Towards distributed architecture for collaborative cloud services in community networks

Internet and communication technologies have lowered the costs for communities to collaborate, leading to new services like user-generated content and social computing, and through collaboration, collectively built infrastructures like community networks have also emerged. Community networks get formed when individuals and local organisations from a geographic area team up to create and run a community-owned IP network to satisfy the community’s demand for ICT, such as facilitating Internet access and providing services of local interest. The consolidation of today’s cloud technologies offers now the possibility of collectively built community clouds, building upon user-generated content and user-provided networks towards an ecosystem of cloud services. To address the limitation and enhance utility of community networks, we propose a collaborative distributed architecture for building a community cloud system that employs resources contributed by the members of the community network for provisioning infrastructure and software services. Such architecture needs to be tailored to the specific social, economic and technical characteristics of the community networks for community clouds to be successful and sustainable. By real deployments of clouds in community networks and evaluation of application performance, we show that community clouds are feasible. Our result may encourage collaborative innovative cloud-based services made possible with the resources of a community.Peer ReviewedPostprint (author’s final draft

A distributed auctioneer for resource allocation in decentralized systems

In decentralized systems, nodes often need to coordinate to access shared resources in a fair manner. One approach to perform such arbitration is to rely on auction mechanisms. Although there is an extensive literature that studies auctions, most of these works assume the existence of a central, trusted auctioneer. Unfortunately, in fully decentralized systems, where the nodes that need to cooperate operate under separate spheres of control, such central trusted entity may not exist. Notable examples of such decentralized systems include community networks, clouds of clouds, cooperative nano data centres, among others. In this paper, we make theoretical and practical contributions to distribute the role of the auctioneer. From the theoretical perspective, we propose a framework of distributed simulations of the auctioneer that are Nash equilibria resilient to coalitions and asynchrony. From the practical perspective, our protocols leverage the distributed nature of the simulations to parallelise the execution. We have implemented a prototype that instantiates the framework for bandwidth allocation in community networks, and evaluated it in a real distributed setting.Peer ReviewedPostprint (author's final draft

Sentiment classification of Roman-Urdu opinions using Naïve Bayesian, Decision Tree and KNN classification techniques

AbstractSentiment mining is a field of text mining to determine the attitude of people about a particular product, topic, politician in newsgroup posts, review sites, comments on facebook posts twitter, etc. There are many issues involved in opinion mining. One important issue is that opinions could be in different languages (English, Urdu, Arabic, etc.). To tackle each language according to its orientation is a challenging task. Most of the research work in sentiment mining has been done in English language. Currently, limited research is being carried out on sentiment classification of other languages like Arabic, Italian, Urdu and Hindi. In this paper, three classification models are used for text classification using Waikato Environment for Knowledge Analysis (WEKA). Opinions written in Roman-Urdu and English are extracted from a blog. These extracted opinions are documented in text files to prepare a training dataset containing 150 positive and 150 negative opinions, as labeled examples. Testing data set is supplied to three different models and the results in each case are analyzed. The results show that Naïve Bayesian outperformed Decision Tree and KNN in terms of more accuracy, precision, recall and F-measure

PAKISTAN IN THE FATF GREY-LIST: CHALLENGES, REMEDIES AND INTERNATIONAL RESPONSE

The Financial Action Task Force (FATF) grey-listed Pakistan due to the latter’s non-compliance to the United Nations Security Council Resolution (UNSCR)-1267. The FATF also demands Pakistan to put strict controls on money laundering and financial lifelines of terrorist organizations in Pakistan. The plan of action was reached between Pakistan and FATF to ensure sufficient action to enforce anti-money laundering policies and freeze assets of designated terrorist groups in Pakistan under UNSCR-1267 and UNSCR-1373. The NACTA in collaboration with FBR, State Bank of Pakistan, FIA, and the Securities and Exchange Commission of Pakistan has mounted operations against illegal movement of money within Pakistan. It also has choked financial lifelines of terrorist organizations and curbed Hawala/Hundi methods of laundering money. Pakistan is struggling to stick to the 26-point action plan to address the necessary concerns of FATF. This paper put forth the ramifications for being blacklisted by FATF and also highlights the Trump administration’s tough stance towards Pakistan. This paper also offers concrete recommendations to exclude Pakistan’s name from the FATF grey-list.   Bibliography Entry Amin, Musarat, Muhammad Khan , and Rizwan Naseer. 2020. "Pakistan in the FATF Grey-List: Challenges, Remedies and International Response." Margalla Papers 24 (1): 31-43

Capital Structure Theories and Speed of Capital Adjustment towards Target Capital Structure along Life Cycle Stages of Asian Manufacturing Firms

