Search results for: spindle noise

Authors: Kensho Takahashi, Ko Watanabe, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara

Abstract:

Near-infrared spectroscopy (NIRS) has been widely used as a non-invasive method to measure brain activity, but it is corrupted by baseline drift noise. Here we present a method to measure regional cerebral blood flow as a derivative of NIRS output. We investigate whether, when listening to languages, blood flow can reasonably localize and represent regional brain activity or not. The prefrontal blood flow distribution pattern when advanced second-language listeners listened to a second language (L2) was most similar to that when listening to their first language (L1) among the patterns of mean and standard deviation. In experiments with 25 healthy subjects, the maximum blood flow was localized to the left BA46 of advanced listeners. The blood flow presented is robust to baseline drift and stably localizes regional brain activity.

Keywords: NIRS, oxy-hemoglobin, baseline drift, blood flow, working memory, BA46, first language, second language

Procedia PDF Downloads 537

Authors: Hyun-Woo Cho

Abstract:

The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

Procedia PDF Downloads 537

Authors: Zeradam Yeshiwas, A. Krishnaia

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The aim of this study is to verify the resulting surface roughness of parts formed by the Single-Point Incremental Forming (SPIF) process for an ISO 3574 Drawing Quality Cold Rolled CR2 Steel. The chemical composition of drawing quality Cold Rolled CR2 steel is comprised of 0.12 percent of carbon, 0.5 percent of manganese, 0.035 percent of sulfur, 0.04 percent phosphorous, and the remaining percentage is iron with negligible impurities. The experiments were performed on a 3-axis vertical CNC milling machining center equipped with a tool setup comprising a fixture and forming tools specifically designed and fabricated for the process. The CNC milling machine was used to transfer the tool path code generated in Mastercam 2017 environment into three-dimensional motions by the linear incremental progress of the spindle. The blanks of Drawing Quality Cold Rolled CR2 steel sheets of 1 mm of thickness have been fixed along their periphery by a fixture and hardened high-speed steel (HSS) tools with a hemispherical tip of 8, 10 and 12mm of diameter were employed to fabricate sample parts. To investigate the surface roughness, hyperbolic-cone shape specimens were fabricated based on the chosen experimental design. The effect of process parameters on the surface roughness was studied using three important process parameters, i.e., tool diameter, feed rate, and step depth. In this study, the Taylor-Hobson Surtronic 3+ surface roughness tester profilometer was used to determine the surface roughness of the parts fabricated using the arithmetic mean deviation (Rₐ). In this instrument, a small tip is dragged across a surface while its deflection is recorded. Finally, the optimum process parameters and the main factor affecting surface roughness were found using the Taguchi design of the experiment and ANOVA. A Taguchi experiment design with three factors and three levels for each factor, the standard orthogonal array L9 (3³) was selected for the study using the array selection table. The lowest value of surface roughness is significant for surface roughness improvement. For this objective, the ‘‘smaller-the-better’’ equation was used for the calculation of the S/N ratio. The finishing roughness parameter Ra has been measured for the different process combinations. The arithmetic means deviation (Rₐ) was measured via the experimental design for each combination of the control factors by using Taguchi experimental design. Four roughness measurements were taken for a single component and the average roughness was taken to optimize the surface roughness. The lowest value of Rₐ is very important for surface roughness improvement. For this reason, the ‘‘smaller-the-better’’ Equation was used for the calculation of the S/N ratio. Analysis of the effect of each control factor on the surface roughness was performed with a ‘‘S/N response table’’. Optimum surface roughness was obtained at a feed rate of 1500 mm/min, with a tool radius of 12 mm, and with a step depth of 0.5 mm. The ANOVA result shows that step depth is an essential factor affecting surface roughness (91.1 %).

Keywords: incremental forming, SPIF, drawing quality steel, surface roughness, roughness behavior

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Authors: M. A. Alavianmehr, A. Tashk, A. Sodagaran

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Modeling background and moving objects are significant techniques for video surveillance and other video processing applications. This paper presents a foreground detection algorithm that is robust against illumination changes and noise based on adaptive mixture Gaussian model (GMM), and provides a novel and practical choice for intelligent video surveillance systems using static cameras. In the previous methods, the image of still objects (background image) is not significant. On the contrary, this method is based on forming a meticulous background image and exploiting it for separating moving objects from their background. The background image is specified either manually, by taking an image without vehicles, or is detected in real-time by forming a mathematical or exponential average of successive images. The proposed scheme can offer low image degradation. The simulation results demonstrate high degree of performance for the proposed method.

