Search results for: similarity based retrieval

Authors: Chao Wang

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Under rapid innovation of information technology, the media plays a very important role in the dissemination of information, and it has a totally different analogy generations face. However, the involvement of narrative images provides more possibilities of narrative text. "Images" through the process of aperture, a camera shutter and developable photosensitive processes are manufactured, recorded and stamped on paper, displayed on a computer screen-concretely saved. They exist in different forms of files, data, or evidence as the ultimate looks of events. By the interface of media and network platforms and special visual field of the viewer, class body space exists and extends out as thin as sebum layer, extremely soft and delicate with real full tension. The physical space of sebum layer of confuses the fact that physical objects exist, needs to be established under a perceived consensus. As at the scene, the existing concepts and boundaries of physical perceptions are blurred. Sebum layer physical simulation shapes the “Topical-Similarity" immersing, leading the contemporary social practice communities, groups, network users with a kind of illusion without the presence, i.e. a non-real illusion. From the investigation and discussion of literatures, digital movies editing manufacture and produce the variability characteristics of time (for example, slices, rupture, set, and reset) are analyzed. Interactive eBook has an unique interaction in "Waiting-Greeting" and "Expectation-Response" that makes the operation of image narrative structure more interpretations functionally. The works of digital editing and interactive technology are combined and further analyze concept and results. After digitization of Interventional Imaging and interactive technology, real events exist linked and the media handing cannot be cut relationship through movies, interactive art, practical case discussion and analysis. Audience needs more rational thinking about images carried by the authenticity of the text.

Keywords: sebum layer, topical and similarity, interactive technology, image narrative

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Authors: P. Srinivasa Rao, K. Venkatesh Sharma, G. Sadhya Devi, V. Nagesh

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Privacy Preserving Data Publication is the main concern in present days because the data being published through the internet has been increasing day by day. This huge amount of data was named as Big Data by its size. This project deals the privacy preservation in the context of Big Data using a data warehousing solution called hive. We implemented Nearest Similarity Based Clustering (NSB) with Bottom-up generalization to achieve (v,l)-anonymity. (v,l)-Anonymity deals with the sensitivity vulnerabilities and ensures the individual privacy. We also calculate the sensitivity levels by simple comparison method using the index values, by classifying the different levels of sensitivity. The experiments were carried out on the hive environment to verify the efficiency of algorithms with Big Data. This framework also supports the execution of existing algorithms without any changes. The model in the paper outperforms than existing models.

Keywords: sensitivity, sensitive level, clustering, Privacy Preserving Data Publication (PPDP), bottom-up generalization, Big Data

Procedia PDF Downloads 289

Authors: Prabhakar Venugopal G.

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Complex environments triggered by globalization have necessitated new paradigms of leadership – complexity leadership that encompasses multiple roles that leaders need to take upon. The success of higher education institutions depends on how well leaders can provide adaptive, administrative and enabling leadership. Complexity leadership seems all the more relevant for institutions that are knowledge-driven and thrive on knowledge creation, knowledge storage and retrieval, knowledge sharing and knowledge applications. In this paper are the elements of globalization, the opportunities and challenges that are brought forth by globalization are discussed. The complexity leadership paradigm in a knowledge-based economy and the need for such a paradigm shift for higher education institutions is presented. Further, the paper also discusses the support the leader requires in a knowledge-driven economy through knowledge management initiatives.

