Search results for: maximum distance separable (MDS) matrix
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7890

Search results for: maximum distance separable (MDS) matrix

6900 The Effects of Plantation Size and Internal Transport on Energy Efficiency of Biofuel Production

Authors: Olga Orynycz, Andrzej Wasiak

Abstract:

Mathematical model describing energetic efficiency (defined as a ratio of energy obtained in the form of biofuel to the sum of energy inputs necessary to facilitate production) of agricultural subsystem as a function of technological parameters was developed. Production technology is characterized by parameters of machinery, topological characteristics of the plantation as well as transportation routes inside and outside of plantation. The relationship between the energetic efficiency of agricultural and industrial subsystems is also derived. Due to the assumed large area of the individual field, the operations last for several days increasing inter-fields routes because of several returns. The total distance driven outside of the fields is, however, small as compared to the distance driven inside of the fields. This results in small energy consumption during inter-fields transport that, however, causes a substantial decrease of the energetic effectiveness of the whole system.

Keywords: biofuel, energetic efficiency, EROEI, mathematical modelling, production system

Procedia PDF Downloads 334
6899 Millimeter-Wave Silicon Power Amplifiers for 5G Wireless Communications

Authors: Kyoungwoon Kim, Cuong Huynh, Cam Nguyen

Abstract:

Exploding demands for more data, faster data transmission speed, less interference, more users, more wireless devices, and better reliable service-far exceeding those provided in the current mobile communications networks in the RF spectrum below 6 GHz-has led the wireless communication industry to focus on higher, previously unallocated spectrums. High frequencies in RF spectrum near (around 28 GHz) or within the millimeter-wave regime is the logical solution to meet these demands. This high-frequency RF spectrum is of increasingly important for wireless communications due to its large available bandwidths that facilitate various applications requiring large-data high-speed transmissions, reaching up to multi-gigabit per second, of vast information. It also resolves the traffic congestion problems of signals from many wireless devices operating in the current RF spectrum (below 6 GHz), hence handling more traffic. Consequently, the wireless communication industries are moving towards 5G (fifth generation) for next-generation communications such as mobile phones, autonomous vehicles, virtual reality, and the Internet of Things (IoT). The U.S. Federal Communications Commission (FCC) proved on 14th July 2016 three frequency bands for 5G around 28, 37 and 39 GHz. We present some silicon-based RFIC power amplifiers (PA) for possible implementation for 5G wireless communications around 28, 37 and 39 GHz. The 16.5-28 GHz PA exhibits measured gain of more than 34.5 dB and very flat output power of 19.4±1.2 dBm across 16.5-28 GHz. The 25.5/37-GHz PA exhibits gain of 21.4 and 17 dB, and maximum output power of 16 and 13 dBm at 25.5 and 37 GHz, respectively, in the single-band mode. In the dual-band mode, the maximum output power is 13 and 9.5 dBm at 25.5 and 37 GHz, respectively. The 10-19/23-29/33-40 GHz PA has maximum output powers of 15, 13.3, and 13.8 dBm at 15, 25, and 35 GHz, respectively, in the single-band mode. When this PA is operated in dual-band mode, it has maximum output powers of 11.4/8.2 dBm at 15/25 GHz, 13.3/3 dBm at 15/35 GHz, and 8.7/6.7 dBm at 25/35 GHz. In the tri-band mode, it exhibits 8.8/5.4/3.8 dBm maximum output power at 15/25/35 GHz. Acknowledgement: This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors

Keywords: Microwaves, Millimeter waves, Power Amplifier, Wireless communications

Procedia PDF Downloads 167
6898 Interpretation and Clustering Framework for Analyzing ECG Survey Data

Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

Abstract:

As Indo-Pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

Procedia PDF Downloads 454
6897 Self-Sensing Concrete Nanocomposites for Smart Structures

Authors: A. D'Alessandro, F. Ubertini, A. L. Materazzi

Abstract:

