Search results for: Core Strength Exercise Training
Commenced in January 2007
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Edition: International
Paper Count: 2851

Search results for: Core Strength Exercise Training

2041 Some Mechanical Properties of Cement Stabilized Malaysian Soft Clay

Authors: Meei-Hoan Ho, Chee-Ming Chan

Abstract:

Soft clays are defined as cohesive soil whose water content is higher than its liquid limits. Thus, soil-cement mixing is adopted to improve the ground conditions by enhancing the strength and deformation characteristics of the soft clays. For the above mentioned reasons, a series of laboratory tests were carried out to study some fundamental mechanical properties of cement stabilized soft clay. The test specimens were prepared by varying the portion of ordinary Portland cement to the soft clay sample retrieved from the test site of RECESS (Research Centre for Soft Soil). Comparisons were made for both homogeneous and columnar system specimens by relating the effects of cement stabilized clay of for 0, 5 and 10 % cement and curing for 3, 28 and 56 days. The mechanical properties examined included one-dimensional compressibility and undrained shear strength. For the mechanical properties, both homogeneous and columnar system specimens were prepared to examine the effect of different cement contents and curing periods on the stabilized soil. The one-dimensional compressibility test was conducted using an oedometer, while a direct shear box was used for measuring the undrained shear strength. The higher the value of cement content, the greater is the enhancement of the yield stress and the decrease of compression index. The value of cement content in a specimen is a more active parameter than the curing period.

Keywords: Soft soil, Oedometer, Direct shear box, Cementstabilisedcolumn.

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2040 Investigation of Compressive Strength of Slag-Based Geopolymer Concrete Incorporated with Rice Husk Ash Using 12M Alkaline Activator

Authors: Festus A. Olutoge, Ahmed A. Akintunde, Anuoluwapo S. Kolade, Aaron A. Chadee, Jovanca Smith

Abstract:

Geopolymer concrete's (GPC) compressive strength was investigated. The GPC was incorporated with rice husk ash (RHA) and ground granulated blast furnace slag (GGBFS), which may have potential in the construction industry to replace Portland limestone cement (PLC) concrete. The sustainable construction binders used were GGBFS and RHA, and a solution of sodium hydroxide (NaOH) and sodium silicate gel (Na2SiO3) was used as the 12-molar alkaline activator. Five GPC mixes comprising fine aggregates, coarse aggregates, GGBS, and RHA, and the alkaline solution in the ratio 2: 2.5: 1: 0.5, respectively, were prepared to achieve grade 40 concrete, and PLC was substituted with GGBFS and RHA in the ratios of 0:100, 25:75, 50:50, 75:25, and 100:0. A control mix was also prepared which comprised of 100% water and 100% PLC as the cementitious material. The GPC mixes were thermally cured at 60-80 ºC in an oven for approximately 24 h. After curing for 7 and 28 days, the compressive strength test results of the hardened GPC samples showed that GPC-Mix #3, comprising 50% GGBFS and 50% RHA, was the most efficient geopolymer mix. The mix had compressive strengths of 35.71 MPa and 47.26 MPa, 19.87% and 8.69% higher than the PLC concrete samples, which had 29.79 MPa and 43.48 MPa after 7 and 28 days, respectively. Therefore, GPC containing GGBFS incorporated with RHA is an efficient method of decreasing the use of PLC in conventional concrete production and reducing the high amounts of CO2 emitted into the atmosphere in the construction industry.

Keywords: Alkaline solution, cementitious material, geopolymer concrete, ground granulated blast furnace slag, rice husk ash.

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2039 Addressing Scalability Issues of Named Entity Recognition Using Multi-Class Support Vector Machines

Authors: Mona Soliman Habib

Abstract:

This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.

