Search results for: robust optimization.

Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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In this paper, we focus on the importance of scalable architecture for data centers and buildings in general to help an enterprise achieve environmental sustainability. The scalable architecture helps in many ways, such as adaptability to the business and user requirements, promotes high availability and disaster recovery solutions that are cost effective and low maintenance. The scalable architecture also plays a vital role in three core areas of sustainability: economy, environment, and social, which are also known as the 3 pillars of a sustainability model. If the architecture is scalable, it has many advantages. A few examples are that scalable architecture helps businesses and industries to adapt to changing technology, drive innovation, promote platform independence, and build resilience against natural disasters. Most importantly, having a scalable architecture helps industries bring in cost-effective measures for energy consumption, reduce wastage, increase productivity, and enable a robust environment. It also helps in the reduction of carbon emissions with advanced monitoring and metering capabilities. Scalable architectures help in reducing waste by optimizing the designs to utilize materials efficiently, minimize resources, decrease carbon footprints by using low-impact materials that are environmentally friendly. In this paper we also emphasize the importance of cultural shift towards the reuse and recycling of natural resources for a balanced ecosystem and maintain a circular economy. Also, since all of us are involved in the use of computers, much of the scalable architecture we have studied is related to data centers.

Keywords: Scalable Architectures, Sustainability, Application Design, Disruptive Technology, Machine Learning, Natural Language Processing, AI, Social Media Platform, Cloud Computing, Advanced Networking, Storage Devices, Advanced Monitoring, Metering Infrastructure, Climate change.

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Authors: Ninlawat Phuangchoke, Waraporn Viyanon, Setta Sasananan

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The most important process of the water treatment plant process is coagulation, which uses alum and poly aluminum chloride (PACL). Therefore, determining the dosage of alum and PACL is the most important factor to be prescribed. This research applies an artificial neural network (ANN), which uses the Levenberg–Marquardt algorithm to create a mathematical model (Soft Jar Test) for chemical dose prediction, as used for coagulation, such as alum and PACL, with input data consisting of turbidity, pH, alkalinity, conductivity, and, oxygen consumption (OC) of the Bangkhen Water Treatment Plant (BKWTP), under the authority of the Metropolitan Waterworks Authority of Thailand. The data were collected from 1 January 2019 to 31 December 2019 in order to cover the changing seasons of Thailand. The input data of ANN are divided into three groups: training set, test set, and validation set. The coefficient of determination and the mean absolute errors of the alum model are 0.73, 3.18 and the PACL model are 0.59, 3.21, respectively.

Keywords: Soft jar test, jar test, water treatment plant process, artificial neural network.

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Authors: S. P. Jordan, G. Christian, S. P. Jeffs

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Modern composite materials are increasingly being chosen in replacement of heavier metallic material systems within many engineering fields including aerospace and automotive industries. The increasing push towards satisfying environmental targets are fuelling new material technologies and manufacturing processes. This paper will introduce materials and manufacturing processes using metal matrix composites along with manufacturing processes optimized at Alvant Ltd., based in Basingstoke in the UK which offers modern, cost effective, selectively reinforced composites for light-weighting applications within engineering. An overview and introduction into modern optimized manufacturing methods capable of producing viable replacements for heavier metallic and lower temperature capable polymer composites are offered. A review of the capabilities and future applications of this viable material is discussed to highlight the potential involved in further optimization of old manufacturing techniques, to fully realize the potential to lightweight material using cost-effective methods.

Keywords: Aluminum matrix composites, light-weighting, hybrid squeeze casting, strategically placed reinforcements.

