Search results for: versatile video coding

Authors: Sarthak Mohapatra, Ajith Babu, Shyam Prasad Ghosh

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The community of gamers has been at the crux of stigmatization and marginalization by the larger society, resulting in dignity erosion. India presents a unique context where e-sports have recently seen large-scale investments, a massive userbase, and appreciable demand for gaming as a career option. Yet the apprehension towards gaming is salient among parents and non-gamers who engage in the de-dignification of gamers, by advocating the discourse of violence promotion via video games. Even the government is relentless in banning games due to data privacy issues. Thus, the current study explores the experiences of gamers and how they navigate these de-dignifying circumstances. The study follows an exploratory qualitative approach where in-depth interviews are used as data collection tools guided by a semi-structured questionnaire. A total of 25 individuals were interviewed comprising casual gamers, professional gamers, and individuals who are indirectly impacted by gaming including parents, relatives, and friends of gamers. Thematic analysis via three-level coding is used to arrive at broad themes (categories) and their sub-themes. The results indicate that the de-dignification of gamers results from attaching stereotypes of introversion, aggression, low intelligence, and low aspirations to them. It is interesting to note that the intensity of de-dignification varies and is more salient in violent shooting games which are perceived to require low cognitive resources to master. The moral disengagement of gamers while playing violent video games becomes the basis for de-dignification. Findings reveal that circumventing de-dignification required gamers to engage in several tactics that included playing behind closed doors, consciously hiding the gamer identity, rationalizing behavior by idolizing professionals, bragging about achievements within the game, and so on. Theoretically, it contributes to dignity and social identity literature by focusing on stereotyping and stigmatization. From a policy perspective, improving legitimacy toward gaming is expected to improve the social standing of gamers and professionals. For practitioners, it is important that proper channels of promotion and communication are used to educate the non-gamers so that the stereotypes blur away.

Keywords: dignity, social identity, stereotyping, video games

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Authors: June Tay, Ivy Chia

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There are numerous changes, both mental and physical, taking place when people age. We need to understand the different aspects required for healthy living, including meeting nutritional needs, regular physical activities to keep agility, sufficient rest and sleep to have physical and mental well-being, social engagement to avoid the risk of social isolation and depression, and access to healthcare to detect and manage chronic conditions. Promoting physical activities for an ageing population is necessary as many may have enjoyed sedentary lifestyles for some time. In our study, we evaluate the considerations when designing a computer vision video game for the elderly. We need to design some low-impact activities, such as stretching and gentle movements, because some elderly individuals may have joint pains or mobility issues. The exercise game should consist of simple movements that are easy to follow and remember. It should be fun and enjoyable so that they can be motivated to do some exercise. Social engagement can keep the elderly motivated and competitive, and they are more willing to engage in game exercises. Elderly citizens can compare their game scores and try to improve them. We propose a computer vision-based video game for the elderly that will capture and track the movement of the elderly hand pushing a ball on the screen into a circle. It can be easily set up using a PC laptop with a webcam. Our video game adhered to the design framework we employed, and it encompassed ease of use, a simple graphical interface, easy-to-play game exercise, and fun gameplay.

Keywords: about computer vision, video games, gerontology technology, caregiving

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Authors: Aishrith Rao

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Human activity recognition is an important aspect of video analytics, and many approaches have been recommended to enable action recognition. In this approach, the model is used to identify the action of the multiple people in the frame and classify them accordingly. A few approaches use RNNs and 3D CNNs, which are computationally expensive and cannot be trained with the small datasets which are currently available. Multi-person action recognition has been performed in order to understand the positions and action of people present in the video frame. The size of the video frame can be adjusted as a hyper-parameter depending on the hardware resources available. OpenPose has been used to calculate pose estimate using CNN to produce heap-maps, one of which provides skeleton features, which are basically joint features. The features are then extracted, and a classification algorithm can be applied to classify the action.

Keywords: human activity recognition, computer vision, pose estimates, convolutional neural networks

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Authors: Ahmed Sameer, Braj Bhushan

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The objective of our study was to compare two techniques (no landmark vs imaginary landmark) of remembering route while traversing in an unfamiliar homogenous environment. We used two videos each having nine identical turns with no landmarks. In the first video participant was required to remember the sequence of turns. In the second video participant was required to imagine a landmark at each turn and associate the turn with it. In both the task the participant was asked to recall the sequence of turns as it appeared in the video. Results showed that performance in the first condition i.e. without use of landmarks was better than imaginary landmark condition. The difference, however, became significant when the participant were tested again about 30 minutes later though performance was still better in no-landmark condition. The finding is surprising given the past research in memory and is explained in terms of cognitive factors such as mental workload.