In the field of civil engineering, Structural Health Monitoring is a topic of growing interest. Effective monitoring instruments permit the control of the working conditions of structures and infrastructures, through the identification of behavioral anomalies due to incipient damages, especially in areas of high environmental hazards as earthquakes. While traditional sensors can be applied only in a limited number of points, providing a partial information for a structural diagnosis, novel transducers may allow a diffuse sensing. Thanks to the new tools and materials provided by nanotechnology, new types of multifunctional sensors are developing in the scientific panorama. In particular, cement-matrix composite materials capable of diagnosing their own state of strain and tension, could be originated by the addition of specific conductive nanofillers. Because of the nature of the material they are made of, these new cementitious nano-modified transducers can be inserted within the concrete elements, transforming the same structures in sets of widespread sensors. This paper is aimed at presenting the results of a research about a new self-sensing nanocomposite and about the implementation of smart sensors for Structural Health Monitoring. The developed nanocomposite has been obtained by inserting multi walled carbon nanotubes within a cementitious matrix. The insertion of such conductive carbon nanofillers provides the base material with piezoresistive characteristics and peculiar sensitivity to mechanical modifications. The self-sensing ability is achieved by correlating the variation of the external stress or strain with the variation of some electrical properties, such as the electrical resistance or conductivity. Through the measurement of such electrical characteristics, the performance and the working conditions of an element or a structure can be monitored. Among conductive carbon nanofillers, carbon nanotubes seem to be particularly promising for the realization of self-sensing cement-matrix materials. Some issues related to the nanofiller dispersion or to the influence of the nano-inclusions amount in the cement matrix need to be carefully investigated: the strain sensitivity of the resulting sensors is influenced by such factors. This work analyzes the dispersion of the carbon nanofillers, the physical properties of the fresh dough, the electrical properties of the hardened composites and the sensing properties of the realized sensors. The experimental campaign focuses specifically on their dynamic characterization and their applicability to the monitoring of full-scale elements. The results of the electromechanical tests with both slow varying and dynamic loads show that the developed nanocomposite sensors can be effectively used for the health monitoring of structures.

Keywords: carbon nanotubes, self-sensing nanocomposites, smart cement-matrix sensors, structural health monitoring

Procedia PDF Downloads 215
6896 Comparison of Power Generation Status of Photovoltaic Systems under Different Weather Conditions

Authors: Zhaojun Wang, Zongdi Sun, Qinqin Cui, Xingwan Ren

Abstract:

Based on multivariate statistical analysis theory, this paper uses the principal component analysis method, Mahalanobis distance analysis method and fitting method to establish the photovoltaic health model to evaluate the health of photovoltaic panels. First of all, according to weather conditions, the photovoltaic panel variable data are classified into five categories: sunny, cloudy, rainy, foggy, overcast. The health of photovoltaic panels in these five types of weather is studied. Secondly, a scatterplot of the relationship between the amount of electricity produced by each kind of weather and other variables was plotted. It was found that the amount of electricity generated by photovoltaic panels has a significant nonlinear relationship with time. The fitting method was used to fit the relationship between the amount of weather generated and the time, and the nonlinear equation was obtained. Then, using the principal component analysis method to analyze the independent variables under five kinds of weather conditions, according to the Kaiser-Meyer-Olkin test, it was found that three types of weather such as overcast, foggy, and sunny meet the conditions for factor analysis, while cloudy and rainy weather do not satisfy the conditions for factor analysis. Therefore, through the principal component analysis method, the main components of overcast weather are temperature, AQI, and pm2.5. The main component of foggy weather is temperature, and the main components of sunny weather are temperature, AQI, and pm2.5. Cloudy and rainy weather require analysis of all of their variables, namely temperature, AQI, pm2.5, solar radiation intensity and time. Finally, taking the variable values in sunny weather as observed values, taking the main components of cloudy, foggy, overcast and rainy weather as sample data, the Mahalanobis distances between observed value and these sample values are obtained. A comparative analysis was carried out to compare the degree of deviation of the Mahalanobis distance to determine the health of the photovoltaic panels under different weather conditions. It was found that the weather conditions in which the Mahalanobis distance fluctuations ranged from small to large were: foggy, cloudy, overcast and rainy.

Keywords: fitting, principal component analysis, Mahalanobis distance, SPSS, MATLAB

Procedia PDF Downloads 127
6895 Investigation of Static Stability of Soil Slopes Using Numerical Modeling

Authors: Seyed Abolhasan Naeini, Elham Ghanbari Alamooti

Abstract:

Static stability of soil slopes using numerical simulation by a finite element code, ABAQUS, has been investigated, and safety factors of the slopes achieved in the case of static load of a 10-storey building. The embankments have the same soil condition but different loading distance from the slope heel. The numerical method for estimating safety factors is 'Strength Reduction Method' (SRM). Mohr-Coulomb criterion used in the numerical simulations. Two steps used for measuring the safety factors of the slopes: first is under gravity loading, and the second is under static loading of a building near the slope heel. These safety factors measured from SRM, are compared with the values from Limit Equilibrium Method, LEM. Results show that there is good agreement between SRM and LEM. Also, it is seen that by increasing the distance from slope heel, safety factors increases.

Keywords: limit equilibrium method, static stability, soil slopes, strength reduction method

Procedia PDF Downloads 144
6894 Using Q Methodology to Capture Attitudes about Academic Resilience in an Online Postgraduate Psychology Course

Authors: Eleanor F. Willard

Abstract:

