Impact of trade openness on output growth for Pakistan: an empirical investigation

In this paper we analyze the impact of trade liberalization policy on GDP growth of Pakistan for the period ranging from 1972 to 2002. We found that there is long run negative relationship between trade growth and GDP growth. When we separate the total trade volume in export and import we find insignificant positive relationship between GDP and export and import. Both the models showed positive and significant relationship between GDP and investment.Trade Openness; Liberalization

Emerging Trends in E-Learning in Punjab- Pakistan

رافق التعلم عبر الإنترنت والجوال ظهور اتجاهات ناشئة في التعليم خلال العقد الماضي الامر الذي يعكس التغييرات الهائلة في انتشار المعرفة المحدثة التي عززت النتاج التعليمي وملاءمة العالم في الوقت الحالي. وعملت شبكة الإنترنت والجوال معًا لتسهيل عملية التعلم الذاتي. وفي هذه الدراسة وضعت ثلاثة مؤشرات لتقييم أهمية التعلم الإلكتروني الذاتي؛ أولاً، التحقق من أن الإنترنت مصدر سهل لتعزيز وتحديث المعرفة من وجهة نظر طلاب الجامعات. ثانيًا، إدراك أن التعلم الإلكتروني هو وسيلة لتوفير الوقت للتعلم الذاتي. ثالثًا، سهولة الحصول على مصادر المعرفة الكترونيا في مجال دراسة معينة ومن خلال استخدام محركات البحث المختلفة. في هذه الدراسة تم إعداد استبيان راجعه النظراء وحكمه مراجعون متخصصون. الذين وافقوا على محتواه والجوانب الدلالية لجميع الأسئلة، لجمع البيانات من مائة طالب مسجلين في ثلاث جامعات عامة في البنجاب في باكستان. أوضحت النتائج أن الإنترنت والجوال يُستخدمان للتسلية والترفيه واكتساب المعرفة ومواد البحث ولتسهيل الدراسات أو الأبحاث في مختلف التخصصات. علاوة على ذلك، بدت نتائج الدراسة الحالية متباينه، وهو ما قد يرجع إلى فحوى الدراسة الحالية والنتائج المحتملة من استخدامات وممارسات المستخدمين الحاليين للتعلم الإلكتروني والجوال. والحقيقة المثبته و بوضوح على أن العلماء والطلاب يميلون في الغالب إلى مثل هذه التوجهات في دولة باكستان.Internet and mobile learning are necessarily emerging trends in education through last decade. They are mirroring vast changes and proliferation of update knowledge, which enhanced our learning productivity and real time world relevancy. Internet and mobile worked together to facilitate the self-learning process. In this study, there are three indicators set up to weigh the importance of E-learning; first, to investigate that the internet is an easy source of promoting and updating knowledge from university students’ points of view. Second,  to recognize that the E-learning is a time saving method of self-learning. Third, to facilitate gaining electronic sources of a specific study field through using different search engines. A peer reviewed questionnaire was prepared and governed by specialist reviewers; who agreed on its content and semantic aspects of all questions, to collect the data from one hundred students enrolled at three public universities of Punjab in Pakistan. Results outlined that internet and mobile are used to fun and entertainment, gain knowledge, search materials, and  to facilitate studies or researches of different disciplines. Furthermore, the outcomes of the current study seemed different, which may be due to the focus of the current study upon perceived consequences rather than uses and practices of current users of mobile and E-learning. The fact that apparently clear demonstrates that scholars and students mostly tend to such trends in Pakistan

Secure data sharing and analysis in cloud-based energy management systems

Analysing data acquired from one or more buildings (through specialist sensors, energy generation capability such as PV panels or smart meters) via a cloud-based Local Energy Management System (LEMS) is increasingly gaining in popularity. In a LEMS, various smart devices within a building are monitored and/or controlled to either investigate energy usage trends within a building, or to investigate mechanisms to reduce total energy demand. However, whenever we are connecting externally monitored/controlled smart devices there are security and privacy concerns. We describe the architecture and components of a LEMS and provide a survey of security and privacy concerns associated with data acquisition and control within a LEMS. Our scenarios specifically focus on the integration of Electric Vehicles (EV) and Energy Storage Units (ESU) at the building premises, to identify how EVs/ESUs can be used to store energy and reduce the electricity costs of the building. We review security strategies and identify potential security attacks that could be carried out on such a system, while exploring vulnerable points in the system. Additionally, we will systematically categorize each vulnerability and look at potential attacks exploiting that vulnerability for LEMS. Finally, we will evaluate current counter measures used against these attacks and suggest possible mitigation strategies

