Search results for: Synthetic jet actuator.

Authors: Zhifeng Kong

Abstract:

Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.

Keywords: Over-parameterization, Rectified Linear Units (ReLU), convergence, gradient descent, neural networks.

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Authors: Asep Saepuloh, Katsuaki Koike

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Field mapping activity for an active volcano mainly in the Torrid Zone is usually hampered by several problems such as steep terrain and bad atmosphere conditions. In this paper we present a simple solution for such problem by a combination Synthetic Aperture Radar (SAR) and geostatistical methods. By this combination, we could reduce the speckle effect from the SAR data and then estimate roughness distribution of the pyroclastic flow deposits. The main purpose of this study is to detect spatial distribution of new pyroclastic flow deposits termed as P-zone accurately using the β°data from two RADARSAT-1 SAR level-0 data. Single scene of Hyperion data and field observation were used for cross-validation of the SAR results. Mt. Merapi in central Java, Indonesia, was chosen as a study site and the eruptions in May-June 2006 were examined. The P-zones were found in the western and southern flanks. The area size and the longest flow distance were calculated as 2.3 km2 and 6.8 km, respectively. The grain size variation of the P-zone was mapped in detail from fine to coarse deposits regarding the C-band wavelength of 5.6 cm.

Keywords: Geostatistical Method, Mt. Merapi, Pyroclastic, RADARSAT-1.

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Authors: Y. Araki, M. Kim, S. Okayama, K. Ikago, K. Uetani

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We study dynamic instability in high-rise steel moment resisting frames (SMRFs) subjected to synthetic long-period ground motions caused by hypothetical huge subduction earthquakes. Since long duration as well as long dominant periods is a characteristic of long-period ground motions, interstory drifts may enter the negative postyield stiffness range many times when high-rise buildings are subjected to long-period ground motions. Through the case studies of 9 high-rise SMRFs designed in accordance with the Japanese design practice in 1980s, we demonstrate that drifting, or accumulation of interstory drifts in one direction, occurs at the lower stories of the SMRFs, if their natural periods are close to the dominant periods of the long-period ground motions. The drifting led to residual interstory drift ratio over 0.01, or to collapse if the design base shear was small.

Keywords: long-period ground motion, P-Delta effect, high-rise steel moment resisting frame (SMRF), subduction earthquake

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Authors: Feng Chia Hsieh, Sheng Kuo Hsieh, Tzyy Rong Jinn

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Characterization and evaluation of the activity of Vespa basalis DPP-IV, which expressed in Spodoptera frugiperda 21 cells. The expression of rDPP-IV was confirmed by SDS–PAGE, Western blot analyses, LC-MS/MS and measurement of its peptidase specificity. One-step purification by Ni-NTA affinity chromatography and the total amount of rDPP-IV recovered was approximately 6.4mg per liter from infected culture medium; an equivalent amount would be produced by 1x109 infected Sf21 insect cells. Through the affinity purification led to highly stable rDPP-IV enzyme was recovered and with significant peptidase activity. The rDPP-IV exhibited classical Michaelis–Menten kinetics, with kcat/Km in the range of 10-500 mM-1×S-1 for the five synthetic substrates and optimum substrate is Ala-Pro-pNA. As expected in inhibition assay, the enzymatic activity of rDPP-IV was significantly reduced by 80 or 60% in the presence of sitagliptin (a DPP-IV inhibitor) or PMSF (a serine protease inhibitor), but was not apparently affected by iodoacetamide (a cysteine protease inhibitor).

