Search results for: satellite imagery classification

Authors: Saleh Nabiyev

Abstract:

Renewable energy is becoming increasingly important in today's world due to its significant impact on the green economy, ecology, environment, and climate change. Renewable energy sources, such as solar and wind, are clean and sustainable, making them an ideal solution to reduce carbon emissions and mitigate the effects of climate change. The Karabakh region is located in the South Caucasus and covers an area of approximately 11,500 km². The region has a mountainous terrain, which can affect the availability of wind and solar resources. The Karabakh region has significant wind power potential, particularly in its mountainous areas where wind speeds are typically higher. According to a study conducted by the European Commission Joint Research Centre, the average wind speed in the Karabakh region is between 4 and 6 meters per second (m/s) at a height of 50 meters above ground level (AGL). However, wind speeds can be higher in some areas, reaching up to 10 m/s in some mountainous areas. The region also has significant solar power potential, with an average of 2,000 to 2,200 hours of sunshine per year. The region's high altitude and clear skies make it particularly suitable for the development of solar power projects. In this research, the application of satellite images, solar radiation, wind speed and direction, as well as various other materials to determine suitable areas for alternative energy sources, is investigated. The methodology for selecting suitable locations for solar and wind energy consists of four main parts: identification of factors, evaluation of factors, data preparation, and application of suitability analysis. At the end of the research, the territory of the Kalbajar and Lachin districts is suitable for wind energy. The southern plain part of Karabakh is highly evaluated in terms of solar energy potential, especially Jabrayil district. Generally, outcomes taken from this research are essential data for increasing of rational using natural resources, as well as combating climate change.

Keywords: GIS, remote sensing, suitability analysis, solar energy, wind energy

Procedia PDF Downloads 16

Authors: Elnaz Lashgari, Emel Demircan

Abstract:

Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.

Keywords: electromyography, manifold learning, ISOMAP, Laplacian Eigenmaps, locally linear embedding

Procedia PDF Downloads 345

Authors: Abdul Rochim, Didier Marot, Luc Sibille

Abstract:

This paper studies the characterization of soil sensibility due to suffusion process by carrying out a series of one-dimensional downward seepage flow tests realized with an erodimeter. Tests were performed under controlled hydraulic gradient in sandy gravel soils. We propose the analysis based on energy induced by the seepage flow to characterize the hydraulic loading and the cumulative eroded dry mass to characterize the soil response. With this approach, the effect of hydraulic loading histories and initial fines contents to soil sensibility are presented. It is found that for given soils, erosion coefficients are different if tests are performed under different hydraulic loading histories. For given initial fines fraction contents, the sensibility may be grouped in the same classification. The lower fines content soils tend to require larger flow energy to the onset of erosion. These results demonstrate that this approach is effective to characterize suffusion sensibility for granular soils.

Keywords: erodimeter, sandy gravel, suffusion, water seepage energy

Procedia PDF Downloads 430

Authors: Carlos A. Martins de Jesus

Abstract:

