Search results for: feature collection

Authors: Eleni Tsangouri, Xander Hillewaere, David Garoz Gómez, Dimitrios Aggelis, Filip Du Prez, Danny Van Hemelrijck

Abstract:

Tapered Double Cantilever Beam (TDCB) is the most commonly used test set-up to evaluate the self-healing feature of thermoset polymers autonomously activated in the presence of crack. TDCB is a modification of the established fracture mechanics set-up of Double Cantilever Beam and is designed to provide constant strain energy release rate with crack length under stable load evolution (mode-I). In this study, the damage of virgin and autonomously healed TDCB polymer samples is evaluated considering the load-crack opening diagram, the strain maps provided by Digital Image Correlation technique and the fractography maps given by optical microscopy. It is shown that the pre-crack introduced prior to testing (razor blade tapping), the loading rate and the length of the side groove are the features that dominate the crack propagation and lead to inconstant fracture energy release rate.

Keywords: polymers, autonomous healing, fracture, tapered double cantilever beam

Procedia PDF Downloads 350

Authors: Laxuman Thakuri

Abstract:

Despite the large number of in-depth case studies focused on policy analysis, institutional arrangement, and collective action of common property resource management; how the local institutions take the pricing decision of forest products in community forest management and what kinds of effects produce it, the answers of these questions are largely silent among the policy-makers and researchers alike. The study examined how the local institutions take the pricing decision of forest products in the lowland community forestry of Nepal and how the decisions affect to equitable distribution of benefits and livelihood improvement which are also objectives of Nepalese community forestry. The study assumes that forest products pricing decisions have multiple effects on equitable distribution and livelihood improvement in the areas having heterogeneous socio-economic conditions. The dissertation was carried out at four community forests of lowland, Nepal that has characteristics of high value species, matured-experience of community forest management and better record-keeping system of forest products production, pricing and distribution. The questionnaire survey, individual to group discussions and direct field observation were applied for data collection from the field, and Lorenz curve, gini-coefficient, χ²-text, and SWOT (Strong, Weak, Opportunity, and Threat) analysis were performed for data analysis and results interpretation. The dissertation demonstrates that the low pricing strategy of high-value forest products was supposed crucial to increase the access of socio-economically weak households, and to and control over the important forest products such as timber, but found counter productive as the strategy increased the access of socio-economically better-off households at higher rate. In addition, the strategy contradicts to collect a large-scale community fund and carry out livelihood improvement activities as per the community forestry objectives. The crucial part of the study is despite the fact of low pricing strategy; the timber alone contributed large part of community fund collection. The results revealed close relation between pricing decisions and livelihood objectives. The action research result shows that positive price discrimination can slightly reduce the prevailing inequality and increase the fund. However, it lacks to harness the full price of forest products and collects a large-scale community fund. For broader outcomes of common property resource management in terms of resource sustainability, equity, and livelihood opportunity, the study suggests local institutions to harness the full price of resource products with respect to the local market.

Keywords: community, equitable, forest, livelihood, socioeconomic, Nepal

Procedia PDF Downloads 535

Authors: Javed Khan, Aamir Saeed Malik, Nidal Kamel, Sarat Chandra Dass, Azura Mohd Affandi

Abstract:

Low contrast images can result from the wrong setting of image acquisition or poor illumination conditions. Such images may not be visually appealing and can be difficult for feature extraction. Contrast enhancement of color images can be useful in medical area for visual inspection. In this paper, a new technique is proposed to improve the contrast of color images. The RGB (red, green, blue) color image is transformed into normalized RGB color space. Adaptive histogram equalization technique is applied to each of the three channels of normalized RGB color space. The corresponding channels in the original image (low contrast) and that of contrast enhanced image with adaptive histogram equalization (AHE) are morphed together in proper proportions. The proposed technique is tested on seventy color images of acne patients. The results of the proposed technique are analyzed using cumulative variance and contrast improvement factor measures. The results are also compared with decorrelation stretch. Both subjective and quantitative analysis demonstrates that the proposed techniques outperform the other techniques.

Keywords: contrast enhacement, normalized RGB, adaptive histogram equalization, cumulative variance.

