Search results for: Digital Learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9447

Search results for: Digital Learning

2247 RGB-D SLAM Algorithm Based on pixel level Dense Depth Map

Authors: Hao Zhang, Hongyang Yu

Abstract:

Scale uncertainty is a well-known challenging problem in visual SLAM. Because RGB-D sensor provides depth information, RGB-D SLAM improves this scale uncertainty problem. However, due to the limitation of physical hardware, the depth map output by RGB-D sensor usually contains a large area of missing depth values. These missing depth information affect the accuracy and robustness of RGB-D SLAM. In order to reduce these effects, this paper completes the missing area of the depth map output by RGB-D sensor and then fuses the completed dense depth map into ORB SLAM2. By adding the process of obtaining pixel-level dense depth maps, a better RGB-D visual SLAM algorithm is finally obtained. In the process of obtaining dense depth maps, a deep learning model of indoor scenes is adopted. Experiments are conducted on public datasets and real-world environments of indoor scenes. Experimental results show that the proposed SLAM algorithm has better robustness than ORB SLAM2.

Keywords: RGB-D, SLAM, dense depth, depth map

Procedia PDF Downloads 140
2246 Efficacy and Mechanisms of Acupuncture for Depression: A Meta-Analysis of Clinical and Preclinical Evidence

Authors: Yimeng Zhang

Abstract:

Major depressive disorder (MDD) is a prevalent mental health condition with a substantial economic impact and limited treatment options. Acupuncture has gained attention as a promising non-pharmacological intervention for alleviating depressive symptoms. However, its mechanisms and clinical effectiveness remain incompletely understood. This meta-analysis aims to (1) synthesize existing evidence on the mechanisms and clinical effectiveness of acupuncture for depression and (2) compare these findings with pharmacological interventions, providing insights for future research. Evidence from animal models and clinical studies indicates that acupuncture may enhance hippocampal and network neuroplasticity and reduce brain inflammation, potentially alleviating depressive disorders. Clinical studies suggest that acupuncture can effectively relieve primary depression, particularly in milder cases, and is beneficial in managing post-stroke depression, pain-related depression, and postpartum depression, both as a standalone and adjunctive treatment. Notably, combining acupuncture with antidepressant pharmacotherapy appears to enhance treatment outcomes and reduce medication side effects, addressing a critical issue in conventional drug therapy's high dropout rates. This meta-analysis, encompassing 12 studies and 710 participants, draws data from eight digital databases (PubMed, EMBASE, Web of Science, EBSCOhost, CNKI, CBM, Wangfang, and CQVIP) covering the period from 2012 to 2022. Utilizing Stata software 15.0, the meta-analysis employed random-effects and fixed-effects models to assess the distribution of depression in Traditional Chinese Medicine (TCM). The results underscore the substantial evidence supporting acupuncture's beneficial effects on depression. However, the small sample sizes of many clinical trials raise concerns about the generalizability of the findings, indicating a need for further research to validate these outcomes and optimize acupuncture's role in treating depression.

Keywords: Chinese medicine, acupuncture, depression, meta-analysis

Procedia PDF Downloads 35
2245 Strong Ground Motion Characteristics Revealed by Accelerograms in Ms8.0 Wenchuan Earthquake

Authors: Jie Su, Zhenghua Zhou, Yushi Wang, Yongyi Li

Abstract:

The ground motion characteristics, which are given by the analysis of acceleration records, underlie the formulation and revision of the seismic design code of structural engineering. China Digital Strong Motion Network had recorded a lot of accelerograms of main shock from 478 permanent seismic stations, during the Ms8.0 Wenchuan earthquake on 12th May, 2008. These accelerograms provided a large number of essential data for the analysis of ground motion characteristics of the event. The spatial distribution characteristics, rupture directivity effect, hanging-wall and footwall effect had been studied based on these acceleration records. The results showed that the contours of horizontal peak ground acceleration and peak velocity were approximately parallel to the seismogenic fault which demonstrated that the distribution of the ground motion intensity was obviously controlled by the spatial extension direction of the seismogenic fault. Compared with the peak ground acceleration (PGA) recorded on the sites away from which the front of the fault rupture propagates, the PGA recorded on the sites toward which the front of the fault rupture propagates had larger amplitude and shorter duration, which indicated a significant rupture directivity effect. With the similar fault distance, the PGA of the hanging-wall is apparently greater than that of the foot-wall, while the peak velocity fails to observe this rule. Taking account of the seismic intensity distribution of Wenchuan Ms8.0 earthquake, the shape of strong ground motion contours was significantly affected by the directional effect in the regions with Chinese seismic intensity level VI ~ VIII. However, in the regions whose Chinese seismic intensity level are equal or greater than VIII, the mutual positional relationship between the strong ground motion contours and the surface outcrop trace of the fault was evidently influenced by the hanging-wall and foot-wall effect.

