Search results for: Quaternion Fourier transform
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1630

Search results for: Quaternion Fourier transform

310 Experiential Learning: Roles and Attributes of an Optometry Educator Recommended by a Millennial Generation

Authors: E. Kempen, M. J. Labuschagne, M. P. Jama

Abstract:

There is evidence that experiential learning is truly influential and favored by the millennial generation. However, little is known about the role and attributes an educator has to adopt during the experiential learning cycle, especially when applied in optometry education. This study aimed to identify the roles and attributes of an optometry educator during the different modes of the experiential learning cycle. Methods: A qualitative case study design was used. Data was collected using an open-ended questionnaire survey, following the application of nine different teaching-learning methods based on the experimental learning cycle. The total sample population of 68 undergraduate students from the Department of Optometry at the University of the Free State, South Africa were invited to participate. Focus group interviews (n=15) added additional data that contributed to the interpretation and confirmation of the data obtained from the questionnaire surveys. Results: The perceptions and experiences of the students identified a variety of roles and attributes as well as recommendations on the effective adoption of these roles and attributes. These roles and attributes included being knowledgeable, creating an interest, providing guidance, being approachable, building confidence, implementing ground rules, leading by example, and acting as a mediator. Conclusion: The findings suggest that the actions of an educator have the most substantial impact on students’ perception of a learning experience. Not only are the recommendations based on the views of a millennial generation, but the implementation of the personalized recommendations may also transform a learning environment. This may lead an optometry student to a deeper understanding of knowledge.

Keywords: experiences and perceptions, experiential learning, millennial generation, recommendation for optometry education

Procedia PDF Downloads 90
309 Negotiated Peace in Africa: A Case Study on the Pretoria Peace Deal between Federal Democratic Republic of Ethiopia and Tigray Peoples Liberation Front

Authors: Daniel Gidey, Kunwar Siddarth Dadhwal, Tagel Wondimu

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There are numerous ways for ending conflict; hitherto, most conflicts are resolved either through negotiated or victor's peace, this article is about the former. Negotiations entail concessions, consensus-building, and mutual trust in order to transform a belligerent situation into a settlement. In such a context, regional and sub-regional organizations play a critical role in mediating conflicting parties so as to prevent, manage, and resolve conflicts between and among conflicting parties. This article is about the AU-led negotiated peace deal on the bloody conflict between the Tigray Peoples Liberation Front (TPLF) and the Federal Democratic Republic of Ethiopia (FDRE) by undertaking the Pretoria Peace Accord as a case study. In terms of research method, the article is based on a critical evaluation of the literature and content analysis on the very research topic. Findings of the study revealed that the AU, through Olusegun Obasanjo and other dignitaries, played a critical role in nurturing compromise and mutual trust between the TPLF and the Ethiopian federal government so as to take along the Pretoria peace deal. Through critical literature review and content analysis of the Peace deal, the article has concluded that negotiated peace is likely, at least, to achieve negative peace.

Keywords: regional organizations, peace promotion, African Union, negotiating conflicts, Northern Ethiopia, conflict resolution

Procedia PDF Downloads 39
308 Sensory Gap Analysis on Port Wine Promotion and Perceptions

Authors: José Manue Carvalho Vieira, Mariana Magalhães, Elizabeth Serra

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The Port Wine industry is essential to Portugal because it carries a tangible cultural heritage and for social and economic reasons. Positioned as a luxury product, brands need to pay more attention to the new generation's habits, preferences, languages, and sensory perceptions. Healthy lifestyles, anti-alcohol campaigns, and digitalisation of their buying decision process need to be better understood to understand the wine market in the future. The purpose of this study is to clarify the sensory perception gap between Port Wine descriptors promotion and the new generation's perceptions to help wineries to align their strategies. Based on the interpretivist approach - multiple methods and techniques (mixed-methods), different world views and different assumptions, and different data collection methods and analysis, this research integrated qualitative semi-structured interviews, Port Wine promotion contents, and social media perceptions mined by Sentiment Analysis Enginius algorithm. Findings confirm that Port Wine CEOs' strategies, brands' promotional content, and social perceptions are not sufficiently aligned. The central insight for Port Wine brands' managers is that there is a long and continuous work of understanding and associating their descriptors with the most relevant perceptual values and criteria of their targets to reposition (when necessary) and sustainably revitalise their brands. Finally, this study hypothesised a sensory gap that leads to a decrease in consumption, trying to find recommendations on how to transform it into an advantage for a better attraction towards the young age group (18-25).

