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"title": "Differentially Private Wireless Data Publication in Large-Scale WLAN Networks",
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"abstract": "Wireless trace data play an important role in wireless network researches. However, publishing the raw WLAN traces poses potential privacy risks of network users. Therefore, it is necessary to sanitize users' sensitive information before these traces are published, and provide high data utility for wireless network researches as well. Although some existing works based on various anonymization methods have started to address the problem of sanitizing WLAN traces, the anonymization techniques cannot provide strong and provable privacy guarantees. Differential Privacy is the only framework that can provide strong and provable privacy guarantees. However, we find that existing studies on differential privacy fail to provide effective data utility on multi-dimensional and large-scale datasets. Aim at WLAN trace datasets that have unique characteristics of multi-dimensional and large-scale, this paper proposes a privacy-preserving data publishing algorithm which not only satisfies differential privacy but also realizes high data utility. Furthermore, the theoretical analysis shows the noise variance of our sanitization algorithm is O(logo(1) n/ϵ2) which indicates the algorithm can achieve a higher data utility on large-scale datasets. Moreover, from the results of extensive experiments on an large-scale WLAN trace dataset, we also show that our sanitization algorithm can provide high data utility.",
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"content": "Wireless trace data play an important role in wireless network researches. However, publishing the raw WLAN traces poses potential privacy risks of network users. Therefore, it is necessary to sanitize users' sensitive information before these traces are published, and provide high data utility for wireless network researches as well. Although some existing works based on various anonymization methods have started to address the problem of sanitizing WLAN traces, the anonymization techniques cannot provide strong and provable privacy guarantees. Differential Privacy is the only framework that can provide strong and provable privacy guarantees. However, we find that existing studies on differential privacy fail to provide effective data utility on multi-dimensional and large-scale datasets. Aim at WLAN trace datasets that have unique characteristics of multi-dimensional and large-scale, this paper proposes a privacy-preserving data publishing algorithm which not only satisfies differential privacy but also realizes high data utility. Furthermore, the theoretical analysis shows the noise variance of our sanitization algorithm is O(logo(1) n/ϵ2) which indicates the algorithm can achieve a higher data utility on large-scale datasets. Moreover, from the results of extensive experiments on an large-scale WLAN trace dataset, we also show that our sanitization algorithm can provide high data utility.",
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"proceeding": {
"id": "17D45VtKirt",
"title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
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"doi": "10.1109/CVPR.2018.00883",
"title": "Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images",
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"abstract": "Images convey a broad spectrum of personal information. If such images are shared on social media platforms, this personal information is leaked which conflicts with the privacy of depicted persons. Therefore, we aim for automated approaches to redact such private information and thereby protect privacy of the individual. By conducting a user study we find that obfuscating the image regions related to the private information leads to privacy while retaining utility of the images. Moreover, by varying the size of the regions different privacy-utility trade-offs can be achieved. Our findings argue for a \"redaction by segmentation\" paradigm. Hence, we propose the first sizable dataset of private images \"in the wild\" annotated with pixel and instance level labels across a broad range of privacy classes. We present the first model for automatic redaction of diverse private information. It is effective at achieving various privacy-utility trade-offs within 83% of the performance of redactions based on ground-truth annotation.",
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"content": "Images convey a broad spectrum of personal information. If such images are shared on social media platforms, this personal information is leaked which conflicts with the privacy of depicted persons. Therefore, we aim for automated approaches to redact such private information and thereby protect privacy of the individual. By conducting a user study we find that obfuscating the image regions related to the private information leads to privacy while retaining utility of the images. Moreover, by varying the size of the regions different privacy-utility trade-offs can be achieved. Our findings argue for a \"redaction by segmentation\" paradigm. Hence, we propose the first sizable dataset of private images \"in the wild\" annotated with pixel and instance level labels across a broad range of privacy classes. We present the first model for automatic redaction of diverse private information. It is effective at achieving various privacy-utility trade-offs within 83% of the performance of redactions based on ground-truth annotation.",
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"title": "2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
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"title": "Interpreting Disparate Privacy-Utility Tradeoff in Adversarial Learning via Attribute Correlation",
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"abstract": "Adversarial learning is commonly used to extract latent data representations which are expressive to predict the target attribute but indistinguishable in the privacy attribute. However, whether they can achieve an expected privacy-utility tradeoff is of great uncertainty. In this paper, we posit it is the complex interaction between different attributes in the training set that causes disparate tradeoff results. We first formulate the measurement of utility, privacy and their tradeoff in adversarial learning. Then we propose the metrics of Statistical Reliability (SR) and Feature Reliability (FR) to quantify the relationship between attributes. Specifically, SR reflects the co-occurrence sampling bias of the joint distribution between two attributes. Beyond the explicit dependence, FR exploits the intrinsic interaction one attribute exerts on the other via exploring the representation disentanglement. We validate the metrics on CelebA and LFW dataset with a suite of target-privacy attribute pairs. Experimental results demonstrate the strong correlations between the metrics and utility, privacy and their tradeoff. We further conclude how to use SR and FR as a guide to the setting of the privacy-utility tradeoff parameter.",
