Search results for: features comparison

Authors: Amna Khan, Zareena Kausar, Saad Malik

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Bio Mechatronics has extended applications in the field of rehabilitation. It has been contributing since World War II in improving the applicability of prosthesis and assistive devices in real life scenarios. In this paper, classification accuracies have been compared for two classifiers against five positions of elbow. Electromyography (EMG) signals analysis have been acquired directly from skeletal muscles of human forearm for each of the three defined positions and at modified extreme positions of elbow flexion and extension using 8 electrode Myo armband sensor. Features were extracted from filtered EMG signals for each position. Performance of two classifiers, support vector machine (SVM) and linear discriminant analysis (LDA) has been compared by analyzing the classification accuracies. SVM illustrated classification accuracies between 90-96%, in contrast to 84-87% depicted by LDA for five defined positions of elbow keeping the number of samples and selected feature the same for both SVM and LDA.

Keywords: classification accuracies, electromyography, linear discriminant analysis (LDA), Myo armband sensor, support vector machine (SVM)

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Authors: M. Pushparani, A. Sagaya

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Embedded systems have emerged as important elements in various domains with extensive applications in automotive, commercial, consumer, healthcare and transportation markets, as there is emphasis on intelligent devices. On the other hand, Business Intelligence (BI) has also been extensively used in a range of applications, especially in the agriculture domain which is the area of this research. The aim of this research is to create a framework for Embedded Weight Comparison Algorithm with Business Intelligence (EWCA-BI). The weight comparison algorithm will be embedded within the plantation management system and the weighbridge system. This algorithm will be used to estimate the weight at the site and will be compared with the actual weight at the plantation. The algorithm will be used to build the necessary alerts when there is a discrepancy in the weight, thus enabling better decision making. In the current practice, data are collected from various locations in various forms. It is a challenge to consolidate data to obtain timely and accurate information for effective decision making. Adding to this, the unstable network connection leads to difficulty in getting timely accurate information. To overcome the challenges embedding is done on a portable device that will have the embedded weight comparison algorithm to also assist in data capture and synchronize data at various locations overcoming the network short comings at collection points. The EWCA-BI will provide real-time information at any given point of time, thus enabling non-latent BI reports that will provide crucial information to enable efficient operational decision making. This research has a high potential in bringing embedded system into the agriculture industry. EWCA-BI will provide BI reports with accurate information with uncompromised data using an embedded system and provide alerts, therefore, enabling effective operation management decision-making at the site.

Keywords: embedded business intelligence, weight comparison algorithm, oil palm plantation, embedded systems

Procedia PDF Downloads 254

Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad

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Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.

Keywords: biometrics, euclidean classifier, features extraction, offline signature verification, voting-based classifier

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Authors: Attallah Bilal, Hendel Fatiha

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This paper proposes the bimodal biometrics system for identity verification iris and fingerprint, at matching score level architecture using weighted sum of score technique. The features are extracted from the pre processed images of iris and fingerprint. These features of a query image are compared with those of a database image to obtain matching scores. The individual scores generated after matching are passed to the fusion module. This module consists of three major steps i.e., normalization, generation of similarity score and fusion of weighted scores. The final score is then used to declare the person as genuine or an impostor. The system is tested on CASIA database and gives an overall accuracy of 91.04% with FAR of 2.58% and FRR of 8.34%.

Keywords: iris, fingerprint, sum rule, fusion

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Authors: N. Alias, W. Z. W. Muhammad, M. N. M. Ibrahim, M. Mohamed, H. F. S. Saipol, U. N. Z. Ariffin, N. A. Zakaria, M. S. Z. Suardi

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This paper presents the performance comparison of some computation software for solving the boundary element method (BEM). BEM formulation is the numerical technique and high potential for solving the advance mathematical modeling to predict the production of oil well in arbitrarily shaped based on multiple leases reservoir. The limitation of data validation for ensuring that a program meets the accuracy of the mathematical modeling is considered as the research motivation of this paper. Thus, based on this limitation, there are three steps involved to validate the accuracy of the oil production simulation process. In the first step, identify the mathematical modeling based on partial differential equation (PDE) with Poisson-elliptic type to perform the BEM discretization. In the second step, implement the simulation of the 2D BEM discretization using COMSOL Multiphysic and MATLAB programming languages. In the last step, analyze the numerical performance indicators for both programming languages by using the validation of Fortran programming. The performance comparisons of numerical analysis are investigated in terms of percentage error, comparison graph and 2D visualization of pressure on oil production of multiple leases reservoir. According to the performance comparison, the structured programming in Fortran programming is the alternative software for implementing the accurate numerical simulation of BEM. As a conclusion, high-level language for numerical computation and numerical performance evaluation are satisfied to prove that Fortran is well suited for capturing the visualization of the production of oil well in arbitrarily shaped.

