Search results for: ParticleSwarm Optimization (PSO).

Authors: G. Ramana Murthy, C. Senthilpari, P. Velrajkumar, Lim Tien Sze

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In this paper, a design methodology to implement low-power and high-speed 2nd order recursive digital Infinite Impulse Response (IIR) filter has been proposed. Since IIR filters suffer from a large number of constant multiplications, the proposed method replaces the constant multiplications by using addition/subtraction and shift operations. The proposed new 6T adder cell is used as the Carry-Save Adder (CSA) to implement addition/subtraction operations in the design of recursive section IIR filter to reduce the propagation delay. Furthermore, high-level algorithms designed for the optimization of the number of CSA blocks are used to reduce the complexity of the IIR filter. The DSCH3 tool is used to generate the schematic of the proposed 6T CSA based shift-adds architecture design and it is analyzed by using Microwind CAD tool to synthesize low-complexity and high-speed IIR filters. The proposed design outperforms in terms of power, propagation delay, area and throughput when compared with MUX-12T, MCIT-7T based CSA adder filter design. It is observed from the experimental results that the proposed 6T based design method can find better IIR filter designs in terms of power and delay than those obtained by using efficient general multipliers.

Keywords: CSA Full Adder, Delay unit, IIR filter, Low-Power, PDP, Parametric Analysis, Propagation Delay, Throughput, VLSI.

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Authors: Karan Vishavjit, Aakash Lakra, Shafaq Khan

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The COVID-19 pandemic has pushed healthcare professionals to use big data analytics as a vital tool for tracking and evaluating the effects of contagious viruses. To effectively analyse huge datasets, efficient NoSQL databases are needed. The analysis of post-COVID-19 health and well-being outcomes and the evaluation of the effectiveness of government efforts during the pandemic is made possible by this research’s integration of several datasets, which cuts down on query processing time and creates predictive visual artifacts. We recommend applying sharding and indexing technologies to improve query effectiveness and scalability as the dataset expands. Effective data retrieval and analysis are made possible by spreading the datasets into a sharded database and doing indexing on individual shards. Analysis of connections between governmental activities, poverty levels, and post-pandemic wellbeing is the key goal. We want to evaluate the effectiveness of governmental initiatives to improve health and lower poverty levels. We will do this by utilising advanced data analysis and visualisations. The findings provide relevant data that support the advancement of UN sustainable objectives, future pandemic preparation, and evidence-based decision-making. This study shows how Big Data and NoSQL databases may be used to address problems with global health.

Keywords: COVID-19, big data, data analysis, indexing, NoSQL, sharding, scalability, poverty.

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Authors: Fl. Loury, P. Sablonière

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In this paper a stochastic scenario-based model predictive control applied to molten salt storage systems in concentrated solar tower power plant is presented. The main goal of this study is to build up a tool to analyze current and expected future resources for evaluating the weekly power to be advertised on electricity secondary market. This tool will allow plant operator to maximize profits while hedging the impact on the system of stochastic variables such as resources or sunlight shortage.

Solving the problem first requires a mixed logic dynamic modeling of the plant. The two stochastic variables, respectively the sunlight incoming energy and electricity demands from secondary market, are modeled by least square regression. Robustness is achieved by drawing a certain number of random variables realizations and applying the most restrictive one to the system. This scenario approach control technique provides the plant operator a confidence interval containing a given percentage of possible stochastic variable realizations in such a way that robust control is always achieved within its bounds. The results obtained from many trajectory simulations show the existence of a ‘’reliable’’ interval, which experimentally confirms the algorithm robustness.

Keywords: Molten Salt Storage System, Concentrated Solar Tower Power Plant, Robust Stochastic Model Predictive Control.

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Authors: Vladyslav Povoroznyuk, Oksana Ivanyk, Nataliia Dzerovych

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In the diagnostics of osteoporosis, the gold standard is considered to be bone mineral density; however, X-ray densitometry is not an accurate indicator of osteoporotic fracture risk under all circumstances. In this regard, the search for new methods that could determine the indicators not only of the mineral density, but of the bone tissue quality, is a logical step for diagnostic optimization. One of these methods is the evaluation of trabecular bone quality. The aim of this study was to examine the quality and mineral density of spine bone tissue, femoral neck, and body composition of women depending on the duration of the postmenopausal period, to determine the correlation of body fat with indicators of bone mineral density and quality. The study examined 179 women in premenopausal and postmenopausal periods. The patients were divided into the following groups: Women in the premenopausal period and women in the postmenopausal period at various stages (early, middle, late postmenopause). A general examination and study of the above parameters were conducted with General Electric X-ray densitometer. The results show that bone quality and mineral density probably deteriorate with advancing of postmenopausal period. Total fat and lean mass ratio is not likely to change with age. In the middle and late postmenopausal periods, the bone tissue mineral density of the spine and femoral neck increases along with total fat mass.

