Search results for: phonetic interpretation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1101

Search results for: phonetic interpretation

621 Study on The Model of Microscopic Contact Parameters for Grinding M300 Using Elastic Abrasive Tool

Authors: Wu Xiaojun, Liu Ruiping, Yu Xingzhan, Wu Qian

Abstract:

In precision grinding, utilizing the elastic matrix ball has higher processing efficiency and better superficial quality than traditional grinding. The diversity of characteristics which elastic abrasive tool contact with bend surface results in irregular wear abrasion,and abrasive tool machining status get complicated. There is no theoretical interpretation that parameters affect the grinding accuracy.Aiming at corrosion resistance, wear resistance and other characteristics of M 300 material, it is often used as a material on aerospace precision components. The paper carried out grinding and polishing experiments by using material of M 300,to theoretically show the relationship between stress magnitude and grinding efficiency,and predict the optimal combination of grinding parameter for effective grinding, just for the high abrasion resistance features of M 300, analyzing the micro-contact of elastic ball abrasive tool (Whetstone), using mathematical methods deduce the functional relationship between residual peak removal rate and the main parameters which impact the grinding accuracy on the plane case.Thus laying the foundation for the study of elastic abrasive prediction and compensation.

Keywords: flexible abrasive tool, polishing parameters, Hertz theory, removal rate

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620 Polite Request Strategies in Commuter Discourse in Xhosa

Authors: Mawande Dlali

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This paper examines the request strategies in commuter discourse involving taxi drivers and passengers in Khayelitsha as well as the responses to these requests. The present study considers requests in commuter transport as face threatening acts (FTAs), hence the need for the commuter crew to strategically shape their communicative actions to achieve their overall discourse goal of getting passengers to perform actions that are in their own interest with minimum resistance or confrontation. The crew presents itself by using communicative devices that prompt the passengers to evaluate it positively as warm, friendly, and respectful. However, the passengers' responses to requests range from compliance to resistance depending on their interpretation of the speaker’s motive and the probable social consequences. Participant observation by the researcher was the main method of collecting examples of requests and responses to the requests. Unstructured interviews and informal discussions were made with randomly selected taxi drivers and commuters. The findings and explanations presented in this article revealed the predominance of polite requests as speech acts in taxi discourse in Khayelitsha. This research makes a contribution to the contemporary pragmatics study of African languages in urban context.

Keywords: face threatening acts, speech acts, request strategies, discourse

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619 Creatures of the Clearing: Forests, People, and Ants in Imperial Brazil

Authors: Diogo de Carvalho Cabral

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This article offers a non-declensionist account of tropical deforestation, arguing that, rather than social stamp upon the environment or ecological endgame, deforestation is part of social site-making and remaking, the process through which humans produce sociality by carrying out nature-mediated – and therefore nature-transforming – practices that inevitably reset the very conditions of those practices. Human landscape-shaping inadvertently alters other species’ habitats –most often decimating them, but sometimes improving them–, the outcomes of which always resonate back upon human inhabitation and land use. Despite the overall tendency of biotic homogenization resulting from modern deforestation processes, there are always winners, i.e., species that gain competitive advantages enabling them to thrive in the novel ecosystems. Here it is examined one such case of deforestation-boosted species, namely leafcutter ants, which wrought havoc in the rural landscapes of nineteenth-century Brazil by defoliating a wide range of crops. By combining Historical GIS analysis and qualitative interpretation, it is shown how agricultural deforestation might have changed the ant species' biogeographies, and how in turn these changes – construed as 'infestation' – stimulated social innovations and rearrangements such as technical ingenuity, legal-administrative practices, and even local electoral arenas.

Keywords: deforestation, leafcutter ants, nineteenth-century Brazil, socio-ecological change

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618 Exploration and Exploitation within Operations

Authors: D. Gåsvaer, L. Stålberg, A. Fundin, M. Jackson, P. Johansson

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Exploration and exploitation capabilities are both important within Operations as means for improvement when managed separately, and for establishing dynamic improvement capabilities when combined in balance. However, it is unclear what exploration and exploitation capabilities imply in improvement and development work within an operations context. So in order to better understand how to develop exploration and exploitation capabilities within operations, the main characteristics of these constructs needs to be identified and further understood. Thus, the objective of this research is to increase the understanding about exploitation and exploration characteristics, to concretize what they translates to within the context of improvement and development work in an operations unit, and to identify practical challenges. A literature review and a case study are presented. In the literature review, different interpretations of exploration and exploitation are portrayed, key characteristics have been identified, and a deepened understanding of exploration and exploitation characteristics is described. The case in the study is an operations unit, and the aim is to explore to what extent and in what ways exploration and exploitation activities are part of the improvement structures and processes. The contribution includes an identification of key characteristics of exploitation and exploration, as well as an interpretation of the constructs. Further, some practical challenges are identified. For instance, exploration activities tend to be given low priority, both in daily work as in the manufacturing strategy. Also, the overall understanding about the concepts of exploitation and exploration (or any similar aspect of dynamic improvement capabilities) is very low.

