Search results for: angle classification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3500

Search results for: angle classification

1400 Human Bone Marrow Stem Cell Behavior on 3D Printed Scaffolds as Trabecular Bone Grafts

Authors: Zeynep Busra Velioglu, Deniz Pulat, Beril Demirbakan, Burak Ozcan, Ece Bayrak, Cevat Erisken

Abstract:

Bone tissue has the ability to perform a wide array of functions including providing posture, load-bearing capacity, protection for the internal organs, initiating hematopoiesis, and maintaining the homeostasis of key electrolytes via calcium/phosphate ion storage. The most common cause for bone defects is extensive trauma and subsequent infection. Bone tissue has the self-healing capability without a scar tissue formation for the majority of the injuries. However, some may result with delayed union or fracture non-union. Such cases include reconstruction of large bone defects or cases of compromised regenerative process as a result of avascular necrosis and osteoporosis. Several surgical methods exist to treat bone defects, including Ilizarov method, Masquelete technique, growth factor stimulation, and bone replacement. Unfortunately, these are technically demanding and come with noteworthy disadvantages such as lengthy treatment duration, adverse effects on the patient’s psychology, repeated surgical procedures, and often long hospitalization times. These limitations associated with surgical techniques make bone substitutes an attractive alternative. Here, it was hypothesized that a 3D printed scaffold will mimic trabecular bone in terms of biomechanical properties and that such scaffolds will support cell attachment and survival. To test this hypothesis, this study aimed at fabricating poly(lactic acid), PLA, structures using 3D printing technology for trabecular bone defects, characterizing the scaffolds and comparing with bovine trabecular bone. Capacity of scaffolds on human bone marrow stem cell (hBMSC) attachment and survival was also evaluated. Cubes with a volume of 1 cm³ having pore sizes of 0.50, 1.00 and 1.25 mm were printed. The scaffolds/grafts were characterized in terms of porosity, contact angle, compressive mechanical properties as well cell response. Porosities of the 3D printed scaffolds were calculated based on apparent densities. For contact angles, 50 µl distilled water was dropped over the surface of scaffolds, and contact angles were measured using ‘Image J’ software. Mechanical characterization under compression was performed on scaffolds and native trabecular bone (bovine, 15 months) specimens using a universal testing machine at a rate of 0.5mm/min. hBMSCs were seeded onto the 3D printed scaffolds. After 3 days of incubation with fully supplemented Dulbecco’s modified Eagle’s medium, the cells were fixed using 2% formaldehyde and glutaraldehyde mixture. The specimens were then imaged under scanning electron microscopy. Cell proliferation was determined by using EZQuant dsDNA Quantitation kit. Fluorescence was measured using microplate reader Spectramax M2 at the excitation and emission wavelengths of 485nm and 535nm, respectively. Findings suggested that porosity of scaffolds with pore dimensions of 0.5mm, 1.0mm and 1.25mm were not affected by pore size, while contact angle and compressive modulus decreased with increasing pore size. Biomechanical characterization of trabecular bone yielded higher modulus values as compared to scaffolds with all pore sizes studied. Cells attached and survived in all surfaces, demonstrating higher proliferation on scaffolds with 1.25mm pores as compared with those of 1mm. Collectively, given lower mechanical properties of scaffolds as compared to native bone, and biocompatibility of the scaffolds, the 3D printed PLA scaffolds of this study appear as candidate substitutes for bone repair and regeneration.

Keywords: 3D printing, biomechanics, bone repair, stem cell

Procedia PDF Downloads 169
1399 Traffic Light Detection Using Image Segmentation

Authors: Vaishnavi Shivde, Shrishti Sinha, Trapti Mishra

Abstract:

Traffic light detection from a moving vehicle is an important technology both for driver safety assistance functions as well as for autonomous driving in the city. This paper proposed a deep-learning-based traffic light recognition method that consists of a pixel-wise image segmentation technique and a fully convolutional network i.e., UNET architecture. This paper has used a method for detecting the position and recognizing the state of the traffic lights in video sequences is presented and evaluated using Traffic Light Dataset which contains masked traffic light image data. The first stage is the detection, which is accomplished through image processing (image segmentation) techniques such as image cropping, color transformation, segmentation of possible traffic lights. The second stage is the recognition, which means identifying the color of the traffic light or knowing the state of traffic light which is achieved by using a Convolutional Neural Network (UNET architecture).