Keywords: image processing, background models, video surveillance, foreground detection, Gaussian mixture model

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Authors: Tanish Mittal, Preyansh Agrawal, Esha Pahwa, Aarya Makwana

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Multi-Scale and U-shaped Networks are widely used in various image restoration problems, including deblurring. Keeping in mind the wide range of applications, we present a comparison of these architectures and their effects on image deblurring. We also introduce a new block called as NFResblock. It consists of a Fast Fourier Transformation layer and a series of modified Non-Linear Activation Free Blocks. Based on these architectures and additions, we introduce NFResnet and NFResnet+, which are modified multi-scale and U-Net architectures, respectively. We also use three differ-ent loss functions to train these architectures: Charbonnier Loss, Edge Loss, and Frequency Reconstruction Loss. Extensive experiments on the Deep Video Deblurring dataset, along with ablation studies for each component, have been presented in this paper. The proposed architectures achieve a considerable increase in Peak Signal to Noise (PSNR) ratio and Structural Similarity Index (SSIM) value.

Keywords: multi-scale, Unet, deblurring, FFT, resblock, NAF-block, nfresnet, charbonnier, edge, frequency reconstruction

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

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Authors: Soha A Soliman, Yasser A Ahmed, Mohamed A Khalaf

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Although the enormous literature describing the histology of the stomach of different avian species during the posthatching development, the available literature on the pre-hatching development of quail stomach development is scanty. Thus, the current study was undertaken to provide a careful description of the main histological events during the embryonic development of quail stomach. To achieve this aim, daily histological specimens from the stomach of quail of 4 days post-incubation till the day 17 (few hours before hatching) were examined with light microscopy. The current study showed that the primitive gut tube of the embryonic quail appeared at the 4th day post incubation, and both parts of stomach (proventriculus and gizzard) were similar in structure and composed of endodermal epithelium of pseudostratified type surrounded by undifferentiated mesenchymal tissue. The sequences of the developmental events in the gut tube were preceded in a cranio-caudal pattern. By the 5th day, the endodermal covering of the primitive proventriculus gave rise to sac-like invaginations. The primitive gizzard was distinguished into thick-walled bodies and thin-walled sacs. In the 6th day, the prospective proventricular glandular epithelium became canalized and the muscular layer was developed in the cranial part of the proventriculus, whereas the primitive muscular coat of the gizzard was represented by a layer of condensed mesenchyme. In the 7th day, the proventricular glandular epithelial invaginations increased in depth and number, while, the muscularis mucosa and the muscular layer began to be distinguished. In the 8th day, the myoblasts differentiated into spindle shaped smooth muscle fibers. In the 10th day, branching of the proventricular glands began. The branching continued later on. The surface and the glandular epithelium were transformed into simple columnar type in the 12th day. The epithelial covering of the gizzard gave rise to tubular invaginations lined by simple cuboidal epithelium and the surface epithelium became simple columnar. Canalization of the tubular glands was recognized in the 14th day. In the 15th day, the proventricular surface epithelium invaginated in an concentric manner around a central cavity to form immature secretory units. The central cavity was lined by eosinophilic cells which form the ductal epithelia. The peripheral lamellae were lined by basophilic cells; the undifferentiated oxyntico-peptic cells. Entero-endocrine cells stained positive for silver impregnation in the proventricular glands. The mucosal folding in the gizzard appeared in the 15th day to form the plicae and the sulci. The wall of the proventriculus and gizzard in the 17th day acquired the main histological features of post-hatching birds, but neither the surface nor the ductal epithelium were differentiated to mucous producing cells. The current results shoed be considered in the molecular developmental studies.

