Search results for: Investment cost recovery

Authors: Lindawati Ismail, Mohd. Imran Ghazali, Shahruddin Mahzan, Ahmad Mujahid Ahmad Zaidi

Abstract:

Arenga pinnata is an abundantly natural fiber that can be used for sound proof material. However, the scientific data of acoustics properties of Arenga pinnata was not available yet. In this study the sound absorption of pure arenga pinnata was measured. The thickness of Arenga pinnata was varied in 10 mm, 20 mm, 30mm, and 40mm. This work was carried out to investigate the potential of using Arenga pinnata fiber as raw material for sound absorbing material. Impedance Tube Method was used to measure sound absorption coefficient (α). The Measurements was done in accordance with ASTM E1050-98, that is the standard test method for impedance and absorption of acoustical materials using a tube, two microphones and a digital frequency analysis system . The results showed that sound absorption coefficients of Arenga pinnata were good from 2000 Hz to 5000 Hz within the range of 0.75 – 0.90. The optimum sound absorption coefficient was obtained from the thickness of 40 mm. These results indicated that Arenga pinnata fiber is promising to be used as raw material of sound absorbing material with low cost, light, and biodegradable.

Keywords: Sound absorption, Arenga pinnata, raw material.

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Authors: Shuen-Tai Wang, Yu-Ching Lin, Hsi-Ya Chang

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Cloud computing is the innovative and leading information technology model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. This paper presents our development on enabling an individual user's desktop in a virtualized environment, which is stored on a remote virtual machine rather than locally. We present the initial work on the integration of virtual desktop and application sharing with virtualization technology. Given the development of remote desktop virtualization, this proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the cost of software licenses and platform maintenances. Moreover, this development also helps boost user productivity by promoting a flexible model that lets users access their desktop environments from virtually anywhere.

Keywords: Cloud Computing, Virtualization, Virtual Desktop, Elastic Environment.

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Authors: Funmilayo L. Amao

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As a result of the high cost of housing, the increasing population is forced to live in substandard housing and unhealthy conditions giving rise to poor residential neighborhoods. The paper examines the causes and characteristics of poor residential neighborhood. The paper finds the problems that have influence poor neighborhoods to; poverty, growth of informal sector and housing shortage. The paper asserts that poor residential neighborhoods have adverse effects on the people.

The secondary data was obtained from books, journals and seminar papers while primary data relating to building and environmental quality from structured questionnaire administered on sample of 500 household heads, from sampling frame of 5000 housing units.

The study reveals that majority of the respondents are poor and employed in informal sector. The paper suggests urban renewal and slum upgrading programs as methods in dealing with the situation and an improvement in the socio-economic circumstances of the inhabitants.

Keywords: Environmental Degeneration, Housing, Poverty, Quality of life, Urban Upgrading.

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Authors: Shohreh Ajoudanian, Mohammad Davarpanah Jazi

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The rapid expansion of the web is causing the constant growth of information, leading to several problems such as increased difficulty of extracting potentially useful knowledge. Web content mining confronts this problem gathering explicit information from different web sites for its access and knowledge discovery. Query interfaces of web databases share common building blocks. After extracting information with parsing approach, we use a new data mining algorithm to match a large number of schemas in databases at a time. Using this algorithm increases the speed of information matching. In addition, instead of simple 1:1 matching, they do complex (m:n) matching between query interfaces. In this paper we present a novel correlation mining algorithm that matches correlated attributes with smaller cost. This algorithm uses Jaccard measure to distinguish positive and negative correlated attributes. After that, system matches the user query with different query interfaces in special domain and finally chooses the nearest query interface with user query to answer to it.

Keywords: Content mining, complex matching, correlation mining, information extraction.