Keywords: port wine, consumer habits, sensory gap analysis, wine marketing

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307 Neural Graph Matching for Modification Similarity Applied to Electronic Document Comparison

Authors: Po-Fang Hsu, Chiching Wei

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In this paper, we present a novel neural graph matching approach applied to document comparison. Document comparison is a common task in the legal and financial industries. In some cases, the most important differences may be the addition or omission of words, sentences, clauses, or paragraphs. However, it is a challenging task without recording or tracing the whole edited process. Under many temporal uncertainties, we explore the potentiality of our approach to proximate the accurate comparison to make sure which element blocks have a relation of edition with others. In the beginning, we apply a document layout analysis that combines traditional and modern technics to segment layouts in blocks of various types appropriately. Then we transform this issue into a problem of layout graph matching with textual awareness. Regarding graph matching, it is a long-studied problem with a broad range of applications. However, different from previous works focusing on visual images or structural layout, we also bring textual features into our model for adapting this domain. Specifically, based on the electronic document, we introduce an encoder to deal with the visual presentation decoding from PDF. Additionally, because the modifications can cause the inconsistency of document layout analysis between modified documents and the blocks can be merged and split, Sinkhorn divergence is adopted in our neural graph approach, which tries to overcome both these issues with many-to-many block matching. We demonstrate this on two categories of layouts, as follows., legal agreement and scientific articles, collected from our real-case datasets.

Keywords: document comparison, graph matching, graph neural network, modification similarity, multi-modal

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306 Analysis of Ionospheric Variations over Japan during 23rd Solar Cycle Using Wavelet Techniques

Authors: C. S. Seema, P. R. Prince

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The characterization of spatio-temporal inhomogeneities occurring in the ionospheric F₂ layer is remarkable since these variations are direct consequences of electrodynamical coupling between magnetosphere and solar events. The temporal and spatial variations of the F₂ layer, which occur with a period of several days or even years, mainly owe to geomagnetic and meteorological activities. The hourly F₂ layer critical frequency (foF2) over 23rd solar cycle (1996-2008) of three ionosonde stations (Wakkanai, Kokunbunji, and Okinawa) in northern hemisphere, which falls within same longitudinal span, is analyzed using continuous wavelet techniques. Morlet wavelet is used to transform continuous time series data of foF2 to a two dimensional time-frequency space, quantifying the time evolution of the oscillatory modes. The presence of significant time patterns (periodicities) at a particular time period and the time location of each periodicity are detected from the two-dimensional representation of the wavelet power, in the plane of scale and period of the time series. The mean strength of each periodicity over the entire period of analysis is studied using global wavelet spectrum. The quasi biennial, annual, semiannual, 27 day, diurnal and 12 hour variations of foF2 are clearly evident in the wavelet power spectra in all the three stations. Critical frequency oscillations with multi-day periods (2-3 days and 9 days in the low latitude station, 6-7 days in all stations and 15 days in mid-high latitude station) are also superimposed over large time scaled variations.

Keywords: continuous wavelet analysis, critical frequency, ionosphere, solar cycle

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305 A Mathematical Study of Magnetic Field, Heat Transfer and Brownian Motion of Nanofluid over a Nonlinear Stretching Sheet

Authors: Madhu Aneja, Sapna Sharma

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Thermal conductivity of ordinary heat transfer fluids is not adequate to meet today’s cooling rate requirements. Nanoparticles have been shown to increase the thermal conductivity and convective heat transfer to the base fluids. One of the possible mechanisms for anomalous increase in the thermal conductivity of nanofluids is the Brownian motions of the nanoparticles in the basefluid. In this paper, the natural convection of incompressible nanofluid over a nonlinear stretching sheet in the presence of magnetic field is studied. The flow and heat transfer induced by stretching sheets is important in the study of extrusion processes and is a subject of considerable interest in the contemporary literature. Appropriate similarity variables are used to transform the governing nonlinear partial differential equations to a system of nonlinear ordinary (similarity) differential equations. For computational purpose, Finite Element Method is used. The effective thermal conductivity and viscosity of nanofluid are calculated by KKL (Koo – Klienstreuer – Li) correlation. In this model effect of Brownian motion on thermal conductivity is considered. The effect of important parameter i.e. nonlinear parameter, volume fraction, Hartmann number, heat source parameter is studied on velocity and temperature. Skin friction and heat transfer coefficients are also calculated for concerned parameters.

Keywords: Brownian motion, convection, finite element method, magnetic field, nanofluid, stretching sheet

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304 Enhancing Temporal Extrapolation of Wind Speed Using a Hybrid Technique: A Case Study in West Coast of Denmark

Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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303 Transforming ESL Teaching and Learning with ICT

Authors: Helena Sit

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Developing skills in using ICT in the language classroom has been discussed at all educational levels. Digital tools and learning management systems enable teachers to transform their instructional activities while giving learners the opportunity to engage with virtual communities. In the field of English as a second language (ESL) teaching and learning, the use of technology-enhanced learning and diverse pedagogical practices continues to grow. Whilst technology and multimodal learning is a way of the future for education, second language teachers now face the predicament as to whether implementing these newer ways of learning is, in fact, beneficial or disadvantageous to learners. Research has shown that integrating multimodality and technology can improve students’ engagement and participation in their English language learning. However, students can experience anxiety or misunderstanding when engaging with E-learning or digital-mediated learning. This paper aims to explore how ESL teaching and learning are transformed via the use of educational technology and what impact it has had on student teachers. Case study is employed in this research. The study reviews the growing presence of technology and multimodality in university language classrooms, discusses their impact on teachers’ pedagogical practices, and proposes scaffolding strategies to help design effective English language courses in the Australian education context. The study sheds light on how pedagogical integration today may offer a way forward for language teachers of tomorrow and provides implications to implement an evidence-informed approach that blends knowledge from research, practice and people experiencing the practice in the digital era.

