Search results for: data reduction

Authors: Dong Hoon Lim

Abstract:

A series of microarray experiments produces observations of differential expression for thousands of genes across multiple conditions. Principal component analysis(PCA) has been widely used in multivariate data analysis to reduce the dimensionality of the data in order to simplify subsequent analysis and allow for summarization of the data in a parsimonious manner. PCA, which can be implemented via a singular value decomposition(SVD), is useful for analysis of microarray data. For application of PCA using SVD we use the DNA microarray data for the small round blue cell tumors(SRBCT) of childhood by Khan et al.(2001). To decide the number of components which account for sufficient amount of information we draw scree plot. Biplot, a graphic display associated with PCA, reveals important features that exhibit relationship between variables and also the relationship of variables with observations.

Keywords: Principal component analysis, singular value decomposition, microarray data, SRBCT

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Authors: Youngji Yoo, Cheong-Sool Park, Jun Seok Kim, Young-Hak Lee, Sung-Shick Kim, Jun-Geol Baek

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In the semiconductor manufacturing process, large amounts of data are collected from various sensors of multiple facilities. The collected data from sensors have several different characteristics due to variables such as types of products, former processes and recipes. In general, Statistical Quality Control (SQC) methods assume the normality of the data to detect out-of-control states of processes. Although the collected data have different characteristics, using the data as inputs of SQC will increase variations of data, require wide control limits, and decrease performance to detect outof- control. Therefore, it is necessary to separate similar data groups from mixed data for more accurate process control. In the paper, we propose a regression tree using split algorithm based on Pearson distribution to handle non-normal distribution in parametric method. The regression tree finds similar properties of data from different variables. The experiments using real semiconductor manufacturing process data show improved performance in fault detecting ability.

Keywords: Semiconductor, non-normal mixed process data, clustering, Statistical Quality Control (SQC), regression tree, Pearson distribution system.

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Authors: Abdulla Rahil, Rupert Gammon, Neil Brown

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The rapid growth of renewable energy sources and their integration into the grid have been motivated by the depletion of fossil fuels and environmental issues. Unfortunately, the grid is unable to cope with the predicted growth of renewable energy which would lead to its instability. To solve this problem, energy storage devices could be used. Electrolytic hydrogen production from an electrolyser is considered a promising option since it is a clean energy source (zero emissions). Choosing flexible operation of an electrolyser (producing hydrogen during the off-peak electricity period and stopping at other times) could bring about many benefits like reducing the cost of hydrogen and helping to balance the electric systems. This paper investigates the price of hydrogen during flexible operation compared with continuous operation, while serving the customer (hydrogen filling station) without interruption. The optimization algorithm is applied to investigate the hydrogen station in both cases (flexible and continuous operation). Three different scenarios are tested to see whether the off-peak electricity price could enhance the reduction of the hydrogen cost. These scenarios are: Standard tariff (1 tier system) during the day (assumed 12 p/kWh) while still satisfying the demand for hydrogen; using off-peak electricity at a lower price (assumed 5 p/kWh) and shutting down the electrolyser at other times; using lower price electricity at off-peak times and high price electricity at other times. This study looks at Derna city, which is located on the coast of the Mediterranean Sea (32° 46′ 0 N, 22° 38′ 0 E) with a high potential for wind resource. Hourly wind speed data which were collected over 24½ years from 1990 to 2014 were in addition to data on hourly radiation and hourly electricity demand collected over a one-year period, together with the petrol station data.

Keywords: Hydrogen filling station off-peak electricity, renewable energy, off-peak electricity, electrolytic hydrogen.

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Authors: H. B. Kekre, Tanuja K. Sarode

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Mostly transforms are used for speech data compressions which are lossy algorithms. Such algorithms are tolerable for speech data compression since the loss in quality is not perceived by the human ear. However the vector quantization (VQ) has a potential to give more data compression maintaining the same quality. In this paper we propose speech data compression algorithm using vector quantization technique. We have used VQ algorithms LBG, KPE and FCG. The results table shows computational complexity of these three algorithms. Here we have introduced a new performance parameter Average Fractional Change in Speech Sample (AFCSS). Our FCG algorithm gives far better performance considering mean absolute error, AFCSS and complexity as compared to others.

Keywords: Vector Quantization, Data Compression, Encoding, , Speech coding.

