Search results for: multipoint optimal minimum entropy deconvolution

Authors: Habib Ur Rahman Habib

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Renewable energy resources are being realized as suitable options in hybrid energy planning for on-grid and micro grid. In this paper, operation, planning and optimal design of on-grid distributed energy resources based hybrid system are investigated. The aim is to minimize the cost of the overall energy system keeping in view the environmental emission and minimum penetration of conventional energy resources. Seven grid connected different case studies including diesel only, diesel-renewable based, and renewable based only are designed to perform economic analysis, operational planning and emission. Sensitivity analysis is implemented to investigate the impact of different parameters on the performance of energy resources.

Keywords: data management, renewable energy, distributed energy, smart grid, micro-grid, modeling, energy planning, design optimization

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Authors: K. P. Shinde, M. V. Tien, H. Lin, H.-R. Park, S.-C.Yu, K. C. Chung, D.-H. Kim

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Magnetic refrigeration provides an attractive alternative cooling technology due to its potential advantages such as high cooling efficiency, environmental friendliness, low noise, and compactness over the conventional cooling techniques based on gas compression. Magnetocaloric effect (MCE) occurs by changes in entropy (ΔS) and temperature (ΔT) under external magnetic fields. We have been focused on identifying materials with large MCE in two temperature regimes, not only room temperature but also at cryogenic temperature for specific technological applications, such as space science and liquefaction of hydrogen in fuel industry. To date, the commonly used materials for cryogenic refrigeration are based on hydrated salts. In the present work, we report giant MCE in rare earth Ho2O3 nanopowder at cryogenic temperature. HoN nanoparticles with average size of 30 nm were prepared by using plasma arc discharge method with gas composition of N2/H2 (80%/20%). The prepared HoN was sintered in air atmosphere at 1200 oC for 24 hrs to convert it into oxide. Structural and morphological properties were studied by XRD and SEM. XRD confirms the pure phase and cubic crystal structure of Ho2O3 without any impurity within error range. It has been discovered that Holmium oxide exhibits giant MCE at low temperature without magnetic hysteresis loss with the second-order antiferromagnetic phase transition with Néels temperature around 2 K. The maximum entropy change was found to be 25.2 J/kgK at an applied field of 6 T.

Keywords: magnetocaloric effect, Ho₂O₃, magnetic entropy change, nanopowder

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Authors: Paul Stonaha, Mariia Romashchenko, Xaio Xu

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Magnetic shape memory alloys (MSMAs) are promising technological materials for a range of fields, from biomaterials to energy harvesting. We have performed inelastic neutron scattering on two powder samples of cobalt-based high-entropy MSMAs across a range of temperatures in an effort to compare calculations of thermodynamic properties (entropy, specific heat, etc.) to the measured ones. The measurements were correct for multiphonon scattering and multiple scattering contributions. We present herein the neutron-weighted vibrational density of states. Future work will utilize DFT calculations of the disordered lattice to correct for the neutron weighting and retrieve the true thermodynamical properties.

Keywords: neutron scattering, vibrational dynamics, computational physics, material science

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Authors: Hanan Alshaher, Jinsheng Xu

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Large amounts of data on the web can provide valuable information. For example, product reviews help business owners measure customer satisfaction. Sentiment analysis classifies texts into two polarities: positive and negative. This paper examines movie reviews and tweets using a new term weighting scheme, called one-over-sigma (1/sigma), on benchmark datasets for sentiment classification. The proposed method aims to improve the performance of sentiment classification. The results show that 1/sigma is more accurate than the popular term weighting schemes. In order to verify if the entropy reflects the discriminating power of terms, we report a comparison of entropy values for different term weighting schemes.