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"content": "Adversarial learning is commonly used to extract latent data representations which are expressive to predict the target attribute but indistinguishable in the privacy attribute. However, whether they can achieve an expected privacy-utility tradeoff is of great uncertainty. In this paper, we posit it is the complex interaction between different attributes in the training set that causes disparate tradeoff results. We first formulate the measurement of utility, privacy and their tradeoff in adversarial learning. Then we propose the metrics of Statistical Reliability (SR) and Feature Reliability (FR) to quantify the relationship between attributes. Specifically, SR reflects the co-occurrence sampling bias of the joint distribution between two attributes. Beyond the explicit dependence, FR exploits the intrinsic interaction one attribute exerts on the other via exploring the representation disentanglement. We validate the metrics on CelebA and LFW dataset with a suite of target-privacy attribute pairs. Experimental results demonstrate the strong correlations between the metrics and utility, privacy and their tradeoff. We further conclude how to use SR and FR as a guide to the setting of the privacy-utility tradeoff parameter.",
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"affiliation": "Institute of Information Engineering,CAS,Beijing,China",
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"affiliation": "Duke University,Department of Electrical and Computer Engineering,Durham,USA",
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"affiliation": "Illinois Institute of Technology,Department of Computer Science,Chicago,USA",
"fullName": "Binghui Wang",
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"affiliation": "Duke University,Department of Electrical and Computer Engineering,Durham,USA",
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"affiliation": "Xidian University,School of Cyber Engineering,Xi’an,China",
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"abstract": "Sentiment analysis is one of the most popular natural language processing techniques. It aims to identify the sentiment polarity (positive, negative, neutral or mixed) within a given text. The proper lexicon knowledge is very important for the lexicon-based sentiment analysis methods since they hinge on using the polarity of the lexical item to determine a text's sentiment polarity. However, it is quite common that some lexical items appear positive in the text of one domain but appear negative in another. In this paper, we propose an innovative knowledge building algorithm to extract sentiment lexicon knowledge through computing their polarity value based on their polarity distribution in text dataset, such as in a set of domain specific reviews. The proposed algorithm was tested by a set of domain microblogs. The results demonstrate the effectiveness of the proposed method. The proposed lexicon knowledge extraction method can enhance the performance of knowledge based sentiment analysis.",
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"abstract": "Sentiment classification categorizes people's opinions from the data. Nowadays, people express their personal interests, feelings, and opinions on social media, and the posts on social media are frequently used as the data for sentiment classification. One of the sentiment classification approaches is a dictionary-based approach. A traditional dictionary-based sentiment classification approach uses word matching based on the lexicon. However, many posts cannot be analyzed by traditional dictionary-based sentiment classifier due to the absence of the sentiment words in the lexicon. For this reason, it is needed to expand the lexicon so that the lexicon can contain the words. In this paper, we propose a method to build thesaurus lexicon using dictionary-based approach for the sentiment classification. The proposed method uses three online dictionaries to collect thesauruses based on the seed words, and stores only co-occurrence words into the thesaurus lexicon in order to improve the reliability of the thesaurus lexicon. Also, this method recursively collects thesauruses which are a set of synonyms and antonyms to expand the thesaurus lexicon. This recursive thesaurus collection provides effective expansion of the lexicon from small set without the use of human resource, and the expanded thesaurus lexicon is used to increase availability of posts and used to increase accuracy of the sentiment classification.",
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"abstract": "Building a polarized lexicon is an essential step towards a reliable opinion mining engine. In this paper we are presenting an approach and describing an experiment to build an Arabic polarized lexicon from analyzing online customer reviews. These reviews are written in Modern Standard Arabic and Palestinian/Jordanian dialect. Therefore, the produced lexicon compromises casual slangs and dialectic entries used by the online community, which is useful for sentiment analysis of informal social media microblogs. We have extracted 28000 entries from processing 15100 reviews and by expanding the initial lexicon with through google translate. Each entry was given a polarity tag and a confidence score. High confidence scores have increased the precision of the polarization process.",
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"abstract": "In subjectivity and sentiment analysis (SSA), there are two main requirements are necessary to improve sentiment analysis effectively in any language and genres, first, high coverage sentiment lexicon - where entries are tagged with semantic orientation (positive, negative and neutral) - second, tagged corpora to train the sentiment classifier. Much of research has been conducted in this area during the last decade, but the need of building these resources is still ongoing, especially for morphologically-Rich language (MRL) such as Arabic. In this paper, we present an automatic expandable wide coverage polarity lexicon of Arabic sentiment words, this lexical resource explicitly devised for supporting Arabic sentiment classification and opinion mining applications. The lexicon is built using a seed of gold-standard Arabic sentiment words which are manually collected and annotated with semantic orientation (positive or negative), and automatically expanded with sentiment orientation detection of the new sentiment words by exploiting some lexical information such as part-of-speech (POS) tags and using synset aggregation techniques from free online Arabic lexicons, thesauruses. We report efforts to expand a manually-built our polarity lexicon using different types of data. Finally, we used various tagged data to evaluate the coverage and quality of our polarity lexicon, moreover, to evaluate the lexicon expansion and its effects on the sentiment analysis accuracy. Our data focus on modern standard Arabic (MSA) and Egyptian dialectal Arabic tweets and Arabic microblogs (hotel reservation, product reviews, and TV program comments).",
