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"abstract": "Accurate per-pixel semantic class annotations of the entire video are crucial for designing and evaluating video semantic segmentation algorithms. However, the annotations are usually limited to a small subset of the video frames due to the high annotation cost and limited budget in practice. In this paper, we propose a novel human-in-the-loop framework called HVSA to generate semantic segmentation annotations for the entire video using only a small annotation budget. Our method alternates between active sample selection and test-time fine-tuning algorithms until annotation quality is satisfied. In particular, the active sample selection algorithm picks the most important samples to get manual annotations, where the sample can be a video frame, a rectangle, or even a super-pixel. Further, the test-time fine-tuning algorithm propagates the manual annotations of selected samples to the entire video. Real-world experiments show that our method generates highly accurate and consistent semantic segmentation annotations while simultaneously enjoys significantly small annotation cost.",
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"content": "Accurate per-pixel semantic class annotations of the entire video are crucial for designing and evaluating video semantic segmentation algorithms. However, the annotations are usually limited to a small subset of the video frames due to the high annotation cost and limited budget in practice. In this paper, we propose a novel human-in-the-loop framework called HVSA to generate semantic segmentation annotations for the entire video using only a small annotation budget. Our method alternates between active sample selection and test-time fine-tuning algorithms until annotation quality is satisfied. In particular, the active sample selection algorithm picks the most important samples to get manual annotations, where the sample can be a video frame, a rectangle, or even a super-pixel. Further, the test-time fine-tuning algorithm propagates the manual annotations of selected samples to the entire video. Real-world experiments show that our method generates highly accurate and consistent semantic segmentation annotations while simultaneously enjoys significantly small annotation cost.",
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"abstract": "Deep learning requires large amounts of annotated data. Manual annotation of objects in video is, regardless of annotation type, a tedious and time-consuming process. In particular, for scarcely used image modalities human annotation is hard to justify. In such cases, semi-automatic annotation provides an acceptable option. In this work, a recursive, semi-automatic annotation method for video is presented. The proposed method utilizes a state-of-the-art video object segmentation method to propose initial annotations for all frames in a video based on only a few manual object segmentations. In the case of a multi-modal dataset, the multi-modality is exploited to refine the proposed annotations even further. The final tentative annotations are presented to the user for manual correction. The method is evaluated on a subset of the RGBT-234 visual-thermal dataset reducing the workload for a human annotator with approximately 78% compared to full manual annotation. Utilizing the proposed pipeline, sequences are annotated for the VOT-RGBT 2019 challenge.",
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"content": "Deep learning requires large amounts of annotated data. Manual annotation of objects in video is, regardless of annotation type, a tedious and time-consuming process. In particular, for scarcely used image modalities human annotation is hard to justify. In such cases, semi-automatic annotation provides an acceptable option. In this work, a recursive, semi-automatic annotation method for video is presented. The proposed method utilizes a state-of-the-art video object segmentation method to propose initial annotations for all frames in a video based on only a few manual object segmentations. In the case of a multi-modal dataset, the multi-modality is exploited to refine the proposed annotations even further. The final tentative annotations are presented to the user for manual correction. The method is evaluated on a subset of the RGBT-234 visual-thermal dataset reducing the workload for a human annotator with approximately 78% compared to full manual annotation. Utilizing the proposed pipeline, sequences are annotated for the VOT-RGBT 2019 challenge.",
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"title": "Parallel Stochastic Portfolio Search for Constraint Solving",
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"title": "2022 IEEE 19th International Conference on Software Architecture (ICSA)",
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"title": "How Do Developers Search for Architectural Information? An Industrial Survey",
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"abstract": "Building software systems often requires knowledge and skills beyond what developers already possess. In such cases, developers have to leverage different sources of information to seek help. A growing number of researchers and practitioners have started investigating what programming-related information developers seek during software development. However, being a high level and a type of the most important development-related information, architectural information search activity is seldom explored. To fill this gap, we conducted an industrial survey completed by 103 participants to understand how developers search for architectural information to solve their architectural problems in development. Our main findings are: (1) searching for architectural information to learn about the pros and cons of certain architectural solutions (e.g., patterns, tactics) and to make an architecture decision among multiple choices are the most frequent purposes or tasks; (2) developers find difficulties mostly in getting relevant architectural information for addressing quality concerns and making design decisions among multiple choices when seeking architectural information; (3) taking too much time to go through architectural information retrieved from various sources and feeling overwhelmed due to the dispersion and abundance of architectural information in various sources are the top two major challenges developers face when searching for architectural information. Our findings (1) provide researchers with future directions, such as the design and development of approaches and tools for searching architectural information from multiple sources, and (2) can be used to provide guidelines for practitioners to refer to when seeking architectural information and providing architectural information that could be considered useful.",
