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"abstract": "Cybersecurity exercises are gaining in popularity in university curricula and professional training paths and are seen as an effective teaching method. Such exercises provide digital datasets to facilitate a learning analytics approach such as by using the traces that learners leave behind to improve the learning process and environment. While there are various learning measurement efforts from digital datasets in the existing literature, a holistic learning analytics approach incorporated into cybersecurity exercises is still lacking. We propose a practical reference model for incorporating a learning analytics approach into the cybersecurity exercise life-cycle. To facilitate this application, we have performed an extensive review of existing academic research on applying learning analytics in the context of cybersecurity exercises. We specifically focus on the learning indicators used to measure empirical impact and training effectiveness that could indicate achievement of defined learning outcomes. This reference model and overview of existing learning analytics use cases and learning metrics in various types of exercises can help educators, organisers and cyber range developers. This results in more adaptive exercise design and measurement using evidence-based data and connects digital learning traces to skills and competencies.",
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"content": "Cybersecurity exercises are gaining in popularity in university curricula and professional training paths and are seen as an effective teaching method. Such exercises provide digital datasets to facilitate a learning analytics approach such as by using the traces that learners leave behind to improve the learning process and environment. While there are various learning measurement efforts from digital datasets in the existing literature, a holistic learning analytics approach incorporated into cybersecurity exercises is still lacking. We propose a practical reference model for incorporating a learning analytics approach into the cybersecurity exercise life-cycle. To facilitate this application, we have performed an extensive review of existing academic research on applying learning analytics in the context of cybersecurity exercises. We specifically focus on the learning indicators used to measure empirical impact and training effectiveness that could indicate achievement of defined learning outcomes. This reference model and overview of existing learning analytics use cases and learning metrics in various types of exercises can help educators, organisers and cyber range developers. This results in more adaptive exercise design and measurement using evidence-based data and connects digital learning traces to skills and competencies.",
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"abstract": "Supervised Capture the Flag games represent a popular method of practical hands-on training in cybersecurity education. However, as cybersecurity training sessions are process-oriented, tutors have only a limited insight into what trainees are doing and how they deal with the tasks. From their perspective, it is necessary to have situational awareness, enabling them to identify and react to any issues during a training session as soon as they emerge. We propose a tool designed in collaboration with cybersecurity educators. Based on user requirements, we developed the Progress Visualization Tool, which provides educators with timely feedback through the session. More specifically, the tool informs educators of the training progression, helps identify the students who might struggle with their tasks, and reveals overall deviation from the schedule. We validated the tool through formative and summative qualitative in-lab evaluations. The participants appraised the impact on the training workflow and gave further insights regarding the tool. We discuss the insights and recommendations that arose from the evaluations as they could aid the design of future tools for supporting educators, not only of CTFs but also in other domains.",
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"abstract": "Automatic 3D extraction of building roofs from remotely sensed data is important for many applications including city modeling. This paper proposes a new method for automatic 3D roof extraction through an effective integration of LIDAR (Light Detection And Ranging) data and multispectral orthoimagery. Using the ground height from a DEM (Digital Elevation Model), the raw LIDAR points are separated into two groups. The first group contains the ground points that are exploited to constitute a ‘ground mask’. The second group contains the non-ground points which are segmented using an innovative image line guided segmentation technique to extract the roof planes. The image lines extracted from the grey-scale version of the orthoimage are classified into several classes such as ‘ground’, ‘tree’, ‘roof edge’ and ‘roof ridge’ using the ground mask and colour and texture information from the orthoimagery. During roof plane extraction the lines from the later two classes are used to fit roof planes to the neighbouring non-ground LIDAR points. Finally, a new rule-based procedure is applied to remove planes constructed on trees. Experimental results show that the proposed method successfully removes vegetation and offers high extraction rates.",