A cloud-based energy management system for building managers

A Local Energy Management System (LEMS) is described to control Electric Vehicle charging and Energy Storage Units within built environments. To this end, the LEMS predicts the most probable half hours for a triad peak, and forecasts the electricity demand of a building facility at those times. Three operational algorithms were designed, enabling the LEMS to (i) flatten the demand profile of the building facility and reduce its peak, (ii) reduce the demand of the building facility during triad peaks in order to reduce the Transmission Network Use of System (TNUoS) charges, and (iii) enable the participation of the building manager in the grid balancing services market through demand side response. The LEMS was deployed on over a cloud-based system and demonstrated on a real building facility in Manchester, UK

RAZMIN by Qureshi Enterprises: Competing with the Secret Sauce of Competitors

The case is comprised of the entrepreneurial venture of Mr. Fahim Qureshi, who visualized the opportunity for growth and marketability for food, beverages and various FMCG products in Pakistan by organizing the scattered demand. He established QURESHI ENTERPRISE (QE) in 1997.  Mr. Qureshi believe that his deep knowledge of the consumer market, compounded with financial strength and other capabilities provides ample opportunities and further scope for expansion and with this in mind he created his brand “ Razmin”. The brand is for numerous culinary products, like corns, curry pastes and wide range of sauces. All these items are manufactured, packed and branded in Thailand

Suspended accounts: A source of Tweets with disgust and anger emotions for augmenting hate speech data sample

In this paper we present a proposal to address the problem of the pricey and unreliable human annotation, which is important for detection of hate speech from the web contents. In particular, we propose to use the text that are produced from the suspended accounts in the aftermath of a hateful event as subtle and reliable source for hate speech prediction. The proposal was motivated after implementing emotion analysis on three sources of data sets: suspended, active and neutral ones, i.e. the first two sources of data sets contain hateful tweets from suspended accounts and active accounts, respectively, whereas the third source of data sets contain neutral tweets only. The emotion analysis indicated that the tweets from suspended accounts show more disgust, negative, fear and sadness emotions than the ones from active accounts, although tweets from both types of accounts might be annotated as hateful ones by human annotators. We train two Random Forest classifiers based on the semantic meaning of tweets respectively from suspended and active accounts, and evaluate the prediction accuracy of the two classifiers on unseen data. The results show that the classifier trained on the tweets from suspended accounts outperformed the one trained on the tweets from active accounts by 16% of overall F-score

Scalable local energy management systems

Commercial buildings have been identified as a major contributor of total global energy consumption. Mechanisms for collecting data about energy consumption patterns within buildings, and their subsequent analysis to support demand estimation (and reduction) remain important research challenges, which have already attracted considerable work. We propose a cloud based energy management system that enables such analysis to scale to both increasing data volumes and number of buildings. We consider both energy consumption and storage to support: (i) flattening the peak demand of commercial building(s); (ii) enable a “cost reduction” mode where the demand of a commercial building is reduced for those hours when a “triad peak” is expected; and (iii) enables a building manager to participate in grid balancing services market by means of demand response. The energy management system is deployed on a cloud infrastructure that adapts the number of computational resources needed to estimate potential demand, and to adaptively run multiple what-if scenarios to choose the most optimum configuration to reduce building energy demand

Spatial Stimuli Gradient Based Multifocus Image Fusion Using Multiple Sized Kernels

Multi-focus image fusion technique extracts the focused areas from all the source images and combines them into a new image which contains all focused objects. This paper proposes a spatial domain fusion scheme for multi-focus images by using multiple size kernels. Firstly, source images are pre-processed with a contrast enhancement step and then the soft and hard decision maps are generated by employing a sliding window technique using multiple sized kernels on the gradient images. Hard decision map selects the accurate focus information from the source images, whereas, the soft decision map selects the basic focus information and contains minimum falsely detected focused/unfocused regions. These decision maps are further processed to compute the final focus map. Gradient images are constructed through state-ofthe-art edge detection technique, spatial stimuli gradient sketch model, which computes the local stimuli from perceived brightness and hence enhances the essential structural and edge information. Detailed experiment results demonstrate that the proposed multi-focus image fusion algorithm performs better than the other well known state-of-the-art multifocus image fusion methods, in terms of subjective visual perception and objective quality evaluation metrics