Search results for: feature film

Authors: Syeda Mainaaz Unnisa, Deepa Suresh

Abstract:

Due to the increase in usage of public domain channels, such as the internet, and communication technology, there is a concern about the protection of intellectual property and security threats. This interest has led to growth in researching and implementing techniques for information hiding. Steganography is the art and science of hiding information in a private manner such that its existence cannot be recognized. Communication using steganographic techniques makes not only the secret message but also the presence of hidden communication, invisible. Steganalysis is the art of detecting the presence of this hidden communication. Parallel to steganography, steganalysis is also gaining prominence, since the detection of hidden messages can prevent catastrophic security incidents from occurring. Steganalysis can also be incredibly helpful in identifying and revealing holes with the current steganographic techniques, which makes them vulnerable to attacks. Through the formulation of new effective steganalysis methods, further research to improve the resistance of tested steganography techniques can be developed. Feature-based steganalysis method for JPEG images calculates the features of an image using the L1 norm of the difference between a stego image and the calibrated version of the image. This calibration can help retrieve some of the parameters of the cover image, revealing the variations between the cover and stego image and enabling a more accurate detection. Applying this method to various steganographic schemes, experimental results were compared and evaluated to derive conclusions and principles for more protected JPEG steganography.

Keywords: cover image, feature-based steganalysis, information hiding, steganalysis, steganography

Procedia PDF Downloads 197

Authors: Nalini C. Iyer, Shraddha H., Anagha B. Varahamurthy, Dikshith C. S., Ishwar G. Kubasad, Vinayak I. Karalatti, Pavan B. Mulimani

Abstract:

The current scenario of the pandemic due to COVID-19 has led to the awareness among the people to avoid unneces-sary contact in public places. There is a need to avoid contact with physical objects to stop the spreading of infection. The contactless feature has to be included in the systems in public places wherever possible. For example, attendance monitoring systems with fingerprint biometric can be replaced with a contactless feature. One more important protocol followed in the current situation is temperature monitoring and screening. The paper describes an attendance system with a contactless feature and temperature screening for the university. The system displays a QR code to scan, which redirects to the student login web page only if the location is valid (the location where the student scans the QR code should be the location of the display of the QR code). Once the student logs in, the temperature of the student is scanned by the contactless temperature sensor (mlx90614) with an error of 0.5°C. If the temperature falls in the range of the desired value (range of normal body temperature), then the attendance of the student is marked as present, stored in the database, and the door opens automatically. The attendance is marked as absent in the other case, alerted with the display of temperature, and the door remains closed. The door is automated with the help of a servomotor. To avoid the proxy, IR sensors are used to count the number of students in the classroom. The hardware system consisting of a contactless temperature sensor and IR sensor is implemented on the microcontroller, NodeMCU.

Keywords: NodeMCU, IR sensor, attendance monitoring, contactless, temperature

Procedia PDF Downloads 172

Authors: Ahmed A. Alghamdi

Abstract:

Single-walled carbon nanotubes (SWCNTs) are an outstanding material for applications in thermoelectric power generation, nanoelectronics, electrochemical energy storage, photovoltaics, and light emission. They are ultra-lightweight and possess electrical as well as thermal conductivity, flexibility, and mechanical strength. SWCNT is applicable in water treatment, brine desalination, removal of heavy metal ions associated with pollutants, and oil-water separation. Carbon nanotube (CNT) is believed to tackle the trade-off issue between permeability, selectivity, and fouling issues in membrane filtration applications. Studying these CNT structures, as well as their interconnection in nanotechnology, assists in finding the precise position to be placed for water desalination. Reverse osmosis (RO) has been used globally for desalination, resulting in purified water. Thin film composite (TFC) membranes were utilized in the RO process for desalination. The sheet thickness increases the salt rejection and decreases the water flux when CNT is utilized as a support layer to this membrane. Thus, through a temperature-induced phase separation technique (TIPS), axially aligned SWCNT (AASWCNT) is fabricated, and its use enhances the salt rejection and water flux at short reaction times with a modified procedure. An evaluation was conducted and analogized with prior works in the literature, which exhibited that the prepared TFC membrane showed a better outcome.

Keywords: single-walled carbon nanotubes, thin film composite, axially aligned swcnt, temperature induced phase separation technique, reverse osmosis

Procedia PDF Downloads 38

Authors: Kilari Nikhil, Ankur Tibrewal, Srinivas Kruthiventi S. S.

