Search results for: matching number
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10151

Search results for: matching number

10091 SIFT and Perceptual Zoning Applied to CBIR Systems

Authors: Simone B. K. Aires, Cinthia O. de A. Freitas, Luiz E. S. Oliveira

Abstract:

This paper contributes to the CBIR systems applied to trademark retrieval. The proposed model includes aspects from visual perception of the shapes, by means of feature extractor associated to a non-symmetrical perceptual zoning mechanism based on the Principles of Gestalt. Thus, the feature set were performed using Scale Invariant Feature Transform (SIFT). We carried out experiments using four different zonings strategies (Z = 4, 5H, 5V, 7) for matching and retrieval tasks. Our proposal method achieved the normalized recall (Rn) equal to 0.84. Experiments show that the non-symmetrical zoning could be considered as a tool to build more reliable trademark retrieval systems.

Keywords: CBIR, Gestalt, matching, non-symmetrical zoning, SIFT

Procedia PDF Downloads 274
10090 Myanmar Character Recognition Using Eight Direction Chain Code Frequency Features

Authors: Kyi Pyar Zaw, Zin Mar Kyu

Abstract:

Character recognition is the process of converting a text image file into editable and searchable text file. Feature Extraction is the heart of any character recognition system. The character recognition rate may be low or high depending on the extracted features. In the proposed paper, 25 features for one character are used in character recognition. Basically, there are three steps of character recognition such as character segmentation, feature extraction and classification. In segmentation step, horizontal cropping method is used for line segmentation and vertical cropping method is used for character segmentation. In the Feature extraction step, features are extracted in two ways. The first way is that the 8 features are extracted from the entire input character using eight direction chain code frequency extraction. The second way is that the input character is divided into 16 blocks. For each block, although 8 feature values are obtained through eight-direction chain code frequency extraction method, we define the sum of these 8 feature values as a feature for one block. Therefore, 16 features are extracted from that 16 blocks in the second way. We use the number of holes feature to cluster the similar characters. We can recognize the almost Myanmar common characters with various font sizes by using these features. All these 25 features are used in both training part and testing part. In the classification step, the characters are classified by matching the all features of input character with already trained features of characters.

Keywords: chain code frequency, character recognition, feature extraction, features matching, segmentation

Procedia PDF Downloads 281
10089 Element-Independent Implementation for Method of Lagrange Multipliers

Authors: Gil-Eon Jeong, Sung-Kie Youn, K. C. Park

Abstract:

Treatment for the non-matching interface is an important computational issue. To handle this problem, the method of Lagrange multipliers including classical and localized versions are the most popular technique. It essentially imposes the interface compatibility conditions by introducing Lagrange multipliers. However, the numerical system becomes unstable and inefficient due to the Lagrange multipliers. The interface element-independent formulation that does not include the Lagrange multipliers can be obtained by modifying the independent variables mathematically. Through this modification, more efficient and stable system can be achieved while involving equivalent accuracy comparing with the conventional method. A numerical example is conducted to verify the validity of the presented method.

Keywords: element-independent formulation, interface coupling, methods of Lagrange multipliers, non-matching interface

Procedia PDF Downloads 376
10088 Size Reduction of Images Using Constraint Optimization Approach for Machine Communications

Authors: Chee Sun Won

Abstract:

This paper presents the size reduction of images for machine-to-machine communications. Here, the salient image regions to be preserved include the image patches of the key-points such as corners and blobs. Based on a saliency image map from the key-points and their image patches, an axis-aligned grid-size optimization is proposed for the reduction of image size. To increase the size-reduction efficiency the aspect ratio constraint is relaxed in the constraint optimization framework. The proposed method yields higher matching accuracy after the size reduction than the conventional content-aware image size-reduction methods.

Keywords: image compression, image matching, key-point detection and description, machine-to-machine communication

Procedia PDF Downloads 374
10087 Quick Similarity Measurement of Binary Images via Probabilistic Pixel Mapping

Authors: Adnan A. Y. Mustafa

Abstract:

In this paper we present a quick technique to measure the similarity between binary images. The technique is based on a probabilistic mapping approach and is fast because only a minute percentage of the image pixels need to be compared to measure the similarity, and not the whole image. We exploit the power of the Probabilistic Matching Model for Binary Images (PMMBI) to arrive at an estimate of the similarity. We show that the estimate is a good approximation of the actual value, and the quality of the estimate can be improved further with increased image mappings. Furthermore, the technique is image size invariant; the similarity between big images can be measured as fast as that for small images. Examples of trials conducted on real images are presented.

