குளோபல் ஜர்னல் ஆஃப் டெக்னாலஜி அண்ட் ஆப்டிமைசேஷன்

Mobile telecommunications’ sector is one of the fastest developing sectors in the world. Both high usage and demand gather to show how this sector is increasing especially with the energy resources it requires to operate. Mobile telecommunications has a direct effect on the environment related to the usage (users’ behavior, network’s interaction, power and energy saving, etc.). The main objectives of this research are to assess the consumers’ awareness and willingness to pay in order to go green in mobile telecommunication, while measuring the attitudes, perceived behavioral control, and subjective norms that affect the consumers’ intentions to go green in mobile telecommunications. The theory of planned behavior is used as the conceptual framework to assess the consumers’ intention and behavior towards green telecommunication. A Questionnaire on the theory of planned behavior was built, translated and face to face self-administered interviews were conducted four areas in Lebanon (Jdeideh, Haret Hreik, Roueis, and Maameltein) that were selected based on the traffic profile (voice and data), number of distinct users, locations, population, and workplaces. Results show that most of the Lebanese consumers are aware of the negative environmental and health impacts of telecommunications. Result show that most of the Lebanese consumers are ready to pay higher mobile fees if green telecom systems are to be applied in Lebanon; and that variables such as attitudes, perceived behavioral control, and subjective norms affect the consumers’ intention to go green in mobile telecommunications.

In this paper recently proposed procedure for purposeful model parameters genesis, originally developed for simple genetic algorithm, has been validated for multi-population genetic algorithm when it is applied for the purposes of parameter identification of S. cerevisiae fed-batch cultivation. Proposed procedure aims to improve the algorithm effectiveness in respect to the convergence time and model accuracy treating intervals of variations of model parameters. Obtained results after the procedure application show more than 12% improvement of multi-population genetic algorithm convergence time while saving and even slightly meliorating the model accuracy.

This paper proposes a self-organizing hierarchical particle swarm optimization (SOHPSO) with time-varying acceleration coefficients (TVAC) for solving security constrained optimal power flow (SCOPF) problem. The SCOPF is to minimize a total generation cost while satisfying generator operational constraints and network security constraints in which the minimum severity index is used to alleviate line loading. The proposed SOHPSO-TVAC re-initializes particle velocities whenever the population stagnates at local optima during the search and TVAC is used to enhance convergence to the global optimum solution. Test results on the IEEE 30 and 118 bus systems indicate that the proposed SCOPF renders a lower total generation cost in a faster convergence rate than the other heuristic methods, which is favorable for online implementation.

The present review article makes an attempt to comprehensively review various aspects of biomass energy sources, environment and sustainable development. This includes all the biomass energy technologies, energy efficiency systems, energy conservation scenarios, energy savings and other mitigation measures necessary to reduce emissions globally. An attempt has been made to review the current literature regarding the ecological, social, cultural and economic impacts of biomass technology. In the present article, an attempt has also been made to present an overview of present and future use of biomass as an industrial feedstock for production of fuels, chemicals and other materials. We may conclude from the review paper that biomass technology must be encouraged, promoted, invested, implemented, and demonstrated, not only in urban areas but also in remote rural areas.