Search results for: high-speed image recordings

Authors: Ayala Amir

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The paper presents interdisciplinary research which draws on the literary study and the cultural study of photography to explore a literary genre defined by nostalgia – the photographed book for children. This genre, which was popular in the second half of the 20th century, presents the romantic, nostalgic image of childhood created in the visual arts in the 18th century (as suggested by Ann Higonnet). At the same time, it capitalizes on the nostalgia inherent in the event of photography as formulated by Jennifer Green-Lewis: photography frames a moment in the present while transforming it into a past longed for in the future. Unlike Freudian melancholy, nostalgia is an effect that enables representation by acknowledging the loss and containing it in the very experience of the object. The representation and preservation of the lost object (nature, childhood, innocence) are in the center of the genre of children's photography books – a modern version of ancient pastoral. In it, the unique synergia of word and image results in a nostalgic image of childhood in an era already conquered by modernization. The nostalgic effect works both in the representation of space – an Edenic image of nature already shadowed by its demise, and of time – an image of childhood imbued by what Gill Bartholnyes calls the "looking backward aesthetics" – under the sign of loss. Little critical attention has been devoted to this genre with the exception of the work of Bettina Kümmerling-Meibauer, who noted the nostalgic effect of the well-known series of photography books by Astrid Lindgren and Anna Riwkin-Brick. This research aims to elaborate Kümmerling-Meibauer's approach using the theories of the study of photography, word-image studies, as well as current studies of childhood. The theoretical perspectives are implemented in the case study of photography books created in one of the most innovative social structures in our time – the Israeli Kibbutz. This communal way of life designed a society where children will experience their childhood in a parentless rural environment that will save them from the fate of the Oedipal fall. It is suggested that in documenting these children in a fictional format, photographers and writers, images and words cooperated in creating nostalgic works situated on the border between nature and culture, imagination and reality, utopia and its realization in history.

Keywords: nostalgia, photography , childhood, children's books, kibutz

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Authors: Pranav Saxena

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This study examines the influence of social media usage, gym activities (weightlifting vs. cardiovascular exercise), and gender on body image perceptions among urban emerging adults in India. The research aimed to assess how these factors interact to shape body esteem, a crucial aspect of psychological well-being in a society increasingly influenced by media portrayals of idealized bodies. A purposive sample of 317 participants aged 18–27 years (167 male, 150 female) was recruited through snowball sampling across diverse urban areas. Body esteem was measured using the Body-Esteem Scale for Adolescents and Adults (BESAA), which evaluates perceptions related to appearance, weight, and how individuals perceive others’ view their bodies. Data was collected via online surveys, and Mann-Whitney U tests were used to examine differences in body esteem scores based on the type of gym activity, gender, and social media usage. Results revealed that participants who engaged in cardiovascular activities had significantly higher body esteem compared to those who participated in weightlifting (p = 0.020). Gender differences were also notable, with females reporting higher body esteem than males (p = 0.01). These findings suggest that women may experience more positive body perceptions, possibly influenced by the broader body positivity movement. Contrary to expectations, social media usage was found to be significantly associated with the drive for thinness (p = 0.030) but not with overall body esteem scores (p = 0.329). This suggests that while social media may contribute to specific body dissatisfaction related to thinness, it does not appear to be a major factor influencing overall body esteem in this sample. These results underscore the significant role of physical activity and gender in shaping body image perceptions while challenging the view that social media is the primary driver of negative body image in emerging adults. The findings indicate that physical activity, particularly cardiovascular exercise, may have a protective effect on body esteem, whereas weightlifting could potentially contribute to body dissatisfaction, especially among males. The study also highlights the need for a nuanced understanding of social media's role in shaping body image, suggesting that its impact may be less pronounced than previously thought when compared to other social factors such as gender and physical activity. This study contributes to the growing body of literature on body image in emerging adults, particularly in the context of urban India, where media and fitness culture heavily influence perceptions of the ideal body. It calls for further research into the long-term effects of social media on body image, the role of specific fitness cultures, and how gender norms continue to shape body image concerns. The findings have important implications for designing mental health and fitness interventions that are tailored to address the unique challenges faced by young adults, especially those who may experience heightened dissatisfaction with their bodies due to societal pressures or media portrayals.