Keywords: globalization, complexity leadership, knowledge management

Procedia PDF Downloads 486

Authors: Mounia El Jaouhari, Mira Goral, Samir Diouny

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Introduction: Previous research has indicated that language impairments are recognized as a feature of many neurodegenerative disorders, including non-language-led dementia subtypes such as Alzheimer´s disease (AD). In this preliminary study, the focal aim is to quantify the semantic content of naming and connected speech samples of Moroccan patients diagnosed with AD using two tasks taken from the culturally adapted and validated Moroccan version of the Boston Diagnostic Aphasia Examination. Methods: Five individuals with AD and five neurologically healthy individuals matched for age, gender, and education will participate in the study. Participants with AD will be diagnosed on the basis of the Moroccan version of the Diagnostic and Statistial Manual of Mental Disorders (DSM-4) screening test, the Moroccan version of the Mini Mental State Examination (MMSE) test scores, and neuroimaging analyses. The participants will engage in two tasks taken from the MDAE-SF: 1) Picture description and 2) Naming. Expected findings: Consistent with previous studies conducted on English speaking AD patients, we expect to find significant word production and retrieval impairments in AD patients in all measures. Moreover, we expect to find category fluency impairments that further endorse semantic breakdown accounts. In sum, not only will the findings of the current study shed more light on the locus of word retrieval impairments noted in AD, but also reflect the nature of Arabic morphology. In addition, the error patterns are expected to be similar to those found in previous AD studies in other languages.

Keywords: alzheimer's disease, anomia, connected speech, semantic impairments, moroccan arabic

Procedia PDF Downloads 138

Authors: Dheyaa Hussein, Peter Armstrong

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The phenomenon of visual disorder is prominent in contemporary townscapes. This paper provides a theoretical framework for the assessment of visual consistency in townscape in order to achieve more favourable outcomes for users. In this paper, visual consistency refers to the amount of similarity between adjacent components of townscape. The paper investigates parameters which relate to visual consistency in townscape, explores the relationships between them and highlights their significance. The paper uses arithmetic methods from outside the domain of urban design to enable the establishment of an objective approach of assessment which considers subjective indicators including users’ preferences. These methods involve the standard of deviation, colour distance and the distance between points. The paper identifies urban space as a key representative of the visual parameters of townscape. It focuses on its two components, geometry and colour in the evaluation of the visual consistency of townscape. Accordingly, this article proposes four measurements. The first quantifies the number of vertices, which are points in the three-dimensional space that are connected, by lines, to represent the appearance of elements. The second evaluates the visual surroundings of urban space through assessing the location of their vertices. The last two measurements calculate the visual similarity in both vertices and colour in townscape by the calculation of their variation using methods including standard of deviation and colour difference. The proposed quantitative assessment is based on users’ preferences towards these measurements. The paper offers a theoretical basis for a practical tool which can alter the current understanding of architectural form and its application in urban space. This tool is currently under development. The proposed method underpins expert subjective assessment and permits the establishment of a unified framework which adds to creativity by the achievement of a higher level of consistency and satisfaction among the citizens of evolving townscapes.

Keywords: townscape, urban design, visual assessment, visual consistency

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Authors: Alev Atak

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In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

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Authors: Nilesh Pancholi, Mangal Bhatt

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This paper highlights comparative results of traditional FMECA and multi-factor decision-making approach based on “Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)” for aluminum wire rolling mill plant. The suggested study is carried out to overcome the limitations of FMECA by assigning the scores against each failure modes in crisp values to evaluate the criticalities of the failure modes without uncertainty. The primary findings of the paper are that sudden impact on the rolls seems to be most critical failure cause and high contact stresses due to rolling & sliding action of mesh to be least critical failure cause. It is suggested to modify the current control practices with proper maintenance strategy based on achieved maintainability criticality index (MCI). The outcome of the study will be helpful in deriving optimized maintenance plan to maximize the performance of continuous process industry.

Keywords: reliability, maintenance, FMECA, TOPSIS, process industry

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Authors: S. Saju, G. Thirugnanam

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In this paper, a medical image watermarking algorithm based on contourlet is proposed. Medical image watermarking is a special subcategory of image watermarking in the sense that images have special requirements. Watermarked medical images should not differ perceptually from their original counterparts because clinical reading of images must not be affected. Watermarking techniques based on wavelet transform are reported in many literatures but robustness and security using contourlet are better when compared to wavelet transform. The main challenge in exploring geometry in images comes from the discrete nature of the data. In this paper, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image. To extract the watermark, Kernel ICA is used and it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that proposed scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with Discrete Wavelet Transform (DWT) to prove the robustness of the scheme. Simulations are carried out using Matlab Software.

