Search results for: patch-based similarity metric
897 Similarity of the Disposition of the Electrostatic Potential of Tetrazole and Carboxylic Group to Investigate Their Bioisosteric Relationship
Authors: Alya A. Arabi
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Bioisosteres are functional groups that can be interchangeably used without affecting the potency of the drug. Bioisosteres have similar pharmacological properties. Bioisosterism is useful for modifying the physicochemical properties of a drug while obeying the Lipinski’s rules. Bioisosteres are key in optimizing the pharmacokinetic and pharmacodynamics properties of a drug. Tetrazole and carboxylate anions are non-classic bioisosteres. Density functional theory was used to obtain the wavefunction of the molecules and the optimized geometries. The quantum theory of atoms in molecules (QTAIM) was used to uncover the similarity of the average electron density in tetrazole and carboxylate anions. This similarity between the bioisosteres capped by a methyl group was valid despite the fact that the groups have different volumes, charges, energies, or electron populations. The biochemical correspondence of tetrazole and carboxylic acid was also determined to be a result of the similarity of the topography of the electrostatic potential (ESP). The ESP demonstrates the pharmacological and biochemical resemblance for a matching “key-and-lock” interaction.Keywords: bioisosteres, carboxylic acid, density functional theory, electrostatic potential, tetrazole
Procedia PDF Downloads 438896 Genetic Diversity Analysis in Triticum Aestivum Using Microsatellite Markers
Authors: Prachi Sharma, Mukesh Kumar Rana
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In the present study, the simple sequence repeat(SSR) markers have been used in analysis of genetic diversity of 37 genotypes of Triticum aestivum. The DNA was extracted using cTAB method. The DNA was quantified using the fluorimeter. The annealing temperatures for 27 primer pairs were standardized using gradient PCR, out of which 16 primers gave satisfactory amplification at temperature ranging from 50-62⁰ C. Out of 16 polymorphic SSR markers only 10 SSR primer pairs were used in the study generating 34 reproducible amplicons among 37 genotypes out of which 30 were polymorphic. Primer pairs Xgwm533, Xgwm 160, Xgwm 408, Xgwm 120, Xgwm 186, Xgwm 261 produced maximum percent of polymorphic bands (100%). The bands ranged on an average of 3.4 bands per primer. The genetic relationship was determined using Jaccard pair wise similarity co-efficient and UPGMA cluster analysis with NTSYS Pc.2 software. The values of similarity index range from 0-1. The similarity coefficient ranged from 0.13 to 0.97. A minimum genetic similarity (0.13) was observed between VL 804 and HPW 288, meaning they are only 13% similar. More number of available SSR markers can be useful for supporting the genetic diversity analysis in the above wheat genotypes.Keywords: wheat, genetic diversity, microsatellite, polymorphism
Procedia PDF Downloads 615895 Resilience Assessment for Power Distribution Systems
Authors: Berna Eren Tokgoz, Mahdi Safa, Seokyon Hwang
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Power distribution systems are essential and crucial infrastructures for the development and maintenance of a sustainable society. These systems are extremely vulnerable to various types of natural and man-made disasters. The assessment of resilience focuses on preparedness and mitigation actions under pre-disaster conditions. It also concentrates on response and recovery actions under post-disaster situations. The aim of this study is to present a methodology to assess the resilience of electric power distribution poles against wind-related events. The proposed methodology can improve the accuracy and rapidity of the evaluation of the conditions and the assessment of the resilience of poles. The methodology provides a metric for the evaluation of the resilience of poles under pre-disaster and post-disaster conditions. The metric was developed using mathematical expressions for physical forces that involve various variables, such as physical dimensions of the pole, the inclination of the pole, and wind speed. A three-dimensional imaging technology (photogrammetry) was used to determine the inclination of poles. Based on expert opinion, the proposed metric was used to define zones to visualize resilience. Visual representation of resilience is helpful for decision makers to prioritize their resources before and after experiencing a wind-related disaster. Multiple electric poles in the City of Beaumont, TX were used in a case study to evaluate the proposed methodology.Keywords: photogrammetry, power distribution systems, resilience metric, system resilience, wind-related disasters
Procedia PDF Downloads 221894 Cross-Dialect Sentence Transformation: A Comparative Analysis of Language Models for Adapting Sentences to British English
Authors: Shashwat Mookherjee, Shruti Dutta