Keywords: body image, gender, gym activity, social media usage

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Authors: Ashish Ashish

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In the last few decades, the discrete chaos of difference equations has gained a massive attention of academicians and scholars due to its tremendous applications in each and every branch of science, such as cryptography, traffic control models, secure communications, weather forecasting, and engineering. In this article, a generalized logistic discrete map is established and discrete chaos is reported through period doubling bifurcation, period three orbit and Lyapunov exponent. It is interesting to see that the generalized logistic map exhibits superior chaos due to the presence of an extra degree of freedom of an ordered parameter. The period doubling bifurcation and Lyapunov exponent are demonstrated for some particular values of parameter and the discrete chaos is determined in the sense of Devaney's definition of chaos theoretically as well as numerically. Moreover, the study discusses an extended chaos based image encryption and decryption scheme in cryptography using this novel system. Surprisingly, a larger key space for coding and more sensitive dependence on initial conditions are examined for encryption and decryption of text messages, images and videos which secure the system strongly from external cyber attacks, coding attacks, statistic attacks and differential attacks.

Keywords: chaos, period-doubling, logistic map, Lyapunov exponent, image encryption

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Authors: Tala Toonsi, Marah Alagha, Lina Alnowaiser, Hala Rajab

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This report is about the Photomath app, which is an AI application that uses image recognition technology, specifically optical character recognition (OCR) algorithms. The (OCR) algorithm translates the images into a mathematical equation, and the app automatically provides a step-by-step solution. The application supports decimals, basic arithmetic, fractions, linear equations, and multiple functions such as logarithms. Testing was conducted to examine the usage of this app, and results were collected by surveying ten participants. Later, the results were analyzed. This paper seeks to answer the question: To what level the artificial intelligence features are accurate and the speed of process in this app. It is hoped this study will inform about the efficiency of AI in Photomath to the users.

Keywords: photomath, image recognition, app, OCR, artificial intelligence, mathematical equations.

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Authors: Nihad Karim Chowdhury, Mohammad Sanaullah Chowdhury, Muhammed Jamshed Alam Patwary, Rubel Biswas

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In content-based 3D shape retrieval system, achieving high search performance has become an important research problem. A challenging aspect of this problem is to find an effective shape descriptor which can discriminate similar shapes adequately. To address this problem, we propose a new shape descriptor for 3D shape models by combining multi-resolution with multi-block center-symmetric local binary pattern operator. Given an arbitrary 3D shape, we first apply pose normalization, and generate a set of multi-viewed 2D rendered images. Second, we apply Gaussian multi-resolution filter to generate several levels of images from each of 2D rendered image. Then, overlapped sub-images are computed for each image level of a multi-resolution image. Our unique multi-block CS-LBP comes next. It allows the center to be composed of m-by-n rectangular pixels, instead of a single pixel. This process is repeated for all the 2D rendered images, derived from both ‘depth-buffer’ and ‘silhouette’ rendering. Finally, we concatenate all the features vectors into one dimensional histogram as our proposed 3D shape descriptor. Through several experiments, we demonstrate that our proposed 3D shape descriptor outperform the previous methods by using a benchmark dataset.

Keywords: 3D shape retrieval, 3D shape descriptor, CS-LBP, overlapped sub-images

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Authors: Katharina Kargel, Frederic Vobbe

