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"doi": "10.1109/CW49994.2020.00036",
"title": "Virtual Reality for Training and Fitness Assessments for Construction Safety",
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"abstract": "Reducing accident rate is a primary goal of construction safety. In this paper, we present a large scale study of using virtual reality technology for safety training. Beyond the training, a technology framework is proposed to assess the fitness of construction workers (e.g. suitability of people with underlining health conditions to work under particular construction environments). The new virtual construction system consists of a Brain-Computer Interface (BCI) of electroencephalography (EEG) neural network to capture EEG signals of users during the virtual simulation training continuously to achieve user profiling. For real-time assessment of the accident susceptibility of a worker under various construction environments, a deep learning neural network is trained to process the EEG crops and a clipping training algorithm that classifies small segments of the EEG dataset is used to improve the computational performance of the system. Physiology data of the person during the training, i.e. blood pressure and heart rate, is also recorded. Based on the EEG data and the physiology data, a statistic model is used in the safety assessment framework to set up the risk standard. The study has tested 117 workers who were employed by the construction sites in Shanghai. People who were tested in the risk group were further underwent medical examinations for risk related medical conditions that deemed unsuitable for working in construction sites. Results show six of the nine workers identified by the VR system have been medically confirmed unsuitable, thus, over 80% accuracy of our virtual reality training and assessment system. Our proposed system can be used as a tool for understanding risk conditions of workers and safety training.",
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"fullName": "Dongiin Huang",
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"fullName": "Xianglong Wang",
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{
"affiliation": "Shanghai University,Shanghai Film Academy,Shanghai,China",
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"affiliation": "University of Bournemouth,Faculty of Science, Design and Technology,Poole,Dorset,UK",
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"title": "2021 International Conference on Management Science and Software Engineering (ICMSSE)",
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"abstract": "A quick, accurate and comprehensive grasp of the damages of the disaster-stricken area after the earthquakes and a timely release of earthquake intensity maps are of great value for planning of emergency rescue initiatives, post-disaster reconstruction, earthquake prevention and disaster relief. To make the earthquake intensity assessment, disaster damage investigation and evaluation more timely, scientific and accurate, this study proposed a simulation training system for earthquake intensity assessment and disaster damage evaluation. Through computer technologies, Web technique, and database technologies, the actual earthquake disaster scenarios were simulated for earthquake rescue workers so that they could perform earthquake intensity assessment and disaster damage investigations through the Internet in a virtual manner. The proposed system would not only provide a set of new training modes for rescue workers, but also improve the emergency training, and enhance the overall quality of the disaster evaluation team. It could increase the fidelity of training and raise the tensity for training, test the rationality of the content and procedures of disaster evaluation, effectively assess the details of disaster evaluation, which could help the rescue team better fulfill on-site earthquake evaluation and disaster damage evaluation in the future.",
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"title": "Compelling AR Earthquake Simulation with AR Screen Shaking",
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"abstract": "Our goal is to simulate earthquakes in a familiar environment, for example in one’s own office, helping users to take the simulation more seriously. We propose an AR earthquake simulation using a video see-through VR headset, use real earthquake data, and implement a novel AR screen shake technique, realistically shaking the entire view of the user. We run a user study (n=25), where participants experienced an earthquake both in a VR scene and two AR scenes with and without the AR screen shake technique. Our results suggest that both AR scenes offer a more compelling experience compared to the VR scene, and the AR screen shake improved immediacy and was preferred by most participants. This showed us how virtual safety training can greatly benefit from an AR implementation, motivating us to further explore this approach for the case of earthquakes.",
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"content": "Our goal is to simulate earthquakes in a familiar environment, for example in one’s own office, helping users to take the simulation more seriously. We propose an AR earthquake simulation using a video see-through VR headset, use real earthquake data, and implement a novel AR screen shake technique, realistically shaking the entire view of the user. We run a user study (n=25), where participants experienced an earthquake both in a VR scene and two AR scenes with and without the AR screen shake technique. Our results suggest that both AR scenes offer a more compelling experience compared to the VR scene, and the AR screen shake improved immediacy and was preferred by most participants. This showed us how virtual safety training can greatly benefit from an AR implementation, motivating us to further explore this approach for the case of earthquakes.",
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"affiliation": "Nara Institute of Science and Technology",
"fullName": "Setthawut Chotchaicharin",
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"abstract": "Light-field head-mounted displays (HMDs) can resolve vergence-accommodation conflicts, which may cause visual discomfort and fatigue. However, light-field HMDs have a narrow field of view (FOV), owing to their small display size and optical configuration. We increased the FOV by adopting a large display and shifting the elemental image from the back of the corresponding microlens. In this study, we proposed a method to generate intermediate images as virtual images to reduce the distance between the microlens array and the eyepiece. We also designed a microlens array suitable for the proposed method and successfully reduced the device depth by 44%.",
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"affiliation": "The University of Tokyo",
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"affiliation": "The University of Tokyo",
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"affiliation": "The University of Tokyo",
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"affiliation": "The University of Tokyo",