"abstracts": [
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"content": "Building software systems often requires knowledge and skills beyond what developers already possess. In such cases, developers have to leverage different sources of information to seek help. A growing number of researchers and practitioners have started investigating what programming-related information developers seek during software development. However, being a high level and a type of the most important development-related information, architectural information search activity is seldom explored. To fill this gap, we conducted an industrial survey completed by 103 participants to understand how developers search for architectural information to solve their architectural problems in development. Our main findings are: (1) searching for architectural information to learn about the pros and cons of certain architectural solutions (e.g., patterns, tactics) and to make an architecture decision among multiple choices are the most frequent purposes or tasks; (2) developers find difficulties mostly in getting relevant architectural information for addressing quality concerns and making design decisions among multiple choices when seeking architectural information; (3) taking too much time to go through architectural information retrieved from various sources and feeling overwhelmed due to the dispersion and abundance of architectural information in various sources are the top two major challenges developers face when searching for architectural information. Our findings (1) provide researchers with future directions, such as the design and development of approaches and tools for searching architectural information from multiple sources, and (2) can be used to provide guidelines for practitioners to refer to when seeking architectural information and providing architectural information that could be considered useful.",
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{
"affiliation": "Monash University,Faculty of Information Technology,Melbourne,Australia",
"fullName": "Mojtaba Shahin",
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"proceeding": {
"id": "1HcmNfwzO80",
"title": "2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)",
"acronym": "ithings-greencom-cpscom-smartdata-cybermatics",
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"title": "How do Programmers Use the Internet? Discovering Domain Knowledge from Browsing and Coding Behaviors",
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"abstract": "The Internet is an effective tool for learners to gain new knowledge. Often, people use search engines (e.g., Google) rather than accessing websites directly. People have their search techniques to find specific information. In particular, people with domain knowledge tend to search more efficiently than novices. By understanding the gap between people with domain knowledge and novices, the novice can understand the path to becoming an expert. Therefore, in this study, we wanted to know what differences exist in search and programming behavior with and without domain knowledge. In this experiment, we asked a group with and without domain knowledge to solve ten programming problems and collected search logs (input knowledge) and compilation logs (output knowledge). Specifically, the first dataset consisted of 13 participants who had taken a university programming class. The second dataset consisted of 20 participants who had not taken a programming class and had no domain knowledge. We examined differences in search and compilation behavior based on participants’ domain knowledge from this data. Since we observed a difference between each group when referring to the correlation coefficient, we performed a binary classification of novice and experienced participants using Random Forest, and achieved an average precision of 0.95, indicating that there were different trends in behavior with and without domain knowledge.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The Internet is an effective tool for learners to gain new knowledge. Often, people use search engines (e.g., Google) rather than accessing websites directly. People have their search techniques to find specific information. In particular, people with domain knowledge tend to search more efficiently than novices. By understanding the gap between people with domain knowledge and novices, the novice can understand the path to becoming an expert. Therefore, in this study, we wanted to know what differences exist in search and programming behavior with and without domain knowledge. In this experiment, we asked a group with and without domain knowledge to solve ten programming problems and collected search logs (input knowledge) and compilation logs (output knowledge). Specifically, the first dataset consisted of 13 participants who had taken a university programming class. The second dataset consisted of 20 participants who had not taken a programming class and had no domain knowledge. We examined differences in search and compilation behavior based on participants’ domain knowledge from this data. Since we observed a difference between each group when referring to the correlation coefficient, we performed a binary classification of novice and experienced participants using Random Forest, and achieved an average precision of 0.95, indicating that there were different trends in behavior with and without domain knowledge.",
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"normalizedAbstract": "The Internet is an effective tool for learners to gain new knowledge. Often, people use search engines (e.g., Google) rather than accessing websites directly. People have their search techniques to find specific information. In particular, people with domain knowledge tend to search more efficiently than novices. By understanding the gap between people with domain knowledge and novices, the novice can understand the path to becoming an expert. Therefore, in this study, we wanted to know what differences exist in search and programming behavior with and without domain knowledge. In this experiment, we asked a group with and without domain knowledge to solve ten programming problems and collected search logs (input knowledge) and compilation logs (output knowledge). Specifically, the first dataset consisted of 13 participants who had taken a university programming class. The second dataset consisted of 20 participants who had not taken a programming class and had no domain knowledge. We examined differences in search and compilation behavior based on participants’ domain knowledge from this data. Since we observed a difference between each group when referring to the correlation coefficient, we performed a binary classification of novice and experienced participants using Random Forest, and achieved an average precision of 0.95, indicating that there were different trends in behavior with and without domain knowledge.",