Keywords: exploitation, exploration, improvement, lean production, manufacturing

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617 Sparse Modelling of Cancer Patients’ Survival Based on Genomic Copy Number Alterations

Authors: Khaled M. Alqahtani

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Copy number alterations (CNA) are variations in the structure of the genome, where certain regions deviate from the typical two chromosomal copies. These alterations are pivotal in understanding tumor progression and are indicative of patients' survival outcomes. However, effectively modeling patients' survival based on their genomic CNA profiles while identifying relevant genomic regions remains a statistical challenge. Various methods, such as the Cox proportional hazard (PH) model with ridge, lasso, or elastic net penalties, have been proposed but often overlook the inherent dependencies between genomic regions, leading to results that are hard to interpret. In this study, we enhance the elastic net penalty by incorporating an additional penalty that accounts for these dependencies. This approach yields smooth parameter estimates and facilitates variable selection, resulting in a sparse solution. Our findings demonstrate that this method outperforms other models in predicting survival outcomes, as evidenced by our simulation study. Moreover, it allows for a more meaningful interpretation of genomic regions associated with patients' survival. We demonstrate the efficacy of our approach using both real data from a lung cancer cohort and simulated datasets.

Keywords: copy number alterations, cox proportional hazard, lung cancer, regression, sparse solution

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616 The Analysis of One Million Reddit Confessions Corpus: The Use of Emotive Verbs and First Person Singular Pronoun as Linguistic Psychotherapy Features

Authors: Natalia Wojarnik

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The paper aims to present the analysis of a Reddit confessions corpus. The interpretation focuses on the use of emotional language, in particular emotive verbs, in the context of personal pronouns. The analysis of the linguistic properties answers the question of what the Reddit users confess about and who is the subject of confessions. The study reveals that the specific language patterns used in Reddit confessions reflect the language of depression and the language used by patients during different stages of their psychotherapy sessions. The paper concludes that Reddit users are more willing to confess about their own experiences, not rarely very private and intimate, extensively using the first person singular pronoun I. It indicates that the Reddit users use the language of depression and the language used by psychotherapy patients. The language they use is very emotionally impacted and includes many emotive verbs such as want, feel, need, hate, love. This finding in Reddit confessions correlates with the extensive use of stative affective verbs in the first stages of the psychotherapy sessions. Lastly, the paper refers to the positive and negative lexicon and helps determine how online posts can serve as a depression detector and “talking cure” for the users.

Keywords: confessions, emotional language, emotive verbs, pronouns, first person pronoun, language of depression, depression detection, psychotherapy language

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615 Deep Learning Based on Image Decomposition for Restoration of Intrinsic Representation

Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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614 Thermographic Tests of Curved GFRP Structures with Delaminations: Numerical Modelling vs. Experimental Validation

Authors: P. D. Pastuszak

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The present work is devoted to thermographic studies of curved composite panels (unidirectional GFRP) with subsurface defects. Various artificial defects, created by inserting PTFE stripe between individual layers of a laminate during manufacturing stage are studied. The analysis is conducted both with the use finite element method and experiments. To simulate transient heat transfer in 3D model with embedded various defect sizes, the ANSYS package is used. Pulsed Thermography combined with optical excitation source provides good results for flat surfaces. Composite structures are mostly used in complex components, e.g., pipes, corners and stiffeners. Local decrease of mechanical properties in these regions can have significant influence on strength decrease of the entire structure. Application of active procedures of thermography to defect detection and evaluation in this type of elements seems to be more appropriate that other NDT techniques. Nevertheless, there are various uncertainties connected with correct interpretation of acquired data. In this paper, important factors concerning Infrared Thermography measurements of curved surfaces in the form of cylindrical panels are considered. In addition, temperature effects on the surface resulting from complex geometry and embedded and real defect are also presented.

