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The purpose of this study is to explore the vital factors that influence teacher's intention to use technology in higher education. PLS-SEM has been used to analyze the data collected from 201 business university teachers. The study strives to examine the impact of eight variables i.e. Performance expectancy, Effort Expectancy, Social influence, facilitating conditions, individual self-efficacy, human assisted self-efficacy, Computer Anxiety and attitude on teacher's intention to use technology using the technology acceptance model of Unified Theory of Acceptance and Usage of Technology. The empirical findings revealed that the social influence, facilitating conditions, individual self-efficacy and attitude have the significant and positive impact, while computer anxiety has a negative significant impact on the intention to use technology. However, performance expectancy, effort expectancy and human assisted self-efficacy have an insignificant impact on teacher's intention to use technology. The present study provides an inclusive view to understanding the acceptance of technology by teachers. The strength of present research lies in studying the extended version of UTAUT which will guide the university administrators and policy makers in understating those factors that influence the technology acceptance among teachers.

Effective software project management plays an important role during requirements collection and implementation for any software system. In Global Software Development (GSD), its significance increase more as stakeholders are far away across the globe. In GSD, challenges such as language differences and time zone differences cause significant barrier during requirements collection and thus need of effective project management increase more and more to handle challenges of GSD. This study address possible solutions and practices for effective global software project management. Through Systematic Literature Review (SLR), 25 practices are identified. These practices will help software vendors to better manage software projects in GSD.

In an Underwater Wireless Sensor Network (UWSN), extreme energy loss is carried out by the early expiration of sensor nodes and causes a reduction in efficiency in the submerged acoustic sensor system. Systems based on clustering strategies, instead of each node sending information by itself, utilize cluster heads to collect information inside the clusters for forwarding collective information to sink. This can effectively minimize the total energy loss during transmission. The environment of UWSN is 3D architecture-based and follows a complex hierarchical clustering strategy involving its most effecting unique parameters such as propagation delay and limited transmission bandwidth. Round base clustering strategy works in rounds, where each round comprises three fundamental stages: cluster head selection, grouping or node association, and data aggregation followed by forwarding data to the sink. In UWSN, the energy consumed during the formation of clusters has been considered casually or completely evaded in the previous works. In this paper, the cluster head setup period has been considered the main contributor to extra energy utilizer. A numerical channel model is proposed to compute extra energy. It is performed by using a UWSN broad model. The results have shown that extra maximum energy consumption is approximately 12.9 percent of the system total energy consumed in information transmissions.

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