Search results for: CSLBP features

Authors: Onder Yakut, Oguzhan Timus, Emine Dogru Bolat

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Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.

Keywords: arrhythmic beat detection, ECG, HRV, kNN classifier

Procedia PDF Downloads 331

Authors: Mariana P. Medeiros, Amanda P. Carvallo, Augusta Isaac, Milos Janecek, Peter Minarik, Mayerling Martinez Celis, Roberto. R. Figueiredo

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The effect of high pressure torsion processing on mechanical properties and corrosion behavior of pure magnesium and Mg-Zn, Mg-Zn-Ca, Mg-Li-Y, and Mg-Y-RE alloys is investigated. Micro-tomography and SEM characterization are used to estimate corrosion rate and evaluate non-uniform corrosion features. The results show the severe plastic deformation processing improves the strength of all magnesium alloys, but deformation localization can take place in the Mg-Zn-Ca and Mg-Y-RE alloys. The occurrence of deformation localization is associated with low strain rate sensitivity in these alloys and with severe corrosion localization. Pure magnesium and Mg-Zn and Mg-Li-Y alloys display good corrosion resistance with low corrosion rate and maintained integrity after 28 days of immersion in Hank`s solution.

Keywords: magnesium alloys, severe plastic deformation, corrosion, biodegradable alloys

Procedia PDF Downloads 82

Authors: Fatma Susilawati Mohamad, Azizah Abdul Manaf, Fadhillah Ahmad, Zarina Mohamad, Wan Suryani Wan Awang

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A simple and robust multi-class linear classifier is proposed and implemented. For a pair of classes of the linear boundary, a collection of segments of hyper planes created as perpendicular bisectors of line segments linking centroids of the classes or part of classes. Nearest Neighbor and Linear Discriminant Analysis are compared in the experiments to see the performances of each classifier in discriminating ripeness of oil palm. This paper proposes a multi-class linear classifier using Linear Discriminant Analysis (LDA) for image identification. Result proves that LDA is well capable in separating multi-class features for ripeness identification.

Keywords: multi-class, linear classifier, nearest neighbor, linear discriminant analysis

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Authors: Gaokai Liu

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Automatic defect detection for nanomaterial images is widely required in industrial scenarios. Deep learning approaches are considered as the most effective solutions for the great majority of image-based tasks. In this paper, an edge guidance network for defect segmentation is proposed. First, the encoder path with multiple convolution and downsampling operations is applied to the acquisition of shared features. Then two decoder paths both are connected to the last convolution layer of the encoder and supervised by the edge and segmentation labels, respectively, to guide the whole training process. Meanwhile, the edge and encoder outputs from the same stage are concatenated to the segmentation corresponding part to further tune the segmentation result. Finally, the effectiveness of the proposed method is verified via the experiments on open nanofibrous datasets.

Keywords: deep learning, defect detection, image segmentation, nanomaterials

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Authors: Arthur Thirion

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Auxetic geometries allow the generation of a negative Poisson ratio (NPR) in conventional materials. This behaviour allows materials to have certain improved mechanical properties, including impact resistance and altered synclastic behaviour. This means these structures have significant potential when it comes to applications as chronic wound dressings. To this end, 6 different "perforated sheet" structure types were 3D printed. These structures all had variations of key geometrical features included cell length and angle. These were tested in compression and tension to assess their Poisson ratio. Both a positive and negative Poisson ratio was generated by the structures depending on the loading. The a/b ratio followed by θ has been shown to impact the Poisson ratio significantly. There is still a significant discrepancy between modelled and observed behaviour.

Keywords: auxetic materials, 3D printing, negative Poisson's ratio, tunable Poisson's ratio

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Authors: Mengqi Zhu, Chang Nyung Kim

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This study numerically investigates three-dimensional liquid-metal (LM) magnetohydrodynamic (MHD) flows in a misaligned duct under a uniform magnetic field. The duct consists of two misaligned horizontal channels (one is inflow channel, the other is outflow channel) and one central vertical channel. Computational fluid dynamics simulations are performed to predict the behavior of the MHD flows, using commercial code CFX. In the current study, a case with Hartmann number 1000 is considered. The electromagnetic features of LM MHD flows are elucidated to examine the interdependency of the flow velocity, current density, electric potential, pressure drop and Lorentz force. The results show that pressure decreases linearly along the main flow direction.