Keywords: educational technology, ICT in higher education, curriculum design and innovation, teacher education, multiliteracies pedagogy

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302 Counter-Urbanisation and Digital Nomads: Connections of the Two Phenomena and Infrastructure in Greece

Authors: Dimitrios Orfanos, Yannis Maniatis, Alcestis Rodi

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The overconcentration of people in big cities (namely Athens and Thessaloniki) and the tendency to increase their density in the upcoming years cause various problems on a personal, environmental, and social level. During the COVID-19 pandemic, a reversal in urbanism was observed. The counter-urbanization that took place, along with the steady growth of the digital nomad lifestyle, opens up new paths for policies that rejuvenate the non-urban regions in Greece and elsewhere. Promoting actions, either through incentives or through creating organized structures, can transform the Greek rural regions into attractive destinations for those who want to avoid life in big cities permanently or for a short period of time. Subsequently, the gain of the regions that will apply such policies will have a multiplier effect. Greece, being a country with great touristic interest from foreigners, can use the infusion of long-stay visitors as a boost to give way to the Greek urban population that works remotely to move permanently to more rural regions and create the conditions for growth in those regions. The paper studies several cases of such policies, in combination with different options to be explored as to the methods that can be used to take better advantage of these policies. Examples from European and worldwide use cases are presented, noting the parts that can be applied in a country like Greece. An example of an abandoned village is also presented that can be revived through the methods described in the paper. The next possible step in research could be a case study in one of the various locations to determine the level of maturity of the market to pursue such actions.

Keywords: counter-urbanization, digital nomads, rural growth, village revival

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301 The Factors Constitute the Interaction between Teachers and Students: An Empirical Study at the Notion of Framing

Authors: Tien-Hui Chiang

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The code theory, proposed by Basil Bernstein, indicates that framing can be viewed as the core element in constituting the phenomenon of cultural reproduction because it is able to regulate the transmission of pedagogical information. Strong framing increases the social relation boundary between a teacher and pupils, which obstructs information transmission, so that in order to improve underachieving students’ academic performances, teachers need to reduce to strength of framing. Weak framing enables them to transform academic knowledge into commonsense knowledge in daily life language. This study posits that most teachers would deliver strong framing due to their belief mainly confined within the aspect of instrumental rationality that deprives their critical minds. This situation could make them view the normal distribution bell curve of students’ academic performances as a natural outcome. In order to examine the interplay between framing, instrumental rationality and pedagogical action, questionnaires were completed by over 5,000 primary school teachers in Henan province, China, who were stratified sample. The statistical results show that most teachers employed psychological concepts to measure students’ academic performances and, in turn, educational inequity was legitimatized as a natural outcome in the efficiency-led approach. Such efficiency-led minds made them perform as the agent practicing the mechanism of social control and in turn sustaining the phenomenon of cultural reproduction.

Keywords: code, cultural reproduction, framing, instrumental rationality, social relation and interaction

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300 Structural Health Monitoring of Buildings–Recorded Data and Wave Method

Authors: Tzong-Ying Hao, Mohammad T. Rahmani

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This article presents the structural health monitoring (SHM) method based on changes in wave traveling times (wave method) within a layered 1-D shear beam model of structure. The wave method measures the velocity of shear wave propagating in a building from the impulse response functions (IRF) obtained from recorded data at different locations inside the building. If structural damage occurs in a structure, the velocity of wave propagation through it changes. The wave method analysis is performed on the responses of Torre Central building, a 9-story shear wall structure located in Santiago, Chile. Because events of different intensity (ambient vibrations, weak and strong earthquake motions) have been recorded at this building, therefore it can serve as a full-scale benchmark to validate the structural health monitoring method utilized. The analysis of inter-story drifts and the Fourier spectra for the EW and NS motions during 2010 Chile earthquake are presented. The results for the NS motions suggest the coupling of translation and torsion responses. The system frequencies (estimated from the relative displacement response of the 8th-floor with respect to the basement from recorded data) were detected initially decreasing approximately 24% in the EW motion. Near the end of shaking, an increase of about 17% was detected. These analysis and results serve as baseline indicators of the occurrence of structural damage. The detected changes in wave velocities of the shear beam model are consistent with the observed damage. However, the 1-D shear beam model is not sufficient to simulate the coupling of translation and torsion responses in the NS motion. The wave method is proven for actual implementation in structural health monitoring systems based on carefully assessing the resolution and accuracy of the model for its effectiveness on post-earthquake damage detection in buildings.