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"abstract": "One of the most promising emerging 3D representation paradigms is the point cloud (PC) model, notably due to the new set of applications that it enables, from immersive telepresence to 3D geographic information systems. Recognizing the potential of this representation model, MPEG has launched a standardization project to specify efficient PC coding solutions. This project has led to the so-called Video-based Point Cloud Coding (V-PCC) standard, which is based on the idea of projecting the dynamic PC geometry and texture into a sequence of frames to be coded with the highly efficient HEVC video coding standard. In V-PCC, the projection of points and color attributes is always performed using the same, rigid set of projection planes, independently of the PC characteristics. This paper proposes a more flexible coding solution, which improves the V-PCC Intra coding mode by adopting a content dependent set of projection planes, thus, more adapted to the characteristics of the PCs to be coded, targeting a better compression performance. The experimental results show an average total bitrate saving of around 15% regarding V-PCC with clear benefits in terms of subjective assessment.",
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"content": "One of the most promising emerging 3D representation paradigms is the point cloud (PC) model, notably due to the new set of applications that it enables, from immersive telepresence to 3D geographic information systems. Recognizing the potential of this representation model, MPEG has launched a standardization project to specify efficient PC coding solutions. This project has led to the so-called Video-based Point Cloud Coding (V-PCC) standard, which is based on the idea of projecting the dynamic PC geometry and texture into a sequence of frames to be coded with the highly efficient HEVC video coding standard. In V-PCC, the projection of points and color attributes is always performed using the same, rigid set of projection planes, independently of the PC characteristics. This paper proposes a more flexible coding solution, which improves the V-PCC Intra coding mode by adopting a content dependent set of projection planes, thus, more adapted to the characteristics of the PCs to be coded, targeting a better compression performance. The experimental results show an average total bitrate saving of around 15% regarding V-PCC with clear benefits in terms of subjective assessment.",
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"abstract": "Summary form only given, as follows. A complete record of the panel discussion was not made available for publication as part of the conference proceedings but each of the five participants provides an abstract of their views. The field of ethics is concerned with the study of the concepts of right and wrong behavior, and generally involves three broad subject areas: metaethics, normative ethics, and applied ethics. Metaethics investigates where our ethical principles come from, and what they mean; normative ethics refer to our study and determination of moral standards that regulate right and wrong conduct; while applied ethics involves the examination of specific controversial issues such as abortion, animal rights, and environmental concerns. In this panel, we will identify and discuss ethics issues as they apply to a number of emergent challenges in the design and development of intelligence analysis systems, as well as during day-to-day operations of law enforcement and military officers. In many discussions on ethics, there is a tendency for the discussions to remain at a high level and surround the main principles of ethics, e.g., respect for autonomy, non-maleficence or do no harm, beneficence, and justice (Beauchamp & Childress, 2013). In this panel, we present some concrete problems that emerged through our research in projects such as the FP7 VALCRI, as we seek to respect the rights of European citizens to liberty and security. These problems include the mosaic effect, protection of personal data, potential misuse and abuse during information exploitation and analysis activities encountered during intelligence and investigative analysis. How should we design to ensure computational and analytic transparency in the decision making processes? How do we design systems and processes that are visible and open to inspection by colleagues and overseers? These are some issues that will be addressed by this Panel.",
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"abstract": "In this paper we address the problem of distributing rendering computations for real-time display of very large 3D models using a graphics cluster. With a programmable graphics processing unit (GPU) in each node, rendering computations are increasingly carried out in two phases using two separate GPU programs: a vertex shader program for vertex (geometry) processing and a fragment shader program for pixel (color) processing. With fragment shader programs becoming more and more time consuming for increased realism and special visual effects, distributing load solely based on geometry as is done in most contemporary systems can cause significant load imbalance. There is often only a weak correlation between geometry and pixel data distribution, due to multiple factors such as occlusion of objects behind, by objects in front. Clearly, load balancing for geometry processing or pixel processing alone is not optimal. In this paper, we present a novel in-frame two-phase load-balancing technique that distributes data first for geometry and then for pixel processing. The technique is implemented on a graphics cluster and experimental results demonstrate considerable improvements in rendering performance.",
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"affiliation": "Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada",
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"content": "Software is modularized to make its high complexity manageable. However, a multitude of modularization criteria exists and is applied. Hence, to extend, reuse, or restructure a system, it is important for developers to understand which criteria have been used. To this end, we provide an interactive visualization approach that compares the current modularization of a system to several software clustering results. The visualization is based on juxtaposed icicle plot representations of the hierarchical modularizations, encoding similarity by color. A detailed comparison is facilitated by an advanced selection concept. Coupling graphs, which form the basis for software clustering, can be explored on demand in matrix representations. We discuss typical modularization patterns that indicate criteria used for structuring the software or suggest opportunities for partial remodularization of the system. We apply the approach to analyze 16 open source Java projects. The results show that identifying those modularization patterns provides valuable insights and can be done efficiently.",