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Authors: V. Goremikins, K. Rocens, D. Serdjuks

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Suspended cable structures are most preferable for large spans covering due to rational use of structural materials, but the problem of suspended cable structures is initial shape change under the action of non-symmetrical load. The problem can be solved by increasing of relation of dead weight and imposed load, but this methods cause increasing of materials consumption.Prestressed cable truss usage is another way how the problem of shape change under the action of non-symmetrical load can be fixed. The better results can be achieved if we replace top chord with cable truss with cross web. Rational structure of the cable truss for prestressed cable truss top chord was developed using optimization realized in FEM program ANSYS 12 environment. Single cable and cable truss model work was discovered.Analytical and model testing results indicate, that usage of cable truss with the cross web as a top chord of prestressed cable truss instead of single cable allows to reduce total displacements by 13-16% in the case of non-symmetrical load. In case of uniformly distributed load single cable is preferable.

Keywords: Cable trusses, Non-symmetrical load, Cable truss models, Vertical displacements

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Authors: Ahmad Yame, Ahad Ali, Badih Jawad, Daw Al-Werfalli Mohamed Nasser, Sabah Abro

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Industries in general have a lot of waste. Wool textile company, Baniwalid, Libya has many complex problems that led to enormous waste generated due to the lack of lean strategies, expertise, technical support and commitment. To successfully address waste at wool textile company, this study will attempt to develop a methodical approach that integrates lean manufacturing tools to optimize performance characteristics such as lead time and delivery. This methodology will utilize Value Stream Mapping (VSM) techniques to identify the process variables that affect production. Once these variables are identified, Design of Experiments (DOE) Methodology will be used to determine the significantly influential process variables, these variables are then controlled and set at their optimal to achieve optimal levels of productivity, quality, agility, efficiency and delivery to analyze the outputs of the simulation model for different lean configurations. The goal of this research is to investigate how the tools of lean manufacturing can be adapted from the discrete to the continuous manufacturing environment and to evaluate their benefits at a specific industrial.

Keywords: Lean manufacturing, DOE, value stream mapping, textiles.

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Authors: Rafał Adamczak

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State-of-the-art methods for secondary structure (Porter, Psi-PRED, SAM-T99sec, Sable) and solvent accessibility (Sable, ACCpro) predictions use evolutionary profiles represented by the position specific scoring matrix (PSSM). It has been demonstrated that evolutionary profiles are the most important features in the feature space for these predictions. Unfortunately applying PSSM matrix leads to high dimensional feature spaces that may create problems with parameter optimization and generalization. Several recently published suggested that applying feature extraction for the PSSM matrix may result in improvements in secondary structure predictions. However, none of the top performing methods considered here utilizes dimensionality reduction to improve generalization. In the present study, we used simple and fast methods for features selection (t-statistics, information gain) that allow us to decrease the dimensionality of PSSM matrix by 75% and improve generalization in the case of secondary structure prediction compared to the Sable server.

Keywords: Secondary structure prediction, feature selection, position specific scoring matrix.

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Authors: Peter Benneth, Tsaroh N. Theophilus, Prince Benjamin

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This research work aims at studying the application of Legendre Transformation Method (LTM) to Hamilton Jacobi Bellman (HJB) equation which is an example of optimal control problem. We discuss the steps involved in modelling the HJB equation as it relates to mathematical finance by applying the Ito’s lemma and maximum principle theorem. By applying the LTM and dual theory, the resultant HJB equation is transformed to a linear Partial Differential Equation (PDE). Also, the Optimal Investment Strategy (OIS) and the optimal value function were obtained under the exponential utility function. Furthermore, some numerical results were also presented with observations that the OIS under exponential utility is directly proportional to the appreciation rate of the risky asset and inversely proportional to the instantaneous volatility, predetermined interest rate, risk averse coefficient. Finally, it was observed that the optimal fund size is an increasing function of the risk free interest rate. This result is consistent with some existing results.

Keywords: Legendre transformation method, Optimal investment strategy, Ito’s lemma, Hamilton Jacobi Bellman equation, Geometric Brownian motion, financial market.