Keywords: hanging-wall and foot-wall effect, peak ground acceleration, rupture directivity effect, strong ground motion

Procedia PDF Downloads 350
2244 Harmonic Data Preparation for Clustering and Classification

Authors: Ali Asheibi

Abstract:

The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

Procedia PDF Downloads 248
2243 Food Security and Utilization in Ethiopia

Authors: Tuji Jemal Ahmed

Abstract:

Food security and utilization are critical aspects of ensuring the well-being and prosperity of a nation. This paper examines the current state of food security and utilization in Ethiopia, focusing on the challenges, opportunities, and strategies employed to address the issue. Ethiopia, a country in East Africa, has made significant progress in recent years to improve food security and utilization for its population. However, persistent challenges such as recurrent droughts, limited access to resources, and low agricultural productivity continue to pose obstacles to achieving sustainable food security. The paper begins by providing an overview of the concept of food security, emphasizing its multidimensional nature and the importance of access, availability, utilization, and stability. It then explores the specific factors influencing food security and utilization in Ethiopia, including natural resources, climate variability, agricultural practices, infrastructure, and socio-economic factors. Furthermore, the paper highlights the initiatives and interventions implemented by the Ethiopian government, non-governmental organizations, and international partners to enhance food security and utilization. These efforts include agricultural extension programs, irrigation projects, investments in rural infrastructure, and social safety nets to protect vulnerable populations. The study also examines the role of technology and innovation in improving food security and utilization in Ethiopia. It explores the potential of sustainable agricultural practices, such as conservation agriculture, improved seed varieties, and precision farming techniques. Additionally, it discusses the role of digital technologies in enhancing access to market information, financial services, and agricultural inputs for smallholder farmers. Finally, the paper discusses the importance of collaboration and partnerships between stakeholders, including government agencies, development organizations, research institutions, and communities, in addressing food security and utilization challenges. It emphasizes the need for integrated and holistic approaches that consider both production and consumption aspects of the food system.

Keywords: food security, utilization, Ethiopia, challenges

Procedia PDF Downloads 121
2242 Food Security and Utilization in Ethiopia

Authors: Tuji Jemal Ahmed

Abstract:

Food security and utilization are critical aspects of ensuring the well-being and prosperity of a nation. This paper examines the current state of food security and utilization in Ethiopia, focusing on the challenges, opportunities, and strategies employed to address the issue. Ethiopia, a country in East Africa, has made significant progress in recent years to improve food security and utilization for its population. However, persistent challenges such as recurrent droughts, limited access to resources, and low agricultural productivity continue to pose obstacles to achieving sustainable food security. The paper begins by providing an overview of the concept of food security, emphasizing its multidimensional nature and the importance of access, availability, utilization, and stability. It then explores the specific factors influencing food security and utilization in Ethiopia, including natural resources, climate variability, agricultural practices, infrastructure, and socio-economic factors. Furthermore, the paper highlights the initiatives and interventions implemented by the Ethiopian government, non-governmental organizations, and international partners to enhance food security and utilization. These efforts include agricultural extension programs, irrigation projects, investments in rural infrastructure, and social safety nets to protect vulnerable populations. The study also examines the role of technology and innovation in improving food security and utilization in Ethiopia. It explores the potential of sustainable agricultural practices, such as conservation agriculture, improved seed varieties, and precision farming techniques. Additionally, it discusses the role of digital technologies in enhancing access to market information, financial services, and agricultural inputs for smallholder farmers. Finally, the paper discusses the importance of collaboration and partnerships between stakeholders, including government agencies, development organizations, research institutions, and communities, in addressing food security and utilization challenges. It emphasizes the need for integrated and holistic approaches that consider both production and consumption aspects of the food system.