Keywords: 1/sigma, natural language processing, sentiment analysis, term weighting scheme, text classification

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Authors: Fuzhang Zhao

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Particle swarm optimization (PSO) is becoming one of the most important swarm intelligent paradigms for solving global optimization problems. Although some progress has been made to improve PSO algorithms over the last two decades, additional work is still needed to balance parameters to achieve better numerical properties of accuracy, efficiency, and stability. In the optimal PSO algorithm, the optimal weightings of (√ 5 − 1)/2 and (3 − √5)/2 are used for the cognitive factor and the social factor, respectively. By the same token, the same optimal weightings have been applied for intensification searches and diversification searches, respectively. Perturbation and constriction effects are optimally balanced. Simulations of the de Jong, the Rosenbrock, and the Griewank functions show that the optimal PSO algorithm indeed achieves better numerical properties and outperforms the canonical PSO algorithm.

Keywords: diversification search, intensification search, optimal weighting, particle swarm optimization

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Authors: Zhibo Zhao, Horst Hahn, Robert Kruk, Abhisheck Sarkar

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High entropy oxides (HEOs), based on the incorporation of multiple-principal cations into the crystal lattice, offer the possibility to explore previously inaccessible oxide compositions and unconventional properties. Here it is demonstrated that despite the chemical complexity of HEOs external stimuli, such as epitaxial strain, can selectively stabilize certain magneto-electronic states. Epitaxial (Co₀.₂Cr₀.₂Fe₀.₂Mn₀.₂Ni₀.₂)₃O₄-HEO thin films are grown in three different strain states: tensile, compressive, and relaxed. A unique coexistence of rocksalt and spinel-HEO phases, which are fully coherent with no detectable chemical segregation, is revealed by transmission electron microscopy. This dual-phase coexistence appears as a universal phenomenon in (Co₀.₂Cr₀.₂Fe₀.₂Mn₀.₂Ni₀.₂)₃O₄ epitaxial films. Prominent changes in the magnetic anisotropy and domain structure highlight the strain-induced bidirectional control of magnetic properties in HEOs. When the films are relaxed, their magnetization behavior is isotropic, similar to that of bulk materials. However, under tensile strain, the hardness of the out-of-plane (OOP) axis increases significantly. On the other hand, compressive straining results in an easy OOP magnetization and a maze-like magnetic domain structure, indicating perpendicular magnetic anisotropy. Generally, this study emphasizes the adaptability of the high entropy design strategy, which, when combined with coherent strain engineering, opens additional prospects for fine-tuning properties in oxides.

Keywords: high entropy oxides, thin film, strain tuning, perpendicular magnetic anistropy

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Authors: Fatima Achouri, Kaddour Chouicha, Abdelwahab Khatir

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It is clear that concrete of quality must be made with selected materials chosen in optimum proportions that remain after implementation, a minimum of voids in the material produced. The different methods of formulations what we use, are based for the most part on a granular curve which describes an ‘optimal granularity’. Many authors have engaged in fundamental research on granular arrangements. A comparison of mathematical models reproducing these granular arrangements with experimental measurements of compactness have to verify that the minimum porosity P according to the following extent granular exactly a power law. So the best compactness in the finite medium are obtained with power laws, such as Furnas, Fuller or Talbot, each preferring a particular setting between 0.20 and 0.50. These considerations converge on the assumption that the optimal granularity Caquot approximates by a power law. By analogy, it can then be analyzed as a granular structure of fractal-type since the properties that characterize the internal similarity fractal objects are reflected also by a power law. Optimized mixtures may be described as a series of installments falling granular stuff to better the tank on a regular hierarchical distribution which would give at different scales, by cascading effects, the same structure to the mix. Likely this model may be appropriate for the entire extent of the size distribution of the components, since the cement particles (and silica fume) correctly deflocculated, micrometric dimensions, to chippings sometimes several tens of millimeters. As part of this research, the aim is to give an illustration of the application of fractal analysis to characterize the granular concrete mixtures optimized for a so-called fractal dimension where different concretes were studying that we proved a fractal structure of their granular mixtures regardless of the method of formulation or the type of concrete.