Abstract:

Conventional speaker identification systems often fall short of capturing the diverse variations present in speech data due to fixed-scale architectures. In this research, we propose a CNN-based architecture, USENet, designed to overcome these limitations. Leveraging two key techniques, our approach achieves superior performance on the VoxCeleb 1 Dataset without any pre-training. Firstly, we adopt a U-net-inspired design to extract features at multiple scales, empowering our model to capture speech characteristics effectively. Secondly, we introduce the squeeze and excitation block to enhance spatial feature learning. The proposed architecture showcases significant advancements in speaker identification, outperforming existing methods, and holds promise for future research in this domain.

Keywords: multi-scale feature extraction, squeeze and excitation, VoxCeleb1 speaker identification, mel-spectrograms, USENet

Procedia PDF Downloads 55

Authors: Kun Xu, Yuan Xu, Jia Qiao

Abstract:

The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD.

Keywords: document detection, corner detection, attention mechanism, lightweight

Procedia PDF Downloads 336

Authors: O. Baghriche, A. Zertal, C. Pulgarin, J. Kiwi, R. Sanjines

Abstract:

High-Power Impulse Magnetron Sputtering (HIPIMS) is a technology that belongs to the field of Ionized PVD of thin films. This study shows the first complete report on ultrathin TiO2/Ag nano-particulate films sputtered by highly ionized pulsed plasma magnetron sputtering (HIPIMS) leading to fast bacterial loss of viability. The Ag and the TiO2/Ag sputtered films induced complete Escherichia coli inactivation in the dark, which was not observed in the case of TiO2. When Ag was present, the bacterial inactivation was accelerated under low intensity solar simulated light and this has implications for a potential for a practical technology. The design, preparation, testing and surface characterization of these innovative films are described in this study. The HIPIMS sputtered composite films present an appreciable savings in metals compared to films obtained by conventional sputtering methods. HIPIMS sputtering induces a strong interaction with the rugous polyester 3-D structure due to the higher fraction of the Ag-ions (M+) attained in the magnetron chamber. The immiscibility of Ag and TiO2 in the TiO2/Ag films is shown by High Angular Dark Field (HAADF) microscopy. The ionization degree of the film forming species is significantly increased and film growth is assisted by an intense ion flux. Reports have revealed the significant enhancement of the film properties as the HIPIMS technology is used. However, a decrease of the deposition rate, as compared to the conventional DC magnetron sputtering Pulsed (DCMSP) process is commonly observed during HIPIMS.

Keywords: E. coli, HIPIMS, inactivation bacterial, sputtering

Procedia PDF Downloads 283

Authors: A. Katsman, L. Bloch, Y. Etinger, Y. Kauffmann, B. Pokroy

Abstract:

Various nanosized amorphous alumina thin films in the range of (2.4 - 63.1) nm were deposited onto amorphous carbon and amorphous Si3N4 membrane grids. Transmission electron microscopy (TEM), electron energy loss spectroscopy (EELS), X-ray photoelectron spectroscopy (XPS) and differential scanning calorimetry (DSC) techniques were used to probe the size effect on the short range order and the amorphous to crystalline phase transition temperature. It was found that the short-range order changes as a function of size: the fraction of tetrahedral Al sites is greater in thinner amorphous films. This result correlates with the change of amorphous alumina density with the film thickness demonstrated by the reflectivity experiments: the thinner amorphous films have the less density. These effects are discussed in terms of surface reconstruction of the amorphous alumina films. The average atomic binding energy in the thin film layer decreases with decease of the thickness, while the average O-Al interatomic distance increases. The reconstruction of amorphous alumina is induced by the surface reconstruction, and the short range order changes being dependent on the density. Decrease of the surface energy during reconstruction is the driving force of the alumina reconstruction (density change) followed by relaxation process (short range order change). The amorphous to crystalline phase transition temperature measured by DSC rises with the decrease in thickness from 997.6°C for 13.9 nm to 1020.4 °C for 2.7 nm thick. This effect was attributed to the different film densities: formation of nanovoids preceding and accompanying crystallization process influences the crystallization rate, and by these means, the temperature of crystallization peak.