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"abstract": "Online Distance Education (ODE) provides massive course videos of various specialties for students across the country to learn professional knowledge anytime and anywhere. Analyzing the utilization of these videos from user log data can help academics better understand the learning process of students, evaluate the quality of service provided by regional learning centers, and improve the quality of program curriculum in the future. However, due to the lack of comparable indicators, it is a great challenge to discover the utilization patterns of massive videos and analyze the learning process of large-scale student population from learning log data. In this paper, we introduce a visual analytics system, called VUSphere, to explore the video utilization from multiple perspectives with two proposed indicators. This system offers three coordinated views: a spherical layout overview to depict the overall utilization distribution of videos, courses, and students; a detailed statistics view with four panels to present video utilization statistics of each element from multiple perspectives; and a comparison view to examine the differences in individual elements. Based on the real dataset from our ODE school, several patterns related to video utilization and enrollment are found in the case study with our domain experts.",
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"content": "Online Distance Education (ODE) provides massive course videos of various specialties for students across the country to learn professional knowledge anytime and anywhere. Analyzing the utilization of these videos from user log data can help academics better understand the learning process of students, evaluate the quality of service provided by regional learning centers, and improve the quality of program curriculum in the future. However, due to the lack of comparable indicators, it is a great challenge to discover the utilization patterns of massive videos and analyze the learning process of large-scale student population from learning log data. In this paper, we introduce a visual analytics system, called VUSphere, to explore the video utilization from multiple perspectives with two proposed indicators. This system offers three coordinated views: a spherical layout overview to depict the overall utilization distribution of videos, courses, and students; a detailed statistics view with four panels to present video utilization statistics of each element from multiple perspectives; and a comparison view to examine the differences in individual elements. Based on the real dataset from our ODE school, several patterns related to video utilization and enrollment are found in the case study with our domain experts.",
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"title": "2020 IEEE Pacific Visualization Symposium (PacificVis)",
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"abstract": "Hierarchical structures are very common in the real world for recording all kinds of relational data generated in our daily life and business procedures. A very popular visualization method for displaying such data structures is called \"Tree\". So far, there are a variety of Tree visualization methods that have been proposed and most of them can only visualize one hierarchical dataset at a time. Hence, it raises the difficulty of comparison between two or more hierarchical datasets.In this paper, we proposed Pansy Tree which used a tree metaphor to visualize merged hierarchies. We design a unique icon named pansy to represent each merged node in the structure. Each Pansy is encoded by three colors mapping data items from three different datasets in the same hierarchical position (or tree node). The petals and sepal on Pansy are designed for showing each attribute’s values and hierarchical information. We also redefine the links in force layout encoded by width and animation to better convey hierarchical information. We further apply Pansy Tree into CNCEE datasets and demonstrate two use cases to verify its effectiveness.The main contribution of this work is to merge three datasets into one tree that makes it much easier to explore and compare the structures, data items and data attributes with visual tools.",
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"content": "Hierarchical structures are very common in the real world for recording all kinds of relational data generated in our daily life and business procedures. A very popular visualization method for displaying such data structures is called \"Tree\". So far, there are a variety of Tree visualization methods that have been proposed and most of them can only visualize one hierarchical dataset at a time. Hence, it raises the difficulty of comparison between two or more hierarchical datasets.In this paper, we proposed Pansy Tree which used a tree metaphor to visualize merged hierarchies. We design a unique icon named pansy to represent each merged node in the structure. Each Pansy is encoded by three colors mapping data items from three different datasets in the same hierarchical position (or tree node). The petals and sepal on Pansy are designed for showing each attribute’s values and hierarchical information. We also redefine the links in force layout encoded by width and animation to better convey hierarchical information. We further apply Pansy Tree into CNCEE datasets and demonstrate two use cases to verify its effectiveness.The main contribution of this work is to merge three datasets into one tree that makes it much easier to explore and compare the structures, data items and data attributes with visual tools.",