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"abstract": "More than 5% of adults suffer from different types of kidney disease, and millions of people die prematurely from cardiovascular diseases associated with chronic kidney disease (CKD) in each year. The best way to reduce death caused by kidney disease is early prophylaxis and treatment, and which could be achieved through accurate and reliable diagnoses at the early stage. Among various diagnostic methods, ultrasonographic diagnosis is a low-cost, convenient, non-invasive, and timeliness method. Most importantly, this type inspection would not cause extra burden for patients who suffer kidney diseases. This paper presents a computer-aided diagnosis tool based on analyzing ultrasonography images, and the developed system could detect and classify different stages of CKD. The image processing techniques focus on detecting the atrophy of kidney and the proportion of fibrosis conditions within kidney tissues. The system includes image in painting, noise filtering, contour detection, local contrast enhancement, tissue clustering, and quantitative indicator measuring for distinguishing various stages of CKD. This study has collected thousands of ultrasonic images from patients with kidney diseases, and the selected representative CKD images were applied to be pre-analyzed and trained for comparison. The calculated transition locations as reference indicators could provide physicians an auxiliary and objective computer-aid diagnosis tool for CKD identification and classification.",
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"content": "More than 5% of adults suffer from different types of kidney disease, and millions of people die prematurely from cardiovascular diseases associated with chronic kidney disease (CKD) in each year. The best way to reduce death caused by kidney disease is early prophylaxis and treatment, and which could be achieved through accurate and reliable diagnoses at the early stage. Among various diagnostic methods, ultrasonographic diagnosis is a low-cost, convenient, non-invasive, and timeliness method. Most importantly, this type inspection would not cause extra burden for patients who suffer kidney diseases. This paper presents a computer-aided diagnosis tool based on analyzing ultrasonography images, and the developed system could detect and classify different stages of CKD. The image processing techniques focus on detecting the atrophy of kidney and the proportion of fibrosis conditions within kidney tissues. The system includes image in painting, noise filtering, contour detection, local contrast enhancement, tissue clustering, and quantitative indicator measuring for distinguishing various stages of CKD. This study has collected thousands of ultrasonic images from patients with kidney diseases, and the selected representative CKD images were applied to be pre-analyzed and trained for comparison. The calculated transition locations as reference indicators could provide physicians an auxiliary and objective computer-aid diagnosis tool for CKD identification and classification.",
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"title": "Detection of oxidative stress in neurodegenerative diseases",
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"abstract": "Oxidative stress is a metabolic condition generating from the disproportion between the production of potentially reactive oxygen species and the scavenging activities. Increased level of reactive oxygen species may cause increased oxidative damage of biomolecules, an accumulation of this damage, and the development of many pathogenic conditions, especially the ones that implicate the human brain. Mitochondrial oxidative damage as well as oxidative nucleoside damage could be a significant issue in the pathogenesis of neurodegenerative diseases. In order to demonstrate the potential contribution of reactive oxygen species in normal aging and especially Alzheimer's disease this research will try to examine if there is a differentiation between the levels of oxidative stress in healthy subjects and patients suffering from the disease. Furthermore, we shall try to demonstrate if the early detection of reactive oxygen species could be used as a prognostic factor for the development of neurodegenerative diseases.",
"abstracts": [
{
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"content": "Oxidative stress is a metabolic condition generating from the disproportion between the production of potentially reactive oxygen species and the scavenging activities. Increased level of reactive oxygen species may cause increased oxidative damage of biomolecules, an accumulation of this damage, and the development of many pathogenic conditions, especially the ones that implicate the human brain. Mitochondrial oxidative damage as well as oxidative nucleoside damage could be a significant issue in the pathogenesis of neurodegenerative diseases. In order to demonstrate the potential contribution of reactive oxygen species in normal aging and especially Alzheimer's disease this research will try to examine if there is a differentiation between the levels of oxidative stress in healthy subjects and patients suffering from the disease. Furthermore, we shall try to demonstrate if the early detection of reactive oxygen species could be used as a prognostic factor for the development of neurodegenerative diseases.",
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"normalizedAbstract": "Oxidative stress is a metabolic condition generating from the disproportion between the production of potentially reactive oxygen species and the scavenging activities. Increased level of reactive oxygen species may cause increased oxidative damage of biomolecules, an accumulation of this damage, and the development of many pathogenic conditions, especially the ones that implicate the human brain. Mitochondrial oxidative damage as well as oxidative nucleoside damage could be a significant issue in the pathogenesis of neurodegenerative diseases. In order to demonstrate the potential contribution of reactive oxygen species in normal aging and especially Alzheimer's disease this research will try to examine if there is a differentiation between the levels of oxidative stress in healthy subjects and patients suffering from the disease. Furthermore, we shall try to demonstrate if the early detection of reactive oxygen species could be used as a prognostic factor for the development of neurodegenerative diseases.",
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"Medical Disorders",
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"affiliation": "Department of Informatics, Ionian University, Corfu, Greece",
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"affiliation": "Department of Informatics, Ionian University, Corfu, Greece",