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Authors: Eun-Jung Ko, Hyung-Jik Lee, Jeun-Woo Lee

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In ubiqutious healthcare environment, user's health data are transfered to the remote healthcare server by the user's wearable system or mobile phone. These collected user's health data should be managed and analyzed in the healthcare server, so that care giver or user can monitor user's physiological state. In this paper, we designed and developed the intelligent Healthcare Server to manage the user's health data using CDSS and ontology. Our system can analyze user's health data semantically using CDSS and ontology, and report the result of user's physiological raw data to the user and care giver.

Keywords: u-healthcare, CDSS, healthcare server, health data, ontology.

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Authors: Qin Ding, Jim Gasvoda

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Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups have diverse properties. Many heuristic algorithms have been applied to the clustering problem, which is known to be NP Hard. Genetic algorithms have been used in a wide variety of fields to perform clustering, however, the technique normally has a long running time in terms of input set size. This paper proposes an efficient genetic algorithm for clustering on very large data sets, especially on image data sets. The genetic algorithm uses the most time efficient techniques along with preprocessing of the input data set. We test our algorithm on both artificial and real image data sets, both of which are of large size. The experimental results show that our algorithm outperforms the k-means algorithm in terms of running time as well as the quality of the clustering.

Keywords: Clustering, data mining, genetic algorithm, image data.

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Authors: Ashly Joseph

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Modern businesses struggle significantly to secure and manage their data properly as the volume and complexity of their data both expand exponentially. Through the use of a multi-layered defense strategy, a centralized management platform, and cutting-edge technologies like AI, this research paper presents a comprehensive framework to integrate data security and management. The constraints of current data protection and management strategies, technological advancements, and the evolving threat landscape are all examined in this article. It suggests best practices for putting into practice integrated data security and governance models, placing an emphasis on ongoing adaptation. The advantages mentioned include a strengthened security posture, simpler procedures, lower costs, and reduced complexity. Additionally, issues including skill shortages, antiquated systems, and cultural obstacles are examined. Security executives and Chief Information Security Officers are given practical advice on how to evaluate, plan, and put into place strong data-centric security and management capabilities. The goal of the paper is to provide a thorough study of the data security and management landscape and to arm contemporary businesses with the knowledge they need to be proactive in protecting their data assets.

Keywords: Data security, security management, cloud computing, cybersecurity, data governance, security architecture, data management.

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Authors: Miroslav Byrtus

Abstract:

Large rotating systems, especially gear drives and gearboxes, occur as parts of many mechanical devices transmitting the torque with relatively small loss of power. With the increased demand for high speed machinery, mathematical modeling and dynamic analysis of gear drives gained importance. Mathematical description of such mechanical systems is a complex task evolving for several decades. In gear drive dynamic models, which include flexible shafts, bearings and gearing and use the finite elements, nonlinear effects due to gear mesh and bearings are usually ignored, for such models have large number of degrees of freedom (DOF) and it is computationally expensive to analyze nonlinear systems with large number of DOF. Therefore, these models are not suitable for simulation of nonlinear behavior with amplitude jumps in frequency response. The contribution uses a methodology of nonlinear large rotating system modeling which is based on degrees of freedom (DOF) number reduction using modal synthesis method (MSM). The MSM enables significant DOF number reduction while keeping the nonlinear behavior of the system in a specific frequency range. Further, the MSM with DOF number reduction is suitable for including detail models of nonlinear couplings (mainly gear and bearing couplings) into the complete gear drive models. Since each subsystem is modeled separately using different FEM systems, it is advantageous to parameterize models of subsystems and to use the parameterization for optimization of chosen design parameters. Final complex model of gear drive is assembled in MATLAB and MATLAB tools are used for dynamical analysis of the nonlinear system. The contribution is further focused on developing of a methodology for investigation of behavior of the system by Nonlinear Normal Modes with combination of the MSM using numerical continuation method. The proposed methodology will be tested using a two-stage gearbox including its housing.

Keywords: Vibro-impact system, rotating system, gear drive, modal synthesis method, numerical continuation method, periodic solution.

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Authors: R. Nedunchezhian, K. Anbumani

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A big organization may have multiple branches spread across different locations. Processing of data from these branches becomes a huge task when innumerable transactions take place. Also, branches may be reluctant to forward their data for centralized processing but are ready to pass their association rules. Local mining may also generate a large amount of rules. Further, it is not practically possible for all local data sources to be of the same size. A model is proposed for discovering valid rules from different sized data sources where the valid rules are high weighted rules. These rules can be obtained from the high frequency rules generated from each of the data sources. A data source selection procedure is considered in order to efficiently synthesize rules. Support Equalization is another method proposed which focuses on eliminating low frequency rules at the local sites itself thus reducing the rules by a significant amount.