Procedia PDF Downloads 374

Authors: A. Szabó Nagy, J. Szabó, Zs. Csanádi, J. Erdős

Abstract:

An assessment of the air quality of Győr (Hungary) was performed by determining the ambient concentrations of PM10-bound carcinogenic polycyclic aromatic hydrocarbons (cPAHs) in different seasons. A high volume sampler was used for the collection of ambient aerosol particles, and the associated cPAH compounds (benzo[a]pyrene (BaP), benzo[a]anthracene, benzofluoranthene isomers, indeno[123-cd]pyrene and dibenzo[ah]anthracene) were analyzed by a gas chromatographic method. Higher mean concentrations of total cPAHs were detected in samples collected in winter (9.62 ng/m³) and autumn (2.69 ng/m³) compared to spring (1.05 ng/m³) and summer (0.21 ng/m³). The calculated BaP toxic equivalent concentrations have also reflected that the local population appears to be exposed to significantly higher cancer risk in the heating seasons. Moreover, the concentration levels of cPAHs determined in this study were compared to other Hungarian urban sites.

Keywords: air, carcinogenic, polycyclic aromatic hydrocarbons (PAH), PM10

Procedia PDF Downloads 270

Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan

Abstract:

Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.

Keywords: data fusion, Dempster-Shafer theory, data mining, event detection

Procedia PDF Downloads 409

Authors: Azeez Ayodele Ayodele

Abstract:

This paper investigated the problem of picture books design and the quality of the pictures in picture books. The research surveyed nursery and primary schools in four major cities in southwest of Nigeria. The instruments including the descriptive survey questionnaire and a structured interview were developed, validated and administered for collection of relevant data. Descriptive statistics was used in analyzing the data. The result of the study revealed that there were poor quality of pictures in picture books and this is due to scarcity of trained graphic designers who understand systems approach to picture books design and production. There is thus a need for more qualified graphic designers, given in-service professional training as well as a refresher course as criteria for upgrading by the stakeholders.

Keywords: pictures, picture books, pre-primary schools, trained graphic designers

Procedia PDF Downloads 246

Authors: Haci Mehmet Guzey, Levent Acar

Abstract:

In this paper, a novel decentralized controller is developed for linear systems with nonlinear unknown interconnections. A model linear decoupled system is assigned for each system. By using the difference actual and model state dynamics, the problem is formulated as inverse problem. Then, the interconnected dynamics are approximated by using Galerkin’s expansion method for inverse problems. Two different sets of orthogonal basis functions are utilized to approximate the interconnected dynamics. Approximated interconnections are utilized in the controller to cancel the interconnections and decouple the systems. Subsequently, the interconnected systems behave as a collection of decoupled systems.

Keywords: decentralized control, inverse problems, large scale systems, nonlinear interconnections, basis functions, system identification

Procedia PDF Downloads 531

Authors: Nathan Elvidge

Abstract:

This paper offers a philosophical argument against the possibility of so-called “ethical porn,” that is, pornographic material produced in a way attempting to remain consistent with feminist principles and female empowerment. One key feature of such material is the requirement for the material to be consensual on the part of the actors or those involved in the material. However, in the contemporary pornography industry, this typically amounts to a single historic act of consent given in exchange for a lump-sum payment which grants the producer lifetime property rights over the explicit material. This paper argues that, by the lights of feminist principles, this situation is inherently unjust and that, as a consequence, the pornography industry requires a radical systematic upheaval before any material produced within it can be considered genuinely ethical. These feminist principles require that for the consumption of pornography to be genuinely ethical, the actors must consent not only to the acts recorded in the material but also to the consumption of that material. This paper argues that this consent to consumption should be treated as on par with other matters of sexual consent and, therefore, that actors should have the right to withdraw consent to the consumption of their material. From this, it is argued to follow that the system of third-party ownership of property rights over someone else’s sexually explicit material legally nullifies this right and therefore is inherently unjust.

Keywords: consent, feminism, pornography, sex work

Procedia PDF Downloads 114

Authors: Yael Cohen Azaria, Sara Zamir

Abstract:

This study examined what motivated Israeli Arab students to choose to study for a degree in education and society and the influence of this academic choice on them while they were studying. The study follows the qualitative paradigm of data collection and analysis, in a case study of a homogeneous group of Arab students in a Jewish multicultural academic institution. 33 students underwent semi-structured in-depth interviews. Findings show that the choice stemmed from a desire to lead social change within their own society; to imitate an educational role-model and to realize a dream of higher education. Among the female students, this field suits the role of the woman in Arab society. The interviewees claimed that the influence of their studies was that they felt more openness towards others and those who are different; they felt pride and self-confidence in their abilities, and the women mentioned that they felt empowered.