Keywords: wayfinding, landmarks, unfamiliar environment, cognitive psychology

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Authors: Olusola Akintunde Adediran

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This study examined differential effect of Gender difference in social interaction skill of pupils with autism using token economy and video modeling as intervention strategies. A pretest, posttest, control group, quasi-experimental research design was adopted in the study. 17 participants (11 males and 6 females) were selected purposively from 5 centres in Ibadan and randomized into three groups (token economy, video modeling and control groups). Two instruments were used in the study; Autism Spectrum Rating Scale (ASRS) for 299.00 Autistic Disorder (r = 0.82) and Children’s Self-report Social Skill Scale (CS4) (r= 0.93). A descriptive statistics was used to analyse the participants social interaction data based on intervention and gender, while inferential statistics of analysis of covariance (ANCOVA) and scheffe post-hoc measure was used to anlayse three null hypotheses tested at 0.05 level of significance. The results obtained indicated that there was a significant main effect of treatment on social interaction of participants, but there was no significant of main effect of gender on the social interaction of participants, hence, (F(2,14) = .741; p > .05, eta = .050). Lastly, there was no significant interaction effect of treatment and gender of the participants, hence (F(2,10) = 2.177; p > .05, eta 2 = 202). The study has contributed to the frontiers of knowledge by establishing that social interaction of autism is attainable when token economy and video modelling are used as treatment intervention, hence, they should be adopted by the teachers, curriculum planners and other stakeholders.

Keywords: social interaction, token economy, video modelling, autism, gender

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Authors: Daniel Vargas-Herrera, Ivette Caldelas, Fernando Brambila-Paz, Rodrigo Montufar-Chaveznava

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In this paper, we present the advances corresponding to the implementation of a set of educational materials based on video games technologies. Essentially these materials correspond to projects developed and under development as bachelor thesis of some Computer Engineering students of the Engineering School. All materials are based on the Unity SDK; integrating some devices such as kinect, leap motion, oculus rift, data gloves and Google cardboard. In detail, we present a virtual reality application for neurosciences students (suitable for neural rehabilitation), and virtual scenes for the Google cardboard, which will be used by the psychology students for phobias treatment. The objective is these materials will be located at a server to be available for all students, in the classroom or in the cloud, considering the use of smartphones has been widely extended between students.

Keywords: virtual reality, interactive technologies, video games, educational materials

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Authors: Martynova Alina, Lyubov Buzoleva

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Streptococcus pneumoniae is the causative agent of pneumonias and meningitids throught all the world. Having high genetic diversity, this microorganism can cause different clinical forms of pneumococcal infections and microbiologically it is really difficult diagnosed by routine methods. Also, epidemiological surveillance requires more developed methods of molecular typing because the recent method of serotyping doesn't allow to distinguish invasive and non-invasive isolates properly. Non-coding genome of bacteria seems to be the interesting source for seeking of highly distinguishable markers to discriminate the subspecies of such a variable bacteria as Streptococcus pneumoniae. Technically, we proposed scheme of discrimination of S.pneumoniae strains with amplification of non-coding region (SP_1932) with the following restriction with 2 types of enzymes of Alu1 and Mn1. Aim: This research aimed to compare different methods of typing and their application for molecular epidemiology purposes. Methods: we analyzed population of 100 strains of S.pneumoniae isolated from different patients by different molecular epidemiology methods such as pulse-field gel electophoresis (PFGE), restriction polymorphism analysis (RFLP) and multilolocus sequence typing (MLST), and all of them were compared with classic typing method as serotyping. The discriminative power was estimated with Simpson Index (SI). Results: We revealed that the most discriminative typing method is RFLP (SI=0,97, there were distinguished 42 genotypes).PFGE was slightly less discriminative (SI=0,95, we identified 35 genotypes). MLST is still the best reference method (SI=1.0). Classic method of serotyping showed quite weak discriminative power (SI=0,93, 24 genotypes). In addition, sensivity of RFLP was 100%, specificity was 97,09%. Conclusion: the most appropriate method for routine epidemiology surveillance is RFLP with non-coding region of Streptococcsu pneumoniae, then PFGE, though in some cases these results should be obligatory confirmed by MLST.

