Search results for: temporal sequences.
527 Codes beyond Bits and Bytes: A Blueprint for Artificial Life
Authors: Rishabh Garg, Anuja Vyas, Aamna Khan, Muhammad Azwan Tariq
Abstract:
The present study focuses on integrating Machine Learning and Genomics, hereafter termed ‘GenoLearning’, to develop Artificial Life (AL). This is achieved by leveraging gene editing to imbue genes with sequences capable of performing desired functions. To accomplish this, a specialized sub-network of Siamese Neural Network (SNN), named Transformer Architecture specialized in Sequence Analysis of Genes (TASAG), compares two sequences: the desired and target sequences. Differences between these sequences are analyzed, and necessary edits are made on-screen to incorporate the desired sequence into the target sequence. The edited sequence can then be synthesized chemically using a Computerized DNA Synthesizer (CDS). The CDS fabricates DNA strands according to the sequence displayed on a computer screen, aided by microprocessors. These synthesized DNA strands can be inserted into an ovum to initiate further development, eventually leading to the creation of an Embot, and ultimately, an H-Bot. While this study aims to explore the potential benefits of Artificial Intelligence (AI) technology, it also acknowledges and addresses the ethical considerations associated with its implementation.
Keywords: Machine Learning, Genomics, Genetronics, DNA, Transformer, Siamese Neural Network, Gene Editing, Artificial Life, H-Bot, Zoobot.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 75526 Adaptive Weighted Averaging Filter Using the Appropriate Number of Consecutive Frames
Authors: Mahmoud Saeidi, Ali Nazemipour
Abstract:
In this paper, we propose a novel adaptive spatiotemporal filter that utilizes image sequences in order to remove noise. The consecutive frames include: current, previous and next noisy frames. The filter proposed in this paper is based upon the weighted averaging pixels intensity and noise variance in image sequences. It utilizes the Appropriate Number of Consecutive Frames (ANCF) based on the noisy pixels intensity among the frames. The number of consecutive frames is adaptively calculated for each region in image and its value may change from one region to another region depending on the pixels intensity within the region. The weights are determined by a well-defined mathematical criterion, which is adaptive to the feature of spatiotemporal pixels of the consecutive frames. It is experimentally shown that the proposed filter can preserve image structures and edges under motion while suppressing noise, and thus can be effectively used in image sequences filtering. In addition, the AWA filter using ANCF is particularly well suited for filtering sequences that contain segments with abruptly changing scene content due to, for example, rapid zooming and changes in the view of the camera.Keywords: Appropriate Number of Consecutive Frames, Adaptive Weighted Averaging, Motion Estimation, Noise Variance, Motion Compensation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1818525 On Pseudo-Random and Orthogonal Binary Spreading Sequences
Authors: Abhijit Mitra
Abstract:
Different pseudo-random or pseudo-noise (PN) as well as orthogonal sequences that can be used as spreading codes for code division multiple access (CDMA) cellular networks or can be used for encrypting speech signals to reduce the residual intelligence are investigated. We briefly review the theoretical background for direct sequence CDMA systems and describe the main characteristics of the maximal length, Gold, Barker, and Kasami sequences. We also discuss about variable- and fixed-length orthogonal codes like Walsh- Hadamard codes. The equivalence of PN and orthogonal codes are also derived. Finally, a new PN sequence is proposed which is shown to have certain better properties than the existing codes.
