جنگی قیدیوں کے حقوق شریعت اسلامیہ اور بین الاقوامی قوانین کی روشنی میں

Islam encourages treating war-prisoners positively. The prophet Muhammad (peace be upon him) showed it by his conduct as he never mal  treated any war-prisinor. Quran also teaches it as Allah describes the qualities of true believers as “and they give food, inspite of their love for it (or for the love of Him), to the Miskīn (the poor), the orphan, and the captive. [Al-Dahar; 8] The same teachings are in practice in the international law. The present article dicusses the rights of war-prisoners both in the light of Islamic and international law.   

Developing an Information and Communcation Technologys Acceptance Model in the Context of Social Environment and Measuring the Performance Using Fuzzy Models

Despite significant investments in information technology in developing nations like Pakistan over recent decades, concern still exists over the extent to which such expenditures have produced the intended benefits. At least part of this concern is based around the issue of how information technology and information systems are accepted by the intended users. The Technology Acceptance Model (TAM) provides us with the fundamental frame work to analyse the acceptance of Information Systems from a behavioural perspective. In this study, we intend to enhance and classify the variables of the existing TAM to account for their importance so that organizations and institutions can rely on this classification to focus on the most important variables for quicker and smooth adoption of technology. Especially in the context of developing countries’ dynamics, the technology acceptance variables will be explored. A classification of the technology acceptance variables has been developed. This is the first of its kind classification based on the random Fuzzy (Burney, Ali, & Mahmood, 2012) Forest model, which in comparison with other fuzzy techniques has given better results for classification. To analyse the results, different statistical methods have been used. The study also involves extensive field study as well as data collection and data-mining techniques to analyse and identify multi-dimensional patterns in data. Measures of social influence on/of Information and Communication Technologies (ICT) will also be identified and a suitable Technology Implementation Model will also be developed. For this purpose, the case of smart watch dissemination in Pakistan will be used and appropriate model to enhance user acceptance of smart watch technology will be proposed. This thesis focuses on the acceptance and adoption of smartwatches, specifically in Pakistan. While there are several research studies on the subject of wearable technology, many do not emphasize a specific piece of wearable technology like the smartwatch. Either that or they are focused on the utilization of these wearable products where fitness tracking, healthcare, biometric sensors and other such applications are discussed. It is important that an innovation be understood from the user’s perspective, especially in its Page 3 of 155 early stages when knowledge of consumer requirements is insufficient. Smartwatch studies should be audience driven instead of technology driven which is the situation in most cases. Because the innovation is made for the user therefore should revolve around not what the technology is capable of but if it fulfils the needs and requirements of the users. Hence, this quantitative research aims to fill that gap and identify the factors that influence people’s intention to use a smartwatch along with the discussion of wearable and smart technology, its history, its advantages and disadvantages, different technology acceptance and adoption frameworks as well as their comparison. In addition to that, a model is proposed along with the respective hypotheses to examine the adoption and acceptance of smartwatches and for validation analyses conducted on the data gathered. A classification of the technology acceptance variables has been developed. This is the first of its kind classification based on the random Fuzzy Forest model, which in comparison with other fuzzy techniques has given better results for classification.