Keywords: quail, proventriculus, gizzard, pre-hatching, histology

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Authors: Katarzyna Drela, Miroslaw Wielgos, Mikolaj Wrobel, Barbara Lukomska

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Mesenchymal stem cells (MSCs) have a great potential in regenerative medicine. Since the initial number of isolated MSCs is limited, in vitro propagation is often required to reach sufficient numbers of cells for therapeutic applications. During long-term culture MSCs may undergo genetic or epigenetic alterations that subsequently increase the probability of spontaneous malignant transformation. Thus, factors that influence genomic stability of MSCs following long-term expansions need to be clarified before cultured MSCs are employed for clinical application. The aim of our study was to investigate the potential for spontaneous transformation of human neonatal cord blood (HUCB-MSCs) and adult bone marrow (BM-MSCs) derived MSCs. Materials and Methods: HUCB-MSCs and BM-MSCs were isolated by standard Ficoll gradient centrifugations method. Isolated cells were initially plated in high density 106 cells per cm2. After 48 h medium were changed and non-adherent cells were removed. The malignant transformation of MSCs in vitro was evaluated by morphological changes, proliferation rate, ability to enter cell senescence, the telomerase expression and chromosomal abnormality. Proliferation of MSCs was analyzed with WST-1 reduction method and population doubling time (PDT) was calculated at different culture stages. Then the expression pattern of genes characteristic for mesenchymal or epithelial cells, as well as transcriptions factors were examined by RT-PCR. Concomitantly, immunocytochemical analysis of gene-related proteins was employed. Results: Our studies showed that MSCs from all bone marrow isolations ultimately entered senescence and did not undergo spontaneous malignant transformation. However, HUCB-MSCs from one of the 15 donors displayed an increased proliferation rate, failed to enter senescence, and exhibited an altered cell morphology. In this sample we observed two different cell phenotypes: one mesenchymal-like exhibited spindle shaped morphology and express specific mesenchymal surface markers (CD73, CD90, CD105, CD166) with low proliferation rate, and the second one with round, densely package epithelial-like cells with significantly increased proliferation rate. The PDT of epithelial-like populations was around 1day and 100% of cells were positive for proliferation marker Ki-67. Moreover, HUCB-MSCs showed a positive expression of human telomerase reverse transcriptase (hTERT), cMYC and exhibit increased number of CFU during the long-term culture in vitro. Furthermore, karyotype analysis revealed chromosomal abnormalities including duplications. Conclusions: Our studies demonstrate that HUCB-MSCs are susceptible to spontaneous malignant transformation during long-term culture. Spontaneous malignant transformation process following in vitro culture has enormous effect on the biosafety issues of future cell-based therapies and regenerative medicine regimens.

Keywords: mesenchymal stem cells, spontaneous, transformation, long-term culture

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Authors: S. Alotaibi, S. Omer, Y. Su

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The conventional Internal Combustion Engine (ICE) based vehicles are a threat to the environment as they account for a large proportion of the overall greenhouse gas (GHG) emissions in the world. Hence, it is required to replace these vehicles with more environment-friendly vehicles. Electric Vehicles (EVs) are promising technologies which offer both human comfort “noise, pollution” as well as reduced (or no) emissions of GHGs. In this paper, different types of EVs are reviewed and their advantages and disadvantages are identified. It is found that in terms of fuel economy, Plug-in Hybrid EVs (PHEVs) have the best fuel economy, followed by Hybrid EVs (HEVs) and ICE vehicles. Since Battery EVs (BEVs) do not use any fuel, their fuel economy is estimated as price per kilometer. Similarly, in terms of GHG emissions, BEVs are the most environmentally friendly since they do not result in any emissions while HEVs and PHEVs produce less emissions compared to the conventional ICE based vehicles. Fuel Cell EVs (FCEVs) are also zero-emission vehicles, but they have large costs associated with them. Finally, if the electricity is provided by using the renewable energy technologies through grid connection, then BEVs could be considered as zero emission vehicles.

Keywords: electric vehicles, zero emission car, fuel economy, CO₂ footprint

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Authors: Manik Sharma, Ganapathy Krishnamurthi

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The cost of some drugs and medical treatments has risen in recent years, that many patients are having to go without. A classification project could make researchers more efficient. One of the more surprising reasons behind the cost is how long it takes to bring new treatments to market. Despite improvements in technology and science, research and development continues to lag. In fact, finding new treatment takes, on average, more than 10 years and costs hundreds of millions of dollars. If successful, we could dramatically improve the industry's ability to model cellular images according to their relevant biology. In turn, greatly decreasing the cost of treatments and ensure these treatments get to patients faster. This work aims at solving a part of this problem by creating a cellular image classification model which can decipher the genetic perturbations in cell (occurring naturally or artificially). Another interesting question addressed is what makes the deep-learning model decide in a particular fashion, which can further help in demystifying the mechanism of action of certain perturbations and paves a way towards the explainability of the deep-learning model.

