Search results for: CMOS image sensors

Authors: A. A. Hussen, I. N. Jleta

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Micro-electromechanical system (MEMS) accelerometers and gyroscopes are suitable for the inertial navigation system (INS) of many applications due to the low price, small dimensions and light weight. The main disadvantage in a comparison with classic sensors is a worse long term stability. The estimation accuracy is mostly affected by the time-dependent growth of inertial sensor errors, especially the stochastic errors. In order to eliminate negative effect of these random errors, they must be accurately modeled. Where the key is the successful implementation that depends on how well the noise statistics of the inertial sensors is selected. In this paper, the Allan variance technique will be used in modeling the stochastic errors of the inertial sensors. By performing a simple operation on the entire length of data, a characteristic curve is obtained whose inspection provides a systematic characterization of various random errors contained in the inertial-sensor output data.

Keywords: Allan variance, accelerometer, gyroscope, stochastic errors

Procedia PDF Downloads 442

Authors: K. S. Vedasingha, K. K. M. T. Perera, K. I. Hathurusinghe, H. W. I. Akalanka, Nelum Chathuranga Amarasena, Nalaka R. Dissanayake

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Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method among all. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways and caused damages to not only precious lives but also to the economy of the countries. There are some major issues which need to be addressed in railways of South Asian countries since they fall under the developing category. The goal of this research is to minimize the influencing aspect of railway level crossing accidents by developing the “railway process automation system”, as there are high-risk areas that are prone to accidents, and safety at these places is of utmost significance. This paper describes the implementation methodology and the success of the study. The main purpose of the system is to ensure human safety by using the Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. And it is possible to do the above-mentioned process through a decision-making system by using past data. The specialty is both processes working parallel. As usual, if the system fails to close the railway gate due to technical or a network failure, the proposed system can identify the current location and close the railway gate through a decision-making system, which is a revolutionary feature. The proposed system introduces further two features to reduce the causes of railway accidents. Railway track crack detection and motion detection are those features which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype, and it is tested with real-world scenarios to gain the above 90% of accuracy.

Keywords: crack detection, decision-making, image processing, Internet of Things, motion detection, prototype, sensors

Procedia PDF Downloads 177

Authors: Dean Raiyasmi, Elvi Citraresmana, Sutiono Mahdi

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Language shapes the human mind and its concept toward things. Using image schemas, in nowadays technology, even AI (artificial intelligence) can concept things in response to their creator negativity or positivity. This is reflected inside one of the most selling game around the world in 2012 called Dragon Age Origins. The AI in form of NPC (Non-Playable Character) inside the game reflects on the creator of the game on negativity or positivity toward the lexical concept of mage. Through image schemas, shaping the lexical concept of mage deemed possible and proved the negativity or positivity creator of the game toward mage. This research analyses the cognitive-semantic process of image schema and shaping the concept of ‘mage’ by describing kinds of image schemas exist in the Dragon Age Origin Game. This research is also aimed to analyse kinds of image schemas and describing the image schemas which shaping the concept of ‘mage’ itself. The methodology used in this research is qualitative where participative observation is employed with five stages and documentation. The results shows that there are four image schemas exist in the game and those image schemas shaping the lexical concept of ‘mage’.

Keywords: cognitive semantic, image-schema, conceptual metaphor, video game

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Authors: Katy Eleanor Addinall

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Women’s body image dissatisfaction is a widespread problem, and it is present in all age groups, on every socioeconomic level, in all occupations, all cultures, and religions. Body image dissatisfaction is a broad term that is used to vary from normal discontent of a woman about one or more of her physical attributes to extreme negative causes, for example, an eating disorder. South African women were examined, and an empirical qualitative study was done to evaluate the women’s thoughts and feelings regarding their bodies. The causes and effects of body image dissatisfaction were examined, and social science literature was used to determine the etiology of body image dissatisfaction, which confirmed that it is multifactorial. A variety of therapeutic aids were studied, and cognitive behavioural therapy appeared to be the most effective. Every woman is an individual with an individual body image and must be approached as an individual holistic being. Thus, a holistic pragmatic model was developed as a possible aid in the woman’s healing process.

