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Analysis of Home Energy Consumption by K-Mean Fahad Razaque, Nareena Soomro, Javed Ahmed Samo, Huma Dharejo and Shoaib Shaikh Abstract: The smart meter offered exceptional chances to well comprehend energy consumption manners in which quantity of data being generated. One request was the separation of energy load-profiles into clusters of related conduct. The Research measured the resemblance between groups them together and load-profiles into clusters by k-means clustering algorithm. The cluster met, also called “Gender (Male/Female), House (Rented/Owned) and customers status (Satisfied/Unsatisfied)” display methods of consuming energy. It provided value information aimed at utilities to generate specific electricity charges and healthier aim energy efficiency programs. The results show that 43% extremely dissatisfied of energy customer is achieved by using energy consumption. Keywords: Load-Profiles; K-means; Clusters; Data Science, Data Set. |
Comparing the Complexity of Two Network Architectures Olivier Z. Zheng, Maaruf Ali and Kashinath Basu Abstract: A Service Provider has different methods to provide a VPN service to its customers. But which method is the least complex to implement? In this paper, two architectures are described and analysed. Based on the analyses, two methods of complexity calculation are designed to evaluate the complexity of the architecture: the first method evaluates the resources consumed, the second evaluates the number of cases possible. Keywords: Computer Networks; Internet Topology; Network Complexity; Multi-protocol Label Switching (MPLS); Virtual Private Networks (VPN). |
An Investigation on Exhaustion of SAP ERP Users: Influence of Pace of Change and Technostress Prashanta Kumar Roy, Imran Mahmud, Nusrat Jahan and Farzana Sadia Abstract: Despite recent growing research interest on ERP research, the understanding on ERP induced exhaustion is still limited. This study examines how the pace of change of ERP functionalities and interface causes exhaustion in workplace. For this purpose, we conducted an investigation on 128 ERP users from two different organizations in Bangladesh. We extended theory of technostress by integrating pace of change of ERP system. Result suggests that pace of change on ERP system significantly affect work-overload, work-life conflict and role ambiguity on ERP users. Result also shows that work-overload and role ambiguity are strong predictors for ERP induced exhaustion. Keywords: Technostress; SAP; ERP; Pace of Change. |
Ideal Node Enquiry Search Algorithm (INESH) in MANETS Mohammad Riyaz Belgaum, Safeeullah Soomro, Zainab Alansari and Muhammad Alam Abstract: The different routing protocols in Mobile Ad hoc Networks take after various methodologies to send the data starting from one node then onto the next. The nodes in the system are non-static and they move arbitrarily and are inclined to interface disappointment which makes dependably to discover new routes to the destination. During the forwarding of packets to the destination, various intermediate nodes take part in routing, where such node should be an ideal node. An algorithm is proposed here to know the ideal node after studying the features of the reactive routing protocols. The malicious node can be eliminated from the networking function and the overhead on the protocol can be reduced. The node chooses the neighbor which can be found in less number of bounces and with less time delay and keeping up the QoS. Keywords: MANETS; DSR Protocol; AODV Protocol; Malicious. |
Cultural, Economic and Societal Impacts on Users’ Behaviour and Mobile Broadband Adoption Trends Mahdi H. Miraz, Maaruf Ali and Peter S. Excell Abstract: The diverse range of Internet enabled devices both mobile and fixed has not only impacted the global economy but the very fabric of human communications and lifestyles. The ease of access and lowered cost has enabled hitherto diametrically opposed people to interact and influence each other globally. The consequence of which is the dire need to address the way culture affects interaction with information systems across the world. The many facets of which encompasses human behaviour, socio-economic and cultural factors including lifestyles and the way of interaction with the information system. The study group involved participants from Bangladesh and the United Kingdom to ascertain the users’ behavioural patterns and mobile broadband technology diffusion trends. Keywords: Culture, Users’ Behaviour; Mobile Broadband; Technology Adoption Trend; Diffusion of IT Innovation. |
Big Data Analytics and Its Applications Mashooque A. Memon, Safeeullah Soomro, Awais K. Jumani and Muneer A. Kartio Abstract: The term, Big Data, has been authored to refer to the extensive heave of data that can't be managed by traditional data handling methods or techniques. The field of Big Data plays an indispensable role in various fields, such as agriculture, banking, data mining, education, chemistry, finance, cloud computing, marketing, health care stocks. Big data analytics is the method for looking at big data to reveal hidden patterns, incomprehensible relationship and other important data that can be utilize to resolve on enhanced decisions. There has been a perpetually expanding interest for big data because of its fast development and since it covers different areas of applications. Apache Hadoop open source technology created in Java and keeps running on Linux working framework was used. The primary commitment of this exploration is to display an effective and free solution for big data application in a distributed environment, with its advantages and indicating its easy use. Later on, there emerge to be a required for an analytical review of new developments in the big data technology. Healthcare is one of the best concerns of the world. Big data in healthcare imply to electronic health data sets that are identified with patient healthcare and prosperity. Data in the healthcare area is developing past managing limit of the healthcare associations and is relied upon to increment fundamentally in the coming years. Keywords: Big Data; Big Data Analytics; Big Data Applications; Tools and Techniques; Challenges and Issues. |
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