Keywords: cellular images, genetic perturbations, deep-learning, explainability

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Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

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In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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Authors: S. Barabas, F. Sarbu, B. Barabas, A. Fota

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Main objective of this paper is to establish a link between inertial forces of the bearings used in construction of wind power plant and its behavior. Using bearings with lower inertial forces has the immediate effect of decreasing inertia rotor system, with significant results in increased energy efficiency, due to decreased friction forces between rollers and raceways. The FEM analysis shows the appearance of uniform contact stress at the ends of the rollers, demonstrated the necessity of production of low mass bearings. Favorable results are expected in the economic field, by reducing material consumption and by increasing the durability of bearings. Using low mass bearings with hollow rollers instead of solid rollers has an impact on working temperature, on vibrations and noise which decrease. Implementation of types of hollow rollers of cylindrical tubular type, instead of expensive rollers with logarithmic profile, will bring significant inertial forces decrease with large benefits in behavior of wind power plant.

Keywords: inertial forces, Von Mises stress, hollow rollers, wind turbine

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Authors: Moez ul Hassan, Bushra Noman, Sarmad Hameed, Shahab Mehmood, Asma Bashir

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The importance of Noble prize winning “Patch Clamp Technique” is well documented. However, Patch Clamp Technique is very expensive and hence hinders research in developing countries. In this paper, detection, processing and recording of ultra low current from induced cells by using transimpedence amplifier is described. The sensitivity of the proposed amplifier is in the range of femto amperes (fA). Capacitive-feedback is used with active load to obtain a 20MΩ transimpedance gain. The challenging task in designing includes achieving adequate performance in gain, noise immunity and stability. The circuit designed by the authors was able to measure current in the rangeof 300fA to 100pA. Adequate performance shown by the amplifier with different input current and outcome result was found to be within the acceptable error range. Results were recorded using LabVIEW 8.5®for further research.

Keywords: drug discovery, ionic current, operational amplifier, patch clamp

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Authors: Ahmad Zaini, F. Muhammad Reza Hadafi, Surya Sumpeno, Muhtadin, Mochamad Hariadi

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The lack of information about museum’s collection reduces the number of visits of museum. Museum’s revitalization is an urgent activity to increase the number of visits. The research's roadmap is building a web-based application that visualizes museum in the virtual form including museum's statue reconstruction in the form of 3D. This paper describes implementation of three-dimensional model reconstruction method based on light-strip pattern on the museum statue using 3D scanner. Noise removal, alignment, meshing and refinement model's processes is implemented to get a better 3D object reconstruction. Model’s texture derives from surface texture mapping between object's images with reconstructed 3D model. Accuracy test of dimension of the model is measured by calculating relative error of virtual model dimension compared against the original object. The result is realistic three-dimensional model textured with relative error around 4.3% to 5.8%.

Keywords: 3D reconstruction, light pattern structure, texture mapping, museum

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Authors: Hyun-Woo Cho

Abstract:

The real-time fault monitoring and diagnosis of large scale production processes is helpful and necessary in order to operate industrial process safely and efficiently producing good final product quality. Unusual and abnormal events of the process may have a serious impact on the process such as malfunctions or breakdowns. This work try to utilize process measurement data obtained in an on-line basis for the safe and some fault-free operation of industrial processes. To this end, this work evaluated the proposed intelligent process data monitoring framework based on a simulation process. The monitoring scheme extracts the fault pattern in the reduced space for the reliable data representation. Moreover, this work shows the results of using linear and nonlinear techniques for the monitoring purpose. It has shown that the nonlinear technique produced more reliable monitoring results and outperforms linear methods. The adoption of the qualitative monitoring model helps to reduce the sensitivity of the fault pattern to noise.

Keywords: process data, data mining, process operation, real-time monitoring

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Authors: Nurul Na'imy Wan, Mohamad Sazali Said, Jaharah Ab. Ghani, Mohd Asri Selamat

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This paper presents the surface roughness of the Aluminium silicon alloy (AlSi) matrix composite which has been reinforced with aluminium nitride (AlN), with three types of carbide inserts. Experiments were conducted at various cutting speeds, feed rates, and depths of cut, according to the Taguchi method, using a standard orthogonal array L27 (34). The signal-to-noise (S/N) ratio and analysis of variance are applied to study the characteristic performance of machining parameters in measuring the surface roughness during the milling operation. The analysis of results, using the Taguchi method concluded that a combination of low feed rate, medium depth of cut, low cutting speed, and insert TiB2 give a better value of surface roughness. From Taguchi method, it was found that cutting speed of 230m/min, feed rate of 0.4 mm/tooth, depth of cut of 0.5mm and type of insert of TiB2 were the optimal machining parameters that gave the optimal value of surface roughness.