Keywords: Association rules, multiple data stores, synthesizing, valid rules.

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Authors: Carmen Maria Moraru, Iuliana Stefan, Ovidiu Balteanu, Ciprian Bucur, Liviu Stefan, Anisia Bornea, Ioan Stefanescu

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The implementation of the new software and hardware-s technologies for tritium processing nuclear plants, and especially those with an experimental character or of new technology developments shows a coefficient of complexity due to issues raised by the implementation of the performing instrumentation and equipment into a unitary monitoring system of the nuclear technological process of tritium removal. Keeping the system-s flexibility is a demand of the nuclear experimental plants for which the change of configuration, process and parameters is something usual. The big amount of data that needs to be processed stored and accessed for real time simulation and optimization demands the achievement of the virtual technologic platform where the data acquiring, control and analysis systems of the technological process can be integrated with a developed technological monitoring system. Thus, integrated computing and monitoring systems needed for the supervising of the technological process will be executed, to be continued with the execution of optimization system, by choosing new and performed methods corresponding to the technological processes within the tritium removal processing nuclear plants. The developing software applications is executed with the support of the program packages dedicated to industrial processes and they will include acquisition and monitoring sub-modules, named “virtually" as well as the storage sub-module of the process data later required for the software of optimization and simulation of the technological process for tritium removal. The system plays and important role in the environment protection and durable development through new technologies, that is – the reduction of and fight against industrial accidents in the case of tritium processing nuclear plants. Research for monitoring optimisation of nuclear processes is also a major driving force for economic and social development.

Keywords: Monitoring system, process simulation.

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Authors: Jincheol Han, Hyunsun Ju, Jonghoon Chun

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Sharing consistent and correct master data among disparate applications in a reverse-logistics chain has long been recognized as an intricate problem. Although a master data management (MDM) system can surely assume that responsibility, applications that need to co-operate with it must comply with proprietary query interfaces provided by the specific MDM system. In this paper, we present a RFID-ready MDM system which makes master data readily available for any participating applications in a reverse-logistics chain. We propose a RFID-wrapper as a part of our MDM. It acts as a gateway between any data retrieval request and query interfaces that process it. With the RFID-wrapper, any participating applications in a reverse-logistics chain can easily retrieve master data in a way that is analogous to retrieval of any other RFID-based logistics transactional data.

Keywords: Reverse Logistics, Master Data Management, RFID.

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Authors: Ali Beydoun, Hamzé H. Alaeddine

Abstract:

One of the main challenges in MIMO-OFDM system to achieve the expected performances in terms of data rate and robustness against multi-path fading channels is the channel estimation. Several methods were proposed in the literature based on either least square (LS) or minimum mean squared error (MMSE) estimators. These methods present high implementation complexity as they require the inversion of large matrices. In order to overcome this problem and to reduce the complexity, this paper presents a solution that benefits from the use of the STBC encoder and transforms the channel estimation process into a set of simple linear operations. The proposed method is evaluated via simulation in AWGN-Rayleigh fading channel. Simulation results show a maximum reduction of 6.85% of the bit error rate (BER) compared to the one obtained with the ideal case where the receiver has a perfect knowledge of the channel.

Keywords: Channel estimation, MIMO, OFDM, STBC, CAZAC sequence.

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Authors: Entisar A. Elgmati

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Recurrent event data is a special type of multivariate survival data. Dynamic and frailty models are one of the approaches that dealt with this kind of data. A comparison between these two models is studied using the empirical standard deviation of the standardized martingale residual processes as a way of assessing the fit of the two models based on the Aalen additive regression model. Here we found both approaches took heterogeneity into account and produce residual standard deviations close to each other both in the simulation study and in the real data set.

Keywords: Dynamic, frailty, misspecification, recurrent events.