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Sexual online grooming is generally defined as digital interactions for the purpose of sexual exploitation of children or minors, i.e. as a process for preparing and framing sexual child abuse. Due to its conceptual history, sexual online grooming is often associated with perpetrators who are previously unknown to those affected. While the strategies of perpetrators and the perception of those affected are increasingly being investigated, the instrumentalisation of digital media has not yet been researched much. Therefore, the present paper aims at contributing to this research gap by examining in what kind of ways perpetrators instrumentalise digital media. Our analyses draw on 46 case documentations and 18 interviews with those affected. The cases and the partly narrative interviews were collected by ten cooperating specialist centers working on sexualized violence in childhood and youth. For this purpose, we designed a documentation grid allowing for a detailed case reconstruction i.e. including information on the violence, digital media use and those affected. By using Reflexive Grounded Theory, our analyses emphasize a) the subjective benchmark of professional practitioners as well as those affected and b) the interpretative implications resulting from our researchers’ subjective and emotional interaction with the data material. It should first be noted that sexualized online grooming can result in both online and offline sexualized violence as well as hybrid forms. Furthermore, the perpetrators either come from the immediate social environment of those affected or are unknown to them. The perpetrator-victim relationship plays a more important role with regard to the question of the instrumentalisation of digital media than the question of the space (on vs. off) in which the primary violence is committed. Perpetrators unknown to those affected instrumentalise digital media primarily to establish a sexualized system of norms, which is usually embedded in a supposed love relationship. In some cases, after an initial exchange of sexualized images or video recordings, a latent play on the position of power takes place. In the course of the grooming process, perpetrators from the immediate social environment increasingly instrumentalise digital media to establish an explicit relationship of power and dependence, which is directly determined by coercion, threats and blackmail. The knowledge of possible vulnerabilities is strategically used in the course of maintaining contact. The above explanations lead to the conclusion that the motive for the crime plays an essential role in the question of the instrumentalisation of digital media. It is therefore not surprising that it is mostly the near-field perpetrators without commercial motives who initiate a spiral of violence and stress by digitally distributing sexualized (violent) images and video recordings within the reference system of those affected.

Keywords: sexualized violence, children and youth, grooming, offender strategies, digital media

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Authors: Hala Zaghloul, Taymoor Nazmy

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One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

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Authors: Eunseop Yeom

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Platelets can be activated by the surrounding blood flows where a blood vessel is narrowed as a result of atherosclerosis. Numerous studies have been conducted to identify the relation between platelets activation and thrombus formation. To measure platelet adhesion, this study proposes an image analysis technique. Blood samples are delivered in the microfluidic channel, and then platelets are activated by a stenotic micro-channel with 90% severity. By applying proposed correlation mapping, which visualizes decorrelation of the streaming blood flow, the area of adhered platelets (APlatelet) was estimated without labeling platelets. In order to evaluate the performance of correlation mapping on the detection of platelet adhesion, the effect of tile size was investigated by calculating 2D correlation coefficients with binary images obtained by manual labeling and the correlation mapping method with different sizes of the square tile ranging from 3 to 50 pixels. The maximum 2D correlation coefficient is observed with the optimum tile size of 5×5 pixels. As the area of the platelet adhesion increases, the platelets plug the channel and there is only a small amount of blood flows. This image analysis could provide new insights for better understanding of the interactions between platelet aggregation and blood flows in various physiological conditions.

Keywords: platelet activation, correlation coefficient, image analysis, shear rate

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Authors: Youcef Faci, Djillali Allou, Ahmed Mebtouche, Badredine Maalem

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The inclination of the bolt in a fastened joint of composite material during a tensile test can be influenced by several parameters, including material properties, bolt diameter and length, the type of composite material being used, the size and dimensions of the bolt, bolt preload, surface preparation, the design and configuration of the joint, and finally testing conditions. These parameters should be carefully considered and controlled to ensure accurate and reliable results during tensile testing of composite materials with fastened joints. Our work focuses on the effect of the stacking sequence and the geometry of specimens. An experimental test is carried out to obtain the inclination of a bolt during a tensile test of a composite material using acoustic emission and digital image correlation. Several types of damage were obtained during load. Digital image correlation techniques permit to obtain the inclination of bolt angle value during tensile test. We concluded that the inclination of the bolt during a tensile test of a composite material can be related to the damage that occurs in the material. It can cause stress concentrations and localized deformation in the material, leading to damage such as delamination, fiber breakage, matrix cracking, and other forms of failure.