The Greek anthology, first put together in the tenth century AD, gathers in two separate books a large number of epigrams devoted to love and its consequences, both of hetero (book V) and homosexual (book XII) nature. While some poets wrote epigrams of only one genre –that is the case of Strato (II cent. BC), the organizer of a wide-spread garland of homosexual epigrams –, several others composed within both categories, often using the same topics of love and suffering. Using Plato’s theorization of two different kinds of Eros (Symp. 180d-182a), the popular (pandemos) and the celestial (ouranios), homoerotic epigrammatic love is more often associated with the first one, while heterosexual poetry tends to be connected to a higher form of love. This paper focuses on the epigrammatic production of a single first-century BC poet, Meleager, aiming to look for the similarities and differences on singing both kinds of love. From Meleager, the Greek Anthology –a garland whose origins have been traced back to the poet’s garland itself– preserves more than sixty heterosexual and 48 homosexual epigrams, an important and unprecedented amount of poems that are able to trace a complete profile of his way of singing love. Meleager’s poetry deals with personal experience and emotions, frequently with love and the unhappiness that usually comes from it. Most times he describes himself not as an active and engaged lover, but as one struck by the beauty of a woman or boy, i.e., in a stage prior to erotic consummation. His epigrams represent the unreal and fantastic (literally speaking) world of the lover, in which the imagery and wordplays are used to convey emotion in the epigrams of both genres. Elsewhere Meleager surprises the reader by offering a surrealist or dreamlike landscape where everyday adventures are transcribed into elaborate metaphors for erotic feeling. For instance, in 12.81, the lovers are shipwrecked, and as soon as they have disembarked, they are promptly kidnapped by a figure who is both Eros and a beautiful boy. Particularly –and worth-to-know why significant – in the homosexual poems collected in Book XII, mythology also plays an important role, namely in the figure and the scene of Ganimedes’ kidnap by Zeus for his royal court (12. 70, 94). While mostly refusing the Hellenistic model of dramatic love epigram, in which a small everyday scene is portrayed –and 5. 182 is a clear exception to this almost rule –, Meleager actually focuses on the tumultuous inside of his (poetic) lovers, in the realm of a subject that feels love and pain far beyond his/her erotic preferences. In relation to loving and suffering –mostly suffering, it has to be said –, Meleager’s love is therefore completely democratic. There is no real place in his epigrams for the traditional association mentioned before between homoeroticism and a carnal-erotic-pornographic love, while the heterosexual one being more evenly and pure, so to speak.

Keywords: epigram, erotic epigram, Greek Anthology, Meleager

Procedia PDF Downloads 239

Authors: Thierry Sammour Sawaya, Heikki Deschacht

Abstract:

In commercial aircraft operations, almost half of the accidents happen during approach or landing phases. Automatic guidance and automatic landings have proven to bring significant safety value added for this challenging landing phase. This is why Airbus and ScioTeq have decided to work together to explore the capability of image-based landing solutions as additional landing aids to further expand the possibility to perform automatic approach and landing to runways where the current guiding systems are either not fitted or not optimum. Current systems for automated landing often depend on radio signals provided by airport ground infrastructure on the airport or satellite coverage. In addition, these radio signals may not always be available with the integrity and performance required for safe automatic landing. Being independent from these radio signals would widen the operations possibilities and increase the number of automated landings. Airbus and ScioTeq are joining their expertise in the field of Computer Vision in the European Program called Clean Sky 2 Large Passenger Aircraft, in which they are leading the IMBALS (IMage BAsed Landing Solutions) project. The ultimate goal of this project is to demonstrate, develop, validate and verify a certifiable automatic landing system guiding an airplane during the approach and landing phases based on an onboard camera system capturing images, enabling automatic landing independent from radio signals and without precision instrument for landing. In the frame of this project, ScioTeq is responsible for the development of the Image Processing Platform (IPP), while Airbus is responsible for defining the functional and system requirements as well as the testing and integration of the developed equipment in a Large Passenger Aircraft representative environment. The aim of this paper will be to describe the system as well as the associated methods and tools developed for validation and verification.

Keywords: aircraft landing system, aircraft safety, autoland, avionic system, computer vision, image processing

Procedia PDF Downloads 80

Authors: Dawood Al Chanti, Alice Caplier

Abstract:

Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

Procedia PDF Downloads 284

Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

Abstract:

The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

Procedia PDF Downloads 125

Authors: Zukhrof Romadhon, Nani Kurniati

Abstract:

Availability of Spare parts is critical to support maintenance tasks and the production system. Managing spare part inventory deals with some parameters and objective functions, as well as the tradeoff between inventory costs and spare parts availability. Several mathematical models and methods have been developed to optimize the spare part policy. Many researchers who proposed optimization models need to be considered to identify other potential models. This work presents a review of several pertinent literature on spare part inventory optimization and analyzes the gaps for future research. Initial investigation on scholars and many journal database systems under specific keywords related to spare parts found about 17K papers. Filtering was conducted based on five main aspects, i.e., replenishment policy, objective function, echelon network, lead time, model solving, and additional aspects of part classification. Future topics could be identified based on the number of papers that haven’t addressed specific aspects, including joint optimization of spare part inventory and maintenance.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenance

Procedia PDF Downloads 40

Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

Abstract:

Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

Procedia PDF Downloads 157

Authors: Grzegorz Sierpiński, Ireneusz Celiński, Marcin Staniek

Abstract:

The article discusses multi modal mobility in contemporary societies as a main planning and organization issue in the functioning of administrative bodies, a problem which really exists in the space of contemporary cities in terms of shaping modern transport systems. The article presents classification of available resources and initiatives undertaken for developing multi modal mobility. Solutions can be divided into three groups of measures–physical measures in the form of changes of the transport network infrastructure, organizational ones (including transport policy) and information measures. The latter ones include in particular direct support for people travelling in the transport network by providing information about ways of using available means of transport. A special measure contributing to this end is a trip planner. The article compares several selected planners. It includes a short description of the Green Travelling Project, which aims at developing a planner supporting environmentally friendly solutions in terms of transport network operation. The article summarizes preliminary findings of the project.

Keywords: mobility, modal split, multimodal trip, multimodal platforms, sustainable transport

Procedia PDF Downloads 394

Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

Abstract:

Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

Procedia PDF Downloads 22

Authors: Miguel Ramirez, Ivan Lizarazo

Abstract:

The emergence of various interpretations of sustainability, including weak and strong paradigms, can be traced back to the definition of sustainable development provided in the 1987 Brundtland report and the subsequent evolution of the sustainability concept. However, there has been limited scholarly attention given to clarifying the concept of sustainability within the theoretical and conceptual framework of geography. The discipline has predominantly been focused on understanding the diverse conceptions of sustainability within its epistemological boundaries, resulting in tensions between sustainability paradigms and their associated dimensions, including the incorporation of political perspectives, with particular emphasis on environmental geography's epistemology. In response to this gap, a conceptual framework for sustainability is proposed, effectively integrating spatial and territorial concepts. This framework aims to enhance geography's role in contributing to sustainability by utilizing the land system theory, which is based on the dynamics of land use change. Such an integrated conceptual framework enables incorporating methodological tools such as remote sensing, encompassing various earth observations and fusion methods, and supervised classification techniques. Additionally, it looks for better integration of socioecological information, thereby capturing essential population-related features.

Keywords: geography, sustainability, land change science, territorial sustainability

Procedia PDF Downloads 58

Authors: Pei-Jun Xue, Ming-Yu Hsiao

Abstract:

Chinese characters, or hanzi, represent a process of simplifying three-dimensional signs into plane signifiers. From pictograms at the beginning to logograms today, a Han linguist thus classified them into six categories known as the six categories of Chinese characters. Design is a process of signification, and cultural-creative design is a process translating ideas into design with creativity upon culture. Aiming to investigate the process of cultural-creative design transforming cultural text into cultural signs, this study analyzed existing cultural-creative products with the six categories of Chinese characters by treating such products as representations which accurately communicate the designer’s ideas to users through the categorization, simplification, and interpretation of sign features. This is a two-phase pilot study on designing cultural-creative products with the six categories of Chinese characters. Phase I reviews the related literature on the theory of the six categories of Chinese characters investigated and concludes with the process and principles of character evolution. Phase II analyzes the design of existing cultural-creative products with the six categories of Chinese characters and explores the conceptualization of product design.

Keywords: six categories of Chinese characters, cultural-creative product design, cultural signs, cultural product

Procedia PDF Downloads 325

Authors: Hema Lattupalli

Abstract:

Introduction: The palate forms a partition between the oral cavity and nasal cavity. The palate is made up of two parts hard palate and soft palate. The Hard palate forms the anterior part of the palate, the soft palate forms a movable muscular fold covered by mucous membrane that is suspended from the posterior border of a hard palate. Aim and Objectives: Soft palate morphological variations have a great paucity in the literature. It’s also believed that the soft palate has no such important anatomical variations. There is a variable presentation of the soft palate morphology in the lateral cephalograms. The aim of this study is to identify the velar morphology. Materials and Methods: 100 normal subjects between the age group of 20 – 35 were taken for the study. Method: Lateral Cephalogram (radiologic study). Results: Different shapes of the soft palate were observed in the lateral cephalograms. The morphology of soft palate was classified into six types 1.Leaf like (50 cases) most common type, 2.Straight line (20 cases), 3.S shaped (4 cases) very rare, 4.Butt like (10 cases), 5. Rat tail (6 cases), 6. Hook shaped (10 cases). Conclusion: This classification helps us to understand the better diversity of the velar morphology in mid-sagittal plane. These findings help us to understand the etiology of OSAS.

