Search results for: optimal path

Authors: Toshihiko Matsuka, James E. Corter

Abstract:

Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.

Keywords: category learning, cognitive modeling, radial basis function, stochastic optimization.

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Authors: A. Vasan

Abstract:

Particle swarm optimization (PSO) technique is applied to design the water distribution pipeline network. A simulation-optimization model is formulated with the objective of minimizing cost and is applied to a benchmark water distribution system optimization problem. The benchmark problem taken for the application of PSO technique to optimize the pipe size of the water distribution network is New York City water supply system problem. The results from the analysis infer that PSO is a potential alternative optimization technique when compared to other heuristic techniques for optimal sizing of water distribution systems.

Keywords: Water distribution systems, Optimization, Particle swarm optimization, Swarm intelligence, New York water supply system.

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Authors: S. Chonsatidjamroen , K-N. Areerak, K-L. Areerak

Abstract:

This paper presents the averaging model of a buck converter derived from the generalized state-space averaging method. The sliding mode control is used to regulate the output voltage of the converter and taken into account in the model. The proposed model requires the fast computational time compared with those of the full topology model. The intensive time-domain simulations via the exact topology model are used as the comparable model. The results show that a good agreement between the proposed model and the switching model is achieved in both transient and steady-state responses. The reported model is suitable for the optimal controller design by using the artificial intelligence techniques.

Keywords: Generalized state-space averaging method, buck converter, sliding mode control, modeling, simulation.

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Authors: C. Pongcharoen, K. Kaiyavongand T. Satapanajaru

Abstract:

Theobjective of this study was to evaluate the optimal treatment condition of Fenton oxidation process to removal contaminant in soil slurry contaminated by petroleum hydrocarbons. This research studied somefactors that affect the removal efficiency of petroleum hydrocarbons in soil slurry including molar ratio of hydrogen peroxide (H2O2) to ferrous ion(Fe2+), pH condition and reaction time.The resultsdemonstrated that the optimum condition was that the molar ratio of H2O2:Fe3+ was 200:1,the pHwas 4.0and the rate of reaction was increasing rapidly from starting point to 7th hour and destruction kinetic rate (k) was 0.24 h-1. Approximately 96% of petroleum hydrocarbon was observed(initialtotal petroleum hydrocarbon (TPH) concentration = 70±7gkg-1)

Keywords: Contaminated soil, Fenton oxidation, Petroleumhydrocarbon, Remediation.

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Authors: Shashwat Gangwal

Abstract:

This paper analyses the effect of adding Bitcoin, to the portfolio (stocks, bonds, Baltic index, MXEF, gold, real estate and crude oil) of an international investor by using daily data available from 2^nd of July, 2010 to 2^{nd of} August, 2016. We conclude that adding Bitcoin to portfolio, over the course of the considered period, always yielded a higher Sharpe ratio. This means that Bitcoin’s returns offset its high volatility. This paper, recognizing the fact that Bitcoin is a relatively new asset class, gives the readers a basic idea about the working of the virtual currency, the increasing number developments in the financial industry revolving around it, its unique features and the detailed look into its continuously growing acceptance across different fronts (Banks, Merchants and Countries) globally. We also construct optimal portfolios to reflect the highly lucrative and largely unexplored opportunities associated with investment in Bitcoin.

Keywords: Portfolio management, Bitcoin, optimization, Sharpe ratio.

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Authors: V. Tawiwat, S. Sarawut

Abstract:

Applied a mouse-s roller with a gripper to increase the efficiency for a gripper can learn to a material handling without slipping. To apply a gripper, we use the optimize principle to develop material handling by use a signal for checking a roller mouse that rotate or not. In case of the roller rotates means that the material slips. A gripper will slide to material handling until the roller will not rotate. As this experiment has test material handling for comparing a grip force that uses to material handling of the 10-human with the applied gripper. We can summarize that human exert the material handling more than the applied gripper. Because of the gripper can exert more befit to material handling than human and may be a minimum force to lift a material without slipping.

