Analytical Investigation of Mobile NFC Adaption with SWOT-AHP Approach: A Case of Italian Telecom

The purpose of this study is to appraise the critical factors in near field communication (NFC) adoption process and to utilize findings in order to support launching NFC implementations in Italy, by means of applying a combination of SWOT and AHP approaches. Hence, a set of twenty SWOT factors is identified qualitatively through extended interviews with telecommunication experts as well as exploratory studies on case which are supported by quantitative investigation through pair-wise comparisons matrices as an application of AHP approach. However, this combined methodology enables us to describe NFC adoption process, providing guidance to clarify the critical factors during adoption process. As the first application of joint SWOT and AHP approaches in telecommunication networks, managerial perceptions are promising either for policy makers concerning NFC or further academic researches on NFC application and full scale deployment in market

Sensitivity analysis of dynamic cell formation problem through meta-heuristic

In spite of many researches in literature investigating dynamic of cell formation (CF) problem, further research needs to be elaborated to assay hidden aspects of cellular manufacturing system (CMS), due to inherent complexity and uncertainty on optimizing this problem. In this paper, sensitivity analysis of modified self-adaptive differential evolution (MSDE) algorithm is proposed for basic parameters of CF problem, considering to the graphical representation supported by statistical analysis. Hence, a dynamic integer model of CF problem is first presented as the NP-hard problem. Then, the two basic test CF problems are introduced thereby the performance of MSDE algorithm assessed by diverse problems sizes through 140 runs from aspects of the average runtime of algorithm and the best local optimum objective function. Finally, statistical analysis is implemented on behavior of objective function values in order to validate our computational results graphically as well as statistically, giving some insights related to importance of CF parameters on designing CMS

Optimization of accurate estimation of single diode solar photovoltaic parameters and extraction of maximum power point under different conditions

Introduction. With the snowballing requirement of renewable resources of energy, solar energy has been an area of key concern to the increasing demand for electricity. Solar photovoltaic has gotten a considerable amount of consideration from researchers in recent years. Purpose. For generating nearly realistic curves for the solar cell model it is needed to estimate unknown parameters with utmost precision. The five unknown parameters include diode-ideality factor, shunt-resistance, photon-current, diode dark saturation current, and series-resistance. Novelty. The proposed research method hybridizes flower pollination algorithm with least square method to better estimate the unknown parameters, and produce more realistic curves. Methodology. The proposed method shows many promising results that are more realistic in nature, as compared to other methods. Shunt-resistance and series-resistance are considered and diode constant is not neglected in this approach that previously has been in practice. The values of series-resistance and diode-ideality factor are found using flower pollination algorithm while shunt-resistance, diode dark saturation current and photon-current are found through least square method. Results. The combination of these techniques has achieved better results compared to other techniques. The simulation studies are carried on MATLAB/Simulink.Вступ. З огляду на величезну потребу у відновлюваних енергетичних ресурсах, сонячна енергія стала ключовою сферою розв’язання проблеми зростання попиту на електроенергію. За останні роки сонячна фотоелектрична техніка отримала значну увагу з боку дослідників. Мета. Для створення майже реалістичних кривих для моделі сонячних батарей необхідно оцінити невідомі параметри з максимальною точністю. П'ять невідомих параметрів включають коефіцієнт ідеальності діодів, опір шунту, фотонний струм, струм темного насичення діодів і послідовний опір. Новизна. Запропонований метод дослідження поєднує алгоритм запилення квітів із методом найменших квадратів для кращої оцінки невідомих параметрів та отримання більш реалістичних кривих. Методологія. Запропонований метод демонструє багато перспективних результатів, які є більш реалістичними за своєю природою, порівняно з іншими методами. Розглянуто опір шунта і послідовний опір, і в цьому підході, який раніше застосовувався на практиці, не нехтують постійною діода. Значення послідовного опору та коефіцієнта ідеальності діодів визначаються за допомогою алгоритму запилення квіток, тоді як опір шунту, струм темного насичення діодів і фотонний струм - методом найменших квадратів. Результати. Поєднання цих методів забезпечило кращі результати у порівнянні з іншими методами. Моделювання проводиться на MATLAB/Simulink