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"content": "Microblogging platforms are now one of the most popular means of social media in China. Carrying sentiment analysis on those platforms can provide valuable insights for various uses. However, the heavy use of Internet slang in microblog contexts and the lack of slang vocabulary in sentiment lexicons make it problematic. Aimed at this issue, we propose a method to build a comprehensive sentiment lexicon for Chinese internet slang. We leverage online sources to acquire a list of slang words first. Then, a method based on SO-PMI (Semantic Orientation from Pointwise Mutual Information) is used to assign the sentiment polarity to each word. By Utilizing online sources, the slang lexicon has comprehensive coverage of internet slang. The sentiment categorization method based on SO-PMI guarantees the sentiment polarity we acquire from microblog flatforms is compatible with the same microblog context the lexicon aimed to analyze.",
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"abstract": "The semantic integration of heterogeneous information sources across the enterprise together with product information available from the Internet of Things will be so vast, that one of the main challenges will be to provide the right information, at the right time, in the right place, and to the right people. This objective is addressed by the Aletheia - a project targeting the development of a distributed information system that enables the federation and semantic integration of very heterogeneous information sources. In this paper, we present the identified scenarios for semantic data federations in industrial service lifecycle management and discuss the utilization of mock-ups to support the software architects and engineers in the development of the Aletheia system.",
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"abstract": "As computing devices become more pervasive in our daily lives, effective communication between the user and the system becomes increasingly important. The ability to describe actions at a human level of abstraction is key. However, the level at which computer system events is most easily captured is often well below the level at which humans conceptualize actions. We present a sequential pattern mining approach to discovering human-level actions-action idioms — from instrumentation logs of lower-level events. To support validation by a human expert, idiom discovery is designed to maximize recall, with filtering heuristics applied to help eliminate false positives. Empirical evaluation on data from a fielded application shows the promise of the approach for the automatic discovery of action idioms.",
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"abstract": "Assisting teams of knowledge workers achieve common strategic and tactical goals is becoming an increasing priority as information analysis tasks become more complex. Tools to monitor and support individual workers, such as TaskTracer, demonstrated the potential for assisting individuals but there is a lack of tools for analyzing workflows and information needs at a collaborative level within enterprises. Providing assistance for collaboration is a current priority for the new generation of `smart digital assistants' and presents unique challenges, in terms of associating collective goals with user activities in way that minimizes disruption to the user's workflow, and in generating useful summaries. To address these challenges, we have developed `Journaling' interfaces to: capture a user or team's tasks and goals, associate them with information artifacts, assist in information recall, and display aggregate visualizations. These interfaces are supported by a passive instrumentation platform that aims to monitor user's consented activities in a minimally intrusive manner, including interactions with various applications, documents and URLs as part of collaborative workflows. We have deployed these interfaces in a production environment using heterogeneous workflows performed by groups of students and intelligence analysts. Evaluations based on user interviews and engagement metrics suggest that our approach is useful for understanding and supporting user collaboration, as well as being easy to work with and suitable for continuous use. In addition, the data gathered provides situational awareness for individuals, teams, educators and managers. Through our platform, we are enabling continuous collection of labelled user activity logs and document corpora that are enabling further research in this nascent field.",
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"content": "Context: There is growing interest in establishing software engineering as an evidence-based discipline. To that end, replication is often used to gain confidence in empirical findings, as opposed to reproduction where the goal is showing the correctness, or validity of the published results. Objective: To consider what is required for a replication study to confirm the original experiment and apply this understanding in software engineering. Method: Simulation is used to demonstrate why the prediction interval for confirmation can be surprisingly wide. This analysis is applied to three recent replications. Results: It is shown that because the prediction intervals are wide, almost all replications are confirmatory, so in that sense there is no 'replication crisis', however, the contributions to knowledge are negligible. Conclusion: Replicating empirical software engineering experiments, particularly if they are under-powered or under-reported, is a waste of scientific resources. By contrast, meta-analysis is strongly advocated so that all relevant experiments are combined to estimate the population effect.",
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"abstract": "Sizing and shape structural optimization problems are normally stated in terms of a minimum weight approach with constraints that limit the maximum allowable stresses and displacements. However, topology structural optimization problems have been usually stated in terms of a maximum stiffness (minimum compliance) approach. In this kind of formulations, while no stress or displacement constraints are taken into account. Moreover in some FEM minimum weight topology optimization method with stress constraints formulation, transferred stress constraint functions cannot completely embody stress constraint requirements. In this paper, we build an equivalent optimization model for the topological optimization problem with the objective function being the structural weight and only stress constraints. In this model all element stress constraints of the structure being optimized under a load case are replaced by its most potential active stress constraint and average stress constraint. In order to make the stress constraint approximations hold true during an optimization process, we propose a solving strategy of varying stress limits. And a set of stress sensitivity formulation is derived and a new topology optimization method is developed and implemented. Several simulation examples show that stress sensitivity computation cost may be greatly reduced and there is not any objective oscillation phenomenon, and verify that the proposed method is of validity and effectiveness.",