Keywords: active thermography, composite, curved structures, defects

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613 Interaction with Earth’s Surface in Remote Sensing

Authors: Spoorthi Sripad

Abstract:

Remote sensing is a powerful tool for acquiring information about the Earth's surface without direct contact, relying on the interaction of electromagnetic radiation with various materials and features. This paper explores the fundamental principle of "Interaction with Earth's Surface" in remote sensing, shedding light on the intricate processes that occur when electromagnetic waves encounter different surfaces. The absorption, reflection, and transmission of radiation generate distinct spectral signatures, allowing for the identification and classification of surface materials. The paper delves into the significance of the visible, infrared, and thermal infrared regions of the electromagnetic spectrum, highlighting how their unique interactions contribute to a wealth of applications, from land cover classification to environmental monitoring. The discussion encompasses the types of sensors and platforms used to capture these interactions, including multispectral and hyperspectral imaging systems. By examining real-world applications, such as land cover classification and environmental monitoring, the paper underscores the critical role of understanding the interaction with the Earth's surface for accurate and meaningful interpretation of remote sensing data.

Keywords: remote sensing, earth's surface interaction, electromagnetic radiation, spectral signatures, land cover classification, archeology and cultural heritage preservation

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612 Corporate Social Responsibility in an Experimental Market

Authors: Nikolaos Georgantzis, Efi Vasileiou

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We present results from experimental price-setting oligopolies in which green firms undertake different levels of energy-saving investments motivated by public subsidies and demand-side advantages. We find that consumers reveal higher willingness to pay for greener sellers’ products. This observation in conjunction to the fact that greener sellers set higher prices is compatible with the use and interpretation of energy-saving behaviour as a differentiation strategy. However, sellers do not exploit the resulting advantage through sufficiently high price-cost margins, because they seem trapped into “run to stay still” competition. Regarding the use of public subsidies to energy-saving sellers we uncover an undesirable crowding-out effect of consumers’ intrinsic tendency to support green manufacturers. Namely, consumers may be less willing to support a green seller whose energy-saving strategy entails a direct financial benefit. Finally, we disentangle two alternative motivations for consumer’s attractions to pro-social firms; first, the self-interested recognition of the firm’s contribution to the public and private welfare and, second, the need to compensate a firm for the cost entailed in each pro-social action. Our results show the prevalence of the former over the latter.

Keywords: corporate social responsibility, energy savings, public good, experiments, vertical differentiation, altruism

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611 Hydrocarbon New Business Opportunities in the Bida Basin of Central Nigeria: Prospect and Challenges

Authors: N. G. Obaje, S. I. Ibrahim, N. Dadi-Mamud, M. K. Musa, I. Yusuf

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An integrated study combining geological prospectivity mapping and geophysical aeromagnetic interpretation was carried out to determine hydrocarbon new business opportunities that may exist in the Bida Basin of Central Nigeria. Geological mapping was used to delineate the geological boundaries between the formations which is a significant initial criterion in evaluating hydrocarbon prospectivity. Processed and interpreted geophysical aeromagnetic data over the basin juxtaposed against the geological map has led to ranking of the prospectivity as less prospective, prospective and more prospective. The prospective and more prospective areas constitute new hydrocarbon business opportunities in the basin. The more prospective areas are at Pattishabakolo near Bida and at Kandi near Gulu. Prospective areas cover Badegi, Lemu, Duba, Kutigi, Auna, Mashegu and Mokwa. Geochemical data show that hydrocarbon source rocks exist within the Enagi and Patti formations in the northern and southern sections respectively. The geophysical aeromagnetic data indicates depths of more than 2,000m (> 2 Km) within the identified prospective areas. New business opportunities as used here refer to open acreages in Nigeria’s sedimentary basins that have not been licensed out by the government (Department of Petroleum Resources) to any operator but with significant potentials for commercial hydrocarbon accumulation.

Keywords: hydrocarbon, aeromagnetic, business opportunity, Bida Basin

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610 The Predicted Values of the California Bearing Ratio (CBR) by Using the Measurements of the Soil Resistivity Method (DC)

Authors: Fathi Ali Swaid

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The CBR test is widely used in the assessment of granular materials in base, subbase and subgrade layers of road and airfield pavements. Despite the success of this method, but it depends on a limited numbers of soil samples. This limitation do not adequately account for the spatial variability of soil properties. Thus, assessment is derived using these cursory soil data are likely to contain errors and thus make interpretation and soil characterization difficult. On the other hand quantitative methods of soil inventory at the field scale involve the design and adoption of sampling regimes and laboratory analysis that are time consuming and costly. In the latter case new technologies are required to efficiently sample and observe the soil in the field. This is particularly the case where soil bearing capacity is prevalent, and detailed quantitative information for determining its cause is required. In this paper, an electrical resistivity method DC is described and its application in Elg'deem Dirt road, located in Gasser Ahmad - Misurata, Libya. Results from the DC instrument were found to be correlated with the CBR values (r2 = 0.89). Finally, it is noticed that, the correlation can be used with experience for determining CBR value using basic soil electrical resistivity measurements and checked by few CBR test representing a similar range of CBR.