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This study explores linguistic distinctions among American, Indian, and Irish English dialects and assesses various Language Models (LLMs) in their ability to generate British English translations from these dialects. Using cosine similarity analysis, the study measures the linguistic proximity between original British English translations and those produced by LLMs for each dialect. The findings reveal that Indian and Irish English translations maintain notably high similarity scores, suggesting strong linguistic alignment with British English. In contrast, American English exhibits slightly lower similarity, reflecting its distinct linguistic traits. Additionally, the choice of LLM significantly impacts translation quality, with Llama-2-70b consistently demonstrating superior performance. The study underscores the importance of selecting the right model for dialect translation, emphasizing the role of linguistic expertise and contextual understanding in achieving accurate translations.Keywords: cross-dialect translation, language models, linguistic similarity, multilingual NLP
Procedia PDF Downloads 77893 Benchmarking Bert-Based Low-Resource Language: Case Uzbek NLP Models
Authors: Jamshid Qodirov, Sirojiddin Komolov, Ravilov Mirahmad, Olimjon Mirzayev
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Nowadays, natural language processing tools play a crucial role in our daily lives, including various techniques with text processing. There are very advanced models in modern languages, such as English, Russian etc. But, in some languages, such as Uzbek, the NLP models have been developed recently. Thus, there are only a few NLP models in Uzbek language. Moreover, there is no such work that could show which Uzbek NLP model behaves in different situations and when to use them. This work tries to close this gap and compares the Uzbek NLP models existing as of the time this article was written. The authors try to compare the NLP models in two different scenarios: sentiment analysis and sentence similarity, which are the implementations of the two most common problems in the industry: classification and similarity. Another outcome from this work is two datasets for classification and sentence similarity in Uzbek language that we generated ourselves and can be useful in both industry and academia as well.Keywords: NLP, benchmak, bert, vectorization
Procedia PDF Downloads 55892 Biohydrogen Production Derived from Banana Pseudo Stem of Agricultural Residues by Dark Fermentation
Authors: Kholik
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Nowadays, the demand of renewable energy in general is increasing due to the crisis of fossil fuels. Biohydrogen is an alternative fuel with zero emission derived from renewable resources such as banana pseudo stem of agricultural residues. Banana plant can be easily found in tropical and subtropical areas, so the resource is abundant and readily available as a biohydrogen substrate. Banana pseudo stem has not been utilised as a resource or substrate of biohydrogen production and it mainly contains 45-65% cellulose (α-cellulose), 5-15% hemicellulose and 20-30% Lignin, which indicates that banana pseudo stem will be renewable, sustainable and promising resource as lignocellulosic biomass. In this research, biohydrogen is derived from banana pseudo stem by dark fermentation. Dark fermentation is the most suitable approach for practical biohydrogen production from organic solid wastes. The process has several advantages including a fast reaction rate, no need of light, and a smaller footprint. 321 million metric tonnes banana pseudo stem of 428 million metric tonnes banana plantation residues in worldwide for 2013 and 22.5 million metric tonnes banana pseudo stem of 30 million metric tonnes banana plantation residues in Indonesia for 2015 will be able to generate 810.60 million tonne mol H2 and 56.819 million tonne mol H2, respectively. In this paper, we will show that the banana pseudo stem is the renewable, sustainable and promising resource to be utilised and to produce biohydrogen as energy generation with high yield and high contain of cellulose in comparison with the other substrates.Keywords: banana pseudo stem, biohydrogen, dark fermentation, lignocellulosic
Procedia PDF Downloads 352891 Gravitational Wave Solutions in Modified Gravity Theories
Authors: Hafiza Rizwana Kausar
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In this paper, we formulate the wave equation in modified theories, particularly in f(R) theory, scalar-tensor theory, and metric palatine f(X) theory. We solve the wave equation in each case and try to find maximum possible solutions in the form polarization modes. It is found that modified theories present at most six modes however the mentioned metric theories allow four polarization modes, two of which are tensor in nature and other two are scalars.Keywords: gravitational waves, modified theories, polariozation modes, scalar tensor theories