Keywords: food security, utilization, Ethiopia, challenges

Procedia PDF Downloads 85
2241 Innovations in Teaching

Authors: Dilek Turan Eroğlu

Abstract:

Educators have been searching the more effective and appalling methods of teaching for ages. It has always been an issue among the teachers and scientists to improve the quality of education and to ensure that all students have equal opportunities to learn. However, when it comes to the effective ways of learning,the learners are exposed to the ways which are chosen and approved to be effective by their teachers not by the learners themselves. This is the main problem of this study as the learners are not always happy to be in their classes being treated with their teachers’ favourite styles. This paper is telling the results of a study which has been conducted with the university students in Turkey. The students have been interviewed and asked to respond some questions related to best practices to find out their favourite styles, medium, techniques and strategies. The study has been conducted using qualitative research methods i.e one to one interviews and group discussions. The results show that the learners have significantly different views than the educators when it comes to modern teaching styles. Their definition of the term “modern teaching styles” is different than the general understanding. The university students expect their teachers to be “early adopter”. of ICT tools and or the other electronic devices, but a modern teacher must have many other characteristics for them.

Keywords: effective, innovation, teaching, modern teaching styles

Procedia PDF Downloads 344
2240 Application of Artificial Neural Network in Initiating Cleaning Of Photovoltaic Solar Panels

Authors: Mohamed Mokhtar, Mostafa F. Shaaban

Abstract:

Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.

Keywords: machine learning, dust, PV panels, renewable energy

Procedia PDF Downloads 144
2239 Meaningful Habit for EFL Learners

Authors: Ana Maghfiroh

Abstract:

Learning a foreign language needs a big effort from the learner itself to make their language ability grows better day by day. Among those, they also need a support from all around them including teacher, friends, as well as activities which support them to speak the language. When those activities developed well as a habit which are done regularly, it will help improving the students’ language competence. It was a qualitative research which aimed to find out and describe some activities implemented in Pesantren Al Mawaddah, Ponorogo, in order to teach the students a foreign language. In collecting the data, the researcher used interview, questionnaire, and documentation. From the study, it was found that Pesantren Al Mawaddah had successfully built the language habit on the students to speak the target language. More than 15 hours a day students were compelled to speak foreign language, Arabic or English, in turn. It aimed to habituate the students to keep in touch with the target language. The habit was developed through daily language activities, such as dawn vocabs giving, dictionary handling, daily language use, speech training and language intensive course, daily language input, and night vocabs memorizing. That habit then developed the students awareness towards the language learned as well as promoted their language mastery.

Keywords: habit, communicative competence, daily language activities, Pesantren

Procedia PDF Downloads 539
2238 Foreign Language Anxiety: Perceptions and Attitudes in the Egyptian ESL Classroom

Authors: Shaden S. Attia

Abstract:

This study investigated foreign language anxiety (FLA) and teachers’ awareness of its presence in the Egyptian ESL classrooms and how FLA correlates with different variables such as four language skills, students' sex, and activities used in class. A combination of quantitative and qualitative instruments was used in order to investigate the previously mentioned variables, which included five interviews with teachers, six classroom observations, a survey for teachers, and a questionnaire for students. The findings of the study revealed that some teachers were aware of the presence of FLA, with some of them believing that other teachers, however, are not aware of this phenomenon, and even when they notice anxiety, they do not always relate it to learning a foreign language. The results also showed that FLA was affected by students’ sex, different language skills, and affective anxieties; however, teachers were unaware of the effect of these variables. The results demonstrated that both teachers and students preferred group and pair work to individual activities as they were more relaxing and less anxiety-provoking. These findings contribute to raising teachers' awareness of FLA in ESL classrooms and how it is affected by different variables.