The attrition rate on distance learning courses can be high. This research examines how online students often react when faced with poor results. Using q methodology, it was found that the emotional response level and the type of social support sought by students were key influences on their attitude to failure. As educational and psychological researchers, we are adept at measuring learning and achievement, but examining attitudes towards barriers to learning are not so well researched. The distance learning student has differing needs from onsite learners and, as the attrition rate is notoriously high in the online student population, examining learners’ attitude towards adversity and barriers is important. Self-report measures such as questionnaires are useful in terms of ascertaining levels of constructs such as resilience and academic confidence. Interviewing, too, can gain in depth detail of the opinions of such a population, but only in individuals. The aim of this research was to ascertain what the feelings and attitudes of online students were when faced with a setback. This was achieved using q methodology due to its use of both quantitative and qualitative methodology and its suitability for exploratory research. The emphasis with this methodology is the attitudes, not the individuals. The work was focused upon a population of distance learning students who attended a school on site for one week as part of their studies. They were engaged in a psychology masters conversion course and, as such, were graduate students. The Q sort had 30 items taken from the Academic Resilience Scale (ARS-30). The scale items represent three constructs; perseverance, reflecting (including adaptive help-seeking) and negative affect. These are widely acknowledged as being relevant concepts underpinning psychological resilience. The q sort was conducted with 19 students in total. This is done by participants arranging statement cards regarding how similar to themselves they believe each statement to be. This was done after reading a vignette describing an experience of academic failure. Commonalities and differences between the sorts from all participants are then analyzed in terms of correlations and response patterns. Following data collection, the participants' responses were initially analyzed and the key perspectives (factors) to emerge were labelled ‘persevering individuals’ and ‘emotional networkers’. The differences between the two perspectives centre around the level of emotion felt when faced with barriers and the extent that students enlist the help of others inside and outside of the university. The dominant factor to emerge from the sorts of ‘persevering individuals’ demonstrated that many distance learners are tenacious. However, for other students, the level of emotional and social support is pivotal in helping them complete their studies when facing adversity. This was demonstrated by the ‘emotional networkers’ perspective. This research forms a starting point for further work on engaging and retaining online students at university and can potentially provide insight into how universities can lower attrition rates on distance learning courses.

Keywords: academic resilience, distance learning, online learning, q methodology

Procedia PDF Downloads 112
6893 Analysis of ECGs Survey Data by Applying Clustering Algorithm

Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

Abstract:

As Indo-pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring the prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

Procedia PDF Downloads 338
6892 Corrosion Behavior of Austempered Ductile Iron Microalloyed with Boron in Rainwater

Authors: S. Gvazava, N. Khidasheli, V. Tediashvili, M. Donadze

Abstract:

The work presented in this paper studied the of austempered ductile iron (ADI) with different combinations of structural composition (upper bainite, lower bainite, retained austenite) in rainwater. A range of structural states of the metal matrix was obtained by changing the regimes of thermal treantments of a high-strength cast iron. The specimens were austenised at 900 0C for 30, 60, 90, 120 minutes. Afterwards, isothermal quenching was performed at 280 and 400 0C for40 seconds. The study was carried out using weight-change (WC), cyclic potentiodynamic polarization (CPP), open-circuit potential (OCP), and electrochemical impedance spectroscopy (EIS) measurements and complemented by scanning electron microscopy (SEM-EDS). According to the results, corrosion resistance of the boron microallyedbainitic ADI greatly depends on the type of the bainitic matrix and the amount of the retained austenite, which is driven by diffusion permeability of interphase and intergrain boundaries.

Keywords: austempered ductile iron, corrosion behaviour, retained austenite, corrosion rate, interphase boundary, upper bainite, lower bainite

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6891 Thermal Stability and Crystallization Behaviour of Modified ABS/PP Nanocomposites

Authors: Marianna I. Triantou, Petroula A. Tarantili

Abstract:

In this research work, poly (acrylonitrile-butadiene-styrene)/polypropylene (ABS/PP) blends were processed by melt compounding in a twin-screw extruder. Upgrading of the thermal characteristics of the obtained materials was attempted by the incorporation of organically modified montmorillonite (OMMT), as well as, by the addition of two types of compatibilizers; polypropylene grafted with maleic anhydride (PP-g-MAH) and ABS grafted with maleic anhydride (ABS-g-MAH). The effect of the above treatments was investigated separately and in combination. Increasing the PP content in ABS matrix seems to increase the thermal stability of their blend and the glass transition temperature (Tg) of SAN phase of ABS. From the other part, the addition of ABS to PP promotes the formation of its β-phase, which is maximum at 30 wt% ABS concentration, and increases the crystallization temperature (Tc) of PP. In addition, it increases the crystallization rate of PP.The β-phase of PP in ABS/PP blends is reduced by the addition of compatibilizers or/and organoclay reinforcement. The incorporation of compatibilizers increases the thermal stability of PP and reduces its melting (ΔΗm) and crystallization (ΔΗc) enthalpies. Furthermore it decreases slightly the Tgs of PP and SAN phases of ABS/PP blends. Regarding the storage modulus of the ABS/PP blends, it presents a change in their behavior at about 10°C and return to their initial behavior at ~110°C. The incorporation of OMMT to no compatibilized and compatibilized ABS/PP blends enhances their storage modulus.