Keywords: California bearing ratio, basic soil electrical resistivity, CBR, soil, subgrade, new technologies

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609 Statistical Tools for SFRA Diagnosis in Power Transformers

Authors: Rahul Srivastava, Priti Pundir, Y. R. Sood, Rajnish Shrivastava

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For the interpretation of the signatures of sweep frequency response analysis(SFRA) of transformer different types of statistical techniques serves as an effective tool for doing either phase to phase comparison or sister unit comparison. In this paper with the discussion on SFRA several statistics techniques like cross correlation coefficient (CCF), root square error (RSQ), comparative standard deviation (CSD), Absolute difference, mean square error(MSE),Min-Max ratio(MM) are presented through several case studies. These methods require sample data size and spot frequencies of SFRA signatures that are being compared. The techniques used are based on power signal processing tools that can simplify result and limits can be created for the severity of the fault occurring in the transformer due to several short circuit forces or due to ageing. The advantages of using statistics techniques for analyzing of SFRA result are being indicated through several case studies and hence the results are obtained which determines the state of the transformer.

Keywords: absolute difference (DABS), cross correlation coefficient (CCF), mean square error (MSE), min-max ratio (MM-ratio), root square error (RSQ), standard deviation (CSD), sweep frequency response analysis (SFRA)

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608 Tectonic Inversion Manifestations in the Jebel Rouas-Ruissate (Northeastern Tunisia)

Authors: Aymen Arfaoui, Abdelkader Soumaya, Noureddine Ben Ayed

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The Rouas-Ruissateis a part of TunisianAtlas system. Analyze of the collected field data allowed us to propose a new interpretation for the main structural features of thisregion. Tectonic inversions along NE-SW trending fault of Zaghouan and holokinetic movements are the main factors controlling the architecture and geometry of the Jebel Rouas-Ruissate. The presence of breccias, Slumps, and synsedimentaryfaults along NW-SE and N-S trending major faults show that they were active during the Mesozoicextensionalepisodes. During Cenozoic inversion period, this structurewas shaped as imbricatefansformed byNE-SW trending thrust faults. The angularunconformitybetweenupperEocene- Oligocene, and Cretaceousdeposits reveals a compressive Eocene tectonic phase (called Pyrenean phase)occurred duringPaleocene-lower Eocene.The Triassicsaltsacted as a decollementlevel in the NE-SW trendingfault propagation fold model of the Rouas-Ruissate.The inversion of fault-slip data along the main regional fault zones reveals a coexistence of strike-slip and reverse fault stress regimes with NW-SE maximum horizontal stress(SHmax) characterizing the Alpine compressive phase (Upper Tortonian).

Keywords: tunisia, imbricate fans, triassic decollement level, fault propagation fold

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607 Jesus’ Approach in Liberation of the Poor, Luke 4:18-19: Lesson for Nigerian Leaders

Authors: Aboekwe, Mary Emilia

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Jesus’ mission was not only a religious one but had social and political implications. From the birth to the death of Jesus, God’s message of liberation is proclaimed in and through Jesus. This work studied Jesus’ inaugural mission in Luke 4: 18 -19 in the context of Nigerian leaders. A theological interpretation was adopted and it was discovered that Luke 4: 18-19 unfolded Jesus’ mission statement. This mission statement centered in preaching the good news to the poor, the release of the captives, healing the sick, liberation to the oppressed, and favour and abundance in the land. Related to the Jewish-Roman world of Jesus and the Nigerian nation, it was discovered that most of the maladies enumerated in Jesus’ inaugural mission statement were prevalent in Nigerian society. Maladies like poverty, oppression, violence, sickness and diseases are widespread in Nigeria. Poverty affects all, irrespective of gender, religion, or ethnicity. There is insecurity everywhere. Unemployment bites harder on Nigeria’s youthful population, and they are unable to find a job at the prevailing wage rate. To this effect, therefore, this study proposes Jesus’ liberative technique as a solution to these maladies prevalent in the country. The work equally challenged the Nigerian leaders to emulate Jesus’ mission statement and take proactive measures in fighting against these social challenges resident in Nigeria today.