Keywords: CFX, liquid-metal magnetohydrodynamic flows, misaligned duct, pressure drop

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Authors: Ivaylo A. Todorov, Peter S. Boyadzhiev

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A new distinctive species of Stepanovia Kostjukov (Hymenoptera: Eulophidae: Tetrastichinae) was reared in laboratory from mature galls of Diplolepis rosae (Linnaeus) (Cynipidae). The galls were collected from Rosa sp. bushes growing in Osogovo Mt. in Western Bulgaria. The new species is close to Stepanovia rosae Boyadzhiev & Todorov but differs in POL and OOL characteristics, width of antennae, forewings and ovipositor sheaths characteristics, different U-shaped pale stripe above clypeus and the length of the ventral plaque on male antenna. The taxonomically important morphological features are illustrated and compared with the rest species of the genus using Scanning electron microscopy and light reflection by compound microscopy. Images of male genitalia are also prepared.

Keywords: Eulophidae, Diplolepis rosae, galls, Stepanovia osogoviensis, Bulgaria

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Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

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Authors: Faisal Aburub, Wael Hadi

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Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.

Keywords: classification, data mining, evaluation measures, groundwater

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Authors: Trevor Toy, Josef Langerman

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Around a quarter of the world’s data is generated by financial with an estimated 708.5 billion global non-cash transactions reached between 2018 and. And with Open Banking still a rapidly developing concept within the financial industry, there is an opportunity to create a secure mechanism for connecting its stakeholders to openly, legitimately and consensually share the data required to enable it. Integration and data sharing of anonymised transactional data are still operated in silos and centralised between the large corporate entities in the ecosystem that have the resources to do so. Smaller fintechs generating data and businesses looking to consume data are largely excluded from the process. Therefore there is a growing demand for accessible transactional data for analytical purposes and also to support the rapid global adoption of Open Banking. The following research has provided a solution framework that aims to provide a secure decentralised marketplace for 1.) data providers to list their transactional data, 2.) data consumers to find and access that data, and 3.) data subjects (the individuals making the transactions that generate the data) to manage and sell the data that relates to themselves. The platform also provides an integrated system for downstream transactional-related data from merchants, enriching the data product available to build a comprehensive view of a data subject’s spending habits. A robust and sustainable data market can be developed by providing a more accessible mechanism for data producers to monetise their data investments and encouraging data subjects to share their data through the same financial incentives. At the centre of the platform is the market mechanism that connects the data providers and their data subjects to the data consumers. This core component of the platform is developed on a decentralised blockchain contract with a market layer that manages transaction, user, pricing, payment, tagging, contract, control, and lineage features that pertain to the user interactions on the platform. One of the platform’s key features is enabling the participation and management of personal data by the individuals from whom the data is being generated. This framework developed a proof-of-concept on the Etheruem blockchain base where an individual can securely manage access to their own personal data and that individual’s identifiable relationship to the card-based transaction data provided by financial institutions. This gives data consumers access to a complete view of transactional spending behaviour in correlation to key demographic information. This platform solution can ultimately support the growth, prosperity, and development of economies, businesses, communities, and individuals by providing accessible and relevant transactional data for big data analytics and open banking.

Keywords: big data markets, open banking, blockchain, personal data management

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Authors: Imran Ali

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General chemotherapy for cancer treatment has many side and toxic effects. A new approach of targeting nano anti-cancer drug is under development stage and only few drugs are available in the market today. The unique features of these drugs are targeted action on cancer cells only without any side effect. Sometimes, these are called magic drugs. The important molecules used for nano anti-cancer drugs are cisplatin, carboplatin, bleomycin, 5-fluorouracil, doxorubicin, dactinomycin, 6-mercaptopurine, paclitaxel, topotecan, vinblastin and etoposide etc. The most commonly used materials for preparing nano particles carriers are dendrimers, polymeric, liposomal, micelles inorganic, organic etc. The proposed lecture will comprise the-of-art of nano drugs in cancer chemo-therapy including preparation, types of drugs, mechanism, future perspectives etc.