Keywords: acrylonitrile, butadiene, styrene terpolymer, compatibilizer, organoclay, polypropylene

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6890 Methane versus Carbon Dioxide Mitigation Prospects

Authors: Alexander J. Severinsky, Allen L. Sessoms

Abstract:

Atmospheric carbon dioxide (CO₂) has dominated the discussion about the causes of climate change. This is a reflection of the time horizon that has become the norm adopted by the IPCC as the planning horizon. Recently, it has become clear that a 100-year time horizon is much too long, and yet almost all mitigation efforts, including those in the near-term horizon of 30 years, are geared toward it. In this paper, we show that, for a 30-year time horizon, methane (CH₄) is the greenhouse gas whose radiative forcing exceeds that of CO₂. In our analysis, we used radiative forcing of greenhouse gases in the atmosphere since they directly affect the temperature rise on Earth. In 2019, the radiative forcing of methane was ~2.5 W/m² and that of carbon dioxide ~2.1 W/m². Under a business-as-usual (BAU) scenario until 2050, such forcing would be ~2.8 W/m² and ~3.1 W/m², respectively. There is a substantial spread in the data for anthropogenic and natural methane emissions as well as CH₄ leakages from production to consumption. We estimated the minimum and maximum effects of the reduction of these leakages. Such action may reduce the annual radiative forcing of all CH₄ emissions by between ~15% and ~30%. This translates into a reduction of the RF by 2050 from ~2.8 W/m² to ~2.5 W/m² in the case of the minimum effect and to ~2.15 W/m² in the case of the maximum. Under the BAU, we found that the RF of CO₂ would increase from ~2.1 W/m² nowadays to ~3.1 W/m² by 2050. We assumed a reduction of 50% of anthropogenic emission linearly over the next 30 years. That would reduce radiative forcing from ~3.1 W/m² to ~2.9 W/m². In the case of ‘net zero,’ the other 50% of reduction of only anthropogenic emissions would be limited to either from sources of emissions or directly from the atmosphere. The total reduction would be from ~3.1 to ~2.7, or ~0.4 W/m². To achieve the same radiative forcing as in the scenario of maximum reduction of methane leakages of ~2.15 W/m², then an additional reduction of radiative forcing of CO₂ would be approximately 2.7 -2.15=0.55 W/m². This is a much larger value than in expectations from ‘net zero’. In total, one needs to remove from the atmosphere ~660 GT to match the maximum reduction of current methane leakages and ~270 GT to achieve ‘net zero.’ This amounts to over 900 GT in total.

Keywords: methane leakages, methane radiative forcing, methane mitigation, methane net zero

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6889 The Effects of Food Matrix and Different Excipient Foods on β-Carotene Bioaccessibility in Carrots

Authors: Birgul Hizlar, Sibel Karakaya

Abstract:

Nowadays, consumers are more and more aware of the benefits beyond basic nutrition provided by food and food compounds. Between these, carotenoids have been demonstrated to exhibit multiple health benefits (for example, some types of cancer, cardiovascular diseases, eye disorders, among others). However, carotenoid bioaccessibility and bioavailability is generally rather low due to their specific localization in plant tissue and lipophilic nature. This situation is worldwide issue, since both developed and developing countries have their interest and benefits in increasing the uptake of carotenoids from the human diet. Recently, a new class of foods designed to improve the bioaccessibility/bioavailability of orally administered bioactive compounds is introduced: excipient foods. Excipient foods are specially designed foods which are prepared depending on the physicochemical properties of target bioactive compounds and increasing the bioavailability or bioaccessibility of bioactive compound. In this study, effects of food matrix (greating, boiling and mashing) and different excipient foods (olive oil, lemon juice, whey curd and dried artichoke leaf powder) on bioaccessibility of β-carotene in carrot were investigated by means of simulating in vitro gastrointestinal (GI) digestion. β-carotene contents of grated, boiled and mashed (after boiling process) carrots were 79.28, 147.63 and 151.19 μg/g respectively. No significant differences among boiled and mashed samples indicated that mashing process had no effect on the release of β-carotene from the food matrix (p > 0.05). On the contrary, mashing causes significant increase in the β-carotene bioaccessibility (p < 0.05). The highest β-carotene content was found in the mashed carrots incorporated with olive oil and lemon juice (C2). However, no significant differences between that sample and C1 (mashed carrot with lemon juice, olive oil, dried artichoke leaf powder), C3 (mashed carrot with addition of olive oil, lemon juice, whey curd) and). Similarly, the highest β-carotene bioaccessibility (50.26%) was found mashed C3 sample (p < 0.05). The increase in the bioaccessibility was approximately 5 fold and 50 fold when compared to grated and mashed samples containing olive oil, lemon juice and whey curd. The results demonstrate that both, food matrix and excipient foods, are able to increase the bioaccessibility of β-carotene.