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"abstract": "Monitoring gait patterns seamlessly and continuously over time provides valuable information that could help physicians diagnose diseases in the early stages. Currently, traditional gait measurement approaches do not support continuous monitoring of gait and focus on collecting limited data points in controlled lab environments. However, with advancements in wireless technology, movement patterns can be recorded using small portable wearable devices. Parkinson's disease (PD) is a progressively disabling neurodegenerative disorder that is affecting gait and posture and consequently leads to higher risk of falling. Several research studies have looked into changes in the gait parameters of PD patients compared to healthy adults. However, there are only few studies with the focus on gait assessment of PD patients in the early stages as compared to patterns associated with patients at advanced stages. In addition, the number of gait-related studies in this domain using accelerometers on ankle is very limited. Knowing which body location could serve as a target place for accelerometers to provide accurate information is a necessary step toward the health assessment of PD patients. The purpose of this study was to evaluate the gait parameters of patients with mild or moderate PD using accelerometers on ankles. A number of gait parameters, including average stride time, stride time variability, stride time symmetry, and oscillation of acceleration in the mediolateral (ML) direction were calculated and compared between PD patients and healthy elderlies. Preliminary results indicate that features extracted from accelerometers on ankles can be effective in differentiating between healthy elderlies and PD patients at mid-stages of disease but less so at earlier stages of disease.",
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"content": "Monitoring gait patterns seamlessly and continuously over time provides valuable information that could help physicians diagnose diseases in the early stages. Currently, traditional gait measurement approaches do not support continuous monitoring of gait and focus on collecting limited data points in controlled lab environments. However, with advancements in wireless technology, movement patterns can be recorded using small portable wearable devices. Parkinson's disease (PD) is a progressively disabling neurodegenerative disorder that is affecting gait and posture and consequently leads to higher risk of falling. Several research studies have looked into changes in the gait parameters of PD patients compared to healthy adults. However, there are only few studies with the focus on gait assessment of PD patients in the early stages as compared to patterns associated with patients at advanced stages. In addition, the number of gait-related studies in this domain using accelerometers on ankle is very limited. Knowing which body location could serve as a target place for accelerometers to provide accurate information is a necessary step toward the health assessment of PD patients. The purpose of this study was to evaluate the gait parameters of patients with mild or moderate PD using accelerometers on ankles. A number of gait parameters, including average stride time, stride time variability, stride time symmetry, and oscillation of acceleration in the mediolateral (ML) direction were calculated and compared between PD patients and healthy elderlies. Preliminary results indicate that features extracted from accelerometers on ankles can be effective in differentiating between healthy elderlies and PD patients at mid-stages of disease but less so at earlier stages of disease.",
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"abstract": "As an irreversible neurodegenerative disease, the progression of Alzheimer's disease includes three stages: cognitively normal (CN), mild cognitive impairment (MCI) and Alzheimer's disease (AD). Early diagnosis of the disease i.e. the stage of MCI is helpful for its early intervention. In this paper we propose a multistage discriminative event-based model (MDEBM). By modelling the discriminative events in cross-sectional data of the patients into three categories through Gaussian Mixture, then staging the patient by Bayesian classifier, the model can detect not only the patients with AD but also those with MCI. besides, the diagnosis of Alzheimer's disease is often based on a combination of factors including the patient's medical history, the results of cognitive tests and neuroimaging. This model supports gradually improving the accuracy of diagnosis through the consecutive input of different categories of patient's examination results. Experiments on Alzheimer's Disease Neuroimaging Initiative (ADNI) data prove the effectiveness of our model.",
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"content": "As an irreversible neurodegenerative disease, the progression of Alzheimer's disease includes three stages: cognitively normal (CN), mild cognitive impairment (MCI) and Alzheimer's disease (AD). Early diagnosis of the disease i.e. the stage of MCI is helpful for its early intervention. In this paper we propose a multistage discriminative event-based model (MDEBM). By modelling the discriminative events in cross-sectional data of the patients into three categories through Gaussian Mixture, then staging the patient by Bayesian classifier, the model can detect not only the patients with AD but also those with MCI. besides, the diagnosis of Alzheimer's disease is often based on a combination of factors including the patient's medical history, the results of cognitive tests and neuroimaging. This model supports gradually improving the accuracy of diagnosis through the consecutive input of different categories of patient's examination results. Experiments on Alzheimer's Disease Neuroimaging Initiative (ADNI) data prove the effectiveness of our model.",
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"abstract": "Computer-Generated Holography (CGH) offers the potential for genuine, high-quality three-dimensional visuals. However, fulfilling this potential remains a practical challenge due to computational complexity and visual quality issues. We propose a new CGH method that exploits gaze-contingency and perceptual graphics to accelerate the development of practical holographic display systems. Firstly, our method infers the user’s focal depth and generates images only at their focus plane without using any moving parts. Second, the images displayed are metamers; in the user’s peripheral vision, they need only be statistically correct and blend with the fovea seamlessly. Unlike previous methods, our method prioritises and improves foveal visual quality without causing perceptually visible distortions at the periphery. To enable our method, we introduce a novel metameric loss function that robustly compares the statistics of two given images for a known gaze location. In parallel, we implement a model representing the relation between holograms and their image reconstructions. We couple our differentiable loss function and model to metameric varifocal holograms using a stochastic gradient descent solver. We evaluate our method with an actual proof-of-concept holographic display, and we show that our CGH method leads to practical and perceptually three-dimensional image reconstructions.",
