Evaluating Competition Strategies for Generic Drug Industries Using Game Theory - A supplement to report “Scenario Planning as a Tool for Long Term Strategic Planning”

This report is a supplement to the project titled “Scenario Planning as a Tool for Long Term Strategic Planning - The Generics Drug Industry in the European Union.” The report will further evaluate the resultant scenarios and strategies build and recommended as part of the titled project mentioned above. Game theory perspectives will be used as a tool to analyse how economic agents (stakeholders of the pharmaceutical generic drugs industry) will react when what they do affects the actions of others. The report will evaluate hypothetical actions taken by generic drugs industry players and their outcomes/payoffs relative to the competitions. It will draw on strategic and extensive forms of games to identify how to act and how to think about your rival’s actions. What would be a more powerful in business strategy than this

Evaluating Competition Strategies for Generic Drug Industries Using Game Theory - A supplement to report “Scenario Planning as a Tool for Long Term Strategic Planning”

This report is a supplement to the project titled “Scenario Planning as a Tool for Long Term Strategic Planning - The Generics Drug Industry in the European Union.” The report will further evaluate the resultant scenarios and strategies build and recommended as part of the titled project mentioned above. Game theory perspectives will be used as a tool to analyse how economic agents (stakeholders of the pharmaceutical generic drugs industry) will react when what they do affects the actions of others. The report will evaluate hypothetical actions taken by generic drugs industry players and their outcomes/payoffs relative to the competitions. It will draw on strategic and extensive forms of games to identify how to act and how to think about your rival’s actions. What would be a more powerful in business strategy than this

Multilayer nanoparticle arrays for broad spectrum absorption enhancement in thin film solar cells

In this paper, we present a theoretical study on the absorption efficiency enhancement of a thin film amorphous Silicon (a-Si) photovoltaic cell over a broad spectrum of wavelengths using multiple nanoparticle arrays. The light absorption efficiency is enhanced in the lower wavelengths by a nanoparticle array on the surface and in the higher wavelengths by another nanoparticle array embedded in the active region. The efficiency at intermediate wavelengths is enhanced by the simultaneous resonance from both nanoparticle layers. We optimize this design by tuning the radius of particles in both arrays, the period of the array and the distance between the two arrays. The optimization results in a total quantum efficiency of 62.35% for a 300nm thick a-Si substrate.Comment: - Article Published in Optics Express on 7 Apr 2014. Link: http://www.opticsinfobase.org/oe/abstract.cfm?uri=oe-22-103-A80

Reduced Complexity Optimal Hard Decision Fusion under Neyman-Pearson Criterion

Distributed detection is an important part of many of the applications like wireless sensor networks, cooperative spectrum sensing in the cognitive radio network. Traditionally optimal non-randomized hard decision fusion rule under Neyman Pearson(NP) criterion is exponential in complexity. But recently [4] this was solved using dynamic programming. As mentioned in [4] that decision fusion problem exhibits semi-monotonic property in a special case. We use this property in our simulations and eventually apply dynamic programming to solve the problem with further reduced complexity. Further, we study the e�ect of using multiple antennas at FC with reduced complexity rule

Smart meter based profiling for load forecasting and demand side management in smart grids

The smart grid incorporates an integrated system of smart meters and communication networks that enable two-way communication between utilities and consumers. The granular information from smart meters can be used to improve the load forecast and influence consumer’s energy consumption patterns through demand side management (DSM). However, for localized studies of power system, using a large quantity of smart meter data having high level of noise preclude the use of computationally intensive techniques. Reduction of smart meter data to extract the load profiles and smoother load profiles at lower aggregation level (individual consumer or small groups of consumers) are highly desirable for use in linear techniques for power system studies. Therefore, this thesis addresses the challenges of smart meter data size, complexity, variability and volatility for efficient use in load forecasting and DSM. This thesis presents a novel clustering-based approach for analysis of smart meter data, aimed at more accurate and detailed load profiling, reduced profile complexity and improved load forecast accuracy and DSM solutions. The approach uses an innovative clustering algorithm to reduce the data size by proposing new cluster validity indices. The extremely volatile profiles having high levels of noise and complexity are linearized using Taylor series linearization process to alleviate the non-linearity and complexity of profiles. Finally, particle swarm optimization is applied for energy optimization in linearized profiles. The approach is demonstrated on Irish smart meter dataset and simulated PV data, to achieve improved load forecast accuracy using artificial neural network and improved DSM solutions using linear optimization with reduced computational burden. Investigations suggest that proposed clustering algorithm can produce clusters with high intra-cluster pattern similarity as a result of the introduction of new stopping criteria specifically tailored for load forecasting applications. A comparison between the proposed alternative profiles and raw profiles further suggests that the alternative profiles guide the underlying energy consumption with reduced complexity making them computationally efficient. Use of the alternative profiles suggests that the load forecasting accuracy can potentially be higher compared to raw profiles. The alternative profiles in combination with the novel cluster selection approach provide higher peak reduction by shifting the load from peak hours to off-peak hours and higher monetary benefits for the participating consumers. The proposed clustering algorithm and the alternative profiles represent an advancement of the conventional load profiling approach, benefiting system operators through more accurate forecasting and efficient DSM. The novel mathematical framework suggested in this thesis provides an advancement to the new knowledge in the area of smart metering and smart power grids

A study of English teachers and students’ perception about the differences between annual and semester system of education at postgraduate level in Mardan

AbstractThis research study tried to seek the perception of English teachers and students’ about the differences between Annual and Semester system in terms of students’ learning strategies at postgraduate level. A public sector university in Mardan (established in February 2009) provided the researchers a population who were new to Semester system and who had been seeking education in Annual system before joining it. In order to achieve the objective of the study, a questionnaire was distributed among a randomly selected 120 students having experience of both the educational systems, and interviews with 10 teachers were conducted to record their perception towards both systems of education.The analysis of the data got from both the tools showed that there was found a significant difference between Annual and Semester system in terms of students learning strategies. In Annual system students used to get ample time to master the target subjects, whereas in Semester system, the students had to synthesize the subjects and were not only made to undergo rigorous evaluation in terms of both intellectual and emotional growth

A Millimetre Wave Embroidered Antennas

WLAN and Body Area Networks(BAN) are rapidly advancing as high data rate wireless commu- nication systems using Ulta Wide Band(UWB) spectrum. The unlicensed UWB spectrum o�ers 7 GHz wide bandwidth which ranges over 57 to 64 GHz. In this UWB communication systems Antenna design plays a crucial role for signal transmission and reception. However Antenna de- sign at UWB spectrum is more challenging than narrow band design Beam forming Antenna arrays play an important role at these frequencies. In this work A novel embroidery type dipole antennas and dipole arrays are proposed for Body area networks. The proposed antennas are designed and analyzed using High Frequency Structure Simulator(HFSS)