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Authors: Debabrata Mazumder

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Constructed and natural wetlands are being used extensively to treat different types of wastewater including the domestic one. Considerable removal efficiency has been achieved for a variety of pollutants like BOD, nitrogen and phosphorous in the wetlands. Wetland treatment appears to be the best choice for treatment or pre-treatment of wastewater because of the low maintenance cost and simplicity of operation. Wetlands are the natural exporters of organic carbon on account of decomposition of organic matter. The emergent plants like reeds, bulrushes and cattails are commonly used in constructed wetland for the treatment process providing surface for bacterial growth, filtration of solids, nutrient uptake and oxygenation to promote nitrification as well as denitrification. The present paper explored different scopes of organic matter (BOD), nitrogen and phosphorous removal from wastewater through wetlands. Emphasis is given to look into the soil chemistry for tracing the behavior of carbon, nitrogen and phosphorus in the wetland. Due consideration is also made to see the viability for upgrading the BOD, nitrogen and phosphorus removal efficiency through different classical modifications of wetland.

Keywords: BOD removal, modification, nitrogen removal, phosphorous removal, wetland.

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Authors: Chun Hsiang Yang, Cheng Chia Lee, Chiun Hsun Chen

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In this study, the effects of biogas fuels on the performance of an annular micro gas turbine (MGT) were assessed experimentally and numerically. In the experiments, the proposed MGT system was operated successfully under each test condition; minimum composition to the fuel with the biogas was roughly 50% CH4 with 50% CO2. The power output was around 170W at 85,000 RPM as 90% CH4 with 10% CO2 was used and 70W at 65,000 RPM as 70% CH4 with 30% CO2 was used. When a critical limit of 60% CH4 was reached, the power output was extremely low. Furthermore, the theoretical Brayton cycle efficiency and electric efficiency of the MGT were calculated as 23% and 10%, respectively. Following the experiments, the measured data helped us identify the parameters of dynamic model in numerical simulation. Additionally, a numerical analysis of re-designed combustion chamber showed that the performance of MGT could be improved by raising the temperature at turbine inlet. This study presents a novel distributed power supply system that can utilize renewable biogas. The completed micro biogas power supply system is small, low cost, easy to maintain and suited to household use.

Keywords: Micro Gas Turbine, Biogas; System Identification, Distributed power supply system

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Authors: Venny, S. Gan, H. K. Ng

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The performance of modified Fenton (MF) treatment to promote PAH oxidation in artificially contaminated soil was investigated in packed soil column with a hydrogen peroxide (H2O2) delivery system simulating in situ injection. Soil samples were spiked with phenanthrene (low molecular weight PAH) and fluoranthene (high molecular weight PAH) to an initial concentration of 500 mg/kg dried soil each. The effectiveness of process parameters H2O2/soil, iron/soil, chelating agent/soil weight ratios and reaction time were studied using a 24 three level factorial design experiments. Statistically significant quadratic models were developed using Response Surface Methodology (RSM) for degrading PAHs from the soil samples. Optimum operating condition was achieved at mild range of H2O2/soil, iron/soil and chelating agent/soil weight ratios, indicating cost efficient method for treating highly contaminated lands.

Keywords: Fenton, polycyclic aromatic hydrocarbon, chelate, response surface methodology

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Authors: Chansiri Singhtaun, Nattaporn Prasartthong

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The purpose of this research is to reduce the amount of incomplete coating of stainless steel washers in the electrodeposition painting process by using an experimental design technique. The surface preparation was found to be a major cause of painted surface quality. The influence of pretreating and painting process parameters, which are cleaning time, chemical concentration and shape of hanger were studied. A 23 factorial design with two replications was performed. The analysis of variance for the designed experiment showed the great influence of cleaning time and shape of hanger. From this study, optimized cleaning time was determined and a newly designed electrical conductive hanger was proved to be superior to the original one. The experimental verification results showed that the amount of incomplete coating defects decreased from 4% to 1.02% and operation cost decreased by 10.5%.

Keywords: Defect reduction, design of experiments, electrodeposition painting, stainless steel.