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"content": "Computer-Generated Holography (CGH) offers the potential for genuine, high-quality three-dimensional visuals. However, fulfilling this potential remains a practical challenge due to computational complexity and visual quality issues. We propose a new CGH method that exploits gaze-contingency and perceptual graphics to accelerate the development of practical holographic display systems. Firstly, our method infers the user’s focal depth and generates images only at their focus plane without using any moving parts. Second, the images displayed are metamers; in the user’s peripheral vision, they need only be statistically correct and blend with the fovea seamlessly. Unlike previous methods, our method prioritises and improves foveal visual quality without causing perceptually visible distortions at the periphery. To enable our method, we introduce a novel metameric loss function that robustly compares the statistics of two given images for a known gaze location. In parallel, we implement a model representing the relation between holograms and their image reconstructions. We couple our differentiable loss function and model to metameric varifocal holograms using a stochastic gradient descent solver. We evaluate our method with an actual proof-of-concept holographic display, and we show that our CGH method leads to practical and perceptually three-dimensional image reconstructions.",
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"abstract": "A density staggered cantilever was developed to measure the micron length gravity between itself and an optically levitated microsphere in high vacuum. The cantilever, has two main density contrasted materials gold(19.3g/cm3) and silicon(2.33g/cm3), where each of the material is finger-shaped and stagger placed next to each other, constitute an integral finger array on the device layer of SOI wafer. The scallop of the DRIE defined fingers was optimized to be less than 50nm to reduce the surface variation between the cantilever and levitated microsphere. The end of each fingers were covered with 2-10um silicon and gold to shield the undesired charged particles. The back side of SOI wafer were defined with DRIE to release the cantilever. The Cantilever will be placed microns away from the microsphere and mechanically move back and forth to interact with the microsphere. This paper introduces the design, manufacturing of the density staggered cantilever for micron length gravity.",
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"abstract": "Haptic feedback has been finding increasing uses in affective interaction design. In this paper, we describe the emotional characteristics of multimodal tactile stimuli that combine vibrotactile and thermal stimuli. While varying three vibrotactile parameters of frequency, amplitude, and duration and one thermal parameter of constant temperature, we experimentally evaluated the valence and arousal of 1) thermal stimuli and 2) multimodal vibrotactile-thermal stimuli with 20 participants. Results indicated that the thermal and vibrotactile parameters have clear and somewhat independent effects on emotional responses. The findings of this study can contribute to expanding the design space of affective user interaction involving touch.",
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"content": "Haptic feedback has been finding increasing uses in affective interaction design. In this paper, we describe the emotional characteristics of multimodal tactile stimuli that combine vibrotactile and thermal stimuli. While varying three vibrotactile parameters of frequency, amplitude, and duration and one thermal parameter of constant temperature, we experimentally evaluated the valence and arousal of 1) thermal stimuli and 2) multimodal vibrotactile-thermal stimuli with 20 participants. Results indicated that the thermal and vibrotactile parameters have clear and somewhat independent effects on emotional responses. The findings of this study can contribute to expanding the design space of affective user interaction involving touch.",
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"affiliation": "Department of Computer Science and Engineering, POSTECH, Pohang, South Korea 37673",
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"abstract": "The first virtual reality (VR) systems have hit the shelves, and 2017 may become the year where VR finally enters the homes of consumers in a big way. By allowing users to perceive and interact in a natural manner, VR offers the promise of realistic experiences of familiar, foreign, and fantastic virtual places and events. However, should we always opt for the highest degree of fidelity when striving to provide users with realistic experiences? In this position paper, we argue that when certain components of fidelity are limited, as they will be in relation to consumer VR, then maximizing the fidelity of other components may be detrimental to the perceived realism of the user. We present three cases supporting this hypothesis, and discuss the potential implications for researchers and developers relying on commercially available VR systems.",
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"abstract": "QR codes are widely used as a means of conveying textual information, such as emails, hyperlinks, or phone numbers, through images that are interpreted using a smartphone camera. The codes take up valuable space in print media. The random appearance of QR codes not only detracts from the production values of the advertisement in which they appear, but the codes are also visually insignificant in the sense that a human cannot discern the vendor, brand, or purpose of the code just by looking at it, without the aid of scanning software. Though neither the aesthetics nor the visual significance of the code matter for scanning purposes, they do matter for advertising layout and, more importantly, can provide valuable brand distinction. In this paper, we show how the visually significant QR codes may be obtained by image blending. Unlike various ad-hoc methods that have been proposed by others, our method leaves completely intact the error correction budget of the code. Our method allows images as diverse as corporate logos and family photographs to be embedded in the code in full color. We provide a detailed statistical analysis of the method to show the effect of blending on error rates in noisy environments.",
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"content": "QR Codes (2D barcodes) are used to encode and decode data at a rapid rate. Using camera phones to read two dimensional barcodes for various purposes is currently a popular topic in both research and in practical applications. But until now, the information provided by QR Codes was solely static. What you see is exactly what was encoded. This paper proposes the notion of contextual QR Codes that merge a public QR Code and private information, in order to provide data related to a particular context. For example, a public tag??will be decoded and translated into \"Good evening John Smith\" or \"Bonjour Jean Dupond\", if the system is able to obtain data such as the name of the user, the language used on the machine (English or French for instance) and the moment when the interaction takes place.",