Keywords: amorphous alumina, density, short range order, size effect

Procedia PDF Downloads 455

Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

Abstract:

The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

Procedia PDF Downloads 234

Authors: Søren Birkvad

Abstract:

This paper traces the development of sexual cinematic freedom in the wake of an epoch-making event in Danish cultural history. As the first in the world, the Danes abolished all censorship for adults in 1969, making the tiny nation of Denmark the world’s largest exporter of pornography for several years. Drawing on the insights of social and cultural history and the focus point of the National Cinema direction of Cinema Studies, this study focuses on Danish film pornography in the 1960s and 1970s in its own right (e.g., its peculiar mix of sex, popular comedy and certain ‘feminist’ agendas). More importantly, however, it covers a broader pattern, namely the culturally deep-rooted tradition of freedom of speech and sexual liberalism in Denmark. Thus, the key concept of frisind (“free mind”) in Danish cultural history took on an increasingly partisan application in the 1960s and 1970s. It became a designation for all-is-permitted hippie excess but was also embraced by dissenting movements on the left, such as feminism, which questioned whether a free mind necessarily meant free love. In all of this, Danish cinema from the 1960s and 1970s offers a remarkable source of historical insight, simultaneously reminding us of a number of acute issues of contemporary society. These issues include gendered ideas of sexuality and freedom then and now and the equivalent clash of cultures between a liberal commercial industry and the accelerating political demands of the “sexual revolution.” Finally, these issues include certain tensions between, on the one hand, a purely materialistic idea of sexual freedom – incarnated by anything from pornography to many of the taboo-breaking youth films and avant-garde films in the wake of the 1968-rebellion – and, on the other hand, growing opposition to this anti-spiritual perception of human sexuality (represented by for instance the ‘closet conservatism’ of Danish art film star Lars von Trier of nowadays). All in all, this presentation offers a reflection on ideas of sexuality and gender rooted in a unique historical moment in cinematic history.

Keywords: Danish film history, cultural history, film pornography, history of sexuality, national cinema, sexual liberalism

Procedia PDF Downloads 200

Authors: Nidal Dwaikat

Abstract:

This work presents the development of alpha spectroscopy method with Solid-state nuclear track detectors using aluminum thin films. The resolution of this method is high, and it is able to discriminate between alpha particles at different incident energy. It can measure the exact number of alpha particles at specific energy without needing a calibration of alpha track diameter versus alpha energy. This method was tested by using Cf-252 alpha standard source at energies 5.11 Mev, 3.86 MeV and 2.7 MeV, which produced by the variation of detector -standard source distance. On front side, two detectors were covered with two Aluminum thin films and the third detector was kept uncovered. The thickness of Aluminum thin films was selected carefully (using SRIM 2013) such that one of the films will block the lower two alpha particles (3.86 MeV and 2.7 MeV) and the alpha particles at higher energy (5.11 Mev) can penetrate the film and reach the detector’s surface. The second thin film will block alpha particles at lower energy of 2.7 MeV and allow alpha particles at higher two energies (5.11 Mev and 3.86 MeV) to penetrate and produce tracks. For uncovered detector, alpha particles at three different energies can produce tracks on it. For quality assurance and accuracy, the detectors were mounted on thick enough copper substrates to block exposure from the backside. The tracks on the first detector are due to alpha particles at energy of 5.11 MeV. The difference between the tracks number on the first detector and the tracks number on the second detector is due to alpha particles at energy of 3.8 MeV. Finally, by subtracting the tracks number on the second detector from the tracks number on the third detector (uncovered), we can find the tracks number due to alpha particles at energy 2.7 MeV. After knowing the efficiency calibration factor, we can exactly calculate the activity of standard source.

Keywords: aluminium thin film, alpha particles, copper substrate, CR-39 detector

Procedia PDF Downloads 348

Authors: Jingting Luo, Yong Wang, Ying Wang

Abstract:

Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

Procedia PDF Downloads 124

Authors: Wilman Septina, Rajiv R. Prabhakar, Thomas Moehl, David Tilley

Abstract:

Cupric oxide (CuO) is a promising absorber material for the fabrication of scalable, low cost solar energy conversion devices, due to the high abundance and low toxicity of copper. It is a p-type semiconductor with a band gap of around 1.5 eV, absorbing a significant portion of the solar spectrum. One of the main challenges in using CuO as solar absorber in an aqueous system is its tendency towards photocorrosion, generating Cu2O and metallic Cu. Although there have been several reports of CuO as a photocathode for hydrogen production, it is unclear how much of the observed current actually corresponds to H2 evolution, as the inevitability of photocorrosion is usually not addressed. In this research, we investigated the effect of the deposition of overlayers onto CuO thin films for the purpose of enhancing its photostability as well as performance for water splitting applications. CuO thin film was fabricated by galvanic electrodeposition of metallic copper onto gold-coated FTO substrates, followed by annealing in air at 600 °C. Photoelectrochemical measurement of the bare CuO film using 1 M phosphate buffer (pH 6.9) under simulated AM 1.5 sunlight showed a current density of ca. 1.5 mA cm-2 (at 0.4 VRHE), which photocorroded to Cu metal upon prolonged illumination. This photocorrosion could be suppressed by deposition of 50 nm-thick TiO2, deposited by atomic layer deposition. In addition, we found that insertion of an n-type CdS layer, deposited by chemical bath deposition, between the CuO and TiO2 layers was able to enhance significantly the photocurrent compared to without the CdS layer. A photocurrent of over 2 mA cm-2 (at 0 VRHE) was observed using the photocathode stack FTO/Au/CuO/CdS/TiO2/Pt. Structural, electrochemical, and photostability characterizations of the photocathode as well as results on various overlayers will be presented.

Keywords: CuO, hydrogen, photoelectrochemical, photostability, water splitting

Procedia PDF Downloads 202

Authors: Vibhushan Subba

Abstract:

B-movies are almost always ‘glanced over’, ‘swept beneath’, ‘hidden from’ and ‘locked away’ to live a secret life; a life that exists but enjoys only a mummified existence behind layers of protective covering. They are more often than not discarded as ‘trash’, ‘sleaze’, ‘porn’ and put down for their ‘bad taste’ or at least that has been the case in India. With the art film entering the realm of high art, the popular and the mainstream has been increasingly equated with the A grade Bollywood film. This leaves the B-movie to survive as a degraded cultural artifact on the fringes of the mainstream. Kanti Shah’s films are part of a secret, traversing the libidinal circuits of the B and C grade through history. His films still circulate like a corporeal reminder of the forbidden and that which is taboo, like a hidden fracture that threatens to split open bourgeois respectability. Seeking to find answers to an aesthetic that has been rejected and hidden, this paper looks at three films of Kanti Shah to see how the notion of taboo, censorship and the unseen coincide, how they operate in the domain of his cinema and try and understand a form that draws our attention to the subterranean forces at work.

Keywords: B-movies, trash, taboo, censorship

Procedia PDF Downloads 440

Authors: Sokkhey Phauk, Takeo Okazaki

Abstract:

The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

Procedia PDF Downloads 94

Authors: Youngjae Jin, Daeshik Kim

Abstract:

This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

Procedia PDF Downloads 427

Authors: Neha Batra Bali, Monika Tomar, Vinay Gupta

Abstract:

A reagentless biosensor for detection of urea based on ZnO-CuO composite thin film is presented in following work. Biosensors have immense potential for varied applications ranging from environmental to clinical testing, health care, and cell analysis. Immense growth in the field of biosensors is due to the huge requirement in today’s world to develop techniques which are both cost effective and accurate for prevention of disease manifestation. The human body comprises of numerous biomolecules which in their optimum levels are essential for functioning. However mismanaged levels of these biomolecules result in major health issues. Urea is one of the key biomolecules of interest. Its estimation is of paramount significance not only for healthcare sector but also from environmental perspectives. If level of urea in human blood/serum is abnormal, i.e., above or below physiological range (15-40mg/dl)), it may lead to diseases like renal failure, hepatic failure, nephritic syndrome, cachexia, urinary tract obstruction, dehydration, shock, burns and gastrointestinal, etc. Various metal nanoparticles, conducting polymer, metal oxide thin films, etc. have been exploited to act as matrix to immobilize urease to fabricate urea biosensor. Amongst them, Zinc Oxide (ZnO), a semiconductor metal oxide with a wide band gap is of immense interest as an efficient matrix in biosensors by virtue of its natural abundance, biocompatibility, good electron communication feature and high isoelectric point (9.5). In spite of being such an attractive candidate, ZnO does not possess a redox couple of its own which necessitates the use of electroactive mediators for electron transfer between the enzyme and the electrode, thereby causing hindrance in realization of integrated and implantable biosensor. In the present work, an effort has been made to fabricate a matrix based on ZnO-CuO composite prepared by pulsed laser deposition (PLD) technique in order to incorporate redox properties in ZnO matrix and to utilize the same for reagentless biosensing applications. The prepared bioelectrode Urs/(ZnO-CuO)/ITO/glass exhibits high sensitivity (70µAmM⁻¹cm⁻²) for detection of urea (5-200 mg/dl) with high stability (shelf life ˃ 10 weeks) and good selectivity (interference ˂ 4%). The enhanced sensing response obtained for composite matrix is attributed to the efficient electron exchange between ZnO-CuO matrix and immobilized enzymes, and subsequently fast transfer of generated electrons to the electrode via matrix. The response is encouraging for fabricating reagentless urea biosensor based on ZnO-CuO matrix.