Keywords: AlSi/AlN Metal Matrix Composite (MMC), surface roughness, Taguchi method

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

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Authors: Osama A. Omer, Amal Hamed

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Successful blind image Super-Resolution algorithms require the exact estimation of the Point Spread Function (PSF). In the absence of any prior information about the imagery system and the true image; this estimation is normally done by trial and error experimentation until an acceptable restored image quality is obtained. Multi-frame blind Super-Resolution algorithms often have disadvantages of slow convergence and sensitiveness to complex noises. This paper presents a Super-Resolution image reconstruction algorithm based on estimation of the PSF that yields the optimum restored image quality. The estimation of PSF is performed by the knife-edge method and it is implemented by measuring spreading of the edges in the reproduced HR image itself during the reconstruction process. The proposed image reconstruction approach is using L1 norm minimization and robust regularization based on a bilateral prior to deal with different data and noise models. A series of experiment results show that the proposed method can outperform other previous work robustly and efficiently.

Keywords: blind, PSF, super-resolution, knife-edge, blurring, bilateral, L1 norm

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Authors: Amhimmid Mohammed Saffour, Mustafa Mohamed Abdullah

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The use of computers for handling image data in the healthcare is growing. However, the amount of data produced by modern image generating techniques is vast. This data might be a problem from a storage point of view or when the data is sent over a network. This paper using wavelet transform technique for medical images compression. MATLAB program, are designed to evaluate medical images storage and transmission time problem at Sebha Medical Center Libya. In this paper, three different Computed Tomography images which are abdomen, brain and chest have been selected and compressed using wavelet transform. Objective evaluation has been performed to measure the quality of the compressed images. For this evaluation, the results show that the Peak Signal to Noise Ratio (PSNR) which indicates the quality of the compressed image is ranging from (25.89db to 34.35db for abdomen images, 23.26db to 33.3db for brain images and 25.5db to 36.11db for chest images. These values shows that the compression ratio is nearly to 30:1 is acceptable.

Keywords: medical image, Matlab, image compression, wavelet's, objective evaluation

Procedia PDF Downloads 269

Authors: Theodore Grosch, Felipe Koji Godinho Hoshino

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In wireless communications, 3GPP LTE is one of the solutions to meet the greater transmission data rate demand. One issue inherent to this technology is the PAPR (Peak-to-Average Power Ratio) of OFDM (Orthogonal Frequency Division Multiplexing) modulation. This high PAPR affects the efficiency of power amplifiers. One approach to mitigate this effect is the Crest Factor Reduction (CFR) technique. In this work, we simulate the impact of Hard Limited Clipping Crest Factor Reduction technique on BER (Bit Error Rate) in OFDM based Systems. In general, the results showed that CFR has more effects on higher digital modulation schemes, as expected. More importantly, we show the worst-case degradation due to CFR on QPSK, 16QAM, and 64QAM signals in a linear system. For example, hard clipping of 9 dB results in a 2 dB increase in signal to noise energy at a 1% BER for 64-QAM modulation.

Keywords: bit error rate, crest factor reduction, OFDM, physical layer simulation

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Authors: C. G. Jinimole, A. Harsha

Abstract:

One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.

Keywords: computed tomography, enhancement techniques, increasing contrast, PSNR and MSE

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Authors: Khalid A. Al-Afandy, El-Sayyed El-Rabaie, Osama Salah, Ahmed El-Mhalaway

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This paper presents a high secure data hiding technique using image cropping and Least Significant Bit (LSB) steganography. The predefined certain secret coordinate crops will be extracted from the cover image. The secret text message will be divided into sections. These sections quantity is equal the image crops quantity. Each section from the secret text message will embed into an image crop with a secret sequence using LSB technique. The embedding is done using the cover image color channels. Stego image is given by reassembling the image and the stego crops. The results of the technique will be compared to the other state of art techniques. Evaluation is based on visualization to detect any degradation of stego image, the difficulty of extracting the embedded data by any unauthorized viewer, Peak Signal-to-Noise Ratio of stego image (PSNR), and the embedding algorithm CPU time. Experimental results ensure that the proposed technique is more secure compared with the other traditional techniques.