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Authors: Rotchanaphan Hengaroonprasan, Malinee Sriariyanun, Prapakorn Tantayotai, Supacharee Roddecha, Kraipat Cheenkachorn

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Lignocellolusic material is a substance that is resistant to be degraded by microorganisms or hydrolysis enzymes. To be used as materials for biofuel production, it needs pretreatment process to improve efficiency of hydrolysis. In this work, chemical pretreatments on rice straw using three diluted organic acids, including acetic acid, citric acid, oxalic acid, were optimized. Using Response Surface Methodology (RSM), the effect of three pretreatment parameters, acid concentration, treatment time, and reaction temperature, on pretreatment efficiency were statistically evaluated. The results indicated that dilute oxalic acid pretreatment led to the highest enhancement of enzymatic saccharification by commercial cellulase and yielded sugar up to 10.67 mg/ml when using 5.04% oxalic acid at 137.11 oC for 30.01 min. Compared to other acid pretreatment by acetic acid, citric acid, and hydrochloric acid, the maximum sugar yields are 7.07, 6.30, and 8.53 mg/ml, respectively. Here, it was demonstrated that organic acids can be used for pretreatment of lignocellulosic materials to enhance of hydrolysis process, which could be integrated to other applications for various biorefinery processes. 

Keywords: Lignocellolusic biomass, pretreatment, organic acid response surface methodology, biorefinery.

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Authors: M. Rajasimman, K. Murugaiyan

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In this work, sorption of nickel from aqueous solution on hypnea valentiae, red macro algae, was investigated. Batch experiments have been carried out to find the effect of various parameters such as pH, temperature, sorbent dosage, metal concentration and contact time on the sorption of nickel using hypnea valentiae. Response surface methodology (RSM) is employed to optimize the process parameters. Based on the central composite design, quadratic model was developed to correlate the process variables to the response. The most influential factor on each experimental design response was identified from the analysis of variance (ANOVA). The optimum conditions for the sorption of nickel were found to be: pH – 5.1, temperature – 36.8oC, sorbent dosage – 5.1 g/L, metal concentration – 100 mg/L and contact time – 30 min. At these optimized conditions the maximum removal of nickel was found to be 91.97%. A coefficient of determination R2 value 0.9548 shows the fitness of response surface methodology in this work.

Keywords: Optimization, metal, Hypnea valentia, response surface methodology, red algae.

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Authors: Harish Kumar Ponnappan, Joseph C. Chen

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The main objective of this research is to optimize the surface roughness of a milling operation on AISI 1018 steel using live tooling on a HAAS ST-20 lathe. In this study, Taguchi analysis is used to optimize the milling process by investigating the effect of different machining parameters on surface roughness. The L₉ orthogonal array is designed with four controllable factors with three different levels each and an uncontrollable factor, resulting in 18 experimental runs. The optimal parameters determined from Taguchi analysis were feed rate – 76.2 mm/min, spindle speed 1150 rpm, depth of cut – 0.762 mm and 2-flute TiN coated high-speed steel as tool material. The process capability Cp and process capability index Cpk values were improved from 0.62 and -0.44 to 1.39 and 1.24 respectively. The average surface roughness values from the confirmation runs were 1.30 µ, decreasing the defect rate from 87.72% to 0.01%. The purpose of this study is to efficiently utilize the Taguchi design to optimize the surface roughness in a milling operation using live tooling.

Keywords: Live tooling, surface roughness, Taguchi analysis, Computer Numerical Control (CNC) milling operation, CNC turning operation.

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Authors: Rabia Korkmaz Tan, Şebnem Bora

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The major problem encountered when modeling complex systems with agent-based modeling and simulation techniques is the existence of large parameter spaces. A complex system model cannot be expected to reflect the whole of the real system, but by specifying the most appropriate parameters, the actual system can be represented by the model under certain conditions. When the studies conducted in recent years were reviewed, it has been observed that there are few studies for parameter tuning problem in agent based simulations, and these studies have focused on tuning parameters of a single model. In this study, an approach of parameter tuning is proposed by using metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colonies (ABC), Firefly (FA) algorithms. With this hybrid structured study, the parameter tuning problems of the models in the different fields were solved. The new approach offered was tested in two different models, and its achievements in different problems were compared. The simulations and the results reveal that this proposed study is better than the existing parameter tuning studies.