Keywords: digital watermarking, independent component analysis, wavelet transform, contourlet

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Authors: Sarabjeet Singh Sidhu, Ajay Batish, Sanjeev Kumar

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This paper reports the optimal process conditions for machining of three different types of metal matrix composites (MMCs): 65vol%SiC/A356.2; 10vol%SiC-5vol%quartz/Al and 30vol%SiC/A359 using PMEDM process. Metal removal rate (MRR), tool wear rate (TWR), surface roughness (SR) and surface integrity (SI) were evaluated after each trial and contributing process parameters were identified. The four responses were then collectively optimized using the technique for order preference by similarity to ideal solution (TOPSIS) and optimal process conditions were identified for each type of MMCS. The density of reinforced particles shields the matrix material from spark energy hence the high MRR and SR was observed with lowest reinforced particle. TWR was highest with Cu-Gr electrode due to disintegration of the weakly bonded particles in the composite electrode. Each workpiece was examined for surface integrity and ranked as per severity of surface defects observed and their rankings were used for arriving at the most optimal process settings for each workpiece.

Keywords: metal matrix composites (MMCS), metal removal rate (MRR), surface roughness (SR), surface integrity (SI), tool wear rate (TWR), technique for order preference by similarity to ideal solution (TOPSIS)

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Authors: Feras Hanandeh, Izzat Alsmadi, Muhammad M. Kwafha

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Prefix trees or tries are data structures that are used to store data or index of data. The goal is to be able to store and retrieve data by executing queries in quick and reliable manners. In principle, the structure of the trie depends on having letters in nodes at the different levels to point to the actual words in the leafs. However, the exact structure of the trie may vary based on several aspects. In this paper, we evaluated different structures for building tries. Using datasets of words of different sizes, we evaluated the different forms of trie structures. Results showed that some characteristics may impact significantly, positively or negatively, the size and the performance of the trie. We investigated different forms and structures for the trie. Results showed that using an array of pointers in each level to represent the different alphabet letters is the best choice.

Keywords: data structures, indexing, tree structure, trie, information retrieval

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Authors: Alexander Machikhin, Olga Polschikova, Vitold Pozhar, Alina Ramazanova

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White-light quantitative phase imaging is an effective technique for achieving sub-nanometer phase sensitivity. Highly stable interferometers based on common-path geometry have been developed in recent years to solve this task. Some of these methods also apply multispectral approach. The purpose of this research is to suggest a simple and effective interferometer for such systems. We developed a three-lens common-path interferometer, which can be used for quantitative phase imaging with or without multispectral modality. The lens system consists of two components, the first one of which is a compound lens, consisting of two lenses. A pinhole is placed between the components. The lens-in-lens approach enables effective light transmission and high stability of the interferometer. The multispectrality is easily implemented by placing a tunable filter in front of the interferometer. In our work, we used an acousto-optical tunable filter. Some design considerations are discussed and multispectral quantitative phase retrieval is demonstrated.

Keywords: acousto-optical tunable filter, common-path interferometry, digital holography, multispectral quantitative phase imaging

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Authors: Helene Martin, Solmaz Boroomandi Barati, Jean-Charles Pinoli, Stephane Valette, Yann Gavet

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In the present work we developed an image processing algorithm to measure water droplets characteristics during dropwise condensation on pillared surfaces. The main problem in this process is the similarity between shape and size of water droplets and the pillars. The developed method divides droplets into four main groups based on their size and applies the corresponding algorithm to segment each group. These algorithms generate binary images of droplets based on both their geometrical and intensity properties. The information related to droplets evolution during time including mean radius and drops number per unit area are then extracted from the binary images. The developed image processing algorithm is verified using manual detection and applied to two different sets of images corresponding to two kinds of pillared surfaces.