Procedia PDF Downloads 363890 Classification of Hyperspectral Image Using Mathematical Morphological Operator-Based Distance Metric
Authors: Geetika Barman, B. S. Daya Sagar
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In this article, we proposed a pixel-wise classification of hyperspectral images using a mathematical morphology operator-based distance metric called “dilation distance” and “erosion distance”. This method involves measuring the spatial distance between the spectral features of a hyperspectral image across the bands. The key concept of the proposed approach is that the “dilation distance” is the maximum distance a pixel can be moved without changing its classification, whereas the “erosion distance” is the maximum distance that a pixel can be moved before changing its classification. The spectral signature of the hyperspectral image carries unique class information and shape for each class. This article demonstrates how easily the dilation and erosion distance can measure spatial distance compared to other approaches. This property is used to calculate the spatial distance between hyperspectral image feature vectors across the bands. The dissimilarity matrix is then constructed using both measures extracted from the feature spaces. The measured distance metric is used to distinguish between the spectral features of various classes and precisely distinguish between each class. This is illustrated using both toy data and real datasets. Furthermore, we investigated the role of flat vs. non-flat structuring elements in capturing the spatial features of each class in the hyperspectral image. In order to validate, we compared the proposed approach to other existing methods and demonstrated empirically that mathematical operator-based distance metric classification provided competitive results and outperformed some of them.Keywords: dilation distance, erosion distance, hyperspectral image classification, mathematical morphology
Procedia PDF Downloads 88889 On Projective Invariants of Spherically Symmetric Finsler Spaces in Rn
Authors: Nasrin Sadeghzadeh
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In this paper we study projective invariants of spherically symmetric Finsler metrics in Rn. We find the necessary and sufficient conditions for the metrics to be Douglas and Generalized Douglas-Weyl (GDW) types. Also we show that two classes of GDW and Douglas spherically symmetric Finsler metrics coincide.Keywords: spherically symmetric finsler metrics in Rn, finsler metrics, douglas metric, generalized Douglas-Weyl (GDW) metric
Procedia PDF Downloads 361888 A Geometrical Perspective on the Insulin Evolution
Authors: Yuhei Kunihiro, Sorin V. Sabau, Kazuhiro Shibuya
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We study the molecular evolution of insulin from the metric geometry point of view. In mathematics, and particularly in geometry, distances and metrics between objects are of fundamental importance. Using a weaker notion than the classical distance, namely the weighted quasi-metrics, one can study the geometry of biological sequences (DNA, mRNA, or proteins) space. We analyze from the geometrical point of view a family of 60 insulin homologous sequences ranging on a large variety of living organisms from human to the nematode C. elegans. We show that the distances between sequences provide important information about the evolution and function of insulin.Keywords: metric geometry, evolution, insulin, C. elegans
Procedia PDF Downloads 339887 A Comparative Assessment of Daylighting Metrics Assessing the Daylighting Performance of Three Shading Devices under Four Different Orientations
Authors: Mohamed Boubekri, Jaewook Lee
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The assessment of the daylighting performance of a design solution is a complex task due to the changing nature of daylight. A few quantitative metrics are available to designers to assess such a performance, among them are the mean hourly illuminance (MHI), the daylight factor (DF), the daylight autonomy (DA) and the useful daylight illuminance (UDI). Each of these metrics has criteria and limitations that affect the outcome of the evaluation. When to use one metric instead of another depends largely on the design goals to be achieved. Using Design Iterate Validate Adapt (DIVA) daylighting simulation program we set out to examine the performance behavior of these four metrics with the changing dimensions of three shading devices: a horizontal overhang, a horizontal louver system, and a vertical louver system, and compare their performance behavior as the orientation of the window changes. The context is a classroom of a prototypical elementary school in South Korea. Our results indicate that not all four metrics behave similarly as we vary the size of each shading device and as orientations changes. The UDI is the metric that leads to outcome most different than the other three metrics. Our conclusion is that not all daylighting metrics lead to the same conclusions and that it is important to use the metric that corresponds to the specific goals and objectives of the daylighting solution.Keywords: daylight factor, hourly daylight illuminance, daylight autonomy, useful daylight illuminance