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

A regulatory governance perspective on health technology assessment (HTA) in France: the contextual mediation of common functional pressures

The new regulatory governance perspective has introduced several insights to the study of health technology assessment (HTA): it has broadened the scope for the analysis of HTA; it has provided a more sophisticated account of national diversity and the potential for cross-border policy learning; and, it has dissolved the distinction between HTA assessment and appraisal processes. In this paper, we undertake a qualitative study of the French process for HTA with a view to introducing a fourth insight: that the emergence and continuing function of national agencies for HTA follows a broadly evolutionary pattern in which contextual factors play an important mediating role. We demonstrate that the French process for HTA is characterised by distinctive institutions, processes and evidential requirements. Consistent with the mediating role of this divergent policy context, we argue that even initiatives for the harmonisation of national approaches to HTA are likely to meet with divergent national policy responses

An improved search ability of particle swarm optimization algorithm for tracking maximum power point under shading conditions

Introduction. Extracting maximum possible power from solar energy is a hot topic of the day as other sources have become costly and lead to pollution. Problem. Dependency on sunlight for power generation makes it unfeasible to extract maximum power. Environmental conditions like shading, partial shading and weak shading are the major aspect due to which the output of photovoltaic systems is greatly affected. Partial shading is the most known issue. Goal. There have been many proposed techniques and algorithms to extract maximum output from solar resources by use of photovoltaic arrays but every technique has had some shortcomings that couldn’t serve the complete purpose. Methodology. Nature inspired algorithms have proven to be good to search global maximum in a partially shaded multipeak curve which includes particle swarm optimization, artificial bee colony algorithm, and flower pollination algorithm. Methods. Particle swarm optimization algorithm is best among these in finding global peaks with less oscillation around maximum power point, less complexity, and easy to implement nature. Particle swarm optimization algorithm has the disadvantage of having a long computational time and converging speed, particularly under strong shading conditions. Originality. In this paper, an improved opposition based particle swarm optimization algorithm is proposed to track the global maximum power point of a solar photovoltaic module. Simulation studies have been carried out in MATLAB/Simulink R2018a. Practical value. Simulation studies have proved that opposition based particle swarm optimization algorithm is more efficient, less complex, more robust, and more flexible and has better convergence speed than particle swarm optimization algorithm, perturb and observe algorithm, hill climbing algorithm, and incremental conductance algorithm.Вступ. Отримання максимально можливої потужності із сонячної енергії є надзвичайно актуальним наразі, оскільки інші джерела енергії стали коштовними та призводять до забруднення. Проблема. Залежність від сонячного світла для вироблення електроенергії унеможливлює отримання максимальної потужності. Умови навколишнього середовища, такі як затінення, часткове затінення і слабке затінення, є основним аспектом, від якого сильно залежить потужність фотоелектричних систем. Часткове затінення – найвідоміша проблема. Мета. Було запропоновано багато методів та алгоритмів для отримання максимальної віддачі від сонячних ресурсів за допомогою фотоелектричних батарей, але кожен метод мав деякі недоліки, які не могли служити досягненню повної мети. Методологія. Алгоритми, натхненні природою, виявилися хорошими для пошуку глобального максимуму на частково затіненій кривій з багатьма піками, включаючи оптимізацію рою частинок, алгоритм штучної бджолиної колонії та алгоритм запилення квітів. Методи. Алгоритм оптимізації рою частинок найкраще підходить для пошуку глобальних піків з меншими коливаннями навколо точки максимальної потужності, меншою складністю та простотою реалізації. Алгоритм оптимізації рою частинок має недолік, що полягає у тривалому часі обчислень та швидкості збіжності, особливо в умовах сильного затінення. Оригінальність. У цій статті пропонується покращений алгоритм оптимізації рою частинок на основі протилежності для відстеження глобальної точки максимальної потужності сонячного фотоелектричного модуля. Розрахункові моделювання проводились у MATLAB/Simulink R2018a. Практична цінність. Дослідження за допомогою моделювання довели, що алгоритм оптимізації рою частинок на основі протилежності є більш ефективним, менш складним, надійнішим і гнучкішим і має кращу швидкість збіжності, ніж алгоритм оптимізації рою частинок, алгоритм збурення та спостереження, алгоритм сходження на пагорб та алгоритм інкрементальної провідності