Keywords: traffic light detection, image segmentation, machine learning, classification, convolutional neural networks

Procedia PDF Downloads 166
1398 Nutrient in River Ecosystems Follows Human Activities More Than Climate Warming

Authors: Mohammed Abdulridha Hamdan

Abstract:

To face the water crisis, understanding the role of human activities on nutrient concentrations in aquatic ecosystems needs more investigations to compare to extensively studies which have been carried out to understand these impacts on the water quality of different aquatic ecosystems. We hypothesized human activates on the catchments of Tigris river may change nutrient concentrations in water along the river. The results showed that phosphate concentration differed significantly among the studied sites due to distributed human activities, while nitrate concentration did not. Phosphate and nitrate concentrations were not affected by water temperature. We concluded that human activities on the surrounding landscapes could be more essential sources for nutrients of aquatic ecosystems than role of ongoing climate warming. Despite the role of warming in driving nutrients availability in aquatic ecosystems, our findings suggest to take the different activities on the surrounding catchments into account in the studies caring about the trophic status classification of aquatic ecosystems.

Keywords: nitrate, phosphate, anthropogenic, warming

Procedia PDF Downloads 76
1397 Multi-scale Geographic Object-Based Image Analysis (GEOBIA) Approach to Segment a Very High Resolution Images for Extraction of New Degraded Zones. Application to The Region of Mécheria in The South-West of Algeria

Authors: Bensaid A., Mostephaoui T., Nedjai R.

Abstract:

A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

Procedia PDF Downloads 103
1396 A Hybrid System of Hidden Markov Models and Recurrent Neural Networks for Learning Deterministic Finite State Automata

Authors: Pavan K. Rallabandi, Kailash C. Patidar

Abstract:

In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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1395 Using Data Mining Techniques to Evaluate the Different Factors Affecting the Academic Performance of Students at the Faculty of Information Technology in Hashemite University in Jordan

Authors: Feras Hanandeh, Majdi Shannag

Abstract:

This research studies the different factors that could affect the Faculty of Information Technology in Hashemite University students’ accumulative average. The research paper verifies the student information, background, their academic records, and how this information will affect the student to get high grades. The student information used in the study is extracted from the student’s academic records. The data mining tools and techniques are used to decide which attribute(s) will affect the student’s accumulative average. The results show that the most important factor which affects the students’ accumulative average is the student Acceptance Type. And we built a decision tree model and rules to determine how the student can get high grades in their courses. The overall accuracy of the model is 44% which is accepted rate.

Keywords: data mining, classification, extracting rules, decision tree

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1394 Self-Calibration of Fish-Eye Camera for Advanced Driver Assistance Systems

Authors: Atef Alaaeddine Sarraj, Brendan Jackman, Frank Walsh

Abstract:

Tomorrow’s car will be more automated and increasingly connected. Innovative and intuitive interfaces are essential to accompany this functional enrichment. For that, today the automotive companies are competing to offer an advanced driver assistance system (ADAS) which will be able to provide enhanced navigation, collision avoidance, intersection support and lane keeping. These vision-based functions require an accurately calibrated camera. To achieve such differentiation in ADAS requires sophisticated sensors and efficient algorithms. This paper explores the different calibration methods applicable to vehicle-mounted fish-eye cameras with arbitrary fields of view and defines the first steps towards a self-calibration method that adequately addresses ADAS requirements. In particular, we present a self-calibration method after comparing different camera calibration algorithms in the context of ADAS requirements. Our method gathers data from unknown scenes while the car is moving, estimates the camera intrinsic and extrinsic parameters and corrects the wide-angle distortion. Our solution enables continuous and real-time detection of objects, pedestrians, road markings and other cars. In contrast, other camera calibration algorithms for ADAS need pre-calibration, while the presented method calibrates the camera without prior knowledge of the scene and in real-time.

