Search results for: Spatial temporal data mining
7643 Adaptive Gaussian Mixture Model for Skin Color Segmentation
Authors: Reza Hassanpour, Asadollah Shahbahrami, Stephan Wong
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Skin color based tracking techniques often assume a static skin color model obtained either from an offline set of library images or the first few frames of a video stream. These models can show a weak performance in presence of changing lighting or imaging conditions. We propose an adaptive skin color model based on the Gaussian mixture model to handle the changing conditions. Initial estimation of the number and weights of skin color clusters are obtained using a modified form of the general Expectation maximization algorithm, The model adapts to changes in imaging conditions and refines the model parameters dynamically using spatial and temporal constraints. Experimental results show that the method can be used in effectively tracking of hand and face regions.Keywords: Face detection, Segmentation, Tracking, Gaussian Mixture Model, Adaptation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24157642 Spatial Objects Shaping with High-Pressure Abrasive Water Jet Controlled By Virtual Image Luminance
Authors: P. J. Borkowski, J. A. Borkowski
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The paper presents a novel method for the 3D shaping of different materials using a high-pressure abrasive water jet and a flat target image. For steering movement process of the jet a principle similar to raster image way of record and readout was used. However, respective colors of pixel of such a bitmap are connected with adequate jet feed rate that causes erosion of material with adequate depth. Thanks to that innovation, one can observe spatial imaging of the object. Theoretical basis as well as spatial model of material shaping and experimental stand including steering program are presented in. There are also presented methodic and some experimental erosion results as well as practical example of object-s bas-relief made of metal.Keywords: High-pressure, abrasive, water jet, material shaping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14267641 Spatio-Temporal Video Slice Edges Analysis for Shot Transition Detection and Classification
Authors: Aissa Saoudi, Hassane Essafi
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In this work we will present a new approach for shot transition auto-detection. Our approach is based on the analysis of Spatio-Temporal Video Slice (STVS) edges extracted from videos. The proposed approach is capable to efficiently detect both abrupt shot transitions 'cuts' and gradual ones such as fade-in, fade-out and dissolve. Compared to other techniques, our method is distinguished by its high level of precision and speed. Those performances are obtained due to minimizing the problem of the boundary shot detection to a simple 2D image partitioning problem.Keywords: Boundary shot detection, Shot transition detection, Video analysis, Video indexing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16397640 Analysis of Textual Data Based On Multiple 2-Class Classification Models
Authors: Shigeaki Sakurai, Ryohei Orihara
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This paper proposes a new method for analyzing textual data. The method deals with items of textual data, where each item is described based on various viewpoints. The method acquires 2- class classification models of the viewpoints by applying an inductive learning method to items with multiple viewpoints. The method infers whether the viewpoints are assigned to the new items or not by using the models. The method extracts expressions from the new items classified into the viewpoints and extracts characteristic expressions corresponding to the viewpoints by comparing the frequency of expressions among the viewpoints. This paper also applies the method to questionnaire data given by guests at a hotel and verifies its effect through numerical experiments.