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"affiliation": "University of Technology,Sydney",
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"normalizedAbstract": "Recent popularization of HMD devices (such as the Oculus Rift, Samsung VR, and the HTC Vive) has shed light into mitigating traditional restrictions of high end devices, bringing attention again to virtual reality and novel possibilities for games and entertainment applications. The advancement of virtual reality technologies and context-awareness give rise to new game genres such as \"live-action virtual reality games\", which we proposed in previous works. Live-action virtual reality games create a kind of \"augmented virtuality\" – a mixed-reality where the virtual world is augmented with real-world information. In these games, players wear HMD devices and see a virtual world that is constructed using the physical world architecture as the basic geometry and context information. Physical objects that reside in the physical world are also mapped to virtual elements. Live-action virtual reality games keep the virtual and real-worlds superimposed, requiring players to physically move in the environment and to use different interaction paradigms (such as tangible & embodied interaction) to complete game activities. This setup enables the players to touch physical architectural elements (such as walls) and other objects, \"feeling\" the mixed-reality environment. We propose an architecture that implements a low cost system for live-action virtual reality games that addresses indoor navigation and tracking of physical elements, providing good results due to its accuracy. The system is based on infrared markers, enabling it to operate in the spectral infrared region to work with low optical noise and better precision when compared to solutions based on fiducial markers. Furthermore, this paper describes our system and presents two case studies based on our architecture.",
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"abstract": "Several critical limitations exist in the currently available tracking technologies for fully-enclosed virtual reality (VR) systems. While several 6DOF tracking projects such as Hedgehog [24] have successfully demonstrated excellent accuracy, precision, and robustness within moderate budgets, these projects still include elements of hardware that can interfere with the user's visual experience. The objective of this project is to design a tracking solution for fully-enclosed VR displays that achieves comparable performance to available commercial solutions but without any artifacts that can obscure the user's view. JanusVF is a tracking solution involving a cooperation of both the hardware sensors and the software rendering system. A small, high-resolution camera is worn on the user's head, but faces backwards (180 degree rotation about vertical from the user's perspective). After acquisition of the initial state, the VR rendering software draws specific fiducial markers with known size and absolute position inside the VR scene. These virtual markers are only drawn behind the user and in view of the camera. These fiducials are tracked by ARToolkitPlus [25] and integrated by a single-constraint-at-a-time (SCAAT) [26] filter algorithm to update the head pose. Early experiments in a six-sided CAVE-like system show performance that is comparable to alternative commercial technologies.",
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"abstract": "Children with Autism Spectrum Disorders (ASD) exhibit a range of developmental disabilities, with mild to severe effects in social interaction and communication. Children with PDD-NOS, Autism and co-existing conditions are facing enormous challenges in their lives, dealing with their difficulties in sensory perception, repetitive behaviors and interests. These challenges result in them being less independent or not independent at all. Part of becoming independent involves being able to function in real world settings, settings that are not controlled. Pedestrian crossings fall under this category: as children (and later as adults) they have to learn to cross roads safely. In this paper, we report on a study we carried out with 6 children with PDD-NOS over a period of four (4) days using a VR CAVE virtual environment to teach them how to safely cross at a pedestrian crossing. Results indicated that most children were able to achieve the desired goal of learning the task, which was verified in the end of the 4-day period by having them cross a real pedestrian crossing (albeit with their parent/educator discretely next to them for safety reasons).",
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"content": "Children with Autism Spectrum Disorders (ASD) exhibit a range of developmental disabilities, with mild to severe effects in social interaction and communication. Children with PDD-NOS, Autism and co-existing conditions are facing enormous challenges in their lives, dealing with their difficulties in sensory perception, repetitive behaviors and interests. These challenges result in them being less independent or not independent at all. Part of becoming independent involves being able to function in real world settings, settings that are not controlled. Pedestrian crossings fall under this category: as children (and later as adults) they have to learn to cross roads safely. In this paper, we report on a study we carried out with 6 children with PDD-NOS over a period of four (4) days using a VR CAVE virtual environment to teach them how to safely cross at a pedestrian crossing. Results indicated that most children were able to achieve the desired goal of learning the task, which was verified in the end of the 4-day period by having them cross a real pedestrian crossing (albeit with their parent/educator discretely next to them for safety reasons).",