Keywords: advanced driver assistance system (ADAS), fish-eye, real-time, self-calibration

Procedia PDF Downloads 244
1393 Examining Effects of Electronic Market Functions on Decrease in Product Unit Cost and Response Time to Customer

Authors: Maziyar Nouraee

Abstract:

Electronic markets in recent decades contribute remarkably in business transactions. Many organizations consider traditional ways of trade non-economical and therefore they do trade only through electronic markets. There are different categorizations of electronic markets functions. In one classification, functions of electronic markets are categorized into classes as information, transactions, and value added. In the present paper, effects of the three classes on the two major elements of the supply chain management are measured. The two elements are decrease in the product unit cost and reduction in response time to the customer. The results of the current research show that among nine minor elements related to the three classes of electronic markets functions, six factors and three factors influence on reduction of the product unit cost and reduction of response time to the customer, respectively.

Keywords: electronic commerce, electronic market, B2B trade, supply chain management

Procedia PDF Downloads 389
1392 Ontology-Driven Generation of Radiation Protection Procedures

Authors: Chamseddine Barki, Salam Labidi, Hanen Boussi Rahmouni

Abstract:

In this article, we present the principle and suitable methodology for the design of a medical ontology that highlights the radiological and dosimetric knowledge, applied in diagnostic radiology and radiation-therapy. Our ontology, which we named «Onto.Rap», is the subject of radiation protection in medical and radiology centers by providing a standardized regulatory oversight. Thanks to its added values of knowledge-sharing, reuse and the ease of maintenance, this ontology tends to solve many problems. Of which we name the confusion between radiological procedures a practitioner might face while performing a patient radiological exam. Adding to it, the difficulties they might have in interpreting applicable patient radioprotection standards. Here, the ontology, thanks to its concepts simplification and expressiveness capabilities, can ensure an efficient classification of radiological procedures. It also provides an explicit representation of the relations between the different components of the studied concept. In fact, an ontology based-radioprotection expert system, when used in radiological center, could implement systematic radioprotection best practices during patient exam and a regulatory compliance service auditing afterwards.

Keywords: knowledge, ontology, radiation protection, radiology

Procedia PDF Downloads 305
1391 Image Retrieval Based on Multi-Feature Fusion for Heterogeneous Image Databases

Authors: N. W. U. D. Chathurani, Shlomo Geva, Vinod Chandran, Proboda Rajapaksha

Abstract:

Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.

Keywords: feature fusion, image retrieval, membership function, normalization

Procedia PDF Downloads 342
1390 Aerodynamics and Aeroelastics Studies of Hanger Bridge with H-Beam Profile Using Wind Tunnel

Authors: Matza Gusto Andika, Malinda Sabrina, Syarie Fatunnisa

Abstract:

Aerodynamic and aeroelastics studies on the hanger bridge profile are important to analyze the aerodynamic phenomenon and Aeroelastics stability of hanger. Wind tunnel tests were conducted on a model of H-beam profile from hanger bridge. The purpose of this study is to investigate steady aerodynamic characteristics such as lift coefficient (Cl), drag coefficient (Cd), and moment coefficient (Cm) under the different angle of attack for preliminary prediction of aeroelastics stability problems. After investigation the steady aerodynamics characteristics from the model, dynamic testing is also conducted in wind tunnel to know the aeroelastics phenomenon which occurs at the H-beam hanger bridge profile. The studies show that the torsional vortex induced vibration occur when the wind speed is 7.32 m/s until 9.19 m/s with maximum amplitude occur when the wind speed is 8.41 m/s. The result of wind tunnel testing is matching to hanger vibration where occur in the field, so wind tunnel studies has successful to model the problem. In order that the H-beam profile is not good enough for the hanger bridge and need to be modified to minimize the Aeroelastics problem. The modification can be done with structure dynamics modification or aerodynamics modification.

Keywords: aerodynamics, aeroelastic, hanger bridge, h-beam profile, vortex induced vibration, wind tunnel

Procedia PDF Downloads 344
1389 Classification of Precipitation Types Detected in Malaysia

Authors: K. Badron, A. F. Ismail, A. L. Asnawi, N. F. A. Malik, S. Z. Abidin, S. Dzulkifly

Abstract:

The occurrences of precipitation, also commonly referred as rain, in the form of "convective" and "stratiform" have been identified to exist worldwide. In this study, the radar return echoes or known as reflectivity values acquired from radar scans have been exploited in the process of classifying the type of rain endured. The investigation use radar data from Malaysian Meteorology Department (MMD). It is possible to discriminate the types of rain experienced in tropical region by observing the vertical characteristics of the rain structure. .Heavy rain in tropical region profoundly affects radiowave signals, causing transmission interference and signal fading. Required wireless system fade margin depends on the type of rain. Information relating to the two mentioned types of rain is critical for the system engineers and researchers in their endeavour to improve the reliability of communication links. This paper highlights the quantification of percentage occurrences over one year period in 2009.