Keywords: performance comparison, 2D visualization, COMSOL multiphysic, MATLAB, Fortran, modelling and simulation, boundary element method, reservoir pressure

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Authors: Priyadarsini Samal, Rajesh Singla

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Many mobile games come with the benefits of entertainment by introducing stress to the human brain. In recognizing this mental stress, the brain-computer interface (BCI) plays an important role. It has various neuroimaging approaches which help in analyzing the brain signals. Electroencephalogram (EEG) is the most commonly used method among them as it is non-invasive, portable, and economical. Here, this paper investigates the pattern in brain signals when introduced with mental stress. Two healthy volunteers played a game whose aim was to search hidden words from the grid, and the levels were chosen randomly. The EEG signals during gameplay were recorded to investigate the impacts of stress with the changing levels from easy to medium to hard. A total of 16 features of EEG were analyzed for this experiment which includes power band features with relative powers, event-related desynchronization, along statistical features. Support vector machine was used as the classifier, which resulted in an accuracy of 93.9% for three-level stress analysis; for two levels, the accuracy of 92% and 98% are achieved. In addition to that, another game that was similar in nature was played by the volunteers. A suitable regression model was designed for prediction where the feature sets of the first and second game were used for testing and training purposes, respectively, and an accuracy of 73% was found.

Keywords: brain computer interface, electroencephalogram, regression model, stress, word search

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Authors: Svetlana Strinyuk, Viacheslav Lanin

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Academic English has become lingua franca for international scientific community which stimulates universities to introduce English for Specific Purposes (EAP) courses into curriculum. Teaching L2 EAP students might be fulfilled with corpus technologies and digital stylistics. A special software developed to reach the manifold task of teaching, assessing and researching academic writing of L2 students on basis of digital stylistics and multidimensional analysis was created. A set of annotations (style markers) – grammar, lexical and syntactic features most significant of academic writing was built. Contrastive comparison of two corpora “model corpus”, subject domain limited papers published by competent writers in leading academic journals, and “students’ corpus”, subject domain limited papers written by last year students allows to receive data about the features of academic writing underused or overused by L2 EAP student. Both corpora are tagged with a special software created in GATE Developer. Style markers within the framework of research might be replaced depending on the relevance and validity of the result which is achieved from research corpora. Thus, selecting relevant (high frequency) style markers and excluding less relevant, i.e. less frequent annotations, high validity of the model is achieved. Software allows to compare the data received from processing model corpus to students’ corpus and get reports which can be used in teaching and assessment. The less deviation from the model corpus students demonstrates in their writing the higher is academic writing skill acquisition. The research showed that several style markers (hedging devices) were underused by L2 EAP students whereas lexical linking devices were used excessively. A special software implemented into teaching of EAP courses serves as a successful visual aid, makes assessment more valid; it is indicative of the degree of writing skill acquisition, and provides data for further research.

Keywords: corpus technologies in EAP teaching, multidimensional analysis, GATE Developer, corpus stylistics

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Authors: S. H. Borghei, E. Teymourian, M. Mobin, G. M. Komaki, S. Sheikh

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Imperialist competitive algorithm (ICA) is a recent meta-heuristic method that is inspired by the social evolutions for solving NP-Hard problems. The ICA is a population based algorithm which has achieved a great performance in comparison to other meta-heuristics. This study is about developing enhanced ICA approach to solve the cell formation problem (CFP) using sequence data. In addition to the conventional ICA, an enhanced version of ICA, namely EICA, applies local search techniques to add more intensification aptitude and embed the features of exploration and intensification more successfully. Suitable performance measures are used to compare the proposed algorithms with some other powerful solution approaches in the literature. In the same way, for checking the proficiency of algorithms, forty test problems are presented. Five benchmark problems have sequence data, and other ones are based on 0-1 matrices modified to sequence based problems. Computational results elucidate the efficiency of the EICA in solving CFP problems.