Keywords: Text mining, Multiple viewpoints, Differential analysis, Questionnaire data
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12907639 Multidimensional Data Mining by Means of Randomly Travelling Hyper-Ellipsoids
Authors: Pavel Y. Tabakov, Kevin Duffy
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The present study presents a new approach to automatic data clustering and classification problems in large and complex databases and, at the same time, derives specific types of explicit rules describing each cluster. The method works well in both sparse and dense multidimensional data spaces. The members of the data space can be of the same nature or represent different classes. A number of N-dimensional ellipsoids are used for enclosing the data clouds. Due to the geometry of an ellipsoid and its free rotation in space the detection of clusters becomes very efficient. The method is based on genetic algorithms that are used for the optimization of location, orientation and geometric characteristics of the hyper-ellipsoids. The proposed approach can serve as a basis for the development of general knowledge systems for discovering hidden knowledge and unexpected patterns and rules in various large databases.Keywords: Classification, clustering, data minig, genetic algorithms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17737638 A Novel Design for Hybrid Space-Time Block Codes and Spatial Multiplexing Scheme
Authors: Seung-Jun Yu, Jang-Kyun Ahn, Eui-Young Lee, Hyoung-Kyu Song
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Space-time block codes (STBC) and spatial multiplexing (SM) are promising techniques that effectively exploit multipleinput multiple-output (MIMO) transmission to achieve more reliable communication and a higher multiplexing rate, respectively. In this paper, we study a practical design for hybrid scheme with multi-input multi-output orthogonal frequency division multiplexing (MIMOOFDM) systems to flexibly maximize the tradeoff between diversity and multiplexing gains. Unlike the existing STBC and SM designs which are suitable for the integer multiplexing rate, the proposed design can achieve arbitrary number of multiplexing rate.Keywords: Space-Time Block Codes, Spatial Multiplexing, MIMO-OFDM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18167637 Top-Down Influences to Multistable Perception: Evidence from Temporal Dynamics
Authors: Daria N. Podvigina, Tatiana V. Chernigovskaya
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We have studied the temporal characteristics of bistable perception of the stimuli of two types: one involves alterations in a perceived depth and another one has an ambiguous content. We used the Necker lattice and lines of shadowed circles ambiguously perceived either as spheres or holes as stimuli of the first type. The Winson figure (the Eskimo/Indian picture) was a stimulus of the second type. We have analyzed how often the reversals occurred (reversal rate) and for how long each of the two interpretations, or percepts, was observed during one presentation (stability durations). For all three ambiguous images the reversal rate and the stability durations had similar values, which provide another evidence for a significant role of top-down processes in multistable perception.Keywords: Multistable perception, perceived depth, reversal rate, top-down processes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24377636 Comparisons of Co-Seismic Gravity Changes between GRACE Observations and the Predictions from the Finite-Fault Models for the 2012 Mw = 8.6 Indian Ocean Earthquake Off-Sumatra
Authors: Armin Rahimi
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The Gravity Recovery and Climate Experiment (GRACE) has been a very successful project in determining math redistribution within the Earth system. Large deformations caused by earthquakes are in the high frequency band. Unfortunately, GRACE is only capable to provide reliable estimate at the low-to-medium frequency band for the gravitational changes. In this study, we computed the gravity changes after the 2012 Mw8.6 Indian Ocean earthquake off-Sumatra using the GRACE Level-2 monthly spherical harmonic (SH) solutions released by the University of Texas Center for Space Research (UTCSR). Moreover, we calculated gravity changes using different fault models derived from teleseismic data. The model predictions showed non-negligible discrepancies in gravity changes. However, after removing high-frequency signals, using Gaussian filtering 350 km commensurable GRACE spatial resolution, the discrepancies vanished, and the spatial patterns of total gravity changes predicted from all slip models became similar at the spatial resolution attainable by GRACE observations, and predicted-gravity changes were consistent with the GRACE-detected gravity changes. Nevertheless, the fault models, in which give different slip amplitudes, proportionally lead to different amplitude in the predicted gravity changes.Keywords: Undersea earthquake, GRACE observation, gravity change, dislocation model, slip distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9917635 Multi-Dimensional Concerns Mining for Web Applications via Concept-Analysis
Authors: Carlo Bellettini, Alessandro Marchetto, Andrea Trentini
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Web applications have become very complex and crucial, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering), the scientific community has focused attention to Web applications design, development, analysis, and testing, by studying and proposing methodologies and tools. This paper proposes an approach to automatic multi-dimensional concern mining for Web Applications, based on concepts analysis, impact analysis, and token-based concern identification. This approach lets the user to analyse and traverse Web software relevant to a particular concern (concept, goal, purpose, etc.) via multi-dimensional separation of concerns, to document, understand and test Web applications. This technique was developed in the context of WAAT (Web Applications Analysis and Testing) project. A semi-automatic tool to support this technique is currently under development.Keywords: Concepts Analysis, Concerns Mining, Multi-Dimensional Separation of Concerns, Impact Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14737634 A Preference-Based Multi-Agent Data Mining Framework for Social Network Service Users' Decision Making
Authors: Ileladewa Adeoye Abiodun, Cheng Wai Khuen
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Multi-Agent Systems (MAS) emerged in the pursuit to improve our standard of living, and hence can manifest complex human behaviors such as communication, decision making, negotiation and self-organization. The Social Network Services (SNSs) have attracted millions of users, many of whom have integrated these sites into their daily practices. The domains of MAS and SNS have lots of similarities such as architecture, features and functions. Exploring social network users- behavior through multiagent model is therefore our research focus, in order to generate more accurate and meaningful information to SNS users. An application of MAS is the e-Auction and e-Rental services of the Universiti Cyber AgenT(UniCAT), a Social Network for students in Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia, built around the Belief- Desire-Intention (BDI) model. However, in spite of the various advantages of the BDI model, it has also been discovered to have some shortcomings. This paper therefore proposes a multi-agent framework utilizing a modified BDI model- Belief-Desire-Intention in Dynamic and Uncertain Situations (BDIDUS), using UniCAT system as a case study.