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Authors: Li-Yeh Chuang, Yu-Jen Hou, Jr., Cheng-Hong Yang

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Single nucleotide polymorphisms (SNPs) hold much promise as a basis for disease-gene association. However, research is limited by the cost of genotyping the tremendous number of SNPs. Therefore, it is important to identify a small subset of informative SNPs, the so-called tag SNPs. This subset consists of selected SNPs of the genotypes, and accurately represents the rest of the SNPs. Furthermore, an effective evaluation method is needed to evaluate prediction accuracy of a set of tag SNPs. In this paper, a genetic algorithm (GA) is applied to tag SNP problems, and the K-nearest neighbor (K-NN) serves as a prediction method of tag SNP selection. The experimental data used was taken from the HapMap project; it consists of genotype data rather than haplotype data. The proposed method consistently identified tag SNPs with considerably better prediction accuracy than methods from the literature. At the same time, the number of tag SNPs identified was smaller than the number of tag SNPs in the other methods. The run time of the proposed method was much shorter than the run time of the SVM/STSA method when the same accuracy was reached.

Keywords: Genetic Algorithm (GA), Genotype, Single nucleotide polymorphism (SNP), tag SNPs.

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Authors: J. Georgiou, K. Dimitropoulos, A. Manitsaris

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Simulations play a major role in education not only because they provide realistic models with which students can interact to acquire real world experiences, but also because they constitute safe environments in which students can repeat processes without any risk in order to perceive easier concepts and theories. Virtual reality is widely recognized as a significant technological advance that can facilitate learning process through the development of highly realistic 3D simulations supporting immersive and interactive features. The objective of this paper is to analyze the influence of virtual reality-s use in chemistry instruction as well as to present an integrated web-based learning environment for the simulation of chemical experiments. The proposed application constitutes a cost-effective solution for both schools and universities without appropriate infrastructure and a valuable tool for distance learning and life-long education in chemistry. Its educational objectives are the familiarization of students with the equipment of a real chemical laboratory and the execution of virtual volumetric analysis experiments with the active participation of students.

Keywords: Chemistry, simulations, experiments, virtual reality.

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Authors: S. Sarumathi, M. Vaishnavi, S. Geetha, P. Ranjetha

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Machine learning is a new and exciting area of artificial intelligence nowadays. Machine learning is the most valuable, time, supervised, and cost-effective approach. It is not a narrow learning approach; it also includes a wide range of methods and techniques that can be applied to a wide range of complex realworld problems and time domains. Biological image classification, adaptive testing, computer vision, natural language processing, object detection, cancer detection, face recognition, handwriting recognition, speech recognition, and many other applications of machine learning are widely used in research, industry, and government. Every day, more data are generated, and conventional machine learning techniques are becoming obsolete as users move to distributed and real-time operations. By providing fundamental knowledge of machine learning tools and research opportunities in the field, the aim of this article is to serve as both a comprehensive overview and a guide. A diverse set of machine learning resources is demonstrated and contrasted with the key features in this survey.

Keywords: Artificial intelligence, machine learning, deep learning, machine learning algorithms, machine learning tools.

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Authors: A. Lovascio, A. D’Orazio, V. Centonze

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From several years till now the aerospace industry is developing more and more small satellites for Low-Earth Orbit (LEO) missions. Such satellites have a low cost of making and launching since they have a size and weight smaller than other types of satellites. However, because of size limitations, small satellites need integrated electronic equipment based on digital logic. Moreover, the LEOs require telecommunication modules with high throughput to transmit to earth a big amount of data in a short time. In order to meet such requirements, in this paper we propose a Telemetry, Tracking & Command module optimized through the use of the Commercial Off-The-Shelf components. The proposed approach exploits the major flexibility offered by these components in reducing costs and optimizing the performance. The method has been applied in detail for the design of the front-end receiver, which has a low noise figure (1.5 dB) and DC power consumption (smaller than 2 W). Such a performance is particularly attractive since it allows fulfilling the energy budget stringent constraints that are typical for LEO small platforms.

Keywords: COTS, small satellites, sub-sampling, TT&C.