Keywords: cell formation problem, group technology, imperialist competitive algorithm, sequence data

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Authors: Mayar Almasri, Rosa Helmi, Rayana Enany

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This report describes the features of AutoCAD software released by Adobe. It explains how the program makes it easier for engineers and designers and reduces their time and effort spent using AutoCAD. Moreover, it highlights how AutoCAD works, how some of the commands used in it, such as Shortcut, make it easy to use, and features that make it accurate in measurements. The results of the report show that most users of this program are designers and engineers, but few people know about it and find it easy to use. They prefer to use it because it is easy to use, and the shortcut commands shorten a lot of time for them. The feature got a high rate and some suggestions for improving AutoCAD in Aperture, but it was a small percentage, and the highest percentage was that they didn't need to improve the program, and it was good.

Keywords: artificial intelligence, design, planning, commands, autodesk, dimensions

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Authors: Yili Liu, Honghao Ren, Mariko Kondo

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In the field of second language (L2) speech learning, it is well-known that that learner’s first language (L1) phonetic and phonological characteristics will be transferred into their L2 production and perception, which lead to foreign accent. For L1 Mandarin learners of Japanese, the confusion of /u/ and /o/ in /CjV/ sequences has been observed in their utterance frequently. L1 transfer is considered to be the cause of this issue, however, other factors which influence the identification of /Cju/ and /Cjo/ sequences still under investigation. This study investigates the perception of Japanese /Cju/ and /Cjo/ units by L1 Mandarin learners of Japanese. It further examined whether learners’ proficiency, syllable position, phonetic features of preceding consonants and background noise affect learners’ performance in perception. Fifty-two Mandarin-speaking learners of Japanese and nine native Japanese speakers were recruited to participate in an identification task. Learners were divided into beginner, intermediate and advanced level according to their Japanese proficiency. The average correct rate was used to evaluate learners’ perceptual performance. Furthermore, the comparison of the correct rate between learners’ groups and the control group was conducted as well to examine learners’ nativelikeness. Results showed that background noise tends to pose an adverse effect on distinguishing /u/ and /o/ in /CjV/ sequences. Secondly, Japanese proficiency has no influence on learners’ perceptual performance in the quiet and in background noise. Then all learners did not reach a native-like level without the distraction of noise. Beginner level learners performed less native-like, although higher level learners appeared to have achieved nativelikeness in the multi-talker babble noise. Finally, syllable position tends to affect distinguishing /Cju/ and /Cjo/ only under the noisy condition. Phonetic features of preceding consonants did not impact learners’ perception in any listening conditions. Findings in this study can give an insight into a further understanding of Japanese vowel acquisition by L1 Mandarin learners of Japanese. In addition, this study indicates that L1 transfer is not the only explanation for the confusion of /u/ and /o/ in /CjV/ sequences, factors such as listening condition and syllable position are also needed to take into consideration in future research. It also suggests the importance of perceiving speech in a noisy environment, which is close to the actual conversation required more attention to pedagogy.

Keywords: background noise, Chinese learners of Japanese, /Cju/ and /Cjo/ sequences, second language perception

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Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Nargiz Ismayilova

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In Kamal Abdulla's "The Adventure of Mysteries", the plot develops on two parallel lines. While reading the work, the future looks hazy on the background of the present and the past. It is impossible to predict the end of the work in particular. This can be considered the success of the author. The novel has reflected the features of postmodernism. The novel is characterized by a richness of intertwined plots, themes, meta- submission, device (fiction) typical of postmodern prose technique. The introduction and progress of the work takes the reader to the place, which is an unrecognizable unknown for him but at the same time, its native for him very well. Parts of the novel, divided into chapter techniques, force the reader to distinguish mystical repetitions from the artistic circulation of reality. This makes people think directly. Intertextual communication and the variety of fiction, intelligence, and informativeness determine the perspective of the exemplary reader. As is well known, “postmodern novels, which often use intertextual communication and superstructure techniques, focus on expression rather than on the subject, and benefit from history by combining fiction with historical facts, are able to attract attention with their extraordinary foreign fiction.

