• Energy Research

Representation of Pre-RST information is very useful using visualized elements for realization of benefits of requirement traceability. This improves the practitioner motivation to maintain Pre-RST information during life cycle processes. Few researchers proposed visualization for Post-RST due to which many benefits of requirement traceability cannot be realized. This paper proposed an improved visualization representing Pre-RST information that demonstrates various benefit of requirement traceability. In order to evaluate empirically, an experiment is conducted and textual representation of traceability information is obtained. In order to strengthen our claim a survey is conducted to compare textual representation of traceability information with proposed visualization and results are compiled.

In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing the energy optimization problem. The goal of each technique is to maintain a balance between user comfort and energy requirements, such that the user can achieve the desired comfort level with the minimum amount of energy consumption. Researchers have addressed the issue with the help of different optimization algorithms and variations in the parameters to reduce energy consumption. To the best of our knowledge, this problem is not solved yet due to its challenging nature. The gaps in the literature are due to advancements in technology, the drawbacks of optimization algorithms, and the introduction of new optimization algorithms. Further, many newly proposed optimization algorithms have produced better accuracy on the benchmark instances but have not been applied yet for the optimization of energy consumption in smart homes. In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes. Detailed discussion has been carried out on different factors contributing towards thermal comfort, visual comfort, and air quality comfort. We have also reviewed the fog and edge computing techniques used in smart homes.

A Data center comprises of servers, storage devices, cooling and power delivery equipment to support other components, exchange data and information to provide general services such as software-as-a-service (SaaS), platform-as-a-service (PaaS), and Internet-as-a-service (IaaS). Data centers require massive amount of computational power to drive complex systems. In return these massive systems bring many challenges and concerns including power dissipation and environmental sustainability. Higher power demand in data centers and changes in computing technology together to maximize data center performance has led to deploying multitude methods to estimate power intensity. Energy cost increment, global economic downturn, and global warming and other concerns have resulted in new research in achieving power efficient data centers. The research proposed in this paper evaluates three task scheduling algorithms RASA, TPPC, and PALB to get the most energy efficient task scheduling algorithm to be used in data centers for measuring their performance and efficiency. The three algorithms are evaluated for performance using three parameters; power efficiency, cost effectiveness, and amount of CO2 emissions. On top of that data center location and climate conditions are also considered and analyzed as parameters as they directly effect the operating costs, the amount of power consumption and CO2 emission. To minimize the power wasted by data center cooling systems is directly related to data center location and climate change. CloudSim simulator is used to implement the algorithms on an IaaS cloud infrastructure, to calculate the power consumption, and to analyze each algorithm׳s behavior for different parameters. The results generated clearly shows that TPPC is the most efficient algorithm due to less amount of power consumption and low volume of CO2 emission; however its implementation cost is bit higher compare to PALB and RASA.

Cloud computing is the de facto platform for deploying resource- and data-intensive real-time applications due to the collaboration of large scale resources operating in cross-administrative domains. For example, real-time systems are generated by smart devices (e.g., sensors in smart homes that monitor surroundings in real-time, security cameras that produce video streams in real-time, cloud gaming, social media streams, etc.). Such low-end devices form a microgrid which has low computational and storage capacity and hence offload data unto the cloud for processing. Cloud computing still lacks mature time-oriented scheduling and resource allocation strategies which thoroughly deliberate stringent QoS. Traditional approaches are sufficient only when applications have real-time and data constraints, and cloud storage resources are located with computational resources where the data are locally available for task execution. Such approaches mainly focus on resource provision and latency, and are prone to missing deadlines during tasks execution due to the urgency of the tasks and limited user budget constraints. The timing and data requirements exacerbate the efficient task scheduling and resource allocation problems. To cope with the aforementioned gaps, we propose a time- and cost-efficient resource allocation strategy for smart systems that periodically offload computational and data-intensive load to the cloud. The proposed strategy minimizes the data files transfer overhead to computing resources by selecting appropriate pairs of computing and storage resources. The celebrated results show the effectiveness of the proposed technique in terms of resource selection and tasks processing within time and budget constraints when compared with the other counterparts.

This paper examines the manner in which audits would be conducted in the future and how technology has transformed and impacted the business processes of public, private sector entities and various organisations and the guidelines which need to be followed to ensure compliance with applicable laws and regulations. The tranperancy of financial statements is of paramount interest to shareholders and other significant stakeholders. This necessities that the financial statements are audited to acquire a certain level of confidence over the integrity of numbers and the validity of business rationale which thereby arises a need for auditor to be well equipped with all the tools and system essentials in carrying out an effective and efficient audit. Information Technology can act as an impediment or stimulant towards the achievement of the above discussed objective. Various organizations use automation tools and ERP applications which have become a vital cog in their internel control environment. Understanding by auditor of these automated controls is necessary to ensure that the they are well equipped with the requisite skills and have knowledge of all technological tweaks that would be required in the audit process of a complex structured entity. The primary function which can be performed by generalized audit software include customizing data in numrous ways to serve the distinct purpose. The audit teams obtain insights into latest developments and plan their procedures accordingly keeping in view the applicable professional standards.

Wearable devices such as exoskeletons are being opted frequently during rehabilitation processes for the post stroke recovery. Such devices are playing important role in the development of assistive rehabilitation robotic systems. In this paper three control strategies MPC and LQR and PID are introduced which were applied to knee joint of lower limb exoskeleton model for passive exercise. The two controls MPC and LQR are model based control which empowers them for stable responses. In this paper the analysis of robustness of control is done under the noisy and disturbance conditions. The results showed good performance of the exoskeleton model with the applied controls in the provided condition. In the future work the applied controls will be implemented on hardware.

Seen through the lens of the educational sector, social media grew to become a vital source of academic learning. The learning through social media occurs mainly through the collaborative approach to information sharing, where the web-based social networking sites provide the optimal platform for knowledge enhancing among colleagues, co-workers, and others. Developed economies have already recognized the significant value of learning through social media. However, developing economies such as Pakistan did not yet interpret future implications and real benefits of social media aided learning. This research focuses on determining significant factors through an integrated framework that features broadly recognized technology models such as Technology acceptance model (TAM) and Innovation diffusion theory (IDT). The subjects of the framework testing were students in higher education institutions that use social media, and the sample size was 350 students. Data analysis results, reached via SPSS software, were substantially in favour of extended model. Results reached through this study, in terms of factors with a significant influence on social media acceptance rate in Pakistani higher education institutions, are particularly crucial for students in the field of education, located in developing countries. This should assist the increasing acceptance and use of technological solutions, benefiting both faculty and students.

In engineering and technology safety of human life has always been a top priority. With the increasing usage of vehicles in everyday life, probability of deaths and injuries has also increased. This paper provides a critical review on the optimization of vehicle frontal crashworthiness studied by researchers using various methods. They investigated the effects of crash at a defined speed using the method of FRB and ODB impact. It further discusses other methods that can be used to save passengers’ life. Also, the designing and manufacturing limitations faced by engineers in actual development processes. Finally, it is concluded that improved structure design and material composition can significantly increase the overall crashworthiness of the vehicle.