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"affiliation": "University of Kaiserslautern & DFKI GmbH,Department of Computer Science,Kaiserslautern,Germany",
"fullName": "Ko Watanabe",
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"affiliation": "Nara Institute of Science and Technology,Graduate School of Science and Technology,Nara,Japan",
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{
"affiliation": "Kyushu University,Graduate School and Faculty of Information Science and Electrical Engineering,Fukuoka,Japan",
"fullName": "Yugo Nakamura",
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"affiliation": "Kyushu University,Graduate School and Faculty of Information Science and Electrical Engineering,Fukuoka,Japan",
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"affiliation": "University of Kaiserslautern & DFKI GmbH,Department of Computer Science,Kaiserslautern,Germany",
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"title": "2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)",
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"doi": "10.1109/HPCC/SmartCity/DSS.2019.00353",
"title": "Progressively-Refined Tree Search for Container Loading Problem",
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"abstract": "This work has presented a method to solve the single container loading problem with both full-support constraint and load-bearing constraint in the block-building based tree search framework. A method to compute load-bearing strength in both block generation and residual space generation is proposed. A modified in-complete tree structure that keeps only the depth 1 tree stemming from each layer is devised to predict the most suitable block to be placed in each residual space. The space utilisation under both orientation constraint and full-support constraint outperforms the best algorithm in the literature with more than 53% reduction in execution time. The space utilisation under load-bearing constraint has seen 6% ~ 12% improvement compared with the existing works with the same set of constraints.",
"abstracts": [
{
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"content": "This work has presented a method to solve the single container loading problem with both full-support constraint and load-bearing constraint in the block-building based tree search framework. A method to compute load-bearing strength in both block generation and residual space generation is proposed. A modified in-complete tree structure that keeps only the depth 1 tree stemming from each layer is devised to predict the most suitable block to be placed in each residual space. The space utilisation under both orientation constraint and full-support constraint outperforms the best algorithm in the literature with more than 53% reduction in execution time. The space utilisation under load-bearing constraint has seen 6% ~ 12% improvement compared with the existing works with the same set of constraints.",
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"abstract": "This study explores smart IT systems' utilization level in the value chain processes of manufacturing and empirically examines the effect of utilization level of IT systems on manufacturing competitiveness in Korean SMEs. Smart IT systems in the manufacturing value chain processes are divided into Sales, Purchasing, Production & logistics, and Support systems. By analyzing the research model with structural equation modelling, this study identify that Sales systems, Purchasing systems, Production & logistics systems, and Support systems have a significant impact on the Manufacturing process efficiency, and Production & logistics systems and Manufacturing process efficiency positively and significantly influenced the Manufacturing Competitiveness. It can be seen that information utilization is directly and positively relationship with manufacturing process efficiency including reducing lead-time, reducing work performance man-hour (M/H), and improving work accuracy. These processes finally have a significant impact on the manufacturing competitiveness. In conclusion, the use of smart IT systems is now becoming an integral part of the manufacturing industry. It will be necessary to gain a competitive edge by introducing and utilizing an optimal smart IT system, considering the size of a manufacturing firms.",
"abstracts": [
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"content": "This study explores smart IT systems' utilization level in the value chain processes of manufacturing and empirically examines the effect of utilization level of IT systems on manufacturing competitiveness in Korean SMEs. Smart IT systems in the manufacturing value chain processes are divided into Sales, Purchasing, Production & logistics, and Support systems. By analyzing the research model with structural equation modelling, this study identify that Sales systems, Purchasing systems, Production & logistics systems, and Support systems have a significant impact on the Manufacturing process efficiency, and Production & logistics systems and Manufacturing process efficiency positively and significantly influenced the Manufacturing Competitiveness. It can be seen that information utilization is directly and positively relationship with manufacturing process efficiency including reducing lead-time, reducing work performance man-hour (M/H), and improving work accuracy. These processes finally have a significant impact on the manufacturing competitiveness. In conclusion, the use of smart IT systems is now becoming an integral part of the manufacturing industry. It will be necessary to gain a competitive edge by introducing and utilizing an optimal smart IT system, considering the size of a manufacturing firms.",
