Search results for: video representation

Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: Venus Torabi

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ISIS, the terrorist organization, modified two videogames, ARMA III and Grand Theft Auto 5 (2013) as means of online recruitment and ideological propaganda. The urge to study the mechanism at work, whether it has been successful or not, derives (Digital) Humanities experts to explore how codes of terror, Islamic ideology and recruitment strategies are incorporated into the ludic mechanics of videogames. Another aspect of the significance lies in the fact that this is a latent problem that has not been fully addressed in an interdisciplinary framework prior to this study, to the best of the researcher’s knowledge. Therefore, due to the complexity of the subject, the present paper entangles with game studies, philosophical and religious poles to form the methodology of conducting the research. As a contextualized epistemology of such exploitation of videogames, the core argument is building on the notion of “Culture Industry” proposed by Theodore W. Adorno and Max Horkheimer in Dialectic of Enlightenment (2002). This article posits that the ideological underpinnings of ISIS’s cause corroborated by the action-bound mechanics of the videogames are in line with adhering to the Islamic Eschatology as a furnishing ground and an excuse in exercising terrorism. It is an account of ISIS’s modification of the videogames, a tool of technological progression to practice online radicalization. Dialectically, this practice is packed up in rhetoric for recognizing a religious myth (the advent of a savior), as a hallmark of regression. The study puts forth that ISIS’s wreaking havoc on the world, both in reality and within action videogames, is negotiating the process of self-assertion in the players of such videogames (by assuming one’s self a member of terrorists) that leads to self-annihilation. It tries to unfold how ludic Mod videogames are misused as tools of mass deception towards ethnic cleansing in reality and line with the distorted Eschatological myth. To conclude, this study posits videogames to be a new avenue of mass deception in the framework of the Culture Industry. Yet, this emerges as a two-edged sword of mass deception in ISIS’s modification of videogames. It shows that ISIS is not only trying to hijack the minds through online/ludic recruitment, it potentially deceives the Muslim communities or those prone to radicalization into believing that it's terrorist practices are preparing the world for the advent of a religious savior based on Islamic Eschatology. This is to claim that the harsh actions of the videogames are potentially breeding minds by seeds of terrorist propaganda and numbing them to violence. The real world becomes an extension of that harsh virtual environment in a ludic/actual continuum, the extension that is contributing to the mass deception mechanism of the terrorists, in a clandestine trend.

Keywords: culture industry, dialectic, ISIS, islamic eschatology, mass deception, video games

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Authors: Rami A. Maher, Ibraheem K. Ibraheem

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This work presents a comparison study between the state-space and polynomial methods for the design of the robust governor for load frequency control of steam turbine power systems. The robust governor is synthesized using the two approaches and the comparison is extended to include time and frequency domains performance, controller order, and uncertainty representation, weighting filters, optimality and sub-optimality. The obtained results are represented through tables and curves with reasons of similarities and dissimilarities.

Keywords: robust control, load frequency control, steam turbine, H∞-norm, system uncertainty, load disturbance

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Authors: Eileen Kim

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As socioeconomic disparities grew in New York during the 1970s, artists represented new values that came with the times. Street art, in particular, was birthed from a distinctly urban, fringe setting to ultimately become one of the most lucrative forms of art today. Examining the economic and psychological reasons behind the rise of street art, this paper delves into the development of the art market as a parallel insight into human behaviors and economic models such as supply and demand. The purpose of this study is to show the role of the increasingly divided socioeconomic classes and the rise of art collecting as an asset-building form. This study concludes that the iconography and market value of street art represented distinct values that came from a series of intertwined social matters such as racial tensions and revolutions in industrial innovation.

Keywords: art industry, cultural representation, ethnicity, markets, public property, social classes, street art

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Authors: Raja Rajeswari K

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Orthogonal Frequency Division Multiplexing (OFDM), a multi Carrier transmission technique that has been used in implementing the majority of wireless applications like Wireless Network Protocol Standards (like IEEE 802.11a, IEEE 802.11n), in telecommunications (like LTE, LTE-Advanced) and also in Digital Audio & Video Broadcast standards. The latest research and development in the area of orthogonal frequency division multiplexing, Universal Filtered Multi Carrier (UFMC) & Filtered OFDM (F-OFDM) has attracted lots of attention for wideband wireless communications. In this paper UFMC & F-OFDM system are implemented and comparative analysis are carried out in terms of M-ary QAM modulation scheme over Dolph-chebyshev filter & rectangular window filter and to estimate Bit Error Rate (BER) over Rayleigh fading channel.