Keywords: Osteoporosis, bone tissue mineral density, bone quality, fat mass, lean mass, postmenopausal osteoporosis.

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Authors: Ghada Badr, Manar Hosny, Nuha Bintayyash, Eman Albilali, Souad Larabi Marie-Sainte

Abstract:

The median problem is significantly applied to derive the most reasonable rearrangement phylogenetic tree for many species. More specifically, the problem is concerned with finding a permutation that minimizes the sum of distances between itself and a set of three signed permutations. Genomes with equal number of genes but different order can be represented as permutations. In this paper, an algorithm, namely BeamGA median, is proposed that combines a heuristic search approach (local beam) as an initialization step to generate a number of solutions, and then a Genetic Algorithm (GA) is applied in order to refine the solutions, aiming to achieve a better median with the smallest possible reversal distance from the three original permutations. In this approach, any genome rearrangement distance can be applied. In this paper, we use the reversal distance. To the best of our knowledge, the proposed approach was not applied before for solving the median problem. Our approach considers true biological evolution scenario by applying the concept of common intervals during the GA optimization process. This allows us to imitate a true biological behavior and enhance genetic approach time convergence. We were able to handle permutations with a large number of genes, within an acceptable time performance and with same or better accuracy as compared to existing algorithms.

Keywords: Median problem, phylogenetic tree, permutation, genetic algorithm, beam search, genome rearrangement distance.

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Authors: A. Aravind, M. Vetrivel, P. Abhimanyu, C. A. Akaash Emmanuel Raj, K. Sundararaj, V. R. S. Kumar

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The choice of high-speed, low budget hatchback car with diversified options is increasing for meeting the new generation buyers trend. This paper is aimed to augment the current speed of the hatchback cars through the aerodynamic drag reduction technique. The inverted airfoils are facilitated at the bottom of the car for generating the downward force for negating the lift while increasing the current speed range for achieving a better road performance. The numerical simulations have been carried out using a 2D steady pressure-based    k-ɛ realizable model with enhanced wall treatment. In our numerical studies, Reynolds-averaged Navier-Stokes model and its code of solution are used. The code is calibrated and validated using the exact solution of the 2D boundary layer displacement thickness at the Sanal flow choking condition for adiabatic flows. We observed through the parametric analytical studies that the inverted airfoil integrated with the bottom surface at various predesigned locations of Hatchback cars can improve its overall aerodynamic efficiency through drag reduction, which obviously decreases the fuel consumption significantly and ensure an optimum road performance lucratively with maximum permissible speed within the framework of the manufactures constraints.

Keywords: Aerodynamics of commercial cars, downward force, hatchback car, inverted airfoil.

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Authors: Javier Roca, Etienne Pugnaghi, Gaëtan Libert

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We introduce an extended resource leveling model that abstracts real life projects that consider specific work ranges for each resource. Contrary to traditional resource leveling problems this model considers scarce resources and multiple objectives: the minimization of the project makespan and the leveling of each resource usage over time. We formulate this model as a multiobjective optimization problem and we propose a multiobjective genetic algorithm-based solver to optimize it. This solver consists in a two-stage process: a main stage where we obtain non-dominated solutions for all the objectives, and a postprocessing stage where we seek to specifically improve the resource leveling of these solutions. We propose an intelligent encoding for the solver that allows including domain specific knowledge in the solving mechanism. The chosen encoding proves to be effective to solve leveling problems with scarce resources and multiple objectives. The outcome of the proposed solvers represent optimized trade-offs (alternatives) that can be later evaluated by a decision maker, this multi-solution approach represents an advantage over the traditional single solution approach. We compare the proposed solver with state-of-art resource leveling methods and we report competitive and performing results.

Keywords: Intelligent problem encoding, multiobjective decision making, evolutionary computing, RCPSP, resource leveling.

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Authors: Jerin John, Subanesh Shyam R., Aravind Kumar T. R., Naveen N., Vignesh R., Krishna Ganesh B, Sanal Kumar V. R.