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Authors: Marc C. Robini, Pierre-Jean Viverge, Yuemin Zhu, Jianhua Luo

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The standard approach to image reconstruction is to stabilize the problem by including an edge-preserving roughness penalty in addition to faithfulness to the data. However, this methodology produces noisy object boundaries and creates a staircase effect. The existing attempts to favor the formation of smooth contour lines take the edge field explicitly into account; they either are computationally expensive or produce disappointing results. In this paper, we propose to incorporate the smoothness of the edge field in an implicit way by means of an additional penalty term defined in the wavelet domain. We also derive an efficient half-quadratic algorithm to solve the resulting optimization problem, including the case when the data fidelity term is non-quadratic and the cost function is nonconvex. Numerical experiments show that our technique preserves edge sharpness while smoothing contour lines; it produces visually pleasing reconstructions which are quantitatively better than those obtained without wavelet-domain constraints.

Keywords:

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Authors: Ichihan Tai, Bill Olson, Paul Blessner

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Traditional early warning systems that alarm against crisis are generally based on structured or numerical data; therefore, a system that can make predictions based on unstructured textual data, an uncorrelated data source, is a great complement to the traditional early warning systems. The Chicago Board Options Exchange (CBOE) Volatility Index (VIX), commonly referred to as the fear index, measures the cost of insurance against market crash, and spikes in the event of crisis. In this study, news data is consumed for prediction of whether there will be a market-wide crisis by predicting the movement of the fear index, and the historical references to similar events are presented in an unsupervised manner. Topic modeling-based prediction and representation are made based on daily news data between 1990 and 2015 from The Wall Street Journal against VIX index data from CBOE.

Keywords: Early Warning System, Knowledge Management, Topic Modeling, Market Prediction.

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Authors: Vikas Pandey, T. L. Joshy, Vyshak Vijayan, N. Babu

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A new and cost effective robotic device was designed for remote tele surgery using dual tone multi frequency technology (DTMF). Tele system with Dual Tone Multiple Frequency has a large capability in sending and receiving of data in hardware and software. The robot consists of DC motors for arm movements and it is controlled manually through a mobile phone through DTMF Technology. The system enables the surgeon from base station to send commands through mobile phone to the patient’s robotic system which includes two robotic arms that translate the input into actual instrument manipulation. A mobile phone attached to the microcontroller 8051 which can activate robot through relays. The Remote robot-assisted tele surgery eliminates geographic constraints for getting surgical expertise where it is needed and allows an expert surgeon to teach or proctor the performance of surgical technique by real-time intervention.

Keywords: Robot, Microcontroller, DTMF, Tele surgery.

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Authors: V. Karamzadeh, J. Adhvaryu, A. Chandrasekaran, M. Packirisamy

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In Bulk Acoustic Wave (BAW) microfluidics, the throughput of particle sorting is dependent on the complex interplay between the geometric configuration of the channel, the size of the particles, and the properties of the fluid medium, which therefore calls for a detailed modeling and understanding of the fluid-particle interaction dynamics under an acoustic field, prior to designing the system. In this work, we propose a simplified Bulk acoustophoretic system that can be used for size dependent particle sorting. A Finite Element Method (FEM) based analytical model has been developed to study the dependence of particle sizes on channel parameters, and the sorting efficiency in a given fluid medium. Based on the results, the microfluidic system has been designed to take into account all the variables involved with the underlying physics, and has been fabricated using an additive manufacturing technique employing a commercial 3D printer, to generate a simple, cost-effective system that can be used for size sensitive particle sorting.

Keywords: 3D printing, 3D microfluidic chip, acoustophoresis, cell separation, MEMS, microfluidics.

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Authors: Debajyoti Mishra, Urmila Bhanja

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In this paper, a novel fuzzy approach is developed while solving the Dynamic Routing and Wavelength Assignment (DRWA) problem in optical networks with Wavelength Division Multiplexing (WDM). In this work, the effect of nonlinear and linear impairments such as Four Wave Mixing (FWM) and amplifier spontaneous emission (ASE) noise are incorporated respectively. The novel algorithm incorporates fuzzy logic controller (FLC) to reduce the effect of FWM noise and ASE noise on a requested lightpath referred in this work as FWM aware fuzzy dynamic routing and wavelength assignment algorithm. The FWM crosstalk products and the static FWM noise power per link are pre computed in order to reduce the set up time of a requested lightpath, and stored in an offline database. These are retrieved during the setting up of a lightpath and evaluated online taking the dynamic parameters like cost of the links into consideration.