Keywords: molecular epidemiology typing, non-coding genome, Streptococcus pneumoniae, MLST

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Authors: Harisudha Kuresan, Dhanalakshmi Samiappan, T. Rama Rao

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In modern telecommunication applications, Glottal Closure Instants location finding is important and is directly evaluated from the speech waveform. Here, we study the GCI using Speech Event Detection using Residual Excitation and the Mean Based Signal (SEDREAMS) algorithm. Speech coding uses parameter estimation using audio signal processing techniques to model the speech signal combined with generic data compression algorithms to represent the resulting modeled in a compact bit stream. This paper proposes a sub-band coder SBC, which is a type of transform coding and its performance for GCI detection using SEDREAMS are evaluated. In SBCs code in the speech signal is divided into two or more frequency bands and each of these sub-band signal is coded individually. The sub-bands after being processed are recombined to form the output signal, whose bandwidth covers the whole frequency spectrum. Then the signal is decomposed into low and high-frequency components and decimation and interpolation in frequency domain are performed. The proposed structure significantly reduces error, and precise locations of Glottal Closure Instants (GCIs) are found using SEDREAMS algorithm.

Keywords: SEDREAMS, GCI, SBC, GOI

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Authors: Raffaele A. Calogero

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RNAseq represents an attractive methodology for the detection of functional genomic variants. RNAseq results obtained from polyA+ RNA selection protocol (POLYA) and from exonic regions capturing protocol (ACCESS) indicate that ACCESS detects 10% more coding SNV/INDELs with respect to POLYA. ACCESS requires less reads for coding SNV detection with respect to POLYA. However, if the analysis aims at identifying SNV/INDELs also in the 5’ and 3’ UTRs, POLYA is definitively the preferred method. No particular advantage comes from ACCESS or POLYA in the detection of fusion transcripts.

Keywords: fusion transcripts, INDEL, RNA-seq, WES, SNV

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Authors: Reut Lanyado, David Mendlovic

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Most biological methods for authentication require special equipment and, some of them are easy to fake. We proposed a method for authentication based on hand movement while typing a sentence with a regular camera. This technique uses the full video of the hand, which is harder to fake. In the first phase, we tracked the hand joints in each frame. Next, we represented a single frame for each individual using our Pose Agnostic Rotation and Movement (PARM) dimensional space. Then, we indicated a full video of hand movement in a fixed low dimensional space using this method: Fixed Dimension Video by Interpolation Statistics (FDVIS). Finally, we identified each individual in the FDVIS representation using unsupervised clustering and supervised methods. Accuracy exceeds 96% for 80 individuals by using supervised KNN.

Keywords: authentication, feature extraction, hand recognition, security, signal processing

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Authors: Tao Feng, Xiaomei Ma, Xian Guo, Jing Wang

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Named Data Network (NDN) is one of the future Internet architecture, all nodes (i.e., hosts, routers) are allowed to have a local cache, used to satisfy incoming requests for content. However, depending on caching allows an adversary to perform attacks that are very effective and relatively easy to implement, such as content pollution attack. In this paper, we use a method of secure network coding based on homomorphic signature system to solve this problem. Firstly ,we use a dynamic public key technique, our scheme for each generation authentication without updating the initial secret key used. Secondly, employing the homomorphism of hash function, intermediate node and destination node verify the signature of the received message. In addition, when the network topology of NDN is simple and fixed, the code coefficients in our scheme are generated in a pseudorandom number generator in each node, so the distribution of the coefficients is also avoided. In short, our scheme not only can efficiently prevent against Intra/Inter-GPAs, but also can against the content poisoning attack in NDN.

Keywords: named data networking, content polloution attack, network coding signature, internet architecture

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Authors: Omair Ghori, Anton Stadler, Stefan Wilk, Wolfgang Effelsberg

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Fire-related incidents account for extensive loss of life and material damage. Quick and reliable detection of occurring fires has high real world implications. Whereas a major research focus lies on the detection of outdoor fires, indoor camera-based fire detection is still an open issue. Cameras in combination with computer vision helps to detect flames and smoke more quickly than conventional fire detectors. In this work, we present a computer vision-based smoke detection algorithm based on contrast changes and a multi-step classification. This work accelerates computer vision-based fire detection considerably in comparison with classical indoor-fire detection.

Keywords: contrast analysis, early fire detection, video smoke detection, video surveillance

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Authors: Nami Takase

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Computer-mediated-communication allows people to connect and interact with each other as if they were sharing the same space. The current study examined the effects of using video letters (VLs) on the development of second language speaking skills of Common European Framework of Reference for Languages (CEFR) A1 and CEFR B2 level learners of English as a foreign language. Two groups were formed to measure the impact of VLs. The experimental and control groups were given the same topic, and both groups worked with a native English-speaking university student from the United States of America. Students in the experimental group exchanged VLs, and students in the control group used video conferencing. Pre- and post-tests were conducted to examine the effects of each practice mode. The transcribed speech-text data showed that the VL group had improved speech accuracy scores, while the video conferencing group had increased sentence complexity scores. The use of VLs may be more effective for beginner-level learners because they are able to notice their own errors and replay videos to better understand the native speaker’s speech at their own pace. Both the VL and video conferencing groups provided positive feedback regarding their interactions with native speakers. The results showed how different types of computer-mediated communication impacts different areas of language learning and speaking practice and how each of these types of online communication tool is suited to different teaching objectives.