Keywords: Chile earthquake, damage detection, earthquake response, impulse response function, shear beam model, shear wave velocity, structural health monitoring, torre central building, wave method

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299 Recognition and Counting Algorithm for Sub-Regional Objects in a Handwritten Image through Image Sets

Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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298 Q-Map: Clinical Concept Mining from Clinical Documents

Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

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Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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297 Near-Infrared Optogenetic Manipulation of a Channelrhodopsin via Upconverting Nanoparticles

Authors: Kanchan Yadav, Ai-Chuan Chou, Rajesh Kumar Ulaganathan, Hua-De Gao, Hsien-Ming Lee, Chien-Yuan Pan, Yit-Tsong Chen

Abstract:

Optogenetics is an innovative technology now widely adopted by researchers in different fields of the biological sciences. However, due to the weak tissue penetration capability of the short wavelengths used to activate light-sensitive proteins, an invasive light guide has been used in animal studies for photoexcitation of target tissues. Upconverting nanoparticles (UCNPs), which transform near-infrared (NIR) light to short-wavelength emissions, can help address this issue. To improve optogenetic performance, we enhance the target selectivity for optogenetic controls by specifically conjugating the UCNPs with light-sensitive proteins at a molecular level, which shortens the distance as well as enhances the efficiency of energy transfer. We tagged V5 and Lumio epitopes to the extracellular N-terminal of channelrhodopsin-2 with an mCherry conjugated at the intracellular C-terminal (VL-ChR2m) and then bound NeutrAvidin-functionalized UCNPs (NAv-UCNPs) to the VL-ChR2m via a biotinylated antibody against V5 (bV5-Ab). We observed an apparent energy transfer from the excited UCNP (donor) to the bound VL-ChR2m (receptor) by measuring emission-intensity changes at the donor-receptor complex. The successful patch-clamp electrophysiological test and an intracellular Ca2+ elevation observed in the designed UCNP-ChR2 system under optogenetic manipulation confirmed the practical employment of UCNP-assisted NIR-optogenetic functionality. This work represents a significant step toward improving therapeutic optogenetics.

Keywords: Channelrhodopsin-2, near infrared, optogenetics, upconverting nanoparticles

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296 Characterisation of Extracellular Polymeric Substances from Bacteria Isolated from Acid Mine Decant in Gauteng, South Africa

Authors: Nonhlanhla Nkosi, Kulsum Kondiah

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The toxicological manifestation of heavy metals motivates interest towards the development of a reliable, eco-friendly biosorption process. With that being said, the aim of the current study was to characterise the EPS from heavy-metal resistant bacteria isolated from acid mine decant on the West Rand, Gauteng, South Africa. To achieve this, six exopolysaccharide (EPS) producing, metal resistant strains (Pb101, Pb102, Pb103, Pb204, Co101, and Ni101) were identified as Bacillus safensis strain NBRC 100820, Bacillus proteolyticus, Micrococcus luteus, Enterobacter sp. Pb204, Bacillus wiedmannii and Bacillus zhangzhouensis, respectively with 16S rRNA sequencing. Thereafter, EPS was extracted using chemical (formaldehyde/NaOH) and physical (ultrasonification) methods followed by physicochemical characterisation of carbohydrate, DNA, and protein contents using chemical assays and spectroscopy (FTIR- Fourier transformed infrared and 3DEEM- three-dimensional excitation-emission matrix fluorescence spectroscopy). EPS treated with formaldehyde/NaOH showed better recovery of macromolecules than ultrasonification. The results of the present study showed that carbohydrates were more abundant than proteins, with carbohydrate and protein concentrations of 8.00 mg/ml and 0.22 mg/ml using chemical method in contrast to 5.00 mg/ml and 0.77 mg/ml using physical method, respectively. The FTIR spectroscopy results revealed that the extracted EPS contained hydroxyl, amide, acyl, and carboxyl groups that corresponded to the aforementioned chemical analysis results, thus asserting the presence of carbohydrates, DNA, polysaccharides, and proteins in the EPS. These findings suggest that identified functional groups of EPS form surface charges, which serve as the binding sites for suspended particles, thus possibly mediating adsorption of divalent cations and heavy metals. Using the extracted EPS in the development of a cost-effective biosorption solution for industrial wastewater treatment is attainable.

Keywords: biosorbent, exopolysaccharides, heavy metals, wastewater treatment

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295 Contextual Enablers and Behaviour Outputs for Action of Knowledge Workers

Authors: Juan-Gabriel Cegarra-Navarro, Alexeis Garcia-Perez, Denise Bedford

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This paper provides guidelines for what constitutes a knowledge worker. Many graduates from non-managerial domains adopt, at some point in their professional careers, management roles at different levels, ranging from team leaders through to executive leadership. This is particularly relevant for professionals from an engineering background. Moving from a technical to an executive-level requires an understanding of those behaviour management techniques that can motivate and support individuals and their performance. Further, the transition to management also demands a shift of contextual enablers from tangible to intangible resources, which allows individuals to create new capacities, competencies, and capabilities. In this dynamic process, the knowledge worker becomes that key individual who can help members of the management board to transform information into relevant knowledge. However, despite its relevance in shaping the future of the organization in its transition to the knowledge economy, the role of a knowledge worker has not yet been studied to an appropriate level in the current literature. In this study, the authors review both the contextual enablers and behaviour outputs related to the role of the knowledge worker and relate these to their ability to deal with everyday management issues such as knowledge heterogeneity, varying motivations, information overload, or outdated information. This study highlights that the aggregate of capacities, competences and capabilities (CCCs) can be defined as knowledge structures, the study proposes several contextual enablers and behaviour outputs that knowledge workers can use to work cooperatively, acquire, distribute and knowledge. Therefore, this study contributes to a better comprehension of how CCCs can be managed at different levels through their contextual enablers and behaviour outputs.

