Search results for: efficiency prediction.

Authors: Rishabh Garg

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Blockchain technology can allow remote, untrusted parties in the banking and financial sector to reach consensus on the state of databases without the involvement of gatekeepers. Like a bookkeeper, it can manage all financial transactions including payments, settlements, fundraising, securities management, loans, credits and trade finance. It can outperform existing systems in terms of identity verification, asset transfers, peer-to-peer transfers, hedge funds, security and auditability. Blockchain-based decentralized finance (DeFi) is a new financial protocol. Being open and programmable, it enables various DeFi use-cases, including asset management, tokenization, tokenized derivatives, decentralized autonomous organizations, data analysis and valuation, payments, lending and borrowing, insurance, margin trading, prediction market, gambling and yield-farming, etc. In addition, it can ease financial transactions, cash-flow, use of programmable currency, no-loss lotteries, etc. This paper aims to assess the potential of decentralized finance by leveraging the blockchain-enabled Ethereum platform as an alternative to traditional finance. The study also aims to find out the impact of decentralized finance on prediction markets, quadratic funding and crowd-funding, together with the potential challenges and solutions associated with its implementation.

Keywords: Advance trading, crowd funding, exchange tokens, fund aggregation, margin trading, quadratic funding, smart contracts, streaming money, token derivatives.

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Authors: N. M. Kamoh, D. G. Gyemang, M. C. Soomiyol

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This paper compared the efficiency of Simpson’s 1/3 and 3/8 rules for the numerical solution of first order Volterra integro-differential equations. In developing the solution, collocation approximation method was adopted using the shifted Legendre polynomial as basis function. A block method approach is preferred to the predictor corrector method for being self-starting. Experimental results confirmed that the Simpson’s 3/8 rule is more efficient than the Simpson’s 1/3 rule.

Keywords: Collocation shifted Legendre polynomials, Simpson’s rule and Volterra integro-differential equations.

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Authors: Ionel Stanculeanu, Theodor Borangiu

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This paper presents a new approach in the identification of the quadrotor dynamic model using a black-box system for identification. Also the paper considers the problems which appear during the identification in the closed-loop and offers a technical solution for overcoming the correlation between the input noise present in the output

Keywords: System identification, UAV, prediction error method, quadrotor.

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Authors: Muhammad Aqil, Ichiro Kita, Akira Yano, Nishiyama Soichi

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This paper presents an alternate approach that uses artificial neural network to simulate the flood level dynamics in a river basin. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach and evolving graphical feature and can be adopted for any similar situation to predict the flood level. The main data processing includes the gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood level data, to train/test the model using various inputs and to visualize results. The program code consists of a set of files, which can as well be modified to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The running results indicate that the decision support system applied to the flood level seems to have reached encouraging results for the river basin under examination. The comparison of the model predictions with the observed data was satisfactory, where the model is able to forecast the flood level up to 5 hours in advance with reasonable prediction accuracy. Finally, this program may also serve as a tool for real-time flood monitoring and process control.

Keywords: Decision Support System, Neural Network, Flood Level

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Authors: Shahryar Shaghaghi G., Mojtaba H. Ghoshouni, Bahareh S. Ghabel

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The issue of scientific – technological parks has been proposed in several countries of the world especially in western countries since a few decades ago and its efficiency is under examination. In our county Iran, some scientific – technological parks have been established or are being established. This design would evaluate the urban role and method of architecture of these parks in order to criticize its efficiency and offer some suggestions, as much as possible to improve its building methods in Iran. The main problem of this design is that how much these parks in Iran do meet the international measurements. So for this reason, one scientific park in Iran and one from western countries would be studied and compared with each other.