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"content": "Sizing and shape structural optimization problems are normally stated in terms of a minimum weight approach with constraints that limit the maximum allowable stresses and displacements. However, topology structural optimization problems have been usually stated in terms of a maximum stiffness (minimum compliance) approach. In this kind of formulations, while no stress or displacement constraints are taken into account. Moreover in some FEM minimum weight topology optimization method with stress constraints formulation, transferred stress constraint functions cannot completely embody stress constraint requirements. In this paper, we build an equivalent optimization model for the topological optimization problem with the objective function being the structural weight and only stress constraints. In this model all element stress constraints of the structure being optimized under a load case are replaced by its most potential active stress constraint and average stress constraint. In order to make the stress constraint approximations hold true during an optimization process, we propose a solving strategy of varying stress limits. And a set of stress sensitivity formulation is derived and a new topology optimization method is developed and implemented. Several simulation examples show that stress sensitivity computation cost may be greatly reduced and there is not any objective oscillation phenomenon, and verify that the proposed method is of validity and effectiveness.",
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"abstract": "Curve extension is a useful function in shape modeling for cyber worlds, while a ball B-spline curve (BBSC) has its advantages in representing freeform tubular objects. In this paper, an extension algorithm for ball B-Spline curve with G2-continuity is investigated. We apply the extending method of B-Spline curves to the center curve of BBSC through generalizing a minimal strain energy method from 2D to 3D. And the initial value of G2-continuity parameter was selected by minimizing the approximate energy function which is a problem with O(1) time complexity. The corresponding scalar function of control balls is determined through applying G2-continuity condition to scalar function. In order to ensure the radii of the control balls are positive, we make a decision about the range of the G2-continuity parameter and then determine it by minimizing the strain energy in the affected area. Some experiments for comparing our method with other methods are given. The results show our method for extending BBSC is effective.",
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"content": "Curve extension is a useful function in shape modeling for cyber worlds, while a ball B-spline curve (BBSC) has its advantages in representing freeform tubular objects. In this paper, an extension algorithm for ball B-Spline curve with G2-continuity is investigated. We apply the extending method of B-Spline curves to the center curve of BBSC through generalizing a minimal strain energy method from 2D to 3D. And the initial value of G2-continuity parameter was selected by minimizing the approximate energy function which is a problem with O(1) time complexity. The corresponding scalar function of control balls is determined through applying G2-continuity condition to scalar function. In order to ensure the radii of the control balls are positive, we make a decision about the range of the G2-continuity parameter and then determine it by minimizing the strain energy in the affected area. Some experiments for comparing our method with other methods are given. The results show our method for extending BBSC is effective.",
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"abstract": "The L_2-norm method is often used in the multi-degree reduction problem of Bezier curves, which achieves an approximation order of m+1 by using polynomials of degree m. This paper presents a tangent method for achieving a higher approximation order, in which a system of linear equations in the unknown control points of the resulting approximation Bezier curve is derived. Given the degrees of the given and the approximation Bezier curves, i.e., n and m, the control points of the approximation curve can be explicitly expressed. In principle, when the given Bezier curve geometrically coincides with a cubic Bezier curve, the new method can exactly recover the cubic Bezier curve. Numerical examples show that the new method can achieve a better approximation effect than that of the L_2-norm method for degree reduction.",
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"title": "Modelling and Simulation of Weft Knitted Fabric Based on Ball B-Spline Curves and Hooke's Law",
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"abstract": "With the development of computer techniques and computer graphics, computer aided design (CAD) technology has been applied widely in the textile printing industry. There are many good methods for simulating weft knitted fabric, however, no work on knitted fabric had been performed using ball B-spline curves. In this paper, we have proposed a novel algorithm based on ball B-spline curves and Hooke's Law for modelling weft knitted fabric in 3D. Ball B-spline curves are based on B-spline curves that use data balls instead of data points. By changing the position and the radius of balls of the ball B-spline curves, we can change the thickness and position of the yarn. The loop is the basic unit of knitted fabric, it requires 7 data points to be represented by a ball B-spline curve, and the model is notably fast. At the same time, the model maintains both its accuracy and the geometrical and topological features of the fabric. With VC++ and Open GL, we added texture and light to simulate different patterns of weft knitted fabric in 3D, including stockinette knit, garter knit, 2-2 rib knit, wing knit, heart knit and stripe knit. Because of the nested structure of knitted fabric, each data point of each loop has changes in a different way when a force is applied to the knitted fabric. The deformation and force on the knitted fabric is modelled using Hooke's Law, which results in a more realistic and faster simulation. We use the parameterization method, and the parameters, such as the radius of ball, the height of a loop, the number of courses, the number of wales and the magnitude of the force, are easy to change. This method is a new means of naturally building and simulating weft knitted fabric in a CAD system.",
