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"doi": "10.1109/ICDAR.1995.599047",
"title": "Automatic recognition of facility drawings and street maps utilizing the facility management database",
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"abstract": "This paper proposes a new approach for inputting handwritten Distribution Facility Drawings (DFD) and their maps into a computer automatically by using the Facility Management Database (FMD). Our recognition method makes use of external information for drawing/map recognition. It identifies each electric-pole symbol and support cable symbol on drawings simply by consulting the FMD. Other symbols such as transformers and electric wires can be placed on drawings automatically. When a contradiction is unsolved due to an inconsistency between the content of the DFD and the FMD, the system requests a manual feedback from the operator. Furthermore, it uses the distribution network of the DFD to recognize the sheet lines on the maps. This can drastically reduce the cost for computerizing drawings and maps.",
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"content": "This paper proposes a new approach for inputting handwritten Distribution Facility Drawings (DFD) and their maps into a computer automatically by using the Facility Management Database (FMD). Our recognition method makes use of external information for drawing/map recognition. It identifies each electric-pole symbol and support cable symbol on drawings simply by consulting the FMD. Other symbols such as transformers and electric wires can be placed on drawings automatically. When a contradiction is unsolved due to an inconsistency between the content of the DFD and the FMD, the system requests a manual feedback from the operator. Furthermore, it uses the distribution network of the DFD to recognize the sheet lines on the maps. This can drastically reduce the cost for computerizing drawings and maps.",
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"Electricity Supply Industry Cartography Feature Extraction Image Recognition Facility Drawings Street Maps Facility Management Database Handwritten Distribution Facility Drawings Recognition Method Map Recognition Electric Pole Symbol Support Cable Symbol"
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"affiliation": "Dept. of Inf. Sci., Central Res. Inst. of Electr. Power Ind., Tokyo, Japan",
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"abstract": "A system for the automatic placement of names on cadastral maps, using a method which, because of its generality, can be easily applied to other types of maps is presented. The method is based on a robust algorithm that, after having detected character strings on the original paper map, encases them with rectangles, and searches for the most convenient location where to place such rectangles on the computer version of the map. The system is part of an operative package working to feed the GIS of the Italian Land Register by means of the automatic interpretation of cadastral maps. Results obtained on a sample set of more than 100 maps are reported.<>",
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"content": "A system for the automatic placement of names on cadastral maps, using a method which, because of its generality, can be easily applied to other types of maps is presented. The method is based on a robust algorithm that, after having detected character strings on the original paper map, encases them with rectangles, and searches for the most convenient location where to place such rectangles on the computer version of the map. The system is part of an operative package working to feed the GIS of the Italian Land Register by means of the automatic interpretation of cadastral maps. Results obtained on a sample set of more than 100 maps are reported.<>",
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"proceeding": {
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"title": "Proceedings of 3rd International Conference on Document Analysis and Recognition",
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"volume": "2",
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"year": "1995",
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"article": {
"id": "12OmNxu6p8d",
"doi": "10.1109/ICDAR.1995.602054",
"title": "Recursive morphological sieve method for searching pictorial point symbols on maps",
"normalizedTitle": "Recursive morphological sieve method for searching pictorial point symbols on maps",
"abstract": "Point symbols on a map represent interesting and significant positional data, such as airports, ski areas and natural parks. Identification of point symbols and finding their positions are important for automatic map understanding. Point symbols on maps may partially overlap on each other. More often they are touched or connected by line symbols, and their background consists of colored and/or textured regions. In this situation, a straightforward morphological template matching method is not feasible. A new partial ordering method for aligning pictorial point symbols which is based on the relationship of K-tolerance covering and a new general method for searching pictorial point symbols on maps, the recursive morphological sieve method, are described. The main ideas of this new method include (1) finding the coverings of the kernels of a symbol instead of the symbol itself, (2) morphologically preprocessing maps to form multi-level sieves, (3) using the sieves to screen out symbol kernels, and (4) renewing sieves during a recursive screening process. This method may also be used to recognize pictorial point symbols on other types of documental files.