Keywords: Code division multiple access, pseudo-noise codes, maximal length, Gold, Barker, Kasami, Walsh-Hadamard, autocorrelation, crosscorrelation, figure of merit.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6053524 Performance of Chaotic Lu System in CDMA Satellites Communications Systems
Authors: K. Kemih, M. Benslama
Abstract:
This paper investigates the problem of spreading sequence and receiver code synchronization techniques for satellite based CDMA communications systems. The performance of CDMA system depends on the autocorrelation and cross-correlation properties of the used spreading sequences. In this paper we propose the uses of chaotic Lu system to generate binary sequences for spreading codes in a direct sequence spread CDMA system. To minimize multiple access interference (MAI) we propose the use of genetic algorithm for optimum selection of chaotic spreading sequences. To solve the problem of transmitter-receiver synchronization, we use the passivity controls. The concept of semipassivity is defined to find simple conditions which ensure boundedness of the solutions of coupled Lu systems. Numerical results are presented to show the effectiveness of the proposed approach.Keywords: About Chaotic Lu system, synchronization, Spreading sequence, Genetic Algorithm. Passive System
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1746523 Power Efficient OFDM Signals with Reduced Symbol's Aperiodic Autocorrelation
Authors: Ibrahim M. Hussain
Abstract:
Three new algorithms based on minimization of autocorrelation of transmitted symbols and the SLM approach which are computationally less demanding have been proposed. In the first algorithm, autocorrelation of complex data sequence is minimized to a value of 1 that results in reduction of PAPR. Second algorithm generates multiple random sequences from the sequence generated in the first algorithm with same value of autocorrelation i.e. 1. Out of these, the sequence with minimum PAPR is transmitted. Third algorithm is an extension of the second algorithm and requires minimum side information to be transmitted. Multiple sequences are generated by modifying a fixed number of complex numbers in an OFDM data sequence using only one factor. The multiple sequences represent the same data sequence and the one giving minimum PAPR is transmitted. Simulation results for a 256 subcarrier OFDM system show that significant reduction in PAPR is achieved using the proposed algorithms.
Keywords: Aperiodic autocorrelation, OFDM, PAPR, SLM, wireless communication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1721522 To Study the Parametric Effects on Optimality of Various Feeding Sequences of a Multieffect Evaporators in Paper Industry using Mathematical Modeling and Simulation with MATLAB
Authors: Deepak Kumar, Vivek Kumar, V. P. Singh
Abstract:
This paper describes a steady state model of a multiple effect evaporator system for simulation and control purposes. The model includes overall as well as component mass balance equations, energy balance equations and heat transfer rate equations for area calculations for all the effects. Each effect in the process is represented by a number of variables which are related by the energy and material balance equations for the feed, product and vapor flow for backward, mixed and split feed. For simulation 'fsolve' solver in MATLAB source code is used. The optimality of three sequences i.e. backward, mixed and splitting feed is studied by varying the various input parameters.Keywords: MATLAB "fsolve" solver, multiple effectevaporators, black liquor, feeding sequences.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3257521 A Decision Support System for Predicting Hospitalization of Hemodialysis Patients
Authors: Jinn-Yi Yeh, Tai-Hsi Wu
Abstract:
Hemodialysis patients might suffer from unhealthy care behaviors or long-term dialysis treatments. Ultimately they need to be hospitalized. If the hospitalization rate of a hemodialysis center is high, its quality of service would be low. Therefore, how to decrease hospitalization rate is a crucial problem for health care. In this study we combined temporal abstraction with data mining techniques for analyzing the dialysis patients' biochemical data to develop a decision support system. The mined temporal patterns are helpful for clinicians to predict hospitalization of hemodialysis patients and to suggest them some treatments immediately to avoid hospitalization.Keywords: Hemodialysis, Temporal abstract, Data mining, Healthcare quality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1729520 Multiple Sequence Alignment Using Optimization Algorithms
Authors: M. F. Omar, R. A. Salam, R. Abdullah, N. A. Rashid
Abstract:
Proteins or genes that have similar sequences are likely to perform the same function. One of the most widely used techniques for sequence comparison is sequence alignment. Sequence alignment allows mismatches and insertion/deletion, which represents biological mutations. Sequence alignment is usually performed only on two sequences. Multiple sequence alignment, is a natural extension of two-sequence alignment. In multiple sequence alignment, the emphasis is to find optimal alignment for a group of sequences. Several applicable techniques were observed in this research, from traditional method such as dynamic programming to the extend of widely used stochastic optimization method such as Genetic Algorithms (GAs) and Simulated Annealing. A framework with combination of Genetic Algorithm and Simulated Annealing is presented to solve Multiple Sequence Alignment problem. The Genetic Algorithm phase will try to find new region of solution while Simulated Annealing can be considered as an alignment improver for any near optimal solution produced by GAs.