Keywords: stratiform, convective, tropical region, attenuation radar reflectivity

Procedia PDF Downloads 281
1388 Deep Learning Strategies for Mapping Complex Vegetation Patterns in Mediterranean Environments Undergoing Climate Change

Authors: Matan Cohen, Maxim Shoshany

Abstract:

Climatic, topographic and geological diversity, together with frequent disturbance and recovery cycles, produce highly complex spatial patterns of trees, shrubs, dwarf shrubs and bare ground patches. Assessment of spatial and temporal variations of these life-forms patterns under climate change is of high ecological priority. Here we report on one of the first attempts to discriminate between images of three Mediterranean life-forms patterns at three densities. The development of an extensive database of orthophoto images representing these 9 pattern categories was instrumental for training and testing pre-trained and newly-trained DL models utilizing DenseNet architecture. Both models demonstrated the advantages of using Deep Learning approaches over existing spectral and spatial (pattern or texture) algorithmic methods in differentiation 9 life-form spatial mixtures categories.

Keywords: texture classification, deep learning, desert fringe ecosystems, climate change

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1387 ViraPart: A Text Refinement Framework for Automatic Speech Recognition and Natural Language Processing Tasks in Persian

Authors: Narges Farokhshad, Milad Molazadeh, Saman Jamalabbasi, Hamed Babaei Giglou, Saeed Bibak

Abstract:

The Persian language is an inflectional subject-object-verb language. This fact makes Persian a more uncertain language. However, using techniques such as Zero-Width Non-Joiner (ZWNJ) recognition, punctuation restoration, and Persian Ezafe construction will lead us to a more understandable and precise language. In most of the works in Persian, these techniques are addressed individually. Despite that, we believe that for text refinement in Persian, all of these tasks are necessary. In this work, we proposed a ViraPart framework that uses embedded ParsBERT in its core for text clarifications. First, used the BERT variant for Persian followed by a classifier layer for classification procedures. Next, we combined models outputs to output cleartext. In the end, the proposed model for ZWNJ recognition, punctuation restoration, and Persian Ezafe construction performs the averaged F1 macro scores of 96.90%, 92.13%, and 98.50%, respectively. Experimental results show that our proposed approach is very effective in text refinement for the Persian language.

Keywords: Persian Ezafe, punctuation, ZWNJ, NLP, ParsBERT, transformers

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1386 A CFD Study of the Performance Characteristics of Vented Cylinders as Vortex Generators

Authors: R. Kishan, R. M. Sumant, S. Suhas, Arun Mahalingam

Abstract:

This paper mainly researched on influence of vortex generator on lift coefficient and drag coefficient, when vortex generator is mounted on a flat plate. Vented cylinders were used as vortex generators which intensify vortex shedding in the wake of the vented cylinder as compared to base line circular cylinder which ensures more attached flow and increases lift force of the system. Firstly vented cylinders were analyzed in commercial CFD software which is compared with baseline cylinders for different angles of attack and further variation of lift and drag forces were studied by varying Reynolds number to account for influence of turbulence and boundary layer in the flow. Later vented cylinders were mounted on a flat plate and variation of lift and drag coefficients was studied by varying angles of attack and studying the dependence of Reynolds number and dimensions of vortex generator on the coefficients. Mesh grid sensitivity is studied to check the convergence of the results obtained It was found that usage of vented cylinders as vortex generators increased lift forces with small variation in drag forces by varying angle of attack.

Keywords: CFD analysis, drag coefficient, FVM, lift coefficient, modeling, Reynolds number, simulation, vortex generators, vortex shedding

Procedia PDF Downloads 427
1385 Targeting Mineral Resources of the Upper Benue trough, Northeastern Nigeria Using Linear Spectral Unmixing

Authors: Bello Yusuf Idi

Abstract:

The Gongola arm of the Upper Banue Trough, Northeastern Nigeria is predominantly covered by the outcrops of Limestone-bearing rocks in form of Sandstone with intercalation of carbonate clay, shale, basaltic, felsphatic and migmatide rocks at subpixel dimension. In this work, subpixel classification algorithm was used to classify the data acquired from landsat 7 Enhance Thematic Mapper (ETM+) satellite system with the aim of producing fractional distribution image for three most economically important solid minerals of the area: Limestone, Basalt and Migmatide. Linear Spectral Unmixing (LSU) algorithm was used to produce fractional distribution image of abundance of the three mineral resources within a 100Km2 portion of the area. The results show that the minerals occur at different proportion all over the area. The fractional map could therefore serve as a guide to the ongoing reconnaissance for the economic potentiality of the formation.