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Point symbols on a map represent interesting and significant positional data, such as airports, ski areas and natural parks. Identification of point symbols and finding their positions are important for automatic map understanding. Point symbols on maps may partially overlap on each other. More often they are touched or connected by line symbols, and their background consists of colored and/or textured regions. In this situation, a straightforward morphological template matching method is not feasible. A new partial ordering method for aligning pictorial point symbols which is based on the relationship of K-tolerance covering and a new general method for searching pictorial point symbols on maps, the recursive morphological sieve method, are described. The main ideas of this new method include (1) finding the coverings of the kernels of a symbol instead of the symbol itself, (2) morphologically preprocessing maps to form multi-level sieves, (3) using the sieves to screen out symbol kernels, and (4) renewing sieves during a recursive screening process. This method may also be used to recognize pictorial point symbols on other types of documental files.",
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"normalizedAbstract": "Point symbols on a map represent interesting and significant positional data, such as airports, ski areas and natural parks. Identification of point symbols and finding their positions are important for automatic map understanding. Point symbols on maps may partially overlap on each other. More often they are touched or connected by line symbols, and their background consists of colored and/or textured regions. In this situation, a straightforward morphological template matching method is not feasible. A new partial ordering method for aligning pictorial point symbols which is based on the relationship of K-tolerance covering and a new general method for searching pictorial point symbols on maps, the recursive morphological sieve method, are described. The main ideas of this new method include (1) finding the coverings of the kernels of a symbol instead of the symbol itself, (2) morphologically preprocessing maps to form multi-level sieves, (3) using the sieves to screen out symbol kernels, and (4) renewing sieves during a recursive screening process. This method may also be used to recognize pictorial point symbols on other types of documental files.",
"fno": "71280931",
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"Cartography Document Image Processing Edge Detection Image Segmentation Identification Recursive Morphological Sieve Method Pictorial Point Symbol Searching Maps Positional Data Point Symbol Identification Automatic Map Understanding Line Symbols Colored Regions Textured Regions Morphological Template Matching Method Partial Ordering Method K Tolerance Covering Symbol Kernel Covering Morphologically Preprocessed Maps Multi Level Sieves Screened Out Symbol Kernels Sieve Renewal Recursive Screening Process Pictorial Point Symbol Recognition Documental Files"
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"authors": [
{
"affiliation": "Dept. of Comput. Sci., Memorial Univ. of Newfoundland, St. John's, Nfld., Canada",
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"title": "Map Creations with OpenStreetMap for RoboCupRescue Simulation",
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"abstract": "In this paper, we discuss map creation for the RoboCupRescue Simulation (RRS) disaster relief simulator, which is a multi-agent testbed for representing large-scale natural urban disasters and rescue activities. The RRS needs map data for various regions because this is important for the disaster relief simulator to enable simulations in these regions. However, RRS currently only provides a few maps because its map creation tool is not adequate for creating the maps of various regions. Therefore, we investigated the reason for the tool being inadequate and we propose a new map creation tool for the RRS based on the results of our investigation. Finally, we confirmed the effectiveness of the tool with many created maps.",
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"content": "In this paper, we discuss map creation for the RoboCupRescue Simulation (RRS) disaster relief simulator, which is a multi-agent testbed for representing large-scale natural urban disasters and rescue activities. The RRS needs map data for various regions because this is important for the disaster relief simulator to enable simulations in these regions. However, RRS currently only provides a few maps because its map creation tool is not adequate for creating the maps of various regions. Therefore, we investigated the reason for the tool being inadequate and we propose a new map creation tool for the RRS based on the results of our investigation. Finally, we confirmed the effectiveness of the tool with many created maps.",
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"abstract": "Association rules mining methods have been recently applied to gene expression data analysis to reveal relationships between genes and different conditions and features. However, not much effort has focused on detecting the relation between gene expression maps and related gene functions. Here we describe such an approach to mine association rules among gene functions in clusters of similar gene expression maps on mouse brain. The experimental results show that the detected association rules make sense biologically. By inspecting the obtained clusters and the genes having the gene functions of frequent itemsets, interesting clues were discovered that provide valuable insight to biological scientists. Moreover, discovered association rules can be potentially used to predict gene functions based on similarity of gene expression maps.",