Keywords: Amplifier spontaneous emission (ASE), Dynamic routing and wavelength assignment, Four wave mixing (FWM), Fuzzy rule based system (FRBS).

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Authors: S. Šupić, M. Malešev, V. Radonjanin, M. Radeka, M. Laban

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The production of low cost and environmentally friendly products represents an important step for developing countries. Biomass is one of the largest renewable energy sources, and Serbia is among the top European countries in terms of the amount of available and unused biomass. Substituting cement with the ashes obtained by the combustion of biomass would reduce the negative impact of concrete industry on the environment and would provide a waste valorization by the reuse of this type of by-product in mortars and concretes manufacture. The study contains data on physical properties, chemical characteristics and pozzolanic properties of obtained biomass ashes: wheat straw ash and mixture of wheat and soya straw ash in Serbia, which were, later, used as supplementary cementitious materials in preparation of mortars. Experimental research of influence of biomass ashes on physical and mechanical properties of cement mortars was conducted. The results indicate that the biomass ashes can be successfully used in mortars as substitutes of cement without compromising their physical and mechanical performances.

Keywords: Biomass, ash, cementitious material, mortar.

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: Information security risk treatment, Selection of risk measures, Risk acceptanceand Multi-objective optimization.

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: Classification, data mining, spam filtering, naive Bayes, decision tree.

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Authors: Shweta Singh, Dipali Bansal, Rashima Mahajan

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Psychoacoustics has become a potential area of research due to the growing interest of both laypersons and medical and mental health professionals. Non invasive brain computer interface like Electroencephalography (EEG) is widely being used in this field. An attempt has been made in this paper to examine the response of EEG signals to acoustic stimuli further analyzing the brain electrical activity. The real time EEG is acquired for 6 participants using a cost effective and portable EMOTIV EEG neuro headset. EEG data analysis is further done using EMOTIV test bench, EDF browser and EEGLAB (MATLAB Tool) application software platforms. Spectral analysis of acquired neural signals (AF3 channel) using these software platforms are clearly indicative of increased brain activity in various bands. The inferences drawn from such an analysis have significant correlation with subject’s subjective reporting of the experiences. The results suggest that the methodology adopted can further be used to assist patients with sleeping and depressive disorders.

Keywords: OM’ chant, Spectral analysis, EDF Browser, EEGLAB, EMOTIV, Real time Acquisition.

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Authors: S. Somaratne, S. R. Weerakoon

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Heavy metal pollution is an environmental concern. Phytoremediation is a low-cost, environmental-friendly approach to solve this problem. Mustard has the potential in reducing heavy metal contents in soils. Among mustard (Brassica juncea (L.) Czern & Coss) genotypes in Sri Lanka, accessions 7788, 8831 and 5088 give significantly a high yield. Therefore, present study was conducted to quantify the phytoextractive potential among these local mustard accessions and to assess the interaction of heavy metals, Pb, Co, Mn on phytoextraction. A pot experiment was designed with acid washed sand (quartz) and a series of heavy metal solutions of 0, 25, 50, 75 and 100 μg/g. Experiment was carried out with factorial experimental design. Mustard accessions were tolerant to heavy metals and could be successfully used in removal of Pb, Co and Mn and they are capable of accumulating significant quantities of heavy metals in vegetative and reproductive organs. The order of the accumulative potential of Pb, Co and Mn in mustard accessions is, root > shoot >seed.