Keywords: bioaccessibility, carotenoids, carrot, β-carotene

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6888 Sparse Unmixing of Hyperspectral Data by Exploiting Joint-Sparsity and Rank-Deficiency

Authors: Fanqiang Kong, Chending Bian

Abstract:

In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation

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6887 Post-Processing Method for Performance Improvement of Aerial Image Parcel Segmentation

Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

Abstract:

In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

Procedia PDF Downloads 63
6886 Acceleration-Based Motion Model for Visual Simultaneous Localization and Mapping

Authors: Daohong Yang, Xiang Zhang, Lei Li, Wanting Zhou

Abstract:

Visual Simultaneous Localization and Mapping (VSLAM) is a technology that obtains information in the environment for self-positioning and mapping. It is widely used in computer vision, robotics and other fields. Many visual SLAM systems, such as OBSLAM3, employ a constant-speed motion model that provides the initial pose of the current frame to improve the speed and accuracy of feature matching. However, in actual situations, the constant velocity motion model is often difficult to be satisfied, which may lead to a large deviation between the obtained initial pose and the real value, and may lead to errors in nonlinear optimization results. Therefore, this paper proposed a motion model based on acceleration, which can be applied on most SLAM systems. In order to better describe the acceleration of the camera pose, we decoupled the pose transformation matrix, and calculated the rotation matrix and the translation vector respectively, where the rotation matrix is represented by rotation vector. We assume that, in a short period of time, the changes of rotating angular velocity and translation vector remain the same. Based on this assumption, the initial pose of the current frame is estimated. In addition, the error of constant velocity model was analyzed theoretically. Finally, we applied our proposed approach to the ORBSLAM3 system and evaluated two sets of sequences on the TUM dataset. The results showed that our proposed method had a more accurate initial pose estimation and the accuracy of ORBSLAM3 system is improved by 6.61% and 6.46% respectively on the two test sequences.

Keywords: error estimation, constant acceleration motion model, pose estimation, visual SLAM

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6885 A Minimum Spanning Tree-Based Method for Initializing the K-Means Clustering Algorithm

Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang

Abstract:

The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Keywords: degree, initial cluster center, k-means, minimum spanning tree

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6884 Efficacy of Collagen Matrix Implants in Phacotrabeculectomy with Mitomycin C at One Year

Authors: Lalit Tejwani, Reetika Sharma, Arun Singhvi, Himanshu Shekhar

Abstract:

Purpose: To assess the efficacy of collagen matrix implant (Ologen) in phacotrabeculectomy augmented with mitomycin C (MMC). Methods: A biodegradable collagen matrix (Ologen) was placed in the subconjunctival and subscleral space in twenty-two eyes of 22 patients with glaucoma and cataract who underwent combined phacoemulsification and trabeculectomy augmented with MMC. All of them were examined preoperatively and on the first postoperative day. They were followed for twelve months after surgery. Any intervention needed in follow-up period was noted. Any complication was recorded. The primary outcome measure was postoperative intraocular pressure at one year follow-up. Any additional postoperative treatments needed and adverse events were noted. Results: The mean age of patients included in the study was 57.77 ± 9.68 years (range=36 to 70 years). All the patients were followed for at least one year. Three patients had history of failed trabeculectomy. Fifteen patients had chronic angle closure glaucoma with cataract, five had primary open angle glaucoma with cataract, one had uveitic glaucoma with cataract, and one had juvenile open angle glaucoma with cataract. Mean preoperative IOP was 32.63 ± 8.29 mm Hg, eighteen patients were on oral antiglaucoma medicines. The mean postoperative IOP was 10.09 ± 2.65 mm Hg at three months, 10.36 ± 2.19 mm Hg at six months and 11.36 ± 2.72 mm Hg at one year follow up. No adverse effect related to Ologen was seen. Anterior chamber reformation was done in five patients, and three needed needling of bleb. Four patients needed additional antiglaucoma medications in the follow-up period. Conclusions: Combined phacotrabeculectomy with MMC with Ologen implantation appears to be a safe and effective option in glaucoma patients needing trabeculectomy with significant cataract. Comparative studies with longer duration of follow-up in larger number of patients are needed.

Keywords: combined surgery, ologen, phacotrabeculectomy, success

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6883 Selecting the Best Sub-Region Indexing the Images in the Case of Weak Segmentation Based on Local Color Histograms

Authors: Mawloud Mosbah, Bachir Boucheham

Abstract:

Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Keywords: CBIR, color global histogram, color local histogram, weak segmentation, Euclidean distance

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6882 Characterization of Articular Cartilage Based on the Response of Cartilage Surface to Loading/Unloading

Authors: Z. Arabshahi, I. Afara, A. Oloyede, H. Moody, J. Kashani, T. Klein

Abstract:

Articular cartilage is a fluid-swollen tissue of synovial joints that functions by providing a lubricated surface for articulation and to facilitate the load transmission. The biomechanical function of this tissue is highly dependent on the integrity of its ultrastructural matrix. Any alteration of articular cartilage matrix, either by injury or degenerative conditions such as osteoarthritis (OA), compromises its functional behaviour. Therefore, the assessment of articular cartilage is important in early stages of degenerative process to prevent or reduce further joint damage with associated socio-economic impact. Therefore, there has been increasing research interest into the functional assessment of articular cartilage. This study developed a characterization parameter for articular cartilage assessment based on the response of cartilage surface to loading/unloading. This is because the response of articular cartilage to compressive loading is significantly depth-dependent, where the superficial zone and underlying matrix respond differently to deformation. In addition, the alteration of cartilage matrix in the early stages of degeneration is often characterized by PG loss in the superficial layer. In this study, it is hypothesized that the response of superficial layer is different in normal and proteoglycan depleted tissue. To establish the viability of this hypothesis, samples of visually intact and artificially proteoglycan-depleted bovine cartilage were subjected to compression at a constant rate to 30 percent strain using a ring-shaped indenter with an integrated ultrasound probe and then unloaded. The response of articular surface which was indirectly loaded was monitored using ultrasound during the time of loading/unloading (deformation/recovery). It was observed that the rate of cartilage surface response to loading/unloading was different for normal and PG-depleted cartilage samples. Principal Component Analysis was performed to identify the capability of the cartilage surface response to loading/unloading, to distinguish between normal and artificially degenerated cartilage samples. The classification analysis of this parameter showed an overlap between normal and degenerated samples during loading. While there was a clear distinction between normal and degenerated samples during unloading. This study showed that the cartilage surface response to loading/unloading has the potential to be used as a parameter for cartilage assessment.

Keywords: cartilage integrity parameter, cartilage deformation/recovery, cartilage functional assessment, ultrasound

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6881 Solar-Powered Adsorption Cooling System: A Case Study on the Climatic Conditions of Al Minya

Authors: El-Sadek H. Nour El-deen, K. Harby

Abstract:

Energy saving and environment friendly applications are turning out to be one of the most important topics nowadays. In this work, a simulation analysis using TRNSYS software has been carried out to study the benefit of employing a solar adsorption cooling system under the climatic conditions of Al-Minya city, Egypt. A theoretical model was carried out on a two bed adsorption cooling system employing granular activated carbon-HFC-404A as working pair. Temporal and averaged history of solar collector, adsorbent beds, evaporator and condenser has been shown. System performance in terms of daily average cooling capacity and average coefficient of performance around the year has been investigated. The results showed that maximum yearly average coefficient of performance (COP) and cooling capacity are about 0.26 and 8 kW respectively. The maximum value of the both average cooling capacity and COP cyclic is directly proportional to the maximum solar radiation. The system performance was found to be increased with the average ambient temperature. Finally, the proposed solar powered adsorption cooling systems can be used effectively under Al-Minya climatic conditions.

Keywords: adsorption, cooling, Egypt, environment, solar energy

Procedia PDF Downloads 147
6880 QI Wireless Charging a Scope of Magnetic Inductive Coupling

Authors: Sreenesh Shashidharan, Umesh Gaikwad

Abstract:

QI or 'Chee' which is an interface standard for inductive electrical power transfer over distances of up to 4 cm (1.6 inches). The Qi system comprises a power transmission pad and a compatible receiver in a portable device which is placed on top of the power transmission pad, which charges using the principle of electromagnetic induction. An alternating current is passed through the transmitter coil, generating a magnetic field. This, in turn, induces a voltage in the receiver coil; this can be used to power a mobile device or charge a battery. The efficiency of the power transfer depends on the coupling (k) between the inductors and their quality (Q) The coupling is determined by the distance between the inductors (z) and the relative size (D2 /D). The coupling is further determined by the shape of the coils and the angle between them. If the receiver coil is at a certain distance to the transmitter coil, only a fraction of the magnetic flux, which is generated by the transmitter coil, penetrates the receiver coil and contributes to the power transmission. The more flux reaches the receiver, the better the coils are coupled.

Keywords: inductive electric power, electromagnetic induction, magnetic flux, coupling

Procedia PDF Downloads 717
6879 Phylogenetic Relationships of the Malaysian Primates Cercopithecine Based on COI Gene Sequences

Authors: B. M. Md-Zain, N. A. Rahman, M. A. B. Abdul-Latiff, W. M. R. Idris

Abstract:

We conducted molecular research to portray phylogenetic relationships of Malaysian primates particularly in the genus of Macaca. We have sequenced cytochrome C oxidase subunit I (COI) of mitochondrial DNA of several individuals from M. fascicularis and M. arctoides. PCR amplifications were performed and COI DNA sequences were aligned using ClustalW. Phylogenetic trees were constructed using distance analyses by employing neighbor-joining algorithm (NJ). We managed to sequence 700 bp of COI DNA sequences. The tree topology showed that M. fascicularis did not clump based on phyleogeography division in Peninsular Malaysia. Individuals from Negeri Sembilan merged together with samples from Perak and Penang into one clade. In addition, phylogenetic analyses indicated that M. arctoides was classified into sinica group instead of fascicularis group supported by genetic distance data. COI gene is an effective locus to clarify phylogenetic position of M. arctoides but not in discriminating M. fascicularis population in Peninsular Malaysia.