Keywords: biosensor, reagentless, urea, ZnO-CuO composite

Procedia PDF Downloads 282

Authors: Asad Abbas, Muhammad Fezan Afzal, Muhammad Latif Anjum, Muhammad Azmat

Abstract:

The Internet of Things (IoT) is used to link up real objects that use the internet to interact. IoT applications allow handling and operating the equipment in accordance with environmental needs, such as transportation and healthcare. IoT devices are linked together via a number of agents that act as a middleman for communications. The operation of a heat sensor differs indoors and outside because agent applications work with environmental variables. In this article, we suggest using Software Product Line (SPL) to model IoT agents and applications' features on an XML-based basis. The contextual diversity within the same domain of application can be handled, and the reusability of features is increased by XML-based feature modelling. For the purpose of managing contextual variability, we have embraced XML for modelling IoT applications, agents, and internet-connected devices.

Keywords: IoT agents, IoT applications, software product line, feature model, XML

Procedia PDF Downloads 77

Authors: Tai Yuan Yu, Pei-Jen Wang

Abstract:

Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings, abbreviated as GFBs, are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional, abbreviated as 3D, fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.

Keywords: fluid-structure interaction, multi-physics simulations, gas foil bearing, oil-free, transient thermo-hydrodynamic

Procedia PDF Downloads 154

Authors: Vijay Goud, Ramasamy Alagirusamy, Apurba Das, Dinesh Kalyanasundaram

Abstract:

Thermoplastic composites render new opportunities as effective processing technology while crafting newer complications into processing. One of the notable challenges is in achieving thorough wettability that is significantly deterred by the high viscosity of the long molecular chains of the thermoplastics. As a result of high viscosity, it is very difficult to impregnate the resin into a tightly interlaced textile structure to fill the voids present in the structure. One potential solution to the above problem, is to pre-deposit resin on the fiber, prior to consolidation. The current study compares DREF spinning, powder coating and film stacking methods of predeposition of resin onto fibers. An investigation into the flexural properties of unidirectional composites (UDC) produced from blending of carbon fiber and polypropylene (PP) matrix in varying forms of fiber, powder and film are reported. Dr. Ernst Fehrer (DREF) yarns or friction spun hybrid yarns were manufactured from PP fibers and carbon tows. The DREF yarns were consolidated to yield unidirectional composites (UDCs) referred to as UDC-D. PP in the form of powder was coated on carbon tows by electrostatic spray coating. The powder-coated towpregs were consolidated to form UDC-P. For the sake of comparison, a third UDC referred as UDC-F was manufactured by the consolidation of PP films stacked between carbon tows. The experiments were designed to yield a matching fiber volume fraction of about 50 % in all the three UDCs. A comparison of mechanical properties of the three composites was studied to understand the efficiency of matrix wetting and impregnation. Approximately 19% and 68% higher flexural strength were obtained for UDC-P than UDC-D and UDC-F respectively. Similarly, 25% and 81% higher modulus were observed in UDC-P than UDC-D and UDC-F respectively. Results from micro-computed tomography, scanning electron microscopy, and short beam tests indicate better impregnation of PP matrix in UDC-P obtained through electrostatic spray coating process and thereby higher flexural strength and modulus.