Purpose: Firms have different costs and benefits and asymmetric information across their life cycle stages and hence each stage has different financial pattern and speed of adjustment towards target capital. Methodology: We use System GMM to test the hypotheses. We use market leverages proxies for the capital structure, life cycle proxies: introduction, growth, mature, shakeout and decline and the control determinants of capital structure such as profitability, tangibility, firm size and growth opportunities. We estimate the financial pattern and speed of adjustment along life cycle stages of manufacturing firms from eleven Asian economies over the period of 2010-2018. Findings: The results show that firms in earlier stages have more long term debt than mature stage. The speed of adjustment towards target capital structure is highest in mature stage than the other stages. The control determinants significantly affect market leverages. Implications: The findings suggest that management has to consider life cycle stages of their firms in order to adjust capital structure. Stockholders should consider stage of firm with relation to profitability and capital structure for long term prospects

The Response of Land Surface Temperature to the Changing Land-Use Land-Cover in a Mountainous Landscape under the Influence of Urbanization: Gilgit City as a case study in the Hindu Kush Himalayan Region of Pakistan

With growing urbanization in mountainous landscapes, the built-up areas dominate other land use classesresulting in increased land surface temperature (LST). Gilgit city in northern Pakistan has witnessed tremendousurban growth in the recent past decades. It is anticipated that this growth will exponentially increase in the nearfuture because of the China-Pakistan Economic Corridor (CPEC) initiatives, as this city happens to be thecommercial hub of the northern region of Pakistan. The objective of present study is to explore the influence ofland use and land cover variations on LST and to evaluate the relationship between LST with normalizeddifference vegetation index (NDVI), normalized difference water index (NDWI), and normalized difference built -up index (NDBI) values. This study is carried out on data from Google earth and three Landsat images (Landsat 5-TM, Landsat 7-ETM, and Landsat OLI_TIRS-8) during the period from 1992, 2004 and 2016. Land use/coverclasses are determined through supervised classification and LST maps are created using the Mono -windowalgorithm. The accuracy assessment of land use/cover classes is carried out comparing Google Earth digitizedvector for the periods of 2004 and 2016 with Landsat classified images. Further, NDVI, NDBI, and NDWI mapsare computed from images for years 1992, 2004, and 2016. The relationships of LST with NDVI, NDBI, andNDWI are computed using Linear Regression analysis. The results reveal that the variations in land use and landcover play a substantial role in LST variability. The maximum temperatures are connected with built -up areas andbarren land, ranging from 48.4°C, 50.7°C, 51.6°C, in 1992, 2004, and 2016, respectively. Inversely, minimumtemperatures are linked to forests and water bodies, ranging from 15.1°C, 16°C, 21.6°C, in 1992, 2004, and 2016respectively. This paper also results that NDBI correlates positively with high temperatures, whereas NDVI andNDWI associate negatively with lesser temperatures. The study will support to policymakers and urban planners tostrategize the initiatives for eco-friendly and climate-resilient urban development in fragile mountainouslandscapes

Industry 4.0 or Pharma 4.0?

This chapter examines the convergence of Industry 4.0 and Pharma 4.0 in the context of healthcare supply chains. It investigates the potential applications of these industrial revolutions to enhance the flexibility, benefits, challenges, and opportunities of healthcare supply chains. This chapter highlights the application of state-of-the-art technology to create intelligent, adaptable, and personalized supply chain systems for the healthcare and pharmaceutical sectors. The literature on “Pharma Industry 4.0” is reviewed, with a focus on the opportunities for sustainable value creation and pharmaceutical supply chain research. Healthcare supply chain has some serious issues like counterfeit drugs, non-transparent supply chain, unfear track and trace system of medicines and biomedical instruments. The authors identified the potential solutions for these issues with the help of current innovative technologies and practices

Corporate Social Responsibility and Firms’ Financial Performance: A Conceptual Framework

This paper conceptually analyses the impact of corporate social responsibility(CSR) on firms’ financial performance. CSR is considered as an important business strategy that achieves a steady growth in firms’ profitability through improving their image. It includes all those strategies which account for are an ethical conduct and society friendly approach beneficial for the development of society. In addition to profit-maximization, the firm is also supposed to undertake activities which uplift the life of employees and the general public. In this regard, the conceptual framework of the current study shows that firms spend on awarding scholarships to needy students, health activities such as health awareness program, free medical camps, environmental protection awareness programs and sports activities. The conceptual framework alsohighlights that firms with large capital spend more on CSR activities owing to anincreased pressure of the government, public, media and other stakeholders. Based on the previous extant literature, it is also assumed that firms which earn higher profits spend more on CSR in the coming year/s that have positive impacts on their profitability. However, by following theoretical postulations, it is assumed the relationship between CSR and firms’ profitability may be endogenous. Accordingly, this study proposes dynamic GMM estimation that is a preferred technique, particularly in the presence of endogeneity