Keywords: Dipeptidyl-Peptidase IV, Phenylmethylsulfonyl fluoride; Serine protease, Sitagliptin, Vespa basalis

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Authors: M. F. Miah, H. Ali, E. Zannath, T. M. Shuvra, M. N. Naser, M. K. Ahmed

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In this study, breeding biology and induced breeding of freshwater mud eel, Monopterus cuchia was observed during the experimental period from February to June, 2013. Breeding biology of freshwater mud eel, Monopterus cuchia was considered in terms of gonadosomatic index, length-weight relationship of gonad, ova diameter and fecundity. The ova diameter was recorded from 0.3 mm to 4.30 mm and the individual fecundity was recorded from 155 to 1495 while relative fecundity was found from 2.64 to 12.45. The fecundity related to body weight and length of fish was also discussed. A peak of GSI was observed 2.14±0.2 in male and 5.1 ±1.09 in female. Induced breeding of freshwater mud eel, Monopterus cuchia was also practiced with different doses of different inducing agents like pituitary gland (PG), human chorionic gonadotropin (HCG), Gonadotropin releasing hormone (GnRH) and Ovuline-a synthetic hormone in different environmental conditions. However, it was observed that the artificial breeding of freshwater mud eel, Monopterus cuchia was not yet succeeded through inducing agents in captive conditions, rather the inducing agent showed negative impacts on fecundity and ovarian tissues. It was seen that mature eggs in the oviduct were reduced, absorbed and some eggs were found in spoiled condition.

Keywords: Breeding biology, induced breeding, Monopterus cuchia.

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Authors: H. Sadi-Guettaf, F. Hadj Bekkouche

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Dexamethasone (Dex) is a synthetic glucocorticoid that is used in therapy. However prolonged treatments with high doses are often required. This causes side effects that interfere with the activity of several endocrine systems, including the gonadotropic axis. The aim of our study is to determine the effect of Dex on testicular function in prepubertal Wistar rats. Newborn Wistar rats are submitted to intraperitoneal injection of Dex (1μg of Dex dissolved in NaCl 0.9% / 5g bw) for 20 days and then sacrificed at the age of 40days. A control group received NaCl 0.9%. The rat is weighed daily. The plasmatic levels of testosterone, LH and FSH were measured by radioimmunoassay. A histomorphometric study was performed on sections of testis. Treated groups showed a significant decrease in body weight (p < 0.05), testis weight (p < 0.05) and plasma levels of testosterone (p < 0.05), of LH (P < .05) and FSH (p> 0.05). There is a reduction of seminiferous tubules average diameter and also of the seminiferous epithelium thickness with an increasing of lumen tubular. The diameter of the Leydig cells and Sertoli cell nucleus is also significantly reduced. Spermatogenesis is blocked at the stage round spermatid unlike witnesses or elongated spermatid stage is found. These results suggest that Dex administered during neonatal life influences testicular activity in the long term.

Keywords: Dexamethasone, FSH, LH, rat, testis, testosterone.

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Authors: Yogita, Durga Toshniwal

Abstract:

Outlier detection in streaming data is very challenging because streaming data cannot be scanned multiple times and also new concepts may keep evolving. Irrelevant attributes can be termed as noisy attributes and such attributes further magnify the challenge of working with data streams. In this paper, we propose an unsupervised outlier detection scheme for streaming data. This scheme is based on clustering as clustering is an unsupervised data mining task and it does not require labeled data, both density based and partitioning clustering are combined for outlier detection. In this scheme partitioning clustering is also used to assign weights to attributes depending upon their respective relevance and weights are adaptive. Weighted attributes are helpful to reduce or remove the effect of noisy attributes. Keeping in view the challenges of streaming data, the proposed scheme is incremental and adaptive to concept evolution. Experimental results on synthetic and real world data sets show that our proposed approach outperforms other existing approach (CORM) in terms of outlier detection rate, false alarm rate, and increasing percentages of outliers.

Keywords: Concept Evolution, Irrelevant Attributes, Streaming Data, Unsupervised Outlier Detection.

