types of inputs; segmented and non-segmented spectrograms. The accuracy of recognising the gestures is higher (92.31%) using the non-segmented spectrograms compared to the segmented spectrogram. The radar-based deaf sign language could be recognised accurately using CNN without segmentation