Keywords: computer-assisted-language-learning, computer-mediated-communication, english as a foreign language, speaking

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Authors: Nassima Noufail, Sara Bouhali

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In this work, we develop a semi-supervised solution for the purpose of action detection in videos and propose an efficient algorithm for video segmentation. The approach is divided into video segmentation, feature extraction, and classification. In the first part, a video is segmented into clips, and we used the K-means algorithm for this segmentation; our goal is to find groups based on similarity in the video. The application of k-means clustering into all the frames is time-consuming; therefore, we started by the identification of transition frames where the scene in the video changes significantly, and then we applied K-means clustering into these transition frames. We used two image filters, the gaussian filter and the Laplacian of Gaussian. Each filter extracts a set of features from the frames. The Gaussian filter blurs the image and omits the higher frequencies, and the Laplacian of gaussian detects regions of rapid intensity changes; we then used this vector of filter responses as an input to our k-means algorithm. The output is a set of cluster centers. Each video frame pixel is then mapped to the nearest cluster center and painted with a corresponding color to form a visual map. The resulting visual map had similar pixels grouped. We then computed a cluster score indicating how clusters are near each other and plotted a signal representing frame number vs. clustering score. Our hypothesis was that the evolution of the signal would not change if semantically related events were happening in the scene. We marked the breakpoints at which the root mean square level of the signal changes significantly, and each breakpoint is an indication of the beginning of a new video segment. In the second part, for each segment from part 1, we randomly selected a 16-frame clip, then we extracted spatiotemporal features using convolutional 3D network C3D for every 16 frames using a pre-trained model. The C3D final output is a 512-feature vector dimension; hence we used principal component analysis (PCA) for dimensionality reduction. The final part is the classification. The C3D feature vectors are used as input to a multi-class linear support vector machine (SVM) for the training model, and we used a multi-classifier to detect the action. We evaluated our experiment on the UCF101 dataset, which consists of 101 human action categories, and we achieved an accuracy that outperforms the state of art by 1.2%.

Keywords: video segmentation, action detection, classification, Kmeans, C3D

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Authors: Ekaterina G. Lipatova

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The developing potential of a video task in teaching foreign languages involves the opportunities to improve four aspects of speech production process: listening, reading, speaking and writing. A video represents the sequence of actions, realized in the pictures logically connected and verbalized speech flow that simplifies and stimulates the process of perception. In this connection listening skills of students are developed effectively as well as their intellectual properties such as synthesizing, analyzing and generalizing the information. In terms of teaching capacity, a video task, in our opinion, is more stimulating than a traditional listening, since it involves the student into the plot of the communicative situation, emotional background and potentially makes them react to the gist in the cognitive and communicative ways. To be an effective method of teaching the video task should be structured in the way of psycho-linguistic characteristics of speech production process, in other words, should include three phases: before-watching, while-watching and after-watching. The system of tasks provided to each phase might involve the situations on reflecting to the video content in the forms of filling-the-gap tasks, multiple choice, True-or-False tasks (reading skills), exercises on expressing the opinion, project fulfilling (writing and speaking skills). In the before-watching phase we offer the students to adjust their perception mechanism to the topic and the problem of the chosen video by such task as “what do you know about such a problem?”, “is it new for you?”, “have you ever faced the situation of…?”. Then we proceed with the lexical and grammatical analysis of language units that form the body of a speech sample to lessen the perception and develop the student’s lexicon. The goal of while-watching phase is to build the student’s awareness about the problem presented in the video and challenge their inner attitude towards what they have seen by identifying the mistakes in the statements about the video content or making the summary, justifying their understanding. Finally, we move on to development of their speech skills within the communicative situation they observed and learnt by stimulating them to search the similar ideas in their backgrounds and represent them orally or in the written form or express their own opinion on the problem. It is compulsory to highlight, that a video task should contain the urgent, valid and interesting event related to the future profession of the student, since it will help to activate cognitive, emotional, verbal and ethic capacity of students. Also, logically structured video tasks are easily integrated into the system of e-learning and can provide the opportunity for the students to work with the foreign language on their own.