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"normalizedAbstract": "Children with Autism Spectrum Disorders (ASD) exhibit a range of developmental disabilities, with mild to severe effects in social interaction and communication. Children with PDD-NOS, Autism and co-existing conditions are facing enormous challenges in their lives, dealing with their difficulties in sensory perception, repetitive behaviors and interests. These challenges result in them being less independent or not independent at all. Part of becoming independent involves being able to function in real world settings, settings that are not controlled. Pedestrian crossings fall under this category: as children (and later as adults) they have to learn to cross roads safely. In this paper, we report on a study we carried out with 6 children with PDD-NOS over a period of four (4) days using a VR CAVE virtual environment to teach them how to safely cross at a pedestrian crossing. Results indicated that most children were able to achieve the desired goal of learning the task, which was verified in the end of the 4-day period by having them cross a real pedestrian crossing (albeit with their parent/educator discretely next to them for safety reasons).",
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"title": "2020 International Conference on Virtual Reality and Visualization (ICVRV)",
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"title": "The Research and Realization of VR for The School-based Textbooks of school for the Mentally Retarded",
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"abstract": "Education has always been the focus of national attention, and special children education is a very important part of the education industry. Traditional education forms lack interest and immersion, making it difficult for these special children to truly understand a piece of knowledge. With the development of science and technology, virtual reality (VR) technology has entered people's field of vision, and “VR + education” has become the focus of attention. This article focuses on special children with intellectual deficiencies, and uses the characteristics of VR to design an educational VR software system that is easy for students to understand. Using C# language to write programs to achieve human-computer interaction, two virtual scenes with a high degree of realistic reproduction were created through Unity3D. In the scenes, there are four classes: math class, Chinese class, English class and life class. It also has an examination function and gives feedback on the results of the examination. The software system has a good feedback mechanism, which allows teachers and parents to understand the children's learning situation in time. The system can complete a series of complex human-computer interaction functions, truly combine virtual and reality, relieve fatigue through children's physical or psychological transfer behavior, and help children truly achieve efficient learning.",
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"content": "Education has always been the focus of national attention, and special children education is a very important part of the education industry. Traditional education forms lack interest and immersion, making it difficult for these special children to truly understand a piece of knowledge. With the development of science and technology, virtual reality (VR) technology has entered people's field of vision, and “VR + education” has become the focus of attention. This article focuses on special children with intellectual deficiencies, and uses the characteristics of VR to design an educational VR software system that is easy for students to understand. Using C# language to write programs to achieve human-computer interaction, two virtual scenes with a high degree of realistic reproduction were created through Unity3D. In the scenes, there are four classes: math class, Chinese class, English class and life class. It also has an examination function and gives feedback on the results of the examination. The software system has a good feedback mechanism, which allows teachers and parents to understand the children's learning situation in time. The system can complete a series of complex human-computer interaction functions, truly combine virtual and reality, relieve fatigue through children's physical or psychological transfer behavior, and help children truly achieve efficient learning.",
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"affiliation": "College of Computer Science and Technology Changchun University,Changchun,China",
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"affiliation": "College of Computer Science and Technology Changchun University,Changchun,China",
"fullName": "Lele Wang",
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"title": "Venetian Blind Control System Based on Fuzzy Neural Network for Indoor Daylighting",
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"abstract": "For the indoor daylighting need, venetian blinds are a key element in the passive control of building's vision environment. They help to control glare, daylighting, and overheating, all of which affect both the comfort of occupants and a building's energy saving. Especially, for the indoor shading and daylighting requirement, the smart control system, which has both function of adjusting the venetian blind position intellectively and indoor lighting control automatically, is built depending on fuzzy neural network in this paper. The venetia blind angle feedback control technology is also used in this system for the blind position self-adaptive control., and in addition, the relation model between the venetian blind shading angle and the visibility for occupants is established as well as fuzzy neural network model for calculating venetian blind operation angle. The theory arithmetic for control and main segments in this system are discussed too. The conclusion is presented that the optimal angle of venetian blind operation can be accurately controlled, and the position is changeable to sun position under condition of indoor visual comfort.",
"abstracts": [
{
"abstractType": "Regular",