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"abstract": "QR codes have emerged as a popular medium to make content instantly accessible. With their high information density and robust error correction, they have found their way to the mobile ecosystem. However, QR codes have also proven to be an efficient attack vector, e.g. To perform phishing attacks. Attackers distribute malicious codes under false pretenses in busy places or paste malicious QR codes over already existing ones on billboards. Ultimately, people depend on reader software to ascertain if a given QR code is benign or malicious. In this paper, we present a comprehensive analysis of QR code security. We determine why users are still susceptible to QR code based attacks and why currently deployed smartphone apps are unable to mitigate these attacks. Based on our findings, we present a set of design recommendations to build usable and secure mobile applications. To evaluate our guidelines, we implemented a prototype and found that secure and usable apps can effectively protect users from malicious QR codes.",
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"abstract": "QR codes are used for various applications, such as access to web pages and to make a settlement. Although users can visually recognize the existence of the QR codes, they need to use dedicated QR code decoder for reading the stored information in the codes. A malicious one creates a fake QR code by making bad use of this feature and guides users to a malicious web page with a careless operation by the users. However, because fake QR codes always guided to a malicious site, the users detect the fake QR code by looking it at attentively and take measures at an early stage. In this paper, we propose a construction method of fake QR codes which are hard to detect by a characteristic of the error correcting codes. Through evaluation experiments, we clarify the risk of the fake QR codes and call attention to this QR codes.",
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"title": "Detection and Recognition of Deformed Multiple QR Codes Based on SR_ESAGAN Algorithm",
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"abstract": "In the study of detection and recognition of distorted, skewed, and other deformation multi-QR codes using the YOLO_CBAM algorithm, there were problems that the detection effect was poor in the case of stacked QR codes, and the small resolution QR codes couldn't be well recognized. In this paper, we used the Real-ESRGAN model for super-resolution reconstruction of polymorphic QR code images. Combining the characteristics of the multi-QR code dataset, we used 3 convolutional layers to reduce the complexity of image super-resolution processing and replaced the LEAKYRELU activation function in the discriminative network with the GELU function. Then we conducted experiments using the SR_ESAGAN algorithm. Experiments showed that after the improvement, the detection rate and recognition rate of multiple QR codes with deformations were enhanced by 3.71% and 5.27%, respectively, compared to those using only the YOLO_CBAM algorithm.",
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"affiliation": "Beijing Wuzi University,Beijing Key Laboratory of Intelligent Logistics Systems,Beijing,China",
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"affiliation": "Beijing Wuzi University,Beijing Key Laboratory of Intelligent Logistics Systems,Beijing,China",
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"affiliation": "Zhongyuan University of Technology,Zhongyuan-Petersburg Aviation College,Zhengzhou,China,450007",
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"title": "2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)",
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"title": "Deep Restoration of Invisible QR Code from TPVM Display",
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"abstract": "QR (Quick Response) codes are widely used in daily lives for their convenience in conveying information from offline to online. However, black-white QR code image takes up space and is not visually appealing when embedded into videos. Owing to the high resolution and high refresh rates of display screens, we are able to embed QR code to be invisible on displays based on temporal psychovisual modulation (TPVM). In this work, we proposed a method to improve the invisibility of QR code via TPVM. Furthermore, we propose a fast restoration-recognition method to scan invisible QR codes by smartphones using deep convolutional neural networks. Extensive experiment results show that our proposed methods effectively improve the indivisibility of QR code and can efficiently recognize the invisible QR code correctly and stably. Our methods can be applied in video copyright protection and Internet shopping without affecting the visual quality for audiences.",
"abstracts": [
{
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"content": "QR (Quick Response) codes are widely used in daily lives for their convenience in conveying information from offline to online. However, black-white QR code image takes up space and is not visually appealing when embedded into videos. Owing to the high resolution and high refresh rates of display screens, we are able to embed QR code to be invisible on displays based on temporal psychovisual modulation (TPVM). In this work, we proposed a method to improve the invisibility of QR code via TPVM. Furthermore, we propose a fast restoration-recognition method to scan invisible QR codes by smartphones using deep convolutional neural networks. Extensive experiment results show that our proposed methods effectively improve the indivisibility of QR code and can efficiently recognize the invisible QR code correctly and stably. Our methods can be applied in video copyright protection and Internet shopping without affecting the visual quality for audiences.",
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"normalizedAbstract": "QR (Quick Response) codes are widely used in daily lives for their convenience in conveying information from offline to online. However, black-white QR code image takes up space and is not visually appealing when embedded into videos. Owing to the high resolution and high refresh rates of display screens, we are able to embed QR code to be invisible on displays based on temporal psychovisual modulation (TPVM). In this work, we proposed a method to improve the invisibility of QR code via TPVM. Furthermore, we propose a fast restoration-recognition method to scan invisible QR codes by smartphones using deep convolutional neural networks. Extensive experiment results show that our proposed methods effectively improve the indivisibility of QR code and can efficiently recognize the invisible QR code correctly and stably. Our methods can be applied in video copyright protection and Internet shopping without affecting the visual quality for audiences.",
"fno": "09105961",
"keywords": [
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"Data Compression",
"Image Coding",
"Image Colour Analysis",