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Authors: Lenka Hurtalová, Eva Tillová, Mária Chalupová, Juraj Belan, Milan Uhríčik

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The secondary alloy A226 is used for many automotive casting produced by mould casting and high pressure die casting. This alloy has excellent castability, good mechanical properties and cost-effectiveness. Production of primary aluminium alloys belong to heavy source fouling of life environs. The European Union calls for the emission reduction and reduction in energy consumption therefore increase production of recycled (secondary) aluminium cast alloys. The contribution is deal with influence of recycling on the quality of the casting made from A226 in automotive industry. The properties of the casting made from secondary aluminium alloys were compared with the required properties of primary aluminium alloys. The effect of recycling on microstructure was observed using combination different analytical techniques (light microscopy upon black-white etching, scanning electron microscopy - SEM upon deep etching and energy dispersive X-ray analysis - EDX). These techniques were used for the identification of the various structure parameters, which was used to compare secondary alloy microstructure with primary alloy microstructure.

Keywords: A226 secondary aluminium alloy, deep etching, mechanical properties, recycling foundry aluminium alloy.

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Authors: Minsoo Lee, Yoon-kyung Lee, Hyejung Yoon, Soo-kyung Song, Sujeong Cheong

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Data Warehousing tools have become very popular and currently many of them have moved to Web-based user interfaces to make it easier to access and use the tools. The next step is to enable these tools to be used within a portal framework. The portal framework consists of pages having several small windows that contain individual data warehouse query results. There are several issues that need to be considered when designing the architecture for a portal enabled data warehouse query tool. Some issues need special techniques that can overcome the limitations that are imposed by the nature of data warehouse queries. Issues such as single sign-on, query result caching and sharing, customization, scheduling and authorization need to be considered. This paper discusses such issues and suggests an architecture to support data warehouse queries within Web portal frameworks.

Keywords: Data Warehousing tools, data warehousing queries, web portal frameworks.

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Authors: B. Bina, M.H. Mehdinejad, Gunnel Dalhammer, Guna RajaraoM. Nikaeen, H. Movahedian Attar

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Coagulation of water involves the use of coagulating agents to bring the suspended matter in the raw water together for settling and the filtration stage. Present study is aimed to examine the effects of aluminum sulfate as coagulant in conjunction with Moringa Oleifera Coagulant Protein as coagulant aid on turbidity, hardness, and bacteria in turbid water. A conventional jar test apparatus was employed for the tests. The best removal was observed at a pH of 7 to 7.5 for all turbidities. Turbidity removal efficiency was resulted between % 80 to % 99 by Moringa Oleifera Coagulant Protein as coagulant aid. Dosage of coagulant and coagulant aid decreased with increasing turbidity. In addition, Moringa Oleifera Coagulant Protein significantly has reduced the required dosage of primary coagulant. Residual Al+3 in treated water were less than 0.2 mg/l and meets the environmental protection agency guidelines. The results showed that turbidity reduction of % 85.9- % 98 paralleled by a primary Escherichia coli reduction of 1-3 log units (99.2 – 99.97%) was obtained within the first 1 to 2 h of treatment. In conclusions, Moringa Oleifera Coagulant Protein as coagulant aid can be used for drinking water treatment without the risk of organic or nutrient release. We demonstrated that optimal design method is an efficient approach for optimization of coagulation-flocculation process and appropriate for raw water treatment.

Keywords: MOCP, Coagulant aid, turbidity removal, E.coliremoval, water, treatment

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Authors: Futoshi Kakuta, Takashi Ishida

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Sewage sludge is a biomass resource that can create a solid fuel and electricity. Utilizing sewage sludge as a renewable energy can contribute to the reduction of greenhouse gases. In Japan, the "National Plan for the Promotion of Biomass Utilization" and the “Priority Plan for Social Infrastructure Development" were approved at cabinet meetings in December 2010 and August 2012, respectively, to promote the energy utilization of sewage sludge. This study investigated costs and greenhouse gas emission in different sewage sludge treatments with technologies for energy from sewage sludge. Expenses were estimated based on capital costs and O&M costs including energy consumption of solid fuel plants and biogas power generation plants for sewage sludge. Results showed that the cost of sludge digestion treatment with solid fuel technologies was 8% lower than landfill disposal. The greenhouse gas emission of sludge digestion treatment with solid fuel technologies was also 6,390t as CO2 smaller than landfill disposal. Biogas power generation reduced the electricity of a wastewater treatment plant by 30% and the cost by 5%.

Keywords: Global warming counter measure, energy technology, solid fuel production, biogas.