Procedia PDF Downloads 285886 Analysis of Chatterjea Type F-Contraction in F-Metric Space and Application
Authors: Awais Asif
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This article investigates fixed point theorems of Chatterjea type F-contraction in the setting of F-metric space. We relax the conditions of F-contraction and define modified F-contraction for two mappings. The study provides fixed point results for both single-valued and multivalued mappings. The results are further extended to common fixed point theorems for two mappings. Moreover, to discuss the applicability of our results, an application is provided, which shows the role of our results in finding the solution to functional equations in dynamic programming. Our results generalize and extend the existing results in the literature.Keywords: Chatterjea type F-contraction, F-cauchy sequence, F-convergent, multi valued mappings
Procedia PDF Downloads 143885 Positive-Negative Asymmetry in the Evaluations of Political Candidates: The Mediating Role of Affect in the Relationship between Cognitive Evaluation and Voting Intention
Authors: Magdalena Jablonska, Andrzej Falkowski
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The negativity effect is one of the most intriguing and well-studied psychological phenomena that can be observed in many areas of human life. The aim of the following study is to investigate how valence framing and positive and negative information about political candidates affect judgments about similarity to an ideal and bad politician. Based on the theoretical framework of features of similarity, it is hypothesized that negative features have a stronger effect on similarity judgments than positive features of comparable value. Furthermore, the mediating role of affect is tested. Method: One hundred sixty-one people took part in an experimental study. Participants were divided into 6 research conditions that differed in the reference point (positive vs negative framing) and the number of favourable and unfavourable information items about political candidates (a positive, neutral and negative candidate profile). In positive framing condition, the concept of an ideal politician was primed; in the negative condition, participants were to think about a bad politician. The effect of independent variables on similarity judgments, affective evaluation, and voting intention was tested. Results: In the positive condition, the analysis showed that the negative effect of additional unfavourable features was greater than the positive effect of additional favourable features in judgements about similarity to the ideal candidate. In negative framing condition, ANOVA was insignificant, showing that neither the addition of positive features nor additional negative information had a significant impact on the similarity to a bad political candidate. To explain this asymmetry, two mediational analyses were conducted that tested the mediating role of affect in the relationship between similarity judgments and voting intention. In both situations the mediating effect was significant, but the comparison of two models showed that the mediation was stronger for a negative framing. Discussion: The research supports the negativity effect and attempts to explain the psychological mechanism behind the positive-negative asymmetry. The results of mediation analyses point to a stronger mediating role of affect in the relationship between cognitive evaluation and voting intention. Such a result suggests that negative comparisons, leading to the activation of negative features, give rise to stronger emotions than positive features of comparable strength. The findings are in line with positive-negative asymmetry, however, by adopting Tversky’s framework of features of similarity, the study integrates the cognitive mechanism of the negativity effect delineated in the contrast model of similarity with its emotional component resulting from the asymmetrical effect of positive and negative emotions on decision-making.Keywords: affect, framing, negativity effect, positive-negative asymmetry, similarity judgements
Procedia PDF Downloads 198884 Factorial Design Analysis for Quality of Video on MANET
Authors: Hyoup-Sang Yoon
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The quality of video transmitted by mobile ad hoc networks (MANETs) can be influenced by several factors, including protocol layers; parameter settings of each protocol. In this paper, we are concerned with understanding the functional relationship between these influential factors and objective video quality in MANETs. We illustrate a systematic statistical design of experiments (DOE) strategy can be used to analyse MANET parameters and performance. Using a 2k factorial design, we quantify the main and interactive effects of 7 factors on a response metric (i.e., mean opinion score (MOS) calculated by PSNR with Evalvid package) we then develop a first-order linear regression model between the influential factors and the performance metric.Keywords: evalvid, full factorial design, mobile ad hoc networks, ns-2