"content": "For the indoor daylighting need, venetian blinds are a key element in the passive control of building's vision environment. They help to control glare, daylighting, and overheating, all of which affect both the comfort of occupants and a building's energy saving. Especially, for the indoor shading and daylighting requirement, the smart control system, which has both function of adjusting the venetian blind position intellectively and indoor lighting control automatically, is built depending on fuzzy neural network in this paper. The venetia blind angle feedback control technology is also used in this system for the blind position self-adaptive control., and in addition, the relation model between the venetian blind shading angle and the visibility for occupants is established as well as fuzzy neural network model for calculating venetian blind operation angle. The theory arithmetic for control and main segments in this system are discussed too. The conclusion is presented that the optimal angle of venetian blind operation can be accurately controlled, and the position is changeable to sun position under condition of indoor visual comfort.",
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"normalizedAbstract": "For the indoor daylighting need, venetian blinds are a key element in the passive control of building's vision environment. They help to control glare, daylighting, and overheating, all of which affect both the comfort of occupants and a building's energy saving. Especially, for the indoor shading and daylighting requirement, the smart control system, which has both function of adjusting the venetian blind position intellectively and indoor lighting control automatically, is built depending on fuzzy neural network in this paper. The venetia blind angle feedback control technology is also used in this system for the blind position self-adaptive control., and in addition, the relation model between the venetian blind shading angle and the visibility for occupants is established as well as fuzzy neural network model for calculating venetian blind operation angle. The theory arithmetic for control and main segments in this system are discussed too. The conclusion is presented that the optimal angle of venetian blind operation can be accurately controlled, and the position is changeable to sun position under condition of indoor visual comfort.",
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"keywords": [
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"Feedback",
"Fuzzy Control",
"Fuzzy Neural Nets",
"Neurocontrollers",
"Position Control",
"Self Adjusting Systems",
"Venetian Blind Control System",
"Fuzzy Neural Network",
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"Lighting Control",
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{
"affiliation": "Coll. of Inf. & Electr. Eng., China Agric. Univ., Beijing, China",
"fullName": "Yifei Chen",
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"affiliation": "Coll. of Inf. & Electr. Eng., China Agric. Univ., Beijing, China",
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"affiliation": "Coll. of Inf. & Electr. Eng., China Agric. Univ., Beijing, China",
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"title": "Multi-objective optimization of energy and daylighting performance of township street house in western Guangdong, China",
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"abstract": "With the development of township economy in Guangdong, a large number of street houses have been built. The requirements of township residents for the quality of living environment are constantly improving, and the energy performance of street houses is becoming increasingly prominent. The research goal is to promote the scientific design of township street houses in western Guangdong, reduce the building energy performance of township street houses and improve daylighting quality. This study investigated 18 township in Xinyi City, Guangdong Province, and summarized the characteristics of street houses in typical township. According to the survey results, Rhino-Grasshopper is used to build a benchmark model, which comprehensively considers the performance of buildings in energy and daylighting. Virtual simulation is carried out by EnergyPlus and Radiance engine, and then multi-objective optimization is carried out by Pareto method to find the optimal solution of energy and daylight performance, and to provide the recommended values of design variables. The results show that the selection of appropriate building materials and structures is of great significance to the optimization of energy performance, and the selection of window-wall ratio is the focus of daylighting environment optimization.",
"abstracts": [
{
"abstractType": "Regular",
"content": "With the development of township economy in Guangdong, a large number of street houses have been built. The requirements of township residents for the quality of living environment are constantly improving, and the energy performance of street houses is becoming increasingly prominent. The research goal is to promote the scientific design of township street houses in western Guangdong, reduce the building energy performance of township street houses and improve daylighting quality. This study investigated 18 township in Xinyi City, Guangdong Province, and summarized the characteristics of street houses in typical township. According to the survey results, Rhino-Grasshopper is used to build a benchmark model, which comprehensively considers the performance of buildings in energy and daylighting. Virtual simulation is carried out by EnergyPlus and Radiance engine, and then multi-objective optimization is carried out by Pareto method to find the optimal solution of energy and daylight performance, and to provide the recommended values of design variables. The results show that the selection of appropriate building materials and structures is of great significance to the optimization of energy performance, and the selection of window-wall ratio is the focus of daylighting environment optimization.",