Keywords: body, body image, females, woman, therapy, dissatisfaction, holistic, cognitive behavioural therapy

Procedia PDF Downloads 139

Authors: Shaik Jilani Basha, Inavolu Avinash, Alla Venu Sai Reddy, Bitragunta Taraka Ramu

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We can use the neural style transfer technique to build a picture with the same "content" as the beginning image but the "style" of the picture we've chosen. Neural style transfer is a technique for merging the style of one image into another while retaining its original information. The only change is how the image is formatted to give it an additional artistic sense. The content image depicts the plan or drawing, as well as the colors of the drawing or paintings used to portray the style. It is a computer vision programme that learns and processes images through deep convolutional neural networks. To implement software, we used to train deep learning models with the train data, and whenever a user takes an image and a styled image, the output will be as the style gets transferred to the original image, and it will be shown as the output.

Keywords: neural networks, computer vision, deep learning, convolutional neural networks

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Authors: Rajani Vishal, C. P. Mishra

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Background: Self-perception of an individual about own body has a strong influence on their food preference and thereby on their nutritional status. Body image is gaining importance in social theory. Globally, women in particular seem to be favour of one ideal body type (Viz A slim, tall and perfectly proportionate body). Beauty and body image ideals among research scholars can play a significant influence on their own actions. Objectives: 1) To assess perception of study subjects about body image; 2)To analyze the relationship between body image and residential status of study subjects. Material and Method: 176 female research scholars of Banaras Hindu University were selected through multistage sampling. They were interviewed with pre designed and pre-tested proforma about area of residence and perception about body image. Result: As much as 86.4% subjects were happy with the way they looked whereas 83.0% subjects considered themselves as attractive. In case of 13.6%, 27.3%, 31.8%, 14.2% and 13.1% subjects, best-described body shapes were thin, normal, curvy, athletic and overweight, respectively. Area of residence was significantly (p< o.o5) associated with perception of attractiveness and description of body shape. Conclusion: In spite of varied description of body image, majority of subjects had positive perception about their body image.

Keywords: attractiveness, body image, body shape, nutritional status

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Authors: Ahmed Ashit

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Image fusion is a significant and efficient image processing method used for detecting different types of tumors. This method has been used as an effective combination technique for obtaining high quality images that combine anatomy and physiology of an organ. It is the main key in the huge biomedical machines for diagnosing cancer such as PET-CT machine. This thesis aims to develop an image analysis system for the detection of the eye tumor. Different image processing methods are used to extract the tumor and then mark it on the original image. The images are first smoothed using median filtering. The background of the image is subtracted, to be then added to the original, results in a brighter area of interest or tumor area. The images are adjusted in order to increase the intensity of their pixels which lead to clearer and brighter images. once the images are enhanced, the edges of the images are detected using canny operators results in a segmented image comprises only of the pupil and the tumor for the abnormal images, and the pupil only for the normal images that have no tumor. The images of normal and abnormal images are collected from two sources: “Miles Research” and “Eye Cancer”. The computerized experimental results show that the developed image fusion based eye tumor detection system is capable of detecting the eye tumor and segment it to be superimposed on the original image.

Keywords: image fusion, eye tumor, canny operators, superimposed

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Authors: S. Benkraouda, Z. Djelloul-Khedda, B. Yagoubi

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we present a method for early detection of forest fires from a thermal infrared satellite image, using the image matrix of the probability of belonging. The principle of the method is to compare a theoretical mathematical model to an experimental model. We considered that each line of the image matrix, as an embodiment of a non-stationary random process. Since the distribution of pixels in the satellite image is statistically dependent, we divided these lines into small stationary and ergodic intervals to characterize the image by an adequate mathematical model. A standard deviation was chosen to generate random variables, so each interval behaves naturally like white Gaussian noise. The latter has been selected as the mathematical model that represents a set of very majority pixels, which we can be considered as the image background. Before modeling the image, we made a few pretreatments, then the parameters of the theoretical Gaussian model were extracted from the modeled image, these settings will be used to calculate the probability of each interval of the modeled image to belong to the theoretical Gaussian model. The high intensities pixels are regarded as foreign elements to it, so they will have a low probability, and the pixels that belong to the background image will have a high probability. Finally, we did present the reverse of the matrix of probabilities of these intervals for a better fire detection.

