Political Instability and the August 1998 Ruble Crisis

The main objective of this study is to highlight the importance of political instability, defined as frequent changes in and of government, in undermining the Russian exchange rate based stabilization program of the 1990s. The empirical evidence supports the significance of political instability along with economic fundamentals in determining Russian real effective exchange rate and exchange market pressure, used as a proxy to the crisis.Currency crises, political instability

Natural convection in polyethylene glycol based molybdenum disulfide nanofluid with thermal radiation, chemical reaction and ramped wall temperature

© 2018 International Information and Engineering Technology Association. All Rights Reserved. The aim of this study is to investigate the unsteady magnetohydrodynamic (MHD) flow of Casson nanofluid over an infinite oscillating vertical plate with ramped wall temperature. The effects of porosity, thermal radiation and first order chemical reaction have been considered. Polyethylene glycol (PEG) is chosen as base fluid which contained molybdenum disulfide (MoS 2 ) nanoparticles. The Laplace transform technique is applied to the momentum, energy and concentration equations to obtain the closed form solutions. The obtained solutions are for both cases ramped and isothermal boundary conditions and compared graphically. From graphical analysis, it is observed that for isothermal plate, the magnitude of velocity, temperature and concentration profiles are greater than ramped wall temperature. Skin-friction, Nusselt number and Sherwood number are evaluated and presented in tabular forms. The effects of various embedded parameters on velocity, temperature and concentration profiles are discussed graphically

Non-cascaded short-term pumped-storage hydro-thermal scheduling using accelerated particle swarm optimization

© 2018 IEEE. This paper presents the implementation of a variant of the famous particle swarm optimization, known as Accelerated Particle Swarm Optimization (APSO), on a non-cascaded or a two-unit hydro-thermal system with consideration of hydal pumping in light loading intervals of hydro-thermal scheduling period. APSO is an easy to program and easy to implement variant of Particle Swarm Optimization (PSO) that has the ability to converge to a good approximate to global optimum within a few iterations. A standard pumped-storage hydrothermal scheduling problem, discussed in existing literature, is considered for the implementation of APSO. A comparison of this implementation is also given with the previously existing implementations of other algorithms

Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function

Introduction. Dynamic Economic Emission Dispatch is the extended version of the traditional economic emission dispatch problem in which ramp rate is taken into account for the limit of generators in a power network. Purpose. Dynamic Economic Emission Dispatch considered the treats of economy and emissions as competitive targets for optimal dispatch problems, and to reach a solution it requires some conflict resolution. Novelty. The decision-making method to solve the Dynamic Economic Emission Dispatch problem has a goal for each objective function, for this purpose, the multi-objective problem is transformed into single goal optimization by using the weighted sum method and then control/solve by Whale Optimization Algorithm. Methodology. This paper presents a newly developed metaheuristic technique based on Whale Optimization Algorithm to solve the Dynamic Economic Emission Dispatch problem. The main inspiration for this optimization technique is the fact that metaheuristic algorithms are becoming popular day by day because of their simplicity, no gradient information requirement, easily bypass local optima, and can be used for a variety of other problems. This algorithm includes all possible factors that will yield the minimum cost and emissions of a Dynamic Economic Emission Dispatch problem for the efficient operation of generators in a power network. The proposed approach performs well to perform in diverse problem and converge the solution to near best optimal solution. Results. The proposed strategy is validated by simulating on MATLAB® for 5 IEEE standard test system. Numerical results show the capabilities of the proposed algorithm to establish an optimal solution of the Dynamic Economic Emission Dispatch problem in a several runs. The proposed algorithm shows good performance over the recently proposed algorithms such as Multi-Objective Neural Network trained with Differential Evolution, Particle swarm optimization, evolutionary programming, simulated annealing, Pattern search, multi-objective differential evolution, and multi-objective hybrid differential evolution with simulated annealing technique.Вступ. Динамічна економна диспетчеризація викидів – це розширена версія традиційної задачі економної диспетчеризації викидів, в якій враховується коефіцієнт нарощування для межі генераторів в енергомережі. Призначення. Динамічна економна  диспетчеризація викидів розглядала питання економії та викидів як конкурентні цілі для оптимальних задач диспетчеризації, і для розв‘язання задачі потрібне певне вирішення конфліктів. Новизна. Метод прийняття рішень для розв‘язання задачі динамічної економної диспетчеризації викидів має мету для кожної цільової функції, для цього багатоцільова задача трансформується в оптимізацію однієї цілі за допомогою методу зваженої суми, а потім контролюється/розв‘язується за допомогою алгоритму оптимізації китів. Методологія. У цій роботі представлена нещодавно розроблена метаевристична методика, заснована на алгоритмі оптимізації китів для розв‘язання задачі динамічної економної диспетчеризації викидів. Основним натхненням для цієї методики оптимізації є той факт, що метаевристичні алгоритми стають популярними з кожним днем завдяки своїй простоті, відсутності вимог до інформації про градієнт, легкості обходу локальних оптимумів та можливості бути використаними для ряду інших задач. Цей алгоритм включає в себе всі можливі фактори, які забезпечать мінімальні вартість та викиди задачі динамічної економної диспетчеризації викидів для ефективної роботи генераторів в енергомережі. Запропонований підхід добре працює для розв‘язання задач і наближення рішення до найкращого оптимального. Результати. Запропонована стратегія перевірена шляхом моделювання на MATLAB® для 5 стандартних тестових систем IEEE. Чисельні результати демонструють можливості запропонованого алгоритму для встановлення оптимального рішення задачі динамічної економної диспетчеризації викидів за кілька прогонів. Запропонований алгоритм демонструє хорошу ефективність порівняно з нещодавно запропонованими алгоритмами, такими як багатоцільова нейронна мережа, навчена з використанням диференціальної еволюції, оптимізація рою частинок, еволюційне програмування, імітаційний відпал, пошук за шаблоном, багатоцільова диференціальна еволюція та багатоцільова гібридна диференціальна еволюція з імітаційним методом відпалу