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2038 Analysis of the Impact of NVivo and EndNote on Academic Research Productivity

Authors: Sujit K. Basak

Abstract:

The aim of this paper is to analyze the impact of literature review software on researchers. The aim of this study was achieved by analyzing models in terms of perceived usefulness, perceived ease of use, and acceptance level. Collected data were analyzed using WarpPLS 4.0 software. This study used two theoretical frameworks, namely, Technology Acceptance Model and the Training Needs Assessment Model. The study was experimental and was conducted at a public university in South Africa. The results of the study showed that acceptance level has a high impact on research productivity followed by perceived usefulness and perceived ease of use.

Keywords: Technology acceptance model, training needs assessment model, literature review software, research productivity.

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2037 The Effect of CaO Addition on Mechanical Properties of Ceramic Tiles

Authors: Lucie Vodova, Radomir Sokolar, Jitka Hroudova

Abstract:

Stoneware clay, fired clay (as a grog), calcite waste and class C fly ash in various mixing rations were the basic raw materials for the mixture for production of dry pressed ceramic tiles. Mechanical properties (water absorption, bulk density, apparent porosity, flexural strength) as well as mineralogical composition were studied on samples with different source of calcium oxide after firing at 900, 1000, 1100 and 1200°C. It was found that samples with addition of calcite waste contain dmisteinbergit and anorthite. This minerals help to improve the strength of the body and reduce porosity fired at lower temperatures. Class C fly ash has not significantly influence on properties of the fired body as calcite waste.

Keywords: Ceramic tiles, class C fly ash, calcite waste, calcium oxide, anorthite.

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2036 Influence of Silica Fume on Ultrahigh Performance Concrete

Authors: Vitoldas Vaitkevičius, Evaldas Šerelis

Abstract:

Silica fume, also known as microsilica (MS) or  condensed silica fume is a by-product of the production of silicon  metal or ferrosilicon alloys. Silica fume is one of the most effective  pozzolanic additives which could be used for ultrahigh performance  and other types of concrete. Despite the fact, however is not entirely  clear, which amount of silica fume is most optimal for UHPC. Main  objective of this experiment was to find optimal amount of silica  fume for UHPC with and without thermal treatment, when different  amount of quartz powder is substituted by silica fume. In this work  were investigated four different composition of UHPC with different  amount of silica fume. Silica fume were added 0, 10, 15 and 20% of  cement (by weight) to UHPC mixture. Optimal amount of silica fume  was determined by slump, viscosity, qualitative and quantitative  XRD analysis and compression strength tests methods.

Keywords: Compressive strength, silica fume, ultrahigh performance concrete, XRD.

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2035 Experimental Inspection of Damage and Performance Evaluation after Repair and Strengthening of Jiamusi Highway Prestressed Concrete Bridge in China

Authors: Ali Fadhil Naser, Wang Zonglin

Abstract:

The main objectives of this study are to inspect and identify any damage of jaimusi highway prestressed concrete bridge after repair and strengthening of damaged structural members and to evaluate the performance of the bridge structural members by adopting static load test. Inspection program after repair and strengthening includes identifying and evaluating the structural members of bridge such as T-shape cantilever structure, hanging beams, corbels, external tendons, anchor beams, sticking steel plate, and piers. The results of inspection show that the overall state of the bridge structural member after repair and strengthening is good. The results of rebound test of concrete strength show that the average strength of concrete is 46.31Mpa. Whereas, the average value of concrete strength of anchor beam is 49.82Mpa. According to the results of static load test, the experimental values are less than theoretical values of internal forces, deflection, and strain, indicating that the stiffness of the experimental structure, overall deformation and integrity satisfy the designed standard and the working performance is good, and the undertaking capacity has a certain surplus. There is not visible change in the length and width of cracks and there are not new cracks under experimental load.

Keywords: Jiamusi Bridge, Damage inspection, deflection, strain.

