Branchless Banking (BB) is an emerging financial segment also known as “banking beyond branches”. Branchless banking has viable opportunities for old as well as new entrants in technology based businesses. The strategic alliances and integrations with banks, mobile network operators (MNO’s), agents, and infinite retail-outlets have the opportunity to maximize their profitability. New and emerging business opportunities always have challenges. Accordingly, BB also faces the challenges such as lack of trust, security, technology, e-readiness, regulatory norms, proper agent checking for implementation of AML (Anti Money Laundering), and KYC (Know Your Customer). The paper examines Strengths Weakness, Opportunities and Threats (SWOT) of BB and recommends some strategies to overcome the identified challenges and make the avenue more profitable specifically in Pakistan. Despite enormous challenges, BB has many potential opportunities and scope to boost up the economy by improving employment opportunities and foreign investments in branchless banking infrastructure in the country.

Field of medical image analysis is evolving at a rapid pace. New advancements have introduced big challenges in analysis and information extraction from the generated images. Usually the scale of input data is so immense that it needs very efficient and smart algorithms to process intended outcomes. Magnetic Resonance Images (MRI) is one of the primary sources for morphometric analysis. Frequently used techniques for this kind of analysis are Principal Component analysis (PCA) and a more robust Incremental Principal Component Analysis (IPCA). Both these techniques apply complex algorithms for producing statistical shape models which ultimately show variance in clinical images. Variance is primarily detected and measured in the articular cartilage. Statistical assessment of cartilage volume and surface area estimation gives an indication of osteoarthritis severity. This research paper proposes an agile framework for segmentation of images of the knee by using Active contour model. Image texture information is merged in the model with the help of effective mathematical functions. Vector valued geodesic was used during segmentation and also to detect and measure variance in the image at pixel level. By use of efficient algorithms and mathematical tools this technique showed promising results in handling noise and nonuniform intensities within the image. The algorithm effectively provided a quantitative cartilage assessment which could help physicians in classifying osteoarthritis stages.

Human activity recognition using Smartphone’s sensors is a growing area now a day. This study is concerned with health monitoring and typically recognized arm and elbow exercise activities with the help of Smartphone’s accelerometer. The recognized arm and elbow exercises are: Bicep Curl, Active Pronator, Active Supinator, Assisted Biceps, Isometric Biceps and Isometric Triceps. The data were collected by placing Smartphone at two positions, i.e. “at wrist” and “in hand”, using supervised approach. Twenty (20) volunteers (ten male and ten female) were engaged for the experiment. Each participant performed these activities approximately 20 minutes and total dataset includes around 400 minutes time. Various algorithms based on literature were used for the recognition of defined activities. Results show that Smartphone’s accelerometer can be used for the recognition of arm & elbow exercises, which can further be extended for the application of stroke and injured patients.

In this era of internet web security is the main issue. The internet growth led the web crimes to increase. The enhancement of new architectures makes the web application prone to security risks. Now a day’s Model View Controller Architecture is very well known name for web application development. It could be a very good solution for rapid application development. This model can be implemented in PHP and ASP.Net. With comparison of both languages regarding their performance, time, and memory our findings show that ASP.Net is better than PHP framework. But there are several security risks that exploit the Model View Controller Architecture. The Open Web Application Security Project identifies common types of risks a typical architecture can expect. Researchers are paramount to secure the websites. Hence security have become major concern and researchers have developed various security detection and prevention approaches. This paper provides the overview of the web applications developed in Model View Controller Architecture using ASP.Net or PHP with common web applications risks that are used to tamper systems assets and possible solutions to secure them. It also proposes the further possibilities to develop a security model in Model View Controller ASP.Net for the protection of sensitive data exposure risk.

The advent of internet has revolutionized every aspect of human communication whereas the arrival of social web has further augmented it. The use of this interactive platform is highly popular among the internet generation. This tremendous increase of social media in short, period of time is because of student's interest in this particular platform. These are the websites and mobile applications assisting students in variety of communication activities, including learning. However, this platform can also divert their attention from effective learning. This situation raised serious treats to young’s future learning performance, and needs to understand their sharing behavior. Prior research has extensively inquired social media. However, fewer efforts have been made to inquire student distraction form their academic achievements. The current study is conducted with the objective to identify the current use and examine factors persuade students for the academic use of social media. Using technology acceptance models, TAM, TAM-2 and UTAUT as a theoretical framework. Data was collected from undergraduate students of higher-education Malaysia. The collected data was analyzed with help of the statistical packages SPSS and AMOS. Findings reveals that perceived usefulness, subjective norms and information quality are the prime factors persuade students to adopt this platform for their academic purposes.