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Numerical studies have been carried out using a validated two-dimensional RNG k-epsilon turbulence model for the design optimization of a thrust vector control system using shock induced supersonic secondary jet. Parametric analytical studies have been carried out with various secondary jets at different divergent locations, jet interaction angles, jet pressures. The results from the parametric studies of the case on hand reveal that the primary nozzle with a small divergence angle, downstream injections with a distance of 2.5 times the primary nozzle throat diameter from the primary nozzle throat location warrant higher efficiency over a certain range of jet pressures and jet angles. We observed that the supersonic secondary jet opposing the core flow with jets interaction angle of 40o to the axis far downstream of the nozzle throat facilitates better thrust vectoring than the secondary jet with same direction as that of core flow with various interaction angles. We concluded that fixing of the supersonic secondary jet nozzle pointing towards the throat direction with suitable angle at a distance 2 to 4 times of the primary nozzle throat diameter, as the case may be, from the primary nozzle throat location could facilitate better thrust vectoring for the supersonic aerospace vehicles.

Keywords: Fluidic thrust vectoring, rocket steering, supersonic secondary jet location, TVC in spacecraft.

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Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using six sigma methodologies to reach the desired shrinkage of a manufactured high-density polyurethane (HDPE) part produced by the injection molding machine. It presents a case study where the correct shrinkage is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for an injection molding process. To improve this process and keep the product within specifications, the six sigma methodology, design, measure, analyze, improve, and control (DMAIC) approach, was implemented in this study. The six sigma approach was paired with the Taguchi methodology to identify the optimized processing parameters that keep the shrinkage rate within the specifications by our customer. An L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of the cooling time, melt temperature, holding time, and metering stroke. The noise factor is the difference between material brand 1 and material brand 2. After the confirmation run was completed, measurements verify that the new parameter settings are optimal. With the new settings, the process capability index has improved dramatically. The purpose of this study is to show that the six sigma and Taguchi methodology can be efficiently used to determine important factors that will improve the process capability index of the injection molding process.

Keywords: Injection molding, shrinkage, six sigma, Taguchi parameter design.

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Authors: Saleem Z. Ramadan

Abstract:

A model is presented to find the optimal design of the mixed renewable warranty policy for non-repairable Weibull life products. The optimal design considers the conflict of interests between the customer and the manufacturer: the customer interests are longer full rebate coverage period and longer total warranty coverage period, the manufacturer interests are lower warranty cost and lower risk. The design factors are full rebate and total warranty coverage periods. Results showed that mixed policy is better than full rebate policy in terms of risk and total warranty coverage period in all of the three bathtub regions. In addition, results showed that linear policy is better than mixed policy in infant mortality and constant failure regions while the mixed policy is better than linear policy in ageing region of the model. Furthermore, the results showed that using burn-in period for infant mortality products reduces warranty cost and risk.

Keywords: Reliability, Mixed warranty policy, Optimization, Weibull Distribution.

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Authors: R. A. Shahmiri, O. C. Standard, J. N. Hart, C. C. Sorrell

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The ceramic yttria-stabilized tetragonal zirconia polycrystal (Y-TZP) has been used as a dental biomaterial for several decades. The strength and toughness of this material can be accounted for by its toughening mechanisms, which include transformation toughening, crack deflection, zone shielding, contact shielding, and crack bridging. Prevention of crack propagation is of critical importance in high-fatigue situations, such as those encountered in mastication and para-function. However, the poor translucence of Y-TZP in polycrystalline form is such that it may not meet the aesthetic requirements due to its white/grey appearance. To improve the optical properties of Y-TZP, more detailed study of the optical properties is required; in particular, precise evaluation of the refractive index, absorption coefficient, and scattering coefficient are necessary. The measurement of the optical parameters has been based on the assumption that light scattered from biological media is isotropically distributed over all angles. In fact, the optical behavior of real biological materials depends on the angular scattering of light due to the anisotropic nature of the materials. The purpose of the present work is to evaluate the optical properties (including color, opacity/translucence, scattering, and fluorescence) of zirconia dental ceramics and their control through modification of the chemical composition, phase composition, and surface microstructure.

Keywords: Optical properties, opacity/translucence, scattering, fluorescence, chemical composition, phase composition, surface microstructure.