Keywords: UFMC, F-OFDM, BER, M-ary QAM

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Authors: Jazim Sohail, Filipe Teixeira-Dias

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Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.

Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI

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Authors: Chloe Shu-Hua Yeh

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Effects of videogame play on players cognitive abilities is a growing research field in the recent decades, however, little is known about how ‘out-of-school’ use of videogame influences creativity. This interdisciplinary research explores the cognitive and emotional effects of two different types of online videogames (an action videogame and a non-action videogame) on subsequent creativity performances using a within-participant design study with 36 participants. Results showed that after playing the action game participants performed higher originality, elaboration and flexibility than after playing the causal game. The results explored effects of emotional states elicited during playing the games suggesting that arousal may be a significant emotional factor which influence subsequent creativity performance. The cognitive and emotional effects of videogame were discussed followed with implications for emotion-creativity-videogame play research, game designers, educational practitioners and parents.

Keywords: attentional breadth, creativity, emotion, videogame play

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Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

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Authors: Te-Jen Chang, I-Hui Pan, Ping-Sheng Huang, Shan-Jen Cheng

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In this paper, a fast multiplication computing method utilizing the complement representation method and canonical recoding technique is proposed. By performing complements and canonical recoding technique, the number of partial products can be reduced. Based on these techniques, we propose an algorithm that provides an efficient multiplication method. On average, our proposed algorithm is to reduce the number of k-bit additions from (0.25k+logk/k+2.5) to (k/6 +logk/k+2.5), where k is the bit-length of the multiplicand A and multiplier B. We can therefore efficiently speed up the overall performance of the multiplication. Moreover, if we use the new proposes to compute common-multiplicand multiplication, the computational complexity can be reduced from (0.5 k+2 logk/k+5) to (k/3+2 logk/k+5) k-bit additions.

Keywords: algorithm design, complexity analysis, canonical recoding, public key cryptography, common-multiplicand multiplication

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Authors: Jutta Hämmerle-Uhl, Georg Penn, Gerhard Pötzelsberger, Andreas Uhl

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Iris codes contain bits with different entropy. This work investigates different strategies to reduce the size of iris code templates with the aim of reducing storage requirements and computational demand in the matching process. Besides simple sub-sampling schemes, also a binary multi-resolution representation as used in the JBIG hierarchical coding mode is assessed. We find that iris code template size can be reduced significantly while maintaining recognition accuracy. Besides, we propose a two stage identification approach, using small-sized iris code templates in a pre-selection satge, and full resolution templates for final identification, which shows promising recognition behaviour.

Keywords: iris recognition, compact iris code, fast matching, best bits, pre-selection identification, two-stage identification

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Authors: Stephen Miller

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The act of applying game mechanics and dynamics (which have been traditionally used in video games) into business applications is being widely trialed in an effort to make conventional business software a bit more participative, fun and engaging. This new trend, named ‘gamification’ has its believers and of course, its critics who still need convincing that the concept is an effective and beneficial business tool worthy of investment. The literature reveals that user engagement of business intelligence (BI) tools is much lower than expected and investors are failing to get a good return on their investment (ROI). So, a software prototype will be designed and developed to add gamification to a BI tool to determine its effect upon the user engagement levels of test participants. The experimental study will be evaluated using the comprehensive User Engagement Scale (UES) to see if there are improvements in areas such as; aesthetics, perceived usability, endurability, novelty, felt involvement and focused attention. The results of this unique study should demonstrate whether or not ‘gamifying’ a BI tool has the potential to increase an individual’s motivation to use BI software more often.