Keywords: linear spectral un-mixing, upper benue trough, gongola arm, geological engineering

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1384 Investigation on a Wave-Powered Electrical Generator Consisted of a Geared Motor-Generator Housed by a Double-Cone Rolling on Concentric Circular Rails

Authors: Barenten Suciu

Abstract:

An electrical generator able to harness energy from the water waves and designed as a double-cone geared motor-generator (DCGMG), is proposed and theoretically investigated. Similar to a differential gear mechanism, used in the transmission system of the auto vehicle wheels, an angular speed differential is created between the cones rolling on two concentric circular rails. Water wave acting on the floating DCGMG produces and a gear-box amplifies the speed differential to gain sufficient torque for power generation. A model that allows computation of the speed differential, torque, and power of the DCGMG is suggested. Influence of various parameters, regarding the construction of the DCGMG, as well as the contact between the double-cone and rails, on the electro-mechanical output, is emphasized. Results obtained indicate that the generated electrical power can be increased by augmenting the mass of the double-cone, the span of the rails, the apex angle of the cones, the friction between cones and rails, the amplification factor of the gear-box, and the efficiency of the motor-generator. Such findings are useful to formulate a design methodology for the proposed wave-powered generator.

Keywords: amplification of angular speed differential, circular concentric rails, double-cone, wave-powered electrical generator

Procedia PDF Downloads 151
1383 Time-Series Load Data Analysis for User Power Profiling

Authors: Mahdi Daghmhehci Firoozjaei, Minchang Kim, Dima Alhadidi

Abstract:

In this paper, we present a power profiling model for smart grid consumers based on real time load data acquired smart meters. It profiles consumers’ power consumption behaviour using the dynamic time warping (DTW) clustering algorithm. Due to the invariability of signal warping of this algorithm, time-disordered load data can be profiled and consumption features be extracted. Two load types are defined and the related load patterns are extracted for classifying consumption behaviour by DTW. The classification methodology is discussed in detail. To evaluate the performance of the method, we analyze the time-series load data measured by a smart meter in a real case. The results verify the effectiveness of the proposed profiling method with 90.91% true positive rate for load type clustering in the best case.

Keywords: power profiling, user privacy, dynamic time warping, smart grid

Procedia PDF Downloads 142
1382 The Malfatti’s Problem in Reuleaux Triangle

Authors: Ching-Shoei Chiang

Abstract:

The Malfatti’s Problem is to ask for fitting 3 circles into a right triangle such that they are tangent to each other, and each circle is also tangent to a pair of the triangle’s side. This problem has been extended to any triangle (called general Malfatti’s Problem). Furthermore, the problem has been extended to have 1+2+…+n circles, we call it extended general Malfatti’s problem, these circles whose tangency graph, using the center of circles as vertices and the edge connect two circles center if these two circles tangent to each other, has the structure as Pascal’s triangle, and the exterior circles of these circles tangent to three sides of the triangle. In the extended general Malfatti’s problem, there are closed-form solutions for n=1, 2, and the problem becomes complex when n is greater than 2. In solving extended general Malfatti’s problem (n>2), we initially give values to the radii of all circles. From the tangency graph and current radii, we can compute angle value between two vectors. These vectors are from the center of the circle to the tangency points with surrounding elements, and these surrounding elements can be the boundary of the triangle or other circles. For each circle C, there are vectors from its center c to its tangency point with its neighbors (count clockwise) pi, i=0, 1,2,..,n. We add all angles between cpi to cp(i+1) mod (n+1), i=0,1,..,n, call it sumangle(C) for circle C. Using sumangle(C), we can reduce/enlarge the radii for all circles in next iteration, until sumangle(C) is equal to 2πfor all circles. With a similar idea, this paper proposed an algorithm to find the radii of circles whose tangency has the structure of Pascal’s triangle, and the exterior circles of these circles are tangent to the unit Realeaux Triangle.