Keywords: education, higher education, Israeli Arabs, minorities

Procedia PDF Downloads 374

Authors: N. Paparisteidi, D. Rodamitou

Abstract:

This article focuses on the skills development and path planning of students studying computer science in EPITECH: french private institute of Higher Education. The researchers examine students’ points of view and experience in a blended learning model based on a skills development curriculum. The study is based on the collection of four main categories of data: semi-participant observation, distribution of questionnaires, interviews, and analysis of internal school databases. The findings seem to indicate that a skills-based program on active learning enables students to develop their learning strategies as well as their personal skills and to actively engage in the creation of their career path and contribute to providing additional information to curricula planners and decision-makers about learning design in higher education.

Keywords: active learning, blended learning, higher education, skills development

Procedia PDF Downloads 103

Authors: Wei Feilong

Abstract:

In this study, an local invariant generalized Houghtransform (LI-GHT) method is proposed for integrated circuit (IC) visual positioning. The original generalized Hough transform (GHT) is robust to external noise; however, it is not suitable for visual positioning of IC chips due to the four-dimensionality (4D) of parameter space which leads to the substantial storage requirement and high computational complexity. The proposed LI-GHT method can reduce the dimensionality of parameter space to 2D thanks to the rotational invariance of local invariant geometric feature and it can estimate the accuracy position and rotation angle of IC chips in real-time under noise and blur influence. The experiment results show that the proposed LI-GHT can estimate position and rotation angle of IC chips with high accuracy and fast speed. The proposed LI-GHT algorithm was implemented in IC visual positioning system of radio frequency identification (RFID) packaging equipment.

Keywords: Integrated Circuit Visual Positioning, Generalized Hough Transform, Local invariant Generalized Hough Transform, ICpacking equipment

Procedia PDF Downloads 263

Authors: Milos Travar, Jovana Nikolov, Andrej Vranicar, Natasa Todorovic

Abstract:

Over the years, High Purity Germanium (HPGe) detectors proved to be an excellent practical tool and, as such, have established their today's wide use in low background γ-spectrometry. One of the advantages of gamma-ray spectrometry is its easy sample preparation as chemical processing and separation of the studied subject are not required. Thus, with a single measurement, one can simultaneously perform both qualitative and quantitative analysis. One of the most prominent features of HPGe detectors, besides their excellent efficiency, is their superior resolution. This feature virtually allows a researcher to perform a thorough analysis by discriminating photons of similar energies in the studied spectra where otherwise they would superimpose within a single-energy peak and, as such, could potentially scathe analysis and produce wrongly assessed results. Naturally, this feature is of great importance when the identification of radionuclides, as well as their activity concentrations, is being practiced where high precision comes as a necessity. In measurements of this nature, in order to be able to reproduce good and trustworthy results, one has to have initially performed an adequate full-energy peak (FEP) efficiency calibration of the used equipment. However, experimental determination of the response, i.e., efficiency curves for a given detector-sample configuration and its geometry, is not always easy and requires a certain set of reference calibration sources in order to account for and cover broader energy ranges of interest. With the goal of overcoming these difficulties, a lot of researches turned towards the application of different software toolkits that implement the Monte Carlo method (e.g., MCNP, FLUKA, PENELOPE, Geant4, etc.), as it has proven time and time again to be a very powerful tool. In the process of creating a reliable model, one has to have well-established and described specifications of the detector. Unfortunately, the documentation that manufacturers provide alongside the equipment is rarely sufficient enough for this purpose. Furthermore, certain parameters tend to evolve and change over time, especially with older equipment. Deterioration of these parameters consequently decreases the active volume of the crystal and can thus affect the efficiencies by a large margin if they are not properly taken into account. In this study, the optimisation method of two HPGe detectors through the implementation of the Geant4 toolkit developed by CERN is described, with the goal of further improving simulation accuracy in calculations of FEP efficiencies by investigating the influence of certain detector variables (e.g., crystal-to-window distance, dead layer thicknesses, inner crystal’s void dimensions, etc.). Detectors on which the optimisation procedures were carried out were a standard traditional co-axial extended range detector (XtRa HPGe, CANBERRA) and a broad energy range planar detector (BEGe, CANBERRA). Optimised models were verified through comparison with experimentally obtained data from measurements of a set of point-like radioactive sources. Acquired results of both detectors displayed good agreement with experimental data that falls under an average statistical uncertainty of ∼ 4.6% for XtRa and ∼ 1.8% for BEGe detector within the energy range of 59.4−1836.1 [keV] and 59.4−1212.9 [keV], respectively.