Keywords: forest fire, forest fire detection, satellite image, normal distribution, theoretical gaussian model, thermal infrared matrix image

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Authors: Marek Gancarz, Agnieszka Nawrocka, Robert Rusinek, Marcin Tadla

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Volatile organic compounds (VOCs) are the fungi metabolites in the gaseous form produced during improper storage of agricultural commodities (e.g. grain, food). The spoilt commodities produce a wide range of VOCs including alcohols, esters, aldehydes, ketones, alkanes, alkenes, furans, phenols etc. The characteristic VOCs and odours can be determined by using electronic nose (e-Nose) which contains a matrix of different kinds of sensors e.g. resistive sensors. The aim of the present studies was to determine relationship between response of the resistive sensors on the chosen volatiles and their concentration. According to the literature, it was chosen volatiles characteristic for the cereals: ethanol, 3-methyl-1-butanol and hexanal. Analysis of the sensor signals shows that a signal shape is different for the different substances. Moreover, each VOC signal gives information about a maximum of the normalized sensor response (R/Rmax), an impregnation time (tIM) and a cleaning time at half maximum of R/Rmax (tCL). These three parameters can be regarded as a ‘VOC fingerprint’. Seven resistive sensors (TGS2600-B00, TGS2602-B00, TGS2610-C00, TGS2611-C00, TGS2611-E00, TGS2612-D00, TGS2620-C00) produced by Figaro USA Inc., and one (AS-MLV-P2) produced by AMS AG, Austria were used. Two out of seven sensors (TGS2611-E00, TGS2612-D00) did not react to the chosen VOCs. The most responsive sensor was AS-MLV-P2. The research was supported by the National Centre for Research and Development (NCBR), Grant No. PBS2/A8/22/2013.

Keywords: agricultural commodities, organic compounds, resistive sensors, volatile

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Authors: N. Chaitawittanun, M. Munlin

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Due to rapid advancement of powerful image processing software, digital images are easy to manipulate and modify by ordinary people. Lots of digital images are edited for a specific purpose and more difficult to distinguish form their original ones. We propose a clustering method to detect a copy-move image forgery of JPEG, BMP, TIFF, and PNG. The process starts with reducing the color of the photos. Then, we use the clustering technique to divide information of measuring data by Hausdorff Distance. The result shows that the purposed methods is capable of inspecting the image file and correctly identify the forgery.

Keywords: image detection, forgery image, copy-paste, attack detection

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Authors: Preeti Kumari, Ridhi Kapoor

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 In any communication, security is the most important issue in today’s world. In this paper, steganography is the process of hiding the important data into other data, such as text, audio, video, and image. The interest in this topic is to provide availability, confidentiality, integrity, and authenticity of data. The steganographic technique that embeds hides content with unremarkable cover media so as not to provoke eavesdropper’s suspicion or third party and hackers. In which many applications of compression, encryption, decryption, and embedding methods are used for digital image steganography. Due to compression, the nose produces in the image. To sustain noise in the image, the LSB insertion technique is used. The performance of the proposed embedding system with respect to providing security to secret message and robustness is discussed. We also demonstrate the maximum steganography capacity and visual distortion.

Keywords: steganography, LSB, encoding, information hiding, color image

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Authors: Melisa Mete, Gary Davies, Susan Whelan

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Maintaining a good employer brand image is crucial for companies since it has numerous advantages such as better recruitment, retention and employee engagement, and commitment. This study aims to understand the relationship between employer brand image and employee satisfaction and engagement in the British context. A panel survey data (N=228) is tested via the regression models from the Hayes (2012) PROCESS macro, in IBM SPSS 23.0. The results are statistically significant and proves that the more positive employer brand image, the greater employee’ engagement and satisfaction, and the greater is employee satisfaction, the greater their engagement.

Keywords: employer brand, employer brand image, employee engagement, employee satisfaction

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Authors: Tabassum Husain, Shen Peng Li, Zhaolin Chen

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This paper evaluates the usability of 3D Guided Image Filtering to enhance the quality of short-time binned dynamic PET images by using MRI images. Guided image filtering is an edge-preserving filter proposed to enhance 2D images. The 3D filter is applied on 1 and 5-minute binned images. The results are compared with 15-minute binned images and the Gaussian filtering. The guided image filter enhances the quality of dynamic PET images while also preserving important information of the voxels.

Keywords: dynamic PET images, guided image filter, image enhancement, information preservation filtering

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Authors: Sayed Obeidullah Abrar

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Nanosensor is the combination of two terms nanoparticles and sensors. These are chemical or physical sensor constructed using nanoscale components, usually microscopic or submicroscopic in size. These sensors are very sensitive and can detect single virus particle or even very low concentrations of substances that could be potentially harmful. Nanosensors have a large scope of research especially in the field of medical sciences, military applications, pharmaceuticals etc.