Keywords: concrete formulation, fractal character, granular packing, method of formulation

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Authors: Denis Constantin Topa, Irina Gabriela Cara, Gerard Jitareanu

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Tillage is a fundamental soil practice with different soil disturbance intensities and unique implications in soil organic carbon, soil structure, and nutrient dynamics. However, the implication of tillage practice on soil organic carbon and soil health is complex and specific to the context. it study evaluated soil health status based on soil carbon sequestration and pools, soil aggregation, and nutrient use under two different tillage practices: conventional and minimum tillage. The results of our study are consistent with the hypothesis that, over time, minimum tillage typically boosts soil health in the 0-10 cm soil layer. Compared to the conventional practice (19.36 t C ha-1) there was a significant accumulation of soil organic carbon (0-30 cm) in the minimum-tillage practice (23.21 t C ha-1). Below 10 cm depth, the soil organic carbon stocks are close to that of the conventional layer (0-30 cm). Soil aggregate stability was improved under conservative tillage, due to soil carbon improvement which facilitated a greater volume of mesopores and micropores. Total nitrogen (TN), available potassium (AK) and phosphorus (AP) content in 0-10 cm depth under minimum-tillage practice were 26%, 6% and 32%, greater respectively, compared to the conventional treatment. Overall, the TN, AP and AK values decreased with depth within the soil profiles as a consequence of soil practice and minimum disturbance. The data show that minimum tillage is a sustainable and effective management practice that maintain soil health with soil carbon increase and efficient nutrient use.

Keywords: minimum tillage, conventional tillage, soil organic carbon, nutrients, soil aggregation, soil health

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Authors: Mallika Supa-Aksorn, Buaream Maneewan, Jiraporn Rojtinnakorn

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For animals, trypsin and chymotrypsin are the 2 proteases that play the important role in protein digestion and involving in growth rate. In many animals, these two enzymes are indicated as growth parameter by feed. Although enzyme assay at optimal condition is significant for its accuracy activity determination. There is less report of trypsin and chymotrypsin. Therefore, in this study, optimization of pH and temperature for trypsin (T) and chymotrypsin (C) in economic species; i.e. Nile tilapia (Oreochromis niloticus), sand goby (Oxyeleotoris marmoratus), giant freshwater prawn (Macrobachium rosenberchii) and native chicken (Gallus gallus) were investigated. Each enzyme of each species was assaying for its specific activity with variation of pH in range of 2-12 and temperature in range of 30-80 °C. It revealed that, for Nile tilapia, T had optimal condition at pH 9 and temperature 50-80 °C, whereas C had optimal condition at pH 8 and temperature 60 °C. For sand goby, T had optimal condition at pH 7 and temperature of 50 °C, while C had optimal condition at pH 11 and temperature of 70-75 °C. For juvenile freshwater prawn, T had optimal condition at pH 10-11 and temperature of 60-65 °C, C had optimal condition at pH 8 and temperature of 70°C. For starter native chicken, T has optimal condition at pH 7 and temperature of 70 °C, whereas C had o optimal condition at pH 8 and temperature of 60°C. This information of optimal conditions will be high valuable in further for, actual enzyme measurement of T and C activities that benefit for growth and feed analysis.

Keywords: trypsin, chymotrypsin, Oreochromis niloticus, Oxyeleotoris marmoratus, Macrobachium rosenberchii, Gallus gallus

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Authors: Sonia Boscenco, Zihan Wang, Euclides José de Mendoça Filho, João Paulo Hoppe, Irina Pokhvisneva, Geoffrey B.C. Hall, Michael J. Meaney, Patricia Pelufo Silveira

