Search results for: Content based image retrieval (CBIR)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13143

Search results for: Content based image retrieval (CBIR)

9333 A New Spectral-based Approach to Query-by-Humming for MP3 Songs Database

Authors: Leon Fu, Xiangyang Xue

Abstract:

In this paper, we propose a new approach to query-by-humming, focusing on MP3 songs database. Since MP3 songs are much more difficult in melody representation than symbolic performance data, we adopt to extract feature descriptors from the vocal sounds part of the songs. Our approach is based on signal filtering, sub-band spectral processing, MDCT coefficients analysis and peak energy detection by ignorance of the background music as much as possible. Finally, we apply dual dynamic programming algorithm for feature similarity matching. Experiments will show us its online performance in precision and efficiency.

Keywords: DP, MDCT, MP3, QBH.

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9332 Evaluation of Algorithms for Sequential Decision in Biosonar Target Classification

Authors: Turgay Temel, John Hallam

Abstract:

A sequential decision problem, based on the task ofidentifying the species of trees given acoustic echo data collectedfrom them, is considered with well-known stochastic classifiers,including single and mixture Gaussian models. Echoes are processedwith a preprocessing stage based on a model of mammalian cochlearfiltering, using a new discrete low-pass filter characteristic. Stoppingtime performance of the sequential decision process is evaluated andcompared. It is observed that the new low pass filter processingresults in faster sequential decisions.

Keywords: Classification, neuro-spike coding, parametricmodel, Gaussian mixture with EM algorithm, sequential decision.

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9331 Illuminating the Policies Affecting Energy Security in Malaysia’s Electricity Sector

Authors: Hussain Ali Bekhet, Endang Jati Mat Sahid

Abstract:

For the past few decades, the Malaysian economy has expanded at an impressive pace, whilst, the Malaysian population has registered a relatively high growth rate. These factors had driven the growth of final energy demand. The ballooning energy demand coupled with the country’s limited indigenous energy resources have resulted in an increased of the country’s net import. Therefore, acknowledging the precarious position of the country’s energy self-sufficiency, this study has identified three main concerns regarding energy security, namely; over-dependence on fossil fuel, increasing energy import dependency, and increasing energy consumption per capita. This paper discusses the recent energy demand and supply trends, highlights the policies that are affecting energy security in Malaysia and suggests strategic options towards achieving energy security. The paper suggested that diversifying energy sources, reducing carbon content of energy, efficient utilization of energy and facilitating low-carbon industries could further enhance the effectiveness of the measures as the introduction of policies and initiatives will be more holistic.

Keywords: Energy security, electricity, energy policy, renewable energy, energy efficiency, Malaysia.

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9330 Automatic Vehicle Location Systems

Authors: S.A. Mahdavifar, G.R. Sotudeh., K. Heydari

Abstract:

In this article, a single application is suggested to determine the position of vehicles using Geographical Information Systems (GIS) and Geographical Position Systems (GPS). The part of the article material included mapping three dimensional coordinates to two dimensional coordinates using UTM or LAMBERT geographical methods, and the algorithm of conversion of GPS information into GIS maps is studied. Also, suggestions are given in order to implement this system based on web (called web based systems). To apply this system in IRAN, related official in this case are introduced and their duties are explained. Finally, economy analyzed is assisted according to IRAN communicational system.

Keywords: GIS-GPS-UTM-LAMBERT.

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9329 Efficiency Based Model for Solar Urban Planning

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

Abstract:

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

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

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

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9328 Determination of Yield and Yield Components of Fodder Beet (Beta vulgaris L. var. rapacea Koch.) Cultivars under the Konya Region Conditions

Authors: A. Özköse

Abstract:

This study was conducted to determination of yield and yield components of some fodder beet types (Amarilla Barres, Feldherr, Kyros, Magnum ve Rota) under the Konya region conditions. Fodder beet was obtained from the Selcuk University, Faculty of Agriculture, at 2006-2007 season and the experiment was established in a randomized complete block design with three replicates. Differences among the averages of the fodder beet cultivars are statistically important in terms of all the characteristics investigated. Leaf attitude value was 1.2 – 2.2 (1=erect; 5= prostrate), root shape scale value was (1=spheroidal – 9=cylindrical), root diameter 11.0 – 12.2cm, remaining part of root on the ground was 6.3 – 13.7cm, root length was 21.4 – 29.6cm, leaf yield 1592 – 1917 kg/da, root yield was 10083 – 12258 kg/da, root dry matter content was %8.2 – 18.6 and root dry matter yield was 889 – 1887 kg/da. As a result of the study, it was determined that fodder beet cultivars are different conditions in terms of yield and yield components. Therefore, determination of appropriate cultivars for each region affect crop yield importantly.