Keywords: knowledge workers, capabilities, capacities, competences, knowledge structures

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294 CT Medical Images Denoising Based on New Wavelet Thresholding Compared with Curvelet and Contourlet

Authors: Amir Moslemi, Amir movafeghi, Shahab Moradi

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One of the most important challenging factors in medical images is nominated as noise.Image denoising refers to the improvement of a digital medical image that has been infected by Additive White Gaussian Noise (AWGN). The digital medical image or video can be affected by different types of noises. They are impulse noise, Poisson noise and AWGN. Computed tomography (CT) images are subjected to low quality due to the noise. The quality of CT images is dependent on the absorbed dose to patients directly in such a way that increase in absorbed radiation, consequently absorbed dose to patients (ADP), enhances the CT images quality. In this manner, noise reduction techniques on the purpose of images quality enhancement exposing no excess radiation to patients is one the challenging problems for CT images processing. In this work, noise reduction in CT images was performed using two different directional 2 dimensional (2D) transformations; i.e., Curvelet and Contourlet and Discrete wavelet transform(DWT) thresholding methods of BayesShrink and AdaptShrink, compared to each other and we proposed a new threshold in wavelet domain for not only noise reduction but also edge retaining, consequently the proposed method retains the modified coefficients significantly that result in good visual quality. Data evaluations were accomplished by using two criterions; namely, peak signal to noise ratio (PSNR) and Structure similarity (Ssim).

Keywords: computed tomography (CT), noise reduction, curve-let, contour-let, signal to noise peak-peak ratio (PSNR), structure similarity (Ssim), absorbed dose to patient (ADP)

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293 The Evaluation of Gravity Anomalies Based on Global Models by Land Gravity Data

Authors: M. Yilmaz, I. Yilmaz, M. Uysal

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The Earth system generates different phenomena that are observable at the surface of the Earth such as mass deformations and displacements leading to plate tectonics, earthquakes, and volcanism. The dynamic processes associated with the interior, surface, and atmosphere of the Earth affect the three pillars of geodesy: shape of the Earth, its gravity field, and its rotation. Geodesy establishes a characteristic structure in order to define, monitor, and predict of the whole Earth system. The traditional and new instruments, observables, and techniques in geodesy are related to the gravity field. Therefore, the geodesy monitors the gravity field and its temporal variability in order to transform the geodetic observations made on the physical surface of the Earth into the geometrical surface in which positions are mathematically defined. In this paper, the main components of the gravity field modeling, (Free-air and Bouguer) gravity anomalies are calculated via recent global models (EGM2008, EIGEN6C4, and GECO) over a selected study area. The model-based gravity anomalies are compared with the corresponding terrestrial gravity data in terms of standard deviation (SD) and root mean square error (RMSE) for determining the best fit global model in the study area at a regional scale in Turkey. The least SD (13.63 mGal) and RMSE (15.71 mGal) were obtained by EGM2008 for the Free-air gravity anomaly residuals. For the Bouguer gravity anomaly residuals, EIGEN6C4 provides the least SD (8.05 mGal) and RMSE (8.12 mGal). The results indicated that EIGEN6C4 can be a useful tool for modeling the gravity field of the Earth over the study area.

Keywords: free-air gravity anomaly, Bouguer gravity anomaly, global model, land gravity

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292 Data Analytics in Energy Management

Authors: Sanjivrao Katakam, Thanumoorthi I., Antony Gerald, Ratan Kulkarni, Shaju Nair

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With increasing energy costs and its impact on the business, sustainability today has evolved from a social expectation to an economic imperative. Therefore, finding methods to reduce cost has become a critical directive for Industry leaders. Effective energy management is the only way to cut costs. However, Energy Management has been a challenge because it requires a change in old habits and legacy systems followed for decades. Today exorbitant levels of energy and operational data is being captured and stored by Industries, but they are unable to convert these structured and unstructured data sets into meaningful business intelligence. It must be noted that for quick decisions, organizations must learn to cope with large volumes of operational data in different formats. Energy analytics not only helps in extracting inferences from these data sets, but also is instrumental in transformation from old approaches of energy management to new. This in turn assists in effective decision making for implementation. It is the requirement of organizations to have an established corporate strategy for reducing operational costs through visibility and optimization of energy usage. Energy analytics play a key role in optimization of operations. The paper describes how today energy data analytics is extensively used in different scenarios like reducing operational costs, predicting energy demands, optimizing network efficiency, asset maintenance, improving customer insights and device data insights. The paper also highlights how analytics helps transform insights obtained from energy data into sustainable solutions. The paper utilizes data from an array of segments such as retail, transportation, and water sectors.

