System Support for Managing Invalid Bindings

Context-aware adaptation is a central aspect of pervasive computing applications, enabling them to adapt and perform tasks based on contextual information. One of the aspects of context-aware adaptation is reconfiguration in which bindings are created between application component and remote services in order to realize new behaviour in response to contextual information. Various research efforts provide reconfiguration support and allow the development of adaptive context-aware applications from high-level specifications, but don't consider failure conditions that might arise during execution of such applications, making bindings between application and remote services invalid. To this end, we propose and implement our design approach to reconfiguration to manage invalid bindings. The development and modification of adaptive context-aware applications is a complex task, and an issue of an invalidity of bindings further complicates development efforts. To reduce the development efforts, our approach provides an application-transparent solution where the issue of the invalidity of bindings is handled by our system, Policy-Based Contextual Reconfiguration and Adaptation (PCRA), not by an application developer. In this paper, we present and describe our approach to managing invalid bindings and compare it with other approaches to this problem. We also provide performance evaluation of our approach

Trade credit promotes industrial growth during the COVID-19 pandemic: Evidence from the textile sector of Pakistan

Relevance. The rapid spread of COVID-19 around the world is disastrous to low-income countries. The pandemic was a serious threat to developing countries. In the case of Pakistan's textile industry, small and medium-sized enterprises (SMEs) have been hit hard. Importantly, the textile sector is the largest industrial sector in Pakistan.Purpose of the study. The purpose of the article is to identify the challenges that SMEs are facing due to the pandemic and to consider trade credit as a possible tool to resolve them.Data and Methods. The data were collected through the questionnaire survey among the representatives of SMEs in the textile industry in Pakistan. In total, representatives of 150 textile industries were surveyed, but due to incomplete data only 115 were used for the analysis. The survey was conducted from March 2020 to March 2021. Then, the structural equation model (SEM) was applied to ensure the accuracy of the results.  Results. The COVID-19 pandemic has impacted the textile industry in Pakistan and the buying process as well as the satisfaction level.  The study highlights the industrial safety issues during the pandemic which exacerbated the economic difficulties. The study also explains the mechanism how perceived control over buying, perceived satisfaction, and perceived trust in science relate to trade credit and COVID-19 pandemic.Conclusions. The Pakistani government has taken many proactive measures, but there is still no consistent policy to attract more agents to the small textile business. Thus, a trade loan is the best solution for SMEs as it does not require immediate cash payments. The lack of government support has exacerbated the general pandemic-related economic crisis. In this light, trade loans may be considered as one of the most effective tools to keep SMEs afloat

Challenges of small- and medium-sized businesses in Pakistan due to COVID-19 pandemic

Relevance. Human health is essential to economic activity and social development. The rapid spread of the coronavirus disease (COVID-19) all around the world can be particularly disastrous for low-income persons, which means that the pandemic poses a severe threat for developing countries. In Pakistan, small and medium enterprises (SMEs) were hit especially hard by the pandemic and lockdown restrictions. This research focuses on the economic challenges faced by Pakistan in combatting the impacts of the pandemic.Research objective.The purpose of the article is to identify the difficulties faced by SMEs as a result of the coronavirus infectionData and methods. The methodological approach presents an analysis of statistical data to show the main problems of the SME sector during the COVID-19 pandemic. The study used the data from the statistical report of the Ministry of Health of the Government of Pakistan (GOP), as well as the data from previous studies on the effects of COVID-19 pandemic.Results. The study identified problems for SMEs during COVID-19, such as the lack of capital and the lack of satisfactory business plans. Moreover, poverty is one of the most serious problems in Pakistan, which is why SMEs cannot afford prolonged isolation during the Covid-19 pandemic and individual entrepreneurs have to risk their lives for their families. The government of Pakistan has adapted steps to control the epidemic, however, so far there is no policy for small business investors. The authorities are still working on the policies for small business units.Conclusions. Although Pakistan has adopted many protective measures, the situation regarding measures to support SMEs still leaves much to be desired.The lack of state support contributes to the general economic crisis the country has faced due to the pandemic

Influence of shareholder equity on trade credit demand: The study of non-financial firms in Pakistan