Keywords: Distributed Data Mining, Multi-Agent Systems, Preference-Based, SNS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15037633 H.264 Video Privacy Protection Method Using Regions of Interest Encryption
Authors: Taekyun Doo, Cheongmin Ji, Manpyo Hong
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Like a closed-circuit television (CCTV), video surveillance system is widely placed for gathering video from unspecified people to prevent crime, surveillance, or many other purposes. However, abuse of CCTV brings about concerns of personal privacy invasions. In this paper, we propose an encryption method to protect personal privacy system in H.264 compressed video bitstream with encrypting only regions of interest (ROI). There is no need to change the existing video surveillance system. In addition, encrypting ROI in compressed video bitstream is a challenging work due to spatial and temporal drift errors. For this reason, we propose a novel drift mitigation method when ROI is encrypted. The proposed method was implemented by using JM reference software based on the H.264 compressed videos, and experimental results show the verification of our proposed methods and its effectiveness.
Keywords: H.264/AVC, video encryption, privacy protection, post compression, region of interest.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15687632 Visual Analytics of Higher Order Information for Trajectory Datasets
Authors: Ye Wang, Ickjai Lee
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Due to the widespread of mobile sensing, there is a strong need to handle trails of moving objects, and trajectories. This paper proposes three visual analytics approaches for higher order information of trajectory datasets based on the higher order Voronoi diagram data structure. Proposed approaches reveal geometrical, topological, and directional information. Experimental resultsdemonstrate the applicability and usefulness of proposed three approaches.
Keywords: Visual Analytics, Higher Order Information, Trajectory Datasets, Spatio-temporal data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16397631 Mining Implicit Knowledge to Predict Political Risk by Providing Novel Framework with Using Bayesian Network
Authors: Siavash Asadi Ghajarloo
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Nowadays predicting political risk level of country has become a critical issue for investors who intend to achieve accurate information concerning stability of the business environments. Since, most of the times investors are layman and nonprofessional IT personnel; this paper aims to propose a framework named GECR in order to help nonexpert persons to discover political risk stability across time based on the political news and events. To achieve this goal, the Bayesian Networks approach was utilized for 186 political news of Pakistan as sample dataset. Bayesian Networks as an artificial intelligence approach has been employed in presented framework, since this is a powerful technique that can be applied to model uncertain domains. The results showed that our framework along with Bayesian Networks as decision support tool, predicted the political risk level with a high degree of accuracy.Keywords: Bayesian Networks, Data mining, GECRframework, Predicting political risk.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21747630 Outdoor Anomaly Detection with a Spectroscopic Line Detector
Authors: O. J. G. Somsen
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One of the tasks of optical surveillance is to detect anomalies in large amounts of image data. However, if the size of the anomaly is very small, limited information is available to distinguish it from the surrounding environment. Spectral detection provides a useful source of additional information and may help to detect anomalies with a size of a few pixels or less. Unfortunately, spectral cameras are expensive because of the difficulty of separating two spatial in addition to one spectral dimension. We investigate the possibility of modifying a simple spectral line detector for outdoor detection. This may be especially useful if the area of interest forms a line, such as the horizon. We use a monochrome CCD that also enables detection into the near infrared. A simple camera is attached to the setup to determine which part of the environment is spectrally imaged. Our preliminary results indicate that sensitive detection of very small targets is indeed possible. Spectra could be taken from the various targets by averaging columns in the line image. By imaging a set of lines of various widths we found narrow lines that could not be seen in the color image but remained visible in the spectral line image. A simultaneous analysis of the entire spectra can produce better results than visual inspection of the line spectral image. We are presently developing calibration targets for spatial and spectral focusing and alignment with the spatial camera. This will present improved results and more use in outdoor application.Keywords: Anomaly detection, spectroscopic line imaging, image analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16467629 A Hybrid Approach for Thread Recommendation in MOOC Forums