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Authors: H. Soleimanimehr, M. J. Nategh , S. Amini

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Development of artificial neural network (ANN) for prediction of aluminum workpieces' surface roughness in ultrasonicvibration assisted turning (UAT) has been the subject of the present study. Tool wear as the main cause of surface roughness was also investigated. ANN was trained through experimental data obtained on the basis of full factorial design of experiments. Various influential machining parameters were taken into consideration. It was illustrated that a multilayer perceptron neural network could efficiently model the surface roughness as the response of the network, with an error less than ten percent. The performance of the trained network was verified by further experiments. The results of UAT were compared with the results of conventional turning experiments carried out with similar machining parameters except for the vibration amplitude whence considerable reduction was observed in the built-up edge and the surface roughness.

Keywords: Aluminum, Artificial Neural Network (ANN), BuiltupEdge, Surface Roughness, Tool Wear, Ultrasonic VibrationAssisted Turning (UAT).

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Authors: M. R. Aghaebrahimi, S. H. Zahiri, M. Amiri

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In this paper a data miner based on the learning automata is proposed and is called LA-miner. The LA-miner extracts classification rules from data sets automatically. The proposed algorithm is established based on the function optimization using learning automata. The experimental results on three benchmarks indicate that the performance of the proposed LA-miner is comparable with (sometimes better than) the Ant-miner (a data miner algorithm based on the Ant Colony optimization algorithm) and CNZ (a well-known data mining algorithm for classification).

Keywords: Data mining, Learning automata, Classification rules, Knowledge discovery.

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Authors: A. Krishna Veni, R.Geetha

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Wireless Sensor Networks (WSNs) are suitable for many scenarios in the real world. The retrieval of data is made efficient by the data aggregation techniques. Many techniques for the data aggregation are offered and most of the existing schemes are not energy efficient and secure. However, the existing techniques use the traditional clustering approach where there is a delay during the packet transmission since there is no proper scheduling. The presented system uses the Velocity Energy-efficient and Link-aware Cluster-Tree (VELCT) scheme in which there is a Data Collection Tree (DCT) which improves the lifetime of the network. The VELCT scheme and the construction of DCT reduce the delay and traffic. The network lifetime can be increased by avoiding the frequent change in cluster topology. Secure and Efficient Transmission of Aggregated data (SETA) improves the security of the data transmission via the trust value of the nodes prior the aggregation of data. Since SETA considers the data only from the trustworthy nodes for aggregation, it is more secure in transmitting the data thereby improving the accuracy of aggregated data.

Keywords: Aggregation, lifetime, network security, wireless sensor network.

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Authors: M. Amir Abas, M. Dahlui

Abstract:

This paper presents the development of analysis tools for Home Agriculture project. The tools are required for monitoring the condition of greenhouse which involves two components: measurement hardware and data analysis engine. Measurement hardware is functioned to measure environment parameters such as temperature, humidity, air quality, dust and etc while analysis tool is used to analyse and interpret the integrated data against the condition of weather, quality of health, irradiance, quality of soil and etc. The current development of the tools is completed for off-line data recorded technique. The data is saved in MMC and transferred via ZigBee to Environment Data Manager (EDM) for data analysis. EDM converts the raw data and plot three combination graphs. It has been applied in monitoring three months data measurement for irradiance, temperature and humidity of the greenhouse..

Keywords: Monitoring, Environment, Greenhouse, Analysis tools

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Authors: Subal Kar, Amitesh Kumar, A. Majumder, S. K. Ghosh, S. Saha, S. S. Sikdar, T. K. Saha

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CRLH (composite right/left-handed) based and SRR (split-ring resonator) based filters have been designed at microwave frequency which can provide better performance compared to conventional edge-coupled band-pass filter designed around the same frequency, 2.45 GHz. Both CRLH and SRR are unit cells used in metamaterial design. The primary aim of designing filters with such structures is to realize size reduction and also to realize novel filter performance. The CRLH based filter has been designed in microstrip transmission line, while the SRR based filter is designed with SRR loading in waveguide. The CRLH based filter designed at 2.45 GHz provides an insertion loss of 1.6 dB with harmonic suppression up to 10 GHz with 67 % size reduction when compared with a conventional edge-coupled band-pass filter designed around the same frequency. One dimensional (1-D) SRR matrix loaded in a waveguide shows the possibility of realizing a stop-band with sharp skirts in the pass-band while a stop-band in the pass-band of normal rectangular waveguide with tailoring of the dimensions of SRR unit cells. Such filters are expected to be very useful for communication systems at microwave frequency.

Keywords: BPF, CRLH, Harmonic, Metamaterial, SRR, Waveguide.