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"abstract": "Curve blending is an essential task in geometric modeling, while a ball B-spline curve (BBSC) has its advantages in representing freeform tubular objects. This paper proposes a blending algorithm for ball B-Spline curve with G2 continuity, which is used to describe the smoothness of the joint point. An original BBSC is extended smoothly to join another one, such that no additional blending curve is created and the two original curves are not changed. The shape of the extended curve is then determined by minimizing strain energy. The corresponding scalar function of the control balls is determined through applying G2-continuity conditions to the scalar function. In order to ensure the radii of the control balls are positive, we make a decision about the range of the G2-continuity parameter and then determine it by minimizing the strain energy in the affected area. The experiment results demonstrate our method for blending BBSC is effective. Moreover, some G2 blending results of the BBSC in simulating the tubular objects are given.",
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"title": "IFQ: a visual query interface and query generator for object-based media retrieval",
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"abstract": "There are two major directions for image retrieval system development. The first direction is the direct manipulation of information using query languages, which are precise to computers but not user friendly. The second direction is the development of natural interfaces, such as query by image example. The latter approach has the advantage of better query visualization, but it usually yields a low precision because users' drawings may not be precise. IFQ (In Frame Query) is a visual user query interface for object-based media retrieval systems. It aims at not only providing a natural visual query interface but also supporting precise direct manipulation through automated query generation. Furthermore, IFQ gives users the flexibility of using combinations of semantic expressions, conceptual definitions, sketch, and image examples to pose queries.",
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"abstract": "Improvements in genome sequencing technology over the past decade have driven down sequencing costs faster than Moore's Law producing a genome sequencing boom [9]. Accelerated rates of complete genome sequence production are particularly evident in bacterial genomics, where small genome sizes enable rapid and inexpensive sequencing. These large volumes of complete genome sequences have given researchers a new approach to the longstanding challenge of identifying and characterizing novel bacterial genes: comparative gene neighborhood analysis. Due to unique properties in bacterial genome organization, researchers believe that it is possible to generate hypotheses around the function and pathway membership of novel genes by examining the neighborhood around gene orthologs, or genes with highly similar sequences. Visual approaches to this problem are necessary, since subtle patterns and relationships can be missed through automated approaches, but current comparative gene neighborhood visualizations are only designed to accomodate comparisons across 2–9 genomes in a single view ( [8, 4, 6, 5, 2, 7, 3]).",
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"abstract": "Most common complex traits are affected by multiple genes and/or environmental factors. To understand genetic architecture of complex traits, the investigation of gene-gene and gene-environment interactions can be essential. However, conducting gene-gene interaction using genome-wide data requires exploring a huge search space and suffers from a computation burden due to high dimensionality of genetic data. To identify gene-gene interaction more efficiently, we propose a gene-based reduction method which first summarizes the gene effect by combining multiple single nucleotide polymorphism (SNP) and then performs the gene-gene interaction via the summarized gene effect. By reducing the search space from SNPs to gene, our gene-based method becomes efficient and fast for identifying gene-gene interaction in genome wide association studies. The gene-based reduction method is illustrated by hypertension data from a Korean population.",
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"Genomics",
"Hypertension",
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"Diseases",
"Logistics",
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"fullName": "Sohee Oh",
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"title": "Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference",
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"title": "Gene recovery of two genome-filtration sequencing techniques when applied to the maize genome",
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"abstract": "The large size of the maize genome and the expectation that most of the genome is represented by repetitive elements is a challenge to standard genome sequencing techniques. Genome-filtration sequencing techniques may target gene-rich regions in the genome. Two such approaches, methylation filtration and high Cot selection, may provide rapid and cost-effective alternative to sequencing the maize genome. Approximately 450k sequence reads have been obtained from both methylation filtration (MF) and high Cot (HC) libraries, and these sequences have been clustered and assembled. An analysis was undertaken to examine whether MF and MC enrich for maize genes and target non-identical sequence space. Simple sequence repeat analysis and mapped marker coverage provide gauges to examine whether MF and HC sample identical sequence space. Marker hits also provide evidence that MF and HC enrich for unique genic portions of the genome. Finally, the identification of maize and other protein sequences in the MF and HC sequence sets can indicate the expected fraction and coverage of the maize gene space by MF and HC.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The large size of the maize genome and the expectation that most of the genome is represented by repetitive elements is a challenge to standard genome sequencing techniques. Genome-filtration sequencing techniques may target gene-rich regions in the genome. Two such approaches, methylation filtration and high Cot selection, may provide rapid and cost-effective alternative to sequencing the maize genome. Approximately 450k sequence reads have been obtained from both methylation filtration (MF) and high Cot (HC) libraries, and these sequences have been clustered and assembled. An analysis was undertaken to examine whether MF and MC enrich for maize genes and target non-identical sequence space. Simple sequence repeat analysis and mapped marker coverage provide gauges to examine whether MF and HC sample identical sequence space. Marker hits also provide evidence that MF and HC enrich for unique genic portions of the genome. Finally, the identification of maize and other protein sequences in the MF and HC sequence sets can indicate the expected fraction and coverage of the maize gene space by MF and HC.",
"__typename": "ArticleAbstractType"
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],