Keywords: liberation, leadership, maladies, poverty

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606 Hybrid Algorithm for Non-Negative Matrix Factorization Based on Symmetric Kullback-Leibler Divergence for Signal Dependent Noise: A Case Study

Authors: Ana Serafimovic, Karthik Devarajan

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Non-negative matrix factorization approximates a high dimensional non-negative matrix V as the product of two non-negative matrices, W and H, and allows only additive linear combinations of data, enabling it to learn parts with representations in reality. It has been successfully applied in the analysis and interpretation of high dimensional data arising in neuroscience, computational biology, and natural language processing, to name a few. The objective of this paper is to assess a hybrid algorithm for non-negative matrix factorization with multiplicative updates. The method aims to minimize the symmetric version of Kullback-Leibler divergence known as intrinsic information and assumes that the noise is signal-dependent and that it originates from an arbitrary distribution from the exponential family. It is a generalization of currently available algorithms for Gaussian, Poisson, gamma and inverse Gaussian noise. We demonstrate the potential usefulness of the new generalized algorithm by comparing its performance to the baseline methods which also aim to minimize symmetric divergence measures.

Keywords: non-negative matrix factorization, dimension reduction, clustering, intrinsic information, symmetric information divergence, signal-dependent noise, exponential family, generalized Kullback-Leibler divergence, dual divergence

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605 Giftedness Cloud Model: A Psychological and Ecological Vision of Giftedness Concept

Authors: Rimeyah H. S. Almutairi, Alaa Eldin A. Ayoub

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The aim of this study was to identify empirical and theoretical studies that explored giftedness theories and identification. In order to assess and synthesize the mechanisms, outcomes, and impacts of gifted identification models. Thus, we sought to provide an evidence-informed answer to how does current giftedness theories work and effectiveness. In order to develop a model that incorporates the advantages of existing models and avoids their disadvantages as much as possible. We conducted a systematic literature review (SLR). The disciplined analysis resulted in a final sample consisting of 30 appropriate searches. The results indicated that: (a) there is no uniform and consistent definition of Giftedness; (b) researchers are using several non-consistent criteria to detect gifted, and (d) The detection of talent is largely limited to early ages, and there is obvious neglect of adults. This study contributes to the development of Giftedness Cloud Model (GCM) which defined as a model that attempts to interpretation giftedness within an interactive psychological and ecological framework. GCM aims to help a talented to reach giftedness core and manifestation talent in creative productivity or invention. Besides that, GCM suggests classifying giftedness into four levels of mastery, excellence, creative productivity, and manifestation. In addition, GCM presents an idea to distinguish between talent and giftedness.

Keywords: giftedness cloud model, talent, systematic literature review, giftedness concept

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604 Schematic Study of Groundwater Potential Zones in Granitic Terrain Using Remotesensing and GIS Techniques, in Miyapur and Bollaram Areas of Hyderabad, India

Authors: Ishrath, Tapas Kumar Chatterjee

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The present study aims developing interpretation and evaluation to integrate various data types for management of existing water resources for sustainable use. Proper study should be followed based on the geomorphology of the area. Thematic maps such as lithology, base map, land use/land cover, geomorphology, drainage and lineaments maps are prepared to study the area by using area toposheet, IRS P6 and LISIII Satellite imagery. These thematic layers are finally integrated by using Arc GIS, Arc View, and software to prepare a ground water potential zones map of the study area. In this study, an integrated approach involving remote sensing and GIS techniques has successfully been used in identifying groundwater potential zones in the study area to classify them as good, moderate and poor. It has been observed that Pediplain shallow (PPS) has good recharge, Pediplain moderate (PPM) has moderately good recharge, Pediment Inselberg complex (PIC) has poor recharge and Inselberg (I) has no recharge. The study has concluded that remote sensing and GIS techniques are very efficient and useful for identifying ground water potential zones.