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"normalizedAbstract": "With the development of township economy in Guangdong, a large number of street houses have been built. The requirements of township residents for the quality of living environment are constantly improving, and the energy performance of street houses is becoming increasingly prominent. The research goal is to promote the scientific design of township street houses in western Guangdong, reduce the building energy performance of township street houses and improve daylighting quality. This study investigated 18 township in Xinyi City, Guangdong Province, and summarized the characteristics of street houses in typical township. According to the survey results, Rhino-Grasshopper is used to build a benchmark model, which comprehensively considers the performance of buildings in energy and daylighting. Virtual simulation is carried out by EnergyPlus and Radiance engine, and then multi-objective optimization is carried out by Pareto method to find the optimal solution of energy and daylight performance, and to provide the recommended values of design variables. The results show that the selection of appropriate building materials and structures is of great significance to the optimization of energy performance, and the selection of window-wall ratio is the focus of daylighting environment optimization.",
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"content": "With the increasing resolution and contrast of brain imaging devices automatic segmentation and quantification of the human cerebral cortex have grown popular for morphological analyses. The tightly folded cortex is often modeled with surfaces in 3D, and morphological features, such as the cortical thickness, can be calculated. In order to average and compare such morphological features within groups of subjects, mappings between the highly diverse cortical surfaces are needed. In this paper we evaluate five algorithms for mapping between discrete polygonal surfaces of cortices. Among the evaluated algorithms we include a new algorithm based on a functional expressing similarity between geometrical features. Four numerical mapping criteria, a landmark test, and statistical maps are used to evaluate the mapping algorithms. We show that the accuracy of manually placed landmarks are difficult to reproduce automatically, and the choice of mapping algorithm impacts the conclusions drawn from statistical maps generated by use of the algorithm. In terms of landmark accuracy, a spherical mapping approach with non-linear optimization is shown to be the best of the tested algorithms.",
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"abstract": "In this paper, we propose a mapping scheme of IP cores into irregular Network on Chips using an example module dedicated to features extraction for automatic speech recognition system. We estimated the core sizes for various frame sizes and overlappings, and then tried to place cores communicating heavily close to each other, we test a number of widths in the 2D Rectangular Strip Packing problem. The obtained result range allows us to pick a solution that is beneficial both in terms of area and transfers between the system cores.",
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"abstract": "This paper presents a technology mapping approach for the standard cell technology, which takes into account both gate area and routing area so as to minimize the total chip area after layout. The routing area is estimated using two parameters available at the mapping stage; one is the fanout count of a gate, and the other is the \"overlap of fanin level intervals\". To estimate the routing area in terms of accurate fanout counts, an algorithm is proposed which solves the problem of dynamic fanout changes in the mapping process. This also enables us to calculate the gate area more accurately. Experimental results show that this approach provides an average reduction of 15% in the final chip area after placement and routing.",
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"content": "This paper presents a technology mapping approach for the standard cell technology, which takes into account both gate area and routing area so as to minimize the total chip area after layout. The routing area is estimated using two parameters available at the mapping stage; one is the fanout count of a gate, and the other is the \"overlap of fanin level intervals\". To estimate the routing area in terms of accurate fanout counts, an algorithm is proposed which solves the problem of dynamic fanout changes in the mapping process. This also enables us to calculate the gate area more accurately. Experimental results show that this approach provides an average reduction of 15% in the final chip area after placement and routing.",
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"affiliation": "Technical University of Munich",
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"affiliation": "Technical University of Munich",
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"content": "During the process of modern industrialization and urbanization, it has become one of the major daily activities that people drive private cars to fulfill their travel demands. The trajectory data generated during the usage of private cars plays as the intuitive embodiment of people's travel behavior. In particular, the stay behavior, i.e., people need to stay and take time carrying out their own activities when they drive to a specific location, contains crucial information for understanding users' travel behavior and mobility motivations. In this paper, via leveraging the private car trajectory data, we strive to propose a novel approach to percept and predict stay of interests, called SOI. The goal is to predict the stay interest of a private car user will stay to a given location, this is important information for vehicle services such as travel semantic analysis and smart recommendation service. Specifically, we first propose a stay behavior perception method