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Authors: Abdenour Bounsiar, Edith Grall, Pierre Beauseroy

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In this paper we are interested in classification problems with a performance constraint on error probability. In such problems if the constraint cannot be satisfied, then a rejection option is introduced. For binary labelled classification, a number of SVM based methods with rejection option have been proposed over the past few years. All of these methods use two thresholds on the SVM output. However, in previous works, we have shown on synthetic data that using thresholds on the output of the optimal SVM may lead to poor results for classification tasks with performance constraint. In this paper a new method for supervised classification with rejection option is proposed. It consists in two different classifiers jointly optimized to minimize the rejection probability subject to a given constraint on error rate. This method uses a new kernel based linear learning machine that we have recently presented. This learning machine is characterized by its simplicity and high training speed which makes the simultaneous optimization of the two classifiers computationally reasonable. The proposed classification method with rejection option is compared to a SVM based rejection method proposed in recent literature. Experiments show the superiority of the proposed method.

Keywords: rejection, Chow's rule, error-reject tradeoff, SupportVector Machine.

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Authors: M. H. Ahmad, A. A. A. Jamil, H. Ahmad, M. A. M. Piah, A. Darus, Y. Z. Arief, N. Bashir

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The use of synthetic retardants in polymeric insulated cables is not uncommon in the high voltage engineering to study electrical treeing phenomenon. However few studies on organic materials for the same investigation have been carried. .This paper describes the study on the effects of Oil Palm Empty Fruit Bunch (OPEFB) microfiller on the tree initiation and propagation in silicone rubber with different weight percentages (wt %) of filler to insulation bulk material. The weight percentages used were 0 wt % and 1 wt % respectively. It was found that the OPEFB retards the propagation of the electrical treeing development. For tree inception study, the addition of 1(wt %) OPEFB has increase the tree inception voltage of silicone rubber. So, OPEFB is a potential retardant to the initiation and growth of electrical treeing occurring in polymeric materials for high voltage application. However more studies on the effects of physical and electrical properties of OPEFB as a tree retardant material are required.

Keywords: Oil palm empty fruit bunch, electrical tree, siliconerubber, fillers.

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Authors: N. Zanganeh, M. Zabet

Abstract:

Lactulose is a synthetic disaccharide which has remarkable applications in food and pharmaceutical fields. Lactulose is not found in nature and it is produced by isomerization reaction of lactose in an alkaline environment. It should be noted that this reaction has a very low yield since significant amount of lactose stays un-reacted in the system. Basically, purification of lactulose is difficult and costly. Previous studies have revealed that solubility of lactose and lactulose are significantly different in ethanol. Considering the fact that solubility is also affected by temperature itself, we investigated the effect of ethanol and temperature on separation process of lactose from the syrup containing lactose and lactulose. For this purpose, a saturated solution containing lactulose and lactose was made at three different temperatures; 25⁰C (room temperature), 31⁰C, and 37⁰C first.  Five samples containing 2g saturated solution was taken and then 2g, 3g, 4g, 5g, and 6g ethanol separately was added to the sampling tubes. Sampling tubes were kept at respective temperatures afterward. The concentration of lactose and lactulose after separation process measured and analyzed by High Performance Liquid Chromatography (HPLC). Results showed that ethanol has such a greater impact than operating temperature on purification process. Also, it was observed that the maximum rate of separation occurred at initial amount of added ethanol.

Keywords: Ethanol, lactose, lactulose syrup, purification.

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Authors: Marjan Omranpour, Saeed Abbasi, Sohbat Bahraminejad

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White rust, caused by Albugo candida, is the most destructive foliar diseases of persian cress, Lepidium sativum in Iran. Application of fungicide is the most common method for the disease control. However, regarding the problems created by synthetic pesticides application, environmentally safe methods are needed to replace chemical pesticides. In this study, the antifungal activity of plant natural extracts was investigated for their ability to inhibit zoospore release from sporangia of A. candida. The crude extract of 46 plants was obtained using methanol. The inhibitory effect of the extracts was examined by mixing the plant extracts with a zoosporangial suspension of A. candida (1×106 spore/ml) at three concentrations, 250, 100 and 50 ppm. The experiments were conducted in a completely randomized design, with three replicates. The results of the experiment showed that three out of 46 plants species, including, Rhus coriaria, Anagallis arvensis and Mespilus germanica were completely inhibit zoospore release from zoosporangia of Albugo candida at concentration of 50 ppm.