Keywords: Simulated annealing, genetic algorithm, sequence alignment, multiple sequence alignment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2408519 Strong Law of Large Numbers for *- Mixing Sequence
Authors: Bainian Li, Kongsheng Zhang
Abstract:
Strong law of large numbers and complete convergence for sequences of *-mixing random variables are investigated. In particular, Teicher-s strong law of large numbers for independent random variables are generalized to the case of *-mixing random sequences and extended to independent and identically distributed Marcinkiewicz Law of large numbers for *-mixing.
Keywords: mixing squences, strong law of large numbers, martingale differences, Lacunary System
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1295518 A Probabilistic View of the Spatial Pooler in Hierarchical Temporal Memory
Authors: Mackenzie Leake, Liyu Xia, Kamil Rocki, Wayne Imaino
Abstract:
In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activation of columns in the spatial pooler is studied. Numerical results suggest that similar inputs are represented by similar sets of columns and dissimilar inputs are represented by dissimilar sets of columns. It is shown that the spatial pooler produces these results under certain conditions for the connectivity and proximal thresholds. Following the discussion of the initialization of parameters for the thresholds, corresponding qualitative arguments about the learning dynamics of the spatial pooler are discussed.Keywords: Hierarchical Temporal Memory, HTM, Learning Algorithms, Machine Learning, Spatial Pooler.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2195517 Surveillance Video Summarization Based on Histogram Differencing and Sum Conditional Variance
Authors: Nada Jasim Habeeb, Rana Saad Mohammed, Muntaha Khudair Abbass
Abstract:
For more efficient and fast video summarization, this paper presents a surveillance video summarization method. The presented method works to improve video summarization technique. This method depends on temporal differencing to extract most important data from large video stream. This method uses histogram differencing and Sum Conditional Variance which is robust against to illumination variations in order to extract motion objects. The experimental results showed that the presented method gives better output compared with temporal differencing based summarization techniques.
Keywords: Temporal differencing, video summarization, histogram differencing, sum conditional variance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1694516 Multi-Temporal Urban Land Cover Mapping Using Spectral Indices
Authors: Mst Ilme Faridatul, Bo Wu
Abstract:
Multi-temporal urban land cover mapping is of paramount importance for monitoring urban sprawl and managing the ecological environment. For diversified urban activities, it is challenging to map land covers in a complex urban environment. Spectral indices have proved to be effective for mapping urban land covers. To improve multi-temporal urban land cover classification and mapping, we evaluate the performance of three spectral indices, e.g. modified normalized difference bare-land index (MNDBI), tasseled cap water and vegetation index (TCWVI) and shadow index (ShDI). The MNDBI is developed to evaluate its performance of enhancing urban impervious areas by separating bare lands. A tasseled cap index, TCWVI is developed to evaluate its competence to detect vegetation and water simultaneously. The ShDI is developed to maximize the spectral difference between shadows of skyscrapers and water and enhance water detection. First, this paper presents a comparative analysis of three spectral indices using Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM) and Operational Land Imager (OLI) data. Second, optimized thresholds of the spectral indices are imputed to classify land covers, and finally, their performance of enhancing multi-temporal urban land cover mapping is assessed. The results indicate that the spectral indices are competent to enhance multi-temporal urban land cover mapping and achieves an overall classification accuracy of 93-96%.