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Authors: Mark Lin, Periklis Papadopoulos

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This paper explores the aerodynamics of the formula racecar when a ‘halo’ driver-protection device is added to the chassis. The halo protection device was introduced at the start of the 2018 racing season as a safety measure against foreign object impacts that a driver may encounter when driving an open-wheel racecar. In the one-year since its introduction, the device has received wide acclaim for protecting the driver on two separate occasions. The benefit of such a safety device certainly cannot be disputed. However, by adding the halo device to a car, it changes the airflow around the vehicle, and most notably, to the engine air-intake and the rear wing. These negative effects in the air supply to the engine, and equally to the downforce created by the rear wing are studied in this paper using numerical technique, and the resulting CFD outputs are presented and discussed. Comparing racecar design prior to and after the introduction of the halo device, it is shown that the design of the air intake and the rear wing has not followed suit since the addition of the halo device. The reduction of engine intake mass flow due to the halo device is computed and presented for various speeds the car may be going. Because of the location of the halo device in relation to the air intake, airflow is directed away from the engine, making the engine perform less than optimal. The reduction is quantified in this paper to show the correspondence to reduce the engine output when compared to a similar car without the halo device. This paper shows that through aerodynamic arguments, the engine in a halo car will not receive unobstructed, clean airflow that a non-halo car does. Another negative effect is on the downforce created by the rear wing. Because the amount of downforce created by the rear wing is influenced by every component that comes before it, when a halo device is added upstream to the rear wing, airflow is obstructed, and less is available for making downforce. This reduction in downforce is especially dramatic as the speed is increased. This paper presents a graph of downforce over a range of speeds for a car with and without the halo device. Acknowledging that although driver safety is paramount, the negative effect of this safety device on the performance of the car should still be well understood so that any possible redesign to mitigate these negative effects can be taken into account in next year’s rules regulation.

Keywords: Automotive aerodynamics, halo device, downforce. engine intake.

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Authors: Jianyin Lu, Masayoshi Seike, Wei Liu, Peihong Wu, Lihua Wang, Yihua Wu, Yasuhiro Naito, Hiromu Nakajima, Yasuhiro Kouchi

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To extract the important physiological factors related to diabetes from an oral glucose tolerance test (OGTT) by mathematical modeling, highly informative but convenient protocols are required. Current models require a large number of samples and extended period of testing, which is not practical for daily use. The purpose of this study is to make model assessments possible even from a reduced number of samples taken over a relatively short period. For this purpose, test values were extrapolated using a support vector machine. A good correlation was found between reference and extrapolated values in evaluated 741 OGTTs. This result indicates that a reduction in the number of clinical test is possible through a computational approach.

Keywords: SVM regression, OGTT, diabetes, mathematical model

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Authors: Emad T. Khalaf, Norrozila Sulaiman

Abstract:

Many researchers are working on information hiding techniques using different ideas and areas to hide their secrete data. This paper introduces a robust technique of hiding secret data in image based on LSB insertion and RSA encryption technique. The key of the proposed technique is to encrypt the secret data. Then the encrypted data will be converted into a bit stream and divided it into number of segments. However, the cover image will also be divided into the same number of segments. Each segment of data will be compared with each segment of image to find the best match segment, in order to create a new random sequence of segments to be inserted then in a cover image. Experimental results show that the proposed technique has a high security level and produced better stego-image quality.

Keywords: steganography; LSB Matching; RSA Encryption; data segments

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Authors: I. Djefour, M. Saidi, I. Tlemsani, S. Toubal

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Lignin is a molecule derived from wood and also generated as waste from the paper industry. With a view to its valorization and protection of the environment, we are interested in its use as a superplasticizer-type adjuvant in mortars and concretes to improve their mechanical strengths. The additives of the concrete have a very strong influence on the properties of the fresh and / or hardened concrete. This study examines the development and use of industrial waste and lignin extracted from a renewable natural source (wood) in cementitious materials. The use of these resources is known at present as a definite resurgence of interest in the development of building materials. Physicomechanical characteristics of mortars are determined by optimization quantity of the natural superplasticizer. The results show that the mechanical strengths of mortars based on natural adjuvant have improved by 20% (64 MPa) for a W/C ratio = 0.4, and the amount of natural adjuvant of dry extract needed is 40 times smaller than commercial adjuvant. This study has a scientific impact (improving the performance of the mortar with an increase in compactness and reduction of the quantity of water), ecological use of the lignin waste generated by the paper industry) and economic reduction of the cost price necessary to elaboration of self-compacting mortars and concretes).