Keywords: soft palate, cephalometric radiographs, morphology, cleft palate, obstructive sleep apnoea syndrome

Procedia PDF Downloads 351

Authors: Monish Sengupta, Benjamin Heydecker, Daniel Woodland

Abstract:

New train control systems rely mainly on Automatic Train Protection (ATP) and Automatic Train Operation (ATO) dynamically to control the speed and hence performance. The ATP and the ATO form the vital element within the CBTC (Communication Based Train Control) and within the ERTMS (European Rail Traffic Management System) system architectures. Reliable and accurate measurement of train location, speed and acceleration are vital to the operation of train control systems. In the past, all CBTC and ERTMS system have deployed a balise or equivalent to correct the uncertainty element of the train location. Typically a CBTC train is allowed to miss only one balise on the track, after which the Automatic Train Protection (ATP) system applies emergency brake to halt the service. This is because the location uncertainty, which grows within the train control system, cannot tolerate missing more than one balise. Balises contribute a significant amount towards wayside maintenance and studies have shown that balises on the track also forms a constraint for future track layout change and change in speed profile.This paper investigates the causes of the location uncertainty that is currently experienced and considers whether it is possible to identify an effective filter to ascertain, in conjunction with appropriate sensors, more accurate speed, distance and location for a CBTC driven train without the need of any external balises. An appropriate sensor fusion algorithm and intelligent sensor selection methodology will be deployed to ascertain the railway location and speed measurement at its highest precision. Similar techniques are already in use in aviation, satellite, submarine and other navigation systems. Developing a model for the speed control and the use of Kalman filter is a key element in this research. This paper will summarize the research undertaken and its significant findings, highlighting the potential for introducing alternative approaches to train positioning that would enable removal of all trackside location correction balises, leading to huge reduction in maintenances and more flexibility in future track design.

Keywords: ERTMS, CBTC, ATP, ATO

Procedia PDF Downloads 399

Authors: R. Bouhennache, T. Bouden, A. A. Taleb, A. Chaddad

Abstract:

In this paper we propose a method to map the urban areas. The method uses an arithmetic calculation processed from the land features indexes and Tasseled cap transformation TC of multi spectral Thematic Mapper Landsat TM image. For this purpose the derived indexes image from the original image such SAVI the soil adjusted vegetation index, UI the urban Index, and EBBI the enhanced built up and bareness index were staked to form a new image and the bands were uncorrelated, also the Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) supervised classification approaches were first applied on the new image TM data using the reference spectra of the spectral library and subsequently the four urban, vegetation, water and soil land cover categories were extracted with their accuracy assessment.The urban features were represented using a logic calculation applied to the brightness, UI-SAVI, NDBI-greenness and EBBI- brightness data sets. The study applied to Blida and mentioned that the urban features can be mapped with an accuracy ranging from 92 % to 95%.

Keywords: EBBI, SAVI, Tasseled Cap Transformation, UI

Procedia PDF Downloads 471

Authors: Zenebu Adere Tola

Abstract:

Informal settlements behave dynamically over space and time and the number of people living in such housing areas is growing worldwide. In the cities of developing countries especially in sub-Saharan Africa, poverty, unemployment rate, poor living condition, lack transparency and accountability, lack of good governance are the major factors to contribute for the people to hold land informally and built houses for residential or other purposes. In most of Ethiopian cities informal settlement is highly seen in peripheral areas this is because people can easily to hold land for housing from local farmers, brokers, speculators without permission from concerning bodies. In Adama informal settlement has created risky living conditions and led to environmental problems in natural areas the main reason for this was the lack of sufficient knowledge about informal settlement development. On the other side there is a strong need to transform informal into formal settlements and to gain more control about the actual spatial development of informal settlements. In another hand to tackle the issue it is at least very important to understand the scale of the problem. To understand the scale of the problem it is important to use up-to-date technology. For this specific problem, it is good to use high-resolution imagery to detect informal settlement in Adama city. The main objective of this study is to assess the spatiotemporal dynamics and environmental impacts of informal settlement using OBIA. Specifically, the objective of this study is to; identify informal settlement in the study area, determine the change in the extent and pattern of informal settlement and to assess the environmental and social impacts of informal settlement in the study area. The methods to be used to detect the informal settlement is object-oriented image analysis. Consequently, reliable procedures for detecting the spatial behavior of informal settlements are required in order to react at an early stage to changing housing situations. Thus, obtaining spatial information about informal settlement areas which is up to date is vital for any actions of enhancement in terms of urban or regional planning. Using data for this study aerial photography for growth and change of informal settlements in Adama city. Software ECognition software for classy to built-up and non-built areas. Thus, obtaining spatial information about informal settlement areas which is up to date is vital for any actions of enhancement in terms of urban or regional planning.

Keywords: informal settlement, change detection, environmental impact, object based analysis

Procedia PDF Downloads 57

Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

Abstract:

The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: color moments, visual thing recognition system, SIFT, color SIFT

Procedia PDF Downloads 446

Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

Abstract:

The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: disentanglement, face detection, generative adversarial networks, video surveillance

Procedia PDF Downloads 109

Authors: Shugufta Mohammad Zubair

Abstract:

This study explores the Effect of the new food System Inspection system also called the new inspection color card scheme on reduction of critical & major food safety violations in Dubai. Data was collected from all retail food service establishments located in two zones in the city. Each establishment was visited twice, once before the launch of the new system and one after the launch of the system. In each visit, the Inspection checklist was used as the evaluation tool for observation of the critical and major violations. The old format of the inspection checklist was concerned with scores based on the violations; but the new format of the checklist for the new inspection color card scheme is divided into administrative, general major and critical which gives a better classification for the inspectors to identify the critical and major violations of concerned. The study found that there has been a better and clear marking of violations after the launch of new inspection system wherein the inspectors are able to mark and categories the violations effectively. There had been a 10% decrease in the number of food establishment that was previously given A grade. The B & C grading were also considerably dropped by 5%.

Keywords: food inspection, risk assessment, color card scheme, violations

Procedia PDF Downloads 311

Authors: Jonathan H. Westover, Ruthann Cunningham, Jaron Harvey

Abstract:

Purpose: Job satisfaction is one of the most critical attitudes among employees. Understanding whether employees are satisfied with their jobs and what is driving that satisfaction is important for any employer, but particularly for healthcare organizations. This study looks at the question of job satisfaction and drivers of job satisfaction among healthcare professionals at a global scale, looking for trends that generalize across 37 countries. Study: This study analyzed job satisfaction responses to the 2015 Work Orientations IV wave of the International Social Survey Programme (ISSP) to understand differences in antecedents for and levels of job satisfaction among healthcare professionals. A total of 18,716 respondents from 37 countries participated in the annual survey. Findings: Respondents self-identified their occupational category based on corresponding International Standard Classification of Occupations (ISCO-08) codes. Results suggest that mean overall job satisfaction was highest among health service managers and generalist medical practitioners and lowest among environmental hygiene professionals and nursing professionals. Originality: Many studies have addressed the issue of job satisfaction in healthcare, examining small samples of specific healthcare workers. In this study, using a large international dataset, we are able to examine questions of job satisfaction across large groups of healthcare workers in different occupations within the healthcare field.