Keywords: Land cover, mapping, multi-temporal, spectral indices.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1111515 Adaptive Kernel Filtering Used in Video Processing
Authors: Rasmus Engholm, Eva B. Vedel Jensen, Henrik Karstoft
Abstract:
In this paper we present a noise reduction filter for video processing. It is based on the recently proposed two dimensional steering kernel, extended to three dimensions and further augmented to suit the spatial-temporal domain of video processing. Two alternative filters are proposed - the time symmetric kernel and the time asymmetric kernel. The first reduces the noise on single sequences, but to handle the problems at scene shift the asymmetric kernel is introduced. The performance of both are tested on simulated data and on a real video sequence together with the existing steering kernel. The proposed kernels improves the Rooted Mean Squared Error (RMSE) compared to the original steering kernel method on video material.
Keywords: Adaptive image filtering, noise reduction, kernel methods, video processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1469514 Parallezation Protein Sequence Similarity Algorithms using Remote Method Interface
Authors: Mubarak Saif Mohsen, Zurinahni Zainol, Rosalina Abdul Salam, Wahidah Husain
Abstract:
One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.
Keywords: Protein sequence algorithm, dynamic programming algorithm, multithread
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1902513 SIMGraph: Simplifying Contig Graph to Improve de Novo Genome Assembly Using Next-generation Sequencing Data
Authors: Chien-Ju Li, Chun-Hui Yu, Chi-Chuan Hwang, Tsunglin Liu , Darby Tien-Hao Chang
Abstract:
De novo genome assembly is always fragmented. Assembly fragmentation is more serious using the popular next generation sequencing (NGS) data because NGS sequences are shorter than the traditional Sanger sequences. As the data throughput of NGS is high, the fragmentations in assemblies are usually not the result of missing data. On the contrary, the assembled sequences, called contigs, are often connected to more than one other contigs in a complicated manner, leading to the fragmentations. False connections in such complicated connections between contigs, named a contig graph, are inevitable because of repeats and sequencing/assembly errors. Simplifying a contig graph by removing false connections directly improves genome assembly. In this work, we have developed a tool, SIMGraph, to resolve ambiguous connections between contigs using NGS data. Applying SIMGraph to the assembly of a fungus and a fish genome, we resolved 27.6% and 60.3% ambiguous contig connections, respectively. These results can reduce the experimental efforts in resolving contig connections.
Keywords: Contig graph, NGS, de novo assembly, scaffold.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1734512 A Class of Recurrent Sequences Exhibiting Some Exciting Properties of Balancing Numbers
Abstract:
The balancing numbers are natural numbers n satisfying the Diophantine equation 1 + 2 + 3 + · · · + (n - 1) = (n + 1) + (n + 2) + · · · + (n + r); r is the balancer corresponding to the balancing number n.The nth balancing number is denoted by Bn and the sequence {Bn}1 n=1 satisfies the recurrence relation Bn+1 = 6Bn-Bn-1. The balancing numbers posses some curious properties, some like Fibonacci numbers and some others are more interesting. This paper is a study of recurrent sequence {xn}1 n=1 satisfying the recurrence relation xn+1 = Axn - Bxn-1 and possessing some curious properties like the balancing numbers.Keywords: Recurrent sequences, Balancing numbers, Lucas balancing numbers, Binet form.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1517511 A System of Automatic Speech Recognition based on the Technique of Temporal Retiming
Authors: Samir Abdelhamid, Noureddine Bouguechal
Abstract:
We report in this paper the procedure of a system of automatic speech recognition based on techniques of the dynamic programming. The technique of temporal retiming is a technique used to synchronize between two forms to compare. We will see how this technique is adapted to the field of the automatic speech recognition. We will expose, in a first place, the theory of the function of retiming which is used to compare and to adjust an unknown form with a whole of forms of reference constituting the vocabulary of the application. Then we will give, in the second place, the various algorithms necessary to their implementation on machine. The algorithms which we will present were tested on part of the corpus of words in Arab language Arabdic-10 [4] and gave whole satisfaction. These algorithms are effective insofar as we apply them to the small ones or average vocabularies.Keywords: Continuous speech recognition, temporal retiming, phonetic decoding, algorithms, vocal signal, dynamic programming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1346510 A Hybrid Image Fusion Model for Generating High Spatial-Temporal-Spectral Resolution Data Using OLI-MODIS-Hyperion Satellite Imagery
Authors: Yongquan Zhao, Bo Huang
Abstract:
Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.Keywords: Hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1235509 A Prediction of Attractive Evaluation Objects Based On Complex Sequential Data
Authors: Shigeaki Sakurai, Makino Kyoko, Shigeru Matsumoto
Abstract:
This paper proposes a method that predicts attractive evaluation objects. In the learning phase, the method inductively acquires trend rules from complex sequential data. The data is composed of two types of data. One is numerical sequential data. Each evaluation object has respective numerical sequential data. The other is text sequential data. Each evaluation object is described in texts. The trend rules represent changes of numerical values related to evaluation objects. In the prediction phase, the method applies new text sequential data to the trend rules and evaluates which evaluation objects are attractive. This paper verifies the effect of the proposed method by using stock price sequences and news headline sequences. In these sequences, each stock brand corresponds to an evaluation object. This paper discusses validity of predicted attractive evaluation objects, the process time of each phase, and the possibility of application tasks.