Keywords: business intelligence, gamification, human computer interaction, user engagement

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Authors: Aicha Aggoune, Abdelkrim Bouramoul, Mohamed Khiereddine Kholladi

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Recent research shows that user profile as important element can improve heterogeneous information retrieval with its content. In this context, we present our indexing model for heterogeneous multimedia documents. This model is based on the combination of user profile to the indexing process. The general idea of our proposal is to operate the common concepts between the representation of a document and the definition of a user through his profile. These two elements will be added as additional indexing entities to enrich the heterogeneous corpus documents indexes. We have developed IRONTO domain ontology allowing annotation of documents. We will present also the developed tool validating the proposed model.

Keywords: indexing model, user profile, multimedia document, heterogeneous of sources, ontology

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Authors: Parthiban Srinivasan

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PubMed provides online access to the National Library of Medicine database (MEDLINE) and other publications, which contain close to 25 million scientific citations from 1865 to the present. There are close to 80 million author name instances in those close to 25 million citations. For any work of literature, a fundamental issue is to identify the individual(s) who wrote it, and conversely, to identify all of the works that belong to a given individual. Due to the lack of universal standards for name information, there are two aspects of name ambiguity: name synonymy (a single author with multiple name representations), and name homonymy (multiple authors sharing the same name representation). In this talk, we present some results from our extensive work in author name disambiguation for PubMed citations. Information will be presented on the effectiveness and shortcomings of different aspects of successful name disambiguation such as parsing, validation, standardization and normalization.

Keywords: disambiguation, normalization, parsing, PubMed

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Authors: Manolo Dulva Hina, Clement Thierry, Assia Soukane, Amar Ramdane-Cherif

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In this paper, we presented our innovative way of determining the driving context for a driving assistance system. We invoke the fusion of all parameters that describe the context of the environment, the vehicle and the driver to obtain the driving context. We created a training set that stores driving situation patterns and from which the system consults to determine the driving situation. A machine-learning algorithm predicts the driving situation. The driving situation is an input to the fission process that yields the action that must be implemented when the driver needs to be informed or assisted from the given the driving situation. The action may be directed towards the driver, the vehicle or both. This is an ongoing work whose goal is to offer an alternative driving assistance system for safe driving, green driving and comfortable driving. Here, ontologies are used for knowledge representation.

Keywords: cognitive driving, intelligent transportation system, multimodal system, ontology, machine learning

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Authors: Esra Ince

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As an important means of cultural transmission, cinema is an important resource for seeing cultural and social definitions, meanings and descriptions of people with disabilities. This study is aimed to reveal how disabled people are represented in the films selected from Turkish cinema. For this purpose, the films were examined with qualitative content analysis. The Goffmanian perspective was adopted in the study. The relationship between disability and stigma has been tried to be explained. How the disabled, which Goffman defines as a stigmatized group due to their differences, are represented in the cinema has been examined within the dramaturgy model. In the research, it was seen that the disabled characters took place in similar representations in different regions of dramaturgy. It has been seen that the films reinforce the negative discourse and behaviors by reflecting the prejudices, attitudes and behaviors in the society and continue to stigmatize disability.

Keywords: disability, Turkish cinema, Goffman, stigma

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Authors: Kerri Alderson

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There is pervasive awareness by post secondary faculty that written feedback on course assignments is inconsistently reviewed by students. In order to support student success and growth, a novel method of providing feedback was sought, and screen casting - short, narrated “movies” of audio visual instructor feedback on students’ scholarly papers - was provided as an alternative to traditional means. An overview of the teaching and learning experience as well as the user-friendly software utilized will be presented. This study covers an overview of this more direct, student-centered medium for providing feedback using technology familiar to post secondary students. Reminiscent of direct personal contact, the personalized video feedback is positively evaluated by students as a formative medium for student growth in scholarly writing.