Procedia PDF Downloads 415883 Unsupervised Learning of Spatiotemporally Coherent Metrics
Authors: Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun
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Current state-of-the-art classification and detection algorithms rely on supervised training. In this work we study unsupervised feature learning in the context of temporally coherent video data. We focus on feature learning from unlabeled video data, using the assumption that adjacent video frames contain semantically similar information. This assumption is exploited to train a convolutional pooling auto-encoder regularized by slowness and sparsity. We establish a connection between slow feature learning to metric learning and show that the trained encoder can be used to define a more temporally and semantically coherent metric.Keywords: machine learning, pattern clustering, pooling, classification
Procedia PDF Downloads 456882 Frequency- and Content-Based Tag Cloud Font Distribution Algorithm
Authors: Ágnes Bogárdi-Mészöly, Takeshi Hashimoto, Shohei Yokoyama, Hiroshi Ishikawa
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The spread of Web 2.0 has caused user-generated content explosion. Users can tag resources to describe and organize them. Tag clouds provide rough impression of relative importance of each tag within overall cloud in order to facilitate browsing among numerous tags and resources. The goal of our paper is to enrich visualization of tag clouds. A font distribution algorithm has been proposed to calculate a novel metric based on frequency and content, and to classify among classes from this metric based on power law distribution and percentages. The suggested algorithm has been validated and verified on the tag cloud of a real-world thesis portal.Keywords: tag cloud, font distribution algorithm, frequency-based, content-based, power law
Procedia PDF Downloads 506881 Robust Image Registration Based on an Adaptive Normalized Mutual Information Metric
Authors: Huda Algharib, Amal Algharib, Hanan Algharib, Ali Mohammad Alqudah
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Image registration is an important topic for many imaging systems and computer vision applications. The standard image registration techniques such as Mutual information/ Normalized mutual information -based methods have a limited performance because they do not consider the spatial information or the relationships between the neighbouring pixels or voxels. In addition, the amount of image noise may significantly affect the registration accuracy. Therefore, this paper proposes an efficient method that explicitly considers the relationships between the adjacent pixels, where the gradient information of the reference and scene images is extracted first, and then the cosine similarity of the extracted gradient information is computed and used to improve the accuracy of the standard normalized mutual information measure. Our experimental results on different data types (i.e. CT, MRI and thermal images) show that the proposed method outperforms a number of image registration techniques in terms of the accuracy.Keywords: image registration, mutual information, image gradients, image transformations
Procedia PDF Downloads 248880 Alignment in Earnings Management Research: Italy Looking towards US
Authors: Giulia Leoni, Cristina Florio
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The paper aims to investigate the factors driving the increasing alignment of Italian earnings management (EM) research to US research on the same field. After characterizing the progressive similarity of Italian EM research with respect to US one by means of an historical comparison, the paper relies on a subsequent secondary source analysis to detect the possible causes of said alignment. Once identified that the alignment increased along three subsequent periods, the paper analyses and discusses this incremental similarity according to new institutional sociology (NIS) and highlights the presence of different combination of isomorphic pressures that help explaining this incremental similarity. The paper contributes to the institutional literature by providing evidence of isomorphism in academic research; it also contributes to accounting research by indicating the forces that are able to drive change and development in accounting research at national and international level. The paper also enlarges the explanatory value of NIS in alternative contexts, like academic accounting research.Keywords: accounting research, earnings management, international comparison, Italy, new institutional sociology, US
Procedia PDF Downloads 573879 Structural Balance and Creative Tensions in New Product Development Teams