Keywords: Fodder beet, root yield, yield components.

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9327 Fuzzy Rules Generation and Extraction from Support Vector Machine Based on Kernel Function Firing Signals

Authors: Prasan Pitiranggon, Nunthika Benjathepanun, Somsri Banditvilai, Veera Boonjing

Abstract:

Our study proposes an alternative method in building Fuzzy Rule-Based System (FRB) from Support Vector Machine (SVM). The first set of fuzzy IF-THEN rules is obtained through an equivalence of the SVM decision network and the zero-ordered Sugeno FRB type of the Adaptive Network Fuzzy Inference System (ANFIS). The second set of rules is generated by combining the first set based on strength of firing signals of support vectors using Gaussian kernel. The final set of rules is then obtained from the second set through input scatter partitioning. A distinctive advantage of our method is the guarantee that the number of final fuzzy IFTHEN rules is not more than the number of support vectors in the trained SVM. The final FRB system obtained is capable of performing classification with results comparable to its SVM counterpart, but it has an advantage over the black-boxed SVM in that it may reveal human comprehensible patterns.

Keywords: Fuzzy Rule Base, Rule Extraction, Rule Generation, Support Vector Machine.

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9326 Thermodynamic Analysis of Activated Carbon- CO2 based Adsorption Cooling Cycles

Authors: Skander Jribi, Anutosh Chakraborty, Ibrahim I. El-Sharkawy, Bidyut Baran Saha, Shigeru Koyama

Abstract:

Heat powered solid sorption is a feasible alternative to electrical vapor compression refrigeration systems. In this paper, activated carbon (powder type Maxsorb and fiber type ACF-A10)- CO2 based adsorption cooling cycles are studied using the pressuretemperature- concentration (P-T-W) diagram. The specific cooling effect (SCE) and the coefficient of performance (COP) of these two cooling systems are simulated for the driving heat source temperatures ranging from 30 ºC to 90 ºC in terms of different cooling load temperatures with a cooling source temperature of 25 ºC. It is found from the present analysis that Maxsorb-CO2 couple shows higher cooling capacity and COP. The maximum COPs of Maxsorb-CO2 and ACF(A10)-CO2 based cooling systems are found to be 0.15 and 0.083, respectively. The main innovative feature of this cooling cycle is the ability to utilize low temperature waste heat or solar energy using CO2 as the refrigerant, which is one of the best alternative for applications where flammability and toxicity are not allowed.

Keywords: Activated carbon, Adsorption cooling system, Carbon dioxide, Performance evaluation.

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9325 Motion Parameter Estimation via Dopplerlet-Transform-Based Matched Field Processing

Authors: Hongyan Dai

Abstract:

This work presents a matched field processing (MFP) algorithm based on Dopplerlet transform for estimating the motion parameters of a sound source moving along a straight line and with a constant speed by using a piecewise strategy, which can significantly reduce the computational burden. Monte Carlo simulation results and an experimental result are presented to verify the effectiveness of the algorithm advocated.