Keywords: foreign language anxiety, situation specific anxiety, skill-specific anxiety, teachers’ perceptions

Procedia PDF Downloads 154
2237 Alternator Fault Detection Using Wigner-Ville Distribution

Authors: Amin Ranjbar, Amir Arsalan Jalili Zolfaghari, Amir Abolfazl Suratgar, Mehrdad Khajavi

Abstract:

This paper describes two stages of learning-based fault detection procedure in alternators. The procedure consists of three states of machine condition namely shortened brush, high impedance relay and maintaining a healthy condition in the alternator. The fault detection algorithm uses Wigner-Ville distribution as a feature extractor and also appropriate feature classifier. In this work, ANN (Artificial Neural Network) and also SVM (support vector machine) were compared to determine more suitable performance evaluated by the mean squared of errors criteria. Modules work together to detect possible faulty conditions of machines working. To test the method performance, a signal database is prepared by making different conditions on a laboratory setup. Therefore, it seems by implementing this method, satisfactory results are achieved.

Keywords: alternator, artificial neural network, support vector machine, time-frequency analysis, Wigner-Ville distribution

Procedia PDF Downloads 374
2236 An Approach to Tackle Start up Problems Using Applied Games

Authors: Aiswarya Gopal, Kamal Bijlani, Vinoth Rengaraj, R. Jayakrishnan

Abstract:

In the business world, the term “startup” is frequently ringing the bell with the high frequency of young ventures. The main dilemma of startups is the unsuccessful management of the unique risks that have to be confronted in the present world of competition and technology. This research work tried to bring out a game based methodology to improve enough real-world experience among entrepreneurs as well as management students to handle risks and challenges in the field. The game will provide experience to the player to overcome challenges like market problems, running out of cash, poor management, and product problems which can be resolved by a proper strategic approach in the entrepreneurship world. The proposed serious game works on the life cycle of a new software enterprise where the entrepreneur moves from the planning stage to secured financial stage, laying down the basic business structure, and initiates the operations ensuring the increment in confidence level of the player.

Keywords: business model, game based learning, poor management, start up

Procedia PDF Downloads 475
2235 English Language Acquisition and Flipped Classroom

Authors: Yuqing Sun

Abstract:

Nowadays, English has been taught in many countries as a second language. One of the major ways to learn this language is through the class teaching. As in the field of second language acquisition, there are many factors to affect its acquisition processes, such as the target language itself, a learner’s personality, cognitive factor, language transfer, and the outward factors (teaching method, classroom, environmental factor, teaching policy, social environment and so on). Flipped Classroom as a newly developed classroom model has been widely used in language teaching classroom, which was, to some extent, accepted by teachers and students for its effect. It distinguishes itself from the traditional classroom for its focus on the learner and its great importance attaching to the personal learning process and the application of technology. The class becomes discussion-targeted, and the class order is somewhat inverted since the teaching process is carried out outside the class, while the class is only for knowledge-internalization. This paper will concentrate on the influences of the flipped classroom, as a classroom affecting factor, on the the process of English acquisition by the way of case studies (English teaching class in China), and the analysis of the mechanism of the flipped classroom itself to propose some feasible advice of promoting the the effectiveness of English acquisition.

Keywords: second language acquisition, English, flipped classroom, case

Procedia PDF Downloads 400
2234 Spectral Anomaly Detection and Clustering in Radiological Search

Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

Abstract:

Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

Procedia PDF Downloads 695
2233 A Second Look at Gesture-Based Passwords: Usability and Vulnerability to Shoulder-Surfing Attacks

Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

Abstract:

For security purposes, it is important to detect passwords entered by unauthorized users. With traditional alphanumeric passwords, if the content of a password is acquired and correctly entered by an intruder, it is impossible to differentiate the password entered by the intruder from those entered by the authorized user because the password entries contain precisely the same character set. However, no two entries for the gesture-based passwords, even those entered by the person who created the password, will be identical. There are always variations between entries, such as the shape and length of each stroke, the location of each stroke, and the speed of drawing. It is possible that passwords entered by the unauthorized user contain higher levels of variations when compared with those entered by the authorized user (the creator). The difference in the levels of variations may provide cues to detect unauthorized entries. To test this hypothesis, we designed an empirical study, collected and analyzed the data with the help of machine-learning algorithms. The results of the study are significant.