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2034 Improving RBF Networks Classification Performance by using K-Harmonic Means

Authors: Z. Zainuddin, W. K. Lye

Abstract:

In this paper, a clustering algorithm named KHarmonic means (KHM) was employed in the training of Radial Basis Function Networks (RBFNs). KHM organized the data in clusters and determined the centres of the basis function. The popular clustering algorithms, namely K-means (KM) and Fuzzy c-means (FCM), are highly dependent on the initial identification of elements that represent the cluster well. In KHM, the problem can be avoided. This leads to improvement in the classification performance when compared to other clustering algorithms. A comparison of the classification accuracy was performed between KM, FCM and KHM. The classification performance is based on the benchmark data sets: Iris Plant, Diabetes and Breast Cancer. RBFN training with the KHM algorithm shows better accuracy in classification problem.

Keywords: Neural networks, Radial basis functions, Clusteringmethod, K-harmonic means.

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2033 Improved Back Propagation Algorithm to Avoid Local Minima in Multiplicative Neuron Model

Authors: Kavita Burse, Manish Manoria, Vishnu P. S. Kirar

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The back propagation algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a training algorithm consisting of a learning rate and a momentum factor. The major drawbacks of above learning algorithm are the problems of local minima and slow convergence speeds. The addition of an extra term, called a proportional factor reduces the convergence of the back propagation algorithm. We have applied the three term back propagation to multiplicative neural network learning. The algorithm is tested on XOR and parity problem and compared with the standard back propagation training algorithm.

Keywords: Three term back propagation, multiplicative neuralnetwork, proportional factor, local minima.

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2032 Dielectric Recovery Characteristics of High Voltage Gas Circuit Breakers Operating with CO2 Mixture

Authors: Peng Lu, Branimir Radisavljevic, Martin Seeger, Daniel Over, Torsten Votteler, Bernardo Galletti

Abstract:

CO₂-based gas mixtures exhibit huge potential as the interruption medium for replacing SF₆ in high voltage switchgears. In this paper, the recovery characteristics of dielectric strength of CO₂-O₂ mixture in the post arc phase after the current zero are presented. As representative examples, the dielectric recovery curves under conditions of different gas filling pressures and short-circuit current amplitudes are presented. A series of dielectric recovery measurements suggests that the dielectric recovery rate is proportional to the mass flux of the blowing gas, and the dielectric strength recovers faster in the case of lower short circuit currents.

Keywords: CO2 mixture, high voltage circuit breakers, dielectric recovery rate, short-circuit current, mass flux.

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2031 Experimental Investigation on Shear Behaviour of Fibre Reinforced Concrete Beams Using Steel Fibres

Authors: G. Beulah Gnana Ananthi, A. Jaffer Sathick, M. Abirami

Abstract:

Fibre reinforced concrete (FRC) has been widely used in industrial pavements and non-structural elements such as pipes, culverts, tunnels, and precast elements. The strengthening effect of fibres in the concrete matrix is achieved primarily due to the bridging effect of fibres at the crack interfaces. The workability of the concrete was reduced on addition of high percentages of steel fibres. The optimum percentage of addition of steel fibres varies with its aspect ratio. For this study, 1% addition of steel has resulted to be the optimum percentage for both Hooked and Crimped Steel Fibres and was added to the beam specimens. The fibres restrain efficiently the cracks and take up residual stresses beyond the cracking. In this sense, diagonal cracks are effectively stitched up by fibres crossing it. The failure of beams within the shear failure range changed from shear to flexure in the presence of sufficient steel fibre quantity. The shear strength is increased with the addition of steel fibres and had exceeded the enhancement obtained with the transverse reinforcement. However, such increase is not directly in proportion with the quantity of fibres used. Considering all the clarification made in the present experimental investigation, it is concluded that 1% of crimped steel fibres with an aspect ratio of 50 is the best type of steel fibres for replacement of transverse stirrups in high strength concrete beams when compared to the steel fibres with hooked ends.

Keywords: Fibre reinforced concrete, steel fibre, shear strength, crack pattern.

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2030 In Search of a Suitable Neural Network Capable of Fast Monitoring of Congestion Level in Electric Power Systems

Authors: Pradyumna Kumar Sahoo, Prasanta Kumar Satpathy

Abstract:

This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Keywords: Line congestion index, critical bus, contingency, neural network.