Keywords: matched field processing; Dopplerlet transform; motion parameter estimation; piecewise strategy

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9324 Factors Influencing the Use of Green Building Practices in the South African Residential Apartment Construction

Authors: Mongezi Nene, Emma Ayesu-Koranteng, Christopher Amoah, Ayo Adeniran

Abstract:

Although its use has been criticised over the years as being unencouraging, the green building concept is quickly overtaking other concepts, particularly in the construction of commercial properties. The goal of the study is to identify the variables influencing the use of green building practices when developing residential structures. A qualitative methodology, using interviews with semi-structured open-ended questions to 35 property practitioners operating residential apartments in Bloemfontein, South Africa, was used to collect primary data which were analysed using thematic content analysis. The findings show that while respondents have a good understanding of green building principles, they are not being used in the construction of residential buildings in South Africa due to issues with green building approval procedures, the potential for tenant rent increases, the cost of materials, technical issues, contractual issues, and a lack of awareness, among others. This paper recommends among others an urgent need to implement measures by stakeholders towards enhancing the adoption of green building concepts in the construction of residential buildings as well as incentivising its construction through lowered property rates.

Keywords: Green building, residential apartments, construction, South Africa.

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9323 Neural Network Based Icing Identification and Fault Tolerant Control of a 340 Aircraft

Authors: F. Caliskan

Abstract:

This paper presents a Neural Network (NN) identification of icing parameters in an A340 aircraft and a reconfiguration technique to keep the A/C performance close to the performance prior to icing. Five aircraft parameters are assumed to be considerably affected by icing. The off-line training for identifying the clear and iced dynamics is based on the Levenberg-Marquard Backpropagation algorithm. The icing parameters are located in the system matrix. The physical locations of the icing are assumed at the right and left wings. The reconfiguration is based on the technique known as the control mixer approach or pseudo inverse technique. This technique generates the new control input vector such that the A/C dynamics is not much affected by icing. In the simulations, the longitudinal and lateral dynamics of an Airbus A340 aircraft model are considered, and the stability derivatives affected by icing are identified. The simulation results show the successful NN identification of the icing parameters and the reconfigured flight dynamics having the similar performance before the icing. In other words, the destabilizing icing affect is compensated.

Keywords: Aircraft Icing, Stability Derivatives, Neural NetworkIdentification, Reconfiguration.

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9322 The Impact of Change Management on Employee Satisfaction and Engagement

Authors: Ju-Chun Chien

Abstract:

The main purpose of this study was to figure out employees’ attitudes toward the new performance appraisal program and to examine whether three different types of appraisal processes differentially affected job satisfaction and employee engagement. The second purpose of this study was to investigate the relationship between performance appraisal reform, job satisfaction, and employee engagement. A large polyester and textile corporation had 2046 non-operational employees in February 2014. The valid participants were 1474 (72.04%) in this study. Data analysis included descriptive statistics, one-way ANOVA, one-way MANOVA, Pearson correlation, Content Validity Index, the exploratory factor analysis, and reliability analysis. The general results showed that employees who received the new performance appraisal program evaluated the program more positively and showed more job satisfaction than those who did not. In particular, the implementation effects of this new performance appraisal program were most highly rated by employees who used the KPI to rate their job performance. Moreover, employees’ attitudes toward the new performance appraisal program were positively related to their job satisfaction and employee engagement. Lastly, most employees regarded themselves as engaged workers. To sum up, the HR department of this company has made an effective contribution to performance appraisal reforms.

Keywords: Change management, Employee engagement, Job satisfaction, Performance appraisal reform.

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9321 Analysis of Sulphur-Oxidizing Bacteria Attack on Concrete Based On Waste Materials

Authors: A. Eštoková, M. Kovalčíková, A. Luptáková, A. Sičáková, M. Ondová

Abstract:

Concrete durability as an important engineering property of concrete, determining the service life of concrete structures very significantly, can be threatened and even lost due to the interactions of concrete with external environment. Bio-corrosion process caused by presence and activities of microorganisms producing sulphuric acid is a special type of sulphate deterioration of concrete materials. The effects of sulphur-oxidizing bacteria Acidithiobacillus thiooxidans on various concrete samples, based on silica fume and zeolite, were investigated in laboratory during 180 days. A laboratory study was conducted to compare the performance of concrete samples in terms of the concrete deterioration influenced by the leaching of calcium and silicon compounds from the cement matrix. The changes in the elemental concentrations of calcium and silicon in both solid samples and liquid leachates were measured by using X – ray fluorescence method. Experimental studies confirmed the silica fume based concrete samples were found out to have the best performance in terms of both silicon and calcium ions leaching.