Keywords: HIV/AIDS, nanosensors, DNA, RNA

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Authors: Prathiksha Kamath, Pratibha Jamkhandi, Prateek Ghanti, Priyanshu Gupta, M. Lakshmi Neelima

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Combining Image Captioning and Visual Question Answering (VQA) tasks have emerged as a new and exciting research area. The image captioning task involves generating a textual description that summarizes the content of the image. VQA aims to answer a natural language question about the image. Both these tasks include computer vision and natural language processing (NLP) and require a deep understanding of the content of the image and semantic relationship within the image and the ability to generate a response in natural language. There has been remarkable growth in both these tasks with rapid advancement in deep learning. In this paper, we present a comprehensive review of recent progress in combining image captioning and visual question-answering (VQA) tasks. We first discuss both image captioning and VQA tasks individually and then the various ways in which both these tasks can be integrated. We also analyze the challenges associated with these tasks and ways to overcome them. We finally discuss the various datasets and evaluation metrics used in these tasks. This paper concludes with the need for generating captions based on the context and captions that are able to answer the most likely asked questions about the image so as to aid the VQA task. Overall, this review highlights the significant progress made in combining image captioning and VQA, as well as the ongoing challenges and opportunities for further research in this exciting and rapidly evolving field, which has the potential to improve the performance of real-world applications such as autonomous vehicles, robotics, and image search.

Keywords: image captioning, visual question answering, deep learning, natural language processing

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Authors: Mohammad A. U. Khan, Omar A. Kittaneh, M. Akbar, Tariq M. Khan, Husam A. Bayoud

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The Shannon Entropy measure has been widely used for measuring uncertainty. However, in partial settings, the histogram is used to estimate the underlying distribution. The histogram is dependent on the number of bins used. In this paper, a modification is proposed that makes the Shannon entropy based on histogram consistent. For providing the benefits, two application are picked in medical image processing applications. The simulations are carried out to show the superiority of this modified measure for image segmentation problem. The improvement may be contributed to robustness shown to uneven background in images.

Keywords: Shannon entropy, medical image processing, image segmentation, modification

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Authors: Sandy Bao, Yankang Bao

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The understanding of information that is being processed in the brain, especially in the lateral geniculate nucleus (LGN), has been proven challenging for modern neuroscience and for researchers with a focus on how neurons process signals and images. In this paper, we are proposing a method to image process different colors within different layers of LGN, that is, green information in layers 4 & 6 and red & blue in layers 3 & 5 based on the surface dimension of layers. We take into consideration the images in LGN and visual cortex, and that the edge detected information from the visual cortex needs to be considered in order to return back to the layers of LGN, along with the image in LGN to form the new image, which will provide an improved image that is clearer, sharper, and making it easier to identify objects in the image. Matrix Laboratory (MATLAB) simulation is performed, and results show that the clarity of the output image has significant improvement.

Keywords: lateral geniculate nucleus, matrix laboratory, neuroscience, visual cortex

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Authors: Seyed Nima Tayarani Bathaie

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In this paper, an image-receiving system was designed and implemented through optimization of object detection algorithms using Haar features. This optimized algorithm served as face and eye detection separately. Then, cascading them led to a clear image of the user. Utilization of this feature brought about higher security by preventing fraud. This attribute results from the fact that services will be given to the user on condition that a clear image of his face has already been captured which would exclude the inappropriate person. In order to expedite processing and eliminating unnecessary ones, the input image was compressed, a motion detection function was included in the program, and detection window size was confined.

Keywords: face detection algorithm, Haar features, security of ATM

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Authors: Shahriar Farzam, Maryam Rastgarpour

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Image denoising plays extremely important role in digital image processing. Enhancement of clinical image research based on Curvelet has been developed rapidly in recent years. In this paper, we present a method for image contrast enhancement for cone beam CT (CBCT) images based on fast discrete curvelet transforms (FDCT) that work through Unequally Spaced Fast Fourier Transform (USFFT). These transforms return a table of Curvelet transform coefficients indexed by a scale parameter, an orientation and a spatial location. Accordingly, the coefficients obtained from FDCT-USFFT can be modified in order to enhance contrast in an image. Our proposed method first uses a two-dimensional mathematical transform, namely the FDCT through unequal-space fast Fourier transform on input image and then applies thresholding on coefficients of Curvelet to enhance the CBCT images. Consequently, applying unequal-space fast Fourier Transform leads to an accurate reconstruction of the image with high resolution. The experimental results indicate the performance of the proposed method is superior to the existing ones in terms of Peak Signal to Noise Ratio (PSNR) and Effective Measure of Enhancement (EME).