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"abstract": "The visual exploration of spatio-temporal eye movement data is challenging, especially if we are interested in the movement patterns of a large number of study participants. For example, if popular visualization techniques like heat maps or gaze plots are used, we may lose the temporal information or get lost in visual clutter. To address these issues, we propose an approach for filtering saccadic eye movement data called hierarchical filter wheels, which employs a radial representation of saccade information. It supports the analysis of sequences of saccades by filtering them with respect to direction and length. The focus of our approach is a fast initial analysis of data from eye tracking studies without the need of defining areas of interest (AOIs) or other preprocessing of the data. The hierarchical filters are interactively generated on users' demand by creating a hierarchy of multiple filter wheels each filtering one element of the sequence. We use a bubble tree layout to represent the generated filter hierarchy. The node positions in our layout directly represent the spatial properties of the filter criteria allowing an intuitive incremental generation and understanding of filter hierarchies. We illustrate the approach by applying it to eye movement data formerly recorded in an eye tracking study investigating the readability of different node-link tree diagrams. We further demonstrate how the hierarchical filter wheels can be used in combination with gaze plots.",
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"content": "The visual exploration of spatio-temporal eye movement data is challenging, especially if we are interested in the movement patterns of a large number of study participants. For example, if popular visualization techniques like heat maps or gaze plots are used, we may lose the temporal information or get lost in visual clutter. To address these issues, we propose an approach for filtering saccadic eye movement data called hierarchical filter wheels, which employs a radial representation of saccade information. It supports the analysis of sequences of saccades by filtering them with respect to direction and length. The focus of our approach is a fast initial analysis of data from eye tracking studies without the need of defining areas of interest (AOIs) or other preprocessing of the data. The hierarchical filters are interactively generated on users' demand by creating a hierarchy of multiple filter wheels each filtering one element of the sequence. We use a bubble tree layout to represent the generated filter hierarchy. The node positions in our layout directly represent the spatial properties of the filter criteria allowing an intuitive incremental generation and understanding of filter hierarchies. We illustrate the approach by applying it to eye movement data formerly recorded in an eye tracking study investigating the readability of different node-link tree diagrams. We further demonstrate how the hierarchical filter wheels can be used in combination with gaze plots.",
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"abstract": "User behavior can be identified by clustering the web-site navigational patterns expressed by clickstream sequences. Representation of clickstream sequences is yet a challenging problem. The main difficulty is related to the fact that one needs to represent clickstream sequences, which mainly consists of dynamic URLs, in such a way that traditional clustering algorithms are applicable to group together these sequences. In this study, we present the application of embedding approaches to represent click-stream data sequences, to enable machine learning algorithms learn the users' navigational behaviors on web-sites. By utilizing embedding representation, we propose an algorithm that takes clickstream data as input and creates clustered sequential patterns. We discuss the details of different representation algorithms and present its evaluations. We investigate the accuracy in finding the hidden clustered data sequences within the clickstream data. The results show that Word2Vec, representation method that can lead to high quality clustering of user navigational patterns.",
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"content": "User behavior can be identified by clustering the web-site navigational patterns expressed by clickstream sequences. Representation of clickstream sequences is yet a challenging problem. The main difficulty is related to the fact that one needs to represent clickstream sequences, which mainly consists of dynamic URLs, in such a way that traditional clustering algorithms are applicable to group together these sequences. In this study, we present the application of embedding approaches to represent click-stream data sequences, to enable machine learning algorithms learn the users' navigational behaviors on web-sites. By utilizing embedding representation, we propose an algorithm that takes clickstream data as input and creates clustered sequential patterns. We discuss the details of different representation algorithms and present its evaluations. We investigate the accuracy in finding the hidden clustered data sequences within the clickstream data. The results show that Word2Vec, representation method that can lead to high quality clustering of user navigational patterns.",
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"abstract": "Studies on augmenting visualization with sound are typically based on the assumption that sound can be complementary and assist in data analysis tasks. While sound promotes a different sense of engagement than vision, we conjecture that by augmenting non-speech audio to a visualization can not only help enhance the users' perception of the data but also increase their engagement with the data exploration process. We have designed a preliminary user study to test users' performance and engagement while exploring in a data visualization system under two different settings: visual-only and audiovisual. For our study, we used basketball player movement data in a game and created an interactive visualization system with three linked views. We supplemented sound to the visualization to enhance the users' understanding of a team's offensive/defensive behavior. The results of our study suggest that we need to better understand the effect of sound choice and encoding before considering engagement. We also find that sound can be useful to draw novice users' attention to patterns or anomalies in the data. Finally, we propose follow-up studies with designs informed by the findings from this study.",
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"title": "Haptic Interfaces for Virtual Environment and Teleoperator Systems, International Symposium on",
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"abstract": "We have developed a multi-modal virtual environment set-up by fusing visual and haptic images through the use of a new autostereoscopic display and a force-feedback haptic device. Most of the earlier visualization systems that integrate stereo displays and haptic devices have utilized polarized or shutter glasses for stereo vision (see, for example, Veldkamp et al., 2002, Chen et al., 2002, and Brederson et al., 2000). In this paper, we discuss the development stages and components of our set-up that allows a user to touch, feel, and manipulate virtual objects through a haptic device while seeing them in stereo without using any special eyewear. We also discuss the transformations involved in mapping the absolute coordinates of virtual objects into visual and haptic workspaces and the synchronization of cursor movements in these workspaces. Future applications of this work will include a) multi-modal visualization of planetary data and b) planning of space mission operations in virtual environments.",