Keywords: white rust, plant extract, Rhus coriaria, Anagallis arvensis and Mespilus germanica

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Authors: J. P. Dubois, O. M. Abdul-Latif

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Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of SAR (synthetic aperture radar) images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to real SAR images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected SAR images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (the detection hypotheses) in the original images.

Keywords: Least Square-Support Vector Machine, SyntheticAperture Radar. Partially Developed Speckle, Multi-Look Model.

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Authors: Akshaya Kumar Verma, Puspendu Bhunia*, Rajesh Roshan Dash

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Magnesium chloride, though cost wise roughly same as of ferrous sulphate, is less commonly used coagulant in comparison to the ferrous sulphate for the treatment of wastewater. The present study was conducted to investigate the comparative effectiveness of ferrous sulphate (FeSO4.7H2O) as iron based salt and magnesium chloride (MgCl2) as magnesium based salt in terms of decolorization and chemical oxygen demand (COD) reduction efficiency of textile wastewater. The coagulants were evaluated for synthetic textile wastewater containing two diazo dyes namely Reactive Black 5 (RB5) and Congo Red (CR) and one anthraquinone dye as Disperse Blue 3 (DB3), in seven possible equi-ratio combinations. Other chemical constituents that are normally released from different textile processing units were also added to replicate a practical scenario. From this study, MgCl2/Lime was found to be a superior coagulant system as compared to FeSO4.7H2O/Lime, FeSO4.7H2O/NaOH and MgCl2/NaOH.

Keywords: Coagulation, Color removal, Magnesium chloride, Textile wastewater

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Authors: Natthawan Likitmongkonsakun, Tawan Limpiyakorn

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17α-ethynylestradiol (EE2) is a synthetic estrogen used as a key ingredient in an oral contraceptives pill. EE2 is an endocrine disrupting compound, high in estrogenic potency. Although EE2 exhibits low degree of biodegradability with common microorganisms in wastewater treatment plants (WWTPs), this compound can be biotransformed by ammonia-oxidizing bacteria (AOB) via a co-metabolism mechanism in WWTPs. This study aimed to investigate the effect of real wastewater on biotransformation of EE2 by AOB. A preliminary experiment on the effect of nitrite and pH levels on abiotic transformation of EE2 suggested that the abiotic transformation occurred at only pH <6.8. Biotransformation of EE2 under the presence of municipal or industrial wastewater demonstrated that different types of wastewater affect EE2 biotransformation differently. Organic matters in wastewater were believed to deteriorate EE2 biotransformation via the competition effect. At a lower initial ammonium concentration, EE2 biotransformation can be retarded and the extent of the deterioration was COD-concentration dependent. However, when an initial ammonium concentration was elevated, thisphenomena disappeared. This is because when increasing the amount of the primary substrate, more AMO enzymes can be produced resulting in unlimited transformation of all compounds in the tests reducing the competitive effect of organic matters on EE2.

Keywords: 17α-ethynylestradiol, ammonia-oxidizing bacteria, nitrifying activated sludge, wastewater.