Keywords: Brassica juncea, heavy metal hyper-accumulation, phytoremediation

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Authors: Osamu Saito

Abstract:

Commercial infrastructures intended for use as leisure retreats such as golf and ski resorts have been extensively developed in many rural areas of Japan. However, following the burst of the economic bubble in the 1990s, several existing resorts faced tough management decisions and some were forced to close their business. In this study, six alternative management options for restructuring the existing golf courses (park, cemetery, biofuel production, reforestation, pasturing and abandonment) are examined and their environmental and economic impacts are quantitatively assessed. In addition, restructuring scenarios of these options and an ex-ante assessment model are developed. The scenario analysis by Monte Carlo simulation shows a clear trade-off between GHG savings and benefit/cost (B/C) ratios, of which “Restoring Nature" scenario absorbs the most CO2 among the four scenarios considered, but its B/C ratio is the lowest. This study can be used to select or examine options and scenarios of golf course management and rural environmental management policies.

Keywords: golf courses, restructuring and management options, scenario analysis, Tokyo Metropolitan Area.

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Authors: C. A. Akaash Emmanuel Raj, V. R. Sanal Kumar

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In this paper using smart materials we have proposed a specially manufactured variable volume spin tub for loading clothes for negating the vibration to a certain extent for getting better operating performance. Additionally, we have recommended a variable spinning speed rotor for handling varieties of garments for an efficient washing, aiming for increasing the life span of both the garments and the machine. As a part of the conflicting dynamic constraints and demands of the customer friendly design optimization of a lucrative and cosmetic washing machine we have proposed a drier and a desalination system capable to supply desirable heat and a pleasing fragrance to the garments. We thus concluded that while incorporating variable volume and variable spinning speed tub integrated with a drier and desalination system, the washing machine could meet the varieties of domestic requirements of the customers cost-effectively.

Keywords: Customer friendly washing machine, drier design, quick cloth cleaning, variable tub volume washing machine, variable spinning speed washing machine.

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Authors: Muniyasamy Kalanchiam, Baskar Mannai

Abstract:

Topology Optimization is a defined as the method of determining optimal distribution of material for the assumed design space with functionality, loads and boundary conditions [1]. Topology optimization can be used to optimize shape for the purposes of weight reduction, minimizing material requirements or selecting cost effective materials [2]. Topology optimization has been implemented through the use of finite element methods for the analysis, and optimization techniques based on the method of moving asymptotes, genetic algorithms, optimality criteria method, level sets and topological derivatives. Case study of Typical “Fuselage design" is considered for this paper to explain the benefits of Topology Optimization in the design cycle. A cylindrical shell is assumed as the design space and aerospace standard pay loads were applied on the fuselage with wing attachments as constraints. Then topological optimization is done using Finite Element (FE) based software. This optimization results in the structural concept design which satisfies all the design constraints using minimum material.

Keywords: Fuselage, Topology optimization, payloads, designoptimization, Finite Element Analysis.

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Authors: Prachi Singh

Abstract:

This paper presents a low-cost, eco-friendly and reproducible microbe mediated biosynthesis of TiO₂ nanoparticles. TiO₂ nanoparticles synthesized using the bacterium, Bacillus subtilis, from titanium as a precursor, were confirmed by TEM analysis. The morphological characteristics state spherical shape, with the size of individual or aggregate nanoparticles, around 30-40 nm. Microbial resistance represents a challenge for the scientific community to develop new bioactive compounds. Here, the antibacterial effect of TiO₂ nanoparticles on Escherichia coli was investigated, which was confirmed by CFU (Colony-forming unit). Further, growth curve study of E. coli Hb101 in the presence and absence of TiO₂ nanoparticles was done. Optical density decrease was observed with the increase in the concentration of TiO₂. It could be attributed to the inactivation of cellular enzymes and DNA by binding to electron-donating groups such as carboxylates, amides, indoles, hydroxyls, thiols, etc. which cause little pores in bacterial cell walls, leading to increased permeability and cell death. This justifies that TiO₂ nanoparticles have efficient antibacterial effect and have potential to be used as an antibacterial agent for different purposes.