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2029 Mechanical and Chemical Reliability Assessment of Silica Optical Fibres

Authors: Irina Severin, M. Caramihai, K. Chung, G. Tasca, T. Park

Abstract:

The current study has investigated the ageing phenomena of silica optical fibres in relation to water activity which might be accelerated when exposed to a supplementary energy, such as microwaves. A controlled stress by winding fibres onto accurate diameter mandrel was applied. Taking into account that normally a decrease in fibre strength is induced in time by chemical action of water, the effects of cumulative reagents such as: water, applied stress and supplementary energy (microwave) in some cases acted in the opposite manner. The microwave effect as a structural relaxation catalyst appears unexpected, even if the overall gain in fibre strength is not high, but the stress corrosion factor revealed significant increase in certain simulation conditions.

Keywords: optical fibres, mechanical testing, aging, microwave, structural relaxation.

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2028 Synthesis and Properties of Biobased Polyurethane/Montmorillonite Nanocomposites

Authors: Teuku Rihayat, Suryani

Abstract:

Polyurethanes (PURs) are very versatile polymeric materials with a wide range of physical and chemical properties. PURs have desirable properties such as high abrasion resistance, tear strength, shock absorption, flexibility and elasticity. Although they have relatively poor thermal stability, this can be improved by using treated clay. Polyurethane/clay nanocomposites have been synthesized from renewable sources. A polyol for the production of polyurethane by reaction with an isocyanate was obtained by the synthesis of palm oil-based oleic acid with glycerol. Dodecylbenzene sulfonic acid (DBSA) was used as catalyst and emulsifier. The unmodified clay (kunipia-F) was treated with cetyltrimethyl ammonium bromide (CTAB-mont) and octadodecylamine (ODAmont). The d-spacing in CTAB-mont and ODA-mont were 1.571 nm and 1.798 nm respectively and larger than that of the pure-mont (1.142 nm). The organoclay was completely intercalated in the polyurethane, as confirmed by a wide angle x-ray diffraction (WAXD) pattern. The results showed that adding clay demonstrated better thermal stability in comparison with the virgin polyurethane. Onset degradation of pure PU is at 200oC, and is lower than that of the CTAB-mont PU and ODA-mont PU which takes place at about 318oC and 330oC, respectively. The mechanical properties (including the dynamic mechanical properties) of pure polyurethane (PU) and PU/clay nanocomposites, were measured. The modified organoclay had a remarkably beneficial effect on the strength and elongation at break of the nanocomposites, which both increased with increasing clay content with the increase of the tensile strength of more than 214% and 267% by the addition of only 5 wt% of the montmorillonite CTAB-mont PU and ODA-mont PU, respectively.

Keywords: Polyurethane, Clay nanocomposites, Biobase

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2027 Study of the Effects of Ceramic Nano-Pigments in Cement Mortar Corrosion Caused by Chlorine Ions

Authors: R. Moradpour, S.B. Ahmadi, T. Parhizkar, M. Ghodsian, E. Taheri-Nassaj

Abstract:

Superfine pigments that consist of natural and artificial pigments and are made of mineral soil with special characteristics are used in cementitious materials for various purposes. These pigments can decrease the amount of cement needed without loss of performance and strength and also change the monotonous and turbid colours of concrete into various attractive and light colours. In this study, the mechanical strength and resistance against chloride and halogen attacks of cement mortars containing ceramic nano-pigments in an affected environment are studied. This research suggests utilisation of ceramic nano-pigments between 50 and 1000 nm, obtaining full-depth coloured concrete, preventing chlorine penetration in the concrete up to a certain depth, and controlling corrosion in steel rebar with the Potentiostat (EG&G) apparatus.

Keywords: Nano-structures, Corrosion, Mechanical properties, Nano-pigments.