Keywords: Parameter tuning, agent based modeling and simulation, metaheuristic algorithms, complex systems.

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Authors: Nader H. Ghareeb, Mohamed S. Gaith, Sayed M. Soleimani

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In modern engineering, weight optimization has a priority during the design of structures. However, optimizing the weight can result in lower stiffness and less internal damping, causing the structure to become excessively prone to vibration. To overcome this problem, active or smart materials are implemented. The coupled electromechanical properties of smart materials, used in the form of piezoelectric ceramics in this work, make these materials well-suited for being implemented as distributed sensors and actuators to control the structural response. The smart structure proposed in this paper is composed of a cantilevered steel beam, an adhesive or bonding layer, and a piezoelectric actuator. The static deflection of the structure is derived as function of the piezoelectric voltage, and the outcome is compared to theoretical and experimental results from literature. The relation between the voltage and the piezoelectric moment at both ends of the actuator is also investigated and a reduced finite element model of the smart structure is created and verified. Finally, a linear controller is implemented and its ability to attenuate the vibration due to the first natural frequency is demonstrated.

Keywords: Active linear control, Lyapunov stability theorem, piezoelectricity, smart structure, static deflection.

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Authors: Mohammad Reza Sedighi, Behnam Nilforooshan Dardashti

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The high temperature degree and uniform Temperature Distribution (TD) on surface of cookware which contact with food are effective factors for improving cookware application. Additionally, the ability of pan material in retaining the heat and nonreactivity with foods are other significant properties. It is difficult for single material to meet a wide variety of demands such as superior thermal and chemical properties. Multi-Layer Plate (MLP) makes more regular TD. In this study the main objectives are to find the best structure (single or multi-layer) and materials to provide maximum temperature degree and uniform TD up side surface of pan. And also heat retaining of used metals with goal of improving the thermal quality of pan to economize the energy. To achieve this aim were employed Finite Element Method (FEM) for analyzing transient thermal behavior of applied materials. The analysis has been extended for different metals, we achieved the best temperature profile and heat retaining in Copper/ Stainless Steel MLP.

Keywords: Cookware, Energy optimization, Heat retaining, Laminated plate, Temperature distribution

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Authors: Zullina H. Shaari, Amzairi Amar, Abdul Mutalib Embong, Hezlina Hashim

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University websites are considered as one of the brand primary touch points for multiple stakeholders, but most of them did not have great designs to create favorable impressions. Some of the elements that web designers should carefully consider are the appearance, the content, the functionality, usability and search engine optimization. However, priority should be placed on website simplicity and negative space. In terms of content, previous research suggests that universities should include reputation, learning environment, graduate career prospects, image destination, cultural integration, and virtual tour on their websites. The study examines how top 200 world ranking science and technology-based universities present their brands online and whether the websites capture the content dimensions. Content analysis of the websites revealed that the top ranking universities captured these dimensions at varying degree. Besides, the UK-based university had better priority on website simplicity and negative space compared to the Malaysian-based university.

Keywords: Science and technology programs, top-ranked universities, online brands, university websites.

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Authors: Hamidullah Binol, Abdullah Bal