Keywords: dropwise condensation, textured surface, image processing, watershed

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Authors: Rana Gill, Chandandeep Kaur

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Segmentation of images can be implemented using different fundamental algorithms like edge detection (discontinuity based segmentation), region growing (similarity based segmentation), iterative thresholding method. A comprehensive literature review relevant to the study gives description of different techniques for vehicle number plate detection and edge detection techniques widely used on different types of images. This research work is based on edge detection techniques and calculating threshold on the basis of five edge operators. Five operators used are Prewitt, Roberts, Sobel, LoG and Canny. Segmentation of characters present in different type of images like vehicle number plate, name plate of house and characters on different sign boards are selected as a case study in this work. The proposed methodology has seven stages. The proposed system has been implemented using MATLAB R2010a. Comparison of all the five operators has been done on the basis of their performance. From the results it is found that Canny operators produce best results among the used operators and performance of different edge operators in decreasing order is: Canny>Log>Sobel>Prewitt>Roberts.

Keywords: segmentation, edge detection, text, extracting characters

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Authors: Debit Datta, Jeffrey J. Coleman, Scott A. Enebak, Lori G. Eckhardt

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Loblolly pine (Pinus taeda) is a leading productive timber species in the southeastern USA. Over the past three years, an emerging threat is expressed by successive needle defoliation followed by stunted growth and tree mortality in loblolly pine plantations. Considering economic significance, it has now become a rising concern among landowners, forest managers, and forest health state cooperators. However, the symptoms of the disease were perplexed somewhat with root disease(s) and recurrently attributed to invasive Phytophthora species due to the similarity of disease nature and devastation. Therefore, the study investigated the potential causal agent of this disease and characterized the fungi associated with loblolly pine needle defoliation in the southeastern USA. Besides, 70 trees were selected at seven long-term monitoring plots at Chatom, Alabama, to monitor and record the annual disease incidence and severity. Based on colony morphology and ITS-rDNA sequence data, a total of 28 species of fungi representing 17 families have been recovered from diseased loblolly pine needles. The native brown-spot pathogen, Lecanosticta acicola, was the species most frequently recovered from unhealthy loblolly pine needles in combination with some other common needle cast and rust pathogen(s). Identification was confirmed using morphological similarity and amplification of translation elongation factor 1-alpha gene region of interest. Tagged trees were consistently found chlorotic and defoliated from 2019 to 2020. The current emergence of the brown-spot pathogen causing loblolly pine mortality necessitates the investigation of the role of changing climatic conditions, which might be associated with increased pathogen pressure to loblolly pines in the southeastern USA.

Keywords: brown-spot needle blight, loblolly pine, needle defoliation, plantation forestry

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Authors: Fengmei Li, Li Xu, Guoliang Xia

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Lysozyme is a catalytic enzyme that performs bacterial cell lysis by cleaving the β-1,4-glycosidic bond between N-acetylmuramic acid and N-acetylglucosamine of peptidoglycan in cell walls. In the present study, an invertebrate-type (i-type) lysozyme gene was cloned from Chinese mitten crab Eriocheir sinensis (designated as EsLysozyme) based on PCR-based rapid amplification of cDNA ends (RACE) technology. The full-length cDNA of EsLysozyme was of 831 bp. SMART and SIGNALP 3.0 program analysis revealed that EsLysozyme contained a signal peptide and a destabilase domain. The five amino acid residues (Tyr63, Trp64, Tyr91, His110, Pro114) and the conserved motif GSLSCG(P/Y)FQI and CL(E/L/R/H)C(I/M)C in i-type lysozymes were also found in EsLysozyme. The high similarity of EsLysozyme with L. vannamei lysozymes and phylogenetic analysis suggested that EsLysozyme should be a new member of i-type lysozyme family.