Keywords: Applicability, Architectural pattern, Scientific _technological park , Urban role

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Authors: M. A. Karim

Abstract:

In countries with hot climates, air-conditioning forms a large proportion of annual peak electrical demand, requiring expansion of power plants to meet the peak demand, which goes unused most of the time. Use of well-designed cool storage can offset the peak demand to a large extent. In this study, an air conditioning system with naturally stratified storage tank was designed, constructed and tested. A new type of diffuser was designed and used in this study. Factors that influence the performance of chilled water storage tanks were investigated. The results indicated that stratified storage tank consistently stratified well without any physical barrier. Investigation also showed that storage efficiency decreased with increasing flow rate due to increased mixing of warm and chilled water. Diffuser design and layout primarily affected the mixing near the inlet diffuser and the extent of this mixing had primary influence on the shape of the thermocline. The heat conduction through tank walls and through the thermocline caused widening of mixed volume. Thermal efficiency of stratified storage tanks was as high as 90 percent, which indicates that stratified tanks can effectively be used as a load management technique.

Keywords: Cool Thermal Storage, Diffuser, Natural Stratification, Efficiency Improvement, Load management.

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Authors: Shao-lun Zeng, Yu-long Ren

Abstract:

Benchmarking cleaner production performance is an effective way of pollution control and emission reduction in coal-fired power industry. A benchmarking method using two-stage super-efficiency data envelopment analysis for coal-fired power plants is proposed – firstly, to improve the cleaner production performance of DEA-inefficient or weakly DEA-efficient plants, then to select the benchmark from performance-improved power plants. An empirical study is carried out with the survey data of 24 coal-fired power plants. The result shows that in the first stage the performance of 16 plants is DEA-efficient and that of 8 plants is relatively inefficient. The target values for improving DEA-inefficient plants are acquired by projection analysis. The efficient performance of 24 power plants and the benchmarking plant is achieved in the second stage. The two-stage benchmarking method is practical to select the optimal benchmark in the cleaner production of coal-fired power industry and will continuously improve plants- cleaner production performance.

Keywords: benchmarking, cleaner production performance, coal-fired power plant, super-efficiency data envelopment analysis

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Authors: Said Ali Al-Hadhrami

Abstract:

Ranked set sampling (RSS) was first suggested to increase the efficiency of the population mean. It has been shown that this method is highly beneficial to the estimation based on simple random sampling (SRS). There has been considerable development and many modifications were done on this method. When a concomitant variable is available, ratio estimation based on ranked set sampling was proposed. This ratio estimator is more efficient than that based on SRS. In this paper some ratio type estimators of the population mean based on RSS are suggested. These estimators are found to be more efficient than the estimators of similar form using simple random sample.

Keywords: Bias, Efficiency, Ranked Set Sampling, Ratio Type Estimator

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Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

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The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and the snapshot and hierarchical index are used in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: Agent, network backup system, three architecture model, NSBS.

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Authors: Insung Jung, Gi-Nam Wang

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In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: G. S. Ayyappan, Srinivas Kota, Jaffer R. C. Sheriff, C. Prakash Chandra Joshua

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In the present scenario of energy crises, energy conservation in the electrical machines is very important in the industries. In order to conserve energy, one needs to monitor the performance of an induction motor on-site and in-situ. The instruments available for this purpose are very meager and very expensive. This paper deals with the design and development of induction motor performance analyser on-line, on-site, and in-situ. The system measures only few electrical input parameters like input voltage, line current, power factor, frequency, powers, and motor shaft speed. These measured data are coupled to name plate details and compute the operating efficiency of induction motor. This system employs the method of computing motor losses with the help of equivalent circuit parameters. The equivalent circuit parameters of the concerned motor are estimated using the developed algorithm at any load conditions and stored in the system memory. The developed instrument is a reliable, accurate, compact, rugged, and cost-effective one. This portable instrument could be used as a handy tool to study the performance of both slip ring and cage induction motors. During the analysis, the data can be stored in SD Memory card and one can perform various analyses like load vs. efficiency, torque vs. speed characteristics, etc. With the help of the developed instrument, one can operate the motor around its Best Operating Point (BOP). Continuous monitoring of the motor efficiency could lead to Life Cycle Assessment (LCA) of motors. LCA helps in taking decisions on motor replacement or retaining or refurbishment.