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"authors": [
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"affiliation": "Shanghai Jiao Tong University,Department of Electronic Engineering,China",
"fullName": "Kaihua Song",
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"affiliation": "Shanghai Jiao Tong University,Department of Electronic Engineering,China",
"fullName": "Ning Liu",
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"affiliation": "Shanghai Jiao Tong University,Department of Electronic Engineering,China",
"fullName": "Zhongpai Gao",
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"affiliation": "Shanghai Jiao Tong University,Department of Electronic Engineering,China",
"fullName": "Jiahe Zhang",
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"affiliation": "Shanghai Jiao Tong University,Department of Electronic Engineering,China",
"fullName": "Guangtao Zhai",
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"affiliation": "Ryerson University,Department of Electrical and Computer Engineering,Toronto,Canada",
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"title": "ArtCoder: An End-to-end Method for Generating Scanning-robust Stylized QR Codes",
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"abstract": "Quick Response (QR) code is one of the most worldwide used two-dimensional codes. Traditional QR codes appear as random collections of black-and-white modules that lack visual semantics and aesthetic elements, which inspires the recent works to beautify the appearances of QR codes. However, these works adopt fixed generation algorithms and therefore can only generate QR codes with a pre-defined style. In this paper, combining the Neural Style Transfer technique, we propose a novel end-to-end method, named ArtCoder, to generate the stylized QR codes that are personalized, diverse, attractive, and scanning-robust. To guarantee that the generated stylized QR codes are still scanning-robust, we propose a Sampling-Simulation layer, a module-based code loss, and a competition mechanism. The experimental results show that our stylized QR codes have high-quality in both the visual effect and the scanning-robustness, and they are able to support the real-world application.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Quick Response (QR) code is one of the most worldwide used two-dimensional codes. Traditional QR codes appear as random collections of black-and-white modules that lack visual semantics and aesthetic elements, which inspires the recent works to beautify the appearances of QR codes. However, these works adopt fixed generation algorithms and therefore can only generate QR codes with a pre-defined style. In this paper, combining the Neural Style Transfer technique, we propose a novel end-to-end method, named ArtCoder, to generate the stylized QR codes that are personalized, diverse, attractive, and scanning-robust. To guarantee that the generated stylized QR codes are still scanning-robust, we propose a Sampling-Simulation layer, a module-based code loss, and a competition mechanism. The experimental results show that our stylized QR codes have high-quality in both the visual effect and the scanning-robustness, and they are able to support the real-world application.",
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"normalizedAbstract": "Quick Response (QR) code is one of the most worldwide used two-dimensional codes. Traditional QR codes appear as random collections of black-and-white modules that lack visual semantics and aesthetic elements, which inspires the recent works to beautify the appearances of QR codes. However, these works adopt fixed generation algorithms and therefore can only generate QR codes with a pre-defined style. In this paper, combining the Neural Style Transfer technique, we propose a novel end-to-end method, named ArtCoder, to generate the stylized QR codes that are personalized, diverse, attractive, and scanning-robust. To guarantee that the generated stylized QR codes are still scanning-robust, we propose a Sampling-Simulation layer, a module-based code loss, and a competition mechanism. The experimental results show that our stylized QR codes have high-quality in both the visual effect and the scanning-robustness, and they are able to support the real-world application.",
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"Bar Codes",
"Neural Nets",
"QR Codes",
"Generating Scanning Robust Stylized QR Codes",
"Response Code",
"Two Dimensional Codes",
"Traditional QR Codes",
"End To End Method",
"Module Based Code Loss",
"Scanning Robustness",
"Art Coder",
"Visual Semantics",
"Aesthetic Elements",
"Computer Vision",
"Codes",
"Semantics",
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"Visual Effects",
"Pattern Recognition"
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"authors": [
{
"affiliation": "Beihang University,State Key Lab of VR Technology and System, School of Computer Science and Engineering",
"fullName": "Hao Su",
"givenName": "Hao",
"surname": "Su",
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"affiliation": "Beihang University,State Key Lab of VR Technology and System, School of Computer Science and Engineering",
"fullName": "Jianwei Niu",
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"surname": "Niu",
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{
"affiliation": "Beihang University,State Key Lab of VR Technology and System, School of Computer Science and Engineering",
"fullName": "Xuefeng Liu",
"givenName": "Xuefeng",
"surname": "Liu",
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{
"affiliation": "Beihang University,State Key Lab of VR Technology and System, School of Computer Science and Engineering",
"fullName": "Qingfeng Li",
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"affiliation": "Beihang University,State Key Lab of VR Technology and System, School of Computer Science and Engineering",
"fullName": "Ji Wan",
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"affiliation": "Zhengzhou University,Industrial Technology Research Institute, School of Information Engineering",
"fullName": "Mingliang Xu",
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{
"affiliation": "Beihang University,State Key Lab of VR Technology and System, School of Computer Science and Engineering",
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"surname": "Ren",
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"title": "2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)",
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"title": "RPPC: A Holistic Runtime System for Maximizing Performance Under Power Capping",