Keywords: big images, binary images, image matching, image similarity

Procedia PDF Downloads 150
10086 A Graph-Based Retrieval Model for Passage Search

Authors: Junjie Zhong, Kai Hong, Lei Wang

Abstract:

Passage Retrieval (PR) plays an important role in many Natural Language Processing (NLP) tasks. Traditional efficient retrieval models relying on exact term-matching, such as TF-IDF or BM25, have nowadays been exceeded by pre-trained language models which match by semantics. Though they gain effectiveness, deep language models often require large memory as well as time cost. To tackle the trade-off between efficiency and effectiveness in PR, this paper proposes Graph Passage Retriever (GraphPR), a graph-based model inspired by the development of graph learning techniques. Different from existing works, GraphPR is end-to-end and integrates both term-matching information and semantics. GraphPR constructs a passage-level graph from BM25 retrieval results and trains a GCN-like model on the graph with graph-based objectives. Passages were regarded as nodes in the constructed graph and were embedded in dense vectors. PR can then be implemented using embeddings and a fast vector-similarity search. Experiments on a variety of real-world retrieval datasets show that the proposed model outperforms related models in several evaluation metrics (e.g., mean reciprocal rank, accuracy, F1-scores) while maintaining a relatively low query latency and memory usage.

Keywords: efficiency, effectiveness, graph learning, language model, passage retrieval, term-matching model

Procedia PDF Downloads 66
10085 Enhancing the Performance of Bug Reporting System by Handling Duplicate Reporting Reports: Artificial Intelligence Based Mantis

Authors: Afshan Saad, Muhammad Saad, Shah Muhammad Emaduddin

Abstract:

Bug reporting systems are most important tool that guides regarding different maintenance activities in software engineering. Duplicate bug reports which describe the bugs and issues in bug reporting system repository increases processing time of bug triage that monitors all such activities and software programmers who are working and spending time on reports which were assigned by triage. These reports can reveal imperfections and degrade software quality. As there is a number of the potential duplicate bug reports increases, the number of bug reports in bug repository increases. Identifying duplicate bug reports help in decreasing development work load in fixing defects. However, it is difficult to manually identify all possible duplicates because of the huge number of already reported bug reports. In this paper, an artificial intelligence based system using Mantis is proposed to automatically detect duplicate bug reports. When new bugs are submitted to repository triages will mark it with a tag. It will investigate that whether it is a duplicate of an existing bug report by matching or not. Reports with duplicate tags will be eliminated from the repository which not only will improve the performance of the system but can also save cost and effort waste on bug triage and finding the duplicate bug.

Keywords: bug tracking, triager, tool, quality assurance

Procedia PDF Downloads 152
10084 Video Stabilization Using Feature Point Matching

Authors: Shamsundar Kulkarni

Abstract:

Video capturing by non-professionals will lead to unanticipated effects. Such as image distortion, image blurring etc. Hence, many researchers study such drawbacks to enhance the quality of videos. In this paper, an algorithm is proposed to stabilize jittery videos .A stable output video will be attained without the effect of jitter which is caused due to shaking of handheld camera during video recording. Firstly, salient points from each frame from the input video are identified and processed followed by optimizing and stabilize the video. Optimization includes the quality of the video stabilization. This method has shown good result in terms of stabilization and it discarded distortion from the output videos recorded in different circumstances.

Keywords: video stabilization, point feature matching, salient points, image quality measurement

Procedia PDF Downloads 267
10083 Workforce Optimization: Fair Workload Balance and Near-Optimal Task Execution Order

Authors: Alvaro Javier Ortega

Abstract:

A large number of companies face the challenge of matching highly-skilled professionals to high-end positions by human resource deployment professionals. However, when the professional list and tasks to be matched are larger than a few dozens, this process result is far from optimal and takes a long time to be made. Therefore, an automated assignment algorithm for this workforce management problem is needed. The majority of companies are divided into several sectors or departments, where trained employees with different experience levels deal with a large number of tasks daily. Also, the execution order of all tasks is of mater consequence, due to some of these tasks just can be run it if the result of another task is provided. Thus, a wrong execution order leads to large waiting times between consecutive tasks. The desired goal is, therefore, creating accurate matches and a near-optimal execution order that maximizes the number of tasks performed and minimizes the idle time of the expensive skilled employees. The problem described before can be model as a mixed-integer non-linear programming (MINLP) as it will be shown in detail through this paper. A large number of MINLP algorithms have been proposed in the literature. Here, genetic algorithm solutions are considered and a comparison between two different mutation approaches is presented. The simulated results considering different complexity levels of assignment decisions show the appropriateness of the proposed model.