Keywords: Optimize, Gripper, Mouse's Roller, Minimum Force.

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Authors: Barenten Suciu

Abstract:

In this paper, effectiveness of a machine design process is evaluated on the basis of the specific output calculus. Concretely, a screw-worm gear mechanical transmission is designed by using the classical and the 3D-CAD methods. Strength analysis and drawing of the designed parts is substantially aided by employing the SolidWorks software. Quality of the design process is assessed by manufacturing (printing) the parts, and by computing the efficiency, specific load, as well as the specific output (work) of the mechanical transmission. Influence of the stroke, travelling velocity and load on the mechanical output, is emphasized. Optimal design of the mechanical transmission becomes possible by the appropriate usage of the acquired results.

Keywords: Mechanical transmission, design, screw, worm-gear, efficiency, specific output, 3D-printing.

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Authors: Arunima Shukla, Vikas Almadi, Devesh Jaiswal, Sunil Saini, Bhusan S. Patil

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Lightning protection consists of three main parts; mainly air termination system, down conductor, and earth termination system. Earth termination system is the most important part as earth is the sink and source of charges. Therefore, even when the charges are captured and delivered to the ground, and an easy path is not provided to the charges, earth termination system would lead to problems. Soil has significantly different resistivities ranging from 10 Ωm for wet organic soil to 10000 Ωm for bedrock. Different methods have been discussed and used conventionally such as deep-ground-well method and altering the length of the rod. Those methods are not considered economical. Therefore, it was a general practice to use charcoal along with salt to reduce the soil resistivity. Bentonite is worldwide acceptable material, that had led our interest towards study of bentonite at first. It was concluded that bentonite is a clay which is non-corrosive, environment friendly. Whereas bentonite is suitable only when there is moisture present in the soil, as in the absence of moisture, cracks will appear on the surface which will provide an open passage to the air, resulting into increase in the resistivity. Furthermore, bentonite without moisture does not have enough bonding property, moisture retention, conductivity, and non-leachability. Therefore, bentonite was used along with the other backfill material to overcome the dependency of bentonite on moisture. Different experiments were performed to get the best ratio of bentonite and carbon backfill. It was concluded that properties will highly depend on the quantity of bentonite and carbon-based backfill material.

Keywords: Backfill material, bentonite, conducting soil, grounding material, low resistivity.

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Authors: N. Dizadji, P. Entezar, A. Shabani

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This study presents energy saving in general-purpose pumps widely used in industrial applications. Such pumps are normally driven by a constant-speed electrical motor which in most applications must support varying load conditions. This is equivalent to saying the loading conditions mismatch the designed optimal energy consumption requirements of the intended application thus resulting in substantial energy losses. In the held experiments it was indicated that combination of mechanical and electrical speed drives can contribute to lower energy consumption in the pump without negatively distorting the required performance indices of a typical centrifugal pump at substantially lower energy consumption. The registered energy savings were recorded to be within the 15-40% margin. It was also indicated that although VSDs are installed at a cost, the financial burden is balanced against the earnings resulting from the associated energy savings.

Keywords: Industrial motors, Pumps, Energy consumption, Energy savings, Variable speed drive.

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Authors: Job H. Domingo, Carolina Bancayrin-Baguio

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The Sphere Method is a flexible interior point algorithm for linear programming problems. This was developed mainly by Professor Katta G. Murty. It consists of two steps, the centering step and the descent step. The centering step is the most expensive part of the algorithm. In this centering step we proposed some improvements such as introducing two or more initial feasible solutions as we solve for the more favorable new solution by objective value while working with the rigorous updates of the feasible region along with some ideas integrated in the descent step. An illustration is given confirming the advantage of using the proposed procedure.

Keywords: Interior point, linear programming, sphere method, initial feasible solution, feasible region, centering and descent steps, optimal solution.