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Entropy can be described as a measure of the number of states of a system, and when used in the context of physiological time-based signals, it serves as a measure of complexity. In functional connectivity data, entropy can account for the moment-to-moment variability that is neglected in traditional functional magnetic resonance imaging (fMRI) analyses. While brain fMRI resting state entropy has been associated with some pathological conditions like schizophrenia, no investigations have explored the association between brain entropy measures and individual differences in child behavior in healthy children. We describe a novel exploratory approach to evaluate brain fMRI resting state data in two child cohorts, and MAVAN (N=54, 4.5 years, 48% males) and GUSTO (N = 206, 4.5 years, 48% males) and its associations to child behavior, that can be used in future research in the context of child exposures and long-term health. Following rs-fMRI data pre-processing and Shannon entropy calculation across 32 network regions of interest to acquire 496 unique functional connections, partial correlation coefficient analysis adjusted for sex was performed to identify associations between entropy data and Strengths and Difficulties questionnaire in MAVAN and Child Behavior Checklist domains in GUSTO. Significance was set at p < 0.01, and we found eight significant associations in GUSTO. Negative associations were found between two frontoparietal regions and cerebellar posterior and oppositional defiant problems, (r = -0.212, p = 0.006) and (r = -0.200, p = 0.009). Positive associations were identified between somatic complaints and four default mode connections: salience insula (r = 0.202, p < 0.01), dorsal attention intraparietal sulcus (r = 0.231, p = 0.003), language inferior frontal gyrus (r = 0.207, p = 0.008) and language posterior superior temporal gyrus (r = 0.210, p = 0.008). Positive associations were also found between insula and frontoparietal connection and attention deficit / hyperactivity problems (r = 0.200, p < 0.01), and insula – default mode connection and pervasive developmental problems (r = 0.210, p = 0.007). In MAVAN, ten significant associations were identified. Two positive associations were found = with prosocial scores: the salience prefrontal cortex and dorsal attention connection (r = 0.474, p = 0.005) and the salience supramarginal gyrus and dorsal attention intraparietal sulcus (r = 0.447, p = 0.008). The insula and prefrontal connection were negatively associated with peer problems (r = -0.437, p < 0.01). Conduct problems were negatively associated with six separate connections, the left salience insula and right salience insula (r = -0.449, p = 0.008), left salience insula and right salience supramarginal gyrus (r = -0.512, p = 0.002), the default mode and visual network (r = -0.444, p = 0.009), dorsal attention and language network (r = -0.490, p = 0.003), and default mode and posterior parietal cortex (r = -0.546, p = 0.001). Entropy measures of resting state functional connectivity can be used to identify individual differences in brain function that are correlated with variation in behavioral problems in healthy children. Further studies applying this marker into the context of environmental exposures are warranted.

Keywords: child behaviour, functional connectivity, imaging, Shannon entropy

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Authors: K. K. Saijaand, K. Prabhakaran Nair

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This study aims to determine change in optimal lo-cations of dual trailing-edge flaps for various thrust coefficient to solidity (Ct /σ) ratios of helicopter to achieve minimum hub vibration levels, with low penalty in terms of required trailing-edge flap control power. Polynomial response functions are used to approximate hub vibration and flap power objective functions. Single objective and multi-objective optimization is carried with the objective of minimizing hub vibration and flap power. The optimization results shows that the inboard flap location at low Ct/σ ratio move farther from the baseline value and at high Ct/σ ratio move towards the root of the blade for minimizing hub vibration.

Keywords: helicopter rotor, trailing-edge flap, thrust coefficient to solidity (Ct /σ) ratio, optimization

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Authors: Giorgi Methodishvili, Iuliia Methodishvili

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In this paper product development algorithm is used to determine the optimal management of financial resources in company. Aspects of financial management considered include put initial investment, examine all possible ways to solve the problem and the optimal rotation length of profit. The software of given problems is based using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: management, software, optimal, greedy algorithm, graph-diagram

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Authors: Anthony R. Hassan, Jacob A. Gbadeyan

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In this paper, the analysis of a reactive hydromagnetic Poiseuille fluid flow under each of sensitized, Arrhenius and bimolecular chemical kinetics through a channel in the presence of heat source is carried out. An exothermic reaction is assumed while the concentration of the material is neglected. Adomian Decomposition Method (ADM) together with Pade Approximation is used to obtain the solutions of the governing nonlinear non – dimensional differential equations. Effects of various physical parameters on the velocity and temperature fields of the fluid flow are investigated. The entropy generation analysis and the conditions for thermal criticality are also presented.