Relevance. Most small-sized firms have little or no access to credit markets, which is why they prefer equity financing and usually pay higher dividends on this equity. When paying higher dividends, these small-sized debt-free firms continue to build a reputation in the markets.Research objective. The analysis focuses on the trade payables that impact shareholder equity. In Pakistan, most of the businesses are small and middle-sized. Most of the Pakistani SMEs have a low capital structure and these enterprises depend on their daily business needs, so equity financing is their primary source of funding.Data and Methods. The data source for our study is the financial statements of non-financial firms (in total, 156 firms) from the balance Sheet Analysis (BSA) and the Financial Statement Analysis (FSA) published by The State Bank of Pakistan (SBP). The financial statements also provide the data listed by the Pakistan Stock Exchange (PSX). The data cover the period from 2001 to 2017. This study primarily relies on the panel data model. The study applied the methods of descriptive analysis, correlation matrix, common regression model, fixed effect model, random effect model and then the Hausman test was performed to choose the best model.Results. The results of the study indicate a positive and significant relationship between shareholder equity and trade credit demand.Conclusion. Many investors require trade credit as a suitable tool for the growth of shareholders of the company. It is also used in many types of business schemes as the shareholder equity factor plays a role in profit generation through the use of trade credit transactions

Moderating Role of Cognitive Style in Decision Making on the Relationshipbetween Satisfaction Factor and Turnover Intention

The aim of the paper is to identify the moderating effect of analytical cognitive style on the relationship between salary satisfaction and turnover intention among academicians. The survey approach questions were used in order to collect the primary data from informants. Total 502 complete questionnaires were collected back and used in the analysis. SPSS 21 was sued for developing database for analyzing data. The bivariate correlation and hierarchical multiple regression was used in analysis. The results of correlation revealed the significant relationship between salary and turnover intention, salary and analytical cognitive style, analytical and turnover intention. The academicians were found satisfied from the salary packages. The analytical cognitive style was found acting as a moderator between salary satisfaction and turnover intention. Complete moderation has occurred. So this study introduced the new model of job satisfaction with novel results of moderation in the theory of job satisfaction

Machine Learning: The Backbone of Intelligent Trade Credit-Based Systems

Technology has turned into a significant differentiator in the money and traditional recordkeeping systems for the financial industry. To depict two customers as potential investors, it is mandatory to give the complex innovation that they anticipate and urge to purchase. In any case, it is difficult to keep on top of and be a specialist in each of the new advancements that are accessible. By reappropriating IT administrations, monetary administrations firms can acquire prompt admittance to the most recent ability and direction. Financial systems, along with machine learning (ML) algorithms, are vital for critical concerns like secure financial transactions and automated trading. These are the key to the provision of financial decisions for investors and stakeholders for the firms which are working with the trade credit (TC) approach, in Small and Medium Industries (SMEs). Huge and very sensitive data is processed in a limited time. The trade credit is a reason for more financial gains. The impact of TC with predictive machine learning algorithms is the reason why intelligent and safe revenue generation is the main target of the proposed study. That is, the combination of financial data and technology (FinTech) domains is a potential reason for sales growth and ultimately more profit.publishedVersio

A Descriptive Study on Patterns of Traumatic Spinal Injuries in a Tertiary Care Hospital Rawalpindi

Introduction: Spinal injuries are one of the most debilitating injuries if not fatal and affect every dimension of patients' lives i.e. early mortality and late complications. Lifelong disability due to spinal cord injury is very common even if the patient survives early death. The current study was aimed to investigate the frequency, management, mortality, the pattern of spinal injuries and to recommend plans for better patient management based on assessment.Material and Methods: The study was descriptive, cross-sectional, and was conducted at the Neurosurgery Department of Rawalpindi Medical University and Allied Hospitals for the duration of October 2018 to January 2019. All cases of traumatic spinal injuries were included and variables noted were gender, age, mode of Injury, presenting motor power in limbs, ASIA score, diagnosis, management, outcome, and deaths.Results: In the sample size of 84 patients, the mean age was 37.1 years, the mechanism of injury due to falls was most common at 73%, the lumbar region was found to be the most common area involved. Male patients outnumbered females in the study. 14% of the patients could not survive due to the injury, 15% received cervical traction, 4% received cervical traction and anterior cervical plating, and 43% of patients underwent Transpedicular Screw Fixation, the total number of patients who expired was 25%.Conclusion: Patterns of traumatic spinal injuries are changing, shifting from road traffic accidents to falls being the primary cause nowadays, with prolonged hospital stay periods, disability for life, and high-cost treatments putting a huge burden on our already exhausted health resources. Efforts should be made to make a national registry for traumatic spinal injuries presented to the emergency department and guidelines should be established regarding occupational hazards. Awareness should be given to the general population regarding hazards at home regarding falls