Keywords: HPGe detector, γ spectrometry, efficiency, Geant4 simulation, Monte Carlo method

Procedia PDF Downloads 117

Authors: Karina Zaccari, Ernesto Cordeiro Marujo

Abstract:

This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: machine learning, medical diagnosis, meningitis detection, pediatric research

Procedia PDF Downloads 149

Authors: B. Ramesh Naik, T. Venugopal

Abstract:

This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

Procedia PDF Downloads 180

Authors: Razieh Rezaeekalantari

Abstract:

Objective: The purpose of this study was to investigate the prediction of parenting orientations in terms of the components of couples' sexual review. Methods: This was a descriptive correlational research method. The population consisted of 500 couples referring to Sari Health Center. Two hundred and fifteen (215) people were selected randomly by using Krejcie-Morgan-sample-size-table. For data collection, the childbearing orientations scale and the Multidimensional Sexual Self-Concept Questionnaire were used. Result: For data analysis, the mean and standard deviation were used and to analyze the research hypothesis regression correlation and inferential statistics were used. Conclusion: The findings indicate that there is not a significant relationship between the tendency to childbearing and the predictive value of sexual review (r = 0.84) with significant level (sig = 219.19) (P < 0.05). So, with 95% confidence, we conclude that there is not a meaningful relationship between sexual orientation and tendency to child-rearing.

Keywords: couples referring, health center, sexual review component, parenting orientations

Procedia PDF Downloads 218

Authors: Khalid Soussi

Abstract:

The study at hand has attempted to describe the acquisition of three EFL lexical knowledge aspects - meaning, synonymy and collocation – across three academic levels: Baccalaureate, second year and fourth year university levels in Morocco. The research also compares the development of the three lexical knowledge aspects between knowledge (reception) and use (production) and attempts to trace their order of acquisition. This has led to the use of three main data collection tasks: translation, acceptability judgment and multiple choices. The study has revealed the following findings. First, L1 and EFL mental lexicons are connected at the lexical knowledge depth. Second, such connection is active whether in language reception or use. Third, the connectivity between L1 and EFL mental lexicons tends to relatively decrease as the academic level of the learners increases. Finally, the research has revealed a significant 'order' of acquisition between the three lexical aspects, though not a very strong one.

Keywords: vocabulary acquisition, EFL lexical knowledge, mental lexicon, vocabulary knowledge depth

Procedia PDF Downloads 281

Authors: Kawinphat Lertpongmanee

Abstract:

The purposes of this study were (1) investigate the English language learning motivation and the attainment of their English proficiency, (2) to find out how motivation and motivational variables of the high and low proficiency subjects are related to their English proficiency. The respondents were 80 fourth-year from Faculty of Management Sciences students in Rajabhat Suansunadha University. The instruments used for data collection were questionnaires. The statistically analyzed by using the SPSS program for frequency, percentage, arithmetic mean, standard deviation (SD), t-test, one-way analysis of variance (ANOVA), and Pearson correlation coefficient. The findings of this study are summarized as there was a significant difference in overall motivation between high and low proficiency groups of subjects at .05 (p < .05), but not in overall motivational variables. Additionally, the high proficiency group had a significantly higher level of intrinsic motivation than did the low proficiency group at .05 (p < .05).

Keywords: English language proficiency, faculty of management sciences, motivation factors, proficiency subjects

Procedia PDF Downloads 259

Authors: Fuyang Peng, Donghong Li

Abstract:

The aim of information systems integration is to make all the data sources, applications and business flows integrated into the new environment so that unwanted redundancies are reduced and bottlenecks and mismatches are eliminated. Two issues have to be dealt with to meet such requirements: the software architecture that supports resource integration, and the adaptor development tool that help integration and migration of legacy applications. In this paper, a service-enabled dependable integration environment (SDIE), is presented, which has two key components, i.e., a dependable service integration platform and a legacy application integration tool. For the dependable platform for service integration, the service integration bus, the service management framework, the dependable engine for service composition, and the service registry and discovery components are described. For the legacy application integration tool, its basic organization, functionalities and dependable measures taken are presented. Due to its service-oriented integration model, the light-weight extensible container, the service component combination-oriented p-lattice structure, and other features, SDIE has advantages in openness, flexibility, performance-price ratio and feature support over commercial products, is better than most of the open source integration software in functionality, performance and dependability support.