Keywords: satellite remote sensing, GIS, ground water potential zones, Miyapur

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603 Developing a Risk Rating Tool for Shopping Centres

Authors: Prandesha Govender, Chris Cloete

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Purpose: The objective of the paper is to develop a tool for the evaluation of the financial risk of a shopping center. Methodology: Important factors that indicate the success of a shopping center were identified from the available literature. Weights were allocated to these factors and a risk rating was calculated for 505 shopping centers in the largest province in South Africa by taking the factor scores, factor weights, and category weights into account. The ratings for ten randomly selected shopping centers were correlated with consumer feedback and standardized against the ECAI (External Credit Assessment Institutions) data for the same centers. The ratings were also mapped to corporates with the same risk rating to provide a better intuitive assessment of the meaning of the inherent risk of each center. Results: The proposed risk tool shows a strong linear correlation with consumer views and can be compared to expert opinions, such as that of fund managers and REITs. Interpretation of the tool was also illustrated by correlating the risk rating of selected shopping centers to the risk rating of reputable and established entities. Conclusions: The proposed Shopping Centre Risk Tool, used in conjunction with financial inputs from the relevant center, should prove useful to an investor when the desirability of investment in or expansion, renovation, or purchase of a shopping center is being considered.

Keywords: risk, shopping centres, risk modelling, investment, rating tool, rating scale

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602 The Relationship between Spanish Economic Variables: Evidence from the Wavelet Techniques

Authors: Concepcion Gonzalez-Concepcion, Maria Candelaria Gil-Fariña, Celina Pestano-Gabino

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We analyze six relevant economic and financial variables for the period 2000M1-2015M3 in the context of the Spanish economy: a financial index (IBEX35), a commodity (Crude Oil Price in euros), a foreign exchange index (EUR/USD), a bond (Spanish 10-Year Bond), the Spanish National Debt and the Consumer Price Index. The goal of this paper is to analyze the main relations between them by computing the Wavelet Power Spectrum and the Cross Wavelet Coherency associated with Morlet wavelets. By using a special toolbox in MATLAB, we focus our interest on the period variable. We decompose the time-frequency effects and improve the interpretation of the results by non-expert users in the theory of wavelets. The empirical evidence shows certain instability periods and reveals various changes and breaks in the causality relationships for sample data. These variables were individually analyzed with Daubechies Wavelets to visualize high-frequency variance, seasonality, and trend. The results are included in Proceeding 20th International Academic Conference, 2015, International Institute of Social and Economic Sciences (IISES), Madrid.

Keywords: economic and financial variables, Spain, time-frequency domain, wavelet coherency

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601 Interpretable Deep Learning Models for Medical Condition Identification

Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

Abstract:

Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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600 Improving Research by the Integration of a Collaborative Dimension in an Information Retrieval (IR) System

Authors: Amel Hannech, Mehdi Adda, Hamid Mcheick

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In computer science, the purpose of finding useful information is still one of the most active and important research topics. The most popular application of information retrieval (IR) are Search Engines, they meet users' specific needs and aim to locate the effective information in the web. However, these search engines have some limitations related to the relevancy of the results and the ease to explore those results. In this context, we proposed in previous works a Multi-Space Search Engine model that is based on a multidimensional interpretation universe. In the present paper, we integrate an additional dimension that allows to offer users new research experiences. The added component is based on creating user profiles and calculating the similarity between them that then allow the use of collaborative filtering in retrieving search results. To evaluate the effectiveness of the proposed model, a prototype is developed. The experiments showed that the additional dimension has improved the relevancy of results by predicting the interesting items of users based on their experiences and the experiences of other similar users. The offered personalization service allows users to approve the pertinent items, which allows to enrich their profiles and further improve research.

Keywords: information retrieval, v-facets, user behavior analysis, user profiles, topical ontology, association rules, data personalization

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599 Pure Scalar Equilibria for Normal-Form Games

Authors: Herbert W. Corley

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A scalar equilibrium (SE) is an alternative type of equilibrium in pure strategies for an n-person normal-form game G. It is defined using optimization techniques to obtain a pure strategy for each player of G by maximizing an appropriate utility function over the acceptable joint actions. The players’ actions are determined by the choice of the utility function. Such a utility function could be agreed upon by the players or chosen by an arbitrator. An SE is an equilibrium since no players of G can increase the value of this utility function by changing their strategies. SEs are formally defined, and examples are given. In a greedy SE, the goal is to assign actions to the players giving them the largest individual payoffs jointly possible. In a weighted SE, each player is assigned weights modeling the degree to which he helps every player, including himself, achieve as large a payoff as jointly possible. In a compromise SE, each player wants a fair payoff for a reasonable interpretation of fairness. In a parity SE, the players want their payoffs to be as nearly equal as jointly possible. Finally, a satisficing SE achieves a personal target payoff value for each player. The vector payoffs associated with each of these SEs are shown to be Pareto optimal among all such acceptable vectors, as well as computationally tractable.