Keywords: Trend rule, frequent pattern, numerical sequential data, text sequential data, evaluation object.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1235508 Validation of Automation Systems using Temporal Logic Model Checking and Groebner Bases
Authors: Quoc-Nam Tran, Anjib Mulepati
Abstract:
Validation of an automation system is an important issue. The goal is to check if the system under investigation, modeled by a Petri net, never enters the undesired states. Usually, tools dedicated to Petri nets such as DESIGN/CPN are used to make reachability analysis. The biggest problem with this approach is that it is impossible to generate the full occurence graph of the system because it is too large. In this paper, we show how computational methods such as temporal logic model checking and Groebner bases can be used to verify the correctness of the design of an automation system. We report our experimental results with two automation systems: the Automated Guided Vehicle (AGV) system and the traffic light system. Validation of these two systems ranged from 10 to 30 seconds on a PC depending on the optimizing parameters.
Keywords: Computational Intelligence, Temporal Logic Reasoning, Model Checking, Groebner Bases.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1435507 The Effects of Four Organic Cropping Sequences on Soil Phosphorous Cycling and Arbuscular Mycorrhizal Fungi
Authors: R. J. Parham, J. D. Knight
Abstract:
Organic farmers across Saskatchewan face soil phosphorus (P) shortages. Due to the restriction on inputs in organic systems, farmers rely on crop rotation and naturally-occurring arbuscular mycorrhizal fungi (AMF) for plant P supply. Crop rotation is important for disease, pest, and weed management. Crops that are not colonized by AMF (non-mycorrhizal) can decrease colonization of a following crop. An experiment was performed to quantify soil P cycling in four cropping sequences under organic management and determine if mustard (non-mycorrhizal) was delaying the colonization of subsequent wheat. Soils from the four cropping sequences were measured for inorganic soil P (Pi), AMF spore density (SD), phospholipid fatty acid analysis (PLFA, for AMF biomarker counts), and alkaline phosphatase activity (ALPase, related to AMF metabolic activity). Plants were measured for AMF colonization and P content and uptake of above-ground biomass. A lack of difference in AMF activity indicated that mustard was not depressing colonization. Instead, AMF colonization was largely determined by crop type and crop rotation.