Keywords: Bio-corrosion, concrete, leaching, bacteria.

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9320 Community Detection-based Analysis of the Human Interactome Network

Authors: Razvan Bocu, Sabin Tabirca

Abstract:

The study of proteomics reached unexpected levels of interest, as a direct consequence of its discovered influence over some complex biological phenomena, such as problematic diseases like cancer. This paper presents a new technique that allows for an accurate analysis of the human interactome network. It is basically a two-step analysis process that involves, at first, the detection of each protein-s absolute importance through the betweenness centrality computation. Then, the second step determines the functionallyrelated communities of proteins. For this purpose, we use a community detection technique that is based on the edge betweenness calculation. The new technique was thoroughly tested on real biological data and the results prove some interesting properties of those proteins that are involved in the carcinogenesis process. Apart from its experimental usefulness, the novel technique is also computationally effective in terms of execution times. Based on the analysis- results, some topological features of cancer mutated proteins are presented and a possible optimization solution for cancer drugs design is suggested.

Keywords: Betweenness centrality, interactome networks, proteinprotein interactions, protein communities, cancer.

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9319 Using Data Mining for Learning and Clustering FCM

Authors: Somayeh Alizadeh, Mehdi Ghazanfari, Mohammad Fathian

Abstract:

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show relations between essential components. In some FCM, there are more nodes, which related to each other and more nodes means more complex in system behaviors and analysis. In this paper, a novel learning method used to construct FCMs based on historical data and by using data mining and DEMATEL method, a new method defined to reduce nodes number. This method cluster nodes in FCM based on their cause and effect behaviors.

Keywords: Clustering, Data Mining, Fuzzy Cognitive Map(FCM), Learning.

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9318 Removal of Hydrogen Sulfide in Terms of Scrubbing Techniques using Silver Nano-Particles

Authors: SeungKyu Shin, Jeong Hyub Ha, Sung Han, JiHyeon Song

Abstract:

Silver nano-particles have been used for antibacterial purpose and it is also believed to have removal of odorous compounds, oxidation capacity as a metal catalyst. In this study, silver nano-particles in nano sizes (5-30 nm) were prepared on the surface of NaHCO3, the supporting material, using a sputtering method that provided high silver content and minimized conglomerating problems observed in the common AgNO3 photo-deposition method. The silver nano-particles were dispersed by dissolving Ag-NaHCO3 into water, and the dispersed silver nano-particles in the aqueous phase were applied to remove inorganic odor compounds, H2S, in a scrubbing reactor. Hydrogen sulfide in the gas phase was rapidly removed by the silver nano-particles, and the concentration of sulfate (SO4 2-) ion increased with time due to the oxidation reaction by silver as a catalyst. Consequently, the experimental results demonstrated that the silver nano-particles in the aqueous solution can be successfully applied to remove odorous compounds without adding additional energy sources and producing any harmful byproducts

Keywords: Silver nano-particles, Scrubbing, Oxidation, Hydrogen sulfide, Ammonia

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9317 Pre-Analysis of Printed Circuit Boards Based On Multispectral Imaging for Vision Based Recognition of Electronics Waste

Authors: Florian Kleber, Martin Kampel

Abstract:

The increasing demand of gallium, indium and rare-earth elements for the production of electronics, e.g. solid state-lighting, photovoltaics, integrated circuits, and liquid crystal displays, will exceed the world-wide supply according to current forecasts. Recycling systems to reclaim these materials are not yet in place, which challenges the sustainability of these technologies. This paper proposes a multispectral imaging system as a basis for a vision based recognition system for valuable components of electronics waste. Multispectral images intend to enhance the contrast of images of printed circuit boards (single components, as well as labels) for further analysis, such as optical character recognition and entire printed circuit board recognition. The results show, that a higher contrast is achieved in the near infrared compared to ultraviolett and visible light.

Keywords: Electronic Waste, Recycling, Multispectral Imaging, Printed Circuit Boards, Rare-Earth Elements.