Keywords: curvelet transform, CBCT, image enhancement, image denoising

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Authors: Fatma Abdedayem

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The most effective and efficient methods in image categorization are almost based on bag-of-words (BOW) which presents image by a histogram of occurrence of visual words. In this paper, we propose a novel extension to this method. Firstly, we extract features in multi-scales by applying a color local descriptor named opponent-SIFT. Secondly, in order to represent image we use Spatial Pyramid Representation (SPR) and an extension to the BOW method which based on weighting visual words. Typically, the visual words are weighted during histogram assignment by computing the ratio of their occurrences in the image to the occurrences in the background. Finally, according to classical BOW retrieval framework, only a few words of the vocabulary is useful for image representation. Therefore, we select the useful weighted visual words that respect the threshold value. Experimentally, the algorithm is tested by using different image classes of PASCAL VOC 2007 and is compared against the classical bag-of-visual-words algorithm.

Keywords: BOW, useful visual words, weighted visual words, bag of visual words

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Authors: Yi Shan Wu, Ting Hsuan Wu, Li Wei Cheng, Pei Yu Guo

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Given the fiercely competitive environment, human capital is one of the most valuable assets in a commercial enterprise. Therefore, developing strategies to acquire more talents is crucial. Talents are mainly attracted by both internal and external employer brands as well as by the messages conveyed from the employer image. This not only manifests the importance of a brand and an image of an organization but shows people might be affected by their personal values when assessing an organization as an employer. The goal of the present study is to examine the association between employer brand, employer image, and the likelihood of increasing organizational attractiveness. In addition, we draw from social identity theory to propose value congruence may affect the relationship between employer brand and employer image. Data was collected from those people who only worked less than a year in the industry via an online survey (N=209). The results show that employer image partly mediates the effect of employer brand on organizational attractiveness. In addition, the results also suggest that value congruence does not moderate the relationship between employer brand and employer image. These findings explain why building a good employer brand could enhance organization attractiveness and indicate there should be other factors that may affect employer image building, offering directions for future research.

Keywords: organizational attractiveness, employer brand, employer image, value congruence

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Authors: Rashi Jain

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The Wireless Body Area Networks (WBANs) is an emerging interdisciplinary area where small sensors are placed on/within the human body. These sensors monitor the physiological activities and vital statistics of the body. The data from these sensors is aggregated and communicated to a remote doctor for immediate attention or to a database for records. On 6 Feb 2012, the IEEE 802.15.6 task group approved the standard for Body Area Network (BAN) technologies. The standard proposes the physical and MAC layer for the WBANs. The work provides an introduction to WBANs and overview of the physical and MAC layers of the standard. The physical layer specifications have been covered. A comparison of different protocols used at MAC layer is drawn. An introduction to the network layer and security aspects of the WBANs is made. The WBANs suffer certain limitations such as regulation of frequency bands, minimizing the effect of transmission and reception of electromagnetic signals on the human body, maintaining the energy efficiency among others. This has slowed down their implementation.

Keywords: vehicular networks, sensors, MicroController 8085, LTE

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Authors: Denis Spirjakin, Alexander Baranov, Saba Akbari, Natalia Kalenova, Vladimir Sleptsov

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In this paper we propose the approach to power management in wireless combustible gas sensors. This approach makes possible drastically prolong sensor nodes autonomous lifetime. That is necessary to tie battery replacement to every year technical service procedures which are claimed by safety standards. Using this approach the current consumption of the wireless combustible gas sensor node was decreased from 80 mA to less than 2 mA and the power consumption from more than 220 mW to 4.6 mW. These values provide autonomous lifetime of the node more than one year.

Keywords: Gas sensors, power management, wireless sensor network

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Authors: Abigail Qian Zhou

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In recent years, the prosperity of mass tourism in China has accelerated the breadth and depth of direct communication between countries, and the national image has been placed in a new communication context. Outbound tourists are not only directly involved in the formation of the national image, but are also the most direct medium and the most active symbol representing the national image. This study uses Chinese middle-class tourists visiting Japan as a case study, and analyzes, through participant observation and semi-structured interviews, the communication function of the national image transmitted by 'human medium' in tourism activities. It also explores the 'human medium' in the era of mass tourism. This study hopes to build a bridge for tourism research and national image and media studies. It will provide a theoretical basis and practical guidance for promoting the national image, strengthening exchanges between tourists and local populations, and expanding the tourism market in the future.