Keywords: Arbuscular mycorrhizal fungi, crop rotation, organic farming, phosphorous, soil microbiology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2110506 Urban Growth Analysis Using Multi-Temporal Satellite Images, Non-stationary Decomposition Methods and Stochastic Modeling
Authors: Ali Ben Abbes, ImedRiadh Farah, Vincent Barra
Abstract:
Remotely sensed data are a significant source for monitoring and updating databases for land use/cover. Nowadays, changes detection of urban area has been a subject of intensive researches. Timely and accurate data on spatio-temporal changes of urban areas are therefore required. The data extracted from multi-temporal satellite images are usually non-stationary. In fact, the changes evolve in time and space. This paper is an attempt to propose a methodology for changes detection in urban area by combining a non-stationary decomposition method and stochastic modeling. We consider as input of our methodology a sequence of satellite images I1, I2, … In at different periods (t = 1, 2, ..., n). Firstly, a preprocessing of multi-temporal satellite images is applied. (e.g. radiometric, atmospheric and geometric). The systematic study of global urban expansion in our methodology can be approached in two ways: The first considers the urban area as one same object as opposed to non-urban areas (e.g. vegetation, bare soil and water). The objective is to extract the urban mask. The second one aims to obtain a more knowledge of urban area, distinguishing different types of tissue within the urban area. In order to validate our approach, we used a database of Tres Cantos-Madrid in Spain, which is derived from Landsat for a period (from January 2004 to July 2013) by collecting two frames per year at a spatial resolution of 25 meters. The obtained results show the effectiveness of our method.
Keywords: Multi-temporal satellite image, urban growth, Non-stationarity, stochastic modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1504505 Efficient Mean Shift Clustering Using Exponential Integral Kernels
Authors: S. Sutor, R. Röhr, G. Pujolle, R. Reda
Abstract:
This paper presents a highly efficient algorithm for detecting and tracking humans and objects in video surveillance sequences. Mean shift clustering is applied on backgrounddifferenced image sequences. For efficiency, all calculations are performed on integral images. Novel corresponding exponential integral kernels are introduced to allow the application of nonuniform kernels for clustering, which dramatically increases robustness without giving up the efficiency of the integral data structures. Experimental results demonstrating the power of this approach are presented.
Keywords: Clustering, Integral Images, Kernels, Person Detection, Person Tracking, Intelligent Video Surveillance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1527504 Spatial and Temporal Variability of Fog Over the Indo-Gangetic Plains, India
Authors: Sanjay Kumar Srivastava, Anu Rani Sharma, Kamna Sachdeva
Abstract:
The aim of the paper is to analyze the characteristics of winter fog in terms of its trend and spatial-temporal variability over Indo-Gangetic plains. The study reveals that during last four and half decades (1971-2015), an alarming increasing trend in fog frequency has been observed during the winter months of December and January over the study area. The frequency of fog has increased by 118.4% during the peak winter months of December and January. It has also been observed that on an average central part of IGP has 66.29% fog days followed by west IGP with 41.94% fog days. Further, Empirical Orthogonal Function (EOF) decomposition and Mann-Kendall variation analysis are used to analyze the spatial and temporal patterns of winter fog. The findings have significant implications for the further research of fog over IGP and formulate robust strategies to adapt the fog variability and mitigate its effects. The decision by Delhi Government to implement odd-even scheme to restrict the use of private vehicles in order to reduce pollution and improve quality of air may result in increasing the alarming increasing trend of fog over Delhi and its surrounding areas regions of IGP.
Keywords: Fog, climatology, spatial variability, temporal variability, empirical orthogonal function, visibility, Mann-Kendall test, variation point.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1654503 Payment for Pain: Differences between Hypothetical and Real Preferences
Authors: J. Trarbach, S. Schosser, B. Vogt
Abstract:
Decision-makers tend to prefer the first alternative over subsequent alternatives which is called the primacy effect. To reliably measure this effect, we conducted an experiment with real consequences for preference statements. Therefore, we elicit preferences of subjects using a rating scale, i.e. hypothetical preferences, and willingness to pay, i.e. real preferences, for two sequences of pain. Within these sequences, both overall intensity and duration of pain are identical. Hence, a rational decision-maker should be indifferent, whereas the primacy effect predicts a stronger preference for the first sequence. What we see is a primacy effect only for hypothetical preferences. This effect vanishes for real preferences.
Keywords: Decision making, primacy effect, real incentives, willingness to pay.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 872502 A Simplified Higher-Order Markov Chain Model
Authors: Chao Wang, Ting-Zhu Huang, Chen Jia
Abstract:
In this paper, we present a simplified higher-order Markov chain model for multiple categorical data sequences also called as simplified higher-order multivariate Markov chain model.
