Analysis of Electronic Banking Services & Its Issues in Pakistan

Technology is making a tremendous impact upon financial services sector is no exception. Today, banks take special attention to customers' perspective by providing quality of services. Loyalty is a very important issue for customers and for the sake of organizational benefits, the banks need to obtain customer satisfaction due to competitive market. In the areas of services the concept of service quality plays a central role in understanding customer satisfaction and retention. To improve the efficiency and enhance pace of working information technology is playing a fundamental role in any business. This becoming a critical success factor to gain competitive edge than competitors. Electronic banking includes phone or mobile banking, Internet or online banking and email banking and ATM. banking Sector or industry, bringing up new product called online banking or e-banking. Customer needs and requirements are changing day by day. Customer wants instant response, access, convenience and security. There are several issues in  electronic banking which customer face; including Non availability of sufficient cash in ATM in particular occasion and time, Link down, customer account debited but receiver’s account is not debited, pin generation process and card blocking process and any cash transaction related problems. The Banks now use different mobile applications app, MAC ID system and code generation to double verify the PIN and customer verification tactics in online banking to secure the customers transactions. The technology brings easiness, reliability and competence. The rate of success of these new products will depend on the suitability of the technology selected for the customers in banks. A well-defined security system and audit plan will ensure the long term success of IT plans of banks. Security is the most critical factor for banks now a days. Keywords: Customer perspective, Service quality, Electronic banking, ATM, MAC ID, Information technology

Understanding and Managing Non-functional Requirements for Machine Learning Systems

Background: Machine Learning (ML) systems learn using big data and solve a wide range of prediction and decision making problems that would be difficult to solve with traditional systems. However, increasing use of ML in complex and safety-critical systems has raised concerns about quality requirements, which are defined as Non-Functional requirements (NFRs). Many NFRs, such as fairness, transparency, explainability, and safety are critical in ensuring the success and acceptance of ML systems. However, many NFRs for ML systems are not well understood (e.g., maintainability), some known NFRs may become more important (e.g., fairness), while some may become irrelevant in the ML context (e.g., modularity), some new NFRs may come into play (e.g., retrainability), and the scope of defining and measuring NFRs in ML systems is also a challenging task.Objective: The research project focuses on addressing and managing issues related to NFRs for ML systems. The objective of the research is to identify current practices and challenges related to NFRs in an ML context, and to develop solutions to manage NFRs for ML systems.Method: We are using design science as a base of the research method. We carried out different empirical methodologies–including interviews, survey, and a part of systematic mapping study to collect data, and to explore the problem space. To get in-depth insights on collected data, we performed thematic analysis on qualitative data and used descriptive statistics to analyze qualitative data. We are working towards proposing a quality framework as an artifact to identify, define, specify, and manage NFRs for ML systems.Findings: We found that NFRs are crucial and play an important role for the success of the ML systems. However, there is a research gap in this area, and managing NFRs for ML systems is challenging. To address the research objectives, we have identified important NFRs for ML systems, and NFR and NFR measurement-related challenges. We also identified preliminary NFR definition and measurement scope and RE-related challenges in different example contexts.Conclusion: Although NFRs are very important for ML systems, it is complex and difficult to define, allocate, specify, and measure NFRs for ML systems. Currently the industry and research is does not have specific and well organized solutions for managing NFRs for ML systems because of unintended bias, the non-deterministic behavior of ML, and expensive and time-consuming exhaustive testing. Currently, we are working on the development of a quality framework to manage (e.g., identify important NFRs, scoping and measuring NFRs) NFRs in the ML systems development process

Money, Interest Rate and Stock Prices: New Evidence from Singapore and The United States

This paper examines the long-term as well as short-term equilibrium relationships between the major stock indices and selected macroeconomic variables (such as money supply and interest rate) of Singapore and the United States by employing the advanced time series analysis techniques that include cointegration, Johansen multivariate cointegrated system, fractional cointegration and Granger causality. The cointegration results based on data covering the period January 1982 to December 2002 suggest that Singapore’s stock prices generally display a long- run equilibrium relationship with interest rate and money supply (M1) but a similar relationship does not hold for the United States. To capture the short-run dynamics of the relationship, we replicate the same experiments with different subsets of data representing shorter time periods. It is evident that stock markets in Singapore moved in tandem with interest rate and money supply before the Asian Crisis of 1997, but this pattern was not observed after the crisis. In the United States, stock prices were strongly cointegrated with macroeconomic variables before the 1987 equity crisis but the relationship gradually weakened and totally disappeared with the emergence of Asian Crisis that also indirectly affected the United States. The results of fractional cointegration and the Johansen multivariate system are consistent with the earlier cointegration result that both Singapore and US stock markets did possess equilibrium relationship with M1 and interest rate at the early days. However, the stability of the systems was disturbed by a series of well-known financial turbulence in the past two decades and eventually weakened for Singapore and completely disappeared for the U.S. This may imply that monetary authority may take action to respond to the asset price turbulence in order to maintain the stability of monetary economy and thus break the existing equilibrium between stock markets and macroeconomic variables like interest rate and M1. Another possible explanation is that the market became more efficient after 1997 Asian crisis. Finally, the results of Granger causality tests uncover some systematic causal relationships implying That stock market performance might be a good gauge for Central Bank’s monetary policy adjustment.