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"content": "Association rules mining methods have been recently applied to gene expression data analysis to reveal relationships between genes and different conditions and features. However, not much effort has focused on detecting the relation between gene expression maps and related gene functions. Here we describe such an approach to mine association rules among gene functions in clusters of similar gene expression maps on mouse brain. The experimental results show that the detected association rules make sense biologically. By inspecting the obtained clusters and the genes having the gene functions of frequent itemsets, interesting clues were discovered that provide valuable insight to biological scientists. Moreover, discovered association rules can be potentially used to predict gene functions based on similarity of gene expression maps.",
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"affiliation": "Dept. of Comput.&Inf. Sci., Temple Univ., Philadelphia, PA, USA",
"fullName": "Li An",
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"affiliation": "Center for Inf. Sci.&Technol., Temple Univ., Philadelphia, PA, USA",
"fullName": "Z. Obradovic",
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"affiliation": "Dept. of Mol.&Med. Pharmacology, UCLA, CA, USA",
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"affiliation": "Lister Hill Nat. Center for Biomed. Commun., U.S. Nat. Libr. of Med., Washington, DC, USA",
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"affiliation": "Dept. of Comput.&Inf. Sci., Temple Univ., Philadelphia, PA, USA",
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"abstract": "Nowadays, technology and technological diversity of the gene expression measurements raise new issues related to proper data analysis and accurate interpretation of results. Because gene expression measurement includes many complex steps and is performed on randomly selected cells from population, the measured value of gene expression is a stochastic variable, and may vary in wide range. Consequently, based on gene expression values it is hard to distinguish the genes associated with condition of interest from those none-associated. Thepresent articleis focused on theoretical justification ofthe mentioned problemand proposesa solutionthrough complementing of data-driven analysis with knowledge-based approaches.",
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"abstract": "One of the important goals in the post-genomic era is to identify the functions of genes, either individually or as group. Recently, there has been an increasing use of the gene ontology (GO) to analyze a list of genes identified via various statistical and/or computational methods. The main assumption behind using GO for interpreting microarray data is that the genes that belong to similar molecular functions or biological processes would display similarly tightly regulated expression patterns. Current methods utilize GO after the statistical analysis of gene expression data. In this paper, we describe a method that utilizes both gene expression values and biological knowledge simultaneously to identify the significant biological functions. The method is different from other methods in that it incorporates GO as prior knowledge into the mining of gene expression data. The method has been applied to the gene expression profiles to cell cycle experiments",
"abstracts": [
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"content": "One of the important goals in the post-genomic era is to identify the functions of genes, either individually or as group. Recently, there has been an increasing use of the gene ontology (GO) to analyze a list of genes identified via various statistical and/or computational methods. The main assumption behind using GO for interpreting microarray data is that the genes that belong to similar molecular functions or biological processes would display similarly tightly regulated expression patterns. Current methods utilize GO after the statistical analysis of gene expression data. In this paper, we describe a method that utilizes both gene expression values and biological knowledge simultaneously to identify the significant biological functions. The method is different from other methods in that it incorporates GO as prior knowledge into the mining of gene expression data. The method has been applied to the gene expression profiles to cell cycle experiments",
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"fno": "04015797",
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"abstract": "In this paper, we present a graph search approach for identifying arbitrarily complex structural genomic variation. Our method leverages the ability of long reads (e.g. from Pacific Biosciences platforms) to span multiple breakpoints of complicated local rearrangements, allowing us to resolve small-scale complexities that may be overlooked by other tools. We applied our method to a subset of NA12878 germline events using two long read datasets and demonstrate, with a concordance rate of 88.4% between the two sets, an increased ability to denote complex events over baseline calls from short read data. In a majority of the regions analyzed we detected small complexities that flank the breakpoints of larger events, including small insertions, inversions, and duplicated sequences. These patterns of complexity match known mechanisms associated with DNA replication and structural variant formation, and showcase the ability of our approach to efficiently unravel such events. Our method automatically classifies complex structural variant calls as a combination of nested or adjacent reference transformations, allowing users to identify specific structure types of interest. Additionally, an output report is generated for each event with interactive visual representations of the rearrangement.",