Keywords: steganography, stego, LSB, crop

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Authors: Katarzyna Baruch, Agata Szelag, Jaroslaw Rubacha, Bartlomiej Chojnacki, Tadeusz Kamisinski

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Methodology used to measure the reduction of transmitted impact sound by floor coverings situated on a massive floor is described in ISO 10140-3: 2010. To carry out such tests, the standardised reverberation room separated by a standard floor from the second measuring room are required. The need to have a special laboratory results in high cost and low accessibility of this measurement. The authors propose their own engineering method to measure the impact sound improvement with floor coverings. This method does not require standard rooms and floor. This paper describes the measurement procedure of proposed engineering method. Further, verification tests were performed. Validation of the proposed method was based on the analytical model, Statistical Energy Analysis (SEA) model and empirical measurements. The received results were related to corresponding ones obtained from ISO 10140-3:2010 measurements. The study confirmed the usefulness of the engineering method.

Keywords: building acoustic, impact noise, impact sound insulation, impact sound transmission, reduction of impact sound

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Authors: Yusuke Kuramitsu, Tomoaki Hashimoto, Hirokazu Tahara

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The control problem of underactuated spacecrafts has attracted a considerable amount of interest. The control method for a spacecraft equipped with less than three control torques is useful when one of the three control torques had failed. On the other hand, the quantized control of systems is one of the important research topics in recent years. The random dither quantization method that transforms a given continuous signal to a discrete signal by adding artificial random noise to the continuous signal before quantization has also attracted a considerable amount of interest. The objective of this study is to develop the control method based on random dither quantization method for stabilizing the rotational motion of a rigid spacecraft with two control inputs. In this paper, the effectiveness of random dither quantization control method for the stabilization of rotational motion of spacecrafts with two torque inputs is verified by numerical simulations.

Keywords: spacecraft control, quantized control, nonlinear control, random dither method

Procedia PDF Downloads 154

Authors: M. M. Hlakola, E. Golovins, D. V. Nicolae

Abstract:

The field of instrumentation electronics is undergoing an explosive growth, due to its wide range of applications. The proliferation of electrical devices in a close working proximity can negatively influence each other’s performance. The degradation in the performance is due to electromagnetic interference (EMI). This paper investigates the negative effects of electromagnetic interference originating in the General Purpose Interface Bus (GPIB) control-network of the ac-dc transfer measurement system. Remedial measures of reducing measurement errors and failure of range of industrial devices due to EMI have been explored. The ac-dc transfer measurement system was analyzed for the common-mode (CM) EMI effects. Further investigation of coupling path as well as more accurate identification of noise propagation mechanism has been outlined. To prevent the occurrence of common-mode (ground loops) which was identified between the GPIB system control circuit and the measurement circuit, a microcontroller-driven GPIB switching isolator device was designed, prototyped, programmed and validated. This mitigation technique has been explored to reduce EMI effectively.

Keywords: CM, EMI, GPIB, ground loops

Procedia PDF Downloads 275

Authors: Reihaneh Rafiemanzelat

Abstract:

due to towards the rapid urbanization, cities throughout the world faced to rapid growth through gray infrastructure. Therefore designing cities based on green and blue infrastructure can offer the best solution to support healthy urban environment. This conformation with a wide range of ecosystem service has a positive impact on the regulation of air temperature, noise reduction, air quality, and also create a pleasant environment for humans activities. Research mainly focuses on the concept and principles of green and blue infrastructure in the city of Esfahan at the center of Iran in order to create a livable and healthy environment. Design principles for green and blue infrastructure are classified into two different but interconnect evaluations. Healthy green infrastructure assessing based on; volume, shape, location, dispersion, and maintenance. For blue infrastructure there are three aspects of water and ecosystem which are; the contribution of water on medical health, the contribution of water on mental health, and creating possibilities to exercise.