Keywords: chemical kinetics, entropy generation, thermal criticality, adomian decomposition method (ADM) and pade approximation

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Authors: V. Makis, L. Jafari

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In this paper, we develop an optimal Bayesian chart to control the expected number of defects per inspection unit in production processes with long production runs. We formulate this control problem in the optimal stopping framework. The objective is to determine the optimal stopping rule minimizing the long-run expected average cost per unit time considering partial information obtained from the process sampling at regular epochs. We prove the optimality of the control limit policy, i.e., the process is stopped and the search for assignable causes is initiated when the posterior probability that the process is out of control exceeds a control limit. An algorithm in the semi-Markov decision process framework is developed to calculate the optimal control limit and the corresponding average cost. Numerical examples are presented to illustrate the developed optimal control chart and to compare it with the traditional u-chart.

Keywords: Bayesian u-chart, economic design, optimal stopping, semi-Markov decision process, statistical process control

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Authors: Marzena Tokarewicz, Malgorzata Gradzka-Dahlke

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High-entropy alloys (HEAs) have gained significant attention due to their great potential as functional and structural materials. HEAs have very good mechanical properties (in particular, alloys based on CoCrNi). They also show the ability to maintain their strength at high temperatures, which is extremely important in some applications. AlCoCrFeNi alloy is one of the most studied high-entropy alloys. Scientists often study the effect of changing the aluminum content in this alloy because it causes significant changes in phase presence and microstructure and consequently affects its hardness, ductility, and other properties. Research conducted by the authors also investigates the effect of aluminium content in AlₓCoCrFeNi alloy on its microstructure and mechanical properties. AlₓCoCrFeNi alloys were prepared by vacuum induction melting. The obtained samples were examined for chemical composition, microstructure, and microhardness. The three-point bending method was carried out to determine the bending strength, bending modulus, and conventional bending yield strength. The obtained results confirm the influence of aluminum content on the properties of AlₓCoCrFeNi alloy. Most studies on AlₓCoCrFeNi alloy focus on the determination of mechanical properties in compression or tension, much less in bending. The achieved results provide valuable information on the bending properties of AlₓCoCrFeNi alloy and lead to interesting conclusions.

Keywords: bending properties, high-entropy alloys, induction melting, microstructure

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Authors: Viliam Makis, Farnoosh Naderkhani, Leila Jafari

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In this paper, we present a model and an algorithm for the calculation of the optimal control limit, average cost, sample size, and the sampling interval for an optimal Bayesian chart to control the proportion of defective items produced using a semi-Markov decision process approach. Traditional p-chart has been widely used for controlling the proportion of defectives in various kinds of production processes for many years. It is well known that traditional non-Bayesian charts are not optimal, but very few optimal Bayesian control charts have been developed in the literature, mostly considering finite horizon. The objective of this paper is to develop a fast computational algorithm to obtain the optimal parameters of a Bayesian p-chart. The decision problem is formulated in the partially observable framework and the developed algorithm is illustrated by a numerical example.

Keywords: Bayesian control chart, semi-Markov decision process, quality control, partially observable process

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Authors: H. Mokaddem, D. Miroud, N. Azouaou, F. Si-Ahmed, Z. Sadaoui