Keywords: compromise equilibrium, greedy equilibrium, normal-form game, parity equilibrium, pure strategies, satisficing equilibrium, scalar equilibria, utility function, weighted equilibrium

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598 Attribute Analysis of Quick Response Code Payment Users Using Discriminant Non-negative Matrix Factorization

Authors: Hironori Karachi, Haruka Yamashita

Abstract:

Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: data science, non-negative matrix factorization, missing data, quality of services

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597 Electrical Transport in Bi₁Sb₁Te₁.₅Se₁.₅ /α-RuCl₃ Heterostructure Nanodevices

Authors: Shoubhik Mandal, Debarghya Mallick, Abhishek Banerjee, R. Ganesan, P. S. Anil Kumar

Abstract:

We report magnetotransport measurements in Bi₁Sb₁Te₁.₅Se₁.₅/RuCl₃ heterostructure nanodevices. Bi₁Sb₁Te₁.₅Se₁.₅ (BSTS) is a strong three-dimensional topological insulator (3D-TI) that hosts conducting topological surface states (TSS) enclosing an insulating bulk. α-RuCl₃ (namely, RuCl₃) is an anti-ferromagnet that is predicted to behave as a Kitaev-like quantum spin liquid carrying Majorana excitations. Temperature (T)-dependent resistivity measurements show the interplay between parallel bulk and surface transport channels. At T < 150 K, surface state transport dominates over bulk transport. Multi-channel weak anti-localization (WAL) is observed, as a sharp cusp in the magnetoconductivity, indicating strong spin-orbit coupling. The presence of top and bottom topological surface states (TSS), including a pair of electrically coupled Rashba surface states (RSS), are indicated. Non-linear Hall effect, explained by a two-band model, further supports this interpretation. Finally, a low-T logarithmic resistance upturn is analyzed using the Lu-Shen model, supporting the presence of gapless surface states with a π Berry phase.

Keywords: topological materials, electrical transport, Lu-Shen model, quantum spin liquid

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596 Rethinking Nigeria's Foreign Policy in the Age of Global Terrorism

Authors: Shuaibu Umar Abdul

Abstract:

This paper examines Nigeria’s foreign policy in the age of global terrorism. It worth saying that the threat of ‘terrorism’ is not peculiar to Western and Middle Eastern countries alone, its tentacles are now spreading all over, Africa inclusive. The issue of domestic terrorism in Nigeria has become pervasive since the return of democratic rule in 1999. This development has never been a witness in any form throughout the year of statehood in Nigeria, the issues of banditry, armed robbery, ritual killing, and criminal activities like kidnapping and pipeline vandalization, the breakdown of law and order, poorly managed infrastructural facilities and corruption remain synonymous to Nigeria. These acts of terrorism no doubt have constituted a challenge that necessitates the paradigm shift in Nigeria’s foreign policy. The study employed the conceptual framework of analysis to lead interrogation; secondary sources were used to generate data while descriptive and content analysis were considered for data presentation and interpretation. In view of the interrogation and discussion on the subject matter, the paper revealed that Nigerian government underrated and underestimated the strength of terrorism within and outside her policy hence, it becomes difficult to address. As a response to the findings and conclusion of the study, the paper recommends among others that Nigeria’s foreign policy has to be rethought, reshaped and remodeled in cognizance to the rising global terrorism for peace, growth and development in the country.

Keywords: foreign policy, globe, Nigeria, rethinking, terrorism

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595 A Comparative Study on Software Patent: The Meaning of 'Use' in Direct Infringement

Authors: Tien Wei Daniel Hwang

Abstract:

The computer program inventors, particularly in Fintech, are unwilling to apply for patents in Taiwan after 2014. Passing the ‘statutory subject matter eligibility’ test and becoming the system patent are not the only cause to the reduction in the number of application. Taiwanese court needs to resolve whether the defendants had ‘used’ that software patent in patent direct infringement suit. Both 35 U.S.C. § 271(a) and article 58 paragraph 2 of Taiwan Patent Law don’t define the meaning of ‘use’ in the statutes. Centillion Data Sys., LLC v. Qwest Commc’ns Int’l, Inc. reconsidered the meaning of ‘use’ in system patent infringement, and held that ‘a party must put the invention into service, i.e., control the system as a whole and obtain benefit from it.’ In Taiwan, Intellectual Property Office, Ministry of Economic Affairs, has explained that ‘using’ the patent is ‘achieving the technical effect of the patent.’ Nonetheless, this definition is too broad to apply to not only the software patent but also the traditional patent. To supply the friendly environment for Fintech corporations, this article aims to let Taiwanese court realize why and how United States District Court, S.D. Indiana, Indianapolis Division and United States Court of Appeals, Federal Circuit defined the meaning of ‘use’ in 35 U.S.C. § 271(a). However, this definition is so lax and confuses many defendants in United States. Accordingly, this article indicates the elements in Taiwan Patent Law are different with 35 U.S.C. § 271(a), so Taiwanese court can follow the interpretation of ‘use’ in Centillion Data case without the same obstacle.