Keywords: education, pedagogy, screen casting, student feedback, teaching and learning

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Authors: Fatima Akhmedova, Simon Liao

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One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work, we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, non-redundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: face recognition, Hahn moments, recognition-by-parts, time-lapse

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Authors: James G. Matthew, Seonmin Huh, Frank X. Bennett

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English for Specific Purposes, ESP, aims to equip learners with necessary English language skills. Many ESP programs address language skills for job performance, including reading job related documents and oral proficiency. Within ESP is English for occupational purposes, EOP, which centers around developing communicative competence for the globalized workplace. Many ESP and EOP courses lack the content needed to assist students to progress at work, resulting in the need to create lexical compilation for different professions. It is important to teach communicative competence and soft skills for real job-related problem situations and address the complexities of the real world to help students to be successful in their professions. ESP and EOP research is therefore trying to balance both profession-specific educational contents as well as international multi-disciplinary language skills for the globalized workforce. The current study will build upon the existing discussion by developing pedagogy to assist students in their career through developing a strong practical command of relevant English vocabulary. Our research question focuses on the pedagogy two professors incorporated in their English for employment courses. The current study is a qualitative case study on the modes of teaching delivery for EOP in South Korea. Two foreign professors teaching at two different universities in South Korea volunteered for the study to explore their teaching practices. Both professors’ curriculums included the components of employment-related concept vocabulary, business presentations, CV/resume and cover letter preparation, and job interview preparation. All the pre-made recorded video lectures, live online class sessions with students, teachers’ lesson plans, teachers’ class materials, students’ assignments, and midterm and finals video conferences were collected for data analysis. The study then focused on unpacking representative patterns in their teaching methods. The professors used their strengths as native speakers to extend the class discussion from narrow and restricted conversations to giving students broader opportunities to practice authentic English conversation. The methods of teaching utilized three main steps to extend the conversation. Firstly, students were taught concept vocabulary. Secondly, the vocabulary was then combined in speaking activities where students had to solve scenarios, and the students were required to expand on the given forms of words and language expressions. Lastly, the students had conversations in English, using the language learnt. The conversations observed in both classes were those of authentic, expanded English communication and this way of expanding concept vocabulary lessons into extended conversation is one representative pedagogical approach that both professors took. Extended English conversation, therefore, is crucial for EOP education.

Keywords: concept vocabulary, english as a foreign language, english for employment, extended conversation

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Authors: Tanapon Keatsamarn, Chuchart Pintavirooj

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Foot pressure measurement provides necessary information for diagnosis diseases, foot insole design, disorder prevention and other application. In this paper, dynamic foot pressure measurement is presented for pressure measuring with high resolution and accuracy. The dynamic foot pressure measurement system consists of hardware and software system. The hardware system uses a transparent acrylic plate and uses steel as the base. The glossy white paper is placed on the top of the transparent acrylic plate and covering with a black acrylic on the system to block external light. Lighting from LED strip entering around the transparent acrylic plate. The optical sensors, the digital cameras, are underneath the acrylic plate facing upwards. They have connected with software system to process and record foot pressure video in avi file. Visual Studio 2017 is used for software system using OpenCV library.

Keywords: foot, foot pressure, image processing, optical sensors

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Authors: Yuzhi Ruan

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This paper investigates the dual functionality of gossip in shaping the action of the comic character, Mrs. Cyrus Packard, in the play “He Said, She Said” by the Chicago playwright Alice Gerstenberg. During the American Little Theater Movement in the early 20th century, when small experimental centers of drama were established, Alice Gerstenberg challenged gender inequality through the use of social satire in her play. Incorporating textual evidence from the play, this study demonstrates that Mrs. Packard is both empowered and disempowered by her gossiping habit in terms of her self-perception and her social relationships within the play. It argues for the dramatic and satirical representation of female identity through the pragmatics of discourse analysis. These perspectives are evident in combining linguistics and literature.

Keywords: discursive power, female identity, feminism in little theater movement, gossip

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Authors: N. Sateesh, C. S. P. Rao, K. Satyanarayana, C. Rajashekar

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This paper proposes a development of a CAD/CAM system for complex profiles of various machine members using a synthetic curve i.e. B-spline. Conventional methods in designing and manufacturing of complex profiles are tedious and time consuming. Even programming those on a computer numerical control (CNC) machine can be a difficult job because of the complexity of the profiles. The system developed provides graphical and numerical representation B-spline profile for any given input. In this paper, the system is applicable to represent a cam profile with B-spline and attempt is made to improve the follower motion.