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"affiliation": "California Institute of Technology",
"fullName": "Cagatay Basdogan",
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"affiliation": "California Institute of Technology",
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"affiliation": "California Institute of Technology",
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"abstract": "In the large-scale geography information system application, the distributed file system is the key approach for data storage and retrieving, but the traditional distributed spatial index's efficiency is low. We present a dynamic pyramid Rtree(DPR) index for the massive geospatial files management, the method is based on the pyramid spatial index and Rtree index, which can be adjusted with the data distributed dynamically, we described index building and data accessing, the experimentation result shows that our method's efficiency in distributed file system is higher than Hilbert tree index and Quad tree index in range query.",
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"content": "The visualization of relational data by node-link diagrams quickly leads to a degradation of performance at some exploration tasks when the diagrams show visual clutter and overdraw. To address this challenge of large-data graph visualization, we introduce Graph Metric Views, a technique that enriches the visualization of traditional layout strategies for node-link diagrams by additionally allowing an analyst to interactively explore graph-specific metrics such as number of nodes, number of link crossings, link coverage, or degree of orthogonality. To this end, we support an analyst with additional histogram-like representations at the axes of the display space for graph-specific metrics. In this way, a cluttered and densely packed node-link diagram becomes more explorable even for dense graph regions: The user can use the distribution of metric values as an overview and then select regions of interest for further investigation and filtering.",
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"abstract": "Ever since Descartes introduced planar coordinate systems, visual representations of data have become a widely accepted way of describing scientific phenomena. Modern advances in measurement and instrumentation have required increasingly sophisticated visual representations, to ensure that scientists can quickly and accurately interpret increasingly complex data. Most recently, wireless sensor networks (WSNs) have emerged as a technology which is capable of collecting a vast amount of data over space and time. The sheer volume of the data makes it difficult to be interpreted by humans into meaningful insights. This presents a number of challenges for developers of visualisation techniques which seek to ``map'' the data sensed by a network. Visualisation techniques helps to turn large amounts of raw data into credible visual information such as graphs, charts, or maps, that can assist in understanding of the meaning of that data. In this paper we propose a map as a suitable data visualisation and extraction tool. We aim to develop an in-network distributed information extraction and visualisation service. Such a service would greatly simplify the production of higher-level information-rich representations suitable for informing other network services and the delivery of field information visualisation.",
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"abstract": "Data encryption is the most important way to provide security in hostile environment. Nearly all of the existing data encryption techniques require a lot of arithmetic and logical computations, which makes their deployment in embedded devices very difficult. To realize firm data encryption without much computation, a novel scheme of physically-embedded data encryption is proposed in this paper. The physically-embedded data encryption extracts the unique and unclonable values that are possessed by the physical device intrinsically, and produces the secret from these values to accomplish the process of data encryption. Because it does not execute arithmetic and logical operations, it is very appropriate to embedded devices with restricted computing resources and computing abilities. At the same time, it provides high assurance of data protection due to the distinct properties of physical effects. One specific design of physically-embedded data encryption is given in this paper, and real physical instantiation of such design is tested. The experiment results show its validity and feasibility. Hence, the proposed physically-embedded data encryption should become a promising substitution of existing encryption techniques for embedded devices.",
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"content": "Data encryption is the most important way to provide security in hostile environment. Nearly all of the existing data encryption techniques require a lot of arithmetic and logical computations, which makes their deployment in embedded devices very difficult. To realize firm data encryption without much computation, a novel scheme of physically-embedded data encryption is proposed in this paper. The physically-embedded data encryption extracts the unique and unclonable values that are possessed by the physical device intrinsically, and produces the secret from these values to accomplish the process of data encryption. Because it does not execute arithmetic and logical operations, it is very appropriate to embedded devices with restricted computing resources and computing abilities. At the same time, it provides high assurance of data protection due to the distinct properties of physical effects. One specific design of physically-embedded data encryption is given in this paper, and real physical instantiation of such design is tested. The experiment results show its validity and feasibility. Hence, the proposed physically-embedded data encryption should become a promising substitution of existing encryption techniques for embedded devices.",