Keywords: job satisfaction, healthcare industry, global comparisons, workplace

Procedia PDF Downloads 129

Authors: S. Rezaei, Z. Mirzaei, M. Khalighi, J. Bahrami

Abstract:

Bridges, as an essential part of road infrastructures, are affected by various deterioration mechanisms over time due to the changes in their performance. As changes in performance can have many negative impacts on society, it is essential to be able to evaluate and measure the performance of bridges throughout their life. This evaluation includes the development or the choice of the appropriate performance indicators, which, in turn, are measured based on the selection of appropriate models for the existing deterioration mechanism. The purpose of this article is a statistical study of indicators and deterioration mechanisms of bridges in order to discover further research capacities in bridges performance assessment. For this purpose, some of the most common indicators of bridge performance, including reliability, risk, vulnerability, robustness, and resilience, were selected. The researches performed on each index based on the desired deterioration mechanisms and hazards were comprehensively reviewed. In addition, the formulation of the indicators and their relationship with each other were studied. The research conducted on the mentioned indicators were classified from the point of view of deterministic or probabilistic method, the level of study (element level, object level, etc.), and the type of hazard and the deterioration mechanism of interest. For each of the indicators, a number of challenges and recommendations were presented according to the review of previous studies.

Keywords: bridge, deterioration mechanism, lifecycle, performance indicator

Procedia PDF Downloads 93

Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak

Abstract:

Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.

Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity

Procedia PDF Downloads 139

Authors: Xin Li, Ji-Yang Yu, Yue-Hua Niu, Lu-Yuan Wang

Abstract:

As an inevitable chain of the space data acquirement system, space-borne storage system based on Nand Flash has gradually been implemented in spacecraft. In face of massive, parallel and varied data on board, efficient data management become an important issue of storage research. Face to the requirements of high-performance and reliability in Nand Flash storage system, a combination of hardware and file system design can drastically increase system dependability, even for missions with a very long duration. More sophisticated flash storage concepts with advanced operating systems have been researched to improve the reliability of Nand Flash storage system on satellites. In this paper, architecture of file system with multi-channel data acquisition and storage on board is proposed, which obtains large-capacity and high-performance with the combine of intra-channel pipeline and device partition in Nand Flash. Multi-channel data in different rate are stored as independent files with parallel-storage system in device partition, which assures the high-effective and reliable throughput of file treatments. For massive and high-speed data storage, an efficiency assessment model is established to calculate the bandwidth formula of intra-channel pipeline. Information tables designed in Magnetoresistive RAM (MRAM) hold the management of bad block in Nand Flash and the arrangement of file system address for the high-reliability of data storage. During the full-load test, the throughput of 3D PLUS Module 160Gb Nand Flash can reach 120Mbps for store and reach 120Mbps for playback, which efficiently satisfies the requirement of multi-channel data acquisition in Satellite. Compared with previous literature, the results of experiments verify the advantages of the proposed system.

Keywords: device partition architecture, intra-channel pipelining, nand flash, parallel storage

Procedia PDF Downloads 279

Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

Abstract:

The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

Procedia PDF Downloads 81

Authors: Soon-Mi Park, Ihn Sook Jeong

Abstract:

This retrospective study was aimed to identify risk factors of intravenous (IV) infiltration for hospitalized children. The participants were 1,174 children for test and 424 children for validation, who admitted to a general hospital, received peripheral intravenous injection therapy at least once and had complete records. Data were analyzed with frequency and percentage or mean and standard deviation were calculated, and decision tree analysis was used to screen for the most important risk factors for IV infiltration for hospitalized children. The decision tree analysis showed that the most important traditional risk factors for IV infiltration were the use of ampicillin/sulbactam, IV insertion site (lower extremities), and medical department (internal medicine) both in the test sample and validation sample. The correct classification was 92.2% in the test sample and 90.1% in the validation sample. More careful attention should be made to patients who are administered ampicillin/sulbactam, have IV site in lower extremities and have internal medical problems to prevent or detect infiltration occurrence.