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"abstract": "Maximizing performance in power-constrained computing environments is highly important in cloud and datacenter computing. To achieve the best possible performance of parallel applications under power capping, it is crucial to execute them with the optimal concurrency level and cross-component power allocation between CPUs and memory. Despite extensive prior works, it still remains unexplored to investigate the efficient runtime support that maximizes the performance of parallel applications under power capping through the coordinated control of concurrency level and cross-component power allocation. To bridge this gap, this work proposes RPPC, a holistic runtime system for maximizing performance under power capping. In contrast to the state-of-the-art techniques, RPPC robustly controls the two performance-critical knobs (i.e., concurrency level and cross-component power allocation) in a coordinated manner to maximize the performance of parallel applications under power capping. RPPC dynamically identifies the characteristics of the target parallel application and explores the system state space to find an efficient system state. Our experimental results demonstrate that RPPC significantly outperforms the two state-of-the-art power-capping techniques, achieves the performance comparable with the static best version that requires extensive per-application offline profiling, incurs small performance overheads, and provides the re-adaptation mechanism to external events such as total power budget changes.",
"abstracts": [
{
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"content": "Maximizing performance in power-constrained computing environments is highly important in cloud and datacenter computing. To achieve the best possible performance of parallel applications under power capping, it is crucial to execute them with the optimal concurrency level and cross-component power allocation between CPUs and memory. Despite extensive prior works, it still remains unexplored to investigate the efficient runtime support that maximizes the performance of parallel applications under power capping through the coordinated control of concurrency level and cross-component power allocation. To bridge this gap, this work proposes RPPC, a holistic runtime system for maximizing performance under power capping. In contrast to the state-of-the-art techniques, RPPC robustly controls the two performance-critical knobs (i.e., concurrency level and cross-component power allocation) in a coordinated manner to maximize the performance of parallel applications under power capping. RPPC dynamically identifies the characteristics of the target parallel application and explores the system state space to find an efficient system state. Our experimental results demonstrate that RPPC significantly outperforms the two state-of-the-art power-capping techniques, achieves the performance comparable with the static best version that requires extensive per-application offline profiling, incurs small performance overheads, and provides the re-adaptation mechanism to external events such as total power budget changes.",
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"normalizedAbstract": "Maximizing performance in power-constrained computing environments is highly important in cloud and datacenter computing. To achieve the best possible performance of parallel applications under power capping, it is crucial to execute them with the optimal concurrency level and cross-component power allocation between CPUs and memory. Despite extensive prior works, it still remains unexplored to investigate the efficient runtime support that maximizes the performance of parallel applications under power capping through the coordinated control of concurrency level and cross-component power allocation. To bridge this gap, this work proposes RPPC, a holistic runtime system for maximizing performance under power capping. In contrast to the state-of-the-art techniques, RPPC robustly controls the two performance-critical knobs (i.e., concurrency level and cross-component power allocation) in a coordinated manner to maximize the performance of parallel applications under power capping. RPPC dynamically identifies the characteristics of the target parallel application and explores the system state space to find an efficient system state. Our experimental results demonstrate that RPPC significantly outperforms the two state-of-the-art power-capping techniques, achieves the performance comparable with the static best version that requires extensive per-application offline profiling, incurs small performance overheads, and provides the re-adaptation mechanism to external events such as total power budget changes.",
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"affiliation": null,
"fullName": "Jinsu Park",
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"affiliation": null,
"fullName": "Woongki Baek",
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"title": "Interactive Runtime Verification — When Interactive Debugging Meets Runtime Verification",
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"abstract": "Runtime Verification consists in studying a system at runtime, looking for input and output events to discover, check or enforce behavioral properties. Interactive debugging consists in studying a system at runtime in order to discover and understand its bugs and fix them, inspecting interactively its internal state.Interactive Runtime Verification (i-RV) combines runtime verification and interactive debugging. We define an efficient and convenient way to check behavioral properties automatically on a program using a debugger. We aim at helping bug discovery and understanding by guiding classical interactive debugging techniques using runtime verification.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Runtime Verification consists in studying a system at runtime, looking for input and output events to discover, check or enforce behavioral properties. Interactive debugging consists in studying a system at runtime in order to discover and understand its bugs and fix them, inspecting interactively its internal state.Interactive Runtime Verification (i-RV) combines runtime verification and interactive debugging. We define an efficient and convenient way to check behavioral properties automatically on a program using a debugger. We aim at helping bug discovery and understanding by guiding classical interactive debugging techniques using runtime verification.",
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"normalizedAbstract": "Runtime Verification consists in studying a system at runtime, looking for input and output events to discover, check or enforce behavioral properties. Interactive debugging consists in studying a system at runtime in order to discover and understand its bugs and fix them, inspecting interactively its internal state.Interactive Runtime Verification (i-RV) combines runtime verification and interactive debugging. We define an efficient and convenient way to check behavioral properties automatically on a program using a debugger. We aim at helping bug discovery and understanding by guiding classical interactive debugging techniques using runtime verification.",
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"Program Debugging",
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"affiliation": null,
"fullName": "Raphaël Jakse",
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"affiliation": null,
"fullName": "Yliès Falcone",
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"affiliation": null,
"fullName": "Jean-François Méhaut",