Keywords: Malfatti’s problem, geometric constraint solver, computer-aided geometric design, circle packing, data visualization

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1381 A Similar Image Retrieval System for Auroral All-Sky Images Based on Local Features and Color Filtering

Authors: Takanori Tanaka, Daisuke Kitao, Daisuke Ikeda

Abstract:

The aurora is an attractive phenomenon but it is difficult to understand the whole mechanism of it. An approach of data-intensive science might be an effective approach to elucidate such a difficult phenomenon. To do that we need labeled data, which shows when and what types of auroras, have appeared. In this paper, we propose an image retrieval system for auroral all-sky images, some of which include discrete and diffuse aurora, and the other do not any aurora. The proposed system retrieves images which are similar to the query image by using a popular image recognition method. Using 300 all-sky images obtained at Tromso Norway, we evaluate two methods of image recognition methods with or without our original color filtering method. The best performance is achieved when SIFT with the color filtering is used and its accuracy is 81.7% for discrete auroras and 86.7% for diffuse auroras.

Keywords: data-intensive science, image classification, content-based image retrieval, aurora

Procedia PDF Downloads 445
1380 Determination of Water Pollution and Water Quality with Decision Trees

Authors: Çiğdem Bakır, Mecit Yüzkat

Abstract:

With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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1379 Correlation between Dynamic Knee Valgus with Isometric Hip Abductors Strength during Single-Leg Landing

Authors: Ahmed Fawzy, Khaled Ayad, Gh. M. Koura, W. Reda

Abstract:

The knee joint complex is one of the most commonly injured areas of the body in athletes. Excessive frontal plane knee excursion is considered a risk factor for multiple knee pathologies such as anterior cruciate ligament and patellofemoral joint injuries, however, little is known about the biomechanical factors that contribute to this loading pattern. Objectives: The purpose of this study was to investigate if there is a relationship between hip abductors isometric strength and the value of FPPA during single leg landing tasks in normal male subjects. Methods: One hundred (male) subjects free from lower extremity injuries for at least six months ago participated in this study. Their mean age was (23.25 ± 2.88) years, mean weight was (74.76 ± 13.54) (Kg), mean height was (174.23 ± 6.56) (Cm). The knee frontal plane projection angle was measured by digital video camera using single leg landing task. Hip abductors isometric strength were assessed by portable hand-held dynamometer. Muscle strength had been normalized to the body weight to obtain more accurate measurements. Results: The results demonstrated that there was no significant relationship between hip abductors isometric strength and the value of FPPA during single leg landing tasks in normal male subjects. Conclusion: It can be concluded that there is no relationship between hip abductors isometric strength and the value of FPPA during functional activities in normal male subjects.

Keywords: 2-dimensional motion analysis, hip strength, kinematics, knee injuries

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1378 The Association between Corporate Social Responsibility Disclosure, Assurance, and Tax Aggressiveness: Evidence from Indonesia

Authors: Eko Budi Santoso

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There is a growing interest in Corporate Social Responsibility (CSR) issues in developing countries such as Indonesia. Firms disclose their CSR activities, and some provide assurance to gain recognition as socially responsible firms. However, several of those socially responsible firms involve in tax scandals and raise a question of whether CSR disclosure is used to disguise firm misconduct or as a reflection of socially responsible firms. Specifically, whether firms engage in CSR disclosure and its assurance also responsible for their tax matters. This study examines the association between CSR disclosure and tax aggressiveness and the role of sustainability reporting assurance to the association. This research develops a modified index according to global reporting initiatives to measure CSR disclosure and various measurement for tax aggressiveness. Using a sample of Indonesian go public companies issued CSR disclosure, the empirical result shows that there is an association between CSR disclosure and tax aggressiveness. In addition, results also indicate sustainability reporting assurance moderate those association. The findings suggest that stakeholder in developing countries should examine carefully firms with active CSR disclosure before label it as socially responsible firms. JEL Classification: M14

Keywords: CSR disclosure, tax aggressiveness, assurance, business ethics

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1377 Computer Anxiety and the Use of Computerized System by University Librarians in Delta State University Library, Nigeria