Keywords: direct infringement, FinTech, software patent, use

Procedia PDF Downloads 286
594 A Comparative Study of Wellness Among Sportsmen and Non Sportsmen

Authors: Jaskaran Singh Sidhu

Abstract:

Aim: The purpose of this study is to find the relationship between wellness among sportsmen and non sportsmen. Methodology: The present study is an experimental study for 80 senior secondary volleyball players of 16-19 years of age from Ludhiana District of Punjab (India), and 80 non-sportsperson were taken from senior secondary school of Ludhiana district. The sample for this study was taken through a random sampling technique. Tools: A five point scale havinf 50 items was used to acess the wellness Statistical Analysis: To find out the relationship among the variables exists or not, a t-test was used to test the significance of the difference between the means. Statistics for each characteristic were calculated; Mean, Standard deviation, Standard error of Mean. Data were analyzed using SPSS (statistical package for the social sciences). Statistical significance was set at p < 0.05. Results: Substantial deviations were noted at p<0.5 in the totality of wellness. Sportsmen show significant differences exist at p<0.5 in three parameters of wellness i.e., physical wellness, mental wellness, and social wellness. In spiritual and emotional wellness attributes, non-sportsmen shows significant difference at p<0.5. Conclusion: From the data interpretation it reflects that overall wellness can be improved by participation in sports. It further noted in study that participation in sports promote the attributes of wellness i.e., physical wellness, mental wellness, emotional wellness and social wellness.

Keywords: physical, mental, social, emotional, wellness, spiritual

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593 Principal Component Analysis in Drug-Excipient Interactions

Authors: Farzad Khajavi

Abstract:

Studies about the interaction between active pharmaceutical ingredients (API) and excipients are so important in the pre-formulation stage of development of all dosage forms. Analytical techniques such as differential scanning calorimetry (DSC), Thermal gravimetry (TG), and Furrier transform infrared spectroscopy (FTIR) are commonly used tools for investigating regarding compatibility and incompatibility of APIs with excipients. Sometimes the interpretation of data obtained from these techniques is difficult because of severe overlapping of API spectrum with excipients in their mixtures. Principal component analysis (PCA) as a powerful factor analytical method is used in these situations to resolve data matrices acquired from these analytical techniques. Binary mixtures of API and interested excipients are considered and produced. Peaks of FTIR, DSC, or TG of pure API and excipient and their mixtures at different mole ratios will construct the rows of the data matrix. By applying PCA on the data matrix, the number of principal components (PCs) is determined so that it contains the total variance of the data matrix. By plotting PCs or factors obtained from the score of the matrix in two-dimensional spaces if the pure API and its mixture with the excipient at the high amount of API and the 1:1mixture form a separate cluster and the other cluster comprise of the pure excipient and its blend with the API at the high amount of excipient. This confirms the existence of compatibility between API and the interested excipient. Otherwise, the incompatibility will overcome a mixture of API and excipient.

Keywords: API, compatibility, DSC, TG, interactions

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592 Integration of Load Introduction Elements into Fabrics

Authors: Jan Schwennen, Harlad Schmid, Juergen Fleischer

Abstract:

Lightweight design plays an important role in the automotive industry. Especially the combination of metal and CFRP shows great potential for future vehicle concepts. This requires joining technologies that are cost-efficient and appropriate for the materials involved. Previous investigations show that integrating load introduction elements during CFRP part manufacturing offers great advantages in mechanical performance. However, it is not yet clear how to integrate the elements in an automated process without harming the fiber structure. In this paper, a test rig is build up to investigate the effect of different parameters during insert integration experimentally. After a short description of the experimental equipment, preliminary tests are performed to determine a set of important process parameters. Based on that, the planning of design of experiments is given. The interpretation and evaluation of the test results show that with a minimization of the insert diameter and the peak angle less harm on the fiber structure can be achieved. Furthermore, a maximization of the die diameter above the insert shows a positive effect on the fiber structure. At the end of this paper, a theoretical description of alternative peak shaping is given and then the results get validated on the basis of an industrial reference part.

Keywords: CFRP, fabrics, insert, load introduction element, integration

Procedia PDF Downloads 226