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Authors: Eka Maulana, Sholeh Hadi Pramono, Dody Fanditya, M. Julius

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In this paper, extract of papaya leaves are used as a natural dye and combined by variations of solvent concentration applied on DSSC (Dye-Sensitized Solar Cell). Indonesian geographic located on the equator line occasions the magnitude of the potential to develop organic solar cells made from extracts of chlorophyll as a substitute for inorganic materials or synthetic dye on DSSC material. Dye serves as absorbing photons which are then converted into electrical energy. A conductive coated glass layer called TCO (Transparent Conductive Oxide) is used as a substrate of electrode. TiO2 nanoparticles as binding dye molecules, redox couple iodide/ tri-iodide as the electrolyte and carbon as the counter electrode in the DSSC are used. TiO2 nanoparticles, organic dyes, electrolytes, and counter electrode are arranged and combined with the layered structure of the photo-catalyst absorption layer. Dye absorption measurements using a spectrophotometer at 400-800 nm light spectrum produces a total amount of chlorophyll 80.076 mg/l. The test cell at 7 watt LED light with 5000 lux luminescence was obtained Voc and Isc of 235.5 mV and 14 μA, respectively.

Keywords: DSSC (Dye-Sensitized Solar Cell), natural dye, chlorophyll, absorption.

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Authors: Rosarin Rujananon, Poonsuk Prasertsan, Amornrat Phongdara, Tanate Panrat, Jibin Sun, Sugima Rappert, An-Ping Zeng

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In this study, a synthetic pathway was created by assembling genes from Clostridium butyricum and Escherichia coli in different combinations. Among the genes were dhaB1 and dhaB2 from C. butyricum VPI1718 coding for glycerol dehydratase (GDHt) and its activator (GDHtAc), respectively, involved in the conversion of glycerol to 3-hydroxypropionaldehyde (3-HPA). The yqhD gene from E.coli BL21 was also included which codes for an NADPHdependent 1,3-propanediol oxidoreductase isoenzyme (PDORI) reducing 3-HPA to 1,3-propanediol (1,3-PD). Molecular modeling analysis indicated that the conformation of fusion protein of YQHD and DHAB1 was favorable for direct molecular channeling of the intermediate 3-HPA. According to the simulation results, the yqhD and dhaB1 gene were assembled in the upstream of dhaB2 to express a fusion protein, yielding the recombinant strain E. coliBL21 (DE3)//pET22b+::yqhD-dhaB1_dhaB2 (strain BP41Y3). Strain BP41Y3 gave 10-fold higher 1,3-PD concentration than E. coliBL21 (DE3)//pET22b+::yqhD-dhaB1_dhaB2 (strain BP31Y2) expressing the recombinant enzymes simultaneously but in a non-fusion mode. This is the first report using a gene fusion approach to enhance the biological conversion of glycerol to the value added compound 1,3- PD.

Keywords: Recombinant E.coli, 1, 3-propanediol, glycerol, fusion protein.

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Authors: Ririn Lestari Sri Rahayu, Mustofa Ahda

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The use of synthetic antioxidants often causes a negative effect on health and increases the incidence of carcinogenesis. Development of the natural antioxidants should be investigated. However, natural antioxidants have a low toxicity and are safe for human consumption. Ethanol extract of mangosteen rind (Garcinia mangostana) contains natural antioxidant compounds that have various pharmacological activities. Antioxidants from the ethanol extract of mangosteen rind have free radicals scavenging activities. The scavenging activity of ethanol extract of mangosteen rind was determined by DPPH method. The phenolic compound from the ethanol extract of mangosteen rind is determined with Folin-Ciocalteu method. The results showed that the absolute ethanol extract of mangosteen rind has IC₅₀ of 40.072 ug/mL. The correlation of total phenols content with free radical scavenging activity has an equation y: 5.207x + 205.51 and determination value (R²) of 0.9329. Total phenols content from the ethanol extract of mangosteen rind has a good correlation with free radicals scavenging activity of DPPH.

Keywords: Antioxidant, Garcinia mangostana, inhibition concentration 50%, total phenolic compounds.