Keywords: i-type lysozyme, Eriocheir sinensis, cloning, characterization

Procedia PDF Downloads 285

Authors: Guoliang Lu, Changhou Lu, Xueyong Li

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In action recognition, previous studies have demonstrated the effectiveness of using multiple features to improve the recognition performance. We focus on two practical issues: i) most studies use a direct way of concatenating/accumulating multi features to evaluate the similarity between two actions. This way could be too strong since each kind of feature can include different dimensions, quantities, etc; ii) in many studies, the employed classification methods lack of a flexible and effective mechanism to add new feature(s) into classification. In this paper, we explore an unified scheme based on recently-proposed multi-dimensional dynamic time warping (MD-DTW). Experiments demonstrated the scheme's effectiveness of combining multi-feature and the flexibility of adding new feature(s) to increase the recognition performance. In addition, the explored scheme also provides us an open architecture for using new advanced classification methods in the future to enhance action recognition.

Keywords: action recognition, multi features, dynamic time warping, feature combination

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Authors: Juan Torralba

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Student digital artifacts were investigated, utilizing a qualitative exploratory research design to understand the ways in which students represented their knowledge of seventh-grade proportionality concepts as they participated in maker-based activities that culminated in the creation of digital 3-dimensional models of their dream homes. Representations of the geometric and numeric dimensions of proportionality were analyzed in the written, verbal, and visual data collected from the students. A directed content analysis approach was utilized in the data analysis, as this work aimed to build upon existing research in the field of maker-based STEAM Education. The results from this work show that students can represent their understanding of proportional reasoning through open-ended written responses more accurately than through verbal descriptions or digital artifacts. The geometric and numeric dimensions of proportionality and their respective components of attributes of similarity representation and percents, rates, and ratios representations were the most represented by the students than any other across the data, suggesting a maker-based instructional approach to teaching proportionality in the middle grades may be promising in helping students gain a solid foundation in those components. Recommendations for practice and research are discussed.

Keywords: learning through making, maker-based education, maker education in the middle grades, making in mathematics, the maker movement

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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

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Authors: Jonah Kenei, Elisha Opiyo

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Electronic health records, as a repository of patient information, is nowadays the most commonly used technology to record, store and review patient clinical records and perform other clinical tasks. However, the accurate identification and retrieval of relevant information from clinical records is a difficult task due to the unstructured nature of clinical documents, characterized in particular by a lack of clear structure. Therefore, medical practice is facing a challenge thanks to the rapid growth of health information in electronic health records (EHRs), mostly in narrative text form. As a result, it's becoming important to effectively manage the growing amount of data for a single patient. As a result, there is currently a requirement to visualize electronic health records (EHRs) in a way that aids physicians in clinical tasks and medical decision-making. Leveraging text visualization techniques to unstructured clinical narrative texts is a new area of research that aims to provide better information extraction and retrieval to support clinical decision support in scenarios where data generated continues to grow. Clinical datasets in electronic health records (EHR) offer a lot of potential for training accurate statistical models to classify facets of information which can then be used to improve patient care and outcomes. However, in many clinical note datasets, the unstructured nature of clinical texts is a common problem. This paper examines the very issue of getting raw clinical texts and mapping them into meaningful structures that can support healthcare professionals utilizing narrative texts. Our work is the result of a collaborative design process that was aided by empirical data collected through formal usability testing.

Keywords: classification, electronic health records, narrative texts, visualization

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Authors: Yumeng Ma, Fang Wang, Jinxia Huang

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Researchers put forward higher requirements for efficient acquisition and utilization of domain knowledge in the big data era. As literature is an effective way for researchers to quickly and accurately understand the research situation in their field, the knowledge discovery based on literature has become a new research method. As a tool to organize and manage knowledge in a specific domain, the subject knowledge base can be used to mine and present the knowledge behind the literature to meet the users' personalized needs. This study designs the construction route of the subject knowledge base for specific research problems. Information extraction method based on knowledge engineering is adopted. Firstly, the subject knowledge model is built through the abstraction of the research elements. Then under the guidance of the knowledge model, extraction rules of knowledge points are compiled to analyze, extract and correlate entities, relations, and attributes in literature. Finally, a database platform based on this structured knowledge is developed that can provide a variety of services such as knowledge retrieval, knowledge browsing, knowledge q&a, and visualization correlation. Taking the construction practices in the field of activating blood circulation and removing stasis as an example, this study analyzes how to construct subject knowledge base based on literature knowledge extraction. As the system functional test shows, this subject knowledge base can realize the expected service scenarios such as a quick query of knowledge, related discovery of knowledge and literature, knowledge organization. As this study enables subject knowledge base to help researchers locate and acquire deep domain knowledge quickly and accurately, it provides a transformation mode of knowledge resource construction and personalized precision knowledge services in the data-intensive research environment.