Keywords: Energy conservation, equivalent circuit parameters, induction motor efficiency, life cycle assessment, motor performance analysis.

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Authors: M. H. Chung, B. Y. Lee, Y. Kim, E. K. Rhee

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With an increase in the interest in the energy conservation for buildings, and the emergence of many methods and easily-understandable approaches to it, energy conservation has now become the public’s main interest, as compared to in the past when it was only focused upon by experts. This study aims to help the occupants of a building to understand the energy efficiency and consumption of the building by providing them information on the building’s energy efficiency through a mobile application. The energy performance assessment models are proposed on the basis of the actual energy usage and building characteristics such as the architectural scheme and the building equipment. The university buildings in Korea are used as a case to demonstrate the mobile application.

Keywords: Energy consumption, energy performance assessment, mobile application, university buildings.

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Authors: A Fouda, Z. Melikyan

Abstract:

Air conditioning systems of houses consume large quantity of electricity. To reducing energy consumption for air conditioning purposes it is becoming attractive the use of evaporative cooling air conditioning which is less energy consuming compared to air chillers. But, it is obvious that higher energy efficiency of evaporative cooling is not enough to judge whether evaporative cooling economically is competitive with other types of cooling systems. To proving the higher energy efficiency and cost effectiveness of the evaporative cooling competitive analysis of various types of cooling system should be accomplished. For noted purpose optimization mathematical model for each system should be composed based on system approach analysis. In this paper different types of evaporative cooling-heating systems are discussed and methods for increasing their energy efficiency and as well as determining of their design parameters are developed. The optimization mathematical models for each of them are composed with help of which least specific costs for each of them are reviled. The comparison of specific costs proved that the most efficient and cost effective is considered the “direct evaporating" system if it is applicable for given climatic conditions. Next more universal and applicable for many climatic conditions system providing least cost of heating and cooling is considered the “direct evaporating" system.

Keywords: air, conditioning, system, evaporative cooling, mathematical model, optimization, thermoeconomic.

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Authors: Orkide Donma, Mustafa M. Donma

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Basal metabolic rate (BMR) is widely used and an accepted measure of energy expenditure. Its principal determinant is body mass. However, this parameter is also correlated with a variety of other factors. The objective of this study is to measure BMR and compare it with the values obtained from predictive equations in adults classified according to their body mass index (BMI) values. 276 adults were included into the scope of this study. Their age, height and weight values were recorded. Five groups were designed based on their BMI values. First group (n = 85) was composed of individuals with BMI values varying between 18.5 and 24.9 kg/m². Those with BMI values varying from 25.0 to 29.9 kg/m² constituted Group 2 (n = 90). Individuals with 30.0-34.9 kg/m², 35.0-39.9 kg/m², > 40.0 kg/m² were included in Group 3 (n = 53), 4 (n = 28) and 5 (n = 20), respectively. The most commonly used equations to be compared with the measured BMR values were selected. For this purpose, the values were calculated by the use of four equations to predict BMR values, by name, introduced by Food and Agriculture Organization (FAO)/World Health Organization (WHO)/United Nations University (UNU), Harris and Benedict, Owen and Mifflin. Descriptive statistics, ANOVA, post-Hoc Tukey and Pearson’s correlation tests were performed by a statistical program designed for Windows (SPSS, version 16.0). p values smaller than 0.05 were accepted as statistically significant. Mean ± SD of groups 1, 2, 3, 4 and 5 for measured BMR in kcal were 1440.3 ± 210.0, 1618.8 ± 268.6, 1741.1 ± 345.2, 1853.1 ± 351.2 and 2028.0 ± 412.1, respectively. Upon evaluation of the comparison of means among groups, differences were highly significant between Group 1 and each of the remaining four groups. The values were increasing from Group 2 to Group 5. However, differences between Group 2 and Group 3, Group 3 and Group 4, Group 4 and Group 5 were not statistically significant. These insignificances were lost in predictive equations proposed by Harris and Benedict, FAO/WHO/UNU and Owen. For Mifflin, the insignificance was limited only to Group 4 and Group 5. Upon evaluation of the correlations of measured BMR and the estimated values computed from prediction equations, the lowest correlations between measured BMR and estimated BMR values were observed among the individuals within normal BMI range. The highest correlations were detected in individuals with BMI values varying between 30.0 and 34.9 kg/m². Correlations between measured BMR values and BMR values calculated by FAO/WHO/UNU as well as Owen were the same and the highest. In all groups, the highest correlations were observed between BMR values calculated from Mifflin and Harris and Benedict equations using age as an additional parameter. In conclusion, the unique resemblance of the FAO/WHO/UNU and Owen equations were pointed out. However, mean values obtained from FAO/WHO/UNU were much closer to the measured BMR values. Besides, the highest correlations were found between BMR calculated from FAO/WHO/UNU and measured BMR. These findings suggested that FAO/WHO/UNU was the most reliable equation, which may be used in conditions when the measured BMR values are not available.