Keywords: energy analytics, energy management, operational data, business intelligence, optimization

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291 Liver and Liver Lesion Segmentation From Abdominal CT Scans

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The interpretation of medical images benefits from anatomical and physiological priors to optimize computer- aided diagnosis applications. Segmentation of liver and liver lesion is regarded as a major primary step in computer aided diagnosis of liver diseases. Precise liver segmentation in abdominal CT images is one of the most important steps for the computer-aided diagnosis of liver pathology. In this papers, a semi- automated method for medical image data is presented for the liver and liver lesion segmentation data using mathematical morphology. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological filters to extract the liver. The second step consists to detect the liver lesion. In this task; we proposed a new method developed for the semi-automatic segmentation of the liver and hepatic lesions. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to improve the quality of the original image and image gradient by applying the spatial filter followed by the morphological filters. The second step consists to calculate the internal and external markers of the liver and hepatic lesions. Thereafter we proceed to the liver and hepatic lesions segmentation by the watershed transform controlled by markers. The validation of the developed algorithm is done using several images. Obtained results show the good performances of our proposed algorithm

Keywords: anisotropic diffusion filter, CT images, hepatic lesion segmentation, Liver segmentation, morphological filter, the watershed algorithm

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290 The Impact of Regulatory Changes on the Development of Mobile Medical Apps

Authors: M. McHugh, D. Lillis

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Mobile applications are being used to perform a wide variety of tasks in day-to-day life, ranging from checking email to controlling your home heating. Application developers have recognized the potential to transform a smart device into a medical device, by using a mobile medical application i.e. a mobile phone or a tablet. When initially conceived these mobile medical applications performed basic functions e.g. BMI calculator, accessing reference material etc.; however, increasing complexity offers clinicians and patients a range of functionality. As this complexity and functionality increases, so too does the potential risk associated with using such an application. Examples include any applications that provide the ability to inflate and deflate blood pressure cuffs, as well as applications that use patient-specific parameters and calculate dosage or create a dosage plan for radiation therapy. If an unapproved mobile medical application is marketed by a medical device organization, then they face significant penalties such as receiving an FDA warning letter to cease the prohibited activity, fines and possibility of facing a criminal conviction. Regulatory bodies have finalized guidance intended for mobile application developers to establish if their applications are subject to regulatory scrutiny. However, regulatory controls appear contradictory with the approaches taken by mobile application developers who generally work with short development cycles and very little documentation and as such, there is the potential to stifle further improvements due to these regulations. The research presented as part of this paper details how by adopting development techniques, such as agile software development, mobile medical application developers can meet regulatory requirements whilst still fostering innovation.

Keywords: agile, applications, FDA, medical, mobile, regulations, software engineering, standards

Procedia PDF Downloads 337
289 Water-Repellent Coating Based on Thermoplastic Polyurethane, Silica Nanoparticles and Graphene Nanoplatelets

Authors: S. Naderizadeh, A. Athanassiou, I. S. Bayer

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This work describes a layer-by-layer spraying method to produce a non-wetting coating, based on thermoplastic polyurethane (TPU) and silica nanoparticles (Si-NPs). The main purpose of this work was to transform a hydrophilic polymer to superhydrophobic coating. The contact angle of pure TPU was measured about 77˚ ± 2, and water droplets did not roll away upon tilting even at 90°. But after applying a layer of Si-NPs on top of this, not only the contact angle increased to 165˚ ± 2, but also water droplets can roll away even below 5˚ tilting. The most important restriction in this study was the weak interfacial adhesion between polymer and nanoparticles, which had a bad effect on durability of the coatings. To overcome this problem, we used a very thin layer of graphene nanoplatelets (GNPs) as an interlayer between TPU and Si-NPs layers, followed by thermal treatment at 150˚C. The sample’s morphology and topography were characterized by scanning electron microscopy (SEM), EDX analysis and atomic force microscopy (AFM). It was observed that Si-NPs embedded into the polymer phase in the presence of GNPs layer. It is probably because of the high surface area and considerable thermal conductivity of the graphene platelets. The contact angle value for the sample containing graphene decreased a little bit respected to the coating without graphene and reached to 156.4˚ ± 2, due to the depletion of the surface roughness. The durability of the coatings against abrasion was evaluated by Taber® abrasion test, and it was observed that superhydrophobicity of the coatings remains for a longer time, in the presence of GNPs layer. Due to the simple fabrication method and good durability of the coating, this coating can be used as a durable superhydrophobic coating for metals and can be produced in large scale.

Keywords: graphene, silica nanoparticles, superhydrophobicity, thermoplastic polyurethane

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288 Exploring the Cross-Cultural Practice of Transnational Community in Taiwan

Authors: Ya-Hsuan Wang

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This project of intercultural education aimed to explore pluricultural people’s interpretation and evaluation of the transnational community in Taiwan. Based on transnationalism and transculturalism, this study concerns the human right issues for immigrants and pluricultural people. Research participants as immigrants in Taiwan were asked about their typical thinking styles in the transnational community, their cultural integration in terms of transnational behaviors, and their collective memory of the transnational community. Interview questions included what key factors were involved in their identity negotiation, what roles the transnational community and collective memory would be for their identity negotiation and what were the positive or negative aspects impacting cross-border identity. Based on the experiences of pluricultural people and transnational communities, this project expected to enhance the depth and width of developing transcultural knowledge in textbook reform on History in K-12 schools. It is to transform cross-border identity into knowledge embedded with local culture in response to globalization and localization. The purpose of this paper is to portrait the cross-cultural practice of transnational community for Taiwan’s immigrants. It is to report their external socio-cultural expectation of ethnic economics, to understand their internal life course of national identity, and to clarify transnational community in relation to their cross-border identity. In conclusion, the cross-cultural practice of transnational community combined the external contexts such as ethnic economic interaction among transnational communities, social report and ethnic industry, and the internal contexts such as ethnic identity, language use, and collective memory in ethnic history.