Keywords: DREF spinning, film stacking, flexural strength, powder coating, thermoplastic composite

Procedia PDF Downloads 212

Authors: Nisha James, Shubha Ranganathan

Abstract:

One of the most poignant forms of organized crime against women, which has rarely made it to the world of Indian cinema, is that of sex trafficking, i.e. the forcible involvement of women in the sex trade through fraud or coercion (Hughes, 2005). In the space of Indian cinema, much of the spotlight has been on the sensational drug trafficking and gang mafia of Bombay. During our research on sex trafficking, the rehabilitated women interviewed often expressed strong criticism about mass media’s naive portrayal of prostitutes as money-minting, happy and sexually driven women. They argued that this unrealistic portrayal ignored the fact that this was not a reality for the majority of trafficked women. Given the gravity of sex trafficking as a human rights issue, it is, therefore, refreshing to see three recent films on sex trafficking in Indian Languages – Naa Bangaaru Talli (2014, Telugu), Mardaani (2014, Hindi) and Lakshmi (2014, Hindi). This paper reviews these three films to explore the portrayal of the everyday reality of trafficking for women. Film analysis was used to understand the representation of psychological issues in the media. The strength of these movies starts with their inspirations which are of true stories and that they are all aimed at bringing awareness about the issue of sex trafficking, which is a rising social evil in Indian society though none of the three films move to portray the next phase of rehabilitation and reintegration of victims, which is a very complex and important process in the life of a survivor. According to findings, survivors of sex trafficking find the rehabilitation and reintegration into society to be a slow and tough part of their life as they continuously face stigma and social exclusion and have to strive to live against all odds of non-acceptance starting from their family.

Keywords: film review, Indian films, sex trafficking, survivors

Procedia PDF Downloads 422

Authors: Seyed Reza Naghibulsadat

Abstract:

The nature of communication includes various forms of media productions, which include film and theater. In the current situation, since social networks have emerged, they have brought their own communication capabilities and have features that show speed, public access, lack of media organization and the production of extensive content, and the development of critical thinking; Also, they contain capabilities to develop access to all kinds of media productions, including movies and theater shows; Of course, this works differently in different conditions and communities. In terms of the scale of exploitation, the film has a more general audience, and the theater has a special audience. The film industry is more developed based on more modern technologies, but the theater, based on the older ways of communication, contains more intimate and emotional aspects. ; But in general, the main focus is the development of access to movies and theater shows, which is emphasized by those involved in this field due to the capabilities of social networks. In this research, we will look at these 2 areas and the relevant components for both areas through social networks and also the common points of both types of media production. The main goal of this research is to know the strengths and weaknesses of using social networks for the marketing of movies and theater shows and, at the same time are, also considered the opportunities and threats of this field. The attractions of these two types of media production, with the emergence of social networks, and the ability to change positions, can provide the opportunity to become a media with greater exploitation and higher profitability; But the main consideration is the opinions about these capabilities and the ability to use them for film and theater marketing. The main question of the research is, what are the marketing components for movies and theaters using social media capabilities? What are its strengths and weaknesses? And what opportunities and threats are facing this market? This research has been done with two methods SWOT and meta-analysis. Non-probability sampling has been used with purposeful technique. The results show that a recent approach is an approach based on eliminating threats and weaknesses and emphasizing strengths, and exploiting opportunities in the direction of developing film and theater marketing based on the capabilities of social networks within the framework of local cultural values and presenting achievements on an international scale or It is universal. This introduction leads to the introduction of authentic Iranian culture and foreign enthusiasts in the framework of movies and theater art. Therefore, for this issue, the model for using the capabilities of social networks for movie or theater marketing, according to the results obtained from Respondents, is a model based on SO strategies and, in other words, offensive strategies so that it can take advantage of the internal strengths and made maximum use of foreign situations and opportunities to develop the use of movies and theater performances.

Keywords: marketing, movies, theatrical show, social network potentials

Procedia PDF Downloads 58

Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

Abstract:

The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: information gain (IG), intrusion detection system (IDS), k-means clustering, Weka

Procedia PDF Downloads 281

Authors: Parthiban S. R.

Abstract:

Spiral heat exchangers are known as excellent heat exchanger because of far compact and high heat transfer efficiency. An innovative spiral heat exchanger based on polymer materials is designed for waste heat recovery process. Such a design based on polymer film technology provides better corrosion and chemical resistance compared to conventional metal heat exchangers. Due to the smooth surface of polymer film fouling is reduced. A new arrangement for flow of hot flue gas and cold fluid is employed for design, flue gas flows in axial path while the cold fluid flows in a spiral path. Heat load recovery achieved with the presented heat exchanger is in the range of 1.5 kW thermic but potential heat recovery about 3.5 kW might be achievable. To measure the performance of the spiral tube heat exchanger, its model is suitably designed and fabricated so as to perform experimental tests. The paper gives analysis of spiral tube heat exchanger.