Keywords: communicative situation, perception mechanism, speech production process, speech skills

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Authors: Anton Stadler, Thorsten Ike

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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: low density, optical flow, upward smoke motion, video based smoke detection

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Authors: Anthony D. Rhodes, Manan Goel

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We provide a high fidelity deep learning algorithm (HyperSeg) for interactive video segmentation tasks using a dense convolutional network with context-aware skip connections and compressed, 'hypercolumn' image features combined with a convolutional tessellation procedure. In order to maintain high output fidelity, our model crucially processes and renders all image features in high resolution, without utilizing downsampling or pooling procedures. We maintain this consistent, high grade fidelity efficiently in our model chiefly through two means: (1) we use a statistically-principled, tensor decomposition procedure to modulate the number of hypercolumn features and (2) we render these features in their native resolution using a convolutional tessellation technique. For improved pixel-level segmentation results, we introduce a boundary loss function; for improved temporal coherence in video data, we include temporal image information in our model. Through experiments, we demonstrate the improved accuracy of our model against baseline models for interactive segmentation tasks using high resolution video data. We also introduce a benchmark video segmentation dataset, the VFX Segmentation Dataset, which contains over 27,046 high resolution video frames, including green screen and various composited scenes with corresponding, hand-crafted, pixel-level segmentations. Our work presents a improves state of the art segmentation fidelity with high resolution data and can be used across a broad range of application domains, including VFX pipelines and medical imaging disciplines.

Keywords: computer vision, object segmentation, interactive segmentation, model compression

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Authors: Dilek Saritas Atalar, Cansu Alsancak Akbulut, İrem Metin Orta, Feyza Yön, Zeynep Yenen, Joan Grusec

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Objective: The aim of this study was to develop semi-structured Domains of Socialization Interview and its coding manual and to test their psychometric properties. Domains of Socialization Interview was designed to assess maternal awareness regarding effective parenting in five socialization domains (protection, mutual reciprocity, control, guided learning, and group participation) within the framework of the domains-of-socialization approach. Method: A series of two studies were conducted to develop and validate the interview and its coding manual. The pilot study, sampled 13 mothers of preschool-aged children, was conducted to develop the assessment tools and to test their function and clarity. Participants of the main study were 82 Turkish mothers (Xage = 34.25, SD = 3.53) who have children aged between 35-76 months (Xage = 50.75, SD = 11.24). Mothers filled in a questionnaire package including Coping with Children’s Negative Emotions Questionnaire, Social Competence and Behavior Evaluation-30, Child Rearing Questionnaire, and Two Dimensional Social Desirability Questionnaire. Afterward, interviews were conducted online by a single interviewer. Interviews were rated independently by two graduate students based on the coding manual. Results: The relationships of the awareness of effective parenting scores to the other measures demonstrate convergent, discriminant, and predictive validity of the coding manual. Intra-class correlation coefficient estimates were ranged between 0.82 and 0.90, showing high interrater reliability of the coding manual. Conclusion: Taken as a whole, the results of these studies demonstrate the validity and reliability of a new and useful interview to measure maternal awareness regarding effective parenting within the framework of the domains-of-socialization approach.

Keywords: domains of socialization, parenting, interview, assessment

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Authors: Josep Domenech Mingot, Francisco Javier Esclapes Jover

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The arrival of the age of information and new technologies allowed humanity to see what the future has in store, but occasionally it also brings the opportunity to look through a window to the past, an opportunity to relive history. This paper introduces a prototype of a digital system that lets us peek into our past making use of augmented reality technologies. A 3D scene will be modeled and animated based on an old image, depicting an event of historical significance. From this scene, a video will be rendered, recreating the events that were taking place at the time. Also, a smartphone app will be created. This app will detect the original image with the smartphone’s camera, overlay the rendered video so that it fully covers it and track the detected image, so that the overlaying video can keep covering the image. The recreation of Alicante’s Central Market bombing during the Spanish Civil War is presented as a case study.

Keywords: augmented reality, digital heritage, history, multimedia, smartphone

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Authors: Hasibul Kabir, Samin Shahriar Tokey, Md. Tofazzal Hossain

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One of the most necessary things in the present time is raising social awareness about global warming and climate change among the people. Though many types of mediums and techniques have been used to teach people about this global phenomenon, there are still more effective ways to reach people with useful information about global warming. As many traditional methods to teach people about global warming and climate change did not work well, video games were overdue. To learn how effective a video game can be in this regard, we developed a Video game, "Historia's Nightmare," that teaches people about Global warming and climate change. The game was designed to entertain people and give them an idea about the reasons and consequences of global warming and climate change while not being like traditional educational games. The game threw a mini quiz consisting of two MCQs based on the information shown in the game, where a gamer had to pass the quiz to reach the next level. We published the game on different platforms to let all types of people play and complete our experiment effectively. The game continuously communicated with our server to send data about gamers' performance. We observed the data, including the participants' performance, time spent, quiz score, and the in-game feedback on a regular basis, and finally came to a verdict. In our experiment, we have found that most participants positively accepted the game and learned something new. The participants who spent more on our game performed better in both quiz and the game. Our experiment's result demonstrates that video games can be a great way to teach people something, particularly to raise social awareness about global warming and climate change. It also demonstrates that the game can be a significant element in education and learning improvement.