Authors: Shankaran Sitarama
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New Product Development involves team members coming together and working in teams to come up with innovative solutions to problems, resulting in new products. Thus, a core attribute of a successful NPD team is their creativity and innovation. They need to be creative as a group, generating a breadth of ideas and innovative solutions that solve or address the problem they are targeting and meet the user’s needs. They also need to be very efficient in their teamwork as they work through the various stages of the development of these ideas, resulting in a POC (proof-of-concept) implementation or a prototype of the product. There are two distinctive traits that the teams need to have, one is ideational creativity, and the other is effective and efficient teamworking. There are multiple types of tensions that each of these traits cause in the teams, and these tensions reflect in the team dynamics. Ideational conflicts arising out of debates and deliberations increase the collective knowledge and affect the team creativity positively. However, the same trait of challenging each other’s viewpoints might lead the team members to be disruptive, resulting in interpersonal tensions, which in turn lead to less than efficient teamwork. Teams that foster and effectively manage these creative tensions are successful, and teams that are not able to manage these tensions show poor team performance. In this paper, it explore these tensions as they result in the team communication social network and propose a Creative Tension Balance index along the lines of Degree of Balance in social networks that has the potential to highlight the successful (and unsuccessful) NPD teams. Team communication reflects the team dynamics among team members and is the data set for analysis. The emails between the members of the NPD teams are processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. This social network is subjected to traditional social network analysis methods to arrive at some established metrics and structural balance analysis metrics. Traditional structural balance is extended to include team interaction pattern metrics to arrive at a creative tension balance metric that effectively captures the creative tensions and tension balance in teams. This CTB (Creative Tension Balance) metric truly captures the signatures of successful and unsuccessful (dissonant) NPD teams. The dataset for this research study includes 23 NPD teams spread out over multiple semesters and computes this CTB metric and uses it to identify the most successful and unsuccessful teams by classifying these teams into low, high and medium performing teams. The results are correlated to the team reflections (for team dynamics and interaction patterns), the team self-evaluation feedback surveys (for teamwork metrics) and team performance through a comprehensive team grade (for high and low performing team signatures).Keywords: team dynamics, social network analysis, new product development teamwork, structural balance, NPD teams
Procedia PDF Downloads 80878 Prediction of Bubbly Plume Characteristics Using the Self-Similarity Model
Authors: Li Chen, Alex Skvortsov, Chris Norwood
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Gas releasing into water can be found in for many industrial situations. This process results in the formation of bubbles and acoustic emission which depends upon the bubble characteristics. If the bubble creation rates (bubble volume flow rate) are of interest, an inverse method has to be used based on the measurement of acoustic emission. However, there will be sound attenuation through the bubbly plume which will influence the measurement and should be taken into consideration in the model. The sound transmission through the bubbly plume depends on the characteristics of the bubbly plume, such as the shape and the bubble distributions. In this study, the bubbly plume shape is modelled using a self-similarity model, which has been normally applied for a single phase buoyant plume. The prediction is compared with the experimental data. It has been found the model can be applied to a buoyant plume of gas-liquid mixture. The influence of the gas flow rate and discharge nozzle size is studied.Keywords: bubbly plume, buoyant plume, bubble acoustics, self-similarity model
Procedia PDF Downloads 287877 Evaluation and Compression of Different Language Transformer Models for Semantic Textual Similarity Binary Task Using Minority Language Resources
Authors: Ma. Gracia Corazon Cayanan, Kai Yuen Cheong, Li Sha