Keywords: decision tree analysis, intravenous infiltration, child, validation

Procedia PDF Downloads 160

Authors: Saugata Bose, Ritambhra Korpal

Abstract:

The internet has increased the copy-paste scenarios amongst students as well as amongst researchers leading to different levels of plagiarized documents. For this reason, much of research is focused on for detecting plagiarism automatically. In this paper, an initiative is discussed where Natural Language Processing (NLP) techniques as well as supervised machine learning algorithms have been combined to detect plagiarized texts. Here, the major emphasis is on to construct a framework which detects external plagiarism from monolingual texts successfully. For successfully detecting the plagiarism, n-gram frequency comparison approach has been implemented to construct the model framework. The framework is based on 120 characteristics which have been extracted during pre-processing the documents using NLP approach. Afterwards, filter metrics has been applied to select most relevant characteristics and then supervised classification learning algorithm has been used to classify the documents in four levels of plagiarism. Confusion matrix was built to estimate the false positives and false negatives. Our plagiarism framework achieved a very high the accuracy score.

Keywords: lexical matching, shallow NLP, supervised machine learning algorithm, word n-gram

Procedia PDF Downloads 342

Authors: Azat Eslamizadeh, Neda Akbarian

Abstract:

The Zaghia Iron ore, in 15 km east of a town named Bafq, is located in Precambrian formation of Central Iran in form of a small local deposit. The Volcano-sedimentary rocks of Precambrian-Cambrian age, belonging to Rizu series have spread through the region. Substantial portion of the deposit is covered by alluvial deposits. The rocks hosting the Zaghia iron ore have a main combination of rhyolitic tuffs along with clastic sediments, carbonate include sandstone, limestone, dolomite, conglomerate and is somewhat metamorphed causing them to have appeared as slate and phyllite. Moreover, carbonate rocks are in existence as skarn compound of marble bearing tremolite with mineralization of magnetite-hematite. The basic igneous rocks have dramatically altered into green rocks consist of actinolite-tremolite and chlorite along with amount of iron (magnetite + Martite). The youngest units of ore-bearing rocks in the area are found as dolerite - diabase dikes. The dikes are cutting the rhyolitic tuffs and carbonate rocks.

Keywords: Zaghia, iron ore deposite, mineralogy, petrography Bafq, Iran

Procedia PDF Downloads 510

Authors: Duygu Dere, Mert Ergeneci, Kaan Gokcesu

Abstract:

Google Trends data has gained increasing popularity in the applications of behavioral finance, decision science and risk management. Because of Google’s wide range of use, the Trends statistics provide significant information about the investor sentiment and intention, which can be used as decisive factors for corporate and risk management fields. However, an anomaly, a significant increase or decrease, in a certain query cannot be detected by the state of the art applications of computation due to the random baseline noise of the Trends data, which is modelled as an Additive white Gaussian noise (AWGN). Since through time, the baseline noise power shows a gradual change an adaptive thresholding method is required to track and learn the baseline noise for a correct classification. To this end, we introduce an online method to classify meaningful deviations in Google Trends data. Through extensive experiments, we demonstrate that our method can successfully classify various anomalies for plenty of different data.

Keywords: adaptive data processing, behavioral finance , convex optimization, online learning, soft minimum thresholding

Procedia PDF Downloads 149

Authors: Abriak Yassine, Zri Abdeljalil, Benzerzour Mahfoud., Hadj Sadok Rachid, Abriak Nor-Edine

Abstract:

In this study, firstly, the study of the capacity reuse of dredged sediments and treated sediments with lime or cement were used in an establishment layer and the base layer of the roadway. Also, the analysis of mineral changes caused by the addition of lime or cement on the way as described in the mechanical results of stabilised sediments. After determining the quantity of lime and cement required to stabilise the sediment, the compaction characteristics were studied using the modified Proctor method. Then the evolution of the three parameters, that is, ideal water content and maximum dry density had been determined. Mechanical exhibitions can be assessed across the resistance to compression, flexibility modulus and the resistance under traction. The resistance of the formulation treated with cement addition (ROLAC®645) increase with the quantity of ROLAC®645. Traction resistances and the elastic modulus were utilized to assess the potential of the formulation as road construction materials utilizing classification diagram. The results show the various formulations with ROLAC® 645may be employed in subgrades and foundation layers for roads.

Keywords: cement, dredged, sediment, foundation layer, resistance

Procedia PDF Downloads 81