Keywords: Antibacterial effect, CFU, Escherichia coli Hb101, growth curve, TEM, TiO2 nanoparticle, toxicity, UV-Vis.

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Authors: Zs. Kovács, Zs. J. Viharos, J. Kodácsy

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As a well-known conventional finishing process, the grinding is commonly used to manufacture seal mating surfaces and bearing surfaces, but is also creates twisted surfaces. The machined surfaces by turning or grinding usually have twist structure on the surfaces, which can convey lubricants such as conveyor screw. To avoid this phenomenon, have to use special techniques or machines, for example start-stop turning, tangential turning, ultrasonic protection or special toll geometries. All of these solutions have high cost and difficult usability. In this paper, we describe a system and summarize the results of the experimental research carried out mainly in the field of Magnetic Abrasive Polishing (MAP) and Magnetic Roller Burnishing (MRB). These technologies are simple and also green while able to produce twist-free surfaces. During the tests, C45 normalized steel was used as workpiece material which was machined by simple and Wiper geometrical turning inserts in a CNC turning lathe. After the turning, the MAP and MRB technologies can be used directly to reduce the twist of surfaces. The evaluation was completed by advanced measuring and IT equipment.

Keywords: Magnetism, finishing, polishing, roller burnishing, twist-free.

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Authors: Mongkorn Klingajay, Tawatchai Jitson

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The pipe inspection operation is the difficult detective performance. Almost applications are mainly relies on a manual recognition of defective areas that have carried out detection by an engineer. Therefore, an automation process task becomes a necessary in order to avoid the cost incurred in such a manual process. An automated monitoring method to obtain a complete picture of the sewer condition is proposed in this work. The focus of the research is the automated identification and classification of discontinuities in the internal surface of the pipe. The methodology consists of several processing stages including image segmentation into the potential defect regions and geometrical characteristic features. Automatic recognition and classification of pipe defects are carried out by means of using an artificial neural network technique (ANN) based on Radial Basic Function (RBF). Experiments in a realistic environment have been conducted and results are presented.

Keywords: Artificial neural network, Radial basic function, Curve fitting, CCTV, Image segmentation, Data acquisition.

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Authors: Aditi Bhadra, Sutapa Choudhury, Daita Kar

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Flood zoning studies have become more efficient in recent years because of the availability of advanced computational facilities and use of Geographic Information Systems (GIS). In the present study, flood inundated areas were mapped using GIS for the Dikrong river basin of Arunachal Pradesh, India, corresponding to different return periods (2, 5, 25, 50, and 100 years). Further, the developed inundation maps corresponding to 25, 50, and 100 year return period floods were compared to corresponding maps developed by conventional methods as reported in the Brahmaputra Board Master Plan for Dikrong basin. It was found that, the average deviation of modelled flood inundation areas from reported map inundation areas is below 5% (4.52%). Therefore, it can be said that the modelled flood inundation areas matched satisfactorily with reported map inundation areas. Hence, GIS techniques were proved to be successful in extracting the flood inundation extent in a time and cost effective manner for the remotely located hilly basin of Dikrong, where conducting conventional surveys is very difficult.

Keywords: Flood hazard mapping, GIS, inundation area, return period.

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Authors: Mandeep Kumar, Hari Singh

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The effective optimization of machining process parameters affects dramatically the cost and production time of machined components as well as the quality of the final products. This paper presents the optimization aspects of a Wire Electrical Discharge Machining operation using Inconel X-750 as work material. The objective considered in this study is minimization of the dimensional deviation. Six input process parameters of WEDM namely spark gap voltage, pulse-on time, pulse-off time, wire feed rate, peak current and wire tension, were chosen as variables to study the process performance. Taguchi's design of experiments methodology has been used for planning and designing the experiments. The analysis of variance was carried out for raw data as well as for signal to noise ratio. Four input parameters and one two-factor interaction have been found to be statistically significant for their effects on the response of interest. The confirmation experiments were also performed for validating the predicted results.

Keywords: ANOVA, DOE, inconel, machining, optimization.

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