Ethanol production from Sorghum bicolor using both separate and simultaneous saccharification and fermentation in batch and fed batch systems

The objective of this work was to find the best combination of different experimental conditions during pre-treatment, enzymatic saccharification, detoxification of inhibitors and fermentation of Sorghum bicolor straw for ethanol production. The optimization of pre-treatment using different concentrations of dilute sulfuric acid, various temperatures and residence times was achieved at 121°C, 1% acid concentration, 60 min residence time and enzyme saccharification using cellulase (celluclast 1.5 L) and -glucosidase (Novozyme 188) at 50°C and pH 4.8 for 48 h. Different surfactants were used in order toincrease the monomeric sugar during enzymatic hydrolysis and it has been observed that the addition of these surfactants contributed significantly in cellulosic conversion but no effect was shown onhemicellulosic hydrolysis. Fermentability of hydrolyzate was tested using Saccharomyces cerevisiae Ethanol RedTM and it was observed that simultaneous saccharification and fermentation (SSF) with bothbatch and fed batch resulted in better ethanol yield as compared to separate hydrolysis and fermentation (SHF). Detoxification of furan during SHF facilitated reduction in fermentation time from 96to 48 h. 98.5% theoretical yield was achieved in SHF with detoxification experiment attaining an ethanol concentration and yield of 23.01 gL-1 and 0.115 gg-1 DM respectively. During the SSF batch and fed batch fermentation, the maximum yields of ethanol per gram of dry matter were 0.1257 and 0.1332 g respectively

A Robust Regression-Based Stock Exchange Forecasting and Determination of Correlation between Stock Markets

Knowledge-based decision support systems for financial management are an important part of investment plans. Investors are avoiding investing in traditional investment areas such as banks due to low return on investment. The stock exchange is one of the major areas for investment presently. Various non-linear and complex factors affect the stock exchange. A robust stock exchange forecasting system remains an important need. From this line of research, we evaluate the performance of a regression-based model to check the robustness over large datasets. We also evaluate the effect of top stock exchange markets on each other. We evaluate our proposed model on the top 4 stock exchanges—New York, London, NASDAQ and Karachi stock exchange. We also evaluate our model on the top 3 companies—Apple, Microsoft, and Google. A huge (Big Data) historical data is gathered from Yahoo finance consisting of 20 years. Such huge data creates a Big Data problem. The performance of our system is evaluated on a 1-step, 6-step, and 12-step forecast. The experiments show that the proposed system produces excellent results. The results are presented in terms of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE)

Pulsatile blood flow through a constricted porous artery

In this paper a speculative study of an incompressible Newtonian blood flow through a constricted porous channel and pulsatile nature is inspected. Porosity parameter λ is incorporated in the momentum equation. Governing nonlinear differential equations are numerically evaluated by employing the perturbation method technique for a very small perturbation parameter ε 1 such that ε ≠ 0 and with conformable boundary conditions. Numerical results of the flow velocity profile and volumetric flow rate have been derived numerically and detailed graphical analysis for different physical parameters porosity, Reynolds number and stenosis has been presented. It is found that arterial blood velocity is dependent upon all of these factors and that the relationship of fluid velocity and flow is more complex and nonlinear than heretofore generally believe. Furthermore the flow velocity enhanced with Reynolds number, porosity parameter and at maximum position of the stenosis/constriction