Keywords: knowledge model, literature knowledge extraction, precision knowledge services, subject knowledge base

Procedia PDF Downloads 159

Authors: Sadegh Marzban, Mohamad Sobhan Sheikh Andalibi, Farnaz Ghassemi, Farzad Towhidkhah

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Parkinson's disease (PD), which is characterized by the tremor at rest, rigidity, akinesia or bradykinesia and postural instability, affects the quality of life of involved individuals. The concept of a fractal is most often associated with irregular geometric objects that display self-similarity. Fractal dimension (FD) can be used to quantify the complexity and the self-similarity of an object such as tremor. In this work, we are aimed to propose a new method for evaluating hyperkinetic movements such as tremor, by using the FD and other correlated parameters in patients who are suffered from PD. In this study, we used 'the tremor data of Physionet'. The database consists of fourteen participants, diagnosed with PD including six patients with high amplitude tremor and eight patients with low amplitude. We tried to extract features from data, which can distinguish between patients before and after medication. We have selected fractal dimensions, including correlation dimension, box dimension, and information dimension. Lilliefors test has been used for normality test. Paired t-test or Wilcoxon signed rank test were also done to find differences between patients before and after medication, depending on whether the normality is detected or not. In addition, two-way ANOVA was used to investigate the possible association between the therapeutic effects and features extracted from the tremor. Just one of the extracted features showed significant differences between patients before and after medication. According to the results, correlation dimension was significantly different before and after the patient's medication (p=0.009). Also, two-way ANOVA demonstrates significant differences just in medication effect (p=0.033), and no significant differences were found between subject's differences (p=0.34) and interaction (p=0.97). The most striking result emerged from the data is that correlation dimension could quantify medication treatment based on tremor. This study has provided a technique to evaluate a non-linear measure for quantifying medication, nominally the correlation dimension. Furthermore, this study supports the idea that fractal dimension analysis yields additional information compared with conventional spectral measures in the detection of poor prognosis patients.

Keywords: correlation dimension, non-linear measure, Parkinson’s disease, tremor

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Authors: Amal Ait El Djoudi

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A thermodynamical model of coexisting hadronic and quark–gluon plasma (QGP) phases is used to study the thermally driven deconfining phase transition occurring between the two phases. A color singlet partition function is calculated for the QGP phase with two massless quarks, as in our previous work, but now the finite extensions of the hadrons are taken into account in the equation of state of the hadronic phase. In the present work, the finite-size effects on the system are examined by probing the behavior of some thermodynamic quantities, called response functions, as order parameter, energy density and their derivatives, on a range of temperature around the transition at different volumes. It turns out that the finiteness of the system size has as effects the rounding of the transition and the smearing of all the singularities occurring in the thermodynamic limit, and the additional finite-size effect introduced by the requirement of exact color-singletness involves a shift of the transition point. This shift as well as the smearing of the transition region and the maxima of both susceptibility and specific heat show a scaling behavior with the volume characterized by scaling exponents. Another striking result is the large similarity noted between the behavior of these response functions and that of the cumulants of the probability density. This similarity is worked to try to extract information concerning the occurring phase transition.