Keywords: plate-cams, cam profile, b-spline, computer numerical control (CNC), computer aided design and computer aided manufacturing (CAD/CAM), R-D-R-D (rise-dwell-return-dwell)

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Authors: Attila Simon

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The subject of this research is an element of Mithras' iconography. It is a new element in the series of research begun with the study of the Bull in the Boat motif. The stylized altars represented by the seven adjacent rectangles appear on only a small group of Mithraic reliefs, which may explain why they have received less attention and fewer attempts at decipherment than other motifs. Using Vermaseren's database, CIMRM (Corpus Inscriptionum et Monumentorum Religionis Mithriacae), one collected all the cases containing the motif under investigation, created a database of them grouped by location, then used a comparative method to compare the different forms of the motif and to isolate these cases, and finally evaluated the results. The aim of this research is to interpret the iconographic element in question and attempt to determine its place of origin. The study may provide an interpretation of a Mithraic representation that, to the best of the author's knowledge, has not been explained so far, and the question may generate scientific discourses.

Keywords: roman history, religion, Mithras, iconography

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Authors: Shih-Pin Chen, Shih-Syuan You

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Fuzzy regression models are useful for investigating the relationship between explanatory variables and responses in fuzzy environments. To overcome the deficiencies of previous models and increase the explanatory power of fuzzy data, the graded mean integration (GMI) representation is applied to determine representative crisp regression coefficients. A fuzzy regression model is constructed based on the modified dissemblance index (MDI), which can precisely measure the actual total error. Compared with previous studies based on the proposed MDI and distance criterion, the results from commonly used test examples show that the proposed fuzzy linear regression model has higher explanatory power and forecasting accuracy.

Keywords: dissemblance index, fuzzy linear regression, graded mean integration, mathematical programming

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Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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Authors: Pamela Aimee Rigor

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This study aims to examine the representation of Syrian refugees resettled in Vancouver and the Lower Mainland in local community and major newspapers. While there is strong support for immigration in Canada, public opinion towards refugees and asylum seekers is a bit more varied. Concerns about the legitimacy of refugee claims are among the common concerns of Canadians, and hateful or negative narratives are still present in Canadian media discourse which affects how people view refugees. To counter the narratives, these Syrian refugees must publicly declare how grateful they are because they are resettled in Canada. The dominant media discourse is that these refugees should be grateful as they have been graciously accepted by Canada and Canadians, once again upholding the image of Canada being a generous and humanitarian nation. The study examined the representation of Syrian refugees and the Syrian refugee resettlement in Canadian newspapers from September 2015 to October 2017 – around the time Prime Minister Trudeau came into power up until the present. Using a combination of content and discourse analysis, it aimed to uncover how local community and major newspapers in Vancouver covered the Syrian refugee ‘crisis’ – more particularly, the arrival and resettlement of the refugees in the country. Using the qualitative data analysis software Nvivo 12, the newspapers were analyzed and sorted into themes. Based on the initial findings, the discourse of Canada being a humanitarian country and Canadians being generous, as well as the idea of Syrian refugees having to publicly announce how grateful they are, is still present in the local community newspapers. This seems to be done to counter the hateful narratives of citizens who might view them as people who are abusing help provided by the community or the services provided by the government. However, compared to the major and national newspapers in Canada, many these local community newspapers are very inclusive of Syrian refugee voices. Most of the News and Community articles interview Syrian refugees and ask them their personal stories of plight, survival, resettlement and starting a ‘new life’ in Canada. They are not seen as potential threats nor are they dismissed – the refugees were named and were allowed to share their personal experiences in these news articles. These community newspapers, even though their representations are far from perfect, actually address some aspects of the refugee resettlement issue and respond to their community’s needs. There are quite a number of news articles that announce community meetings and orientations about the Syrian refugee crisis, ways to help in the resettlement process, as well as community fundraising activities to help sponsor refugees or resettle newly arrived refugees. This study aims to promote awareness of how these individuals are socially constructed so we can, in turn, be aware of the certain biases and stereotypes present, and its implications on refugee laws and public response to the issue.