"normalizedAbstract": "The large size of the maize genome and the expectation that most of the genome is represented by repetitive elements is a challenge to standard genome sequencing techniques. Genome-filtration sequencing techniques may target gene-rich regions in the genome. Two such approaches, methylation filtration and high Cot selection, may provide rapid and cost-effective alternative to sequencing the maize genome. Approximately 450k sequence reads have been obtained from both methylation filtration (MF) and high Cot (HC) libraries, and these sequences have been clustered and assembled. An analysis was undertaken to examine whether MF and MC enrich for maize genes and target non-identical sequence space. Simple sequence repeat analysis and mapped marker coverage provide gauges to examine whether MF and HC sample identical sequence space. Marker hits also provide evidence that MF and HC enrich for unique genic portions of the genome. Finally, the identification of maize and other protein sequences in the MF and HC sequence sets can indicate the expected fraction and coverage of the maize gene space by MF and HC.",
"fno": "01332509",
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"Proteins",
"Molecular Biophysics",
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"Pattern Clustering",
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"High Cot Selection",
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"authors": [
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"affiliation": "Donald Danforth Plant Sci. Center, Saint Louis, MO, USA",
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"fullName": "Li Zheng",
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"title": "Toward a Network-Based Approach to Modeling Epistatic Interactions in Genome-Wide Association Studies",
"normalizedTitle": "Toward a Network-Based Approach to Modeling Epistatic Interactions in Genome-Wide Association Studies",
"abstract": "In genome-wide association studies, statistical procedures such as logistic regression or the Cochran-Armitage test for trend can be used for the analysis of genetic variants while taking the underlying genetic model into consideration. Should a researcher was to investigate the role played by the interaction between two or more of these genetic variants (epistasis), it would suffice to add an interaction term, which corresponds to their product, to a logistic regression model. However, we question whether such a model is able to capture the intricacy of the genetic architecture in complex traits. Therefore, this paper proposes a network-based model that allows graph theory to characterize both genetic variants and their interactions in a genome-wide context, including a simulation study that proves its applicability.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In genome-wide association studies, statistical procedures such as logistic regression or the Cochran-Armitage test for trend can be used for the analysis of genetic variants while taking the underlying genetic model into consideration. Should a researcher was to investigate the role played by the interaction between two or more of these genetic variants (epistasis), it would suffice to add an interaction term, which corresponds to their product, to a logistic regression model. However, we question whether such a model is able to capture the intricacy of the genetic architecture in complex traits. Therefore, this paper proposes a network-based model that allows graph theory to characterize both genetic variants and their interactions in a genome-wide context, including a simulation study that proves its applicability.",
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"normalizedAbstract": "In genome-wide association studies, statistical procedures such as logistic regression or the Cochran-Armitage test for trend can be used for the analysis of genetic variants while taking the underlying genetic model into consideration. Should a researcher was to investigate the role played by the interaction between two or more of these genetic variants (epistasis), it would suffice to add an interaction term, which corresponds to their product, to a logistic regression model. However, we question whether such a model is able to capture the intricacy of the genetic architecture in complex traits. Therefore, this paper proposes a network-based model that allows graph theory to characterize both genetic variants and their interactions in a genome-wide context, including a simulation study that proves its applicability.",
"fno": "1710a225",
"keywords": [
"Association",
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"Epistatic Interactions",
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"affiliation": null,
"fullName": "Camilo Palazuelos",
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"abstract": "The knowledge about the skeleton of a given geometric shape has many practical applications such as shape animation, shape comparison, shape recognition, and estimating structural strength. Skeleton extraction becomes a more challenging problem when the topology is represented in point cloud domain. In this paper, we present the network architecture, PSPU-SkelNet, for TeamPH which ranked 3rd in Point SkelNetOn 2019 challenge. PSPU-SkelNet is a pyramid of three U-Nets that predicts the skeleton from a given shape point cloud. PSPU-SkelNet achieves a Chamfer Distance (CD) of 2.9105 on the final test dataset. The code of PSPU SkelNet is available at https://github.com/roatienza/skelnet.",
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"abstract": "A method of encoding monochrome video sequences is presented. This method is applicable to slow-moving scenes with a zoom factor close to unity. It incorporates a perceptual model for the detection and tracking of image blocks perceived to be in apparent motion. The perceptual model is a threshold model based on contrast. Weber fractions in the spatiotemporal domain are used to set the threshold for the detection of motion. The threshold is determined on a scene-adaptive basis. The information content of the scene is derived from the spectral distribution of image data and the masking characteristics of the human visual system. The perceptual model is used in the block-classification process, which in turn determines the coding strategy used for each block type. The discrete cosine transform is used for encoding image blocks which have changed beyond a perceptual threshold. A comparison of the perceptually encoded image sequence with that using no perceptual model indicates substantially improved quality and performance of the perceptual encoder for compression ratios up to 100:1.<>",
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"abstract": "We describe a generalized shape-axis (SA) model for representing both open and closed planar curves. The SA model is an effective way to represent shapes by comparing their self-similarities. Given a 2D shape, whether it is closed or open, we use two different parameterizations (one parameterization is oriented clockwise and the other counterclockwise) for the curve. To study the self-similarity, the two parameterizations are matched to each other via a variational framework, where the self-similarity criterion is to be defined depending on the class of shapes and human perception factors. Useful self-similarity criteria include symmetry, parallelism and convexity, and so forth. A match is allowed to have discontinuities, and a dynamic programming algorithm can compute the optimal match in O(N4) time, where N is the size of the shape. We use a grouping process for the shape axis to construct a unique SA-tree, however, when a planar shape is open, it is possible to derive an SA-forest. The generalized SA model provides a compact and informative way for 2D shape representation.",