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"normalizedAbstract": "Data encryption is the most important way to provide security in hostile environment. Nearly all of the existing data encryption techniques require a lot of arithmetic and logical computations, which makes their deployment in embedded devices very difficult. To realize firm data encryption without much computation, a novel scheme of physically-embedded data encryption is proposed in this paper. The physically-embedded data encryption extracts the unique and unclonable values that are possessed by the physical device intrinsically, and produces the secret from these values to accomplish the process of data encryption. Because it does not execute arithmetic and logical operations, it is very appropriate to embedded devices with restricted computing resources and computing abilities. At the same time, it provides high assurance of data protection due to the distinct properties of physical effects. One specific design of physically-embedded data encryption is given in this paper, and real physical instantiation of such design is tested. The experiment results show its validity and feasibility. Hence, the proposed physically-embedded data encryption should become a promising substitution of existing encryption techniques for embedded devices.",
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"content": "Charts are graphical representations of numbers that help us to extract trends, relations and in general to have a better understanding of data. For this reason, multiple systems have been developed to display charts in a digital or physical manner. Here, we introduce Floating Charts, a modular display that utilizes acoustic levitation for positioning free-floating objects. Multiple objects are individually levitated to compose a dynamic floating chart with the ability to move in real time to reflect changes in data. Floating objects can have different sizes and colours to represent extra information. Additionally, they can be levitated across other physical structures to improve depth perception. We present the system design, a technical evaluation and a catalogue of chart variations.",
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"normalizedAbstract": "Charts are graphical representations of numbers that help us to extract trends, relations and in general to have a better understanding of data. For this reason, multiple systems have been developed to display charts in a digital or physical manner. Here, we introduce Floating Charts, a modular display that utilizes acoustic levitation for positioning free-floating objects. Multiple objects are individually levitated to compose a dynamic floating chart with the ability to move in real time to reflect changes in data. Floating objects can have different sizes and colours to represent extra information. Additionally, they can be levitated across other physical structures to improve depth perception. We present the system design, a technical evaluation and a catalogue of chart variations.",
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"abstract": "In recent years augmented reality applications have been increasingly demonstrating the requirement for an interaction with information related to and directly shown in the surrounding environment. Situated information is visualized in its semantic and spatial context, building up an environment enhanced by an information level that dynamically adapts to the production of the information and to the actions of the user. The exploration and manipulation of this type of data through see-through augmented reality devices still represents a challenging task. The development of specific interaction strategies capable to mitigating the current limitations of augmented reality devices is essential. In this context, our contribution has been to design possible solutions to address some of these challenges allowing a dynamic interaction with situated information. Following the visual \"information-seeking mantra\" proposed by Shneiderman and introducing some \"superpowers\" for the users, in this work we present different strategies aimed at obtaining an overview and filtering, and acquiring details of a collection of situated data.",
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"content": "Nowadays, people use more and more social media as a source of information, leading to an increased and uncontrolled spread of misinformation. For this reason, tools to detect unverified and instrumentally relevant news, named as rumours, are necessary. In this work we compare two state-of-the-art handcrafted representations, namely User-Network and Social-Content, designed for developing machine learning-based rumour detection systems, in order to analyse which descriptors best capture the information hidden in unknown rumours. To this end we set up an experimental assessment implementing a Leave-One-Topic-Out evaluation on 8 different topics retrieved from Twitter social microblog. The results obtained for both representations are low as we designed a simple and non optimised pipeline for a fair comparison. Besides this, we were able to find out that the User-Network set of feature results more stable to topic changes. As a further contribution, we introduce two new datasets labelled for rumour detection task on Twitter.",
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"affiliation": "Università Campus Bio-Medico di Roma,Unit of Computer Systems and Bioinformatics,Department of Engineering,Italy",
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"affiliation": "Università Campus Bio-Medico di Roma,Unit of Computer Systems and Bioinformatics,Department of Engineering,Italy",
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"affiliation": "Università Campus Bio-Medico di Roma,Unit of Computer Systems and Bioinformatics,Department of Engineering,Italy",
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"abstract": "Open-source projects rely on attracting new and retaining old contributors for achieving sustainable success. One may suspect that adopting new development practices like Continuous Integration (CI) should improve the attractiveness of a project. However, little is known about the impact that adoption of CI has on developer attraction and retention. To bridge this gap, we study how the introduction of TRAVIS CI-a popular CI service provider-impacts developer attraction and retention in 217 GITHUB repositories. Surprisingly, we find that heuristics that estimate the developer attraction and retention of a project are higher in the year before adopting TRAVIS CI than they are in the year following TRAVIS CI adoption. Moreover, the results are statistically significant (Wilcoxon signed rank test, α = 0:05), with small but non-negligible effect sizes (Cliff's delta). Although we do not suspect a causal link, our results are worrisome. More work is needed to ascertain the relationship between CI and developer attraction and retention.",