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"abstract": "Many games are populated by synthetic humanoid actors that act as autonomous agents. The animation of humanoids in real-time applications is yet a challenge if the problem involves attaining a precise location in a virtual world (path-planning), and moving realistically according to its own personality, intentions and mood (motion planning). In this paper we present a strategy to implement – using CUDA on GPU – a path planner that produces natural steering behaviors for virtual humans using a numerical solution for boundary value problems. The planner is based on the potential field formalism that allows synthetic actors to move negotiating space, avoiding collisions, and attaining goals, while producing very individual paths. The individuality of each character can be set by changing its inner field parameters leading to a broad range of possible behaviors without jeopardizing its performance. With our GPU-based strategy we achieve a speed up to 56 times the previous implementation, allowing its use in situations with a large number of autonomous characters, which is commonly found in games.",
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"abstract": "In wireless sensor networks (WSNs), data can be subject to malicious attacks and failures, leading to unreliability. This vulnerability poses a challenge to environmental monitoring applications by creating false alarms. To guarantee a trustworthy system, we therefore need to detect abnormal nodes. In this paper, we propose a new framework for detecting abnormal nodes in clustered heterogeneous WSNs. It makes use of observed spatiotemporal (ST) and multivariate-attribute (MVA) sensor correlations, while considering the background knowledge of the monitored environment. Based on the ST correlations, the collected data is analyzed by computing the crosscorrelation between sensor streams. A new method is proposed for evaluating the intensity of the correlation between two sensor streams. The crosscorrelation value obtained is compared against two thresholds, the lag threshold and the correlation threshold. Based on available background knowledge and the observed MVA correlations, a number of rules are presented to detect abnormal nodes while identifying real events. Our experiments on real-world sensor data demonstrate that our approach captures the correlation and discovers abnormal nodes efficiently.",
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"abstract": "Multivariate time series (MTS) classification has been regarded as one of the most challenging problems in data mining due to the difficulty in modeling the correlation of variables and samples. In addition, high-dimensional MTS modeling has a large time and space consumption. This paper proposes a novel method, Gaussian Model-based Fully Convolutional Networks (GM-FCN), to improve the performance of high-dimensional MTS classification. Each original MTS is converted into multivariate Gaussian model parameters as the input of FCN. These parameters effectively capture the correlation be-tween MTS variables and significantly reduce the data scale by aligning an MTS size to its dimension. FCN is designed to learn more in-depth features of MTS based on these parameters for modeling the correlation between samples. Thus, GM-FCN can not only model the correlation between variables, but also the correlation between samples. We compare GM-FCN with nine state-of-the-art MTS classification methods, INN-ED, INN-DTW-i, INN-DTW-D, KLD-GMC, MLP, ResNet, Encoder, MCNN, and MCDCNN, on four high-dimensional public datasets, experimen-tal results show that the accuracy of G M - FCN is significantly superior to the others. Besides, the training time of GM-FCN is dozens of times faster than FCN using the original equal-length MTS data as input.",
"abstracts": [
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"content": "Multivariate time series (MTS) classification has been regarded as one of the most challenging problems in data mining due to the difficulty in modeling the correlation of variables and samples. In addition, high-dimensional MTS modeling has a large time and space consumption. This paper proposes a novel method, Gaussian Model-based Fully Convolutional Networks (GM-FCN), to improve the performance of high-dimensional MTS classification. Each original MTS is converted into multivariate Gaussian model parameters as the input of FCN. These parameters effectively capture the correlation be-tween MTS variables and significantly reduce the data scale by aligning an MTS size to its dimension. FCN is designed to learn more in-depth features of MTS based on these parameters for modeling the correlation between samples. Thus, GM-FCN can not only model the correlation between variables, but also the correlation between samples. We compare GM-FCN with nine state-of-the-art MTS classification methods, INN-ED, INN-DTW-i, INN-DTW-D, KLD-GMC, MLP, ResNet, Encoder, MCNN, and MCDCNN, on four high-dimensional public datasets, experimen-tal results show that the accuracy of G M - FCN is significantly superior to the others. Besides, the training time of GM-FCN is dozens of times faster than FCN using the original equal-length MTS data as input.",
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"abstract": "Today's HPC applications are producing extremely large amounts of data, such that data storage and analysis are becoming more challenging for scientific research. In this work, we design a new error-controlled lossy compression algorithm for large-scale scientific data. Our key contribution is significantly improving the prediction hitting rate (or prediction accuracy) for each data point based on its nearby data values along multiple dimensions. We derive a series of multilayer prediction formulas and their unified formula in the context of data compression. One serious challenge is that the data prediction has to be performed based on the preceding decompressed values during the compression in order to guarantee the error bounds, which may degrade the prediction accuracy in turn. We explore the best layer for the prediction by considering the impact of compression errors on the prediction accuracy. Moreover, we propose an adaptive error-controlled quantization encoder, which can further improve the prediction hitting rate considerably. The data size can be reduced significantly after performing the variable-length encoding because of the uneven distribution produced by our quantization encoder. We evaluate the new compressor on production scientific data sets and compare it with many other state-of-the-art compressors: GZIP, FPZIP, ZFP, SZ-1.1, and ISABELA. Experiments show that our compressor is the best in class, especially with regard to compression factors (or bit-rates) and compression errors (including RMSE, NRMSE, and PSNR). Our solution is better than the second-best solution by more than a 2x increase in the compression factor and 3.8x reduction in the normalized root mean squared error on average, with reasonable error bounds and user-desired bit-rates.",
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