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Nowadays, food safety is a great public concern; therefore, robust and effective techniques are required for detecting the safety situation of goods. Hyperspectral Imaging (HSI) is an attractive material for researchers to inspect food quality and safety estimation such as meat quality assessment, automated poultry carcass inspection, quality evaluation of fish, bruise detection of apples, quality analysis and grading of citrus fruits, bruise detection of strawberry, visualization of sugar distribution of melons, measuring ripening of tomatoes, defect detection of pickling cucumber, and classification of wheat kernels. HSI can be used to concurrently collect large amounts of spatial and spectral data on the objects being observed. This technique yields with exceptional detection skills, which otherwise cannot be achieved with either imaging or spectroscopy alone. This paper presents a nonlinear technique based on kernel Fukunaga-Koontz transform (KFKT) for detection of fat content in ground meat using HSI. The KFKT which is the nonlinear version of FKT is one of the most effective techniques for solving problems involving two-pattern nature. The conventional FKT method has been improved with kernel machines for increasing the nonlinear discrimination ability and capturing higher order of statistics of data. The proposed approach in this paper aims to segment the fat content of the ground meat by regarding the fat as target class which is tried to be separated from the remaining classes (as clutter). We have applied the KFKT on visible and nearinfrared (VNIR) hyperspectral images of ground meat to determine fat percentage. The experimental studies indicate that the proposed technique produces high detection performance for fat ratio in ground meat.

Keywords: Food (Ground meat) inspection, Fukunaga-Koontz transform, hyperspectral imaging, kernel methods.

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Authors: Mohammad Beyki, Justus Pawlak, Robert Patzke, Franz Renz

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In the context of planetary exploration, the MIMOS II (miniaturized M¨ossbauer spectrometer) serves as a proven and reliable measuring instrument. The transmission behaviour of the electronics in the M¨ossbauer spectroscopy is further developed and optimized. For this purpose, the overall electronics is split into three parts. This elaboration deals exclusively with the first part of the signal chain for the evaluation of photons in experiments with gamma radiation. Parallel to the analysis of the electronics, an additional method for analysing the stability of linear and non-linear systems is presented: The extended method of Lyapunov’s stability criteria. The design helps to weigh advantages and disadvantages against other simulated circuits in order to optimize the MIMOS II for the terestric and extraterestric measurment. Finally, after stability analysis, the controller design according to Ackermann is performed, achieving the best possible optimization of the output variable through a skillful pole assignment.

Keywords: Controller design for MIMOS II, stability analysis, M¨ossbauer spectroscopy, electronic signal amplifier, light processing technology, photocurrent, transimpedance amplifier, extended Lyapunov method.

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Authors: Jingya Liu, Yue Wu, Jiabin Luo

Abstract:

This work investigates an intermodal transportation system for delivering goods from a Regional Distribution Centre to supermarkets on the Isle of Wight (IOW) via the port of Southampton or Portsmouth in the UK. We consider this integrated logistics chain as a 3-echelon transportation system. In such a system, there are two types of transport methods used to deliver goods across the Solent Channel: one is accompanied transport, which is used by most supermarkets on the IOW, such as Spar, Lidl and Co-operative food; the other is unaccompanied transport, which is used by Aldi. Five transport scenarios are studied based on different transport modes and ferry routes. The aim is to determine an optimal delivery plan for supermarkets of different business scales on IOW, in order to minimise the total running cost, fuel consumptions and carbon emissions. The problem is modelled as a vehicle routing problem with time windows and solved by genetic algorithm. The computing results suggested that accompanied transport is more cost efficient for small and medium business-scale supermarket chains on IOW, while unaccompanied transport has the potential to improve the efficiency and effectiveness of large business scale supermarket chains.

Keywords: Genetic algorithm, intermodal transport system, Isle of Wight, optimization, supermarket.

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Authors: Sara Mohtashami, Habib Rajabi Mashhadi

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With the growth of electricity generation from gas energy gas pipeline reliability can substantially impact the electric generation. A physical disruption to pipeline or to a compressor station can interrupt the flow of gas or reduce the pressure and lead to loss of multiple gas-fired electric generators, which could dramatically reduce the supplied power and threaten the power system security. Gas pressure drops during peak loading time on pipeline system, is a common problem in network with no enough transportation capacity which limits gas transportation and causes many problem for thermal domain power systems in supplying their demand. For a feasible generation scheduling planning in networks with no sufficient gas transportation capacity, it is required to consider gas pipeline constraints in solving the optimization problem and evaluate the impacts of gas consumption in power plants on gas pipelines operating condition. This paper studies about operating of gas fired power plants in critical conditions when the demand of gas and electricity peak together. An integrated model of gas and electric model is used to consider the gas pipeline constraints in the economic dispatch problem of gas-fueled thermal generator units.