Keywords: cross-cultural practice, immigrants, pluricultural people, transnational community

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287 Performance Evaluation and Comparison between the Empirical Mode Decomposition, Wavelet Analysis, and Singular Spectrum Analysis Applied to the Time Series Analysis in Atmospheric Science

Authors: Olivier Delage, Hassan Bencherif, Alain Bourdier

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Signal decomposition approaches represent an important step in time series analysis, providing useful knowledge and insight into the data and underlying dynamics characteristics while also facilitating tasks such as noise removal and feature extraction. As most of observational time series are nonlinear and nonstationary, resulting of several physical processes interaction at different time scales, experimental time series have fluctuations at all time scales and requires the development of specific signal decomposition techniques. Most commonly used techniques are data driven, enabling to obtain well-behaved signal components without making any prior-assumptions on input data. Among the most popular time series decomposition techniques, most cited in the literature, are the empirical mode decomposition and its variants, the empirical wavelet transform and singular spectrum analysis. With increasing popularity and utility of these methods in wide ranging applications, it is imperative to gain a good understanding and insight into the operation of these algorithms. In this work, we describe all of the techniques mentioned above as well as their ability to denoise signals, to capture trends, to identify components corresponding to the physical processes involved in the evolution of the observed system and deduce the dimensionality of the underlying dynamics. Results obtained with all of these methods on experimental total ozone columns and rainfall time series will be discussed and compared

Keywords: denoising, empirical mode decomposition, singular spectrum analysis, time series, underlying dynamics, wavelet analysis

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286 Effects of Spectrotemporal Modulation of Music Profiles on Coherence of Cardiovascular Rhythms

Authors: I-Hui Hsieh, Yu-Hsuan Hu

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The powerful effect of music is often associated with changes in physiological responses such as heart rate and respiration. Previous studies demonstrate that Mayer waves of blood pressure, the spontaneous rhythm occurring at 0.1 Hz, corresponds to a progressive crescendo of the musical phrase. However, music contain dynamic changes in temporal and spectral features. As such, it remains unclear which aspects of musical structures optimally affect synchronization of cardiovascular rhythms. This study investigates the independent contribution of spectral pattern, temporal pattern, and dissonance level on synchronization of cardiovascular rhythms. The regularity of acoustical patterns occurring at a periodic rhythm of 0.1 Hz is hypothesized to elicit the strongest coherence of cardiovascular rhythms. Music excerpts taken from twelve pieces of Western classical repertoire were modulated to contain varying degrees of pattern regularity of the acoustic envelope structure. Three levels of dissonance were manipulated by varying the harmonic structure of the accompanying chords. Electrocardiogram and photoplethysmography signals were recorded for 5 minutes of baseline and simultaneously while participants listen to music excerpts randomly presented over headphones in a sitting position. Participants were asked to indicate the pleasantness of each music excerpt by adjusting via a slider presented on screen. Analysis of the Fourier spectral power of blood pressure around 0.1 Hz showed a significant difference between music excerpts characterized by spectral and temporal pattern regularity compared to the same content in random pattern. Phase coherence between heart rate and blood pressure increased significantly during listening to spectrally-regular phrases compared to its matched control phrases. The degree of dissonance of the accompanying chord sequence correlated with level of coherence between heart rate and blood pressure. Results suggest that low-level auditory features of music can entrain coherence of autonomic physiological variables. These findings have potential implications for using music as a clinical and therapeutic intervention for regulating cardiovascular functions.

Keywords: cardiovascular rhythms, coherence, dissonance, pattern regularity

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285 Does Pakistan Stock Exchange Offer Diversification Benefits to Regional and International Investors: A Time-Frequency (Wavelets) Analysis

Authors: Syed Jawad Hussain Shahzad, Muhammad Zakaria, Mobeen Ur Rehman, Saniya Khaild

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This study examines the co-movement between the Pakistan, Indian, S&P 500 and Nikkei 225 stock markets using weekly data from 1998 to 2013. The time-frequency relationship between the selected stock markets is conducted by using measures of continuous wavelet power spectrum, cross-wavelet transform and cross (squared) wavelet coherency. The empirical evidence suggests strong dependence between Pakistan and Indian stock markets. The co-movement of Pakistani index with U.S and Japanese, the developed markets, varies over time and frequency where the long-run relationship is dominant. The results of cross wavelet and wavelet coherence analysis indicate moderate covariance and correlation between stock indexes and the markets are in phase (i.e. cyclical in nature) over varying durations. Pakistan stock market was lagging during the entire period in relation to Indian stock market, corresponding to the 8~32 and then 64~256 weeks scale. Similar findings are evident for S&P 500 and Nikkei 225 indexes, however, the relationship occurs during the later period of study. All three wavelet indicators suggest strong evidence of higher co-movement during 2008-09 global financial crises. The empirical analysis reveals a strong evidence that the portfolio diversification benefits vary across frequencies and time. This analysis is unique and have several practical implications for regional and international investors while assigning the optimal weightage of different assets in portfolio formulation.