Authors: L. Arumuru

Abstract:

The paper investigates computer anxiety and the use of computerized library system by university librarians in Delta State University library, Abraka, Nigeria. Some of the root causes of computer anxiety among university librarians such as lack of exposure to computers at early age, inadequate computer skills, inadequate computer training, fear at the sight of a computer, lack of understanding of how computers work, etc. were pin-pointed in the study. Also, the different services rendered in the university libraries with the aid of computers such as reference services, circulation services, acquisition services, cataloguing and classification services, etc. were identified. The study employed the descriptive survey research design through the expo-facto method, with a population of 56 librarians, while the simple percentage and frequency counts were used to analyze the data generated from the administered copies of the questionnaire. Based on the aforementioned root causes of computer anxiety and the resultant effect on computerized library system, recommendations were proffered in the study.

Keywords: computer anxiety, computerized library system, library services, university librarians

Procedia PDF Downloads 382
1376 Storage Durations Affect the Physico-Chemical Characteristics of Physalis Minima L.

Authors: Norhanizan U., S. H. Ahmad, N. A. P. Abdullah, G. B. Saleh

Abstract:

Physalis minima from the family of Solanaceae is one of the promising fruits which contains the high amount of vitamin C and other antioxidants as well. However, it is a perishable fruit where the deterioration process will commence if the fruits are not stored in proper conditions. There is not much work has been carried out to study the effects of storage durations on Physalis fruit. Therefore, this study was conducted to determine the effects of 0, 3, 6, and 9 days of storage on postharvest quality of Physalis minima fruits. Total of 120g of uniform sizes of fruits (2.3 to 2.5g) were used for each replication and the experiment was repeated thrice. The fruits were divided equally into four groups with each group labeled according to the days of storage. The fruits were then stored in the cool room for nine days with temperature maintain at 12 ° C. The fruits were analyzed for weight loss, firmness, color (L*, C* and hue angle), titratable acidity (TA), soluble solids concentrations (SSC), pH and ascorbic acids. Data were analyzed using analysis of variance and means was separated using least significant difference (LSD). The storage durations affect the quality characteristics of the fruits. On the day 9, the average of fruit weight loss and fruit firmness decreased about 21 and 24% respectively. The level of ascorbic acids and titrable acidity were also decreased while the soluble solids concentration increased during storage. Thus, in order to retain the quality of the fruits, it is recommended that the Physalis fruit can be stored only up to 6 days at 12 ° C.

Keywords: fruit quality, Physalis minima, Solanaceae, storage durations

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1375 Design and Fabrication of a Parabolic trough Collector and Experimental Investigation of Direct Steam Production in Tehran

Authors: M. Bidi, H. Akhbari, S. Eslami, A. Bakhtiari

Abstract:

Due to the high potential of solar energy utilization in Iran, development of related technologies is of great necessity. Linear parabolic collectors are among the most common and most efficient means to harness the solar energy. The main goal of this paper is design and construction of a parabolic trough collector to produce hot water and steam in Tehran. To provide precise and practical plans, 3D models of the collector under consideration were developed using Solidworks software. This collector was designed in a way that the tilt angle can be adjusted manually. To increase concentraion ratio, a small diameter absorber tube is selected and to enhance solar absorbtion, a shape of U-tube is used. One of the outstanding properties of this collector is its simple design and use of low cost metal and plastic materials in its manufacturing procedure. The collector under consideration was installed in Shahid Beheshti University of Tehran and the values of solar irradiation, ambient temperature, wind speed and collector steam production rate were measured in different days and hours of July. Results revealed that a 1×2 m parabolic trough collector located in Tehran is able to produce steam by the rate of 300ml/s under the condition of atmospheric pressure and without using a vacuum cover over the absorber tube.

Keywords: desalination, parabolic trough collector, direct steam production, solar water heater, design and construction

Procedia PDF Downloads 305
1374 Automatic Lead Qualification with Opinion Mining in Customer Relationship Management Projects

Authors: Victor Radich, Tania Basso, Regina Moraes

Abstract:

Lead qualification is one of the main procedures in Customer Relationship Management (CRM) projects. Its main goal is to identify potential consumers who have the ideal characteristics to establish a profitable and long-term relationship with a certain organization. Social networks can be an important source of data for identifying and qualifying leads since interest in specific products or services can be identified from the users’ expressed feelings of (dis)satisfaction. In this context, this work proposes the use of machine learning techniques and sentiment analysis as an extra step in the lead qualification process in order to improve it. In addition to machine learning models, sentiment analysis or opinion mining can be used to understand the evaluation that the user makes of a particular service, product, or brand. The results obtained so far have shown that it is possible to extract data from social networks and combine the techniques for a more complete classification.