Keywords: spiral heat exchanger, polymer based materials, fouling factor, heat load

Procedia PDF Downloads 372

Authors: Rajkumar Kolangarakandy

Abstract:

Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

Procedia PDF Downloads 322

Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

Abstract:

Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

Procedia PDF Downloads 571

Authors: Dalila Hammiche, Lisa Klaai, Sonia Imzi, Amar Boukerrou

Abstract:

The fight against plastic pollution implies the development of polymers as alternatives to synthetic polymers. Starch is a natural polymer that can easily be plasticized by means of additives. The objective of this work is to develop and characterize biodegradable biofilms based on starch, plasticized by glycerol (20 and 30%). The elaboration of the biofilms was carried out by the casting method under simple conditions. The samples were characterized by infrared spectroscopy analysis with Fourier transform (FTIR), thermogravimetric analysis, and biodegradability test. Infrared spectral analysis showed that the 30% and 20% glycerol films have the same chemical structure and no functional group changes occurred. Thermogravimetric analysis showed that a 30% glycerol film has higher thermal stability than a 20% glycerol film. Biodegradability test showed that the lower the percentage of glycerol, the more easily the biofilm degrades.

Keywords: starch, natural sources, FTIR, thermogravimetric analysis, biodegradability test

Procedia PDF Downloads 85

Authors: Kyung Min Park, Cheol Hee Moon

Abstract:

In this study we are to develop a sealing process using a mixture of a LMPA and an epoxy for the atmospheric OLED sealing process as a substitute for the thin-film process. Electrode lines were formed on the substrates, which were covered with insulating layers and sacrificial layers. A mixture of a LMPA and an epoxy was screen printed between the two electrodes. In order to generate a heat for the melting of the mixture, Joule heating method was used. Were used instantaneous discharge process for generating Joule heating. Experimental conditions such as voltage, time and constituent of the electrode were varied to optimize the heating conditions. As a result, the mixture structure of this study showed a great potential for a low-cost, low-temperature, atmospheric OLED sealing process as a substitute for the thin-film process.

Keywords: organic light emitting diode, encapsulation, low melting point alloy, joule heat

Procedia PDF Downloads 531

Authors: Salim H. Al Salmani, Kevin Tansey, Mohammed S. Ozigis

Abstract:

The study of the growth of built-up areas and settlement expansion is a major exercise that city managers seek to undertake to establish previous and current developmental trends. This is to ensure that there is an equal match of settlement expansion needs to the appropriate levels of services and infrastructure required. This research aims at demonstrating the potential of satellite image processing technique, harnessing the utility of single feature probability-object based image analysis technique in assessing the urban growth dynamics of the Muscat Governorate in Oman for the period 1990, 2002 and 2013. This need is fueled by the continuous expansion of the Muscat Governorate beyond predicted levels of infrastructural provision. Landsat Images of the years 1990, 2002 and 2013 were downloaded and preprocessed to forestall appropriate radiometric and geometric standards. A novel approach of probability filtering of the target feature segment was implemented to derive the spatial extent of the final Built-Up Area of the Muscat governorate for the three years period. This however proved to be a useful technique as high accuracy assessment results of 55%, 70%, and 71% were recorded for the Urban Landcover of 1990, 2002 and 2013 respectively. Furthermore, the Normalized Differential Built – Up Index for the various images were derived and used to consolidate the results of the SFP-OBIA through a linear regression model and visual comparison. The result obtained showed various hotspots where urbanization have sporadically taken place. Specifically, settlement in the districts (Wilayat) of AL-Amarat, Muscat, and Qurayyat experienced tremendous change between 1990 and 2002, while the districts (Wilayat) of AL-Seeb, Bawshar, and Muttrah experienced more sporadic changes between 2002 and 2013.

Keywords: urban growth, single feature probability, object based image analysis, landcover change

Procedia PDF Downloads 259

Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao

Abstract:

Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R-colour component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.

Keywords: feature extraction, remote sensing, image retrieval, chromaticity, water index, spectral library, integrated method

Procedia PDF Downloads 367

Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

Abstract:

The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

Procedia PDF Downloads 100