Keywords: damage, digital image correlation, bolt inclination angle, joint

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Authors: Iman A. Saad, Loay E. George

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Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

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Authors: Nizar Karim Uribe-Orihuela, Fernando Brambila-Paz, Ivette Caldelas, Rodrigo Montufar-Chaveznava

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In this paper, we present the advances corresponding to the implementation of a strategy to visualize geographical data using a Software Development Kit (SDK) for video games. We use multispectral images from Landsat 7 platform and Laser Imaging Detection and Ranging (LIDAR) data from The National Institute of Geography and Statistics of Mexican (INEGI). We select a place of interest to visualize from Landsat platform and make some processing to the image (rotations, atmospheric correction and enhancement). The resulting image will be our gray scale color-map to fusion with the LIDAR data, which was selected using the same coordinates than in Landsat. The LIDAR data is translated to 8-bit raw data. Both images are fused in a software developed using Unity (an SDK employed for video games). The resulting image is then displayed and can be explored moving around. The idea is the software could be used for students of geology and geophysics at the Engineering School of the National University of Mexico. They will download the software and images corresponding to a geological place of interest to a smartphone and could virtually visit and explore the site with a virtual reality visor such as Google cardboard.

Keywords: virtual reality, interactive technologies, geographical data visualization, video games technologies, educational material

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Authors: González A. Julio, Ramírez L. Leonardo, Puerta A. Gabriel

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Telemedicine services use a large amount of data, most of which are diagnostic images in Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7) formats. Metadata is generated from each related image to support their identification. This study presents the use of decision trees for the optimization of information search processes for diagnostic images, hosted on the cloud server. To analyze the performance in the server, the following quality of service (QoS) metrics are evaluated: delay, bandwidth, jitter, latency and throughput in five test scenarios for a total of 26 experiments during the loading and downloading of DICOM images, hosted by the telemedicine group server of the Universidad Militar Nueva Granada, Bogotá, Colombia. By applying decision trees as a data mining technique and comparing it with the sequential search, it was possible to evaluate the search times of diagnostic images in the server. The results show that by using the metadata in decision trees, the search times are substantially improved, the computational resources are optimized and the request management of the telemedicine image service is improved. Based on the experiments carried out, search efficiency increased by 45% in relation to the sequential search, given that, when downloading a diagnostic image, false positives are avoided in management and acquisition processes of said information. It is concluded that, for the diagnostic images services in telemedicine, the technique of decision trees guarantees the accessibility and robustness in the acquisition and manipulation of medical images, in improvement of the diagnoses and medical procedures in patients.

Keywords: cloud storage, decision trees, diagnostic image, search, telemedicine

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Authors: N. Ibrahim-Rassoul, A. Kessi, E. K. Si-Ahmed, N. Djilali, J. Legrand

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The static and dynamic formation of liquid water bridges is analyzed using a combination of visualization experiments in a microchannel with a mathematical model. This paper presents experimental and theoretical findings of water plug/capillary bridge formation in a 250 μm squared microchannel. The approach combines mathematical and numerical modeling with experimental visualization and measurements. The generality of the model is also illustrated for flow conditions encountered in manipulation of polymeric materials and formation of liquid bridges between patterned surfaces. The predictions of the model agree favorably the observations as well as with the experimental recordings.

Keywords: green energy, mathematical modeling, fuel cell, water plug, gas diffusion layer, surface of revolution

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Authors: Djallel Bouamama, Yasser R. Haddadi

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Accurate brain tumor segmentation is crucial for diagnosis and treatment planning, yet it remains a challenging task due to the variability in tumor shapes and intensities. This paper introduces a distinct approach to brain tumor image segmentation by leveraging an advanced architecture known as Mamba-Unet. Building on the well-established U-Net framework, Mamba-Unet incorporates distinct design enhancements to improve segmentation performance. Our proposed method integrates a multi-scale attention mechanism and a hybrid loss function to effectively capture fine-grained details and contextual information in brain MRI scans. We demonstrate that Mamba-Unet significantly enhances segmentation accuracy compared to conventional U-Net models by utilizing a comprehensive dataset of annotated brain MRI scans. Quantitative evaluations reveal that Mamba-Unet surpasses traditional U-Net architectures and other contemporary segmentation models regarding Dice coefficient, sensitivity, and specificity. The improvements are attributed to the method's ability to manage class imbalance better and resolve complex tumor boundaries. This work advances the state-of-the-art in brain tumor segmentation and holds promise for improving clinical workflows and patient outcomes through more precise and reliable tumor detection.