Keywords: Kamal Abdulla, postmodernism, parallelism, labyrinth, comparison, novel

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Authors: Djelloul Benatiallah

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Due to the current high consumption and recent industry growth, the depletion of fossil and natural energy supplies like oil, gas, and uranium is declining. Due to pollution and climate change, there needs to be a swift switch to renewable energy sources. Research on renewable energy is being done to meet energy needs. Solar energy is one of the renewable resources that can currently meet all of the world's energy needs. In most parts of the world, solar energy is a free and unlimited resource that can be used in a variety of ways, including photovoltaic systems for the generation of electricity and thermal systems for the generation of heatfor the residential sector's production of hot water. In this article, we'll conduct a comparison. The first step entails identifying the two empirical models that will enable us to estimate the daily irradiations on a horizontal plane. On the other hand, we compare it using the data obtained from measurements made at the Adrar site over the four distinct seasons. The model 2 provides a better estimate of the global solar components, with an absolute mean error of less than 7% and a correlation coefficient of more than 0.95, as well as a relative coefficient of the bias error that is less than 6% in absolute value and a relative RMSE that is less than 10%, according to a comparison of the results obtained by simulating the two models.

Keywords: solar radiation, renewable energy, fossil, photovoltaic systems

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Authors: Hassan Eshkiki, Benjamin Mora

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The Neighbor Migrating Generator is a simple and efficient approach to finding the closest potential neighbor(s) with a different label for a given instance and so without the need to calibrate any kernel settings at all. This allows determining and explaining the most important features that will influence an AI model. It can be used to either migrate a specific sample to the class decision boundary of the original model within a close neighborhood of that sample or identify global features that can help localising neighbor classes. The proposed technique works by minimizing a loss function that is divided into two components which are independently weighted according to three parameters α, β, and ω, α being self-adjusting. Results show that this approach is superior to past techniques when detecting the smallest changes in the feature space and may also point out issues in models like over-fitting.

Keywords: explainable AI, EX AI, feature importance, counterfactual explanations

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Authors: Isa Moazen, Ali Nahvi

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Driver drowsiness is a major cause of vehicle accidents, and facial images are highly valuable to detect drowsiness. In this paper, we perform our research via a thermal camera to record drivers' facial images on a driving simulator. A robust real-time algorithm extracts the features using horizontal and vertical integration projection, contours, contour orientations, and cropping tools. The features are included four target areas on the cheeks and forehead. Qt compiler and OpenCV are used with two cameras with different resolutions. A high-resolution thermal camera is used for fifteen subjects, and a low-resolution one is used for a person. The results are investigated by four temperature plots and evaluated by observer rating of drowsiness.

Keywords: advanced driver assistance systems, thermal imaging, driver drowsiness detection, feature extraction

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Authors: Jawharah Alasmari

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In verb inflection, tense marks past/present/future action, and aspect marks progressive/continues perfect/completed actions. This usage and meaning of tense and aspect differ in Arabic and English. In this research, we applied data mining methods to test the predictive function of candidate features by using our dataset of Arabic verbs in-context, and their 7 translations. Weka machine learning classifiers is used in this experiment in order to examine the key features that can be used to provide guidance to enable a translator’s appropriate English translation of the Arabic verb tense and aspect.

Keywords: Arabic verb, English translations, mining methods, Weka software

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Authors: Aphinan Phukaoluan, Surachai Dechkunakorn, Niwat Anuwongnukroh, Anak Khantachawana, Pongpan Kaewtathip, Julathep Kajornchaiyakul, Peerapong Tua-Ngam