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2026 Experimental Investigation of the Influence of Cement on Soil-Municipal Solid Incineration Fly Ash Mix Properties

Authors: G. Aouf, D. Tabbal, A. Sabsabi, R. Aouf

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The aim of this study is to assess the viability of utilizing Municipal Solid Waste Incineration Fly Ash (MSWIFA) with Ordinary Portland cement as soil reinforcement materials for geotechnical engineering applications. A detailed experimental program is carried out followed by analysis of results. Soil samples were prepared by adding cement to MSWIFA-soil mix at different percentages. Then, a series of laboratory tests were performed namely: Sieve analysis, Atterberg limits tests, Unconfined compression test, and Proctor tests. A parametric study is conducted to investigate the effect of adding the cement at different percentages on the unconfined compression strength, maximum dry density (MDD), and optimum moisture content (OMC) of clayey soil-MSWIFA. The variations of admixtures’ contents were 10%, 20%, and 30% for MSWIFA by dry total weight of soil and 10%, 15%, and 20% for Portland cement by dry total weight of the mix. The test results reveal that adding MSWIFA to the soil up to 20% increased the MDD of the mixture and decreased the OMC, then an opposite trend for results were found when the percentage of MSWIFA exceeds 20%. This is due to the low specific gravity of MSWIFA and to the greater water absorption of MSWIFA. The laboratory tests also indicate that the Unconfined Compression Test values were found to be increased for all the mixtures with curing periods of 7, 14, and 28 days. It is also observed that the cement increased the strength of the finished product of the mix of soil and MSWIFA.

Keywords: Clayey soil, cement, Municipal Solid Waste Incineration Fly Ash, MSWIFA, unconfined compression strength.

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2025 Public Service Ethics in Public Administration: An Empirical Investigation

Authors: Kalsoom Sumra

Abstract:

The increasing concern of public sector reforms brings new challenges to public service ethics in developing countries not only at central level but also at local level. This paper aims to identify perceptions on public service ethics of public officials and examines more generally the understanding of public servants in Pakistan towards public service ethics in local public organizations. The study uses an independently administered structured questionnaire to collect data to know the extent of the recognition of public service ethics in local organizations. A total of 150 completed questionnaires are analyzed received from public servants working at the local level in Pakistan. The analysis explores how traditional, social patterns and cultural ethics can provide us with a rounded picture of the main antecedents, moderators of public service ethics in Pakistan. Moreover, the findings of this study contribute in association of public service ethics which are crucial in ongoing political and administrative culture of Pakistan, the most crucial core for public organizational ethical climate. This study also has numerous implications for local public administration and it highlights the importance of expanding research agenda on public service ethics in developing settings with challenging institutional contexts with imperfect training and operating environments. This study may well be particularly important for practice of public service ethics in developing countries in public administration. To the best of author’s knowledge, this study is the first of its kind to provide an initial step in practical implications to emphasize relevant public service ethics in public administration in developing transparent and accountable organization.

Keywords: Public service ethics, accountability and transparency, public service reforms, public administration, organizational ethical climate.

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2024 Envelope-Wavelet Packet Transform for Machine Condition Monitoring

Authors: M. F. Yaqub, I. Gondal, J. Kamruzzaman

Abstract:

Wavelet transform has been extensively used in machine fault diagnosis and prognosis owing to its strength to deal with non-stationary signals. The existing Wavelet transform based schemes for fault diagnosis employ wavelet decomposition of the entire vibration frequency which not only involve huge computational overhead in extracting the features but also increases the dimensionality of the feature vector. This increase in the dimensionality has the tendency to 'over-fit' the training data and could mislead the fault diagnostic model. In this paper a novel technique, envelope wavelet packet transform (EWPT) is proposed in which features are extracted based on wavelet packet transform of the filtered envelope signal rather than the overall vibration signal. It not only reduces the computational overhead in terms of reduced number of wavelet decomposition levels and features but also improves the fault detection accuracy. Analytical expressions are provided for the optimal frequency resolution and decomposition level selection in EWPT. Experimental results with both actual and simulated machine fault data demonstrate significant gain in fault detection ability by EWPT at reduced complexity compared to existing techniques.