Keywords: application integration, dependability, legacy, SOA

Procedia PDF Downloads 358

Authors: Atefeh Heydari, Mohammadali Tavakoli, Zuriati Ismail, Naomie Salim

Abstract:

Seeking and sharing knowledge on online forums have made them popular in recent years. Although online forums are valuable sources of information, due to variety of sources of messages, retrieving reliable threads with high quality content is an issue. Majority of the existing information retrieval systems ignore the quality of retrieved documents, particularly, in the field of thread retrieval. In this research, we present an approach that employs various quality features in order to investigate the quality of retrieved threads. Different aspects of content quality, including completeness, comprehensiveness, and politeness, are assessed using these features, which lead to finding not only textual, but also conceptual relevant threads for a user query within a forum. To analyse the influence of the features, we used an adopted version of voting model thread search as a retrieval system. We equipped it with each feature solely and also various combinations of features in turn during multiple runs. The results show that incorporating the quality features enhances the effectiveness of the utilised retrieval system significantly.

Keywords: content quality, forum search, thread retrieval, voting techniques

Procedia PDF Downloads 211

Authors: Igor V. Kuzminov

Abstract:

According to its content, the proposed article is a collection of articles with comments and additions. All articles, in one way or another, have a connection with the Second Law of Thermodynamics. The content of the articles is given in a concise form. The articles were published in different journals at different times. Main topics are presented: gravity, biography of the Earth, physics of global warming-cooling cycles, multiverse. The articles are based on the laws of classical physics. Along the way, it should be noted that the Second Law of thermodynamics can be formulated as the Law of Matter Cooling. As it cools down, the processes of condensation, separation, and changes in the aggregate states of matter occur. In accordance with these changes, a picture of the world is being formed. Also, the main driving force of these processes is the inverse temperature dependence of the forces of gravity. As matter cools, the forces of gravity increase. The actions of these phenomena in the compartment form a picture of the world.

Keywords: gravitational forces, cooling of matter, inverse temperature dependence of gravitational forces, planetary model of the atom

Procedia PDF Downloads 242

Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri

Abstract:

Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.

Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation

Procedia PDF Downloads 103

Authors: Atef Abdallah Abouelmaaty

Abstract:

The aim of this paper is to study the theme of alienation in some contemporary novels of the most prominent Arab writers who live in Britain and write in English. The paper will focus on three female novelists of Arab origins who won wide fame among reading public, and also won international prizes for their literary creation. The first is the Egyptian Ahdaf Soueif(born in 1950) whose novel The Map of Love(1999) was shortlisted for the Man Booker Prize, and has been translated into twenty one languages and sold over a million copies. The second is the Jordanian Fadia Faqir (born in 1956) whose My Name is Salma(2007) was translated into thirteen languages, and was a runner up for the ALOA literary prize. The third is the Sudanese Leila Aboulela(born in 1964) who The Translator was nominated for the Orange Prize and was chosen as a a notable book of the year by the New York Times in 2006. The main reason of choosing the theme of alienation is that it is the qualifying feature of the above mentioned novels. This is because the theme is clearly projected and we can see different kinds of alienation: alienation of man from himself, alienation of man from other men, and alienation of man from society. The paper is concerned with studying this central theme together with its different forms. Moreover, the paper will try to identify the main causes of this alienation among which are frustrated love, the failure to adjust to change, and ethnic pride.

Keywords: alienation, Anglo-Arab, contemporary, novels

Procedia PDF Downloads 437

Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, Rebecca K. Rossi, Yanmin Yuan, Xianpei Li

Abstract:

The fiscal growth of any country hinges on the prudent administration of water resources. The river Yamuna and Ganga are measured as the life line of India as it affords the needs for life to endure. Earth observation over remote sensing images permits the precise description and identification of ingredients on the superficial from space and airborne platforms. Multiple and heterogeneous image sources are accessible for the same geographical section; multispectral, hyperspectral, radar, multitemporal, and multiangular images. In this paper, a taxonomical learning of the fluvial geomorphological features of river Yamuna and Ganga over doon valley using color fusion of multispectral remote sensing images was performed. Experimental results exhibited that the segmentation based colorization technique stranded on pattern recognition, and color mapping fashioned more colorful and truthful colorized images for geomorphological feature extraction.