Authors: Ahmad. A. Kardan, Amir Narimani, Foozhan Ataiefard
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Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC forums by applying social network analysis and association rule mining techniques. Initial results indicate that the proposed recommender system performs comparatively well with regard to limited available data from users' previous posts in the forum.Keywords: Association rule mining, hybrid recommender system, massive open online courses, MOOCs, social network analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12637628 Present Status, Driving Forces and Pattern Optimization of Territory in Hubei Province, China
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“National Territorial Planning (2016-2030)” was issued by the State Council of China in 2017. As an important initiative of putting it into effect, territorial planning at provincial level makes overall arrangement of territorial development, resources and environment protection, comprehensive renovation and security system construction. Hubei province, as the pivot of the “Rise of Central China” national strategy, is now confronted with great opportunities and challenges in territorial development, protection, and renovation. Territorial spatial pattern experiences long time evolution, influenced by multiple internal and external driving forces. It is not clear what are the main causes of its formation and what are effective ways of optimizing it. By analyzing land use data in 2016, this paper reveals present status of territory in Hubei. Combined with economic and social data and construction information, driving forces of territorial spatial pattern are then analyzed. Research demonstrates that the three types of territorial space aggregate distinctively. The four aspects of driving forces include natural background which sets the stage for main functions, population and economic factors which generate agglomeration effect, transportation infrastructure construction which leads to axial expansion and significant provincial strategies which encourage the established path. On this basis, targeted strategies for optimizing territory spatial pattern are then put forward. Hierarchical protection pattern should be established based on development intensity control as respect for nature. By optimizing the layout of population and industry and improving the transportation network, polycentric network-based development pattern could be established. These findings provide basis for Hubei Territorial Planning, and reference for future territorial planning in other provinces.Keywords: Driving forces, Hubei, optimizing strategies, spatial pattern, territory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6247627 Radar Hydrology: New Z/R Relationships for Klang River Basin Malaysia based on Rainfall Classification
Authors: R. Suzana, T. Wardah, A.B. Sahol Hamid
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The use of radar in Quantitative Precipitation Estimation (QPE) for radar-rainfall measurement is significantly beneficial. Radar has advantages in terms of high spatial and temporal condition in rainfall measurement and also forecasting. In Malaysia, radar application in QPE is still new and needs to be explored. This paper focuses on the Z/R derivation works of radarrainfall estimation based on rainfall classification. The works developed new Z/R relationships for Klang River Basin in Selangor area for three different general classes of rain events, namely low (<10mm/hr), moderate (>10mm/hr, <30mm/hr) and heavy (>30mm/hr) and also on more specific rain types during monsoon seasons. Looking at the high potential of Doppler radar in QPE, the newly formulated Z/R equations will be useful in improving the measurement of rainfall for any hydrological application, especially for flood forecasting.