Keywords: Envelope Detection, Wavelet Transform, Bearing Faults, Machine Health Monitoring.

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2023 Low Resolution Single Neural Network Based Face Recognition

Authors: Jahan Zeb, Muhammad Younus Javed, Usman Qayyum

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This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.

Keywords: Average filtering, Bicubic Interpolation, Neurons, vectorization.

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2022 Speaker Identification by Atomic Decomposition of Learned Features Using Computational Auditory Scene Analysis Principals in Noisy Environments

Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

Abstract:

Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.

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2021 Neural Networks-Based Acoustic Annoyance Model for Laptop Hard Disk Drive

Authors: Yi Chao Ma, Cheng Siong Chin, Wai Lok Woo

Abstract:

Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and threedimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who are the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system, which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Keywords: Hard disk drive noise, jury test, neural network model, psychoacoustic annoyance.

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2020 Application of Digital Tools for Improving Learning

Authors: José L. Jiménez

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The use of technology in the classroom is an issue that is constantly evolving. Digital age students learn differently than their teachers did, so now the teacher should be constantly evolving their methods and teaching techniques to be more in touch with the student. In this paper a case study presents how were used some of these technologies by accompanying a classroom course, this in order to provide students with a different and innovative experience as their teacher usually presented the activities to develop. As students worked in the various activities, they increased their digital skills by employing unknown tools that helped them in their professional training. The twenty-first century teacher should consider the use of Information and Communication Technologies in the classroom thinking in skills that students of the digital age should possess. It also takes a brief look at the history of distance education and it is also highlighted the importance of integrating technology as part of the student's training.

Keywords: Digital tools, on-line learning, social networks, technology.

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2019 Factors that Contribute to the Improvement of the Sense of Self-Efficacy of Special Educators in Inclusive Settings in Greece

Authors: Sotiria Tzivinikou, Dimitra Kagkara

Abstract:

Teacher’s sense of self-efficacy can affect significantly both teacher’s and student’s performance. More specific, self-efficacy is associated with the learning outcomes as well as student’s motivation and self-efficacy. For example, teachers with high sense of self-efficacy are more open to innovations and invest more effort in teaching. In addition to this, effective inclusive education is associated with higher levels of teacher’s self-efficacy. Pre-service teachers with high levels of self-efficacy could handle student’s behavior better and more effectively assist students with special educational needs. Teacher preparation programs are also important, because teacher’s efficacy beliefs are shaped early in learning, as a result the quality of teacher’s education programs can affect the sense of self-efficacy of pre-service teachers. Usually, a number of pre-service teachers do not consider themselves well prepared to work with students with special educational needs and do not have the appropriate sense of self-efficacy. This study aims to investigate the factors that contribute to the improvement of the sense of self-efficacy of pre-service special educators by using an academic practicum training program. The sample of this study is 159 pre-service special educators, who also participated in the academic practicum training program. For the purpose of this study were used quantitative methods for data collection and analysis. Teacher’s self-efficacy was assessed by the teachers themselves with the completion of a questionnaire which was based on the scale of Teacher’s Sense of Efficacy Scale. Pre and post measurements of teacher’s self-efficacy were taken. The results of the survey are consistent with those of the international literature. The results indicate that a significant number of pre-service special educators do not hold the appropriate sense of self-efficacy regarding teaching students with special educational needs. Moreover, a quality academic training program constitutes a crucial factor for the improvement of the sense of self-efficacy of pre-service special educators, as additional for the provision of high quality inclusive education.

Keywords: Inclusive education, pre-service, self-efficacy, training program.