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Aims: The objectives of this study was to determine the load-deflecting characteristics of a fabricated orthodontic wire with alloy composition of 50.6% (atomic weight) Ni and 49.4% (atomic weight) Ti and to compare the results with Ormco, a commercially available pre-formed NiTi orthodontic archwire. Materials and Methods: The ingots alloys with atomic weight ratio 50.6 Ni: 49.4 Ti alloy were used in this study. Three specimens were cut to have wire dimensions of 0.016 inch x0.022 inch. For comparison, a commercially available pre-formed NiTi archwire, Ormco, with dimensions of 0.016 inch x 0.022 inch was used. Three-point bending tests were performed at the temperature 36+1 °C using a Universal Testing Machine on the newly fabricated and commercial archwires to assess the characteristics of the load-deflection curve with loading and unloading forces. The loading and unloading features at the deflection points 0.25, 0.50, 0.75. 1.0, 1.25, and 1.5 mm were compared. Descriptive statistics was used to evaluate each variables, and independent t-test at p < 0.05 was used to analyze the mean differences between the two groups. Results: The load-deflection curve of the 50.6Ni: 49.4Ti wires exhibited the characteristic features of superelasticity. The curves at the loading and unloading slope of Ormco NiTi archwire were more parallel than the newly fabricated NiTi wires. The average deflection force of the 50.6Ni: 49.4Ti wire was 304.98 g and 208.08 g for loading and unloading, respectively. Similarly, the values were 358.02 g loading and 253.98 g for unloading of Ormco NiTi archwire. The interval difference forces between each deflection points were in the range 20.40-121.38 g and 36.72-92.82 g for the loading and unloading curve of 50.6Ni: 49.4Ti wire, respectively, and 4.08-157.08 g and 14.28-90.78 g for the loading and unloading curve of commercial wire, respectively. The average deflection force of the 50.6Ni: 49.4Ti wire was less than that of Ormco NiTi archwire, which could have been due to variations in the wire dimensions. Although a greater force was required for each deflection point of loading and unloading for the 50.6Ni: 49.4Ti wire as compared to Ormco NiTi archwire, the values were still within the acceptable limits to be clinically used in orthodontic treatment. Conclusion: The 50.6Ni: 49.4Ti wires presented the characteristics of a superelastic orthodontic wire. The loading and unloading force were also suitable for orthodontic tooth movement. These results serve as a suitable foundation for further studies in the development of new orthodontic NiTi archwires.

Keywords: 50.6 ni 49.4 Ti alloy wire, load deflection curve, loading and unloading force, orthodontic

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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This paper discusses on power spectral density (PSD) characteristics which are extracted from three-dimensional (3D) electroencephalogram (EEG) models. The EEG signal recording was conducted on 150 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, the values of maximum PSD were extracted as features from the model. These features are analysed using mean relative power (MRP) and different mean relative power (DMRP) technique to observe the pattern among different brain balancing indexes. The results showed that by implementing these techniques, the pattern of brain balancing indexes can be clearly observed. Some patterns are indicates between index 1 to index 5 for left frontal (LF) and right frontal (RF).

Keywords: power spectral density, 3D EEG model, brain balancing, mean relative power, different mean relative power

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Authors: Elena Carcano, Mirzi Betasolo

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This study helps Public Water Bureaus in giving reliable answers to water concession requests. Rapidly increasing water requests can be supported provided that further uses of a river course are not totally compromised, and environmental features are protected as well. Strictly speaking, a water concession can be considered a continuous drawing from the source and causes a mean annual streamflow reduction. Therefore, deciding if a water concession is appropriate or inappropriate seems to be easily solved by comparing the generic demand to the mean annual streamflow value at disposal. Still, the immediate shortcoming for such a comparison is that streamflow data are information available only for few catchments and, most often, limited to specific sites. Subsequently, comparing the generic water demand to mean daily discharge is indeed far from being completely satisfactory since the mean daily streamflow is greater than the water withdrawal for a long period of a year. Consequently, such a comparison appears to be of little significance in order to preserve the quality and the quantity of the river. In order to overcome such a limit, this study aims to complete the information provided by flow duration curves introducing a link between Flow Duration Curves (FDCs) and recession curves and aims to show the chronological sequence of flows with a particular focus on low flow data. The analysis is carried out on 25 catchments located in North-Eastern Italy for which daily data are provided. The results identify groups of catchments as hydrologically homogeneous, having the lower part of the FDCs (corresponding streamflow interval is streamflow Q between 300 and 335, namely: Q(300), Q(335)) smoothly reproduced by a common recession curve. In conclusion, the results are useful to provide more reliable answers to water request, especially for those catchments which show similar hydrological response and can be used for a focused regionalization approach on low flow data. A mathematical link between streamflow duration curves and recession curves is herein provided, thus furnishing streamflow duration curves information upon a temporal sequence of data. In such a way, by introducing assumptions on recession curves, the chronological sequence upon low flow data can also be attributed to FDCs, which are known to lack this information by nature.

Keywords: chronological sequence of discharges, recession curves, streamflow duration curves, water concession

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Authors: Olivia Rybak-Karkosz

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This paper's purpose was to present a case study on a questioned Claude Monet's signature forensic handwriting analysis. It is an example taken from the author’s experience as a court handwriting expert. A comparative study was conducted to determine whether the signature resembles similarities (and if so, to what measure) with the features representing the writing patterns and their natural variability typical for Claude Monet. It was conducted to check whether all writing features are within the writer's normal range of variation. The paper emphasizes the difficulties and challenges encountered by the forensic handwriting expert while analysing the questioned signature.