Keywords: employees, genetic algorithm, industry management, workforce

Procedia PDF Downloads 119
10082 Indoor Real-Time Positioning and Mapping Based on Manhattan Hypothesis Optimization

Authors: Linhang Zhu, Hongyu Zhu, Jiahe Liu

Abstract:

This paper investigated a method of indoor real-time positioning and mapping based on the Manhattan world assumption. In indoor environments, relying solely on feature matching techniques or other geometric algorithms for sensor pose estimation inevitably resulted in cumulative errors, posing a significant challenge to indoor positioning. To address this issue, we adopt the Manhattan world hypothesis to optimize the camera pose algorithm based on feature matching, which improves the accuracy of camera pose estimation. A special processing method was applied to image data frames that conformed to the Manhattan world assumption. When similar data frames appeared subsequently, this could be used to eliminate drift in sensor pose estimation, thereby reducing cumulative errors in estimation and optimizing mapping and positioning. Through experimental verification, it is found that our method achieves high-precision real-time positioning in indoor environments and successfully generates maps of indoor environments. This provides effective technical support for applications such as indoor navigation and robot control.

Keywords: Manhattan world hypothesis, real-time positioning and mapping, feature matching, loopback detection

Procedia PDF Downloads 22
10081 New-Born Children and Marriage Stability: An Evaluation of Divorce Risk Based on 2010-2018 China Family Panel Studies Data

Authors: Yuchao Yao

Abstract:

As two of the main characteristics of Chinese demographic trends, increasing divorce rates and decreasing fertility rates both shaped the population structure in the recent decade. Figuring out to what extent can be having a child make a difference in the divorce rate of a couple will not only draw a picture of Chinese families but also bring about a new perspective to evaluate the Chinese child-breeding policies. Based on China Family Panel Studies (CFPS) Data 2010-2018, this paper provides a systematic evaluation of how children influence a couple’s marital stability through a series of empirical models. Using survival analysis and propensity score matching (PSM) model, this paper finds that the number and age of children that a couple has mattered in consolidating marital relationship, and these effects vary little over time; during the last decade, newly having children can in fact decrease the possibility of divorce for Chinese couples; the such decreasing effect is largely due to the birth of a second child. As this is an inclusive attempt to study and compare not only the effects but also the causality of children on divorce risk in the last decade, the results of this research will do a good summary of the status quo of divorce in China. Furthermore, this paper provides implications for further reforming the current marriage and child-breeding policies.

Keywords: divorce risk, fertility, China, survival analysis, propensity score matching

Procedia PDF Downloads 43
10080 Effects of Reversible Watermarking on Iris Recognition Performance

Authors: Andrew Lock, Alastair Allen

Abstract:

Fragile watermarking has been proposed as a means of adding additional security or functionality to biometric systems, particularly for authentication and tamper detection. In this paper we describe an experimental study on the effect of watermarking iris images with a particular class of fragile algorithm, reversible algorithms, and the ability to correctly perform iris recognition. We investigate two scenarios, matching watermarked images to unmodified images, and matching watermarked images to watermarked images. We show that different watermarking schemes give very different results for a given capacity, highlighting the importance of investigation. At high embedding rates most algorithms cause significant reduction in recognition performance. However, in many cases, for low embedding rates, recognition accuracy is improved by the watermarking process.

Keywords: biometrics, iris recognition, reversible watermarking, vision engineering

Procedia PDF Downloads 410
10079 Regeneration of Geological Models Using Support Vector Machine Assisted by Principal Component Analysis

Authors: H. Jung, N. Kim, B. Kang, J. Choe

Abstract:

History matching is a crucial procedure for predicting reservoir performances and making future decisions. However, it is difficult due to uncertainties of initial reservoir models. Therefore, it is important to have reliable initial models for successful history matching of highly heterogeneous reservoirs such as channel reservoirs. In this paper, we proposed a novel scheme for regenerating geological models using support vector machine (SVM) and principal component analysis (PCA). First, we perform PCA for figuring out main geological characteristics of models. Through the procedure, permeability values of each model are transformed to new parameters by principal components, which have eigenvalues of large magnitude. Secondly, the parameters are projected into two-dimensional plane by multi-dimensional scaling (MDS) based on Euclidean distances. Finally, we train an SVM classifier using 20% models which show the most similar or dissimilar well oil production rates (WOPR) with the true values (10% for each). Then, the other 80% models are classified by trained SVM. We select models on side of low WOPR errors. One hundred channel reservoir models are initially generated by single normal equation simulation. By repeating the classification process, we can select models which have similar geological trend with the true reservoir model. The average field of the selected models is utilized as a probability map for regeneration. Newly generated models can preserve correct channel features and exclude wrong geological properties maintaining suitable uncertainty ranges. History matching with the initial models cannot provide trustworthy results. It fails to find out correct geological features of the true model. However, history matching with the regenerated ensemble offers reliable characterization results by figuring out proper channel trend. Furthermore, it gives dependable prediction of future performances with reduced uncertainties. We propose a novel classification scheme which integrates PCA, MDS, and SVM for regenerating reservoir models. The scheme can easily sort out reliable models which have similar channel trend with the reference in lowered dimension space.

Keywords: history matching, principal component analysis, reservoir modelling, support vector machine

Procedia PDF Downloads 126
10078 Size-Reduction Strategies for Iris Codes

Authors: Jutta Hämmerle-Uhl, Georg Penn, Gerhard Pötzelsberger, Andreas Uhl

Abstract:

Iris codes contain bits with different entropy. This work investigates different strategies to reduce the size of iris code templates with the aim of reducing storage requirements and computational demand in the matching process. Besides simple sub-sampling schemes, also a binary multi-resolution representation as used in the JBIG hierarchical coding mode is assessed. We find that iris code template size can be reduced significantly while maintaining recognition accuracy. Besides, we propose a two stage identification approach, using small-sized iris code templates in a pre-selection satge, and full resolution templates for final identification, which shows promising recognition behaviour.

Keywords: iris recognition, compact iris code, fast matching, best bits, pre-selection identification, two-stage identification

Procedia PDF Downloads 407
10077 Dimension Free Rigid Point Set Registration in Linear Time

Authors: Jianqin Qu

Abstract:

This paper proposes a rigid point set matching algorithm in arbitrary dimensions based on the idea of symmetric covariant function. A group of functions of the points in the set are formulated using rigid invariants. Each of these functions computes a pair of correspondence from the given point set. Then the computed correspondences are used to recover the unknown rigid transform parameters. Each computed point can be geometrically interpreted as the weighted mean center of the point set. The algorithm is compact, fast, and dimension free without any optimization process. It either computes the desired transform for noiseless data in linear time, or fails quickly in exceptional cases. Experimental results for synthetic data and 2D/3D real data are provided, which demonstrate potential applications of the algorithm to a wide range of problems.

Keywords: covariant point, point matching, dimension free, rigid registration

Procedia PDF Downloads 135
10076 A Computer-Aided System for Tooth Shade Matching

Authors: Zuhal Kurt, Meral Kurt, Bilge T. Bal, Kemal Ozkan

Abstract:

Shade matching and reproduction is the most important element of success in prosthetic dentistry. Until recently, shade matching procedure was implemented by dentists visual perception with the help of shade guides. Since many factors influence visual perception; tooth shade matching using visual devices (shade guides) is highly subjective and inconsistent. Subjective nature of this process has lead to the development of instrumental devices. Nowadays, colorimeters, spectrophotometers, spectroradiometers and digital image analysing systems are used for instrumental shade selection. Instrumental devices have advantages that readings are quantifiable, can obtain more rapidly and simply, objectively and precisely. However, these devices have noticeable drawbacks. For example, translucent structure and irregular surfaces of teeth lead to defects on measurement with these devices. Also between the results acquired by devices with different measurement principles may make inconsistencies. So, its obligatory to search for new methods for dental shade matching process. A computer-aided system device; digital camera has developed rapidly upon today. Currently, advances in image processing and computing have resulted in the extensive use of digital cameras for color imaging. This procedure has a much cheaper process than the use of traditional contact-type color measurement devices. Digital cameras can be taken by the place of contact-type instruments for shade selection and overcome their disadvantages. Images taken from teeth show morphology and color texture of teeth. In last decades, a new method was recommended to compare the color of shade tabs taken by a digital camera using color features. This method showed that visual and computer-aided shade matching systems should be used as concatenated. Recently using methods of feature extraction techniques are based on shape description and not used color information. However, color is mostly experienced as an essential property in depicting and extracting features from objects in the world around us. When local feature descriptors with color information are extended by concatenating color descriptor with the shape descriptor, that descriptor will be effective on visual object recognition and classification task. Therefore, the color descriptor is to be used in combination with a shape descriptor it does not need to contain any spatial information, which leads us to use local histograms. This local color histogram method is remain reliable under variation of photometric changes, geometrical changes and variation of image quality. So, coloring local feature extraction methods are used to extract features, and also the Scale Invariant Feature Transform (SIFT) descriptor used to for shape description in the proposed method. After the combination of these descriptors, the state-of-art descriptor named by Color-SIFT will be used in this study. Finally, the image feature vectors obtained from quantization algorithm are fed to classifiers such as Nearest Neighbor (KNN), Naive Bayes or Support Vector Machines (SVM) to determine label(s) of the visual object category or matching. In this study, SVM are used as classifiers for color determination and shade matching. Finally, experimental results of this method will be compared with other recent studies. It is concluded from the study that the proposed method is remarkable development on computer aided tooth shade determination system.