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Authors: Aleksandra Mišan, Bojana Šarić, Nataša Nedeljković, Mladenka Pestorić, Pavle Jovanov, Milica Pojić, Jelena Tomić, Bojana Filipčev, Miroslav Hadnađev, Anamarija Mandić

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With the aim of improving nutritional profile and antioxidant capacity of gluten-free cookies, blueberry pomace, by-product of juice production, was processed into a new food ingredient by drying and grinding and used for a gluten-free cookie formulation. Since the quality of a baked product is highly influenced by the baking conditions, the objective of this work was to optimize the baking time and thickness of dough pieces, by applying Response Surface Methodology (RSM) in order to obtain the best technological quality of the cookies. The experiments were carried out according to a Central Composite Design (CCD) by selecting the dough thickness and baking time as independent variables, while hardness, color parameters (L*, a* and b* values), water activity, diameter and short/long ratio were response variables. According to the results of RSM analysis, the baking time of 13.74min and dough thickness of 4.08mm was found to be the optimal for the baking temperature of 170°C. As similar optimal parameters were obtained by previously conducted experiment based on sensory analysis, response surface methodology (RSM) can be considered as a suitable approach to optimize the baking process.

Keywords: Baking process, blueberry pomace, gluten-free cookies, Response Surface Methodology.

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Authors: Amado, M. P., Amado, A., Poggi, F., Correia de Freitas, J.

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Today is widely understood that global energy consumption patterns are directly related to the urban expansion and development process. This expansion is based on the natural growth of human activities and has left most urban areas totally dependent on fossil fuel derived external energy inputs. This status-quo of production, transportation, storage and consumption of energy has become inefficient and is set to become even more so when the continuous increases in energy demand are factored in. The territorial management of land use and related activities is a central component in the search for more efficient models of energy use, models that can meet current and future regional, national and European goals.

In this paper a methodology is developed and discussed with the aim of improving energy efficiency at the municipal level. The development of this methodology is based on the monitoring of energy consumption and its use patterns resulting from the natural dynamism of human activities in the territory and can be utilized to assess sustainability at the local scale. A set of parameters and indicators are defined with the objective of constructing a systemic model based on the optimization, adaptation and innovation of the current energy framework and the associated energy consumption patterns. The use of the model will enable local governments to strike the necessary balance between human activities and economic development and the local and global environment while safeguarding fairness in the energy sector.

Keywords: Solar urban planning, solar smart city, urban development, energy efficiency.

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Authors: Mohamed Al Mahdi Eshtawie, Masuri Bin Othman

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Finite impulse response (FIR) filters have the advantage of linear phase, guaranteed stability, fewer finite precision errors, and efficient implementation. In contrast, they have a major disadvantage of high order need (more coefficients) than IIR counterpart with comparable performance. The high order demand imposes more hardware requirements, arithmetic operations, area usage, and power consumption when designing and fabricating the filter. Therefore, minimizing or reducing these parameters, is a major goal or target in digital filter design task. This paper presents an algorithm proposed for modifying values and the number of non-zero coefficients used to represent the FIR digital pulse shaping filter response. With this algorithm, the FIR filter frequency and phase response can be represented with a minimum number of non-zero coefficients. Therefore, reducing the arithmetic complexity needed to get the filter output. Consequently, the system characteristic i.e. power consumption, area usage, and processing time are also reduced. The proposed algorithm is more powerful when integrated with multiplierless algorithms such as distributed arithmetic (DA) in designing high order digital FIR filters. Here the DA usage eliminates the need for multipliers when implementing the multiply and accumulate unit (MAC) and the proposed algorithm will reduce the number of adders and addition operations needed through the minimization of the non-zero values coefficients to get the filter output.

Keywords: Pulse shaping Filter, Distributed Arithmetic, Optimization algorithm.

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Authors: Mina Dabirinezhad, Mohsen Bayat Pour, Amin Dabirinejad

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This paper is intended to introduce the technology to solve some of the deficiencies of the direct digital radiology. Nowadays, digital radiology is the latest progression in dental imaging, which has become an essential part of dentistry. There are two main parts of the direct digital radiology comprised of an intraoral X-ray machine and a sensor (digital image receptor). The dentists and the dental nurses experience afflictions during the taking image process by the direct digital X-ray machine. For instance, sometimes they need to readjust the sensor in the mouth of the patient to take the X-ray image again due to the low quality of that. Another problem is, the position of the sensor may move in the mouth of the patient and it triggers off an inappropriate image for the dentists. It means that it is a time-consuming process for dentists or dental nurses. On the other hand, taking several the X-ray images brings some problems for the patient such as being harmful to their health and feeling pain in their mouth due to the pressure of the sensor to the jaw. The author provides a technology to solve the above-mentioned issues that is called “Self-Recognition Direct Digital Radiology” (SDDR). This technology is based on the principle that the intraoral X-ray machine is capable to diagnose the location of the sensor in the mouth of the patient automatically. In addition, to solve the aforementioned problems, SDDR technology brings out fewer environmental impacts in comparison to the previous version.