Keywords: artist’s signatures, authenticity of an artwork, forensic handwriting analysis, graphic-comparative method

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Authors: Anahita Farhang Ghahfarokhi, Alessandro Berti, Wil M.P. van der Aalst

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Process mining provides ways to analyze business processes. Common process mining techniques consider the process as a whole. However, in real-life business processes, different behaviors exist that make the overall process too complex to interpret. Process comparison is a branch of process mining that isolates different behaviors of the process from each other by using process cubes. Process cubes organize event data using different dimensions. Each cell contains a set of events that can be used as an input to apply process mining techniques. Existing work on process cubes assume single case notions. However, in real processes, several case notions (e.g., order, item, package, etc.) are intertwined. Object-centric process mining is a new branch of process mining addressing multiple case notions in a process. To make a bridge between object-centric process mining and process comparison, we propose a process cube framework, which supports process cube operations such as slice and dice on object-centric event logs. To facilitate the comparison, the framework is integrated with several object-centric process discovery approaches.

Keywords: multidimensional process mining, mMulti-perspective business processes, OLAP, process cubes, process discovery, process mining

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Authors: R. Korchiyne, A. Sbihi, S. M. Farssi, R. Touahni, M. Tahiri Alaoui

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Trabecular bone structure is important texture in the study of osteoporosis. Legendre multifractal spectrum can reflect the complex and self-similarity characteristic of structures. The main objective of this paper is to develop a new technique of medical image classification based on Legendre multifractal spectrum. Novel features have been developed from basic geometrical properties of this spectrum in a supervised image classification. The proposed method has been successfully used to classify medical images of bone trabeculations, and could be a useful supplement to the clinical observations for osteoporosis diagnosis. A comparative study with existing data reveals that the results of this approach are concordant.

Keywords: multifractal analysis, medical image, osteoporosis, fractal dimension, Legendre spectrum, supervised classification

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Authors: Hussein Yousif Aziz

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This paper discussed the design and analysis of bridge foundation subjected to load of train with three codes, namely AASHTO code, British Standard BS Code 8004 (1986), and Chinese code (TB10002.5-2005).The study focused on the design and analysis of bridge’s foundation manually with the three codes and found which code is better for design and controls the problem of high settlement due to the applied loads. The results showed the Chinese codes are costly that the number of reinforcement bars in the pile cap and piles is more than those with AASHTO code and BS code with the same dimensions. Settlement of the bridge was calculated depending on the data collected from the project site. The vertical ultimate bearing capacity of single pile for three codes is also discussed. Other analyses by using the two-dimensional Plaxis program and other programs like SAP2000 14, PROKON many parameters are calculated. The maximum values of the vertical displacement are close to the calculated ones. The results indicate that the AASHTO code is economics and safer in the bearing capacity of single pile. The purpose of this project is to study out the pier on the basis of the design of the pile foundation. There is a 32m simply supported beam of box section on top of the structure. The pier of bridge is round-type. The main component of the design is to calculate pile foundation and the settlement. According to the related data, we choose 1.0m in diameter bored pile of 48m. The pile is laid out in the rectangular pile cap. The dimension of the cap is 12m 9 m. Because of the interaction factors of pile groups, the load-bearing capacity of simple pile must be checked, the punching resistance of pile cap, the shearing strength of pile cap, and the part in bending of pile cap, all of them are very important to the structure stability. Also, checking soft sub-bearing capacity is necessary under the pile foundation. This project provides a deeper analysis and comparison about pile foundation design schemes. Firstly, here are brief instructions of the construction situation about the Bridge. With the actual construction geological features and the upper load on the Bridge, this paper analyzes the bearing capacity and settlement of single pile. In the paper the Equivalent Pier Method is used to calculate and analyze settlements of the piles.

Keywords: pile foundation, settlement, bearing capacity, civil engineering

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Authors: Ahmad K. Samaila, Basant K. Jha

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This paper presents the effects of suction/injection of transient/steady natural convection flow of reactive viscous fluid in a vertical porous pipe. The mathematical model capturing the time dependent flow of viscous reactive fluid is solved using implicit finite difference method while the corresponding steady state model is solved using regular perturbation technique. Results of analytical and numerical solutions are reported for various parametric conditions to illustrate special features of the solutions. The coefficient of skin friction and rate of heat transfer are obtained and illustrated graphically. The numerical solution is shown to be in excellent agreement with the closed form analytical solution. It is interesting to note that time required to reach steady state is higher in case of injection in comparison to suction.

