Firm-Level Determinants Of Export Performance

Contribution of small and medium enterprises (SMEs) in global export is becoming significant but still a large number of these are unable to outperform in international market.  In this study, we have identified and classified the firm-level controllable determinants of export performance.  Based upon a comprehensive and systematic literature study we finally developed a synthesized model which may provide a broader understanding of the export behavior of the SMEs to enhance their export performance.  Many information sources have been explored to collect the relevant literature.  The determinants found from the literature are classified into firm’s characteristics, management characteristics, and export marketing strategic capabilities. In this paper, we have proposed a synthesized model for the researchers who are interested to investigate the issue further (i.e. about SMEs export performance determinants)

Misperception About Epilepsy Among Common Public in Balochistan

ABSTRACT Background and Objective: Epilepsy is a treatable chronic neurological illness that is frequently associated with supernatural activity. The objectives of this study were to determine common myths and misperception about epilepsy by analysing a comprehensive panel of variables in our local population. Methods: We conducted a face-to-face questionnaire interview survey in three different shopping malls. One thousand people were randomly enrolled in this cross-sectional study at Quetta, Baluchistan, during the period of 21 august 2021 to 30 august 2021. Results: A total of 1000 people were interviewed; among them 220(22%) were male and 780(78%) were female. Individuals between the age of 20 years and above were included in the study. Nine-hundred-eighty (98%) respondents had heard about epilepsy. Out of thousand people 419 (41.9%) thought that epilepsy was a brain disease, 488 (48.8%) responded that it was a ghost attack. Twenty-three (2.3%) believed it to be psychosis. The aspects of knowledge tested were on causes, types, and management of epilepsy. Forty-nine (4.9%) people believed that epilepsy was due to head trauma, 488 (48.8%) said it’s ghost attack, 67 (6.7%) said it’s because of evil eye, and 293 (29.3%) peoples believed that epilepsy was caused by black magic. Nine-hundred-twenty-eight (92.8%) people believed that home remedies such as sniffing shoes were effective in epilepsy. Conclusion: This study revealed a lack of awareness about epilepsy in Balochistan, as well as the prevalence of both negative and favourable attitudes about epilepsy. This result was much surprising because in this era of modern medicine and technology, still superstitious beliefs prevail among large population. The study also emphasized to increase public awareness and epilepsy education initiatives to change public opinions and promote the use of standard epileptic treatment

Joint Optimization of Interference and Cost in Cognitive Radio Heterogeneous Network Using Fuzzy Logic Powered Ants

The advent of emerging wireless technologies has increased the demand of spectrum resources. On the other hand, present spectrum assignment is fixed and underutilized. Cognitive radio (CR) provides good solution to spectrum scarcity problem to accommodate new wireless applications. The network selection is an important mechanism in cognitive radio heterogeneous network (CRHN) to provide optimal Quality of Service (QoS) to both Primary Users (PUs) and Secondary Users (SUs). The aim of this work is to provide optimal QoS to SUs by appropriate network selection and channel assignment. The proposed FLACSA selects the best network while maximizing the data rate and minimizing the interference and cost simultaneously. Simulation results show the attractive performance of our proposed algorithm

Learning Local Heuristics for Search-Based Navigation Planning

Graph search planning algorithms for navigation typically rely heavily on heuristics to efficiently plan paths. As a result, while such approaches require no training phase and can directly plan long horizon paths, they often require careful hand designing of informative heuristic functions. Recent works have started bypassing hand designed heuristics by using machine learning to learn heuristic functions that guide the search algorithm. While these methods can learn complex heuristic functions from raw input, they i) require significant training and ii) do not generalize well to new maps and longer horizon paths. Our contribution is showing that instead of learning a global heuristic estimate, we can define and learn local heuristics which results in a significantly smaller learning problem and improves generalization. We show that using such local heuristics can reduce node expansions by 2-20x while maintaining bounded suboptimality, are easy to train, and generalize to new maps & long horizon plans

Requirement change management in agile offshore development (RCMAOD)

Requirements get changed during the course of development. It is almost impossible to stop the requirements from changing. Different software development approaches tackle changing requirement in different ways. Unlike Waterfall or document driven approaches of software development, agile methodologies welcome change during the course of software development but at the same time manage the changes in a systematic manner. This paper discusses the offshore development model with respect to agile requirement change management. An important condition for agile approach is to have continuous collaboration and relationship with the customer so that requirements could be elicited as well as verified regularly. But in offshore environment, this approach can't be applied due to presence of the client on geographically distant location. Therefore this paper also highlights some of the elicitation techniques, tools and methodologies that can be applied in offshore development model in such a way to minimize lack of face to face interactions among different stakeholders of application while working with Agile