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Authors: Ratchadaporn Oonsivilai, Jutarat Manatwiyangkool, Anant Oonsivilai

Abstract:

Theoptimal extraction condition of dried Phaseolus vulgaris powderwas studied. The three independent variables are raw material concentration, shaking and centrifugaltime. The dependent variables are both yield percentage of crude extract and alphaamylase enzyme inhibition activity. The experimental design was based on box-behnkendesign. Highest yield percentage of crude extract could get from extraction condition at concentration of 1, 0,1, concentration of 0.15 M ,extraction time for 2hour, and separationtime for60 min. Moreover, the crude extract with highest alpha-amylase enzyme inhibition activityoccurred by extraction condition at concentration of 0.10 M, extraction time for 2 min, and separation time for 45 min

Keywords: Extraction time, Optimal condition, Alpha-amylase enzymeinhibition activity

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Authors: Arash Hassanpour Isfahani, Siavash Sadeghi

Abstract:

Permanent magnet synchronous machines are known as a good candidate for hybrid electric vehicles due to their unique merits. However they have two major drawbacks i.e. high cost and small speed range. In this paper an optimal design of a permanent magnet machine is presented. A reduction of permanent magnet material for a constant torque and an extension in speed and torque ranges are chosen as the optimization aims. For this purpose the analytical model of the permanent magnet synchronous machine is derived and the appropriate design algorithm is devised. The genetic algorithm is then employed to optimize some machine specifications. Finally the finite element method is used to validate the designed machine.

Keywords: Design, Finite Element, Hybrid electric vehicle, Optimization, Permanent magnet synchronous machine.

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Authors: Ali Reza Sahab, Amir Gholami Pastaki

Abstract:

In this paper, backstepping method (BM) is proposed for a single-link flexible mechanical manipulator. In each step of this method a positive value is obtained. Selections of the gain factor values are very important because controller will have different behavior for each different set of values. Improper selection of these gains can lead to instability of the system. In order to choose proper values for gains BELBIC method has been used in this work. Finally, to prove the efficiency of this method, the obtained results of proposed model are compared with robust controller one. Results show that the combination of backstepping and BELBIC that is presented here, can stabilized the system with higher speed, shorter settling time and lower overshoot in than robust controller.

Keywords: single-link flexible manipulator, backstepping, BELBIC

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Authors: Iau-Teh Wang, Chin-Yu Lee

Abstract:

Rockfall is a kind of irregular geological disaster. Its destruction time, space and movements are highly random. The impact force is determined by the way and velocity rocks move. The movement velocity of a rockfall depends on slope gradient of its moving paths, height, slope surface roughness and rock shapes. For effectively mitigate and prevent disasters brought by rockfalls, it is required to precisely calculate the moving paths of a rockfall so as to provide the best protective design. This paper applies Colorado Rockfall Simulation Program (CRSP) as our study tool to discuss the impact of slope shape and surface roughness on the moving paths of a single rockfall. The analytical results showed that the slope, m=1:1, acted as the threshold for rockfall bounce height on a monoclinal slight slope. When JRC ´╝£ 1.2, movement velocity reduced and bounce height increased as JCR increased. If slope fixed and JRC increased, the bounce height of rocks increased gradually with reducing movement velocity. Therefore, the analysis on the moving paths of rockfalls with CRSP could simulate bouncing of falling rocks. By analyzing moving paths, velocity, and bounce height of falling rocks, we could effectively locate impact points of falling rocks on a slope. Such analysis can be served as a reference for future disaster prevention and control.

Keywords: Rockfall, Slope Shape, Moving Path, SurfaceRoughness.

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Authors: Kahraman Ayyildiz, Stefan Conrad

Abstract:

In this paper we illuminate a frequency domain based classification method for video scenes. Videos from certain topical areas often contain activities with repeating movements. Sports videos, home improvement videos, or videos showing mechanical motion are some example areas. Assessing main and side frequencies of each repeating movement gives rise to the motion type. We obtain the frequency domain by transforming spatio-temporal motion trajectories. Further on we explain how to compute frequency features for video clips and how to use them for classifying. The focus of the experimental phase is on transforms utilized for our system. By comparing various transforms, experiments show the optimal transform for a motion frequency based approach.