Keywords: Dental direct digital imaging, digital image receptor, digital x-ray machine, and environmental impacts.

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Authors: Diana Gómez-Cano, J. C. Ochoa-Botero, Roberto Bernal Correa, Yhan Paul Arias

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To obtain high mechanical performance, the fresh conditions of a mortar are decisive. Measuring the absorption of aggregates used in mortar mixes is a fundamental requirement for proper design of the mixes prior to their placement in construction sites. In this sense, absorption is a determining factor in the design of a mix because it conditions the amount of water, which in turn affects the water/cement ratio and the final porosity of the mortar. Thus, this work focuses on the mechanical behavior of recycled mortars manufactured from moisture correction using the Thermogravimetric Balancing Halogen Light (TBHL) technique in comparison with the traditional ASTM C 128 International Standard method. The advantages of using the TBHL technique are favorable in terms of reduced consumption of resources such as materials, energy and time. The results show that in contrast to the ASTM C 128 method, the TBHL alternative technique allows obtaining a higher precision in the absorption values of recycled aggregates, which is reflected not only in a more efficient process in terms of sustainability in the characterization of construction materials, but also in an effect on the mechanical performance of recycled mortars.

Keywords: Alternative raw materials, halogen light, recycled mortar, resources optimization, water absorption.

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Authors: Nihad Chakri, Btissam El Amrani, Faouzi Berrada, Fouad Amraoui

Abstract:

In Morocco, water scarcity requires the exploitation of non-conventional resources. Rural areas are under-equipped with sanitation infrastructure, unlike urban areas. Decentralized and low-cost solutions could improve the quality of life of the population and the environment. In this context, the Faculty of Sciences Ain Chock (FSAC) has undertaken an integrated project to treat part of its wastewater using a decentralized compact system. The project will propose alternative solutions that are inexpensive and adapted to the context of peri-urban and rural areas in order to treat the wastewater generated and to use it for irrigation, watering and cleaning. For this purpose, several tests were carried out in the laboratory in order to develop a liquid waste treatment system optimized for local conditions. Based on the results obtained at laboratory scale of the different proposed scenarios, we designed and implemented a prototype of a mini wastewater treatment plant for the faculty. In this article, we will outline the steps of dimensioning, construction and monitoring of the mini-station in our faculty.

Keywords: Wastewater, purification, response methodology surfaces optimization, vertical filter, Moving Bed Biofilm Reactors, MBBR process, sizing, prototype, Faculty of Sciences Ain Chock, decentralized approach, mini wastewater treatment plant, reuse of treated wastewater reuse, irrigation, sustainable development.

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Authors: Seyedvahid Najafi, Viliam Makis

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In recent years, maintenance optimization has attracted special attention due to the growth of industrial systems complexity. Maintenance costs are high for many systems, and preventive maintenance is effective when it increases operations' reliability and safety at a reduced cost. The novelty of this research is to consider general repair in the modeling of multi-unit series systems and solve the maintenance problem for such systems using the semi-Markov decision process (SMDP) framework. We propose an opportunistic maintenance policy for a series system composed of two main units. Unit 1, which is more expensive than unit 2, is subjected to condition monitoring, and its deterioration is modeled using a gamma process. Unit 1 hazard rate is estimated by the proportional hazards model (PHM), and two hazard rate control limits are considered as the thresholds of maintenance interventions for unit 1. Maintenance is performed on unit 2, considering an age control limit. The objective is to find the optimal control limits and minimize the long-run expected average cost per unit time. The proposed algorithm is applied to a numerical example to compare the effectiveness of the proposed policy (policy Ⅰ) with policy Ⅱ, which is similar to policy Ⅰ, but instead of general repair, replacement is performed. Results show that policy Ⅰ leads to lower average cost compared with policy Ⅱ. 

Keywords: Condition-based maintenance, proportional hazards model, semi-Markov decision process, two-unit series systems.