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Authors: Z. Salleh, M. N. Berhan, Koay Mei Hyie, D. H. Isaac

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Natural fibres have emerged as the potential reinforcement material for composites and thus gain attraction by many researchers. This is mainly due to their applicable benefits as they offer low density, low cost, renewable, biodegradability and environmentally harmless and also comparable mechanical properties with synthetic fibre composites. The properties of hybrid composites highly depends on several factors, including the interaction of fillers with the polymeric matrix, shape and size (aspect ratio), and orientation of fillers [1]. In this study, natural fibre kenaf composites and kenaf/fibreglass hybrid composites were fabricated by a combination of hand lay-up method and cold-press method. The effect of different fibre types (powder, short and long) on the tensile properties of composites is investigated. The kenaf composites with and without the addition of fibreglass were then characterized by tensile testing and scanning electron microscopy. A significant improvement in tensile strength and modulus were indicated by the introduction of long kenaf/woven fibreglass hybrid composite. However, the opposite trends are observed in kenaf powder composite. Fractographic observation shows that fibre/matrix debonding causes the fibres pull out. This phenomenon results in the fibre and matrix fracture.

Keywords: Kenaf, Fibreglass, Hybrid Composite, Tensile Strength, Tensile Modulus.

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Authors: Jacqueline R. T. Alipo-on, Francesca I. F. Escobar, Myles J. T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

Abstract:

Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases which are considered as one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis on the ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heart beat types. The dataset used in this work is the synthetic MIT-Beth Israel Hospital (MIT-BIH) Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: Heartbeat classification, convolutional neural network, electrocardiogram signals, ECG signals, generative adversarial networks, long short-term memory, LSTM, ResNet-50.

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Authors: Iva Košek Bartošová

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There is great attention being paid in the field of development of first reading, thus early literacy skills in the Czech Republic. Yet inconclusive results of PISA and PIRLS force us to think over the teacher´s work, his/her roles in the education process and methods and forms used in lessons. There is also a significant importance to monitor the family environment and the pupil, themselves. The aim of the publishing output is to focus on one side dealing with methods of practicing reading technique and their results in the process of comprehension. In the first part of the contribution there are the goals of development of reading literacy and the methods used in reading practice in some EU countries and a follow-up comparison of research implemented by the help of modern technology of an eye tracker device in the year 2015 and a research conducted at the Institute of Education and Psychological Counselling of the Czech Republic in the year 2011/12. These are the results of a diagnostic test of reading in first classes of primary schools, taught by the genetic method and analytic-synthetic method. The results show that in the first stage of practice there are no statistically significant differences between any researched subjects taught by different methods of reading practice (with the use of several diagnostic texts focused on reading technique and its comprehension). Different results are shown at the end of Grade One and during Grade Two of primary school.

Keywords: Elementary literacy, eye tracker device, diagnostic reading tests, reading teaching method.

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Authors: Herlandson C. Moura, Jorge H. Bidinotto, Eduardo M. Belo

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The present work proposes the development of an adaptive control system which enables the suppression of Pilot Induced Oscillations (PIO) in Digital Fly-By-Wire (DFBW) aircrafts. The proposed system consists of a Modified Model Reference Adaptive Control (M-MRAC) integrated with the Gain Scheduling technique. The PIO oscillations are detected using a Real Time Oscillation Verifier (ROVER) algorithm, which then enables the system to switch between two reference models; one in PIO condition, with low proneness to the phenomenon and another one in normal condition, with high (or medium) proneness. The reference models are defined in a closed loop condition using the Linear Quadratic Regulator (LQR) control methodology for Multiple-Input-Multiple-Output (MIMO) systems. The implemented algorithms are simulated in software implementations with state space models and commercial flight simulators as the controlled elements and with pilot dynamics models. A sequence of pitch angles is considered as the reference signal, named as Synthetic Task (Syntask), which must be tracked by the pilot models. The initial outcomes show that the proposed system can detect and suppress (or mitigate) the PIO oscillations in real time before it reaches high amplitudes.

Keywords: Adaptive control, digital fly-by-wire, oscillations suppression, PIO.