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9316 Facilitating a Cyber-Enabled Fraud Using the O.MG Cable to Incriminate the Victim

Authors: Damola O. Lawal, David W. Gresty, Diane E. Gan, Louise Hewitt

Abstract:

This paper investigates the feasibility of using a programmable USB such as the O.MG Cable to perform a file tampering attack. Here, the O.MG Cable, an apparently harmless mobile device charger is used in an unauthorised way, to alter the content of a file (an accounts record-January_Contributions.xlsx). The aim is to determine if a forensics analyst can reliably determine who has altered the target file; the O.MG Cable or the user of the machine. This work highlights some of the traces of the O.MG Cable left behind on the target computer itself such as the Product ID (PID) and Vendor ID (ID). Also discussed is the O.MG Cable’s behaviour during the experiments. We determine if a forensics analyst could identify if any evidence has been left behind by the programmable device on the target file once it has been removed from the computer to establish if the analyst would be able to link the traces left by the O.MG Cable to the file tampering. It was discovered that the forensic analyst might mistake the actions of the O.MG Cable for the computer users. Experiments carried out in this work could further the discussion as to whether an innocent user could be punished for the unauthorised changes made by a programmable device.

Keywords: O.MG Cable, programmable USB, file tampering attack, digital evidence credibility, miscarriage of justice, cyber fraud.

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9315 Solution of Optimal Reactive Power Flow using Biogeography-Based Optimization

Authors: Aniruddha Bhattacharya, Pranab Kumar Chattopadhyay

Abstract:

Optimal reactive power flow is an optimization problem with one or more objective of minimizing the active power losses for fixed generation schedule. The control variables are generator bus voltages, transformer tap settings and reactive power output of the compensating devices placed on different bus bars. Biogeography- Based Optimization (BBO) technique has been applied to solve different kinds of optimal reactive power flow problems subject to operational constraints like power balance constraint, line flow and bus voltages limits etc. BBO searches for the global optimum mainly through two steps: Migration and Mutation. In the present work, BBO has been applied to solve the optimal reactive power flow problems on IEEE 30-bus and standard IEEE 57-bus power systems for minimization of active power loss. The superiority of the proposed method has been demonstrated. Considering the quality of the solution obtained, the proposed method seems to be a promising one for solving these problems.

Keywords: Active Power Loss, Biogeography-Based Optimization, Migration, Mutation, Optimal Reactive Power Flow.

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9314 Crystalline Structure of Starch Based Nano Composites

Authors: Farid Amidi Fazli, Afshin Babazadeh, Farnaz Amidi Fazli

Abstract:

In contrast with literal meaning of nano, researchers have been achieved mega adventures in this area and every day more nanomaterials are being introduced to the market. After long time application of fossil-based plastics, nowadays accumulation of their waste seems to be a big problem to the environment. On the other hand, mankind has more attention to safety and living environment. Replacing common plastic packaging materials with degradable ones that degrade faster and convert to non-dangerous components like water and carbon dioxide have more attractions; these new materials are based on renewable and inexpensive sources of starch and cellulose. However, the functional properties of them do not suitable for packaging. At this point, nanotechnology has an important role. Utilizing of nanomaterials in polymer structure will improve mechanical and physical properties of them; nanocrystalline cellulose (NCC) has this ability. This work has employed a chemical method to produce NCC and starch bio nanocomposite containing NCC. X-Ray Diffraction technique has characterized the obtained materials. Results showed that applied method is a suitable one as well as applicable one to NCC production.

Keywords: Biofilm, cellulose, nanocomposite, starch.

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9313 Hydrogenation of CO2 to Methanol over Copper-Zinc Oxide-Based Catalyst

Authors: S. F. H. Tasfy, N. A. M. Zabidi, M. S. Shaharun

Abstract:

Carbon dioxide is highly thermochemical stable molecules where it is very difficult to activate the molecule and achieve higher catalytic conversion into alcohols or other hydrocarbon compounds. In this paper, series of the bimetallic Cu/ZnO-based catalyst supported by SBA-15 were systematically prepared via impregnation technique with different Cu: Zn ratio for hydrogenation of CO2 to methanol. The synthesized catalysts were characterized by transmission electron microscopy (TEM), temperature programmed desorption, reduction, oxidation and pulse chemisorption (TPDRO), and surface area determination was also performed. All catalysts were tested with respect to the hydrogenation of CO2 to methanol in microactivity fixed-bed reactor at 250oC, 2.25 MPa, and H2/CO2 ratio of 3. The results demonstrate that the catalytic structure, activity, and methanol selectivity was strongly affected by the ratio between Cu: Zn, Where higher catalytic activity of 14 % and methanol selectivity of 92 % was obtained over Cu/ZnO-SBA-15 catalyst with Cu:Zn ratio of 7:3 wt. %. Comparing with the single catalyst, the synergetic between Cu and Zn provides additional active sites to adsorb more H2 and CO2 and accelerate the CO2 conversion, resulting in higher methanol production under mild reaction conditions.

Keywords: Hydrogenation of carbon dioxide, methanol synthesis, Cu/ZnO-based catalyst, mesoporous silica (SBA-15), and metal ratio.

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9312 AI Tutor: A Computer Science Domain Knowledge Graph-Based QA System on JADE platform

Authors: Yingqi Cui, Changran Huang, Raymond Lee

Abstract:

In this paper, we proposed an AI Tutor using ontology and natural language process techniques to generate a computer science domain knowledge graph and answer users’ questions based on the knowledge graph. We define eight types of relation to extract relationships between entities according to the computer science domain text. The AI tutor is separated into two agents: learning agent and Question-Answer (QA) agent and developed on JADE (a multi-agent system) platform. The learning agent is responsible for reading text to extract information and generate a corresponding knowledge graph by defined patterns. The QA agent can understand the users’ questions and answer humans’ questions based on the knowledge graph generated by the learning agent.

Keywords: Artificial intelligence, natural language process, knowledge graph, agent, QA system.

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9311 Control Improvement of a C Sugar Cane Crystallization Using an Auto-Tuning PID Controller Based on Linearization of a Neural Network

Authors: S. Beyou, B. Grondin-Perez, M. Benne, C. Damour, J.-P. Chabriat

Abstract:

The industrial process of the sugar cane crystallization produces a residual that still contains a lot of soluble sucrose and the objective of the factory is to improve its extraction. Therefore, there are substantial losses justifying the search for the optimization of the process. Crystallization process studied on the industrial site is based on the “three massecuites process". The third step of this process constitutes the final stage of exhaustion of the sucrose dissolved in the mother liquor. During the process of the third step of crystallization (Ccrystallization), the phase that is studied and whose control is to be improved, is the growing phase (crystal growth phase). The study of this process on the industrial site is a problem in its own. A control scheme is proposed to improve the standard PID control law used in the factory. An auto-tuning PID controller based on instantaneous linearization of a neural network is then proposed.

Keywords: Auto-tuning, PID, Instantaneous linearization, Neural network, Non linear process, C-crystallisation.

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9310 Smartphone-Based Human Activity Recognition by Machine Learning Methods

Authors: Yanting Cao, Kazumitsu Nawata

Abstract:

As smartphones are continually upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described more refined, complex and detailed. In this context, we analyzed a set of experimental data, obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model become extremely challenging. After a series of feature selection and parameters adjustments, a well-performed SVM classifier has been trained. 

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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9309 The Role and Effectiveness of Audit Committee in Corporate Governance of Credit Institutions

Authors: Tina Vuko, Marija Maretić, Marko Čular

Abstract:

The aim of this study is to analyze the role and effectiveness of internal mechanism (audit committee) of corporate governance on credit institutions performance in Croatia. Based on research objective, sample of 78 credit institutions listed on Zagreb Stock Exchange, from 2007 to 2012, has been collected and efficiency index of audit committee (EIAC) has been created. Based on the sample and created EIAC, conclusions are as follows: audit committees of credit institutions have medium efficiency, based on EIAC measurement; there is a significant difference in audit committee effectiveness, in observed period; there is no positive relationship between audit committee effectiveness and credit institution performance; there is a significant difference between level of audit committee effectiveness and audit firm type. Future research should contain increased number of elements in EIAC creation and increased sample, for all obligators who need to establish audit committee.