Keywords: classifiers, color determination, computer-aided system, tooth shade matching, feature extraction

Procedia PDF Downloads 392
10075 Interaction between Trapezoidal Hill and Subsurface Cavity under SH Wave Incidence

Authors: Yuanrui Xu, Zailin Yang, Yunqiu Song, Guanxixi Jiang

Abstract:

It is an important subject of seismology on the influence of local topography on ground motion during earthquake. In mountainous areas with complex terrain, the construction of the tunnel is often the most effective transportation scheme. In these projects, the local terrain can be simplified into hills with different shapes, and the underground tunnel structure can be regarded as a subsurface cavity. The presence of the subsurface cavity affects the strength of the rock mass and changes the deformation and failure characteristics. Moreover, the scattering of the elastic waves by underground structures usually interacts with local terrains, which leads to a significant influence on the surface displacement of the terrains. Therefore, it is of great practical significance to study the surface displacement of local terrains with underground tunnels in earthquake engineering and seismology. In this work, the region is divided into three regions by the method of region matching. By using the fractional Bessel function and Hankel function, the complex function method, and the wave function expansion method, the wavefield expression of SH waves is introduced. With the help of a constitutive relation between the displacement and the stress components, the hoop stress and radial stress is obtained subsequently. Then, utilizing the continuous condition at different region boundaries, the undetermined coefficients in wave fields are solved by the Fourier series expansion and truncation of the finite term. Finally, the validity of the method is verified, and the surface displacement amplitude is calculated. The surface displacement amplitude curve is discussed in the numerical results. The results show that different parameters, such as radius and buried depth of the tunnel, wave number, and incident angle of the SH wave, have a significant influence on the amplitude of surface displacement. For the underground tunnel, the increase of buried depth will make the response of surface displacement amplitude increases at first and then decreases. However, the increase of radius leads the response of surface displacement amplitude to appear an opposite phenomenon. The increase of SH wave number can enlarge the amplitude of surface displacement, and the change of incident angle can obviously affect the amplitude fluctuation.

Keywords: method of region matching, scattering of SH wave, subsurface cavity, trapezoidal hill

Procedia PDF Downloads 95
10074 Pathological Gambling and Impulsivity: Comparison of the Eight Laboratory Measures of Inhibition Capacities

Authors: Semion Kertzman, Pinhas Dannon

Abstract:

Impulsive behaviour and the underlying brain processes are hypothesized to be central in the development and maintenance of pathological gambling. Inhibition ability can be differentially impaired in pathological gamblers (PGs). Aims: This study aimed to compare the ability of eight widely used inhibition measures to discriminate between PGs and healthy controls (HCs). Methods: PGs (N=51) and demographically matched HCs (N=51) performed cognitive inhibition (the Stroop), motor inhibition (the Go/NoGo) and reflective inhibition (the Matching Familiar Figures (MFFT)) tasks. Results: An augmented total interference response time in the Stroop task (η² =0.054), a large number of commission errors (η² =0.053) in the Go/NoGo task, and the total number of errors in the MFFT (η² =0.05) can discriminate PGs from HCs. Other measures are unable to differentiate between PGs and HCs. No significant correlations were observed between inhibition measures. Conclusion: Inhibition measures varied in the ability to discriminate PGs from HCs. Most inhibition measures were not relevant to gambling behaviour. PGs do not express rash, impulsive behaviour, such as quickly choosing an answer without thinking. In contrast, in PGs, inhibition impairment was related to slow-inaccurate performance.