Keywords: cancer, nano-anti-cancer drugs, chemo-therapy, mechanism of action, future perspectives

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Authors: Debjit Ray

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Horizontal gene transfer (HGT) and recombination leads to the emergence of bacterial antibiotic resistance and pathogenic traits. HGT events can be identified by comparing a large number of fully sequenced genomes across a species or genus, define the phylogenetic range of HGT, and find potential sources of new resistance genes. In-depth comparative phylogenomics can also identify subtle genome or plasmid structural changes or mutations associated with phenotypic changes. Comparative phylogenomics requires that accurately sequenced, complete and properly annotated genomes of the organism. Assembling closed genomes requires additional mate-pair reads or “long read” sequencing data to accompany short-read paired-end data. To bring down the cost and time required of producing assembled genomes and annotating genome features that inform drug resistance and pathogenicity, we are analyzing the performance for genome assembly of data from the Illumina NextSeq, which has faster throughput than the Illumina HiSeq (~1-2 days versus ~1 week), and shorter reads (150bp paired-end versus 300bp paired end) but higher capacity (150-400M reads per run versus ~5-15M) compared to the Illumina MiSeq. Bioinformatics improvements are also needed to make rapid, routine production of complete genomes a reality. Modern assemblers such as SPAdes 3.6.0 running on a standard Linux blade are capable in a few hours of converting mixes of reads from different library preps into high-quality assemblies with only a few gaps. Remaining breaks in scaffolds are generally due to repeats (e.g., rRNA genes) are addressed by our software for gap closure techniques, that avoid custom PCR or targeted sequencing. Our goal is to improve the understanding of emergence of pathogenesis using sequencing, comparative genomics, and machine learning analysis of ~1000 pathogen genomes. Machine learning algorithms will be used to digest the diverse features (change in virulence genes, recombination, horizontal gene transfer, patient diagnostics). Temporal data and evolutionary models can thus determine whether the origin of a particular isolate is likely to have been from the environment (could it have evolved from previous isolates). It can be useful for comparing differences in virulence along or across the tree. More intriguing, it can test whether there is a direction to virulence strength. This would open new avenues in the prediction of uncharacterized clinical bugs and multidrug resistance evolution and pathogen emergence.

Keywords: genomics, pathogens, genome assembly, superbugs

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Authors: Matheus Fernando Pereira, Varese Salvador Timoteo

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In this work, we have solved the two-dimensional advection-diffusion equation numerically for a spatially dependent solute dispersion along non-uniform flow with a pulse type source in order to make a systematic study on the influence of medium heterogeneity, initial flow velocity, and initial dispersion coefficient parameters on the solutions of the equation. The behavior of the solutions is then investigated as we change the three parameters independently. Our results show that even though the parameters represent different physical features of the system, the effect on their variation is very similar. We also observe that the effects caused by the parameters on the concentration depend on the distance from the source. Finally, our numerical results are in good agreement with the exact solutions for all values of the parameters we used in our analysis.

Keywords: advection-diffusion equation, dispersion, numerical methods, pulse-type source

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Authors: Jiaqi Yan, Yani Shi

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With the growing popularity of bitcoin transactions, criminals have exploited the bitcoin like cryptocurrencies, and cybercriminals such as money laundering have thrived. Unlike traditional currencies, the Internet-based virtual currencies can be used anonymously via the blockchain technology underpinning. In this paper, we analyze the double-edged sword features of blockchain technology in the context of money laundering. In particular, the traceability feature of blockchain-based system facilitates a level of governance, while the decentralization feature of blockchain-based system may bring governing difficulties. Based on the analysis, we propose guidelines for policy makers in governing blockchain-based cryptocurrency systems.

Keywords: cryptocurrency, money laundering, blockchain, decentralization, traceability

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Authors: Khaled Mohammed

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This paper presents novel face recognition and identification approaches for the real-time attendance management problem in large companies/factories and government institutions. The proposed uses the Minimum Ratio (MR) approach for employee identification. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the Previous approaches at a rate between 2% to 5%. In addition, it decreased the time two times if compared with the Previous techniques, such as Extreme Learning Machine (ELM) & Multi-Scale Structural Similarity index (MS-SSIM). Finally, it achieved an accuracy of 99%.

Keywords: attendance management system, face detection and recognition, live face recognition, minimum ratio

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Authors: Fatma Abdedayem

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The most effective and efficient methods in image categorization are almost based on bag-of-words (BOW) which presents image by a histogram of occurrence of visual words. In this paper, we propose a novel extension to this method. Firstly, we extract features in multi-scales by applying a color local descriptor named opponent-SIFT. Secondly, in order to represent image we use Spatial Pyramid Representation (SPR) and an extension to the BOW method which based on weighting visual words. Typically, the visual words are weighted during histogram assignment by computing the ratio of their occurrences in the image to the occurrences in the background. Finally, according to classical BOW retrieval framework, only a few words of the vocabulary is useful for image representation. Therefore, we select the useful weighted visual words that respect the threshold value. Experimentally, the algorithm is tested by using different image classes of PASCAL VOC 2007 and is compared against the classical bag-of-visual-words algorithm.