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The synthesis and characterization of activated carbon from local lignocellulosic precursor (Algerian alfa) was carried out for the removal of cationic dyes from aqueous solutions. The effect of the production variables such as impregnation chemical agents, impregnation ratio, activation temperature and activation time were investigated. Carbon obtained using the optimum conditions (CaCl2/ 1:1/ 500°C/2H) was characterized by various analytical techniques scanning electron microscopy (SEM), infrared spectroscopic analysis (FTIR) and zero-point-of-charge (pHpzc). Adsorption tests of methylene blue on the optimal activated carbon were conducted. The effects of contact time, amount of adsorbent, initial dye concentration and pH were studied. The adsorption equilibrium examined using Langmuir, Freundlich, Temkin and Redlich–Peterson models reveals that the Langmuir model is most appropriate to describe the adsorption process. The kinetics of MB sorption onto activated carbon follows the pseudo-second order rate expression. The examination of the thermodynamic analysis indicates that the adsorption process is spontaneous (ΔG ° < 0) and endothermic (ΔH ° > 0), the positive value of the standard entropy shows the affinity between the activated carbon and the dye. The present study showed that the produced optimal activated carbon prepared from Algerian alfa is an effective low-cost adsorbent and can be employed as alternative to commercial activated carbon for removal of MB dye from aqueous solution.

Keywords: activated carbon, adsorption, cationic dyes, Algerian alfa

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Authors: Minakshi Mainaji Sonawane, Bharti W. Gawali, Sudhir Mendhekar, Ramesh R. Manza

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People's lives and health are severely impacted by skin diseases. A new study proposes an effective method for identifying the different forms of skin diseases. Image denoising is a technique for improving image quality after it has been harmed by noise. The proposed technique is based on the usage of the wavelet transform. Wavelet transform is the best method for analyzing the image due to the ability to split the image into the sub-band, which has been used to estimate the noise ratio at the noisy image. According to experimental results, the proposed method presents the best values for MSE, PSNR, and Entropy for denoised images. we can found in Also, by using different types of wavelet transform filters is make the proposed approach can obtain the best results 23.13, 20.08, 50.7 for the image denoising process

Keywords: MSE, PSNR, entropy, Gaussian filter, DWT

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Authors: Hung-Shuo Wu, Huan-Chieh Chiu, Xiang-Yao Zheng, Yu-Cheng Yang, Chien-Hao Wang, Jen-Cheng Wang, Chwan-Lu Tseng, Joe-Air Jiang

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Dynamic Thermal Rating (DTR) provides crucial information by estimating the ampacity of transmission lines to improve power dispatching efficiency. To perform the DTR, it is necessary to install on-line thermal sensors to monitor conductor temperature and weather variables. A simple and intuitive strategy is to allocate a thermal sensor to every span of transmission lines, but the cost of sensors might be too high to bear. To deal with the cost issue, a thermal sensor placement problem must be solved. This research proposes and implements a hybrid algorithm which combines proper orthogonal decomposition (POD) with particle swarm optimization (PSO) methods. The proposed hybrid algorithm solves a multi-objective optimization problem that concludes the minimum number of sensors and the minimum error on conductor temperature, and the optimal sensor placement is determined simultaneously. The data of 345 kV transmission lines and the hourly weather data from the Taiwan Power Company and Central Weather Bureau (CWB), respectively, are used by the proposed method. The simulated results indicate that the number of sensors could be reduced using the optimal placement method proposed by the study and an acceptable error on conductor temperature could be achieved. This study provides power companies with a reliable reference for efficiently monitoring and managing their power grids.

Keywords: dynamic thermal rating, proper orthogonal decomposition, particle swarm optimization, sensor placement, smart grid

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Authors: A. Bari

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Integer programming is a branch of mathematical programming techniques in operations research in which some or all of the variables are required to be integer valued. Various cuts have been used to solve these problems. We have also developed cuts known as NAZ cut & A-T cut to solve the integer programming problems. These cuts are used to reduce the feasible region and then reaching the optimal solution in minimum number of steps.

Keywords: Integer Programming, NAZ cut, A-T cut, Cutting plane method

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Authors: Chur Hee Lee, Ju Sik Kwak, Seung Wan Kim

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This paper deals about economics and control of optimal placement of multi-terminal HVDC in Korea. Currently, No.1 and 2 HVDC are installed in Jeju and Mainland, Dangjin Godeok HVDC starts operation in 2020. Jeju No.3 HVDC also starts operation in 2022. HVDC systems in Korea are expanding. Also, super grid projects with China, Japan, and Russia are under consideration. In this situation, it is necessary to study how to install optimal HVDC in Korea and how to control it. After initializing the Optical Polwer Flow (OPF) procudure using lossless economic dispatch, grobal iteration will be set. And then, this will be formed as the Lagrangian function and linearizied. We will also analyze the advantages and disadvantages of each operation mode for optimal operating conditions of voltage and current complex HVDC in Korea.