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Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

Abstract:

In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other.

As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO.

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Authors: Ndidi F. Amulu, Godian O. Mbah, Maxwel I. Onyiah, Callistus N. Ude

Abstract:

Analysis of the properties of coconut (Cocos nucifera) and its oil was evaluated in this work using standard analytical techniques. The analyses carried out include proximate composition of the fruit, extraction of oil from the fruit using different process parameters and physicochemical analysis of the extracted oil. The results showed the percentage (%) moisture, crude lipid, crude protein, ash and carbohydrate content of the coconut as 7.59, 55.15, 5.65, 7.35 and 19.51 respectively. The oil from the coconut fruit was odourless and yellowish liquid at room temperature (30oC). The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant differences (P<0.05) in the yield of oil from coconut flour. The oil yield ranged between 36.25%-49.83%. Lipid indices of the coconut oil indicated the acid value (AV) as 10.05Na0H/g of oil, free fatty acid (FFA) as 5.03%, saponification values (SV) as 183.26mgKOH-1g of oil, iodine value (IV) as 81.00 I2/g of oil, peroxide value (PV) as 5.00 ml/ g of oil and viscosity (V) as 0.002. A standard statistical package minitab version 16.0 program was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to generate various plots such as single effect plot, interactions effect plot and contour plot. The response or yield of oil from the coconut flour was used to develop a mathematical model that correlates the yield to the process variables studied. The maximum conditions obtained that gave the highest yield of coconut oil were leaching time of 2hrs, leaching temperature of 50oC and solute/solvent ratio of 0.05g/ml.

Keywords: Coconut, oil-extraction, optimization, physicochemical, proximate.

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Authors: Sakshi Kausha, R.K Sharma

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High speed networks provide realtime variable bit rate service with diversified traffic flow characteristics and quality requirements. The variable bit rate traffic has stringent delay and packet loss requirements. The burstiness of the correlated traffic makes dynamic buffer management highly desirable to satisfy the Quality of Service (QoS) requirements. This paper presents an algorithm for optimization of adaptive buffer allocation scheme for traffic based on loss of consecutive packets in data-stream and buffer occupancy level. Buffer is designed to allow the input traffic to be partitioned into different priority classes and based on the input traffic behavior it controls the threshold dynamically. This algorithm allows input packets to enter into buffer if its occupancy level is less than the threshold value for priority of that packet. The threshold is dynamically varied in runtime based on packet loss behavior. The simulation is run for two priority classes of the input traffic – realtime and non-realtime classes. The simulation results show that Adaptive Partial Buffer Sharing (ADPBS) has better performance than Static Partial Buffer Sharing (SPBS) and First In First Out (FIFO) queue under the same traffic conditions.

Keywords: Buffer Management, Consecutive packet loss, Quality-of-Service, Priority based packet discarding, partial buffersharing.

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Authors: Ashish Saini, A.K. Saxena

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The genetic algorithm (GA) based solution techniques are found suitable for optimization because of their ability of simultaneous multidimensional search. Many GA-variants have been tried in the past to solve optimal power flow (OPF), one of the nonlinear problems of electric power system. The issues like convergence speed and accuracy of the optimal solution obtained after number of generations using GA techniques and handling system constraints in OPF are subjects of discussion. The results obtained for GA-Fuzzy OPF on various power systems have shown faster convergence and lesser generation costs as compared to other approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF) using penalty factors to handle line flow constraints and load bus voltage limits for both normal network and contingency case with congestion. In addition to crossover and mutation rate adaptation scheme that adapts crossover and mutation probabilities for each generation based on fitness values of previous generations, a block swap operator is also incorporated in proposed EGA-OPF. The line flow limits and load bus voltage magnitude limits are handled by incorporating line overflow and load voltage penalty factors respectively in each chromosome fitness function. The effects of different penalty factors settings are also analyzed under contingent state.

Keywords: Contingent operation state, Fuzzy rule base, Genetic Algorithms, Optimal Power Flow.

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Authors: Seema Chopra, R. Mitra, Vijay Kumar

Abstract:

A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.

Keywords: Fuzzy control, neuro-fuzzy techniques, fuzzy subtractive clustering, extraction of rules, and optimization of membership functions.