Keywords: BOW, useful visual words, weighted visual words, bag of visual words

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Authors: Mohammed F. Haddad, Mohammad A. Albenayyan

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Realistically, 3-D printing as a technology has not yet reached the required maturity level to handle construction housing projects for citizens on a country scale. However, potentially, it has all of the required elements for addressing this issue. There are two main high-level elements of this technology that need to be capitalized on in order for the technology to reach its full potential, technical and logistical. This paper aims to cover how 3-D printing can be a viable technical solution for housing projects and describe the impact of 3-D printing technical features on the logistical aspects of completing a housing project. Additionally, a perspective about 3-D printing in Saudi Arabia will be presented in order to give the reader an idea of where the kingdom stands in the deployment of this technology. Finally, a glimpse will be given regarding the potential utilization of this technology for space applications.

Keywords: large-scale 3-D printing, additive manufacturing, D- shape, contour crafting

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Authors: Shashwat Gangwal

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This paper analyses the effect of adding Bitcoin, to the portfolio (stocks, bonds, Baltic index, MXEF, gold, real estate and crude oil) of an international investor by using daily data available from 2^nd of July, 2010 to 2^{nd of} August, 2016. We conclude that adding Bitcoin to portfolio, over the course of the considered period, always yielded a higher Sharpe ratio. This means that Bitcoin’s returns offset its high volatility. This paper, recognizing the fact that Bitcoin is a relatively new asset class, gives the readers a basic idea about the working of the virtual currency, the increasing number developments in the financial industry revolving around it, its unique features and the detailed look into its continuously growing acceptance across different fronts (Banks, Merchants and Countries) globally. We also construct optimal portfolios to reflect the highly lucrative and largely unexplored opportunities associated with investment in Bitcoin.

Keywords: bitcoin, financial instruments, portfolio management, risk adjusted return

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Authors: Ewelina Nowak, Anna Wisla-Swider

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Deoxyribonucleic acid (DNA) is a biomolecule which exhibits an electro-optic properties. These features are related with structure of double-stranded helix. Modification of DNA with ionic liquids allows intensify these properties. The aim of our study was synthesis of ionic liquids that are used the formation of DNA-surfactant complexes in order to obtain new materials with potential application for nonlinear optics. Complexes were achieved through the ion exchange reactions of carbazole-based and imidazole-based ionic liquids with H+ ions from salmon DNA. To examination the properties of obtained complexes DNA-ionic liquids there were investigated using circular dichroism (CD), UV-Vis spectra and infrared spectroscopy (IR). Additionally, the resulting DNA-surfactant complexes were characterized in terms of solubility in common organic solvents and water.

Keywords: deoxyribonucleic acid, biomolecule, carbazole, imidazole, ionic liquids, ion exchange reactions

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Authors: Yogesh S. Patel

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Novel polyimides were synthesized by Diels–Alder polymerization. Bisfuran was reacted with a couple of bismaleimides containing diglycidyl ether of bisphenol-A and F (epoxy) segment to obtain Diels–Alder polyadducts. Polyadducts were then aromatized and imidized (i.e. cyclized) through carboxylic and amide groups to afford polyimides. Synthesized polyadducts and polyimides were characterized by elemental analysis, spectral features, the number of average molecular weight (Mn) and thermal analysis. The ‘in situ’ glass fiber reinforced composites were prepared and characterized by mechanical, electrical, and chemical properties. These properties were compared with the other reported polyimides. All the composites showed good mechanical and electrical properties and good resistance to organic solvents and mineral acids.

Keywords: Diels-Alder reaction, bisfuran, bismaleimides, polyimide

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Authors: Shofiayuningtyas Luftiani