Keywords: Radar, Quantitative Precipitation Estimation, Z/R development, flood forecasting
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21517626 The Role of Velocity Map Quality in Estimation of Intravascular Pressure Distribution
Authors: Ali Pashaee, Parisa Shooshtari, Gholamreza Atae, Nasser Fatouraee
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Phase-Contrast MR imaging methods are widely used for measurement of blood flow velocity components. Also there are some other tools such as CT and Ultrasound for velocity map detection in intravascular studies. These data are used in deriving flow characteristics. Some clinical applications are investigated which use pressure distribution in diagnosis of intravascular disorders such as vascular stenosis. In this paper an approach to the problem of measurement of intravascular pressure field by using velocity field obtained from flow images is proposed. The method presented in this paper uses an algorithm to calculate nonlinear equations of Navier- Stokes, assuming blood as an incompressible and Newtonian fluid. Flow images usually suffer the lack of spatial resolution. Our attempt is to consider the effect of spatial resolution on the pressure distribution estimated from this method. In order to achieve this aim, velocity map of a numerical phantom is derived at six different spatial resolutions. To determine the effects of vascular stenoses on pressure distribution, a stenotic phantom geometry is considered. A comparison between the pressure distribution obtained from the phantom and the pressure resulted from the algorithm is presented. In this regard we also compared the effects of collocated and staggered computational grids on the pressure distribution resulted from this algorithm.Keywords: Flow imaging, pressure distribution estimation, phantom, resolution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16827625 Learning and Evaluating Possibilistic Decision Trees using Information Affinity
Authors: Ilyes Jenhani, Salem Benferhat, Zied Elouedi
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This paper investigates the issue of building decision trees from data with imprecise class values where imprecision is encoded in the form of possibility distributions. The Information Affinity similarity measure is introduced into the well-known gain ratio criterion in order to assess the homogeneity of a set of possibility distributions representing instances-s classes belonging to a given training partition. For the experimental study, we proposed an information affinity based performance criterion which we have used in order to show the performance of the approach on well-known benchmarks.Keywords: Data mining from uncertain data, Decision Trees, Possibility Theory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15157624 On the Differentiation of Strategic Spatial Planning Making Mechanisms in New Era: Between Melbourne and Tianjin
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Strategic spatial planning, which is taken as an effective and competitive way for the governors of the city to improve the development and management level of a city, has been blooming in recent years all over the world. In the context of globalization and informatization, strategic spatial planning must transfer its focus on three different levels: global, regional and urban. Internal and external changes in environmental conditions lead to new advances in strategic planning both theoretically and practically. However, such advances or changes respond differently to cities on account of different dynamic mechanisms. This article aims at two cities of Tianjin in China and Melbourne in Australia, through a comparative study on strategic planning, to explore the differentiation of mechanisms in urban planning making. By comparison and exploration, the purpose of this article is to exhibit two different planning worlds between western and Chinese in a new way nowadays.
Keywords: Differentiation, Tianjin China, Melbourne Australia, strategic planning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22617623 A Study on Finding Similar Document with Multiple Categories
Authors: R. Saraçoğlu, N. Allahverdi
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Searching similar documents and document management subjects have important place in text mining. One of the most important parts of similar document research studies is the process of classifying or clustering the documents. In this study, a similar document search approach that includes discussion of out the case of belonging to multiple categories (multiple categories problem) has been carried. The proposed method that based on Fuzzy Similarity Classification (FSC) has been compared with Rocchio algorithm and naive Bayes method which are widely used in text mining. Empirical results show that the proposed method is quite successful and can be applied effectively. For the second stage, multiple categories vector method based on information of categories regarding to frequency of being seen together has been used. Empirical results show that achievement is increased almost two times, when proposed method is compared with classical approach.
Keywords: Document similarity, Fuzzy classification, Multiple categories, Text mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17077622 Statistical Relation between Vegetation Cover and Land Surface Temperature in Phnom Penh City
Authors: Gulam Mohiuddin, Jan-Peter Mund
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This study assessed the correlation between Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) in Phnom Penh City (Cambodia) from 2016 to 2020. Understanding the LST and NDVI can be helpful to understand the Urban Heat Island (UHI) scenario, and it can contribute to planning urban greening and combating the effects of UHI. The study used Landsat-8 images as the data for analysis. They have 100 m spatial resolution (per pixel) in the thermal band. The current study used an approach for the statistical analysis that considers every pixel from the study area instead of taking few sample points or analyzing descriptive statistics. Also, this study is examining the correlation between NDVI and LST with a spatially explicit approach. The study found a strong negative correlation between NDVI and LST (coefficient range -0.56 to -0.59), and this relationship is linear. This study showed a way to avoid the probable error from the sample-based approach in examining two spatial variables. The method is reproducible for a similar type of analysis on the correlation between spatial phenomena. The findings of this study will be used further to understand the causation behind LST change in that area triangulating LST, NDVI and land-use changes.