Keywords: lead qualification, sentiment analysis, opinion mining, machine learning, CRM, lead scoring

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1373 Reminiscence Therapy for Alzheimer’s Disease Restrained on Logistic Regression Based Linear Bootstrap Aggregating

Authors: P. S. Jagadeesh Kumar, Mingmin Pan, Xianpei Li, Yanmin Yuan, Tracy Lin Huan

Abstract:

Researchers are doing enchanting research into the inherited features of Alzheimer’s disease and probable consistent therapies. In Alzheimer’s, memories are extinct in reverse order; memories formed lately are more transitory than those from formerly. Reminiscence therapy includes the conversation of past actions, trials and knowledges with another individual or set of people, frequently with the help of perceptible reminders such as photos, household and other acquainted matters from the past, music and collection of tapes. In this manuscript, the competence of reminiscence therapy for Alzheimer’s disease is measured using logistic regression based linear bootstrap aggregating. Logistic regression is used to envisage the experiential features of the patient’s memory through various therapies. Linear bootstrap aggregating shows better stability and accuracy of reminiscence therapy used in statistical classification and regression of memories related to validation therapy, supportive psychotherapy, sensory integration and simulated presence therapy.

Keywords: Alzheimer’s disease, linear bootstrap aggregating, logistic regression, reminiscence therapy

Procedia PDF Downloads 302
1372 Surface Modified Polyvinylidene Fluoride Membranes for Potential Use in Membrane Distillation

Authors: Lebea Nthunya, Arne Verliefde, Bhekie Mamba, Sabelo Mhlanga

Abstract:

A study aimed at developing membrane distillation (MD) processes that can be used for brackish/saline water purification will be presented. MD is a membrane-based technology that presents a possibility to counteract challenges associated with pressure driven membranes at high separation efficiencies. Membrane distillation membranes (MDM) are affected by wettability and fouling. Wetting inside the pores of the membrane is elevated by the hydrophilic characteristic of the membrane, while fouling is mostly induced by the hydrophobic-hydrophobic interaction of pollutants and the surface of the hydrophobic membranes, hence block the pores of the membranes. These properties are not desirable. As such, a carefully designed polyvinylidene fluoride (PVDF) MDM composed of a super-hydrophobic modified backbone and a super-hydrophilic thin layer has been developed to concurrently overcome these challenges. The membranes were characterized using contact angle measurements to confirm their hydrophobicity/hydrophilicity. SEM and SAXS were used to study the morphology and pore distribution on the surface of the membrane. The contact angles of the active surface ≤ 30º and that of the backbone ≥ 140º has thus revealed that the active surface was highly hydrophilic while the backbone was highly hydrophobic. The SEM and the SAXS results have also confirmed that the membranes are highly porous. These materials demonstrated a potential to remove salts from water at high efficiencies.

Keywords: membrane distillation, modification, energy efficiency, desalination

Procedia PDF Downloads 248
1371 Definition, Structure, and Core Functions of the State Image

Authors: Rosa Nurtazina, Yerkebulan Zhumashov, Maral Tomanova

Abstract:

Humanity is entering an era when 'virtual reality' as the image of the world created by the media with the help of the Internet does not match the reality in many respects, when new communication technologies create a fundamentally different and previously unknown 'global space'. According to these technologies, the state begins to change the basic technology of political communication of the state and society, the state and the state. Nowadays, image of the state becomes the most important tool and technology. Image is a purposefully created image granting political object (person, organization, country, etc.) certain social and political values and promoting more emotional perception. Political image of the state plays an important role in international relations. The success of the country's foreign policy, development of trade and economic relations with other countries depends on whether it is positive or negative. Foreign policy image has an impact on political processes taking place in the state: the negative image of the countries can be used by opposition forces as one of the arguments to criticize the government and its policies.

Keywords: image of the country, country's image classification, function of the country image, country's image components

Procedia PDF Downloads 427