Keywords: equation of state, thermodynamics, deconfining phase transition, quark–gluon plasma (QGP)

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Authors: Adrian Forca, Simeon Cainday III

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The Electronic Payment Recording with Payment History Retrieval Module is developed intendedly for the College of Science and Technology. This system software innovates the manual process of recording the payments done in the department through the development of electronic payment recording system software shifting from the slow and time-consuming procedure to quick yet reliable and accurate way of recording payments because it immediately generates receipts for every transaction. As an added feature to its software process, generation of recorded payment report is integrated eliminating the manual reporting to a more easy and consolidated report. As an added feature to the system, all recorded payments of the students can be retrieved immediately making the system transparent and reliable payment recording software. Viewing the whole process, the system software will shift from the manual process to an organized software technology because the information will be stored in a logically correct and normalized database. Further, the software will be developed using the modern programming language and implement strict programming methods to validate all users accessing the system, evaluate all data passed into the system and information retrieved to ensure data accuracy and reliability. In addition, the system will identify the user and limit its access privilege to establish boundaries of the specific access to information allowed for the store, modify, and update making the information secure against unauthorized data manipulation. As a result, the System software will eliminate the manual procedure and replace with an innovative modern information technology resulting to the improvement of the whole process of payment recording fast, secure, accurate and reliable software innovations.

Keywords: collection, information system, manual procedure, payment

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Authors: Ching-Yuan Huang, Rhay-Hung Weng, Yi-Ting Chen

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Mentoring functions will improve new nurses' job performance, provide support with new nurses, and then reduce the turnover rate of them. This study explored the impact of transformational leadership and interpersonal interaction on mentoring functions. We employed a questionnaire survey to collect data and selected a sample of new nurses from three hospitals in Taiwan. A total of 306 valid surveys were obtained. Multiple regression model analysis was conducted to test the study hypothesis. Inspirational motivation, idealized influence, and individualized consideration had a positive influence on overall mentoring function, but intellectual stimulation had a positive influence on career development function only. Perceived similarity and interaction frequency also had positive influences on mentoring functions. When the shift overlap rate exceeded 80%, mentoring function experienced a negative result. The transformational leadership of mentors actually would improve the mentoring functions among new staff nurses. Perceived similarity and interaction frequency between mentees and mentors also had a positive influence on mentoring functions. Managers should enhance the transformational leadership of mentors by designing leadership training and motivation programs. Furthermore, nursing managers should promote the interaction between new staff nurses and their mentors, but the shift overlap rate should not exceed 80%.

Keywords: interpersonal interaction, mentoring function, mentor, new nurse, transformational leadership

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Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients

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Authors: Issam Ben Jami

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Information retrieval in digital libraries is very important because most famous historical documents occupy a significant value. The word spotting in historical documents is a very difficult notion, because automatic recognition of such documents is naturally cursive, it represents a wide variability in the level scale and translation words in the same documents. We first present a system for the automatic recognition, based on the extraction of interest points words from the image model. The extraction phase of the key points is chosen from the representation of the image as a synthetic description of the shape recognition in a multidimensional space. As a result, we use advanced methods that can find and describe interesting points invariant to scale, rotation and lighting which are linked to local configurations of pixels. We test this approach on documents of the 15th century. Our experiments give important results.

Keywords: feature matching, historical documents, pattern recognition, word spotting

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Authors: Vladimir A. Rozov

Abstract:

Comparative studies of religion and ritual could contribute better understanding of human culture universalities. Belief in supernatural beings seems to be a common feature of the religion. A significant part of the Islamic concepts that concern supernatural beings is based on a tradition based on the Hadiths. They reflect, among other things, his ideas about a proper way to interact with supernatural beings. These ideas to a large extent follow from the pre-Islamic religious experience of the Arabs and had been reflected in a number of ritual actions. Some of those beliefs concern a particular function of clothing. For example, it is known that Muhammad was wrapped in clothes during the revelation of the Quran. The same thing was performed by pre-Islamic soothsayers (kāhin) and by rival opponents of Muhammad during their trances. Muhammad also turned the clothes inside out during religious rituals (prayer for rain). Besides these specific ways of clothing which prove the external similarity of Muhammad with the soothsayers and other people who claimed the connection with supernatural forces, the pre-Islamic soothsayers had another characteristic feature which is physical flaws. In this regard, it is worth to note Muhammad's so-called "Seal the Prophecy" (h̠ ātam an- nubūwwa) -protrusion or outgrowth on his back. Another interesting feature of Muhammad's behavior was his attitude to eating onion and garlic. In particular, the Prophet didn`t eat them and forbade people who had tasted these vegetables to enter mosques, until the smell ceases to be felt. The reason for this ban on eating onion and garlic is caused by a belief that the smell of these products prevents communication with otherworldly forces. The materials of the Hadith also suggest that Muhammad shared faith in the apotropical properties of water. Both of these ideas have parallels in other cultures of the world. Muhammad's actions supposed to provide an interaction with the supernatural beings are not accidental. They have parallels in the culture of pre-Islamic Arabia as well as in many past and present world cultures. The latter fact can be explained by the similarity of the universal human beliefs in supernatural beings and how they should be interacted with. Later a number of similar ideas shared by the Prophet Muhammad was legitimized by the Islamic tradition and formed the basis of popular Islamic rituals. Thus, these parallels emphasize the commonality of human notions of supernatural beings and also demonstrate the significance of the pre-Islamic cultural context in analyzing the genesis of Islamic religious beliefs.