Keywords: brain tumor classification, image segmentation, CNN, U-NET

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Authors: Carlos Vera, Tetyana Baydyk, Ernst Kussul, Graciela Velasco, Miguel Aparicio

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This article describes the Random Subspace Neural Classifier (RSC) for the recognition of meteors in the night sky. We used images of meteors entering the atmosphere at night between 8:00 p.m.-5: 00 a.m. The objective of this project is to classify meteor and star images (with stars as the image background). The monitoring of the sky and the classification of meteors are made for future applications by scientists. The image database was collected from different websites. We worked with RGB-type images with dimensions of 220x220 pixels stored in the BitMap Protocol (BMP) format. Subsequent window scanning and processing were carried out for each image. The scan window where the characteristics were extracted had the size of 20x20 pixels with a scanning step size of 10 pixels. Brightness, contrast and contour orientation histograms were used as inputs for the RSC. The RSC worked with two classes and classified into: 1) with meteors and 2) without meteors. Different tests were carried out by varying the number of training cycles and the number of images for training and recognition. The percentage error for the neural classifier was calculated. The results show a good RSC classifier response with 89% correct recognition. The results of these experiments are presented and discussed.

Keywords: contour orientation histogram, meteors, night sky, RSC neural classifier, stars

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Authors: Muhammad Zubair Khan, Yugyung Lee

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Deep learning has recently achieved enormous response in semantic image segmentation. The previously developed U-Net inspired architectures operate with continuous stride and pooling operations, leading to spatial data loss. Also, the methods lack establishing long-term pixels connection to preserve context knowledge and reduce spatial loss in prediction. This article developed encoder-decoder architecture with bi-directional LSTM embedded in long skip-connections and densely connected convolution blocks. The network non-linearly combines the feature maps across encoder-decoder paths for finding dependency and correlation between image pixels. Additionally, the densely connected convolutional blocks are kept in the final encoding layer to reuse features and prevent redundant data sharing. The method applied batch-normalization for reducing internal covariate shift in data distributions. The empirical evidence shows a promising response to our method compared with other semantic segmentation techniques.

Keywords: deep learning, semantic segmentation, image analysis, pixels connection, convolution neural network

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Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

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Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

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Authors: Ren Zuo Wang

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In this paper, in order to investigate the joint behaviors of the Dieh-Dou structure. A pushover experiment of Dieh-Dou Jia-Dong is implemented. NDI, LVDT and image measurement system are used to measure displacements of joints and deformations of Dieh-Dou Jia-Dong. In addition, joint rotation-moment relationships of column restoring force, purlin-supporting, Dou-Shu, Dou-Gong brackets, primary beam-Gua Tong, secondary beam-Gua Tong, Tertiary beam are builied. From Jia-Dong experiments, formulations of joint rotation are proposed.

Keywords: pushover experiment, Dieh-Dou timber frame, image measurement system, joint rotation-moment relationships

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Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

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Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

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Authors: Rajpal Kaur, Pooja Choudhary

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Biometrics, which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capabilities to the reliably distinguish between an authorized person and an imposter. The Signature recognition systems can categorized as offline (static) and online (dynamic). This paper presents Surf Feature based recognition of offline signatures system that is trained with low-resolution scanned signature images. The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. However the signatures of human can be handled as an image and recognized using computer vision and HMM techniques. With modern computers, there is need to develop fast algorithms for signature recognition. There are multiple techniques are defined to signature recognition with a lot of scope of research. In this paper, (static signature) off-line signature recognition & verification using surf feature with HMM is proposed, where the signature is captured and presented to the user in an image format. Signatures are verified depended on parameters extracted from the signature using various image processing techniques. The Off-line Signature Verification and Recognition is implemented using Mat lab platform. This work has been analyzed or tested and found suitable for its purpose or result. The proposed method performs better than the other recently proposed methods.