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"abstract": "One of the types of genovariation is the intrasequence rearrangement. If we consider nucleotide sequence as a string, then the intrasequence rearrangement may be interpreted as mutual transposition of string parts. Common instruments for the analysis of the nucleotide strings (such as BLAST (Altschul et al., 1990)) are based on the computation of edit distance. Edit-distance approach is very efficient in case of such mutations as deletion, insertion or substitution of a single nucleotide, but almost inapplicable for the sequences with rearrangements. Another approach to the approximate searching in strings under condition of sequence rearrangements is block-edit approach (Lopresti and Tomkins, 1997). However algorithms based on this approach have a very high time complexity, which leads to the tight restrictions in its bioinformatics applications. One of the modern methods of approximate searching with rearrangements is reflected in QUASAR system (Burkhardt et al., 1999). In this article an approach to the search is proposed that is similar to QUASAR. The proposed approach gives visualization of the searching results. As distinct from QUASAR the proposed approach does not involve edit distance concept which allows to obtain time complexity O(n middot ln m), where n is the length of data string and m is the length of pattern. Another peculiarity is the visualization of the results",
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"abstract": "Human beings find it difficult to analyze local and global oligonucleotide patterns in the linear primary sequences of a genome. In this paper, we present a family of iterated function systems (IFS) that can be used to generate a set of visual models of a DNA sequence. A new visualization function, the W-curve, that is derived from this IFS family is introduced. Using W-curves, a user can readily compare subsequences within a long genomic sequence - or between genomic sequences - and can visually evaluate the effect of local variations (mutations) upon the global genomic information content.<>",
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"title": "A new framework for designing parallel algorithms on series parallel graphs",
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"abstract": "The authors propose a novel framework for designing efficient parallel algorithms on series parallel graphs. Recently, a novel approach for recognizing series parallel graphs was presented by D. Eppstein. Eppstein explored characterizations of the ear decomposition of series parallel graphs, which can be identified efficiently, in parallel. The authors extend Eppstein's results and show in a unified manner how to solve problems on series parallel graphs efficiently, in parallel, by finding a special ear decomposition of the graph. They demonstrate the utility of their novel framework by presenting O(log n) concurrent read exclusive write (CREW) parallel random access machine (PRAM) algorithms for the construction of a depth-first spanning tree, st-numbering, and a breadth-first spanning tree on series parallel graphs.",
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"abstract": "In this paper we present two novel multivariate time series representations to classify physiological data of different lengths. The representations may be applied to any group of multivariate time series data that examine the state or health of an entity. Multivariate Bag-of-Patterns and Stacked Bags of-Patterns improve on their univariate counterpart, inspired by the bag-of-words model, by using multiple time series and analyzing the data in a multivariate fashion. We also borrow techniques from the natural language processing domain such as term frequency and inverse document frequency to improve classification accuracy. We introduce a technique named inverse frequency and present experimental results on classifying patients who have experienced acute episodes of hypotension.",
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"abstract": "This paper introduces a novel application of artificial bee colony (ABC) in designing the coordinated Power System Stabilizer (PSS) with Thyristor Controlled Series Compensator (TCSC) based Controller to improve the transient stability of single machine connected to infinite bus through transmission line. Various simulation results and comparisons over different loading conditions on a single machine infinite bus power system shows the superiority of ABC in designing the coordinated controller.",
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"abstract": "A new Kalman Filtering model for 3D constant turn (3DCT) target had been presented. This paper makes a study of changing measurements from Pole coordinate to Cartesian coordinate. Then on this basis, this paper uses the method of EKF to make nonlinear equation linearity in the case of unknown pitch and azimuth angular velocity (Convert Measurements Kalman Filtering, CMKF). At last a method for the pseudo kalman filtering using radial velocity and angular velocity is presented for radar awareness system (Adopted Velocity Kalman Filtering, AVKF) which can detect target radial velocity and angular velocity. Simulation results indicate that the 3DCT can increase the convergent rate and precision.",
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"abstract": "As orthogonal moments in the polar coordinate, radial orthogonal moments such as Zernike, pseudo-Zernike and orthogonal Fourier-Mellin moments have been successfully used in the field of pattern recognition. However, the scale and rotation invariant property of these moments has not been studied. In this paper, we present a generic approach based on Jacobi-Fourier moments for scale and rotation invariant analysis of radial orthogonal moments. It provides a fundamental mathematical tool for invariant analysis of the radial orthogonal moments since Jacobi-Fourier moments are the generic expressions of radial orthogonal moments. Experimental results show the efficiency and the robustness to noise of the proposed method for recognition tasks.",