Monetary Targeting in Pakistan: A Skeptical Note

The objective of this study is to evaluate monetary targeting strategy in Pakistan by testing the Quantity Theory of Money and the income velocity of money stated by Monetarists and the endogenous money hypothesis postulated by the Post Keynesians. Our tests on the Pakistani data covering about thirty years reveal that the quantity theory is an inadequate explanation of inflation, income velocity of money is unstable, and money is endogenous. These results suggest rethinking on monetary targeting strategy in Pakistan

Impact of Fungiform Papillae Count on Taste Perception and Different Methods of Taste Assessment and their Clinical Applications: A comprehensive review

Fungiform papillae are raised lingual structures which contain taste buds and thus play an important role in taste perception. These structures vary in number due to their relative sensitivity to a range of systemic and local factors which affect the dorsum of the tongue. Taste sensation can be measured using both chemical and electrical methods; however, the number of fungiform papillae has a direct effect on chemogustometric and electrogustometric values during evaluation. This review provides a general overview of fungiform papillae, their quantification methods and the various factors which may affect these structures. In addition, numerous methods of recording taste sensation and their clinical applications are highlighted.Keywords: Sensation; Taste; Taste Perception; Tongue; Taste Buds; Investigative Techniques

Container shipment demand forecasting in the Australian shipping industry: A case study of asia–oceania trade lane

Demand forecasting has a pivotal role in making informed business decisions by predicting future sales using historical data. Traditionally, demand forecasting has been widely used in the management of production, staffing and warehousing for sales and marketing data. However, the use of demand forecasting has little been studied in the container shipping industry. Improved visibility into the demand for container shipments has been a long-held objective of industry stakeholders. This paper addresses the shortcomings of both short-term and long-term shipment demand forecasting for the Australian container shipping industry. In this study, we compare three forecasting models, namely, the seasonal auto-regressive integrated moving average (SARIMA), Holt–Winters’ seasonal method and Facebook’s Prophet, to find the best fitting model for short-term and long-term import demand forecasting in the Australian shipping industry. Demand data from three years, i.e., 2016–2018, is used for the Asia–Oceania trade lane. The mean absolute percentage error (MAPE), root mean squared error (RMSE) and 2-fold walk-forward cross-validation are used for the model evalua-tion. The experiment results observed from the selected metrics suggest that Prophet outperforms the other models in its comparison for container shipment demand forecasting