Keywords: Corporate Governance, Audit Committee, Financial Institutions, Efficiency Index of Audit Committee.

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9308 Time Series Simulation by Conditional Generative Adversarial Net

Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

Abstract:

Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: Conditional Generative Adversarial Net, market and credit risk management, neural network, time series.

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9307 Alternative Animal Feed Additive Obtain with Different Drying Methods from Carrot Unsuitable for Human Consumption

Authors: Rabia Göçmen, Gülşah Kanbur, Sinan Sefa Parlat

Abstract:

This study was conducted to determine that carrot powder obtain by different drying methods (oven and vacuum-freeze dryer) of carrot unfit for human consumption that whether feed additives in animal nutrition or not. Carrots randomly divided 2 groups. First group was dried by using oven, second group was by using vacuum freeze dryer methods. Dried carrot prepared from fresh carrot was analysed nutrient matter (energy, crude protein, crude oil, crude ash, beta carotene, mineral concentration and colour). The differences between groups in terms of energy, crude protein, ash, Ca and Mg was not significant (P>0,05). Crude oil, P, beta carotene content and colour values (L, a, b) with vacuum-freeze dryer group was greater than oven group (P<0,05). Consequently, carrot powder obtained by drying the vacuum-freeze dryer method can be used as a source of carotene. 

Keywords: Carrot, vacuum freeze dryer, oven, beta carotene.

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9306 A New Graphical Password: Combination of Recall & Recognition Based Approach

Authors: Md. Asraful Haque, Babbar Imam

Abstract:

Information Security is the most describing problem in present times. To cop up with the security of the information, the passwords were introduced. The alphanumeric passwords are the most popular authentication method and still used up to now. However, text based passwords suffer from various drawbacks such as they are easy to crack through dictionary attacks, brute force attacks, keylogger, social engineering etc. Graphical Password is a good replacement for text password. Psychological studies say that human can remember pictures better than text. So this is the fact that graphical passwords are easy to remember. But at the same time due to this reason most of the graphical passwords are prone to shoulder surfing. In this paper, we have suggested a shoulder-surfing resistant graphical password authentication method. The system is a combination of recognition and pure recall based techniques. Proposed scheme can be useful for smart hand held devices (like smart phones i.e. PDAs, iPod, iPhone, etc) which are more handy and convenient to use than traditional desktop computer systems.

Keywords: Authentication, Graphical Password, Text Password, Information Security, Shoulder-surfing.

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9305 Analysis of Web User Identification Methods

Authors: Renáta Iváncsy, Sándor Juhász

Abstract:

Web usage mining has become a popular research area, as a huge amount of data is available online. These data can be used for several purposes, such as web personalization, web structure enhancement, web navigation prediction etc. However, the raw log files are not directly usable; they have to be preprocessed in order to transform them into a suitable format for different data mining tasks. One of the key issues in the preprocessing phase is to identify web users. Identifying users based on web log files is not a straightforward problem, thus various methods have been developed. There are several difficulties that have to be overcome, such as client side caching, changing and shared IP addresses and so on. This paper presents three different methods for identifying web users. Two of them are the most commonly used methods in web log mining systems, whereas the third on is our novel approach that uses a complex cookie-based method to identify web users. Furthermore we also take steps towards identifying the individuals behind the impersonal web users. To demonstrate the efficiency of the new method we developed an implementation called Web Activity Tracking (WAT) system that aims at a more precise distinction of web users based on log data. We present some statistical analysis created by the WAT on real data about the behavior of the Hungarian web users and a comprehensive analysis and comparison of the three methods

Keywords: Data preparation, Tracking individuals, Web useridentification, Web usage mining

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9304 Wavelet Based Identification of Second Order Linear System

Authors: Sudipta Majumdar, Harish Parthasarathy

Abstract:

In this paper, a wavelet based method is proposed to identify the constant coefficients of a second order linear system and is compared with the least squares method. The proposed method shows improved accuracy of parameter estimation as compared to the least squares method. Additionally, it has the advantage of smaller data requirement and storage requirement as compared to the least squares method.

Keywords: Least squares method, linear system, system identification, wavelet transform.

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