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"content": "As orthogonal moments in the polar coordinate, radial orthogonal moments such as Zernike, pseudo-Zernike and orthogonal Fourier-Mellin moments have been successfully used in the field of pattern recognition. However, the scale and rotation invariant property of these moments has not been studied. In this paper, we present a generic approach based on Jacobi-Fourier moments for scale and rotation invariant analysis of radial orthogonal moments. It provides a fundamental mathematical tool for invariant analysis of the radial orthogonal moments since Jacobi-Fourier moments are the generic expressions of radial orthogonal moments. Experimental results show the efficiency and the robustness to noise of the proposed method for recognition tasks.",
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"fullName": "Bin Xiao",
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"abstract": "In this paper, we suggest a new system to estimate the direction of a user's eye gaze. Our system consisted of five IR LEDs and a CCD camera. The IR LEDs that are attached to the corners of a computer monitor make glints on the surface of the cornea of the eye. If the user sees the monitor, the center of a pupil is always in a polygon that is made by the glints. Consequently, the direction of the user's eye gaze can be computed without computing the geometrical relation among the eye, the camera, and the monitor in 3D space. Our method is comparatively simple and fast. We will introduce the method and show experimental results.",
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"content": "Wireless capsule endoscopy (WCE) is a modality used for the non-invasive examination of the gastrointestinal (GI) tract. Physicians diagnose pathologies in images derived from Capsule Endoscopy (CE) using specific gaze patterns to observe pathologically related visual cues. Lately, deep learning has advanced in the domain of human eye-fixation estimation in natural images. However, the potentials of predicting the eye related patterns, such as eye fixations, in medical images has not been thoroughly investigated. In this work, we propose a CNN auto-encoder model, that is capable of predicting saliency maps estimating the gaze-patterns, in terms of eye-fixations, of physicians in CE images. The proposed model outperforms other approaches for visual saliency estimation based on physicians' eye fixation by providing an AUC-J of 0.726 among CE images depicting various pathological and normal cases.",
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"normalizedAbstract": "Wireless capsule endoscopy (WCE) is a modality used for the non-invasive examination of the gastrointestinal (GI) tract. Physicians diagnose pathologies in images derived from Capsule Endoscopy (CE) using specific gaze patterns to observe pathologically related visual cues. Lately, deep learning has advanced in the domain of human eye-fixation estimation in natural images. However, the potentials of predicting the eye related patterns, such as eye fixations, in medical images has not been thoroughly investigated. In this work, we propose a CNN auto-encoder model, that is capable of predicting saliency maps estimating the gaze-patterns, in terms of eye-fixations, of physicians in CE images. The proposed model outperforms other approaches for visual saliency estimation based on physicians' eye fixation by providing an AUC-J of 0.726 among CE images depicting various pathological and normal cases.",
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"abstract": "This paper presents a cascaded scheme with block-based and pixel-based codebooks for background subtraction. The codebook is mainly used to compress information to achieve high efficient processing speed. In the block-based stage, 12 intensity values are employed to represent a block. The algorithm extends the concept of the Block Truncation Coding (BTC), and thus it can further improve the processing efficiency by enjoying its low complexity advantage. In detail, the block-based stage can remove the most noise without reducing the True Positive (TP) rate, yet it has low precision. To overcome this problem, the pixel-based stage is adopted to enhance the precision, which also can reduce the False Positive (FP) rate. Moreover, this study also presents a color model and a match function which can classify an input pixel as shadow, highlight, background, or foreground. As documented in the experimental results, the proposed algorithm can provide superior performance to that of the former approaches.",
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"abstract": "Image Encryption has gain popularity because of need of secure transmission of images over open networks and increased attacks on data flowing over network. Different type of data have different features, that is why for images different techniques were evolved to protect confidential data from unauthorized access. Encryption techniques used for encrypting textual data does not work with images, so separate encryption techniques are required for images. So, we proposed here a new scheme for image encryption which is helpful for end to end secure transmission of digital information on open network using explosive block displacement followed by inter-pixel displacement of RGB values.",
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"content": "Image Encryption has gain popularity because of need of secure transmission of images over open networks and increased attacks on data flowing over network. Different type of data have different features, that is why for images different techniques were evolved to protect confidential data from unauthorized access. Encryption techniques used for encrypting textual data does not work with images, so separate encryption techniques are required for images. So, we proposed here a new scheme for image encryption which is helpful for end to end secure transmission of digital information on open network using explosive block displacement followed by inter-pixel displacement of RGB values.",