to detect stay behavior from large-scale private car trajectory dataset. Then, we design a spatiotemporal factor extraction method considering the spatial aggregation, time period and spatiotemporal similarity correlation of stay behaviors, which can reduce the sparsity and non-stationary problems of stay behavior data. Furthermore, we propose a prediction method based gradient boosting decision trees to estimate the future stay interest of private car users' stay behavior. We conduct extensive experiments based on the real-life private car trajectory dataset. For the stay interest prediction of stay behavior, achieve prediction precision of 0.89 and recall of 0.85. To the best of authors' knowledge, this is the first work in literature that exploits private car trajectory data and discovers the stay behavior of private car users and hence provides new perspective for understanding people's travel behavior.",
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"abstract": "The use of surface harmonics for rigid and nonrigid shape description is well known. In this paper we define a set of complete hemispherical harmonic basis functions on a hemisphere domain and propose a novel parametric shape description method to efficiently and flexibly represent the surfaces of anatomical structures in medical images. As the first application of hemispherical harmonic theory in shape description, our technique differs from the previous surface harmonics shape descriptors, all of which don't work efficiently on the hemisphere-like objects that often exist in medical anatomical structures (e.g., ventricles, atriums, etc.). We demonstrate the effectiveness of our approach through theoretic and experimental exploration of a set of medical image applications. Furthermore, an evaluation criterion for surface modeling efficiency is described and the comparison results demonstrated that our method outperformed the previous approaches using spherical harmonic models.",
"abstracts": [
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"content": "The use of surface harmonics for rigid and nonrigid shape description is well known. In this paper we define a set of complete hemispherical harmonic basis functions on a hemisphere domain and propose a novel parametric shape description method to efficiently and flexibly represent the surfaces of anatomical structures in medical images. As the first application of hemispherical harmonic theory in shape description, our technique differs from the previous surface harmonics shape descriptors, all of which don't work efficiently on the hemisphere-like objects that often exist in medical anatomical structures (e.g., ventricles, atriums, etc.). We demonstrate the effectiveness of our approach through theoretic and experimental exploration of a set of medical image applications. Furthermore, an evaluation criterion for surface modeling efficiency is described and the comparison results demonstrated that our method outperformed the previous approaches using spherical harmonic models.",
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"normalizedAbstract": "The use of surface harmonics for rigid and nonrigid shape description is well known. In this paper we define a set of complete hemispherical harmonic basis functions on a hemisphere domain and propose a novel parametric shape description method to efficiently and flexibly represent the surfaces of anatomical structures in medical images. As the first application of hemispherical harmonic theory in shape description, our technique differs from the previous surface harmonics shape descriptors, all of which don't work efficiently on the hemisphere-like objects that often exist in medical anatomical structures (e.g., ventricles, atriums, etc.). We demonstrate the effectiveness of our approach through theoretic and experimental exploration of a set of medical image applications. Furthermore, an evaluation criterion for surface modeling efficiency is described and the comparison results demonstrated that our method outperformed the previous approaches using spherical harmonic models.",
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"affiliation": "Dartmouth College, USA",
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"affiliation": "SUNY at Stony Brook, USA",
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"abstract": "The main objective of medical image segmentation is to extract and characterize anatomical structures with respect to some input features or expert knowledge. Traditional two-dimensional Otsu method for medical image segmentation is time–consuming computation and become an obstacle in real time application systems. This paper describes a way of medical image segmentation using optimized two-dimensional Otsu method based on improved genetic algorithm (GA). In proposed algorithm, the probability-ties of crossover are adaptively varied depending on the ranking value of individuals instead of fitness, and dyadic mutation operator was presented to take the place of the traditional one. The experimental results show that the new optimized method dramatically reduces the operating time in medical image segmentation while ensures the final image segmentation quality.",
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"abstract": "Visualization of topological information of a vector field can provide useful information on the structure of the field. However, in turbulent flows standard critical point visualization will result in a cluttered image which is difficult to interpret. This paper presents a technique for collapsing topologies. The governing idea is to classify the importance of the critical points in the topology. By only displaying the more important critical points, a simplified depiction of the topology can be provided. Flow consistency is maintained when collapsing the topology, resulting in a visualization which is consistent with the original topology. We apply the collapsing topology technique to a turbulent flow field.",
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