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2018 A Research on the Coordinated Development of Chengdu-Chongqing Economic Circle Under the Background of New Urbanization

Authors: Deng Tingting

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The coordinated and integrated development of regions is an inevitable requirement for China to move towards high-quality sustainable development. As one of the regions with the best economic foundation and the strongest economic strength in the western China, it is a typical area with national importance and strong network connection characteristics in terms of the comprehensive effect of linking the inland hinterland and connecting the western and national urban networks. The integrated development of the Chengdu-Chongqing economic circle is of great strategic significance for the rapid and high-quality development of the western region. In the context of new urbanization, this paper takes 16 urban units within the economic circle as the research object, based on the 5-year panel data of population, regional economy and spatial construction and development from 2016 to 2020, using the entropy method and Theil index to analyze the three target layers, and cause analysis. The research shows that there are temporal and spatial differences in the Chengdu-Chongqing economic circle, and there are significant differences between the core city and the surrounding cities. Therefore, by reforming and innovating the regional coordinated development mechanism, breaking administrative barriers, and strengthening the "polar nucleus" radiation function to release the driving force for economic development, especially in the gully areas of economic development belts, will not only promote the coordinated development of internal regions, but also promote the coordinated and sustainable development of the western region and toward a high-quality development path.

Keywords: Chengdu-Chongqing economic circle, new urbanization, coordinated regional development, Theil Index.

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2017 Quality of Life Assessment across the Cancer Continuum: Understanding the Role of an Exercise Rehabilitation Programme

Authors: Bernat-Carles Serdà Ferrer, Arantza Del Valle Gómez

Abstract:

The Quality of Life (QoL) paradigm is multidimensional, dynamic and modular and its definition differs across the cancer continuum. The challenge in the interpretation of QoL data in clinical research is that QoL is influenced by psychological phenomena such as adaptation to illness. This research aims to obtain a valid and sensitive assessment of QoL change over the continuum disease, and to evaluate a rehabilitation programme aimed at inverting the observed decrease in QoL when patients return to daily living activities. The sample comprised 66 men. Patients were first assessed to establish a baseline (P1-diagnosis). This was followed by a post-test (P2-discharge) and a then-test measurement (P3-retrospective evaluation) and after returning home patients were randomized in experimental and control groups. The experimental group attended a rehabilitation programme over 24 weeks (P4). Results show that from baseline to post-test, QoL decreased significantly. The recalibration then-test confirmed a low QoL in all periods evaluated. Significant differences between the experimental and control groups prove the positive effect of the Exercise Rehabilitation Programme (ERP) on QoL. Understanding the real dynamic of QoL over time would help to adapt rehabilitation programmes by improving sensitivity and efficacy and provide professionals with a more accurate perception of the impact of treatment and side effects on patients’ QoL. Our results underline the importance of changing the approach adopted by health professionals towards one of watchful waiting on patients’ QoL until their complete recovery in daily life.

Keywords: Prostate cancer, quality of life, rehabilitation programme, response shift.

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2016 Reliability Indices Evaluation of SEIG Rotor Core Magnetization with Minimum Capacitive Excitation for WECs

Authors: Lokesh Varshney, R. K. Saket

Abstract:

This paper presents reliability indices evaluation of the rotor core magnetization of the induction motor operated as a self excited induction generator by using probability distribution approach and Monte Carlo simulation. Parallel capacitors with calculated minimum capacitive value across the terminals of the induction motor operated as a SEIG with unregulated shaft speed have been connected during the experimental study. A three phase, 4 poles, 50Hz, 5.5 hp, 12.3A, 230V induction motor coupled with DC Shunt Motor was tested in the electrical machine laboratory with variable reactive loads. Based on this experimental study, it is possible to choose a reliable induction machines operated as a SEIG for unregulated renewable energy application in remote area or where grid is not available. Failure density function, cumulative failure distribution function, survivor function, hazard model, probability of success and probability of failure for reliability evaluation of the three phase induction motor operating as a SEIG have been presented graphically in this paper.

Keywords: Residual magnetism, magnetization curve, induction motor, self excited induction generator, probability distribution, Monte Carlo simulation.