Keywords: pathological gambling, impulsivity, neurocognition, addiction

Procedia PDF Downloads 265
10073 Matching on Bipartite Graphs with Applications to School Course Registration Systems

Authors: Zhihan Li

Abstract:

Nowadays, most universities use the course enrollment system considering students’ registration orders. However, the students’ preference level to certain courses is also one important factor to consider. In this research, the possibility of applying a preference-first system has been discussed and analyzed compared to the order-first system. A bipartite graph is applied to resemble the relationship between students and courses they tend to register. With the graph set up, we apply Ford-Fulkerson (F.F.) Algorithm to maximize parings between two sets of nodes, in our case, students and courses. Two models are proposed in this paper: the one considered students’ order first, and the one considered students’ preference first. By comparing and contrasting the two models, we highlight the usability of models which potentially leads to better designs for school course registration systems.

Keywords: bipartite graph, Ford-Fulkerson (F.F.) algorithm, graph theory, maximum matching

Procedia PDF Downloads 73
10072 Discovering Word-Class Deficits in Persons with Aphasia

Authors: Yashaswini Channabasavegowda, Hema Nagaraj

Abstract:

Aim: The current study aims at discovering word-class deficits concerning the noun-verb ratio in confrontation naming, picture description, and picture-word matching tasks. A total of ten persons with aphasia (PWA) and ten age-matched neurotypical individuals (NTI) were recruited for the study. The research includes both behavioural and objective measures to assess the word class deficits in PWA. Objective: The main objective of the research is to identify word class deficits seen in persons with aphasia, using various speech eliciting tasks. Method: The study was conducted in the L1 of the participants, considered to be Kannada. Action naming test and Boston naming test adapted to the Kannada version are administered to the participants; also, a picture description task is carried out. Picture-word matching task was carried out using e-prime software (version 2) to measure the accuracy and reaction time with respect to identification verbs and nouns. The stimulus was presented through auditory and visual modes. Data were analysed to identify errors noticed in the naming of nouns versus verbs, with respect to the Boston naming test and action naming test and also usage of nouns and verbs in the picture description task. Reaction time and accuracy for picture-word matching were extracted from the software. Results: PWA showed a significant difference in sentence structure compared to age-matched NTI. Also, PWA showed impairment in syntactic measures in the picture description task, with fewer correct grammatical sentences and fewer correct usage of verbs and nouns, and they produced a greater proportion of nouns compared to verbs. PWA had poorer accuracy and lesser reaction time in the picture-word matching task compared to NTI, and accuracy was higher for nouns compared to verbs in PWA. The deficits were noticed irrespective of the cause leading to aphasia.

Keywords: nouns, verbs, aphasia, naming, description

Procedia PDF Downloads 67
10071 Spatial Object-Oriented Template Matching Algorithm Using Normalized Cross-Correlation Criterion for Tracking Aerial Image Scene

Authors: Jigg Pelayo, Ricardo Villar

Abstract:

Leaning on the development of aerial laser scanning in the Philippine geospatial industry, researches about remote sensing and machine vision technology became a trend. Object detection via template matching is one of its application which characterized to be fast and in real time. The paper purposely attempts to provide application for robust pattern matching algorithm based on the normalized cross correlation (NCC) criterion function subjected in Object-based image analysis (OBIA) utilizing high-resolution aerial imagery and low density LiDAR data. The height information from laser scanning provides effective partitioning order, thus improving the hierarchal class feature pattern which allows to skip unnecessary calculation. Since detection is executed in the object-oriented platform, mathematical morphology and multi-level filter algorithms were established to effectively avoid the influence of noise, small distortion and fluctuating image saturation that affect the rate of recognition of features. Furthermore, the scheme is evaluated to recognized the performance in different situations and inspect the computational complexities of the algorithms. Its effectiveness is demonstrated in areas of Misamis Oriental province, achieving an overall accuracy of 91% above. Also, the garnered results portray the potential and efficiency of the implemented algorithm under different lighting conditions.