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Training a language model for a minority language has been a challenging task. The lack of available corpora to train and fine-tune state-of-the-art language models is still a challenge in the area of Natural Language Processing (NLP). Moreover, the need for high computational resources and bulk data limit the attainment of this task. In this paper, we presented the following contributions: (1) we introduce and used a translation pair set of Tagalog and English (TL-EN) in pre-training a language model to a minority language resource; (2) we fine-tuned and evaluated top-ranking and pre-trained semantic textual similarity binary task (STSB) models, to both TL-EN and STS dataset pairs. (3) then, we reduced the size of the model to offset the need for high computational resources. Based on our results, the models that were pre-trained to translation pairs and STS pairs can perform well for STSB task. Also, having it reduced to a smaller dimension has no negative effect on the performance but rather has a notable increase on the similarity scores. Moreover, models that were pre-trained to a similar dataset have a tremendous effect on the model’s performance scores.Keywords: semantic matching, semantic textual similarity binary task, low resource minority language, fine-tuning, dimension reduction, transformer models
Procedia PDF Downloads 211876 Maintenance Alternatives Related to Costs of Wind Turbines Using Finite State Markov Model
Authors: Boukelkoul Lahcen
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The cumulative costs for O&M may represent as much as 65%-90% of the turbine's investment cost. Nowadays the cost effectiveness concept becomes a decision-making and technology evaluation metric. The cost of energy metric accounts for the effect replacement cost and unscheduled maintenance cost parameters. One key of the proposed approach is the idea of maintaining the WTs which can be captured via use of a finite state Markov chain. Such a model can be embedded within a probabilistic operation and maintenance simulation reflecting the action to be done. In this paper, an approach of estimating the cost of O&M is presented. The finite state Markov model is used for decision problems with number of determined periods (life cycle) to predict the cost according to various options of maintenance.Keywords: cost, finite state, Markov model, operation and maintenance
Procedia PDF Downloads 533875 Mutual Information Based Image Registration of Satellite Images Using PSO-GA Hybrid Algorithm
Authors: Dipti Patra, Guguloth Uma, Smita Pradhan
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Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information
Procedia PDF Downloads 409874 Study on the Self-Location Estimate by the Evolutional Triangle Similarity Matching Using Artificial Bee Colony Algorithm
Authors: Yuji Kageyama, Shin Nagata, Tatsuya Takino, Izuru Nomura, Hiroyuki Kamata
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In previous study, technique to estimate a self-location by using a lunar image is proposed. We consider the improvement of the conventional method in consideration of FPGA implementation in this paper. Specifically, we introduce Artificial Bee Colony algorithm for reduction of search time. In addition, we use fixed point arithmetic to enable high-speed operation on FPGA.Keywords: SLIM, Artificial Bee Colony Algorithm, location estimate, evolutional triangle similarity
Procedia PDF Downloads 519873 Destination Port Detection For Vessels: An Analytic Tool For Optimizing Port Authorities Resources
Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin
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Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization
Procedia PDF Downloads 122872 Recognizing Customer Preferences Using Review Documents: A Hybrid Text and Data Mining Approach
Authors: Oshin Anand, Atanu Rakshit
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The vast increment in the e-commerce ventures makes this area a prominent research stream. Besides several quantified parameters, the textual content of reviews is a storehouse of many information that can educate companies and help them earn profit. This study is an attempt in this direction. The article attempts to categorize data based on a computed metric that quantifies the influencing capacity of reviews rendering two categories of high and low influential reviews. Further, each of these document is studied to conclude several product feature categories. Each of these categories along with the computed metric is converted to linguistic identifiers and are used in an association mining model. The article makes a novel attempt to combine feature attraction with quantified metric to categorize review text and finally provide frequent patterns that depict customer preferences. Frequent mentions in a highly influential score depict customer likes or preferred features in the product whereas prominent pattern in low influencing reviews highlights what is not important for customers. This is achieved using a hybrid approach of text mining for feature and term extraction, sentiment analysis, multicriteria decision-making technique and association mining model.Keywords: association mining, customer preference, frequent pattern, online reviews, text mining