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Some private schools in Indonesia started integrating the online program Gizmos in the teaching-learning process. Gizmos was developed to supplement the existing curriculum by integrating it into the instructional programs. The program has some features using an inquiry-based simulation, in which students conduct exploration by using a worksheet while teachers use the teacher guidelines to direct and assess students’ performance In this study, the discussion about Gizmos highlights its features as the assessment media of mathematics learning for secondary school students. The discussion is based on the case study and literature review from the Indonesian context. The purpose of applying Gizmos as an assessment media refers to the diagnostic assessment. As a part of the diagnostic assessment, the teachers review the student exploration sheet, analyze particularly in the students’ difficulties and consider findings in planning future learning process. This assessment becomes important since the teacher needs the data about students’ persistent weaknesses. Additionally, this program also helps to build student’ understanding by its interactive simulation. Currently, the assessment over-emphasizes the students’ answers in the worksheet based on the provided answer keys while students perform their skill in translating the question, doing the simulation and answering the question. Whereas, the assessment should involve the multiple perspectives and sources of students’ performance since teacher should adjust the instructional programs with the complexity of students’ learning needs and styles. Consequently, the approach to improving the assessment components is selected to challenge the current assessment. The purpose of this challenge is to involve not only the cognitive diagnosis but also the analysis of skills and error. Concerning the selected setting for this diagnostic assessment that develops the combination of cognitive diagnosis, skills analysis and error analysis, the teachers should create an assessment rubric. The rubric plays the important role as the guide to provide a set of criteria for the assessment. Without the precise rubric, the teacher potentially ineffectively documents and follows up the data about students at risk of failure. Furthermore, the teachers who employ the program of Gizmos as the diagnostic assessment might encounter some obstacles. Based on the condition of assessment in the selected setting, the obstacles involve the time constrain, the reluctance of higher teaching burden and the students’ behavior. Consequently, the teacher who chooses the Gizmos with those approaches has to plan, implement and evaluate the assessment. The main point of this assessment is not in the result of students’ worksheet. However, the diagnostic assessment has the two-stage process; the process to prompt and effectively follow-up both individual weaknesses and those of the learning process. Ultimately, the discussion of Gizmos as the media of the diagnostic assessment refers to the effort to improve the mathematical learning process.

Keywords: diagnostic assessment, error analysis, Gizmos online program, skills analysis

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Authors: B.-Y.-S. Lau, Y.-C.-T. Jonathan, M.-S. Alias

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Heritage trees are natural large, individual trees with exceptionally value due to association with age or event or distinguished people. In Malaysia, there is an abundance of tropical heritage trees throughout the country. It is essential to set up a repository of heritage trees to prevent valuable trees from being cut down. In this cross domain study, a web-based online expert system namely the Heritage Tree Expert Assessment and Classification (HTEAC) is developed and deployed for public to nominate potential heritage trees. Based on the nomination, tree care experts or arborists would evaluate and verify the nominated trees as heritage trees. The expert system automatically rates the approved heritage trees according to pre-defined grades via Delphi technique. Features and usability test of the expert system are presented. Preliminary result is promising for the system to be used as a full scale public system.

Keywords: arboriculture, Delphi, expert system, heritage tree, urban forestry

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Authors: Yanheng Zhang, Lu Feng, Yilan Kang, Donghui Fu, Qian Zhang, Qiu Li, Wei Qiu

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Diamond-reinforced Ni matrix composite has been widely applied in engineering for coating large-area structural parts owing to its high hardness, good wear resistance and corrosion resistance compared with those features of pure nickel. The mechanical properties of Ni-diamond composite coating can be promoted by the high incorporation and uniform distribution of diamond particles in the nickel matrix, while the distribution features of particles are affected by electrodeposition process parameters, especially the additives in the plating bath. Glycine has been utilized as an organic additive during the preparation of pure nickel coating, which can effectively increase the coating hardness. Nevertheless, to author’s best knowledge, no research about the effects of glycine on the Ni-diamond co-deposition has been reported. In this work, the diamond reinforced Ni nanocomposite coatings were fabricated by a co-electrodeposition technique from a modified Watt’s type bath in the presence of glycine. After preparation, the SEM morphology of the composite coatings was observed combined with energy dispersive X-ray spectrometer, and the diamond incorporation was analyzed. The surface morphology and roughness were obtained by a three-dimensional profile instrument. 3D-Debye rings formed by XRD were analyzed to characterize the nickel grain size and orientation in the coatings. The average coating thickness was measured by a digital micrometer to deduce the deposition rate. The microhardness was tested by automatic microhardness tester. The friction coefficient and wear volume were measured by reciprocating wear tester to characterize the coating wear resistance and cutting performance. The experimental results confirmed that the presence of glycine effectively improved the surface morphology and roughness of the composite coatings. By optimizing the glycine concentration, the incorporation of diamond particles was increased, while the nickel grain size decreased with increasing glycine. The hardness of the composite coatings was increased as the glycine concentration increased. The friction and wear properties were evaluated as the glycine concentration was optimized, showing a decrease in the wear volume. The wear resistance of the composite coatings increased as the glycine content was increased to an optimum value, beyond which the wear resistance decreased. Glycine complexation contributed to the nickel grain refinement and improved the diamond dispersion in the coatings, both of which made a positive contribution to the amount and uniformity of embedded diamond particles, thus enhancing the microhardness, reducing the friction coefficient, and hence increasing the wear resistance of the composite coatings. Therefore, additive glycine can be used during the co-deposition process to improve the mechanical properties of protective coatings.