Keywords: algorithm, LiDAR, object recognition, OBIA

Procedia PDF Downloads 211
10070 Investigating Malaysian Prereader’s Cognitive Processes when Reading English Picture Storybooks: A Comparative Eye-Tracking Experiment

Authors: Siew Ming Thang, Wong Hoo Keat, Chee Hao Sue, Fung Lan Loo, Ahju Rosalind

Abstract:

There are numerous studies that explored young learners’ literacy skills in Malaysia but none that uses the eye-tracking device to track their cognitive processes when reading picture storybooks. This study used this method to investigate two groups of prereaders’ cognitive processes in four conditions. (1) A congruent picture was presented, and a matching narration was read aloud by a recorder; (2) Children heard a narration telling about the same characters in the picture but involves a different scene; (3) Only a picture with matching text was present; (4) Students only heard the reading aloud of the text on the screen. The two main objectives of this project are to test which content of pictures helps the prereaders (i.e., young children who have not received any formal reading instruction) understand the narration and whether children try to create a coherent mental representation from the oral narration and the pictures. The study compares two groups of children from two different kindergartens. Group1: 15 Chinese children; Group2: 17 Malay children. The medium of instruction was English. An eye-tracker were used to identify Areas of Interest (AOI) of each picture and the five target elements and calculate number of fixations and total time spent on fixation of pictures and written texts. Two mixed factorial ANOVAs with the storytelling performance (good, average, or weak) and vocabulary level (low, medium, high) as between-subject variables, and the Areas of Interests (AOIs) and display conditions as the within-subject variables were performedon the variables.

Keywords: eye-tracking, cognitive processes, literacy skills, prereaders, visual attention

Procedia PDF Downloads 55
10069 Parameters of Minimalistic Mosque in India within Minimalism

Authors: Hafila Banu

Abstract:

Minimalism is a postmodern style movement which emerged in the 50s of the twentieth century, but it was rapidly growing in the years of 60s and 70s. Minimalism is defined as the concept of minimizing distractions from what is truly valuable or essential. On the same grounds, works of minimalism offer a direct view at and raises questions about the true nature of the subject or object inviting the viewer to consider it for it for the real shape, a thought, a movement reminding us to focus on what is really important. The Architecture of Minimalism is characterized by an economy with materials , focusing on building quality with considerations for ‘essences’ as light, form, detail of material, texture, space and scale, place and human conditions . The research of this paper is mainly into the basis of designing a minimalistic mosque in India while analysing the parameters for the design from the matching characteristics of Islamic architecture in specific to a mosque and the minimalism. Therefore, the paper is about the mosque architecture and minimalism and of their underlying principles, matching characteristics and design goals.

Keywords: Islamic architecture, minimalism, minimalistic mosque, mosque in India

Procedia PDF Downloads 162
10068 Analysis of Matching Pursuit Features of EEG Signal for Mental Tasks Classification

Authors: Zin Mar Lwin

Abstract:

Brain Computer Interface (BCI) Systems have developed for people who suffer from severe motor disabilities and challenging to communicate with their environment. BCI allows them for communication by a non-muscular way. For communication between human and computer, BCI uses a type of signal called Electroencephalogram (EEG) signal which is recorded from the human„s brain by means of an electrode. The electroencephalogram (EEG) signal is an important information source for knowing brain processes for the non-invasive BCI. Translating human‟s thought, it needs to classify acquired EEG signal accurately. This paper proposed a typical EEG signal classification system which experiments the Dataset from “Purdue University.” Independent Component Analysis (ICA) method via EEGLab Tools for removing artifacts which are caused by eye blinks. For features extraction, the Time and Frequency features of non-stationary EEG signals are extracted by Matching Pursuit (MP) algorithm. The classification of one of five mental tasks is performed by Multi_Class Support Vector Machine (SVM). For SVMs, the comparisons have been carried out for both 1-against-1 and 1-against-all methods.

Keywords: BCI, EEG, ICA, SVM

Procedia PDF Downloads 243
10067 Hash Based Block Matching for Digital Evidence Image Files from Forensic Software Tools

Authors: M. Kaya, M. Eris

Abstract:

Internet use, intelligent communication tools, and social media have all become an integral part of our daily life as a result of rapid developments in information technology. However, this widespread use increases crimes committed in the digital environment. Therefore, digital forensics, dealing with various crimes committed in digital environment, has become an important research topic. It is in the research scope of digital forensics to investigate digital evidences such as computer, cell phone, hard disk, DVD, etc. and to report whether it contains any crime related elements. There are many software and hardware tools developed for use in the digital evidence acquisition process. Today, the most widely used digital evidence investigation tools are based on the principle of finding all the data taken place in digital evidence that is matched with specified criteria and presenting it to the investigator (e.g. text files, files starting with letter A, etc.). Then, digital forensics experts carry out data analysis to figure out whether these data are related to a potential crime. Examination of a 1 TB hard disk may take hours or even days, depending on the expertise and experience of the examiner. In addition, it depends on examiner’s experience, and may change overall result involving in different cases overlooked. In this study, a hash-based matching and digital evidence evaluation method is proposed, and it is aimed to automatically classify the evidence containing criminal elements, thereby shortening the time of the digital evidence examination process and preventing human errors.