Keywords: Higher-order multivariate Markov chain model, Categorical data sequences, Multivariate Markov chain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3287501 Spatio-Temporal Data Mining with Association Rules for Lake Van
Authors: T. Aydin, M. F. Alaeddinoglu
Abstract:
People, throughout the history, have made estimates and inferences about the future by using their past experiences. Developing information technologies and the improvements in the database management systems make it possible to extract useful information from knowledge in hand for the strategic decisions. Therefore, different methods have been developed. Data mining by association rules learning is one of such methods. Apriori algorithm, one of the well-known association rules learning algorithms, is not commonly used in spatio-temporal data sets. However, it is possible to embed time and space features into the data sets and make Apriori algorithm a suitable data mining technique for learning spatiotemporal association rules. Lake Van, the largest lake of Turkey, is a closed basin. This feature causes the volume of the lake to increase or decrease as a result of change in water amount it holds. In this study, evaporation, humidity, lake altitude, amount of rainfall and temperature parameters recorded in Lake Van region throughout the years are used by the Apriori algorithm and a spatio-temporal data mining application is developed to identify overflows and newlyformed soil regions (underflows) occurring in the coastal parts of Lake Van. Identifying possible reasons of overflows and underflows may be used to alert the experts to take precautions and make the necessary investments.Keywords: Apriori algorithm, association rules, data mining, spatio-temporal data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1405500 Using PFA in Feature Analysis and Selection for H.264 Adaptation
Authors: Nora A. Naguib, Ahmed E. Hussein, Hesham A. Keshk, Mohamed I. El-Adawy
Abstract:
Classification of video sequences based on their contents is a vital process for adaptation techniques. It helps decide which adaptation technique best fits the resource reduction requested by the client. In this paper we used the principal feature analysis algorithm to select a reduced subset of video features. The main idea is to select only one feature from each class based on the similarities between the features within that class. Our results showed that using this feature reduction technique the source video features can be completely omitted from future classification of video sequences.
Keywords: Adaptation, feature selection, H.264, Principal Feature Analysis (PFA)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1606499 A Study of Environmental Test Sequences for Electrical Units
Authors: Jung Ho Yang, Yong Soo Kim
Abstract:
Electrical units are operated by electrical and electronic components. An environmental test sequence is useful for testing electrical units to reduce reliability issues. This study introduces test sequence guidelines based on relevant principles and considerations for electronic testing according to International Standard IEC-60068-1 and the United States Military Standard MIL-STD-810G. Test sequences were then proposed based on the descriptions for each test. Finally, General Motors (GM) specification GMW3172 was interpreted and compared to IEC-60068-1 and MIL-STD-810G.
Keywords: Reliability, Environmental test sequence, Electrical units, IEC 60068-1, MIL-STD-810G.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4318498 Timescape-Based Panoramic View for Historic Landmarks
Authors: H. Ali, A. Whitehead
Abstract:
Providing a panoramic view of famous landmarks around the world offers artistic and historic value for historians, tourists, and researchers. Exploring the history of famous landmarks by presenting a comprehensive view of a temporal panorama merged with geographical and historical information presents a unique challenge of dealing with images that span a long period, from the 1800’s up to the present. This work presents the concept of temporal panorama through a timeline display of aligned historic and modern images for many famous landmarks. Utilization of this panorama requires a collection of hundreds of thousands of landmark images from the Internet comprised of historic images and modern images of the digital age. These images have to be classified for subset selection to keep the more suitable images that chronologically document a landmark’s history. Processing of historic images captured using older analog technology under various different capturing conditions represents a big challenge when they have to be used with modern digital images. Successful processing of historic images to prepare them for next steps of temporal panorama creation represents an active contribution in cultural heritage preservation through the fulfillment of one of UNESCO goals in preservation and displaying famous worldwide landmarks.
Keywords: Cultural heritage, image registration, image subset selection, registered image similarity, temporal panorama, timescapes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1051