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Authors: Cora Fernandez Dacosta, John A. Posada, Andrea Ramirez

Abstract:

The biodegradable family of polymers polyhydroxyalkanoates is an interesting substitute for convectional fossil-based plastics. However, the manufacturing and environmental impacts associated with their production via intracellular bacterial fermentation are strongly dependent on the raw material used and on energy consumption during the extraction process, limiting their potential for commercialization. Industrial wastewater is studied in this paper as a promising alternative feedstock for waste valorization. Based on results from laboratory and pilot-scale experiments, a conceptual process design, techno-economic analysis and life cycle assessment are developed for the large-scale production of the most common type of polyhydroxyalkanoate, polyhydroxbutyrate. Intracellular polyhydroxybutyrate is obtained via fermentation of microbial community present in industrial wastewater and the downstream processing is based on chemical digestion with surfactant and hypochlorite. The economic potential and environmental performance results help identifying bottlenecks and best opportunities to scale-up the process prior to industrial implementation. The outcome of this research indicates that the fermentation of wastewater towards PHB presents advantages compared to traditional PHAs production from sugars because the null environmental burdens and financial costs of the raw material in the bioplastic production process. Nevertheless, process optimization is still required to compete with the petrochemicals counterparts.

Keywords: Circular economy, life cycle assessment, polyhydroxyalkanoates, waste valorization.

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Authors: C. S. Saini

Abstract:

The composite flour blend consisting of corn, pearl millet, black gram and wheat bran in the ratio of 80:5:10:5 was taken to prepare the extruded product and their effect on physical properties of extrudate was studied. The extrusion process was conducted in laboratory by using twin screw extruder. The physical characteristics evaluated include lateral expansion, bulk density, water absorption index, water solubility index, and rehydration ratio and moisture retention. The Central Composite Rotatable Design (CCRD) was used to decide the level of processing variables i.e. feed moisture content (%), screw speed (rpm), and barrel temperature (oC) for the experiment. The data obtained after extrusion process were analyzed by using response surface methodology. A second order polynomial model for the dependent variables was established to fit the experimental data. The numerical optimization studies resulted in 127°C of barrel temperature, 246 rpm of screw speed, and 14.5% of feed moisture as optimum variables to produce acceptable extruded product. The responses predicted by the software for the optimum process condition resulted in lateral expansion 126%, bulk density 0.28 g/cm3, water absorption index 4.10 g/g, water solubility index 39.90%, rehydration ratio 544% and moisture retention 11.90% with 75% desirability.

Keywords: Black gram, corn flour, extrusion, physical characteristics.

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Authors: Emma K. Sales

Abstract:

Durian is the flagship fruit of Mindanao and there is an abundance of several cultivars with many confusing identities/ names. The project was conducted to develop procedure for reliable and rapid detection and sorting of durian planting materials. Moreover, it is also aimed to establish specific genetic or DNA markers for routine testing and authentication of durian cultivars in question. The project developed molecular procedures for routine testing. SSR primers were also screened and identified for their utility in discriminating durian cultivars collected. Results of the study showed the following accomplishments: 1. Twenty (29) SSR primers were selected and identified based on their ability to discriminate durian cultivars, 2. Optimized and established standard procedure for identification and authentication of Durian cultivars 3. Genetic profile of durian is now available at Biotech Unit Our results demonstrate the relevance of using molecular techniques in evaluating and identifying durian clones. The most polymorphic primers tested in this study could be useful tools for detecting variation even at the early stage of the plant especially for commercial purposes. The process developed combines the efficiency of the microsatellites development process with the optimization of non-radioactive detection process resulting in a user-friendly protocol that can be performed in two (2) weeks and easily incorporated into laboratories about to start microsatellite development projects. This can be of great importance to extend microsatellite analyses to other crop species where minimal genetic information is currently available. With this, the University can now be a service laboratory for routine testing and authentication of durian clones.

Keywords: DNA, SSR Analysis, genotype, genetic diversity, cultivars.