Keywords: offline signature verification, offline signature recognition, signatures, SURF features, HMM

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Authors: Attallah Bilal, Hendel Fatiha

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This paper proposes the bimodal biometrics system for identity verification iris and fingerprint, at matching score level architecture using weighted sum of score technique. The features are extracted from the pre processed images of iris and fingerprint. These features of a query image are compared with those of a database image to obtain matching scores. The individual scores generated after matching are passed to the fusion module. This module consists of three major steps i.e., normalization, generation of similarity score and fusion of weighted scores. The final score is then used to declare the person as genuine or an impostor. The system is tested on CASIA database and gives an overall accuracy of 91.04% with FAR of 2.58% and FRR of 8.34%.

Keywords: iris, fingerprint, sum rule, fusion

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Authors: Sijie Fu, Pascal-Henry Biwolé, Christian Mathis

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Among modern airflow measurement methods, Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV), as visualized and non-instructive measurement techniques, are playing more important role. This paper conducts a comparative experimental study for airflow measurement employing both techniques with the same condition. Velocity vector fields, velocity contour fields, voticity profiles and turbulence profiles are selected as the comparison indexes. The results show that the performance of both PIV and PTV techniques for airflow measurement is satisfied, but some differences between the both techniques are existed, it suggests that selecting the measurement technique should be based on a comprehensive consideration.

Keywords: airflow measurement, comparison, PIV, PTV

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Authors: Aissa Belmeguenai, Oulaya Berrak, Khaled Mansouri

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In this work, efficiency implementation and security evaluation of the keystream generator of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written with MATLAB.7.5. First of all, two different original images are used to validate the proposed design. The developed program is used to transform the original images data into digital image file. Finally, the proposed program is implemented to encrypt and decrypt images data. Several tests are done to prove the design performance, including visual tests and security evaluation.

Keywords: Achterbahn-128, keystream generator, stream cipher, image encryption, security analysis

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Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

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Authors: P. Suparada, D. Eakapotch

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This research’s objectives were to analyze the using of new media in the form of set up candid clip that affects the product and presenter, to study the effectiveness of using new media in the form of set up candid clip in order to increase the circulation and audience satisfaction and to use the earned information and knowledge to develop the communication for publicizing and advertising via new media. This research is qualitative research based on questionnaire from 50 random sampling representative samples and in-depth interview from experts in publicizing and advertising fields. The findings indicated the positive and negative effects to the brands’ image and presenters’ image of product named “Scotch 100” and “Snickers” that used set up candid clips via new media for publicizing and advertising in Thailand. It will be useful for fields of publicizing and advertising in the new media forms.

Keywords: candid clip, effect, new media, social network

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Authors: Irina Maria Artinescu, Costin Radu Boldea, Eduard-Ionut Matei

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The paper is a comparative study of two classical variants of parallel projection methods for solving the convex feasibility problem with their equivalents that involve variable weights in the construction of the solutions. We used a graphical representation of these methods for inpainting a convex area of an image in order to investigate their effectiveness in image reconstruction applications. We also presented a numerical analysis of the convergence of these four algorithms in terms of the average number of steps and execution time in classical CPU and, alternatively, in parallel GPU implementation.

Keywords: convex feasibility problem, convergence analysis, inpainting, parallel projection methods

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Authors: Punnoose A. K.

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This paper presents an approach for identifying noisy speech recording using a multi-layer perception (MLP) trained to predict phonemes from acoustic features. Characteristics of the MLP posteriors are explored for clean speech and noisy speech at the frame level. Appropriate density functions are used to fit the softmax probability of the clean and noisy speech. A function that takes into account the ratio of the softmax probability density of noisy speech to clean speech is formulated. These phoneme independent scoring is weighted using a phoneme-specific weightage to make the scoring more robust. Simple thresholding is used to identify the noisy speech recording from the clean speech recordings. The approach is benchmarked on standard databases, with a focus on precision.