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"abstract": "An axiomatization of the isomorphisms that hold in all Cartesian closed categories (CCCs), discovered independently by S.V. Soloviev (1983) and by K.B. Bruce and G. Longo (1985), leads to seven equalities. It is shown that the unification problem for this theory is undecidable, thus setting an open question. It is also shown that an important subcase, namely unification modulo the linear isomorphisms, is NP-complete. Furthermore, the problem of matching in CCCs is NP-complete when the subject term is irreducible. CCC-matching and unification form the basis for an elegant and practical solution to the problem of retrieving functions from a library indexed by types investigated by M. Rittri (1990, 1991). It also has potential applications to the problem of polymorphic higher-order unification, which in turn is relevant to theorem proving, logic programming, and type reconstruction in higher-order languages.<>",
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"abstract": "In this paper we analyze the effectiveness of Prevoyant, a planning-based computational model of surprise arousal suggested in our previous paper. This evaluation was performed by measuring the effect of stories produced by this method on several factors contributing to surprise in narratives (e.g., expectation failures, the importance of story events, the emotional valence of a reader, and resolution) and their relation to story interest. To measure the ratings of a reader's surprise and story interest, we conducted a pilot study, where three different discourse types - chronological, flashback, and flashback with foreshadowing - were compared. A one-way ANOVA and a priori pair-wise comparisons confirmed that the mean ratings of surprise and interestingness increased at the .01 and .05 level, respectively. While the number of subjects in this study was relatively small, the significance of our results argues for support to the claim that the computational model we evaluated can effectively manipulate readers' sense of surprise in their experience of a narrative.",
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"content": "In this paper we analyze the effectiveness of Prevoyant, a planning-based computational model of surprise arousal suggested in our previous paper. This evaluation was performed by measuring the effect of stories produced by this method on several factors contributing to surprise in narratives (e.g., expectation failures, the importance of story events, the emotional valence of a reader, and resolution) and their relation to story interest. To measure the ratings of a reader's surprise and story interest, we conducted a pilot study, where three different discourse types - chronological, flashback, and flashback with foreshadowing - were compared. A one-way ANOVA and a priori pair-wise comparisons confirmed that the mean ratings of surprise and interestingness increased at the .01 and .05 level, respectively. While the number of subjects in this study was relatively small, the significance of our results argues for support to the claim that the computational model we evaluated can effectively manipulate readers' sense of surprise in their experience of a narrative.",
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"abstract": "This paper presents an examination of augmented reality (AR) as a rising form of interactive narrative that combines computer-generated elements with reality, fictional with non-fictional objects, in the same immersive experience. Based on contemporary theory in narratology, we propose to view this blending of reality worlds as a metalepsis, a transgression of reality and fiction boundaries, and argue that authors could benefit from using existing conventions of narration to emphasize the transgressed boundaries, as is done in other media. Our contribution is three-fold, first we analyze the inherent connection between narrative, immersion, interactivity, fictionality and AR using narrative theory, and second we comparatively survey actual works in AR narratives from the past 15 years based on these elements from the theory. Lastly, we postulate a future for AR narratives through the perspective of the advancing technologies of both interactive narratives and AR.",
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"abstract": "This paper proposes the progressive attention memory network (PAMN) for movie story question answering (QA). Movie story QA is challenging compared to VQA in two aspects: (1) pinpointing the temporal parts relevant to answer the question is difficult as the movies are typically longer than an hour, (2) it has both video and subtitle where different questions require different modality to infer the answer. To overcome these challenges, PAMN involves three main features: (1) progressive attention mechanism that utilizes cues from both question and answer to progressively prune out irrelevant temporal parts in memory, (2) dynamic modality fusion that adaptively determines the contribution of each modality for answering the current question, and (3) belief correction answering scheme that successively corrects the prediction score on each candidate answer. Experiments on publicly available benchmark datasets, MovieQA and TVQA, demonstrate that each feature contributes to our movie story QA architecture, PAMN, and improves performance to achieve the state-of-the-art result. Qualitative analysis by visualizing the inference mechanism of PAMN is also provided.",
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"abstract": "Inspired by the remarkable advances in video analytics, research teams are stepping towards a greater ambition - movie understanding. However, compared to those activity videos in conventional datasets, movies are significantly different. Generally, movies are much longer and consist of much richer temporal structures. More importantly, the interactions among characters play a central role in expressing the underlying story. To facilitate the efforts along this direction, we construct a dataset called Movie Synopses Associations (MSA) over 327 movies, which provides a synopsis for each movie, together with annotated associations between synopsis paragraphs and movie segments. On top of this dataset, we develop a framework to perform matching between movie segments and synopsis paragraphs. This framework integrates different aspects of a movie, including event dynamics and character interactions, and allows them to be matched with parsed paragraphs, based on a graph-based formulation. Our study shows that the proposed framework remarkably improves the matching accuracy over conventional feature-based methods. It also reveals the importance of narrative structures and character interactions in movie understanding. Dataset and code are available at: https://ycxioooong.github.io/projects/moviesyn.",