Keywords: video game, global warming, social awareness, climate change, education, feedback

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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: Mokhlisur Rahman

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The growing consensus among scientists and world leaders indicates that immediate action should be considered regarding the climate change phenomenon. However, climate change is no more a global issue but a personal one. Thus, individual participation is necessary to address such a significant issue. Studies show that individuals who perceive climate change as a personal issue are more likely to act toward it. This abstract presents augmented reality (A.R.) technology in the social media platform Facebook video advertising. The idea involves creating a video advertisement that enables users to interact with the video by navigating its features and experiencing the result uniquely and engagingly. This advertisement uses A.R. to bring changes, such as people making changes in real-life scenarios by simple clicks on the video and hearing an instant rewarding fact about their choices. The video shows three options: room, lawn, and driveway. Users select one option and engage in interaction based on while holding the camera in their personal spaces: Suppose users select the first option, room, and hold their camera toward spots such as by the windows, balcony, corners, and even walls. In that case, the A.R. offers users different plants appropriate for those unoccupied spaces in the room. Users can change the options of the plants and see which space at their house deserves a plant that makes it more natural. When a user adds a natural element to the video, the video content explains a piece of beneficiary information about how the user contributes to the world more to be livable and why it is necessary. With the help of A.R., if users select the second option, lawn, and hold their camera toward their lawn, the options are various small trees for their lawn to make it more environmentally friendly and decorative. The video plays a beneficiary explanation here too. Suppose users select the third option, driveway, and hold their camera toward their driveway. In that case, the A.R. video option offers unique recycle bin designs using A.I. measurement of spaces. The video plays audio information on anthropogenic contribution to greenhouse gas emission. IoT embeds tracking code in the video ad on Facebook, which stores the exact number of views in the cloud for data analysis. An online survey at the end collects short qualitative answers. This study helps understand the number of users involved and willing to change their behavior; It makes personalized advertising in social media. Considering the current state of climate change, the urgency for action is increasing. This ad increases the chance to make direct connections with individuals and gives a sense of personal responsibility for climate change to act

Keywords: motivations, climate, iot, personalized-advertising, action

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Authors: Ruolan Zhou

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Trisomy of human chromosome 21 is the primary cause of Down Syndrome (DS), and this genetic disease has significantly burdened families and countries, causing great controversy. To address this problem, the research takes an approach in exploring the relationship between genetic abnormality and this disease's symptoms, adopting several techniques, including data analysis and enrichment analysis. It also explores open-source websites, such as NCBI, DAVID, SOURCE, STRING, as well as UCSC, to complement its result. This research has analyzed the variety of genes on human chromosome 21 with simple coding, and by using analysis, it has specified the protein-coding genes, their function, and their location. By using enrichment analysis, this paper has found the abundance of keratin production-related coding-proteins on human chromosome 21. By adopting past researches, this research has attempted to disclose the relationship between trisomy of human chromosome 21 and keratin production abnormality, which might be the reason for common diseases in patients with Down Syndrome. At last, by addressing the advantage and insufficiency of this research, the discussion has provided specific directions for future research.

Keywords: Down Syndrome, protein production, genome, enrichment analysis

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Authors: Abiola Falilat Ibraheem, Akinyimika Sowunmi, Valerie Otti

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Background: Introduction of innovative cancer clinical trials to Nigeria is a critical step in addressing global inequities of cancer burden. Low health and clinical trial literacy among Nigerian patients have been sighted as a significant barrier to ensuring that patients enrolled in clinical trials are truly informed. Video intervention has been shown to be the most proactive method to improving patient’s clinical trial knowledge. In the US, video interventions have been successful at improving education about cancer clinical trials among minority patients. Thus, this study aimed to apply and adapt video interventions addressing attitudinal barriers peculiar to Nigerian patients. Methods: A hospital-based representative mixed-method study was conducted at the Lagos State University Teaching Hospital (LASUTH) from July to December 2020, comprising of cancer patients aged 18 and above. Patients were randomly selected during every clinic day, of which 63 patients volunteered to participate in this study. We first administered a cancer literacy survey to determine patients’ knowledge about clinical trials. For patients who had prior knowledge, a pre-intervention test was administered, after which a 15-minute video (attitudes and intention to enroll in therapeutic clinical trials (AIET)) to improve patients’ knowledge, perception, and attitudes towards clinical trials was played, and then ended by administering a post-intervention test to the patients. For patients who had no prior knowledge, the AIET video was played for them, followed by the post-intervention test. Results: Out of 63 patients sampled, 43 (68.3%) had breast cancer. On average, patients agreed to understand their cancer diagnosis and treatment very well. 84.1% of patients had never heard about cancer clinical trials, and 85.7% did not know what cancer clinical trials were. There was a strong positive relationship (r=0.916) between the pretest and posttest, which means that the intervention improved patients’ knowledge, perception, and attitudes about cancer clinical trials. In the focus groups, patients recommended adapting the video in Nigerian settings and representing all religions in order to address trust in local clinical trialists. Conclusion: Due to the small size of patients, change in clinical trial knowledge was not statistically significant. However, there is a trend suggesting that culturally adapted video interventions can be used to improve knowledge and perception about cancer clinical trials.