Keywords:

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Authors: Abbas Al-Refaie, Nour Bata

Abstract:

A distributor of Apple products' experiences numerous difficulties in developing marketing strategies for new and existing mobile product entries that maximize customer satisfaction and the firm's profitability. This research, therefore, integrates market segmentation in platform-based product family design and conjoint analysis to identify iSystem combinations that increase customer satisfaction and business profits. First, the enhanced market segmentation grid is created. Then, the estimated demand model is formulated. Finally, the profit models are constructed then used to determine the ideal product family design that maximizes profit. Conjoint analysis is used to explore customer preferences with their satisfaction levels. A total of 200 surveys are collected about customer preferences. Then, simulation is used to determine the importance values for each attribute. Finally, sensitivity analysis is conducted to determine the product family design that maximizes both objectives. In conclusion, the results of this research shall provide great support to Apple distributors in determining the best marketing strategies that enhance their market share.

Keywords: Market segmentation, conjoint analysis, market strategies, optimization.

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Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

Abstract:

Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA.

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Authors: Rohith K Reddy, David Mayerich, Michael Walsh, P Scott Carney, Rohit Bhargava

Abstract:

Fourier transform infrared (FT-IR) spectroscopic imaging is an emerging technique that provides both chemically and spatially resolved information. The rich chemical content of data may be utilized for computer-aided determinations of structure and pathologic state (cancer diagnosis) in histological tissue sections for prostate cancer. FT-IR spectroscopic imaging of prostate tissue has shown that tissue type (histological) classification can be performed to a high degree of accuracy [1] and cancer diagnosis can be performed with an accuracy of about 80% [2] on a microscopic (≈ 6μm) length scale. In performing these analyses, it has been observed that there is large variability (more than 60%) between spectra from different points on tissue that is expected to consist of the same essential chemical constituents. Spectra at the edges of tissues are characteristically and consistently different from chemically similar tissue in the middle of the same sample. Here, we explain these differences using a rigorous electromagnetic model for light-sample interaction. Spectra from FT-IR spectroscopic imaging of chemically heterogeneous samples are different from bulk spectra of individual chemical constituents of the sample. This is because spectra not only depend on chemistry, but also on the shape of the sample. Using coupled wave analysis, we characterize and quantify the nature of spectral distortions at the edges of tissues. Furthermore, we present a method of performing histological classification of tissue samples. Since the mid-infrared spectrum is typically assumed to be a quantitative measure of chemical composition, classification results can vary widely due to spectral distortions. However, we demonstrate that the selection of localized metrics based on chemical information can make our data robust to the spectral distortions caused by scattering at the tissue boundary.

Keywords: Infrared, Spectroscopy, Imaging, Tissue classification

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Authors: Wahab Ali Shah, Junjia He

Abstract:

Transferring electrical power without any wiring has been a dream since late 19^th century. There were some advances in this area as to know more about microwave systems. However, this subject has recently become very attractive due to their practiScal systems. There are low power applications such as charging the batteries of contactless tooth brushes or implanted devices, and higher power applications such as charging the batteries of electrical automobiles or buses. In the first group of applications operating frequencies are in microwave range while the frequency is lower in high power applications. In the latter, the concept is also called inductive power transfer. The aim of the paper is to have an overview of the inductive power transfer for electrical vehicles with a special concentration on coil design and power converter simulation for static charging. Coil design is very important for an efficient and safe power transfer. Coil design is one of the most critical tasks. Power converters are used in both side of the system. The converter on the primary side is used to generate a high frequency voltage to excite the primary coil. The purpose of the converter in the secondary is to rectify the voltage transferred from the primary to charge the battery. In this paper, an inductive power transfer system is studied. Inductive power transfer is a promising technology with several possible applications. Operation principles of these systems are explained, and components of the system are described. Finally, a single phase 2 kW system was simulated and results were presented. The work presented in this paper is just an introduction to the concept. A reformed compensation network based on traditional inductor-capacitor-inductor (LCL) topology is proposed to realize robust reaction to large coupling variation that is common in dynamic wireless charging application. In the future, this type compensation should be studied. Also, comparison of different compensation topologies should be done for the same power level.