Keywords: human medium, national image, communication, Chinese middle class, outbound tourists

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Authors: Zeenat Parveen, Ashiq Hussain

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This review paper consists of applications of PDMS (polydimethylsiloxane) materials for enhanced performance, optical fiber sensors in acousto-ultrasonic, mechanical measurements, current applications, sensing, measurements and interferometric optical fiber sensors. We will discuss the basic working principle of fiber optic sensing technology, various types of fiber optic and the PDMS as a coating material to increase the performance. Optical fiber sensing methods for detecting dynamic strain signals, including general sound and acoustic signals, high frequency signals i.e. ultrasonic/ultrasound, and other signals such as acoustic emission and impact induced dynamic strain. Optical fiber sensors have Industrial and civil engineering applications in mechanical measurements. Sometimes it requires different configurations and parameters of sensors. Optical fiber current sensors are based on Faraday Effect due to which we obtain better performance as compared to the conventional current transformer. Recent advancement and cost reduction has simulated interest in optical fiber sensing. Optical techniques are also implemented in material measurement. Fiber optic interferometers are used to sense various physical parameters including temperature, pressure and refractive index. There are four types of interferometers i.e. Fabry–perot, Mach-Zehnder, Michelson, and Sagnac. This paper also describes the future work of fiber optic sensors.

Keywords: fiber optic sensing, PDMS materials, acoustic, ultrasound, current sensor, mechanical measurements

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Authors: Aleksei Samarin, Artyom Nazarenko, Valentin Malykh

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Image enhancement is becoming more and more popular, especially on mobile devices. Nowadays, it is a common approach to enhance an image using a convolutional neural network (CNN). Such a network should be of significant size; otherwise, a possibility for the artifacts to occur is overgrowing. The existing large CNNs are computationally expensive, which could be crucial for mobile devices. Another important flaw of such models is they are poorly interpretable. There is another approach to image enhancement, namely, the usage of predefined filters in combination with the prediction of their applicability. We present an approach following this paradigm, which outperforms both existing CNN-based and filter-based approaches in the image enhancement task. It is easily adaptable for mobile devices since it has only 47 thousand parameters. It shows the best SSIM 0.919 on RANDOM250 (MIT Adobe FiveK) among small models and is thrice faster than previous models.

Keywords: universal filter, image enhancement, neural networks, computer vision

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Authors: Lutful Karim, Mohammed S. Al-kahtani

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Sensors are being used in various applications such as agriculture, health monitoring, air and water pollution monitoring, traffic monitoring and control and hence, play the vital role in the growth of big data. However, sensors collect redundant data. Thus, aggregating and filtering sensors data are significantly important to design an efficient big data framework. Current researches do not focus on aggregating and filtering data at multiple layers of sensor-based big data framework. Thus, this paper introduces (i) three layers data aggregation and framework for big data and (ii) a priority-based, dynamic data aggregation scheme (PDDA) for the lowest layer at sensors. Simulation results show that the PDDA outperforms existing tree and cluster-based data aggregation scheme in terms of overall network energy consumptions and end-to-end data transmission delay.

Keywords: big data, clustering, tree topology, data aggregation, sensor networks

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Authors: Salim Çalışkan, Hakan Akyüz

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Digital image correlation has been accustomed as a versatile and efficient method for measuring displacements on the article surfaces by comparing reference subsets in undeformed images with the define target subset in the distorted image. The theoretical model points out that the accuracy of the digital image correlation displacement data can be exactly anticipated based on the divergence of the image noise and the sum of the squares of the subset intensity gradients. The digital image correlation procedure locates each subset of the original image in the distorted image. The software then determines the displacement values of the centers of the subassemblies, providing the complete displacement measures. In this paper, the effect of the speckle distribution and its effect on displacements measured out plane displacement data as a function of the size of the subset was investigated. Nine groups of speckle patterns were used in this study: samples are sprayed randomly by pre-manufactured patterns of three different hole diameters, each with three coverage ratios, on a computer numerical control punch press. The resulting displacement values, referenced at the center of the subset, are evaluated based on the average of the displacements of the pixel’s interior the subset.

Keywords: digital image correlation, speckle pattern, experimental mechanics, tensile test, aluminum alloy

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Authors: D. López-Mancilla, J. M. Roblero-Villa

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Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

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Authors: Sajid Hussain

Abstract:

The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

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