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Authors: Mithilesh Singh, Rakhi Chaturvedi

Abstract:

Neem is a highly heterozygous and commercially important perennial plant. Conventionally, it is propagated by seeds which loose viability within two weeks. Strictly cross pollinating nature of the plant causes serious barrier to the genetic improvement by conventional methods. Alternative methods of tree improvement such as somatic hybridization, mutagenesis and genetic transformation require an efficient in vitro plant regeneration system. In this regard, somatic embryogenesis particularly secondary somatic embryogenesis may offer an effective system for large scale plant propagation without affecting the clonal fidelity of the regenerants. It can be used for synthetic seed production, which further bolsters conservation of this tree species which is otherwise very difficult The present report describes the culture conditions necessary to induce and maintain repetitive somatic embryogenesis, for the first time, in neem. Out of various treatments tested, the somatic embryos were induced directly from immature zygotic embryos of neem on MS + TDZ (0.1 μM) + ABA (4 μM), in more than 76 % cultures. Direct secondary somatic embryogenesis occurred from primary somatic embryos on MS + IAA (5 μM) + GA3 (5 μM) in 12.5 % cultures. Embryogenic competence of the explant as well as of the primary embryos was maintained for a long period by repeated subcultures at frequent intervals. A maximum of 10 % of these somatic embryos were converted into plantlets.

Keywords: Azadirachta indica A. Juss., Cytokinin, Somatic embryogenesis, zygotic embryo culture.

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Authors: Wei Zhang, Yao-Yu Li, Yi-Fan Zhu, Qun Li, Wei-Ping Wang

Abstract:

It-s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in the form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prior Knowledge, SPK). This paper explores the incorporation of SPK in SVR by constructing appropriate admissible support vector kernel (SV kernel) based on the properties of reproducing kernel (R.K). Three-levels specifications of SPK are studied with the corresponding sub-levels of prior knowledge that can be considered for the method. These include Hierarchical SPK (HSPK), Interactional SPK (ISPK) consisting of independence, global and local interaction, Functional SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A convenient tool for describing the SPK, namely Description Matrix of SPK is introduced. Subsequently, a new SVR, namely Motivated Support Vector Regression (MSVR) whose structure is motivated in part by SPK, is proposed. Synthetic examples show that it is possible to incorporate a wide variety of SPK and helpful to improve the approximation performance in complex cases. The benefits of MSVR are finally shown on a real-life military application, Air-toground battle simulation, which shows great potential for MSVR to the complex military applications.

Keywords: admissible support vector kernel, reproducing kernel, structural prior knowledge, motivated support vector regression

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Authors: Wei Zhang, Yao-Yu Li, Yi-Fan Zhu, Qun Li, Wei-Ping Wang

Abstract:

It-s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prior Knowledge, SPK). This paper explores the incorporation of SPK in SVR by constructing appropriate admissible support vector kernel (SV kernel) based on the properties of reproducing kernel (R.K). Three-levels specifications of SPK are studies with the corresponding sub-levels of prior knowledge that can be considered for the method. These include Hierarchical SPK (HSPK), Interactional SPK (ISPK) consisting of independence, global and local interaction, Functional SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A convenient tool for describing the SPK, namely Description Matrix of SPK is introduced. Subsequently, a new SVR, namely Motivated Support Vector Regression (MSVR) whose structure is motivated in part by SPK, is proposed. Synthetic examples show that it is possible to incorporate a wide variety of SPK and helpful to improve the approximation performance in complex cases. The benefits of MSVR are finally shown on a real-life military application, Air-toground battle simulation, which shows great potential for MSVR to the complex military applications.