Keywords: Coil design, contactless charging, electrical automobiles, inductive power transfer, operating frequency.

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Authors: Lady Marianne E. Polinga, Candy C. Mercado, Camilo A. Polinga

Abstract:

This study was an investigation on the suitability of Lahar/HDPE composite as a primary material for low-cost smallscale biogas digesters. While sources of raw materials for biogas are abundant in the Philippines, cost of the technology has made the widespread utilization of this resource an indefinite proposition. Aside from capital economics, another problem arises with space requirements of current digester designs. These problems may be simultaneously addressed by fabricating digesters on a smaller, household scale to reach a wider market, and to use materials that may accommodate optimization of overall design and fabrication cost without sacrificing operational efficiency. This study involved actual fabrication of the Lahar/HDPE composite at varying composition and geometry, subsequent mechanical and thermal characterization, and implementation of Statistical Analysis to find intrinsic relationships between variables. From the results, Lahar/HDPE composite was found to be feasible for use as digester material from both mechanical and economic standpoints. 

Keywords: Biogas digester, Composite, High density polyethylene, Lahar.

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Authors: Seema Chopra, R. Mitra, Vijay Kumar

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In this paper, a neural network tuned fuzzy controller is proposed for controlling Multi-Input Multi-Output (MIMO) systems. For the convenience of analysis, the structure of MIMO fuzzy controller is divided into single input single-output (SISO) controllers for controlling each degree of freedom. Secondly, according to the characteristics of the system-s dynamics coupling, an appropriate coupling fuzzy controller is incorporated to improve the performance. The simulation analysis on a two-level mass–spring MIMO vibration system is carried out and results show the effectiveness of the proposed fuzzy controller. The performance though improved, the computational time and memory used is comparatively higher, because it has four fuzzy reasoning blocks and number may increase in case of other MIMO system. Then a fuzzy neural network is designed from a set of input-output training data to reduce the computing burden during implementation. This control strategy can not only simplify the implementation problem of fuzzy control, but also reduce computational time and consume less memory.

Keywords: Fuzzy Control, Neural Network, MIMO System, Optimization of Membership functions.

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Authors: Mohamed Watfa, William Daher, Hisham Al Azar

Abstract:

The main idea behind in network aggregation is that, rather than sending individual data items from sensors to sinks, multiple data items are aggregated as they are forwarded by the sensor network. Existing sensor network data aggregation techniques assume that the nodes are preprogrammed and send data to a central sink for offline querying and analysis. This approach faces two major drawbacks. First, the system behavior is preprogrammed and cannot be modified on the fly. Second, the increased energy wastage due to the communication overhead will result in decreasing the overall system lifetime. Thus, energy conservation is of prime consideration in sensor network protocols in order to maximize the network-s operational lifetime. In this paper, we give an energy efficient approach to query processing by implementing new optimization techniques applied to in-network aggregation. We first discuss earlier approaches in sensors data management and highlight their disadvantages. We then present our approach “Energy Efficient Indexed Aggregation" (EEIA) and evaluate it through several simulations to prove its efficiency, competence and effectiveness.