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"abstract": "In this paper, we propose a new approach for color image simplification in order to improve flame pixel classification. The fire detection performance depends critically on the performance of the flame pixel classifier. Color image simplification is the process of simplifying an image in order to decrease the number of colors while preserving, as much as possible, shapes. In this work, a hierarchical clustering method in a given color space is used to map the original colors into a smaller set of representative ones, allowing the use of a simple heuristic rule for classifying the clusters related to candidate flame colors. Using reverse mapping, we identify possible flame colors in the image. Main contributions of our work are the application of a simple hierarchical clustering method to color simplification, that decreases the number of possible flame colors, and a filtering methodology to reduce the influence of outliers. Several color spaces and distance measures were used to evaluate the proposed method. Experimental results demonstrate that color simplification is essential to successfully employ heuristic classification of flame colors.",
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"content": "In this paper, we propose a new approach for color image simplification in order to improve flame pixel classification. The fire detection performance depends critically on the performance of the flame pixel classifier. Color image simplification is the process of simplifying an image in order to decrease the number of colors while preserving, as much as possible, shapes. In this work, a hierarchical clustering method in a given color space is used to map the original colors into a smaller set of representative ones, allowing the use of a simple heuristic rule for classifying the clusters related to candidate flame colors. Using reverse mapping, we identify possible flame colors in the image. Main contributions of our work are the application of a simple hierarchical clustering method to color simplification, that decreases the number of possible flame colors, and a filtering methodology to reduce the influence of outliers. Several color spaces and distance measures were used to evaluate the proposed method. Experimental results demonstrate that color simplification is essential to successfully employ heuristic classification of flame colors.",
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"abstract": "A novel feature extraction method based on parallel coordinate plots was presented. Observing the parallel coordinate plots, discovered that using the distance of one point to others on one dimensionality to measurement the classify performance of the variable, can express the fact classify performance more impersonally. The Euclidean distance or module matrix and the relative distance matrix were given. And the distance ratio of every sample point to other sorts and it to its own sort has more classify information. We achieved better performance when experiment on data which has poor statistical performance.",
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"abstract": "With the appearance of more and more mental health problems, mental health education has been paid more and more attention by people. In order to popularize the knowledge of mental health education, colleges and universities have opened courses of mental health education, and psychological counseling rooms have been set up to carry out mental health education. With the great popularity of computers, the ability to apply computer technology to all walks of life is constantly improving. Various platforms built by computers to measure psychological problems are welcomed by people. Therefore I developed an online psychometric system based on DW. This system includes six modules, such as Love test, Personality test, Social test, Successful test, Personality test, Heterogeneous test. Users can choose different aspects to measure their own psychological problems, analyze and evaluate their own psychological problems, and then find out the problem and solve the problem, so as to help us become a healthy person. From the perspective of school education, it is meaningful and valuable for students to conduct self-assessment of mental health and reduce the burden of mental health education for schools.",
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"abstract": "Clinical Named Entity Recognition (CNER) aims to automatically identity clinical terminologies in Electronic Health Records (EHRs), which is a fundamental and crucial step for clinical research. To train a high-performance model for CNER, it usually requires a large number of EHRs with high-quality labels. However, labeling EHRs, especially Chinese EHRs, is time-consuming and expensive. One effective solution to this issue is active learning, where a model asks labelers to annotate data which is beneficial to model performance improvement. Conventional active learning assumes a single labeler that always replies noiseless answers to queried labels. However, in real settings, multiple labelers provide diverse quality of annotation with varied cost and labelers with low overall annotation quality can still assign correct labels for some specific instances. In this paper, we propose a Cost-Quality Adaptive Active Learning (CQAAL) approach for CNER in Chinese EHRs, which maintains a balance between the annotation quality, labeling cost and the informativeness of selected instances. Specifically, our proposed CQAAL method selects cost-effective instance-labeler pairs to achieve better annotation quality with lower cost in an adaptive manner. Computational results on the CCKS2017 dataset demonstrate the superiority and effectiveness of CQAAL.",