Keywords: Land Surface Temperature, NDVI, Normalized Difference Vegetation Index, remote sensing, methodological development.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4717621 Mining User-Generated Contents to Detect Service Failures with Topic Model
Authors: Kyung Bae Park, Sung Ho Ha
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Online user-generated contents (UGC) significantly change the way customers behave (e.g., shop, travel), and a pressing need to handle the overwhelmingly plethora amount of various UGC is one of the paramount issues for management. However, a current approach (e.g., sentiment analysis) is often ineffective for leveraging textual information to detect the problems or issues that a certain management suffers from. In this paper, we employ text mining of Latent Dirichlet Allocation (LDA) on a popular online review site dedicated to complaint from users. We find that the employed LDA efficiently detects customer complaints, and a further inspection with the visualization technique is effective to categorize the problems or issues. As such, management can identify the issues at stake and prioritize them accordingly in a timely manner given the limited amount of resources. The findings provide managerial insights into how analytics on social media can help maintain and improve their reputation management. Our interdisciplinary approach also highlights several insights by applying machine learning techniques in marketing research domain. On a broader technical note, this paper illustrates the details of how to implement LDA in R program from a beginning (data collection in R) to an end (LDA analysis in R) since the instruction is still largely undocumented. In this regard, it will help lower the boundary for interdisciplinary researcher to conduct related research.Keywords: Latent Dirichlet allocation, R program, text mining, topic model, user generated contents, visualization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12167620 Journey to Cybercrime and Crime Opportunity: Quantitative Analysis of Cyber Offender Spatial Decision Making
Authors: Sinchul Back, Sun Ho Kim, Jennifer LaPrade, Ilju Seong
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Due to the advantage of using the Internet, cybercriminals can reach target(s) without border controls. Prior research on criminology and crime science has largely been void of empirical studies on journey-to-cybercrime and crime opportunity. Thus, the purpose of this study is to understand more about cyber offender spatial decision making associated with crime opportunity factors (i.e., co-offending, offender-stranger). Data utilized in this study were derived from 306 U.S. Federal court cases of cybercrime. The findings of this study indicated that there was a positive relationship between co-offending and journey-to-cybercrime, whereas there was no link between offender-stranger and journey-to-cybercrime. Also, the results showed that there was no relationship between cybercriminal sex, age, and journey-to-cybercrime. The policy implications and limitations of this study are discussed.
Keywords: Co-offending, crime opportunity, journey-to-cybercrime, offender-stranger.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7377619 Thailand National Biodiversity Database System with webMathematica and Google Earth
Authors: W. Katsarapong, W. Srisang, K. Jaroensutasinee, M. Jaroensutasinee
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National Biodiversity Database System (NBIDS) has been developed for collecting Thai biodiversity data. The goal of this project is to provide advanced tools for querying, analyzing, modeling, and visualizing patterns of species distribution for researchers and scientists. NBIDS data record two types of datasets: biodiversity data and environmental data. Biodiversity data are specie presence data and species status. The attributes of biodiversity data can be further classified into two groups: universal and projectspecific attributes. Universal attributes are attributes that are common to all of the records, e.g. X/Y coordinates, year, and collector name. Project-specific attributes are attributes that are unique to one or a few projects, e.g., flowering stage. Environmental data include atmospheric data, hydrology data, soil data, and land cover data collecting by using GLOBE protocols. We have developed webbased tools for data entry. Google Earth KML and ArcGIS were used as tools for map visualization. webMathematica was used for simple data visualization and also for advanced data analysis and visualization, e.g., spatial interpolation, and statistical analysis. NBIDS will be used by park rangers at Khao Nan National Park, and researchers.Keywords: GLOBE protocol, Biodiversity, Database System, ArcGIS, Google Earth and webMathematica.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19847618 Clustering Unstructured Text Documents Using Fading Function
Authors: Pallav Roxy, Durga Toshniwal
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Clustering unstructured text documents is an important issue in data mining community and has a number of applications such as document archive filtering, document organization and topic detection and subject tracing. In the real world, some of the already clustered documents may not be of importance while new documents of more significance may evolve. Most of the work done so far in clustering unstructured text documents overlooks this aspect of clustering. This paper, addresses this issue by using the Fading Function. The unstructured text documents are clustered. And for each cluster a statistics structure called Cluster Profile (CP) is implemented. The cluster profile incorporates the Fading Function. This Fading Function keeps an account of the time-dependent importance of the cluster. The work proposes a novel algorithm Clustering n-ary Merge Algorithm (CnMA) for unstructured text documents, that uses Cluster Profile and Fading Function. Experimental results illustrating the effectiveness of the proposed technique are also included.Keywords: Clustering, Text Mining, Unstructured TextDocuments, Fading Function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19857617 Unsupervised Outlier Detection in Streaming Data Using Weighted Clustering