Keywords: Adult, basal metabolic rate, FAO/WHO/UNU, obesity, prediction equations.

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Authors: B. Bahri, A. A. Aziz, M. Shahbakhti, M. F. Muhamad Said

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The greenhouse effect and limitations on carbon dioxide emissions concern engine maker and the future of the internal combustion engines should go toward substantially and improved thermal efficiency engine. Homogeneous charge compression ignition (HCCI) is an alternative high-efficiency technology for combustion engines to reduce exhaust emissions and fuel consumption. However, there are still tough challenges in the successful operation of HCCI engines, such as controlling the combustion phasing, extending the operating range, and high unburned hydrocarbon and CO emissions. HCCI and the exploitation of ethanol as an alternative fuel is one way to explore new frontiers of internal combustion engines with an eye towards maintaining its sustainability. This study was done to extend database knowledge about HCCI with ethanol a fuel.

Keywords: Ethanol combustion, Ethanol fuel, HCCI.

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Authors: Anabel Fernandez, Leandro Rodriguez-Ortiz, Rosa Rodríguez

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Due to the negative impact of fossil fuels, renewable energies are promising sources to limit global temperature rise and damage to the environment. Also, the development of technology is focused on obtaining energetic products from renewable sources. In this study, a thermodynamic model including exergy balance and a subsequent Life Cycle Assessment (LCA) were carried out for four subsystems of the integrated gasification-combustion of pinewood. Results of exergy analysis and LCA showed the process feasibility in terms of exergy efficiency and global energy efficiency of the life cycle (GEELC). Moreover, the energy return on investment (EROI) index was calculated. The global exergy efficiency resulted in 67%. For pretreatment, reaction, cleaning, and electric generation subsystems, the results were 85%, 59%, 87%, and 29%, respectively. Results of LCA indicated that the emissions from the electric generation caused the most damage to the atmosphere, water, and soil. GEELC resulted in 31.09% for the global process. This result suggested the environmental feasibility of an integrated gasification-combustion system. EROI resulted in 3.15, which determines the sustainability of the process.

Keywords: Exergy analysis, Life Cycle Assessment, LCA, renewability, sustainability.

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Authors: Raoul Zamblé, Michel Babri, Souleymane Oumtanaga, Boubacar Barry, Claude Lishou

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Cognitive radio devices have been considered as a key technology for next-generation of wireless communication. These devices in the context of IEEE 802.11 standards and IEEE 802.16 standards, can opportunistically utilize the wireless spectrum to achieve better user performance and improve the overall spectrumutilization efficiency, mainly in the unlicensed 5 GHz bands. However, opportunistic use of wireless spectrum creates news problems such as peaceful coexistence with other wireless technologies, such as the radiolocation systems, as well as understanding the influence of interference that each of these networks can create. In this paper, we suggest a dynamic access model that considerably reduces this interference and allows efficiency and fairness use of the wireless spectrum.