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"content": "Understanding the evolution of code clones is important for both developers and researchers to understand the maintenance implications of clones and to design robust clone management systems. Generally, a study of clone evolution starts with extracting clone genealogies across multiple versions of a program and classifying them according to their change patterns. Although these tasks are straightforward for exact clones, extracting the history of near-miss clones and classifying their change patterns automatically is challenging due to the potential diverse variety of clone fragments even in the same clone class. In this tool demonstration paper we describe the design and implementation of a near-miss clone genealogy extractor, gCad, that can extract and classify both exact and near-miss clone genealogies. Developers and researchers can compute a wide range of popular metrics regarding clone evolution by simply post processing the gCad results. gCad scales well to large subject systems, works for different granularities of clones, and adapts easily to popular clone detection tools.",
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"abstract": "Genealogy is one of the three kinds of historical literatures which are valuable to historical research and humanities research. However, traditionally, it is hard to build and revise a genealogy. And it is even impossible to manage and query the genealogy efficiently. In this paper, we proposed PZXG, which is a genealogy data service platform, to solve these issues. Firstly, for structured and unstructured genealogy data, we employ relational database, graph database and distributed file system to store them respectively. Secondly, depending on the hybrid data model of genealogy data, various management features like data acquisition, kin seeking, genealogy exhibition and automatic typesetting are provided. Then in order to extract knowledge from genealogy data, the features of routine statistics and query, root tracing, correlation analysis and data visualization in genealogical data are discussed, and several methods and ideas of text mining for genealogical text are given. Finally, two more urgent research points in the genealogical data management platform are suggested: extracting structural information from unstructured genealogy data and construction of genealogy-specific text language model.",
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"content": "A large amount of log data is generated every moment in many real-world applications. System logs, mobile application logs, web logs etc., all of which contain rich information and can be analyzed for valuable information. At the same time, genealogy attracts more and more attention in recent decades, especially for Chinese. People utilize the genealogy system to seek roots, find source of family, build a family tree and so on. Due to the complexity of genealogy data and specific features of genealogy system, how to extract and analyze the valued genealogy information effectively is a huge challenge. Motivated by this, we propose a novel analysis method using web logs in genealogy system for drawing user profile and providing personalized recommendations. More specifically, firstly, all web logs are extracted from genealogy system based on the enhanced logs which record the behaviors and data of user. Secondly, the extracted logs are formatted for analysis, and we analyze the logs to extract various user-related attributes for drawing user profile. Finally, personalized recommendations like interested people and family tree are provided for each user in system. The high availability and effectiveness of our proposed method is verified on genealogy system-Huapu system.",
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"abstract": "Amusement parks are complex facilities with various attractions and shops, and many events for entertainment, making it a very difficult target for marketing research. Therefore, we proposed and built an opinion collection system using smartphones to efficiently collect user's opinions for improvement. In this paper, we propose and construct an opinion analysis and visualization system to support the grasping the situation of the amusement park, the planning of improvement. It is difficult for marketing researchers to extract important opinions from a large number of opinions. To cope with this problem, we propose a method to visualize emotional information of opinion on a map. The method classifies emotions for opinions based on Plutchik's wheel of emotions. The evaluation result by questionnaires is 4.75 on average out of 5 scales. The result shows that the proposed system can support the action of proposing business ideas.",
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"content": "Amusement parks are complex facilities with various attractions and shops, and many events for entertainment, making it a very difficult target for marketing research. Therefore, we proposed and built an opinion collection system using smartphones to efficiently collect user's opinions for improvement. In this paper, we propose and construct an opinion analysis and visualization system to support the grasping the situation of the amusement park, the planning of improvement. It is difficult for marketing researchers to extract important opinions from a large number of opinions. To cope with this problem, we propose a method to visualize emotional information of opinion on a map. The method classifies emotions for opinions based on Plutchik's wheel of emotions. The evaluation result by questionnaires is 4.75 on average out of 5 scales. The result shows that the proposed system can support the action of proposing business ideas.",
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"affiliation": "Meiji University",
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