Keywords: co-movement, Pakistan stock exchange, S&P 500, Nikkei 225, wavelet analysis

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284 Indian Emigration to Gulf Countries: Opportunities and Challenges

Authors: Sudhaveni Naresh

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International migration is an important subject and gaining more significance andinterest among scholars in recent years. It is defined as crossing of the boundaries of political or administrative units for a certain minimum period for reasons such as education, employment, etc.International migration is not new for India because it has a long history with the Gulf region since ancient period. India is also one of the largest migrant-sending countries after China in the world. Migration towards the Gulf region became more prominent during early 1970s due to oil boom which led to rapid increase in the demand for foreign labour. Of 25 million Indian emigrants are living across the world, about six million Indian emigrants working in the Gulf. Most of these migrants were either unskilled or semi-skilled. Both the pull and push factors behind labour emigrate to Gulf countries. India is world’s leading receiver of remittances and the flow of remittances to India has been increasing steadily since the 1970s. In 2011-12, it was about 4 percent of GDP.Emigrants play a significant role in the economic development and growth of the country via the remittances and knowledge and skill transfer. Scholars see remittances as vital tool in the development for origin country. This paper examines the recent trend and pattern of migration from India to Gulf countries and explores impact of remittances on emigrants’ families at home country. It also highlights opportunities, challenges and the need for strengthening multilateral cooperation to transform migration into an efficient, orderly and humane process.The study propose to undertake a primary survey for this purpose. Both quantitative and qualitative research methods will be used to study the above issues.

Keywords: development, international migration, remittances, unskilled labour

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283 Virtual Reality as a Method in Transformative Learning: A Strategy to Reduce Implicit Bias

Authors: Cory A. Logston

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It is imperative researchers continue to explore every transformative strategy to increase empathy and awareness of racial bias. Racism is a social and political concept that uses stereotypical ideology to highlight racial inequities. Everyone has biases they may not be aware of toward disparate out-groups. There is some form of racism in every profession; doctors, lawyers, and teachers are not immune. There have been numerous successful and unsuccessful strategies to motivate and transform an individual’s unconscious biased attitudes. One method designed to induce a transformative experience and identify implicit bias is virtual reality (VR). VR is a technology designed to transport the user to a three-dimensional environment. In a virtual reality simulation, the viewer is immersed in a realistic interactive video taking on the perspective of a Black man. The viewer as the character experiences discrimination in various life circumstances growing up as a child into adulthood. For instance, the prejudice felt in school, as an adolescent encountering the police and false accusations in the workplace. Current research suggests that an immersive VR simulation can enhance self-awareness and become a transformative learning experience. This study uses virtual reality immersion and transformative learning theory to create empathy and identify any unintentional racial bias. Participants, White teachers, will experience a VR immersion to create awareness and identify implicit biases regarding Black students. The desired outcome provides a springboard to reconceptualize their own implicit bias. Virtual reality is gaining traction in the research world and promises to be an effective tool in the transformative learning process.

Keywords: empathy, implicit bias, transformative learning, virtual reality

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282 An Analytical Formulation of Pure Shear Boundary Condition for Assessing the Response of Some Typical Sites in Mumbai

Authors: Raj Banerjee, Aniruddha Sengupta

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An earthquake event, associated with a typical fault rupture, initiates at the source, propagates through a rock or soil medium and finally daylights at a surface which might be a populous city. The detrimental effects of an earthquake are often quantified in terms of the responses of superstructures resting on the soil. Hence, there is a need for the estimation of amplification of the bedrock motions due to the influence of local site conditions. In the present study, field borehole log data of Mangalwadi and Walkeswar sites in Mumbai city are considered. The data consists of variation of SPT N-value with the depth of soil. A correlation between shear wave velocity (Vₛ) and SPT N value for various soil profiles of Mumbai city has been developed using various existing correlations which is used further for site response analysis. MATLAB program is developed for studying the ground response analysis by performing two dimensional linear and equivalent linear analysis for some of the typical Mumbai soil sites using pure shear (Multi Point Constraint) boundary condition. The model is validated in linear elastic and equivalent linear domain using the popular commercial program, DEEPSOIL. Three actual earthquake motions are selected based on their frequency contents and durations and scaled to a PGA of 0.16g for the present ground response analyses. The results are presented in terms of peak acceleration time history with depth, peak shear strain time history with depth, Fourier amplitude versus frequency, response spectrum at the surface etc. The peak ground acceleration amplification factors are found to be about 2.374, 3.239 and 2.4245 for Mangalwadi site and 3.42, 3.39, 3.83 for Walkeswar site using 1979 Imperial Valley Earthquake, 1989 Loma Gilroy Earthquake and 1987 Whitter Narrows Earthquake, respectively. In the absence of any site-specific response spectrum for the chosen sites in Mumbai, the generated spectrum at the surface may be utilized for the design of any superstructure at these locations.

Keywords: deepsoil, ground response analysis, multi point constraint, response spectrum

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281 Life Prediction Method of Lithium-Ion Battery Based on Grey Support Vector Machines

Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines.For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

Procedia PDF Downloads 431