Keywords: forced migration and conflict, media representations, race and multiculturalism, refugee studies

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Authors: Elena A. Troubitsyna

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Designers of modern safety-critical control systems are increasingly relying on networking to provide the systems with advanced functionality and satisfy customer’s needs. However, networking nature of modern control systems also brings new technological challenges associated with ensuring system safety in the presence of openness and hence, potential security threats. In this paper, we propose a methodology that relies on systems-theoretic analysis to enable an integrated analysis of safety and security requirements of controlling software. We demonstrate how to create a safety case – a structured argument about system safety – with explicit representation of both safety and security goals. Our approach provides the designers with a systematic approach to analysing safety and security interdependencies while designing safety-critical control systems.

Keywords: controlling software, integrated analysis, security, safety-security co-engineering

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Authors: Khald Anisse, Amina Radgui, Mohammed Rziza

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Tracking objects on video sequences is a very challenging task in many works in computer vision applications. However, there is no article that treats this topic in catadioptric vision. This paper is an attempt that tries to describe a new approach of omnidirectional images processing based on inverse stereographic projection in the half-sphere. We used the spherical model proposed by Gayer and al. For object tracking, our work is based on snake method, with optimization using the Greedy algorithm, by adapting its different operators. The algorithm will respect the deformed geometries of omnidirectional images such as spherical neighborhood, spherical gradient and reformulation of optimization algorithm on the spherical domain. This tracking method that we call "spherical snake" permitted to know the change of the shape and the size of object in different replacements in the spherical image.

Keywords: computer vision, spherical snake, omnidirectional image, object tracking, inverse stereographic projection

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Authors: Shyam Sajan, Kamal Bijlani

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The widespread effects of digital media help people to explore the world more and get entertained with no effort. People became fond of these kind of sedentary life style. The increase in sedentary time and a decrease in physical activities has negative impacts on human health. Even though the addiction to video games has been exploited in exergames, to make people exercise and enjoy game challenges, the contribution is restricted only to physical wellness. This paper proposes creation and implementation of a game with the help of digital media in a virtual environment. The game is designed by collaborating ideas from neural linguistic programming and Stroop effect that can also be used to identify a person’s mental state, to improve concentration and to eliminate various phobias. The multiplayer game is played in a virtual environment created with Kinect sensor, to make the game more motivating and interactive.

Keywords: exergaming, Kinect Sensor, Neural Linguistic Programming, Stroop Effect

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Authors: Mounir Zekkaoui, Abdelhadi Fennan

Abstract:

The software evolution control requires a deep understanding of the changes and their impact on different system heterogeneous artifacts. And an understanding of descriptive knowledge of the developed software artifacts is a prerequisite condition for the success of the evolutionary process. The implementation of an evolutionary process is to make changes more or less important to many heterogeneous software artifacts such as source code, analysis and design models, unit testing, XML deployment descriptors, user guides, and others. These changes can be a source of degradation in functional, qualitative or behavioral terms of modified software. Hence the need for a unified approach for extraction and representation of different heterogeneous artifacts in order to ensure a unified and detailed description of heterogeneous software artifacts, exploitable by several software tools and allowing to responsible for the evolution of carry out the reasoning change concerned.

Keywords: heterogeneous software artifacts, software evolution control, unified approach, meta model, software architecture

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Authors: Reji Thankachan, Varsha PS

Abstract:

Both image capturing devices and human visual systems are nonlinear. Hence nonlinear filtering methods outperforms its linear counterpart in many applications. Linear methods are unable to remove impulsive noise in images by preserving its edges and fine details. In addition, linear algorithms are unable to remove signal dependent or multiplicative noise in images. This paper presents an approach to denoise and smoothen the Bipolar impulse noised images and videos using improved Kuwahara filter. It involves a 2 stage algorithm which includes a noise detection followed by filtering. Numerous simulation demonstrate that proposed method outperforms the existing method by eliminating the painting like flattening effect along the local feature direction while preserving edge with improvement in PSNR and MSE.

Keywords: bipolar impulse noise, Kuwahara, PSNR MSE, PDF

Procedia PDF Downloads 499