Keywords: economics, HVDC, multi terminal, optimal

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Authors: Osei Kwabena Brefo

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The Germany takeover regulations mandate the minimum offer price to be set in accordance with section 31 (1) of the WpÜG. To safeguard this right of the shareholders, the WpÜG contains minimum price regulations that are based on the fundamental principle of equal treatment of shareholders. The minimum offer price is determined based on the maximum of either the highest price the bidder has offered other shareholders within the last six months (§ 4 WpÜG) or the three-month weighted average stock price (§ 5 Abs. 1 WpÜG) before the announcement of the offer. This study provides the first empirical evidence on differences between setting the minimum offer price based on the highest price paid to another shareholder within the last six months (“6MH offers”) as against the three-month weighted average stock before the announcement of the offer (“VWAP offers”) in terms of their impact on acquisition outcome. Using a sample of 358 acquisitions announced between 2004 and 2023, the study finds that the market and legal minimum premium in 6MH offers are significantly lower than three-month weighted average stock price offers. The study also employed Propensity Score Matching and endogenous Linear regression model to address for endogeneity concerns. Consistent with the Ordinary Least Square estimation, the study finds that after controlling for self-selection bias, market and legal premiums in 6MH offers are significantly lower than VWAP offers.

Keywords: mergers and acquisition, offer premium, minimum price regulation, takeover regulation

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Authors: Karthikeyan Kalirajan, Ashok Joshi

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An optimization problem is to setup to maximize the terminal kinetic energy of a maneuverable reentry vehicle (MaRV). The target location, the impact angle is given as constraints. The MaRV uses an explicit guidance law called Vector guidance. This law has two gains which are taken as decision variables. The problem is to find the optimal value of these gains which will result in minimum miss distance and impact angle error. Using a simple 3DOF non-rotating flat earth model and Lockheed martin HP-MARV as the reentry vehicle, the nature of solutions of the optimization problem is studied. This is achieved by carrying out a parametric study for a range of closed loop gain values and the corresponding impact angle error and the miss distance values are generated. The results show that there are well defined lower and upper bounds on the gains that result in near optimal terminal guidance solution. It is found from this study, that there exist common permissible regions (values of gains) where all constraints are met. Moreover, the permissible region lies between flat regions and hence the optimization algorithm has to be chosen carefully. It is also found that, only one of the gain values is independent and that the other dependent gain value is related through a simple straight-line expression. Moreover, to reduce the computational burden of finding the optimal value of two gains, a guidance law called Diveline guidance is discussed, which uses single gain. The derivation of the Diveline guidance law from Vector guidance law is discussed in this paper.

Keywords: Marv guidance, reentry trajectory, trajectory optimization, guidance gain selection

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Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi

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Distillation is one of the most important and utilized separation methods in the industrial practice. There are different ways to design of distillation column. One of these ways is short cut method. In short cut method, material balance and equilibrium are employed to calculate number of tray in distillation column. There are different methods that are classified in short cut method. One of these methods is Fenske-Underwood-Gilliland method. In this method, minimum reflux ratio should be calculated by underwood equation. Underwood proposed an equation that is useful for simple distillation column with one feed and one top and bottom product. In this study, underwood method is developed to predict minimum reflux ratio for column with one side stream upper than feed. The result of this model compared with McCabe-Thiele method. The result shows that proposed method able to calculate minimum reflux ratio with very small error.