Keywords: admissible support vector kernel, reproducing kernel, structural prior knowledge, motivated support vector regression

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

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Authors: Sanae Attioui, Said Najah

Abstract:

The Earth's surface is constantly changing through forces of nature and human activities. Reliable, accurate, and timely change detection is critical to environmental monitoring, resource management, and planning activities. Recently, interest in deep learning algorithms, especially convolutional neural networks, has increased in the field of image change detection due to their powerful ability to extract multi-level image features automatically. However, these networks are prone to drawbacks that limit their applications, which reside in their inability to capture spatial relationships between image instances, as this necessitates a large amount of training data. As an alternative, Capsule Network has been proposed to overcome these shortcomings. Although its effectiveness in remote sensing image analysis has been experimentally verified, its application in change detection tasks remains very sparse. Motivated by its greater robustness towards improved hierarchical object representation, this study aims to apply a capsule network for PolSAR image Change Detection. The experimental results demonstrate that the proposed change detection method can yield a significantly higher detection rate compared to methods based on convolutional neural networks.

Keywords: Change detection, capsule network, deep network, Convolutional Neural Networks, polarimetric synthetic aperture radar images, PolSAR images.

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Authors: J.-C. Cexus, A.O. Boudraa

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In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.

Keywords: Target recognition, Empirical mode decomposition, Teager-Kaiser energy operator, Features extraction.

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Authors: Dipti Patra, Mridula J

Abstract:

In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.

Keywords: Texture Image Segmentation, Gray Level Cooccurrence Matrix, Markov Random Field Model, Ohta colour space, ICM algorithm.

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Authors: Chong Wang, Kellem M. Soares, Luis E. Kosteski

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The problem of toughening in brittle materials reinforced by fibers is complex, involving all of the mechanical properties of fibers, matrix and the fiber/matrix interface, as well as the geometry of the fiber. Development of new numerical methods appropriate to toughening simulation and analysis is necessary. In this work, we have performed simulations and analysis of toughening in brittle matrix reinforced by randomly distributed fibers by means of the discrete elements method. At first, we put forward a mechanical model of toughening contributed by random fibers. Then with a numerical program, we investigated the stress, damage and bridging force in the composite material when a crack appeared in the brittle matrix. From the results obtained, we conclude that: (i) fibers of high strength and low elasticity modulus are beneficial to toughening; (ii) fibers of relatively high elastic modulus compared to the matrix may result in substantial matrix damage due to spalling effect; (iii) employment of high-strength synthetic fibers is a good option for toughening. We expect that the combination of the discrete element method (DEM) with the finite element method (FEM) can increase the versatility and efficiency of the software developed. The present work can guide the design of ceramic composites of high performance through the optimization of the parameters.

Keywords: Bridging stress, discrete element method, fiber reinforced composites, toughening.

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Authors: Eric S. Lee, Connie Bygrave, Jordan Mahar, Naina Garg, Suzanne Cottreau

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Marking exams is universally detested by lecturers. Final exams in many higher education courses often last 3.0 hrs. Do exams really need to be so long? Can we justifiably reduce the number of questions on them? Surprisingly few have researched these questions, arguably because of the complexity and difficulty of using traditional methods. To answer these questions empirically, we used a new approach based on three key elements: Use of an unusual variation of a true experimental design, equivalence hypothesis testing, and an expanded set of six psychometric criteria to be met by any shortened exam if it is to replace a current 3.0-hr exam (reliability, validity, justifiability, number of exam questions, correspondence, and equivalence). We compared student performance on each official 3.0-hr exam with that on five shortened exams having proportionately fewer questions (2.5, 2.0, 1.5, 1.0, and 0.5 hours) in a series of four experiments conducted in two classes in each of two finance courses (224 students in total). We found strong evidence that, in these courses, shortening of final exams to 2.0 hrs was warranted on all six psychometric criteria. Shortening these exams by one hour should result in a substantial one-third reduction in lecturer time and effort spent marking, lower student stress, and more time for students to prepare for other exams. Our approach provides a relatively simple, easy-to-use methodology that lecturers can use to examine the effect of shortening their own exams.

Keywords: Exam length, psychometric criteria, synthetic experimental designs, test length.

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