Keywords: Biopolymer, lignin, industrial waste, mechanical resistances, self-compacting mortars.

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Authors: S. Sarumathi, N. Shanthi

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Due to the fast and flawless technological innovation there is a tremendous amount of data dumping all over the world in every domain such as Pattern Recognition, Machine Learning, Spatial Data Mining, Image Analysis, Fraudulent Analysis, World Wide Web etc., This issue turns to be more essential for developing several tools for data mining functionalities. The major aim of this paper is to analyze various tools which are used to build a resourceful analytical or descriptive model for handling large amount of information more efficiently and user friendly. In this survey the diverse tools are illustrated with their extensive technical paradigm, outstanding graphical interface and inbuilt multipath algorithms in which it is very useful for handling significant amount of data more indeed.

Keywords: Classification, Clustering, Data Mining, Machine learning, Visualization.

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Authors: B. Alamsari, S. Torii, A. Trianto, Y. Bindar

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Isobaric and cooling zone of iron ore reactor have been simulated. In this paper, heat and mass transfer equation are formulated to perform the temperature and concentration of gas and solid phase respectively. Temperature profile for isobaric zone is simulated on the range temperature of 873-1163K while cooling zone is simulated on the range temperature of 733-1139K. The simulation results have a good agreement with the plant data. Total carbon formation in the isobaric zone is only 30% of total carbon contained in the sponge iron product. The formation of Fe3C in isobaric zone reduces metallization degree up to 0.58% whereas reduction of metallization degree in cooling zone up to 1.139%. The decreasing of sponge iron temperature in the isobaric and cooling zone is around 300 K and 600 K respectively.

Keywords: Mathematical Model, Iron Ore Reactor, Cooling Zone, Isobaric zone.

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Authors: Guolong Zhong, Venkatesh Chennam Vijay, Ilias Oraifige

Abstract:

In the last 20 years, Knowledge Based Engineering (KBE) has shown its advantages in product development in different engineering areas such as automation, mechanical, civil and aerospace engineering in terms of digital design automation and cost reduction by automating repetitive design tasks through capturing, integrating, utilising and reusing the existing knowledge required in various aspects of the product design. However, in primary design stages, the descriptive information of a product is discrete and unorganized while knowledge is in various forms instead of pure data. Thus, it is crucial to have an integrated product model which can represent the entire product information and its associated knowledge at the beginning of the product design. One of the shortcomings of the existing product models is a lack of required knowledge representation in various aspects of product design and its mapping to an interoperable schema. To overcome the limitation of the existing product model and methodologies, two key factors are considered. First, the product model must have well-defined classes that can represent the entire product information and its associated knowledge. Second, the product model needs to be represented in an interoperable schema to ensure a steady data exchange between different product modelling platforms and CAD software. This paper introduced a method to provide a general product model as a generative representation of a product, which consists of the geometry information and non-geometry information, through a product modelling framework. The proposed method for capturing the knowledge from the designers through a knowledge file provides a simple and efficient way of collecting and transferring knowledge. Further, the knowledge schema provides a clear view and format on the data that needed to be gathered in order to achieve a unified knowledge exchange between different platforms. This study used a game-based platform to make product modelling environment accessible for non-engineers. Further the paper goes on to test use case based on the proposed game-based product modelling environment to validate the effectiveness among non-engineers.

Keywords: Game-based learning, knowledge based engineering, product modelling, design automation.

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Authors: Shigeaki Sakurai, Makino Kyoko, Shigeru Matsumoto

Abstract:

This paper proposes a method that predicts attractive evaluation objects. In the learning phase, the method inductively acquires trend rules from complex sequential data. The data is composed of two types of data. One is numerical sequential data. Each evaluation object has respective numerical sequential data. The other is text sequential data. Each evaluation object is described in texts. The trend rules represent changes of numerical values related to evaluation objects. In the prediction phase, the method applies new text sequential data to the trend rules and evaluates which evaluation objects are attractive. This paper verifies the effect of the proposed method by using stock price sequences and news headline sequences. In these sequences, each stock brand corresponds to an evaluation object. This paper discusses validity of predicted attractive evaluation objects, the process time of each phase, and the possibility of application tasks.

Keywords: Trend rule, frequent pattern, numerical sequential data, text sequential data, evaluation object.

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