Keywords: cercopithecine, long-tailed macaque, Macaca fascicularis, Macaca arctoides

Procedia PDF Downloads 342
6878 An Estimating Parameter of the Mean in Normal Distribution by Maximum Likelihood, Bayes, and Markov Chain Monte Carlo Methods

Authors: Autcha Araveeporn

Abstract:

This paper is to compare the parameter estimation of the mean in normal distribution by Maximum Likelihood (ML), Bayes, and Markov Chain Monte Carlo (MCMC) methods. The ML estimator is estimated by the average of data, the Bayes method is considered from the prior distribution to estimate Bayes estimator, and MCMC estimator is approximated by Gibbs sampling from posterior distribution. These methods are also to estimate a parameter then the hypothesis testing is used to check a robustness of the estimators. Data are simulated from normal distribution with the true parameter of mean 2, and variance 4, 9, and 16 when the sample sizes is set as 10, 20, 30, and 50. From the results, it can be seen that the estimation of MLE, and MCMC are perceivably different from the true parameter when the sample size is 10 and 20 with variance 16. Furthermore, the Bayes estimator is estimated from the prior distribution when mean is 1, and variance is 12 which showed the significant difference in mean with variance 9 at the sample size 10 and 20.

Keywords: Bayes method, Markov chain Monte Carlo method, maximum likelihood method, normal distribution

Procedia PDF Downloads 343
6877 Microstructure and Mechanical Evaluation of PMMA/Al₂O₃ Nanocomposite Fabricated via Friction Stir Processing

Authors: Reham K. El Sawah, N. S. M. El-Tayeb

Abstract:

This study aims to produce a polymer matrix composite reinforced with Al₂O₃ nanoparticles in order to enhance the mechanical properties of PMMA. The composite was fabricated via Friction stir processing to ensure homogenous dispersion of Al₂O₃ nanoparticles in the polymer, and the processing was submerged to prevent the sputtering of nanoparticles. The surface quality, microstructure, impact energy and hardness of the prepared samples were investigated. Good surface quality and dispersion of nanoparticles were attained through employing sufficient processing conditions. The experimental results indicated that as the percentage of nanoparticles increased, the impact energy and hardness increased, reaching 2 kJ/m2 and 14.7 HV at a nanoparticle concentration of 25%, which means that the toughness and the hardness of the polymer-ceramic produced composite is higher than unprocessed PMMA by 66% and 33% respectively.

Keywords: friction stir processing, polymer matrix nanocomposite, mechanical properties, microstructure

Procedia PDF Downloads 153
6876 Bayesian Using Markov Chain Monte Carlo and Lindley's Approximation Based on Type-I Censored Data

Authors: Al Omari Moahmmed Ahmed

Abstract:

These papers describe the Bayesian Estimator using Markov Chain Monte Carlo and Lindley’s approximation and the maximum likelihood estimation of the Weibull distribution with Type-I censored data. The maximum likelihood method can’t estimate the shape parameter in closed forms, although it can be solved by numerical methods. Moreover, the Bayesian estimates of the parameters, the survival and hazard functions cannot be solved analytically. Hence Markov Chain Monte Carlo method and Lindley’s approximation are used, where the full conditional distribution for the parameters of Weibull distribution are obtained via Gibbs sampling and Metropolis-Hastings algorithm (HM) followed by estimate the survival and hazard functions. The methods are compared to Maximum Likelihood counterparts and the comparisons are made with respect to the Mean Square Error (MSE) and absolute bias to determine the better method in scale and shape parameters, the survival and hazard functions.

Keywords: weibull distribution, bayesian method, markov chain mote carlo, survival and hazard functions

Procedia PDF Downloads 462
6875 Autonomous Ground Vehicle Navigation Based on a Single Camera and Image Processing Methods

Authors: Auday Al-Mayyahi, Phil Birch, William Wang

Abstract:

A vision system-based navigation for autonomous ground vehicle (AGV) equipped with a single camera in an indoor environment is presented. A proposed navigation algorithm has been utilized to detect obstacles represented by coloured mini- cones placed in different positions inside a corridor. For the recognition of the relative position and orientation of the AGV to the coloured mini cones, the features of the corridor structure are extracted using a single camera vision system. The relative position, the offset distance and steering angle of the AGV from the coloured mini-cones are derived from the simple corridor geometry to obtain a mapped environment in real world coordinates. The corridor is first captured as an image using the single camera. Hence, image processing functions are then performed to identify the existence of the cones within the environment. Using a bounding box surrounding each cone allows to identify the locations of cones in a pixel coordinate system. Thus, by matching the mapped and pixel coordinates using a projection transformation matrix, the real offset distances between the camera and obstacles are obtained. Real time experiments in an indoor environment are carried out with a wheeled AGV in order to demonstrate the validity and the effectiveness of the proposed algorithm.