Keywords: minimum reflux ratio, side stream, distillation, Underwood’s method

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Authors: Tomoaki Hashimoto

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Recently, optimal control problems subject to probabilistic constraints have attracted much attention in many research field. Although probabilistic constraints are generally intractable in optimization problems, several methods haven been proposed to deal with probabilistic constraints. In most methods, probabilistic constraints are transformed to deterministic constraints that are tractable in optimization problems. This paper examines a method for transforming probabilistic constraints into deterministic constraints for a class of probabilistic constrained optimal control problems.

Keywords: optimal control, stochastic systems, discrete-time systems, probabilistic constraints

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Authors: Songul Cinaroglu

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Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

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Authors: Liang Bai, Yandong Xiao, Haorang Wang, Songyang Lao

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The directedness of links is crucial to determine the controllability in complex networks. Even the edge directions can determine the controllability of complex networks. Obviously, for a given network, we wish to design its edge directions that make this network approach the optimal controllability. In this work, we firstly introduce two methods to enhance network by assigning edge directions. However, these two methods could not completely mitigate the negative effects of inaccessibility and dilations. Thus, to approach the optimal network controllability, the edge directions must mitigate the negative effects of inaccessibility and dilations as much as possible. Finally, we propose the edge direction for optimal controllability. The optimal method has been found to be successfully useful on real-world and synthetic networks.

Keywords: complex network, dynamics, network control, optimization

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Authors: Ashwini Gowda K. S, Archana M. R, Anjaneyappa V

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This paper presents pavement maintenance and management system (PMMS) to obtain optimum pavement maintenance and rehabilitation strategies and maintenance scheduling for a network using a multi-objective genetic algorithm (MOGA). Optimal pavement maintenance & rehabilitation strategy is to maximize the pavement condition index of the road section in a network with minimum maintenance and rehabilitation cost during the planning period. In this paper, NSGA-II is applied to perform maintenance optimization; this maintenance approach was expected to preserve and improve the existing condition of the highway network in a cost-effective way. The proposed PMMS is applied to a network that assessed pavement based on the pavement condition index (PCI). The minimum and maximum maintenance cost for a planning period of 20 years obtained from the non-dominated solution was found to be 5.190x10¹⁰ ₹ and 4.81x10¹⁰ ₹, respectively.

Keywords: genetic algorithm, maintenance and rehabilitation, optimization technique, pavement condition index

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Authors: Nattachote Rugthaicharoencheep

Abstract:

This paper presents a feeder reconfiguration problem in distribution systems. The objective is to minimize the system power loss and to improve bus voltage profile. The optimization problem is subjected to system constraints consisting of load-point voltage limits, radial configuration format, no load-point interruption, and feeder capability limits. A method based on genetic algorithm, a search algorithm based on the mechanics of natural selection and natural genetics, is proposed to determine the optimal pattern of configuration. The developed methodology is demonstrated by a 33-bus radial distribution system with distributed generations and feeder capacitors. The study results show that the optimal on/off patterns of the switches can be identified to give the minimum power loss while respecting all the constraints.

Keywords: network reconfiguration, distributed generation capacitor placement, loss reduction, genetic algorithm

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Authors: Amirreza Kosari, Hossein Maghsoudi, Malahat Givar

Abstract:

In this study, the three-dimensional optimal path planning of a flying robot for Terrain Following / Terrain Avoidance (TF/TA) purposes using Direct Collocation has been investigated. To this purpose, firstly, the appropriate equations of motion representing the flying robot translational movement have been described. The three-dimensional optimal path planning of the flying vehicle in terrain following/terrain avoidance maneuver is formulated as an optimal control problem. The terrain profile, as the main allowable height constraint has been modeled using Fractal Generation Method. The resulting optimal control problem is discretized by applying Direct Collocation numerical technique, and then transformed into a Nonlinear Programming Problem (NLP). The efficacy of the proposed method is demonstrated by extensive simulations, and in particular, it is verified that this approach could produce a solution satisfying almost all performance and environmental constraints encountering a low-level flying maneuver

Keywords: path planning, terrain following, optimal control, nonlinear programming

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