Keywords: noisy speech identification, speech pre-processing, noise robustness, feature engineering

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Authors: S. Tehsin, S. Kausar

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The ultimate aim of machine intelligence is to explore and materialize the human capabilities, one of which is the ability to detect various text objects within one or more images displayed on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However, it needs to technologically testify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed. Subsequent examination bears testimony to the fact that the features extracted proved instrumental to text detection.

Keywords: biologically inspired vision, content based retrieval, document analysis, text extraction

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Authors: Yinjun Tu, Qiang Fang, Glenn I. Matthews, Shuenn-Yuh Lee

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This paper reports an efficient and rigorous self-adaptive stimulus artifacts removal approach for a mixed surface EMG (Electromyography) and stimulus signal during muscle stimulation. The recording of EMG and the stimulation of muscles were performing simultaneously. It is difficult to generate muscle fatigue feature from the mixed signal, which can be further used in closed loop system. A self-adaptive method is proposed in this paper, the stimulation frequency was calculated and verified firstly. Then, a mask was created based on this stimulation frequency to remove the undesired stimulus. 20 EMG signal recordings were analyzed, and the ANOVA (analysis of variance) approach illustrated that the decreasing trend of median power frequencies was successfully generated from the 'cleaned' EMG signal.

Keywords: EMG, FES, stimulus artefacts, self-adaptive

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Authors: Yanyan Wang

Abstract:

This paper on second language teaching and learning uses conversation analysis (CA) approach and focuses on how second language learners of Chinese do repair when making clarification requests. In order to demonstrate their behavior in interaction, a comparison was made to study the differences between native speakers of Chinese with non-native speakers of Chinese. The significance of the research is to make second language teachers and learners aware of repair and how to seek clarification. Utilizing the methodology of CA, the research involved two sets of naturally occurring recordings, one of native speaker students and the other of non-native speaker students. Both sets of recording were telephone talks between students and teachers. There were 50 native speaker students and 50 non-native speaker students. From multiple listening to the recordings, the parts with repairs for clarification were selected for analysis which included the moments in the talk when students had problems in understanding or hearing the speaker and had to seek clarification. For example, ‘Sorry, I do not understand ‘and ‘Can you repeat the question? ‘were the parts as repair to make clarification requests. In the data, there were 43 such cases from native speaker students and 88 cases from non-native speaker students. The non-native speaker students were more likely to use repair to seek clarification. Analysis on how the students make clarification requests during their conversation was carried out by investigating how the students initiated problems and how the teachers repaired the problems. In CA term, it is called other-initiated self-repair (OISR), which refers to student-initiated teacher-repair in this research. The findings show that, in initiating repair, native speaker students pay more attention to mutual understanding (inter-subjectivity) while non-native speaker students, due to their lack of language proficiency, pay more attention to their status of knowledge (epistemic) switch. There are three major differences: 1, native Chinese students more often initiate closed-class OISR (seeking specific information in the request) such as repeating a word or phrases from the previous turn while non-native students more frequently initiate open-class OISR (not specifying clarification) such as ‘sorry, I don’t understand ‘. 2, native speakers’ clarification requests are treated by the teacher as understanding of the content while non-native learners’ clarification requests are treated by teacher as language proficiency problem. 3, native speakers don’t see repair as knowledge issue and there is no third position in the repair sequences to close repair while non-native learners take repair sequence as a time to adjust their knowledge. There is clear closing third position token such as ‘oh ‘ to close repair sequence so that the topic can go back. In conclusion, this paper uses conversation analysis approach to compare differences between native Chinese speakers and non-native Chinese learners in their ways of conducting repair when making clarification requests. The findings are useful in future Chinese language teaching and learning, especially in teaching pragmatics such as requests.

Keywords: conversation analysis (CA), clarification request, second language (L2), teaching implication

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