Keywords: color fusion, geomorphology, fluvial processes, multispectral images, pattern recognition

Procedia PDF Downloads 305

Authors: Meng Wu, Atif Rahman, Eng Gee, Lim, Jeong Jin Yu, Rong Yan

Abstract:

Context: The COVID-19 pandemic has had a profound impact on mental health, with increased rates of anxiety and depression observed. Social support, a critical factor in mental well-being, has also undergone significant changes during the pandemic. This study aims to explore the relationship between social support, anxiety, and depression during COVID-19, taking into account various demographic and contextual factors. Research Aim: The main objective of this study is to conduct a comprehensive systematic review and meta-analysis to examine the impact of social support on anxiety and depression during the COVID-19 pandemic. The study aims to determine the consistency of these relationships across different age groups, occupations, regions, and research paradigms. Methodology: A scoping review and meta-analytic approach were employed in this study. A search was conducted across six databases from 2020 to 2022 to identify relevant studies. The selected studies were then subjected to random effects models, with pooled correlations (r and ρ) estimated. Homogeneity was assessed using Q and I² tests. Subgroup analyses were conducted to explore variations across different demographic and contextual factors. Findings: The meta-analysis of both cross-sectional and longitudinal studies revealed significant correlations between social support, anxiety, and depression during COVID-19. The pooled correlations (ρ) indicated a negative relationship between social support and anxiety (ρ = -0.30, 95% CI = [-0.333, -0.255]) as well as depression (ρ = -0.27, 95% CI = [-0.370, -0.281]). However, further investigation is required to validate these results across different age groups, occupations, and regions. Theoretical Importance: This study emphasizes the multifaceted role of social support in mental health during the COVID-19 pandemic. It highlights the need to reevaluate and expand our understanding of social support's impact on anxiety and depression. The findings contribute to the existing literature by shedding light on the associations and complexities involved in these relationships. Data Collection and Analysis Procedures: The data collection involved an extensive search across six databases to identify relevant studies. The selected studies were then subjected to rigorous analysis using random effects models and subgroup analyses. Pooled correlations were estimated, and homogeneity was assessed using Q and I² tests. Question Addressed: This study aimed to address the question of the impact of social support on anxiety and depression during the COVID-19 pandemic. It sought to determine the consistency of these relationships across different demographic and contextual factors. Conclusion: The findings of this study highlight the significant association between social support, anxiety, and depression during the COVID-19 pandemic. However, further research is needed to validate these findings across different age groups, occupations, and regions. The study emphasizes the need for a comprehensive understanding of social support's multifaceted role in mental health and the importance of considering various contextual and demographic factors in future investigations.

Keywords: social support, anxiety, depression, COVID-19, meta-analysis

Procedia PDF Downloads 59

Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

Abstract:

This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

Procedia PDF Downloads 179

Authors: Saifurahman Fayiz

Abstract:

E-government has become a widespread focus of government efforts in various countries around the world. Many governments around the world have been adopted and introduced e-government systems. This research examines the implementation of the Information& communication technology (ICTS) Model in the Kabul Municipality. The objective of this research is to propose an ICT model in the Kabul Municipality to prevent revenue leakage. The research methodology consists qualitative research method based on a comparative case study. The research findings propose that implementing ICT prevent revenue leakage, increases transparency and paves the way for better services. The key conclusion of this research is that the practice of advanced technology in revenue collection paves the way for transparency and provides services in a decent way. The usage of experiences from other Municipalities, especially Jakarta province and Mitaka Municipality Helps KM to improve revenue and provide better services to the citizens

Keywords: E-government, ICT, municipality, revenue

Procedia PDF Downloads 235

Authors: Vangelis Drosos, Dimitrios Tsoukalos, Dimitrios Tsolis

Abstract:

We present a simple algorithm for capturing a 3D scene (focused on the usage of mobile device cameras in the context of augmented/mixed reality) by using a floating origin camera solution and storing the resulting information in a linear voxel octree. Data is derived from cloud points captured by a mobile device camera. For the purposes of this paper, we assume a scene of fixed size (known to us or determined beforehand) and a fixed voxel resolution. The resulting data is stored in a linear voxel octree using a hashtable. We commence by briefly discussing the logic behind floating origin approaches and the usage of linear voxel octrees for efficient storage. Following that, we present the algorithm for translating captured feature points into voxel data in the context of a fixed origin world and storing them. Finally, we discuss potential applications and areas of future development and improvement to the efficiency of our solution.