Keywords: hadith, Prophet Muhammad, ritual, supernatural beings

Procedia PDF Downloads 381

Authors: Mohsen Maraoui

Abstract:

In the aim of natural language processing applications improvement, such as information retrieval, machine translation, lexical disambiguation, we focus on statistical approach to semantic indexing for multilingual text documents based on conceptual network formalism. We propose to use this formalism as an indexing language to represent the descriptive concepts and their weighting. These concepts represent the content of the document. Our contribution is based on two steps. In the first step, we propose the extraction of index terms using the multilingual lexical resource Euro WordNet (EWN). In the second step, we pass from the representation of index terms to the representation of index concepts through conceptual network formalism. This network is generated using the EWN resource and pass by a classification step based on association rules model (in attempt to discover the non-taxonomic relations or contextual relations between the concepts of a document). These relations are latent relations buried in the text and carried by the semantic context of the co-occurrence of concepts in the document. Our proposed indexing approach can be applied to text documents in various languages because it is based on a linguistic method adapted to the language through a multilingual thesaurus. Next, we apply the same statistical process regardless of the language in order to extract the significant concepts and their associated weights. We prove that the proposed indexing approach provides encouraging results.

Keywords: concept extraction, conceptual network formalism, fuzzy association rules, multilingual thesaurus, semantic indexing

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Authors: Masood Beheshtirad

Abstract:

Identification of regions having potential for landslide occurrence is one of the basic measures in natural resources management. Different landslide hazard mapping models are proposed based on the environmental condition and goals. In this research landslide hazard map using multiple regression model were provided and applicability of this model is investigated in Baghdasht watershed. Dependent variable is landslide inventory map and independent variables consist of information layers as Geology, slope, aspect, distance from river, distance from road, fault and land use. For doing this, existing landslides have been identified and an inventory map made. The landslide hazard map is based on the multiple regression provided. The level of similarity potential hazard classes and figures of this model were compared with the landslide inventory map in the SPSS environments. Results of research showed that there is a significant correlation between the potential hazard classes and figures with area of the landslides. The multiple regression model is suitable for application in the Baghdasht Watershed.

Keywords: landslide, mapping, multiple model, regression

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Authors: Jing Zhang, Jie Chen

Abstract:

In this paper, we deal with the optimal I/O point location in an automated parking system. In this system, the S/R machine (storage and retrieve machine) travels independently in vertical and horizontal directions. Based on the characteristics of the parking system and the basic principle of AS/RS system (Automated Storage and Retrieval System), we obtain the continuous model in units of time. For the single command cycle using the randomized storage policy, we calculate the probability density function for the system travel time and thus we develop the travel time model. And we confirm that the travel time model shows a good performance by comparing with discrete case. Finally in this part, we establish the optimal model by minimizing the expected travel time model and it is shown that the optimal location of the I/O point is located at the middle of the left-hand above corner.

Keywords: parking system, optimal location, response time, S/R machine

Procedia PDF Downloads 403