Procedia PDF Downloads 389871 Flow and Heat Transfer of a Nanofluid over a Shrinking Sheet
Authors: N. Bachok, N. L. Aleng, N. M. Arifin, A. Ishak, N. Senu
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The problem of laminar fluid flow which results from the shrinking of a permeable surface in a nanofluid has been investigated numerically. The model used for the nanofluid incorporates the effects of Brownian motion and thermophoresis. A similarity solution is presented which depends on the mass suction parameter S, Prandtl number Pr, Lewis number Le, Brownian motion number Nb and thermophoresis number Nt. It was found that the reduced Nusselt number is decreasing function of each dimensionless number.Keywords: Boundary layer, nanofluid, shrinking sheet, Brownian motion, thermophoresis, similarity solution
Procedia PDF Downloads 415870 A Comparison between Different Segmentation Techniques Used in Medical Imaging
Authors: Ibtihal D. Mustafa, Mawia A. Hassan
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Tumor segmentation from MRI image is important part of medical images experts. This is particularly a challenging task because of the high assorting appearance of tumor tissue among different patients. MRI images are advance of medical imaging because it is give richer information about human soft tissue. There are different segmentation techniques to detect MRI brain tumor. In this paper, different procedure segmentation methods are used to segment brain tumors and compare the result of segmentations by using correlation and structural similarity index (SSIM) to analysis and see the best technique that could be applied to MRI image.Keywords: MRI, segmentation, correlation, structural similarity
Procedia PDF Downloads 410869 3D Object Retrieval Based on Similarity Calculation in 3D Computer Aided Design Systems
Authors: Ahmed Fradi
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Nowadays, recent technological advances in the acquisition, modeling, and processing of three-dimensional (3D) objects data lead to the creation of models stored in huge databases, which are used in various domains such as computer vision, augmented reality, game industry, medicine, CAD (Computer-aided design), 3D printing etc. On the other hand, the industry is currently benefiting from powerful modeling tools enabling designers to easily and quickly produce 3D models. The great ease of acquisition and modeling of 3D objects make possible to create large 3D models databases, then, it becomes difficult to navigate them. Therefore, the indexing of 3D objects appears as a necessary and promising solution to manage this type of data, to extract model information, retrieve an existing model or calculate similarity between 3D objects. The objective of the proposed research is to develop a framework allowing easy and fast access to 3D objects in a CAD models database with specific indexing algorithm to find objects similar to a reference model. Our main objectives are to study existing methods of similarity calculation of 3D objects (essentially shape-based methods) by specifying the characteristics of each method as well as the difference between them, and then we will propose a new approach for indexing and comparing 3D models, which is suitable for our case study and which is based on some previously studied methods. Our proposed approach is finally illustrated by an implementation, and evaluated in a professional context.Keywords: CAD, 3D object retrieval, shape based retrieval, similarity calculation
Procedia PDF Downloads 263868 Hybrid Approximate Structural-Semantic Frequent Subgraph Mining
Authors: Montaceur Zaghdoud, Mohamed Moussaoui, Jalel Akaichi
Abstract:
Frequent subgraph mining refers usually to graph matching and it is widely used in when analyzing big data with large graphs. A lot of research works dealt with structural exact or inexact graph matching but a little attention is paid to semantic matching when graph vertices and/or edges are attributed and typed. Therefore, it seems very interesting to integrate background knowledge into the analysis and that extracted frequent subgraphs should become more pruned by applying a new semantic filter instead of using only structural similarity in graph matching process. Consequently, this paper focuses on developing a new hybrid approximate structuralsemantic graph matching to discover a set of frequent subgraphs. It uses simultaneously an approximate structural similarity function based on graph edit distance function and a possibilistic vertices similarity function based on affinity function. Both structural and semantic filters contribute together to prune extracted frequent set. Indeed, new hybrid structural-semantic frequent subgraph mining approach searches will be suitable to be applied to several application such as community detection in social networks.Keywords: approximate graph matching, hybrid frequent subgraph mining, graph mining, possibility theory
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