Keywords: voxel, octree, computer vision, XR, floating origin

Procedia PDF Downloads 132

Authors: Isabell Koinig, Sandra Diehl

Abstract:

In recent years, the health-care context has not been left unaffected by technological developments. In recent years, the Internet of Medical Things (IoMT)has not only led to a collaboration between disease management and advanced care coordination but also to more personalized health care and patient empowerment. With more than 40 % of all health technology being IoMT-related by 2020, questions regarding privacy become more prevalent, even more so during COVID-19when apps allowing for an intensive tracking of people’s whereabouts and their personal contacts cause privacy advocates to protest and revolt. There is a widespread tendency that even though users may express concerns and fears about their privacy, they behave in a manner that appears to contradict their statements by disclosing personal data. In literature, this phenomenon is discussed as a privacy paradox. While there are some studies investigating the privacy paradox in general, there is only scarce research related to the privacy paradox in the health sector and, to the authors’ knowledge, no empirical study investigating young people’s attitudes toward data security when using wearables and health apps. The empirical study presented in this paper tries to reduce this research gap by focusing on the area of digital and mobile health. It sets out to investigate the degree of importance individuals attribute to protecting their privacy and individual privacy protection strategies. Moreover, the question to which degree individuals between the ages of 20 and 30 years are willing to grant commercial parties access to their private data to use digital health services and apps are put to the test. To answer this research question, results from 6 focus groups with 40 participants will be presented. The focus was put on this age segment that has grown up in a digitally immersed environment. Moreover, it is particularly the young generation who is not only interested in health and fitness but also already uses health-supporting apps or gadgets. Approximately one-third of the study participants were students. Subjects were recruited in August and September 2019 by two trained researchers via email and were offered an incentive for their participation. Overall, results indicate that the young generation is well informed about the growing data collection and is quite critical of it; moreover, they possess knowledge of the potential side effects associated with this data collection. Most respondents indicated to cautiously handle their data and consider privacy as highly relevant, utilizing a number of protective strategies to ensure the confidentiality of their information. Their willingness to share information in exchange for services was only moderately pronounced, particularly in the health context, since health data was seen as valuable and sensitive. The majority of respondents indicated to rather miss out on using digital and mobile health offerings in order to maintain their privacy. While this behavior might be an unintended consequence, it is an important piece of information for app developers and medical providers, who have to find a way to find a user base for their products against the background of rising user privacy concerns.

Keywords: digital health, privacy, privacy paradox, IoMT

Procedia PDF Downloads 136

Authors: Jiexiu Chen

Abstract:

This research aims to examine several vital issues relating to the foreign scholars’ cross-cultural adaptation in China, including how they perceive about the adaptation process, what the affecting factors are in the adaptation, and which strategies they will apply to deal with perceived cultural differences. The target population of this research is academics regularly working or long-term visiting in these joint colleges, and semi-structured interviews are used in data collection. Moreover, the theoretical perspectives mainly include Ward’s sociocultural and psychological adaptation theory, Berry’s adaptation strategies and Black and his colleague’s expatriate’s adjustment model. This research offers an in-depth profile as well as theory-based analysis about this unique group, and the results of this research are profound in offering directory suggestions for foreign scholars to facilitate their adaptation in China better and for the Chinese universities to eliminate intercultural obstacles, and optimize the international cooperation programs in China.

Keywords: cross-cultural adaptation, foreign scholars, expatriates

Procedia PDF Downloads 422

Authors: Patrizia Barroero, Saliha Yagoubi

Abstract:

Mindfulness meditation practices in the context of higher education are becoming more and more common. Some of the reported benefits of mediation interventions and workshops include: improved focus, general well-being, diminished stress, and even increased resilience and grit. A series of workshops free to students, faculty, and staff was offered twice a week over two semesters at Hudson County Community College, New Jersey. The results of an exploratory study based on participants’ subjective reactions to these workshops will be presented. A qualitative approach was used to collect and analyze the data and a hermeneutic phenomenological perspective served as a framework for the research design and data collection and analysis. The data collected includes three recorded videos of semi-structured interviews and several written surveys submitted by volunteer participants.

Keywords: mindfulness meditation practices, stress reduction, resilience, grit, higher education success, qualitative research

Procedia PDF Downloads 73