Keywords: Dynamic access, exclusive access, spectrumopportunities, unlicensed band.

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Authors: Rooholah Hasanizadeh, Saadan Zokaei

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Energy efficient protocol design is the aim of current researches in the area of sensor networks where limited power resources impose energy conservation considerations. In this paper we care for Medium Access Control (MAC) protocols and after an extensive literature review, two adaptive schemes are discussed. Of them, adaptive-rate MACs which were introduced for throughput enhancement show the potency to save energy, even more than adaptive-power schemes. Then we propose an allocation algorithm for getting accurate and reliable results. Through a simulation study we validated our claim and showed the power saving of adaptive-rate protocols.

Keywords: Adaptive-rate, adaptive-power, MAC protocol, energy efficiency, sensor networks.

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Authors: Surinder Deswal

Abstract:

There has been a growing interest in the oxygenation by plunging water jets in the last few years due to their inherent advantages, like energy-efficient, low operation cost, etc. Though a lot of work has been reported on the oxygen-transfer by single plunging water jets but very few studies have been carried out using multiple plunging jets. In this paper, volumetric oxygen-transfer coefficient and oxygen-transfer efficiency has been studied experimentally for multiple inclined plunging jets (having jet plunge angle of 60 0 ) in a pool of water for different configurations, in terms of varying number of jets and jet diameters. This research suggests that the volumetric oxygen-transfer coefficient and oxygentransfer efficiency of the multiple inclined plunging jets for air-water system are significantly higher than those of a single vertical as well as inclined plunging jet for same flow area and other similar conditions. The study also reveals that the oxygen-transfer increase with increase in number of multiple jets under similar conditions, which will be most advantageous and energy-efficient in practical situations when large volumes of wastewaters are to be treated. A relationship between volumetric oxygen-transfer coefficient and jet parameters is also proposed. The suggested relationship predicts the volumetric oxygen-transfer coefficient for multiple inclined plunging jet(s) within a scatter of ±15 percent. The relationship will be quite useful in scale-up and in deciding optimum configuration of multiple inclined plunging jet aeration system.

Keywords: Multiple inclined plunging jets, jet plunge angle, volumetric oxygen-transfer coefficient, oxygen-transfer efficiency.

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

Abstract:

Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies  the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: Retail stores, Faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition.

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Authors: Suboohi Shervani, Jingjing Ling, Jiabin Liu, Tahir Husain

Abstract:

Offshore oil-spill has become the most emerging problem in the world. In the current paper, a graphene/ZnO/polymer nanocomposite thin film is coated on stainless steel mesh via layer by layer deposition method. The structural characterization of materials is determined by Scanning Electron Microscopy (SEM) and X-ray diffraction (XRD). The total petroleum hydrocarbons (TPHs) and separation efficiency have been measured via gas chromatography – flame ionization detector (GC-FID). TPHs are reduced to 2 ppm and separation efficiency of the nanocomposite coated mesh is reached ≥ 99% for the final sample. The nanocomposite coated mesh acts as a promising candidate for the separation of oil- water mixture.

Keywords: Oil-spill, graphene, oil-water separation, nanocomposite.

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Authors: Zaineb Ben Messaoud, Dorra Gargouri, Saida Zribi, Ahmed Ben Hamida

Abstract:

This paper presents a formant-tracking linear prediction (FTLP) model for speech processing in noise. The main focus of this work is the detection of formant trajectory based on Hidden Markov Models (HMM), for improved formant estimation in noise. The approach proposed in this paper provides a systematic framework for modelling and utilization of a time- sequence of peaks which satisfies continuity constraints on parameter; the within peaks are modelled by the LP parameters. The formant tracking LP model estimation is composed of three stages: (1) a pre-cleaning multi-band spectral subtraction stage to reduce the effect of residue noise on formants (2) estimation stage where an initial estimate of the LP model of speech for each frame is obtained (3) a formant classification using probability models of formants and Viterbi-decoders. The evaluation results for the estimation of the formant tracking LP model tested in Gaussian white noise background, demonstrate that the proposed combination of the initial noise reduction stage with formant tracking and LPC variable order analysis, results in a significant reduction in errors and distortions. The performance was evaluated with noisy natual vowels extracted from international french and English vocabulary speech signals at SNR value of 10dB. In each case, the estimated formants are compared to reference formants.

Keywords: Formants Estimation, HMM, Multi Band Spectral Subtraction, Variable order LPC coding, White Gauusien Noise.

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

Abstract:

The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: Structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm.

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Authors: Samir J. Deshmukh, Lalit B. Bhuyar, Shashank B. Thakre, Sachin S. Ingole

Abstract:

The aim of this study is to develop mathematical relationships for the performance parameter brake thermal efficiency (BTE) and emission parameter nitrogen oxides (NOx) for the various esters of vegetable oils used as CI engine fuel. The BTE is an important performance parameter defining the ability of engine to utilize the energy supplied and power developed similarly it is indication of efficiency of fuels used. The esters of cottonseed oil, soybean oil, jatropha oil and hingan oil are prepared using transesterification process and characterized for their physical and main fuel properties including viscosity, density, flash point and higher heating value using standard test methods. These esters are tried as CI engine fuel to analyze the performance and emission parameters in comparison to diesel. The results of the study indicate that esters as a fuel does not differ greatly with that of diesel in properties. The CI engine performance with esters as fuel is in line with the diesel where as the emission parameters are reduced with the use of esters. The correlation developed between BTE and brake power(BP), gross calorific value(CV), air-fuel ratio(A/F), heat carried away by cooling water(HCW). Another equation is developed between the NOx emission and CO, HC, smoke density (SD), exhaust gas temperature (EGT). The equations are verified by comparing the observed and calculated values which gives the coefficient of correlation of 0.99 and 0.96 for the BTE and NOx equations respectively.

Keywords: Esters, emission, performance, and vegetable oil.

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Authors: D. G. Badagha, C. D. Modhera, S. A. Vasanwala

Abstract:

There is a great challenge for civil engineering field to contribute in environment prevention by finding out alternatives of cement and natural aggregates. There is a problem of global warming due to cement utilization in concrete, so it is necessary to give sustainable solution to produce concrete containing waste. It is very difficult to produce designated grade of concrete containing different ingredient and water cement ratio including waste to achieve desired fresh and harden properties of concrete as per requirement and specifications. To achieve the desired grade of concrete, a number of trials have to be taken, and then after evaluating the different parameters at long time performance, the concrete can be finalized to use for different purposes. This research work is carried out to solve the problem of time, cost and serviceability in the field of construction. In this research work, artificial neural network introduced to fix proportion of concrete ingredient with 50% waste replacement for M20, M25, M30, M35, M40, M45, M50, M55 and M60 grades of concrete. By using the neural network, mix design of high performance concrete was finalized, and the main basic mechanical properties were predicted at 3 days, 7 days and 28 days. The predicted strength was compared with the actual experimental mix design and concrete cube strength after 3 days, 7 days and 28 days. This experimentally and neural network based mix design can be used practically in field to give cost effective, time saving, feasible and sustainable high performance concrete for different types of structures.

Keywords: Artificial neural network, ANN, high performance concrete, rebound hammer, strength prediction.