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"content": "Open-source projects rely on attracting new and retaining old contributors for achieving sustainable success. One may suspect that adopting new development practices like Continuous Integration (CI) should improve the attractiveness of a project. However, little is known about the impact that adoption of CI has on developer attraction and retention. To bridge this gap, we study how the introduction of TRAVIS CI-a popular CI service provider-impacts developer attraction and retention in 217 GITHUB repositories. Surprisingly, we find that heuristics that estimate the developer attraction and retention of a project are higher in the year before adopting TRAVIS CI than they are in the year following TRAVIS CI adoption. Moreover, the results are statistically significant (Wilcoxon signed rank test, α = 0:05), with small but non-negligible effect sizes (Cliff's delta). Although we do not suspect a causal link, our results are worrisome. More work is needed to ascertain the relationship between CI and developer attraction and retention.",
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"normalizedAbstract": "Open-source projects rely on attracting new and retaining old contributors for achieving sustainable success. One may suspect that adopting new development practices like Continuous Integration (CI) should improve the attractiveness of a project. However, little is known about the impact that adoption of CI has on developer attraction and retention. To bridge this gap, we study how the introduction of TRAVIS CI-a popular CI service provider-impacts developer attraction and retention in 217 GITHUB repositories. Surprisingly, we find that heuristics that estimate the developer attraction and retention of a project are higher in the year before adopting TRAVIS CI than they are in the year following TRAVIS CI adoption. Moreover, the results are statistically significant (Wilcoxon signed rank test, α = 0:05), with small but non-negligible effect sizes (Cliff's delta). Although we do not suspect a causal link, our results are worrisome. More work is needed to ascertain the relationship between CI and developer attraction and retention.",
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"Developer Retention",
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"GITHUB Repositories",
"TRAVIS CI Adoption",
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"Standards",
"Tools",
"Metadata",
"Electronic Mail",
"Measurement",
"Software"
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"fullName": "Keheliya Gallaba",
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{
"affiliation": null,
"fullName": "Shane McIntosh",
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"abstract": "Differences between members within teams can align to create potential faultlines. Faultlines have the potential to significantly disrupt performance due to the creation of intergroup bias. In geographically-dispersed teams, due to dispersed locations and other diversity characteristics, potential intergroup bias could be a major issue in Global Virtual Teams (GVT's) that needs to be more fully understood. This study examines whether public self-disclosure via weblogs can alleviate intergroup bias in geographically-dispersed teams by enabling the development of personal relationships. An experimental study of 34 4-person student teams found that public self-disclosure does not have a direct effect on reducing intergroup bias but has a mediated effect through social attraction. That is, as team members disclose their personal information and out-group team members are attracted to such disclosure, perceived in-group and out-group differences are diminished. Overall, findings support the common in-group identity model and highlight the potential benefits of socialization via weblogs in dispersed teams.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Differences between members within teams can align to create potential faultlines. Faultlines have the potential to significantly disrupt performance due to the creation of intergroup bias. In geographically-dispersed teams, due to dispersed locations and other diversity characteristics, potential intergroup bias could be a major issue in Global Virtual Teams (GVT's) that needs to be more fully understood. This study examines whether public self-disclosure via weblogs can alleviate intergroup bias in geographically-dispersed teams by enabling the development of personal relationships. An experimental study of 34 4-person student teams found that public self-disclosure does not have a direct effect on reducing intergroup bias but has a mediated effect through social attraction. That is, as team members disclose their personal information and out-group team members are attracted to such disclosure, perceived in-group and out-group differences are diminished. Overall, findings support the common in-group identity model and highlight the potential benefits of socialization via weblogs in dispersed teams.",
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"normalizedAbstract": "Differences between members within teams can align to create potential faultlines. Faultlines have the potential to significantly disrupt performance due to the creation of intergroup bias. In geographically-dispersed teams, due to dispersed locations and other diversity characteristics, potential intergroup bias could be a major issue in Global Virtual Teams (GVT's) that needs to be more fully understood. This study examines whether public self-disclosure via weblogs can alleviate intergroup bias in geographically-dispersed teams by enabling the development of personal relationships. An experimental study of 34 4-person student teams found that public self-disclosure does not have a direct effect on reducing intergroup bias but has a mediated effect through social attraction. That is, as team members disclose their personal information and out-group team members are attracted to such disclosure, perceived in-group and out-group differences are diminished. Overall, findings support the common in-group identity model and highlight the potential benefits of socialization via weblogs in dispersed teams.",
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"fullName": "Yi-Te Chiu",
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{
"proceeding": {
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"title": "Modeling Correlated Effect and Random Effect of Advertising and Word-of-Mouth on Product Diffusion",