Keywords: block matching, digital evidence, hash list, evaluation of digital evidence

Procedia PDF Downloads 220
10066 An Electrically Small Silver Ink Printed FR4 Antenna for RF Transceiver Chip CC1101

Authors: F. Majeed, D. V. Thiel, M. Shahpari

Abstract:

An electrically small meander line antenna is designed for impedance matching with RF transceiver chip CC1101. The design provides the flexibility of tuning the reactance of the antenna over a wide range of values: highly capacitive to highly inductive. The antenna was printed with silver ink on FR4 substrate using the screen printing design process. The antenna impedance was perfectly matched to CC1101 at 433 MHz. The measured radiation efficiency of the antenna was 81.3% at resonance. The 3 dB and 10 dB fractional bandwidth of the antenna was 14.5% and 4.78%, respectively. The read range of the antenna was compared with a copper wire monopole antenna over a distance of five meters. The antenna, with a perfect impedance match with RF transceiver chip CC1101, shows improvement in the read range compared to a monopole antenna over the specified distance.

Keywords: meander line antenna, RFID, silver ink printing, impedance matching

Procedia PDF Downloads 227
10065 The Theory of Number "0"

Authors: Iryna Shevchenko

Abstract:

The science of mathematics was originated at the order of count of objects and subsequently for the measurement of size and quality of objects using the logical or abstract means. The laws of mathematics are based on the study of absolute values. The number 0 or "nothing" is the purely logical (as the opposite to absolute) value as the "nothing" should always assume the space for the something that had existed there; otherwise the "something" would never come to existence. In this work we are going to prove that the number "0" is the abstract (logical) and not an absolute number and it has the absolute value of “∞” (infinity). Therefore, the number "0" might not stand in the row of numbers that symbolically represents the absolute values, as it would be the mathematically incorrect. The symbolical value of number "0" in the row of numbers could be represented with symbol "∞" (infinity). As a result, we have the mathematical row of numbers: epsilon, ...4, 3, 2, 1, ∞. As the conclusions of the theory of number “0” we presented the statements: multiplication and division by fractions of numbers is illegal operation and the mathematical division by number “0” is allowed.

Keywords: illegal operation of division and multiplication by fractions of number, infinity, mathematical row of numbers, theory of number “0”

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10064 Organisationmatcher: An Organisation Ranking System for Student Placement Using Preference Weights

Authors: Nor Sahida Ibrahim, Ruhaila Maskat, Aishah Ahmad

Abstract:

Almost all tertiary-level students will undergo some form of training in organisations prior to their graduation. This practice provides the necessary exposure and experience to allow students to cope with actual working environment and culture in the future. Nevertheless, a particular degree of “matching” between what is expected and what can be offered between students and organisations underpins how effective and enriching the experience is. This matching of students and organisations is challenging when preferences from both parties must be satisfied. This work developed a web-based system, namely the OrganisationMatcher, which leverage on the use of preference weights to score each organisation and rank them based on “suitability”. OrganisationMatcher has been implemented on a relational database, designed using object-oriented methods and developed using PHP programming language for browser front-end access. We outline the challenges and limitations of our system and discuss future improvements to the system, specifically in the utilisation of intelligent methods.

Keywords: student industrial placement, information system, web-based, ranking

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10063 Definition of Quality Indicators for Damascus Rose Oil (Rosa damascena) Flora of Morocco

Authors: Serebryanaya Fatima, Essaih Hind

Abstract:

The Rosa damascena (Rosa damascena Mill.) is an interesting medicinal plant; it is famous in different countries and has medicinal use in many cultures. The main groups of pharmacological actions of rose oil are connected with anti-inflammatory, antifungal activity, also antioxidant and antibacterial, and antiparasitic properties. We have prepared the quality indicators analysis of the Damascus rose oil. An iodine number, acid number, and oil peroxide number were determined. The following indicators of the quality of rose oil have been studied. The determination was carried out according to the pharmacopoeic methods of analysis of essential oils, the definition of peroxide number (1,971%), iodine number (3,365%), and acid number (0,0526%).

Keywords: Rosa damascene, Rosa damascena Mill., iodine number, acid number, oil peroxide number

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10062 Generalized Additive Model for Estimating Propensity Score

Authors: Tahmidul Islam

Abstract:

Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

Procedia PDF Downloads 323