Keywords: action recognition, frequency, transform, motion recognition, repeating movement, video classification

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Authors: Zhang Lei, Liu Min, Liu Botao

Abstract:

In order to improve the simulation effects of space cold black environment, this paper described a rectangular channel plate heat sink. By using fluid mechanics theory and finite element method, the internal fluid flow and heat transfer in heat sink was numerically simulated to analyze the impact of channel structural on fluid flow and heat transfer. The result showed that heat sink temperature uniformity is well, and the impact of channel structural on the heat sink temperature uniformity is not significant. The channel depth and spacing are important factors which affect the fluid flow and heat transfer in the heat sink. The two factors of heat transfer and resistance need to be considered comprehensively to determine the optimal flow structure parameters.

Keywords: heat transfer, heat sink, numerical simulation

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Authors: Jasmin Velagic, Nedim Osmic, Bakir Lacevic

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In this paper the neural network-based controller is designed for motion control of a mobile robot. This paper treats the problems of trajectory following and posture stabilization of the mobile robot with nonholonomic constraints. For this purpose the recurrent neural network with one hidden layer is used. It learns relationship between linear velocities and error positions of the mobile robot. This neural network is trained on-line using the backpropagation optimization algorithm with an adaptive learning rate. The optimization algorithm is performed at each sample time to compute the optimal control inputs. The performance of the proposed system is investigated using a kinematic model of the mobile robot.

Keywords: Mobile robot, kinematic model, neural network, motion control, adaptive learning rate.

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Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim, Rashidah Ghazali, Noramli Abdul Razak

Abstract:

Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of prediction models has facilitated the estimation process in recent years. In this study, 110 crude palm oil (CPO) samples were used to build a free fatty acid (FFA) prediction model. 60% of the collected data were used for training purposes and the remaining 40% used for testing. The visible peaks on the NIR spectrum were at 1725 nm and 1760 nm, indicating the existence of the first overtone of C-H bands. Principal component regression (PCR) was applied to the data in order to build this mathematical prediction model. The optimal number of principal components was 10. The results showed R2=0.7147 for the training set and R2=0.6404 for the testing set.

Keywords: Palm oil, fatty acid, NIRS, regression.

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Authors: Paul Lajbcygier, Seng Lee

Abstract:

Co-integration models the long-term, equilibrium relationship of two or more related financial variables. Even if cointegration is found, in the short run, there may be deviations from the long run equilibrium relationship. The aim of this work is to forecast these deviations using neural networks and create a trading strategy based on them. A case study is used: co-integration residuals from Australian Bank Bill futures are forecast and traded using various exogenous input variables combined with neural networks. The choice of the optimal exogenous input variables chosen for each neural network, undertaken in previous work [1], is validated by comparing the forecasts and corresponding profitability of each, using a trading strategy.

Keywords: Artificial neural networks, co-integration, forecasting, trading rule.

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Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

Abstract:

In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: Availability, design for maintenance, DFM, dynamic maintenance, life cycle cost, LCC, maintenance free operating period, MFOP, simultaneous optimization.

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Authors: Nathar Shah, Bu Kiat Seng

Abstract:

Mobile application development is different from regular application development due to the hardware resource limitations existed in the mobile platforms. In the mobile environment, the application needs to be optimized by the developer to produce optimal software with least overhead. This study discussed about performance optimization techniques that are employed in general application development, and how such techniques are performing on mobile platforms through some empirical evaluations on a mobile emulator, Nokia X3-02 and Nokia C5-03devices. The scope of the work is only confined to mobile platform based on Java Mobile edition architecture. The empirical results showed that techniques such as loop unrolling, dependency chain, and linearized getter and setter performed better by a factor of 3 to 7. Whereas declaration and initialization on the same line or separate line did not improve the performance.