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"abstract": "We develop a non-homogeneous Poisson model to study how the relationship between advertising and WOM and the occurrence of unexpected events affect product diffusion. For correlated effect, we generate parameters of advertising and WOM with given correlation by Copula method. For random effect, we use a Markov chain to modulate correlation between two parameters as well as distributions of two parameters. Numerical studies show that correlation between advertising and WOM speeds up diffusion process, but when considering a reasonable level within substitution or complement, managers should balance between scale of diffusion and speed of diffusion. Also, when random effect is neutral, complementary relationship creates more adoptions as unexpected events occur more frequently. Consequently, managers might be able to use correlation wisely to hedge from uncertainties.",
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{
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"content": "We develop a non-homogeneous Poisson model to study how the relationship between advertising and WOM and the occurrence of unexpected events affect product diffusion. For correlated effect, we generate parameters of advertising and WOM with given correlation by Copula method. For random effect, we use a Markov chain to modulate correlation between two parameters as well as distributions of two parameters. Numerical studies show that correlation between advertising and WOM speeds up diffusion process, but when considering a reasonable level within substitution or complement, managers should balance between scale of diffusion and speed of diffusion. Also, when random effect is neutral, complementary relationship creates more adoptions as unexpected events occur more frequently. Consequently, managers might be able to use correlation wisely to hedge from uncertainties.",
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"fno": "7367d374",
"keywords": [
"Advertising",
"Correlation",
"Correlation Coefficient",
"Random Variables",
"Markov Processes",
"Uncertainty",
"Companies"
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{
"affiliation": null,
"fullName": "Yang Cenying",
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{
"affiliation": null,
"fullName": "Zhang Cheng",
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"abstract": "Social media provides access to diverse and potentially conflicting information about organizations to potential job candidates. However, little is known about the impact of conflicting information between social media and corporate websites for recruitment and attraction. Using an experimental design, we exposed participants to a fictitious company website promoting an employer brand of diversity. Participants were then randomly shown a fictitious Linked In employee search result page depicting high-or low-employee diversity. Using the instrumental-symbolic framework and warranting theory, we posit that consistent information from Linked In will result in more positive image perceptions of organizations, ultimately leading to higher organizational attraction. Results show that participants who were exposed to information consistent with the organizational website promoting diversity rated that organization higher in agreeableness, and perceived agreeableness fully mediated the relationship between the experimental condition and organizational attractiveness.",
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"content": "Social media provides access to diverse and potentially conflicting information about organizations to potential job candidates. However, little is known about the impact of conflicting information between social media and corporate websites for recruitment and attraction. Using an experimental design, we exposed participants to a fictitious company website promoting an employer brand of diversity. Participants were then randomly shown a fictitious Linked In employee search result page depicting high-or low-employee diversity. Using the instrumental-symbolic framework and warranting theory, we posit that consistent information from Linked In will result in more positive image perceptions of organizations, ultimately leading to higher organizational attraction. Results show that participants who were exposed to information consistent with the organizational website promoting diversity rated that organization higher in agreeableness, and perceived agreeableness fully mediated the relationship between the experimental condition and organizational attractiveness.",
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"abstract": "VQA models may tend to rely on language bias as a shortcut and thus fail to sufficiently learn the multi-modal knowledge from both vision and language. Recent debiasing methods proposed to exclude the language prior during inference. However, they fail to disentangle the \"good\" language context and \"bad\" language bias from the whole. In this paper, we investigate how to mitigate language bias in VQA. Motivated by causal effects, we proposed a novel counterfactual inference framework, which enables us to capture the language bias as the direct causal effect of questions on answers and reduce the language bias by subtracting the direct language effect from the total causal effect. Experiments demonstrate that our proposed counterfactual inference framework 1) is general to various VQA backbones and fusion strategies, 2) achieves competitive performance on the language-bias sensitive VQA-CP dataset while performs robustly on the balanced VQA v2 dataset without any augmented data. The code is available at https://github.com/yuleiniu/cfvqa.",
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"content": "VQA models may tend to rely on language bias as a shortcut and thus fail to sufficiently learn the multi-modal knowledge from both vision and language. Recent debiasing methods proposed to exclude the language prior during inference. However, they fail to disentangle the \"good\" language context and \"bad\" language bias from the whole. In this paper, we investigate how to mitigate language bias in VQA. Motivated by causal effects, we proposed a novel counterfactual inference framework, which enables us to capture the language bias as the direct causal effect of questions on answers and reduce the language bias by subtracting the direct language effect from the total causal effect. Experiments demonstrate that our proposed counterfactual inference framework 1) is general to various VQA backbones and fusion strategies, 2) achieves competitive performance on the language-bias sensitive VQA-CP dataset while performs robustly on the balanced VQA v2 dataset without any augmented data. The code is available at https://github.com/yuleiniu/cfvqa.",
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