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2015 Combining ILP with Semi-supervised Learning for Web Page Categorization

Authors: Nuanwan Soonthornphisaj, Boonserm Kijsirikul

Abstract:

This paper presents a semi-supervised learning algorithm called Iterative-Cross Training (ICT) to solve the Web pages classification problems. We apply Inductive logic programming (ILP) as a strong learner in ICT. The objective of this research is to evaluate the potential of the strong learner in order to boost the performance of the weak learner of ICT. We compare the result with the supervised Naive Bayes, which is the well-known algorithm for the text classification problem. The performance of our learning algorithm is also compare with other semi-supervised learning algorithms which are Co-Training and EM. The experimental results show that ICT algorithm outperforms those algorithms and the performance of the weak learner can be enhanced by ILP system.

Keywords: Inductive Logic Programming, Semi-supervisedLearning, Web Page Categorization

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2014 The Study of Applying Models: House, Temple and School for Sufficiency Development to Participate in ASEAN Economic Community: A Case Study of Trimitra Temple (China Town) Bangkok, Thailand

Authors: Saowapa Phaithayawat

Abstract:

The purposes of this study are 1) to study the impact of the 3-community-core model: House (H), Temple (T), and School (S) with the co-operation of official departments on community development to ASEAN economic community involvement and 2) to study the procedures and extension of the model. The research which is a qualitative research is based on the formal and informal interviews. Local people in a community are observed. Group interview is, also, operated by executors and cooperators in the school in the community. In terms of social and cultural dimension, the 3-community-core model consisting of house, temple and school is the base of Thai cultures bringing about understanding, happiness and unity to the community. The result of this research is that the official departments in accompanied with this model developers cooperatively work together in the community to support such factors as budget, plan, activities. Moreover, the need of community, and the continual result to sustain the community are satisfied by the model implementation. In terms of the procedures of the model implementation, executors and co-operators can work, coordinate, think, and launch their public relation altogether. Concerning the model development, this enables the community to achieve its goal to prepare the community’s readiness for ASEAN Economic Community involvement.

Keywords: ASEAN Economic Community, Community Development.

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2013 Performance Analysis of Evolutionary ANN for Output Prediction of a Grid-Connected Photovoltaic System

Authors: S.I Sulaiman, T.K Abdul Rahman, I. Musirin, S. Shaari

Abstract:

This paper presents performance analysis of the Evolutionary Programming-Artificial Neural Network (EPANN) based technique to optimize the architecture and training parameters of a one-hidden layer feedforward ANN model for the prediction of energy output from a grid connected photovoltaic system. The ANN utilizes solar radiation and ambient temperature as its inputs while the output is the total watt-hour energy produced from the grid-connected PV system. EP is used to optimize the regression performance of the ANN model by determining the optimum values for the number of nodes in the hidden layer as well as the optimal momentum rate and learning rate for the training. The EPANN model is tested using two types of transfer function for the hidden layer, namely the tangent sigmoid and logarithmic sigmoid. The best transfer function, neural topology and learning parameters were selected based on the highest regression performance obtained during the ANN training and testing process. It is observed that the best transfer function configuration for the prediction model is [logarithmic sigmoid, purely linear].

Keywords: Artificial neural network (ANN), Correlation coefficient (R), Evolutionary programming-ANN (EPANN), Photovoltaic (PV), logarithmic sigmoid and tangent sigmoid.

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2012 Determination of Material Properties for Biodegradable Polylactic Acid Plastic Used in 3D Printers

Authors: Juraj Beniak, Ľubomír Šooš, Peter Križan, Miloš Matúš

Abstract:

Within Rapid Prototyping technologies are used many types of materials. Many of them are recyclable but there are still as plastic like, so practically they do not degrade in the landfill. Polylactic acid (PLA) is one of the special plastic materials, which are biodegradable and available for 3D printing within Fused Deposition Modeling (FDM) technology. The question is, if the mechanical properties of produced models are comparable to similar technical plastic materials which are usual for prototype production. Presented paper shows the experiments results for tensile strength measurements for specimens prepared with different 3D printer settings and model orientation. Paper contains also the comparison of tensile strength values with values measured on specimens produced by conventional technologies as injection moulding.

Keywords: 3D printing, biodegradable plastic, fused deposition modeling, PLA plastic, rapid prototyping.

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