Keywords: healthy cities, livability, urban landscape, green and blue infrastructure

Procedia PDF Downloads 281

Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

Abstract:

The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: cross-validation support vector machine, refined com- posite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device

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Authors: Justin Zhengjie Tan, Yang Zhao

Abstract:

Adiabatic Rapid Passage, a popular method of achieving population inversion, is studied in a Rabi dimer model in the presence of noise which acts as a dissipative environment. The integration of the multi-Davydov D2 Ansatz into the time-dependent variational framework enables us to model the intricate quantum system accurately. By influencing the system with a driving field strength resonant with the energy spacing, the probability of adiabatic rapid passage, which is modelled after the Landau Zener model, can be derived along with several other observables, such as the photon population. The effects of a dissipative environment can be reproduced by coupling the system to a common phonon mode. By manipulating the strength and frequency of the driving field, along with the coupling strength of the phonon mode to the qubits, we are able to control the qubits and photon dynamics and subsequently increase the probability of Adiabatic Rapid Passage happening.

Keywords: quantum electrodynamics, adiabatic rapid passage, Landau-Zener transitions, dissipative environment

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Authors: Rohit T. P., Sahil Athrij, Sasi Gopalan

Abstract:

Currently, the content entertainment industry is dominated by mobile devices. As the trends slowly shift towards Augmented/Virtual Reality applications the computational demands on these devices are increasing exponentially and we are already reaching the limits of hardware optimizations. This paper proposes a software solution to this problem. By leveraging the capabilities of cloud computing we can offload the work from mobile devices to dedicated rendering servers that are way more powerful. But this introduces the problem of latency. This paper introduces a protocol that can achieve high-performance low latency Augmented/Virtual Reality experience. There are two parts to the protocol, 1) In-flight compression The main cause of latency in the system is the time required to transmit the camera frame from client to server. The round trip time is directly proportional to the amount of data transmitted. This can therefore be reduced by compressing the frames before sending. Using some standard compression algorithms like JPEG can result in minor size reduction only. Since the images to be compressed are consecutive camera frames there won't be a lot of changes between two consecutive images. So inter-frame compression is preferred. Inter-frame compression can be implemented efficiently using WebGL but the implementation of WebGL limits the precision of floating point numbers to 16bit in most devices. This can introduce noise to the image due to rounding errors, which will add up eventually. This can be solved using an improved interframe compression algorithm. The algorithm detects changes between frames and reuses unchanged pixels from the previous frame. This eliminates the need for floating point subtraction thereby cutting down on noise. The change detection is also improved drastically by taking the weighted average difference of pixels instead of the absolute difference. The kernel weights for this comparison can be fine-tuned to match the type of image to be compressed. 2) Dynamic Load distribution Conventional cloud computing architectures work by offloading as much work as possible to the servers, but this approach can cause a hit on bandwidth and server costs. The most optimal solution is obtained when the device utilizes 100% of its resources and the rest is done by the server. The protocol balances the load between the server and the client by doing a fraction of the computing on the device depending on the power of the device and network conditions. The protocol will be responsible for dynamically partitioning the tasks. Special flags will be used to communicate the workload fraction between the client and the server and will be updated in a constant interval of time ( or frames ). The whole of the protocol is designed so that it can be client agnostic. Flags are available to the client for resetting the frame, indicating latency, switching mode, etc. The server can react to client-side changes on the fly and adapt accordingly by switching to different pipelines. The server is designed to effectively spread the load and thereby scale horizontally. This is achieved by isolating client connections into different processes.

Keywords: 2D kernelling, augmented reality, cloud computing, dynamic load distribution, immersive experience, mobile computing, motion tracking, protocols, real-time systems, web-based augmented reality application

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Authors: Komal Babbar

Abstract:

Multiuser Detection is the intelligent estimation/demodulation of transmitted bits in the presence of Multiple Access Interference. The authors have presented the Bit-error rate (BER) achieved by linear multi-user detectors: Matched filter (which treats the MAI as AWGN), Decorrelating and MMSE. In this work, authors investigate the bit error probability analysis for Matched filter, decorrelating, and MMSE. This problem arises in several practical CDMA applications where the receiver may not have full knowledge of the number of active users and their signature sequences. In particular, the behavior of MAI at the output of the Multi-user detectors (MUD) is examined under various asymptotic conditions including large signal to noise ratio; large near-far ratios; and a large number of users. In the last section Authors also shows Matlab Simulation results for Multiuser detection techniques i.e., Matched filter, Decorrelating, MMSE for 2 users and 10 users.

Keywords: code division multiple access, decorrelating, matched filter, minimum mean square detection (MMSE) detection, multiple access interference (MAI), multiuser detection (MUD)

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