Keywords: clinical trials, culturally targeted intervention, patient education, video intervention

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Authors: I Gede Puja Astawa, Yoedy Moegiharto, Ahmad Zainudin, Imam Dui Agus Salim, Nur Annisa Anggraeni

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Performance of Orthogonal Frequency Division Multiplexing (OFDM) system can be improved by adding channel coding (error correction code) to detect and correct the errors that occur during data transmission. One can use the convolution code. This paper presents performance of OFDM using Space Time Block Codes (STBC) diversity technique use QAM modulation with code rate 1/2. The evaluation is done by analyzing the value of Bit Error Rate (BER) vs. Energy per Bit to Noise Power Spectral Density Ratio (Eb/No). This scheme is conducted 256 sub-carrier which transmits Rayleigh multipath channel in OFDM system. To achieve a BER of 10-3 is required 30 dB SNR in SISO-OFDM scheme. For 2x2 MIMO-OFDM scheme requires 10 dB to achieve a BER of 10-3. For 4x4 MIMO-OFDM scheme requires 5 dB while adding convolution in a 4x4 MIMO-OFDM can improve performance up to 0 dB to achieve the same BER. This proves the existence of saving power by 3 dB of 4x4 MIMO-OFDM system without coding, power saving 7 dB of 2x2 MIMO-OFDM system without coding and significant power savings from SISO-OFDM system.

Keywords: convolution code, OFDM, MIMO, QAM, BER

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Authors: Souhir Chelly, Chahida Harizi, Aicha Hechaichi, Sihem Aissaoui, Leila Ben Ayed, Maha Bergaoui, Mohamed Kouni Chahed

Abstract:

Introduction: The International Classification of Primary Care (ICPC) is part of the morbidity classification system. It had 17 chapters, and each is coded by an alphanumeric code: the letter corresponds to the chapter, the number to a paragraph in the chapter. The objective of this study is to show the utility of this classification in the coding of the reasons for demand for care in Primary health care (PHC), its advantages and limits. Methods: This is a cross-sectional descriptive study conducted in 4 PHC in Ariana district. Data on the demand for care during 2 days in the same week were collected. The coding of the information was done according to the CISP. The data was entered and analyzed by the EPI Info 7 software. Results: A total of 523 demands for care were investigated. The patients who came for the consultation are predominantly female (62.72%). Most of the consultants are young with an average age of 35 ± 26 years. In the ICPC, there are 7 rubrics: 'infections' is the most common reason with 49.9%, 'other diagnoses' with 40.2%, 'symptoms and complaints' with 5.5%, 'trauma' with 2.1%, 'procedures' with 2.1% and 'neoplasm' with 0.3%. The main advantage of the ICPC is the fact of being a standardized tool. It is very suitable for classification of the reasons for demand for care in PHC according to their specificity, capacity to be used in a computerized medical file of the PHC. Its current limitations are related to the difficulty of classification of some reasons for demand for care. Conclusion: The ICPC has been developed to provide healthcare with a coding reference that takes into account their specificity. The CIM is in its 10th revision; it would gain from revision to revision to be more efficient to be generalized and used by the teams of PHC.