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Authors: Muhammad Ashraf Fauzi, Nurhayati Abdul Malek, Jamilah Othman

Abstract:

The implementations of green roof have been widely used in the developed countries such as Germany, United Kingdom, United States and Canada. Green roof have many benefits such as aesthetic and economic value, ecological gain which are optimization of storm water management, urban heat island mitigation and energy conservation. In term of pollution, green roof can control the air and noise pollution in urban cities. The application of green roof in Malaysian building has been studied with the previous work of green roof either in Malaysia or other Asian region as like Indonesia, Singapore, Thailand, Taiwan and several other countries that have similar climate and environment as in Malaysia. These technologies of adapting green roof have been compared to the Green Building Index (GBI) of Malaysian buildings. The study has concentrated on the technical aspect of green roof system having focused on i) waste & recyclable materials ii) types of plants and method of planting and iii) green roof as tool to reduce storm water runoff. The finding of these areas will be compared to the suitability in achieving good practice of the GBI in Malaysia. Results show that most of the method are based on the countries own climate and environment. This suggests that the method of using green roof must adhere to the tropical climate of Malaysia. Suggestion of this research will be viewed in term of the sustainability of the green roof. Further research can be developed to implement the best method and application in Malaysian climate especially in urban cities and township.

Keywords: Green roofs, vegetation, plants, material, stormwater.

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Authors: Edison Muzenda, Corina M Mateescu

Abstract:

Group contribution methods such as the UNIFAC are very useful to researchers and engineers involved in synthesis, feasibility studies, design and optimization of separation processes. They can be applied successfully to predict phase equilibrium and excess properties in the development of chemical and separation processes. The main focus of this work was to investigate the possibility of absorbing selected volatile organic compounds (VOCs) into polydimethylsiloxane (PDMS) using three selected UNIFAC group contribution methods. Absorption followed by subsequent stripping is the predominant available abatement technology of VOCs from flue gases prior to their release into the atmosphere. The original, modified and effective UNIFAC models were used in this work. The thirteen selected VOCs that have been considered in this research are: pentane, hexane, heptanes, trimethylamine, toluene, xylene, cyclohexane, butyl acetate, diethyl acetate, chloroform, acetone, ethyl methyl ketone and isobutyl methyl ketone. The computation was done for solute VOC concentration of 8.55x10-8 which is well in the infinite dilution region. The results obtained in this study compare very well with those published in literature obtained through both measurements and predictions. The phase equilibrium obtained in this study show that PDMS is a good absorbent for the removal of VOCs from contaminated air streams through physical absorption.

Keywords: Absorption, Computation, Feasibility studies, Infinite dilution, Volatile organic compounds

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Authors: L. Wang, Y. Chen, T. Wu, S. Hu

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In order to enhance the security of critical financial infrastructure, this study carries out a transformation of the architecture of a financial trading terminal to a zero trust architecture (ZTA), constructs an active defense system for the cybersecurity, improves the security level of trading services in the Internet environment, enhances the ability to prevent network attacks and unknown risks, and reduces the industry and security risks brought about by cybersecurity risks. This study introduces Software Defined Perimeter (SDP) technology of ZTA, adapts and applies it to a financial trading terminal to achieve security optimization and fine-grained business grading control. The upgraded architecture of the trading terminal moves security protection forward to the user access layer, replaces VPN to optimize remote access and significantly improves the security protection capability of Internet transactions. The study achieves: 1. deep integration with the access control architecture of the transaction system; 2. no impact on the performance of terminals and gateways, and no perception of application system upgrades; 3. customized checklist and policy configuration; 4. introduction of industry-leading security technology such as single-packet authorization (SPA) and secondary authentication. This study carries out a successful application of ZTA in the field of financial trading, and provides transformation ideas for other similar systems while improving the security level of financial transaction services in the Internet environment.

Keywords: Zero trust, trading terminal, architecture, network security, cybersecurity.

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Authors: Ashish Saini, A.K. Saxena

Abstract:

In competitive electricity markets all over the world, an adoption of suitable transmission pricing model is a problem as transmission segment still operates as a monopoly. Transmission pricing is an important tool to promote investment for various transmission services in order to provide economic, secure and reliable electricity to bulk and retail customers. The nodal pricing based on SRMC (Short Run Marginal Cost) is found extremely useful by researchers for sending correct economic signals. The marginal prices must be determined as a part of solution to optimization problem i.e. to maximize the social welfare. The need to maximize the social welfare subject to number of system operational constraints is a major challenge from computation and societal point of views. The purpose of this paper is to present a nodal transmission pricing model based on SRMC by developing new mathematical expressions of real and reactive power marginal prices using GA-Fuzzy based optimal power flow framework. The impacts of selecting different social welfare functions on power marginal prices are analyzed and verified with results reported in literature. Network revenues for two different power systems are determined using expressions derived for real and reactive power marginal prices in this paper.

Keywords: Deregulation, electricity markets, nodal pricing, social welfare function, short run marginal cost.

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