Poverty Alleviation Through Access to Education: Can E-Learning Deliver?

Access to education has long been considered an important vehicle for poverty alleviation and tremendous efforts (national as well as international) have been made to broaden such access in LDCs. The ICT revolution in the past decade has greatly facilitated such efforts as education can now be provided to millions living in inaccessible (rural, mountainous, or landlocked) areas at the click of a mouse and at a relatively low cost without compromising quality. The webbased mode of education, popularly known as e-learning , has the capacity to make the acquisition of human capital cheaper and easier in poverty-ridden LDCs. Also, e-learning eliminates the human capital \u27bootstrapping problem\u27 by guaranteeing \u27just-in-time\u27 training of a superior quality at employees\u27 fingertips (literally and metaphorically!) It also has the potential to help reduce poverty by empowerment of the socially disadvantaged and less privileged in society including lower-income groups, the handicapped, sick and disabled (particularly those with writing, speaking and hearing impairments), members of ethnic minority groups, and women affected by cultural and religious prejudice. This is possible largely because, as this paper argues, physical location or ability is not critical for successful e-learning. The authors canvass all of these issues before proposing a new model for the optimal level of education in developing countries

Targeted Genome Editing for Cotton Improvement

Conventional tools induce mutations randomly throughout the cotton genome—making breeding difficult and challenging. During the last decade, progress has been made to edit the gene of interest in a very precise manner. Targeted genome engineering with engineered nucleases (ENs) specifically zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeat (CRISPR) RNA-guided nucleases (e.g., Cas9) has been described as a “game-changing technology” for diverse fields as human genetics and plant biotechnology. In eukaryotic systems, ENs create double-strand breaks (DSBs) at the targeted DNA sequence which are repaired by nonhomologous end joining (NHEJ) or homology-directed recombination (HDR) mechanisms. ENs have been used successfully for targeted mutagenesis, gene knockout, and multisite genome editing (GenEd) in model plants and crop plants such as cotton, rice, and wheat. Recently, cotton genome has also been edited for targeted mutagenesis through CRISPR/Cas for improved lateral root formation. In addition, an efficient and fast method has been developed to evaluate guide RNAs transiently in cotton. The targeted disruption of undesirable genes or metabolic pathway can be achieved to increase quality of cotton. Undesirable metabolites like gossypol in cottonseed can be targeted efficiently using ENs for seed-specific low-gossypol cotton. Moreover, ENs are also helpful in gene stacking for herbicide resistance, insect resistance, and abiotic stress tolerance

Non-Functional Requirements for Machine Learning: An Exploration of System Scope and Interest

Systems that rely on Machine Learning (ML systems) have differing demands on quality—non-functional requirements (NFRs)— compared to traditional systems. NFRs for ML systems may differ in their definition, scope, and importance. Despite the importance of NFRs for ML systems, our understanding of their definitions and scope—and of the extent of existing research—is lacking compared to our understanding in traditional domains.Building on an investigation into importance and treatment of ML system NFRs in industry, we make three contributions towards narrowing this gap: (1) we present clusters of ML system NFRs based on shared characteristics, (2) we use Scopus search results— as well as inter-coder reliability on a sample of NFRs—to estimate the number of relevant studies on a subset of the NFRs, and (3), we use our initial reading of titles and abstracts in each sample to define the scope of NFRs over parts of the system (e.g., training data, ML model). These initial findings form the groundwork for future research in this emerging domain

Association of seed morphology with seedling vigor in wheat (Triticum aestivum L)

Phenotyping of 225 spring wheat genotypes was carried out to determine theassociation of seed morphological traits with seedling vigour traits. The seed lengthappeared to be key trait being significantly and positively correlated with seed thickness,seed width, and coleoptile length. The seed length was also positively but non-significantlyassociated with root length, shoot length and number of seminal roots. The seed length, seedthickness and seed width were the major contributors to diversity among genotypes. Themost diverse genotypes with respect to seed morphological traits and seedling vigor traitswere KANCHAN, LU-26, OASIS, SHAHKAR-95, and SHALIMAR-88. The overall effect ofseed length, seed width and seed thickness was positive on seedling vigor traits

TERMINALIA CHEBULA: AN EPHEMERAL GLANCE

Herbal drugs represent a major allocation of all the recognized systems of health in the world. Also, the medicinal plants have been regarded as valuable and cheap sources of various phytoconstituents which are used extensively in the development of drugs against various diseases. Terminalia chebula, commonly called as black myrobalan, ink tree, or chebulic myrobalan, is a deciduous tree belonging to the family Combretaceae, has been regarded as one of the most important medicinal plants used in medicines of ayurveda, siddha, unani and homeopathy. Numbers of phytochemical constituents have been found to be associated with the drug such as tannins, chebulinic acid, ellagic acid, gallic acid, punicalagin and flavonoids. Moreover, Terminalia chebula has been well reported to possess antioxidant, antidiabetic, antibacterial, antiviral, antifungal, anticancerous, antiulcer, antimutagenic and wound healing activities. In addition, Terminalia chebula has been used extensively in the preparation of many Ayurvedic formulations for infectious diseases like chronic ulcer, leucorrhoea, pyorrhoea and fungal infections of the skin. The present review article has been designed to elucidate data on phytochemistry, pharmacognostic characters and pharmacological activities associated with Terminali