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Authors: S.K. Mazloomi, Nasri b. Sulaiman

Abstract:

By analyzing the sources of energy and power loss in PWM (Pulse Width Modulation) controlled drivers of water electrolysis cells, it is possible to reduce the power dissipation and enhance the efficiency of such hydrogen production units. A PWM controlled power driver is based on a semiconductor switching element where its power dissipation might be a remarkable fraction of the total power demand of an electrolysis system. Power dissipation in a semiconductor switching element is related to many different parameters which could be fitted into two main categories: switching losses and conduction losses. Conduction losses are directly related to the built, structure and capabilities of a switching device itself and indeed the conditions in which the element is handling the switching application such as voltage, current, temperature and of course the fabrication technology. On the other hand, switching losses have some other influencing variables other than the mentioned such as control system, switching method and power electronics circuitry of the PWM power driver. By analyzings the characteristics of recently developed power switching transistors from different families of Bipolar Junction Transistors (BJT), Metal Oxide Semiconductor Field Effect Transistors (MOSFET) and Insulated Gate Bipolar Transistors (IGBT), some recommendations are made in this paper which are able to lead to achieve higher hydrogen production efficiency by utilizing PWM controlled water electrolysis cells.

Keywords: Power switch, PWM, Semiconductor switch, Waterelectrolysis

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Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi

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Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.

Keywords: Time-series clustering, feature extraction, hoax prediction, geospatial events.

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Authors: A. Nicknam, N. Eftekhari, A. Mazarei, M. Ganjvar

Abstract:

This article presents an alternative collapse capacity intensity measure in the three elements form which is influenced by the spectral ordinates at periods longer than that of the first mode period at near and far source sites. A parameter, denoted by β, is defined by which the spectral ordinate effects, up to the effective period (2T1), on the intensity measure are taken into account. The methodology permits to meet the hazard-levelled target extreme event in the probabilistic and deterministic forms. A MATLAB code is developed involving OpenSees to calculate the collapse capacities of the 8 archetype RC structures having 2 to 20 stories for regression process. The incremental dynamic analysis (IDA) method is used to calculate the structure’s collapse values accounting for the element stiffness and strength deterioration. The general near field set presented by FEMA is used in a series of performing nonlinear analyses. 8 linear relationships are developed for the 8structutres leading to the correlation coefficient up to 0.93. A collapse capacity near field prediction equation is developed taking into account the results of regression processes obtained from the 8 structures. The proposed prediction equation is validated against a set of actual near field records leading to a good agreement. Implementation of the proposed equation to the four archetype RC structures demonstrated different collapse capacities at near field site compared to those of FEMA. The reasons of differences are believed to be due to accounting for the spectral shape effects.

Keywords: Collapse capacity, fragility analysis, spectral shape effects, IDA method.

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Authors: H. Siswoyo Jo, N. Mir-Nasiri, E. Jayamani

Abstract:

This paper presents a new type of mechanism and trajectory planning strategy for bipedal walking robot. The newly designed mechanism is able to improve the performance of bipedal walking robot in terms of energy efficiency and weight reduction by utilizing minimum number of actuators. The usage of parallelogram mechanism eliminates the needs of having an extra actuator at the knee joint. This mechanism works together with the joint space trajectory planning in order to realize straight legged walking which cannot be achieved by conventional inverse kinematics trajectory planning due to the singularity. The effectiveness of the proposed strategy is confirmed by computer simulation results.

Keywords: Bipedal robot, Energy efficiency, Straight legged walking, Trajectory planning.

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Authors: Poonam Garg, Aditya Shastri, D.C. Agarwal

Abstract:

With the exponential growth of networked system and application such as eCommerce, the demand for effective internet security is increasing. Cryptology is the science and study of systems for secret communication. It consists of two complementary fields of study: cryptography and cryptanalysis. The application of genetic algorithms in the cryptanalysis of knapsack ciphers is suggested by Spillman [7]. In order to improve the efficiency of genetic algorithm attack on knapsack cipher, the previously published attack was enhanced and re-implemented with variation of initial assumptions and results are compared with Spillman results. The experimental result of research indicates that the efficiency of genetic algorithm attack on knapsack cipher can be improved with variation of initial assumption.

Keywords: Genetic Algorithm, Knapsack cipher, Key search.

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