Keywords: Sensor Networks, Data Base, Data Fusion, Aggregation, Indexing, Energy Efficiency

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Authors: Hamed K. Arzani, Ahmad Amiri, Hamid K. Arzani, Salim Newaz Kazi, Ahmad Badarudin

Abstract:

The new design of heat exchangers utilizing an annular distributor opens a new gateway for realizing higher energy optimization. To realize this goal, graphene nanoplatelet-based water nanofluids with promising thermophysical properties were synthesized in the presence of covalent and noncovalent functionalization. Thermal conductivity, density, viscosity and specific heat capacity were investigated and employed as a raw data for ANSYS-Fluent to be used in two-phase approach. After validation of obtained results by analytical equations, two special parameters of convective heat transfer coefficient and pressure drop were investigated. The study followed by studying other heat transfer parameters of annular pass in the presence of graphene nanopletelesbased water nanofluids at different weight concentrations, input powers and temperatures. As a result, heat transfer performance and friction loss are predicted for both synthesized nanofluids.

Keywords: Heat transfer, nanofluid, turbulent flow, forced convection flow, graphene nanoplatelet.

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Authors: Javier Barrachina, Piedad Garrido, Manuel Fogue, Julio A. Sanguesa, Francisco J. Martinez

Abstract:

It is very common to observe, especially in Computer Science studies that students have difficulties to correctly understand how some mechanisms based on Artificial Intelligence work. In addition, the scope and limitations of most of these mechanisms are usually presented by professors only in a theoretical way, which does not help students to understand them adequately. In this work, we focus on the problems found when teaching Evolutionary Algorithms (EAs), which imitate the principles of natural evolution, as a method to solve parameter optimization problems. Although this kind of algorithms can be very powerful to solve relatively complex problems, students often have difficulties to understand how they work, and how to apply them to solve problems in real cases. In this paper, we present two interactive graphical applications which have been specially designed with the aim of making Evolutionary Algorithms easy to be understood by students. Specifically, we present: (i) TSPS, an application able to solve the ”Traveling Salesman Problem”, and (ii) FotEvol, an application able to reconstruct a given image by using Evolution Strategies. The main objective is that students learn how these techniques can be implemented, and the great possibilities they offer.

Keywords: Education, evolutionary algorithms, evolution strategies, interactive learning applications.

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Authors: M. Maleki, M. Latifi, M. Amani-Tehran

Abstract:

Nano fibers produced by electrospinning are of industrial and scientific attention due to their special characteristics such as long length, small diameter and high surface area. Applications of electrospun structures in nanotechnology are included tissue scaffolds, fibers for drug delivery, composite reinforcement, chemical sensing, enzyme immobilization, membrane-based filtration, protective clothing, catalysis, solar cells, electronic devices and others. Many polymer and ceramic precursor nano fibers have been successfully electrospun with diameters in the range from 1 nm to several microns. The process is complex so that fiber diameter is influenced by various material, design and operating parameters. The objective of this work is to apply genetic algorithm on the parameters of electrospinning which have the most significant effect on the nano fiber diameter to determine the optimum parameter values before doing experimental set up. Effective factors including initial polymer concentration, initial jet radius, electrical potential, relaxation time, initial elongation, viscosity and distance between nozzle and collector are considered to determine finest diameter which is selected by user.

Keywords: Electrospinning, genetic algorithm, nano fiber diameter, optimization.

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Authors: Marina Franulovic, Robert Basan, Bozidar Krizan

Abstract:

Constitutive modeling of material behavior is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behavior of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behavior modeling.

Keywords: Genetic algorithm, kinematic hardening, material model, objective function

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

Abstract:

The aim of this work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. With our research and based on a feature selection in different phases, we are trying to design a neural network system with an optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each region of interest (ROI), 6 distinct sets of texture features are extracted such as: first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. When analyzing more phases, we show that the injection of liquid cause changes to the high relevant features in each region. Our results demonstrate that for detecting HCC tumor phase 3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between pathology and healthy classes, according to our method, relates to first order histogram parameters with accuracy of 85% in phase 1, 95% in phase 2, and 95% in phase 3.

Keywords: Feature selection, Multi-phasic liver images, Neural network, Texture analysis.

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