Keywords: autonomous ground vehicle, navigation, obstacle avoidance, vision system, single camera, image processing, ultrasonic sensor

Procedia PDF Downloads 287
6874 Different Data-Driven Bivariate Statistical Approaches to Landslide Susceptibility Mapping (Uzundere, Erzurum, Turkey)

Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

Abstract:

The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

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6873 Residual Stress Around Embedded Particles in Bulk YBa2Cu3Oy Samples

Authors: Anjela Koblischka-Veneva, Michael R. Koblischka

Abstract:

To increase the flux pinning performance of bulk YBa2Cu3O7-δ (YBCO or Y-123) superconductors, it is common to employ secondary phase particles, either Y2BaCuO5 (Y-211) particles created during the growth of the samples or additionally added (nano)particles of various types, embedded in the superconducting Y-123 matrix. As the crystallographic parameters of all the particles indicate a misfit to Y-123, there will be residual strain within the Y-123 matrix around such particles. With a dedicated analysis of electron backscatter diffraction (EBSD) data obtained on various bulk, Y-123 superconductor samples, the strain distribution around such embedded secondary phase particles can be revealed. The results obtained are presented in form of Kernel Average Misorientation (KAM) mappings. Around large Y-211 particles, the strain can be so large that YBCO subgrains are formed. Therefore, it is essential to properly control the particle size as well as their distribution within the bulk sample to obtain the best performance. The impact of the strain distribution on the flux pinning properties is discussed.

Keywords: Bulk superconductors, EBSD, Strain, YBa2Cu3Oy

Procedia PDF Downloads 135
6872 Flexural Properties of Carbon/Polypropylene Composites: Influence of Matrix Forming Polypropylene in Fiber, Powder, and Film States

Authors: Vijay Goud, Ramasamy Alagirusamy, Apurba Das, Dinesh Kalyanasundaram

Abstract:

Thermoplastic composites render new opportunities as effective processing technology while crafting newer complications into processing. One of the notable challenges is in achieving thorough wettability that is significantly deterred by the high viscosity of the long molecular chains of the thermoplastics. As a result of high viscosity, it is very difficult to impregnate the resin into a tightly interlaced textile structure to fill the voids present in the structure. One potential solution to the above problem, is to pre-deposit resin on the fiber, prior to consolidation. The current study compares DREF spinning, powder coating and film stacking methods of predeposition of resin onto fibers. An investigation into the flexural properties of unidirectional composites (UDC) produced from blending of carbon fiber and polypropylene (PP) matrix in varying forms of fiber, powder and film are reported. Dr. Ernst Fehrer (DREF) yarns or friction spun hybrid yarns were manufactured from PP fibers and carbon tows. The DREF yarns were consolidated to yield unidirectional composites (UDCs) referred to as UDC-D. PP in the form of powder was coated on carbon tows by electrostatic spray coating. The powder-coated towpregs were consolidated to form UDC-P. For the sake of comparison, a third UDC referred as UDC-F was manufactured by the consolidation of PP films stacked between carbon tows. The experiments were designed to yield a matching fiber volume fraction of about 50 % in all the three UDCs. A comparison of mechanical properties of the three composites was studied to understand the efficiency of matrix wetting and impregnation. Approximately 19% and 68% higher flexural strength were obtained for UDC-P than UDC-D and UDC-F respectively. Similarly, 25% and 81% higher modulus were observed in UDC-P than UDC-D and UDC-F respectively. Results from micro-computed tomography, scanning electron microscopy, and short beam tests indicate better impregnation of PP matrix in UDC-P obtained through electrostatic spray coating process and thereby higher flexural strength and modulus.

Keywords: DREF spinning, film stacking, flexural strength, powder coating, thermoplastic composite

Procedia PDF Downloads 212
6871 Effect of Surface Treatment on Physico-Mechanical Properties of Sisal Fiber-Unsaturated Polyester Composites

Authors: A. H. Birniwa, A. A. Salisu, M. Y. Yakasai, A. Sabo, K. Aujara, A. Isma’il

Abstract:

Sisal fibre was extracted from Sisal leaves by enzymatic retting method. A portion of the fibre was subjected to treatment with alkali, benzoyl chloride and silane compounds. Sisal fibre composites were fabricated using unsaturated polyester resin, by hand lay-up technique using both the treated and untreated fibre. Tensile, flexural and water absorption tests were conducted and evaluated on the composites. The results obtained were found to increase in the treated fibre compared to untreated fibre. Surface morphology of the fibre was observed using scanning electron microscopy (SEM) and the result obtained showed variation in the morphology of the treated and untreated fibre. FT-IR results showed inclusion of benzoyl and silane groups on the fibre surface. The fibre chemical modification improves its adhesion to the matrix, mechanical properties of the composites were also found to improve.

Keywords: composite, flexural strength, matrix, sisal fibre

Procedia PDF Downloads 375