Keywords: porous pipe, reactive viscous fluid, transient natural-convective flow, analytical solution

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Authors: Hema V. Vanar, R. K. Soni, N. D. Shah

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Slabs supported directly on columns without beams are known as Flat slabs. Flat slabs are highly versatile elements widely used in construction, providing minimum depth, fast construction and allowing flexible column grids. The main objective of this thesis is comparison of analytical method and soft ware for analysis of flat slab subjected to various parametric loadings. Study presents analysis of flat slab is performed under different types of gravity.

Keywords: fat slab, parametric load, analysis, software

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Authors: Saman Javadi, Mehdi Hashemy, Mohahammad Mahmoodi

Abstract:

Vulnerability maps are employed as an important solution in order to handle entrance of pollution into the aquifers. The common way to provide vulnerability map is DRASTIC. Meanwhile, application of the method is not easy to apply for any aquifer due to choosing appropriate constant values of weights and ranks. In this study, a new approach using k-means clustering is applied to make vulnerability maps. Four features of depth to groundwater, hydraulic conductivity, recharge value and vadose zone were considered at the same time as features of clustering. Five regions are recognized out of the case study represent zones with different level of vulnerability. The finding results show that clustering provides a realistic vulnerability map so that, Pearson’s correlation coefficients between nitrate concentrations and clustering vulnerability is obtained 61%.

Keywords: clustering, data mining, groundwater, vulnerability assessment

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Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

Abstract:

Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

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Authors: Zainab Yahaya Suleiman

Abstract:

Physical fitness, as one of the most important keys to a healthy wellbeing, is the basis of dynamic and creative intellectual activity. As a result, the fitness world is expanding every day. It is believed that a fitness centre is a place of healing and also the natural environment is vital to speedy recovery. The aim of this paper is to propose and designs a suitable location for a fitness centre in Batagarawa metropolis. Batagarawa city is enriched with four tertiary institutions with diverse commerce and culture but lacks the facility of a well-equipped fitness centre. The proposed fitness centre intends to be an organically sound centre that will make use of principles of organic architecture to create a new pleasant environment between man and his environments. Organic architecture is the science of designing a building within pleasant natural resources and features surrounding the environment. It is regarded as visual poetry and reinterpretation of nature’s principles; as well as embodies a settlement of person, place, and materials. Using organic architecture, the design was interlaced with the dynamic, organic and monumental features surrounding the environment. The city has inadequate/no facility that is considered organic where one can keep fit in a friendly, conducive and adequate location. Thus, the need for establishing a fitness centre to cater for this need cannot be over-emphasised. Conclusively, a fitness centre will be an added advantage to this fast growing centre of learning.

Keywords: organic architecture, fitness center, environment, natural resources, natural features, building design

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Authors: Anthony D. Rhodes, Manan Goel

Abstract:

We provide a high fidelity deep learning algorithm (HyperSeg) for interactive video segmentation tasks using a dense convolutional network with context-aware skip connections and compressed, 'hypercolumn' image features combined with a convolutional tessellation procedure. In order to maintain high output fidelity, our model crucially processes and renders all image features in high resolution, without utilizing downsampling or pooling procedures. We maintain this consistent, high grade fidelity efficiently in our model chiefly through two means: (1) we use a statistically-principled, tensor decomposition procedure to modulate the number of hypercolumn features and (2) we render these features in their native resolution using a convolutional tessellation technique. For improved pixel-level segmentation results, we introduce a boundary loss function; for improved temporal coherence in video data, we include temporal image information in our model. Through experiments, we demonstrate the improved accuracy of our model against baseline models for interactive segmentation tasks using high resolution video data. We also introduce a benchmark video segmentation dataset, the VFX Segmentation Dataset, which contains over 27,046 high resolution video frames, including green screen and various composited scenes with corresponding, hand-crafted, pixel-level segmentations. Our work presents a improves state of the art segmentation fidelity with high resolution data and can be used across a broad range of application domains, including VFX pipelines and medical imaging disciplines.

Keywords: computer vision, object segmentation, interactive segmentation, model compression

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