Keywords: co-electrodeposition, glycine, mechanical properties, Ni-diamond nanocomposite coatings

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Authors: Shabir Ahmad Sofi, Shubham Aggarwal, Sanyam Singhal, Roohie Naaz

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Biometric recognition refers to an automatic recognition of individuals based on a feature vector(s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. These features are used to provide an authentication for computer based security systems. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on 'who she/he is' rather than 'what she/he has' (card, token, key) or 'what she/he knows' (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal and their advantages and disadvantages, will be presented.

Keywords: biometric, DNA, fingerprint, ear, face, retina scan, gait, iris, voice recognition, unimodal biometric, multimodal biometric

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Authors: Yu-Shan Hsu

Abstract:

This paper studies a two-sector growth model with a technology of social constant returns and with a utility that features either a zero or a positive income effect on the demand for leisure. The purpose is to investigate how the existence of aggregate instability or equilibrium indeterminacy depends on both the intensity of the income effect on the demand for leisure and the value of the labor supply elasticity. The main finding is that when there is a factor intensity reversal between the private perspective and the social perspective, indeterminacy arises even if the utility has a positive income effect on leisure demand. Moreover, we find that a smaller value of the labor supply elasticity increases the range of the income effect on leisure demand and thus increases the possibility of equilibrium indeterminacy. JEL classification: E3; O41

Keywords: indeterminacy, non-separable preferences, income effect, labor supply elasticity

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Authors: J. Klofac, P. Bazant, I. Kuritka

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This work is focused on the preparation of polymeric blend composed of polyamide (PA) and polyvinyl alcohol (PVA) with the intention to explore its basic characteristics important for potential use in medicine, especially for drug delivery systems. PA brings brilliant mechanical properties to the blend while PVA is inevitable due to its water solubility. Blend with different PA/PVA ratios were prepared and the release study of PVA into the water was carried out in a time interval 0-48 hours via the gravimetric method. The weight decrease is caused by the leaching of PVA domains what can be also followed by the optical and scanning electron microscopy. In addition, the thermal properties and the miscibility of blend components were evaluated by the differential scanning calorimeter. On the bases of performed experiments, it was found that the kinetics, continuity development and micro structure features of PA/PVA blends is strongly dependent on the blend composition and miscibility of its components.

Keywords: releas study, polyvinyl alcohol, polyamide morphology, polymeric blend

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Authors: Grishma D. Solanki, Karshan Kandoriya

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In modern era of information age, digitalization has revolutionized like never before. Powerful computers, advanced photo editing software packages and high resolution capturing devices have made manipulation of digital images incredibly easy. As per as image forensics concerns, one of the most actively researched area are detection of copy move forgeries. Higher computational complexity is one of the major component of existing techniques to detect such tampering. Moreover, copy move forgery is usually performed in three steps. First, copying of a region in an image then pasting the same one in the same respective image and finally doing some post-processing like rotation, scaling, shift, noise, etc. Consequently, pseudo Zernike moment is used as a features extraction method for matching image blocks and as a primary factor on which performance of detection algorithms depends.

Keywords: copy-move image forgery, digital forensics, image forensics, image forgery

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Authors: Vladislav A. Nazukin, Valery G. Avgustinovich, Vakhtang V. Tsatiashvili

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The most important part of modern lean low NOx combustors is a premixer where swirlers are often used for intensification of mixing processes and further formation of required flow pattern in combustor liner. Swirling flow leads to formation of complex eddy structures causing flow perturbations. It is able to cause combustion instability. Therefore, at design phase, it is necessary to pay great attention to aerodynamics of premixers. Analysis based on unsteady CFD modeling of swirling flow in production combustor swirler showed presence of large number of different eddy structures that can be conditionally divided into three types relative to its location of origin and a propagation path. Further, features of each eddy type were subsequently defined. Comparison of calculated and experimental pressure fluctuations spectrums verified correctness of computations.

Keywords: DES simulation, swirler, vortical structures, combustion chamber

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Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

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Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

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Authors: Ng Liang Shen, Hau Yuan Wen

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Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.

Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS

Procedia PDF Downloads 346