Keywords: Optimization Techniques, Mobile Applications, Performance Evaluation, J2ME, Empirical Experiments

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Authors: Sara Mensou, Ahmed Essadki, Issam Minka, Tamou Nasser, Badr Bououlid Idrissi

Abstract:

In this paper we present a contribution for the modeling and control of wind energy conversion system based on a Doubly Fed Induction Generator (DFIG). Since the wind speed is random the system has to produce an optimal electrical power to the Network and ensures important strength and stability. In this work, the Backstepping controller is used to control the generator via two converter witch placed a DC bus capacitor and connected to the grid by a Filter R-L, in order to optimize capture wind energy. All is simulated and presented under MATLAB/Simulink Software to show performance and robustness of the proposed controller.

Keywords: Wind turbine, doubly fed induction generator, MPPT control, backstepping controller, power converter.

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Authors: K. M. Faraoun, A. Boukelif

Abstract:

In the present work, we propose a new technique to enhance the learning capabilities and reduce the computation intensity of a competitive learning multi-layered neural network using the K-means clustering algorithm. The proposed model use multi-layered network architecture with a back propagation learning mechanism. The K-means algorithm is first applied to the training dataset to reduce the amount of samples to be presented to the neural network, by automatically selecting an optimal set of samples. The obtained results demonstrate that the proposed technique performs exceptionally in terms of both accuracy and computation time when applied to the KDD99 dataset compared to a standard learning schema that use the full dataset.

Keywords: Neural networks, Intrusion detection, learningenhancement, K-means clustering

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Authors: M. S. Bani, Z. A. Rashid, K. H. K. Hamid, M. E. Harbawi, A.B.Alias, M. J. Aris

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Most Decision Support Systems (DSS) for waste management (WM) constructed are not widely marketed and lack practical applications. This is due to the number of variables and complexity of the mathematical models which include the assumptions and constraints required in decision making. The approach made by many researchers in DSS modelling is to isolate a few key factors that have a significant influence to the DSS. This segmented approach does not provide a thorough understanding of the complex relationships of the many elements involved. The various elements in constructing the DSS must be integrated and optimized in order to produce a viable model that is marketable and has practical application. The DSS model used in assisting decision makers should be integrated with GIS, able to give robust prediction despite the inherent uncertainties of waste generation and the plethora of waste characteristics, and gives optimal allocation of waste stream for recycling, incineration, landfill and composting.

Keywords: Review, decision support system, GIS and waste management.

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Authors: Naveed Ahmed, Gunar Matthies

Abstract:

We deal with the numerical solution of time-dependent convection-diffusion-reaction equations. We combine the local projection stabilization method for the space discretization with two different time discretization schemes: the continuous Galerkin-Petrov (cGP) method and the discontinuous Galerkin (dG) method of polynomial of degree k. We establish the optimal error estimates and present numerical results which shows that the cGP(k) and dG(k)- methods are accurate of order k +1, respectively, in the whole time interval. Moreover, the cGP(k)-method is superconvergent of order 2k and dG(k)-method is of order 2k +1 at the discrete time points. Furthermore, the dependence of the results on the choice of the stabilization parameter are discussed and compared.

Keywords: Convection-diffusion-reaction equations, stabilized finite elements, discontinuous Galerkin, continuous Galerkin-Petrov.

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Authors: Ahmed Z. Gabr, Ahmed A. Helal, Hussein E. Said

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With the incessant increase of power systems capacity and voltage grade, the safety of grounding grid becomes more and more prominent. In this paper, the designing substation grounding grid is presented by means of genetic algorithm (GA). This approach purposes to control the grounding cost of the power system with the aid of controlling grounding rod number and conductor lengths under the same safety limitations. The proposed technique is used for the design of the substation grounding grid in Khalda Petroleum Company “El-Qasr” power plant and the design was simulated by using CYMGRD software for results verification. The result of the design is highly complying with IEEE 80-2000 standard requirements.

Keywords: Genetic algorithm, optimum grounding grid design, power system analysis, power system protection, single layer model, substation.