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"abstract": "Procedural story generation (PCG) tailors a unique narrative experience for a player and can be accomplished via multiple techniques, from matching storylets to grammar-based generation. There exists a rich opportunity for evolutionary algorithms to be applied to this domain for intelligently constructing game narratives. This paper describes a conceptual procedure for applying genetic improvement to a grammar-driven procedural narrative within the context of a browser-based game.",
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"abstract": "Video entity linking, which connects online videos to the related entities in a semantic knowledge base, can enable a wide variety of video based applications including video retrieval and video recommendation. Most existing systems for video entity linking rely on video metadata. In this paper, we propose to exploit video visual content to improve video entity linking. In the proposed framework, videos are first linked to entity candidates using a text-based method. Next, the entity candidates are verified and reranked according to visual content. In order to properly handle large variations in visual content matching, we propose to use Multiple Instance Metric Learning to learn a \"set to sequence\" metric for this specific matching problem. To evaluate the proposed framework, we collect and annotate 1912 videos crawled from the YouTube open API. Experiment results have shown consistent gains by the proposed framework over several strong baselines.",
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"content": "We propose a new halftoning approach that ensures the average graylevels in a grayscale image to be equal to that of a halftone over corresponding local neighborhoods, where the neighborhoods are taken with respect to a quad-tree structure. The halftoning algorithm first determines the total number of black and white dots in the entire halftone using a global mean requirement. It then distributes the dots to various local neighborhoods of the halftone using a multiscale dot distribution technique over the nodes of a quad-tree. We show that such a halftoning method produces high quality halftones particularly in the rendering of details.",
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"abstract": "VFD (Vacuum Fluorescent Display) dot-matrix display module GU160X32-800B can display the character, Chinese and the figure. Its displaying dot-matrix has 160*32 dots and has some advantages, such as convenient application, higher brightness and being regulated. In this paper, the basic theory of GU160X32-800B is introduced and the methods of designing its hardware and programming its software.",
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"content": "VFD (Vacuum Fluorescent Display) dot-matrix display module GU160X32-800B can display the character, Chinese and the figure. Its displaying dot-matrix has 160*32 dots and has some advantages, such as convenient application, higher brightness and being regulated. In this paper, the basic theory of GU160X32-800B is introduced and the methods of designing its hardware and programming its software.",
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"abstract": "Coordinated multiple view (CMV) approaches have become commonplace in the development of visual tools for information visualization and visual analytics. However, research and development in CMV has focused almost exclusively on the exploratory and analytic needs of individual users working in traditional interactive desktop environments. Current understanding of collaboration in terms of perception, interaction, conceptualization, and social organization begs for integrated approaches to exploration and analysis that support visualization of information in multiple coordinated views by multiple actors working across time and space in multiple roles and environments. This statement outlines two key aspects of a possible strategy for achieving acquisition, exploration, communication, and management of information in a collaborative exploratory visualization environment built on top of a solid foundation of well-established CMV techniques.",
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"title": "2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
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"abstract": "We present SPARVIS, a conceptual framework that combines the strength of both AR and smartphones to enhance visual data analyt-ics. The framework uses AR to display coordinated visualizations and a smartphone to interact with and organize them. This design enables users to take advantage of their surrounding space to exter-nalize and organize their intermediate analysis results in an AR environment and manipulate the visualizations via familiar smartphone interactions. We identify four interactions that are fundamental to vi-sual analytics tasks and propose alternative implementations of these techniques in the SPARVIS framework following existing design guidelines. We run an empirical evaluation to quantitatively test the efficiency and physical demand of two alternative implementations of the “click” mechanism (the most fundamental one among the four) and provide design suggestions based on the study result. We further develop a prototype application based on the framework to illustrate SPARVIS's usage and conduct a user study with 22 participants to validate its usability. Based on the finding, we provide implications for research and design of integrating AR and smartphone for visual data analytics.",
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"content": "We present SPARVIS, a conceptual framework that combines the strength of both AR and smartphones to enhance visual data analyt-ics. The framework uses AR to display coordinated visualizations and a smartphone to interact with and organize them. This design enables users to take advantage of their surrounding space to exter-nalize and organize their intermediate analysis results in an AR environment and manipulate the visualizations via familiar smartphone interactions. We identify four interactions that are fundamental to vi-sual analytics tasks and propose alternative implementations of these techniques in the SPARVIS framework following existing design guidelines. We run an empirical evaluation to quantitatively test the efficiency and physical demand of two alternative implementations of the “click” mechanism (the most fundamental one among the four) and provide design suggestions based on the study result. We further develop a prototype application based on the framework to illustrate SPARVIS's usage and conduct a user study with 22 participants to validate its usability. Based on the finding, we provide implications for research and design of integrating AR and smartphone for visual data analytics.",
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"affiliation": "Arizona State University",
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