Authors: Yogita, Durga Toshniwal
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Outlier detection in streaming data is very challenging because streaming data cannot be scanned multiple times and also new concepts may keep evolving. Irrelevant attributes can be termed as noisy attributes and such attributes further magnify the challenge of working with data streams. In this paper, we propose an unsupervised outlier detection scheme for streaming data. This scheme is based on clustering as clustering is an unsupervised data mining task and it does not require labeled data, both density based and partitioning clustering are combined for outlier detection. In this scheme partitioning clustering is also used to assign weights to attributes depending upon their respective relevance and weights are adaptive. Weighted attributes are helpful to reduce or remove the effect of noisy attributes. Keeping in view the challenges of streaming data, the proposed scheme is incremental and adaptive to concept evolution. Experimental results on synthetic and real world data sets show that our proposed approach outperforms other existing approach (CORM) in terms of outlier detection rate, false alarm rate, and increasing percentages of outliers.
Keywords: Concept Evolution, Irrelevant Attributes, Streaming Data, Unsupervised Outlier Detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26377616 A New H.264-Based Rate Control Algorithm for Stereoscopic Video Coding
Authors: Yi Liao, Wencheng Yang, Gangyi Jiang
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According to investigating impact of complexity of stereoscopic frame pairs on stereoscopic video coding and transmission, a new rate control algorithm is presented. The proposed rate control algorithm is performed on three levels: stereoscopic group of pictures (SGOP) level, stereoscopic frame (SFrame) level and frame level. A temporal-spatial frame complexity model is firstly established, in the bits allocation stage, the frame complexity, position significance and reference property between the left and right frames are taken into account. Meanwhile, the target buffer is set according to the frame complexity. Experimental results show that the proposed method can efficiently control the bitrates, and it outperforms the fixed quantization parameter method from the rate distortion perspective, and average PSNR gain between rate-distortion curves (BDPSNR) is 0.21dB.
Keywords: Stereoscopic video coding, rate control, stereoscopic group of pictures, complexity of stereoscopic frame pairs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17177615 Frontal EEG Asymmetry Based Classification of Emotional Valence using Common Spatial Patterns
Authors: Irene Winkler, Mark Jager, Vojkan Mihajlovic, Tsvetomira Tsoneva
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In this work we evaluate the possibility of predicting the emotional state of a person based on the EEG. We investigate the problem of classifying valence from EEG signals during the presentation of affective pictures, utilizing the "frontal EEG asymmetry" phenomenon. To distinguish positive and negative emotions, we applied the Common Spatial Patterns algorithm. In contrast to our expectations, the affective pictures did not reliably elicit changes in frontal asymmetry. The classifying task thereby becomes very hard as reflected by the poor classifier performance. We suspect that the masking of the source of the brain activity related to emotions, coming mostly from deeper structures in the brain, and the insufficient emotional engagement are among main reasons why it is difficult to predict the emotional state of a person.Keywords: Emotion, Valence, EEG, Common Spatial Patterns(CSP).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26117614 A Hybrid Recommendation System Based On Association Rules
Authors: Ahmed Mohammed K. Alsalama
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Recommendation systems are widely used in e-commerce applications. The engine of a current recommendation system recommends items to a particular user based on user preferences and previous high ratings. Various recommendation schemes such as collaborative filtering and content-based approaches are used to build a recommendation system. Most of current recommendation systems were developed to fit a certain domain such as books, articles, and movies. We propose1 a hybrid framework recommendation system to be applied on two dimensional spaces (User × Item) with a large number of Users and a small number of Items. Moreover, our proposed framework makes use of both favorite and non-favorite items of a particular user. The proposed framework is built upon the integration of association rules mining and the content-based approach. The results of experiments show that our proposed framework can provide accurate recommendations to users.
Keywords: Data Mining, Association Rules, Recommendation Systems, Hybrid Systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3989