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Authors: C. C. Lv, Y. L. Sun, D. W. Zuo

Abstract:

Cemented carbide balls are usually implemented in industry under the environment of high speed, high temperature, corrosiveness and strong collisions. However, its application is limited due to high fabrication cost, processing efficiency and quality. A novel eccentric lapping method with two rotatable lapping plates was proposed in this paper. A mathematical model was constructed to analyze the influence of each design parameter on this lapping method. To validate this new lapping method, an orthogonal experiment was conducted with cemented carbide balls (YG6). The simulation model was verified and the optimal lapping parameters were derived. The results show that the surface roundness of the balls reaches to 0.65um from 2um in 1 hour using this lapping method. So, using this novel lapping method, it can effectively improve the machining precision and efficiency of cemented carbide balls.

Keywords: Cemented carbide balls, eccentric lapping, high precision, lapping tracks, V-groove.

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Authors: Deshar Bashu Dev

Abstract:

In this modern age, most people in developed and developing countries are affected by mental illness. There are many mental illnesses, and their differing symptoms impact peoples’ lives in different ways. These illnesses affect the way people think and feel, as well as how they behave with others. Mental illness results from compound interactions between the mind, body, and environment. New technologies and sciences make the world a better place. These technologies are becoming smarter and are being developed every day to help make daily life easier However, people suffer from mental illness in every part of the world. The philosophy propounded by the Buddha, Buddhism, teaches that all life is connected, from the microcosm to macrocosm. In the 2,500 years that elapsed since the death of the Buddha, his disciples have spread his teachings and developed sophisticated psycho-therapeutic methodologies. We can find many examples in Buddhist texts and in the modern age where Buddhist philosophy modern science could not solve. The Noble Eightfold Path, which is one of the main philosophies of Buddhism; it eradicates hatred and ill will and cultivates good deeds, kindness, and compassion. Buddhism, as a practice of dialectic conversation and mindfulness training, is full of rich therapeutic tools that the mental health community has adopted to help people. Similarly, Buddhist meditation is very necessary; it purifies thoughts and avoids unnecessary thinking. This research aims to study different causes of mental illness; analyzes the different approaches to eradicate mental illness problems and provides conclusions and recommendations present solutions through Buddhism in this modern age.

Keywords: Mental illness, Buddhism, mindfulness, Buddhist practices.

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Authors: Wei Chen, Cui-you Yao, Yue Qiu

Abstract:

This paper deals with a portfolio selection problem based on the possibility theory under the assumption that the returns of assets are LR-type fuzzy numbers. A possibilistic portfolio model with transaction costs is proposed, in which the possibilistic mean value of the return is termed measure of investment return, and the possibilistic variance of the return is termed measure of investment risk. Due to considering transaction costs, the existing traditional optimization algorithms usually fail to find the optimal solution efficiently and heuristic algorithms can be the best method. Therefore, a particle swarm optimization is designed to solve the corresponding optimization problem. At last, a numerical example is given to illustrate our proposed effective means and approaches.

Keywords: Possibility theory, portfolio selection, transaction costs, particle swarm optimization.

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Authors: A. Peter Amala Sujith, T.V. Hymavathi, P. Yasoda Devi

Abstract:

Lutein is a dietary oxycarotenoid which is found to reduce the risks of Age-related Macular Degeneration (AMD). Supercritical fluid extraction of lutein esters from marigold petals was carried out and was found to be much effective than conventional solvent extraction. The saponification of pre-concentrated lutein esters to produce free lutein was studied which showed a composition of about 88% total carotenoids (UV-VIS spectrophotometry) and 90.7% lutein (HPLC). The lipase catalyzed hydrolysis of lutein esters in conventional medium was investigated. The optimal temperature, pH, enzyme concentration and water activity were found to be 50°C, 7, 15% and 0.33 respectively and the activity loss of lipase was about 25% after 8 times re-use in at 50°C for 12 days. However, the lipase catalyzed hydrolysis of lutein esters in conventional media resulted in poor conversions (16.4%).

Keywords: lutein, preconcentration, saponification, lipase

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