Keywords: international classification of primary care, medical file, primary health care, Tunisia

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Authors: Kristin Lewis, Howard Steele, Anne Murphy, Miriam Steele, Karen Bonuck, Paul Meissner

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The present study examines data collected during the randomized control trial (RCT) of the Group Attachment-Based Intervention (GABI©), a trauma-informed, attachment-based intervention aimed at promoting healthy parent-child relationships that support child development. Families received treatment at Treatment Center and were randomly assigned to either the GABI condition or the treatment as usual condition, a parenting class called Systematic Training for Effective Parenting (STEP). Significant improvements in the parent-child relationship have been reported for families participating in GABI, but not in the STEP control group relying on Coding Interactive Behavior (CIB) as applied to 5-minute video-films of mothers and their toddlers in a free play context. This report considers five additional attachment-relevant 'clinical codes' that were also applied to the 5-minute free play sessions. Seventy-two parent-child dyads (38 in GABI and 34 in STEP) were compared to one another at intake and end-of-treatment, on these five-point dimensions: two-parent codes—the dissociation and ignoring; two child codes—simultaneous display of contradictory behavior and fear; and one parent-child code, i.e., role reversal. Overall, scores were low for these clinical codes; thus, a binary measure was computed contrasting no evidence with some evidence of each clinical code. Crosstab analyses indicate that child fear at end-of-treatment was significantly lower among children who participated in GABI (7% or 3 children) as compared to those whose mothers participated in STEP (29% or 10 children) Chi Sq= 6.57 (1), p < .01. Discussion focuses on the potential for GABI to reduce childhood fearfulness and so enhance the child's health.

Keywords: coding interactive behavior, clinical codes, group attachment based intervention, GABI, attachment, fear

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Authors: Harpal Singh, Sakshi Batra

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The widespread and easy accesses to multimedia contents and possibility to make numerous copies without loss of significant fidelity have roused the requirement of digital rights management. Thus this problem can be effectively solved by Digital watermarking technology. This is a concept of embedding some sort of data or special pattern (watermark) in the multimedia content; this information will later prove ownership in case of a dispute, trace the marked document’s dissemination, identify a misappropriating person or simply inform user about the rights-holder. The primary motive of digital watermarking is to embed the data imperceptibly and robustly in the host information. Extensive counts of watermarking techniques have been developed to embed copyright marks or data in digital images, video, audio and other multimedia objects. With the development of digital video-based innovations, copyright dilemma for the multimedia industry increases. Video watermarking had been proposed in recent years to serve the issue of illicit copying and allocation of videos. It is the process of embedding copyright information in video bit streams. Practically video watermarking schemes have to address some serious challenges as compared to image watermarking schemes like real-time requirements in the video broadcasting, large volume of inherently redundant data between frames, the unbalance between the motion and motionless regions etc. and they are particularly vulnerable to attacks, for example, frame swapping, statistical analysis, rotation, noise, median and crop attacks. In this paper, an effective, robust and imperceptible video watermarking algorithm is proposed based on hybridization of powerful mathematical transforms; Fractional Fourier Transform (FrFT), Discrete Wavelet transforms (DWT) and Singular Value Decomposition (SVD) using redundant wavelet. This scheme utilizes various transforms for embedding watermarks on different layers by using Hybrid systems. For this purpose, the video frames are portioned into layers (RGB) and the watermark is being embedded in two forms in the video frames using SVD portioning of the watermark, and DWT sub-band decomposition of host video, to facilitate copyright safeguard as well as reliability. The FrFT orders are used as the encryption key that allows the watermarking method to be more robust against various attacks. The fidelity of the scheme is enhanced by introducing key generation and wavelet based key embedding watermarking scheme. Thus, for watermark embedding and extraction, same key is required. Therefore the key must be shared between the owner and the verifier via some safe network. This paper demonstrates the performance by considering different qualitative metrics namely Peak Signal to Noise ratio, Structure similarity index and correlation values and also apply some attacks to prove the robustness. The Experimental results are presented to demonstrate that the proposed scheme can withstand a variety of video processing attacks as well as imperceptibility.

Keywords: discrete wavelet transform, robustness, video watermarking, watermark

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Authors: Doaa Hashad, Amany Elbanna, Abeer Ibrahim, Gihan Khedr

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Background: H19 is one of the long non coding RNAs (LncRNA) that is related to the progression of many diseases including cancers. This work was carried out to study the level of the long non-coding RNA; H119, in plasma of patients with gastric cancer (GC) and to assess its significance in their clinical management. Methods: A total of sixty-two participants were enrolled in the present study. The first group included thirty-two GC patients, while the second group was formed of thirty age and sex matched healthy volunteers serving as a control group. Plasma samples were used to assess H19 gene expression using real time quantitative PCR technique. Results: H19 expression was up-regulated in GC patients with positive correlation to TNM cancer stages. Conclusions: Up-regulation of H19 is closely associated with gastric cancer and correlates well with tumor staging. Convenient, efficient quantification of H19 in plasma using real time PCR technique implements its role as a potential noninvasive prognostic biomarker in gastric cancer, that predicts patient’s outcome and most importantly as a novel target in gastric cancer treatment with better performance achieved on using both CEA and H19 simultaneously.

Keywords: biomarker, gastric, cancer, LncRNA

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Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela

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Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.

Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution

Procedia PDF Downloads 517