Keywords: authentication, gesture-based passwords, shoulder-surfing attacks, usability

Procedia PDF Downloads 139
2232 Development of Innovative Islamic Web Applications

Authors: Farrukh Shahzad

Abstract:

The rich Islamic resources related to religious text, Islamic sciences, and history are widely available in print and in electronic format online. However, most of these works are only available in Arabic language. In this research, an attempt is made to utilize these resources to create interactive web applications in Arabic, English and other languages. The system utilizes the Pattern Recognition, Knowledge Management, Data Mining, Information Retrieval and Management, Indexing, storage and data-analysis techniques to parse, store, convert and manage the information from authentic Arabic resources. These interactive web Apps provide smart multi-lingual search, tree based search, on-demand information matching and linking. In this paper, we provide details of application architecture, design, implementation and technologies employed. We also presented the summary of web applications already developed. We have also included some screen shots from the corresponding web sites. These web applications provide an Innovative On-line Learning Systems (eLearning and computer based education).

Keywords: Islamic resources, Muslim scholars, hadith, narrators, history, fiqh

Procedia PDF Downloads 283
2231 Outcome of Bowel Management Program in Patient with Spinal Cord Injury

Authors: Roongtiwa Chobchuen, Angkana Srikhan, Pattra Wattanapan

Abstract:

Background: Neurogenic bowel is common condition after spinal cord injury. Most of spinal cord injured patients have motor weakness, mobility impairment which leads to constipation. Moreover, the neural pathway involving bowel function is interrupted. Therefore, the bowel management program should be implemented in nursing care in the earliest time after the onset of the disease to prevent the morbidity and mortality. Objective: To study the outcome of bowel management program of the patients with spinal cord injury who admitted for rehabilitation program. Study design: Descriptive study. Setting: Rehabilitation ward in Srinagarind Hospital. Populations: patients with subacute to chronic spinal cord injury who admitted at rehabilitation ward, Srinagarind hospital, aged over 18 years old. Instrument: The neurogenic bowel dysfunction score (NBDS) was used to determine the severity of neurogenic bowel. Procedure and statistical analysis: All participants were asked to complete the demographic data; age gender, duration of disease, diagnosis. The individual bowel function was assessed using NBDS at admission. The patients and caregivers were trained by nurses about the bowel management program which consisted of diet modification, abdominal massage, digital stimulation, stool evacuation including medication and physical activity. The outcome of the bowel management program was assessed by NBDS at discharge. The chi-square test was used to detect the difference in severity of neurogenic bowel at admission and discharge. Results: Sixteen spinal cord injured patients were enrolled in the study (age 45 ± 17 years old, 69% were male). Most of them (50%) were tetraplegia. On the admission, 12.5%, 12.5%, 43.75% and 31.25% were categorized as very minor (NBDS 0-6), minor (NBDS 7-9), moderate (NBDS 10-13) and severe (NBDS 14+) respectively. The severity of neurogenic bowel was decreased significantly at discharge (56.25%, 18.755%, 18.75% and 6.25% for very minor, minor, moderate and severe group respectively; p < 0.001) compared with NBDS at admission. Conclusions: Implementation of the effective bowel program decrease the severity of the neurogenic bowel in patient with spinal cord injury.

Keywords: neurogenic bowel, NBDS, spinal cord injury, bowel program

Procedia PDF Downloads 243
2230 Positive Politeness in Writing Centre Consultations with an Emphasis on Praise

Authors: Avasha Rambiritch, Adelia Carstens

Abstract:

In especially the context of a writing center, learning takes place during, and as part of, the conversations between the writing center tutor and the student. This interaction or dialogue is an integral part of writing center research and is the focus of this largely qualitative study, employing a politeness lens. While there is some research on positive politeness strategies employed by writing center tutors, there is very little research on specifically praising as a positive politeness strategy. This study attempts to fill this gap by analyzing a corpus of 10 video-recorded consultations to determine how tutors in a writing center utilize the positive politeness strategy of praise. Findings indicate that while tutors exploit a range of politeness strategies, praise is used more often than any other strategy. The research indicates that praise as a politeness strategy is utilized significantly more when commenting on higher-order concerns, as in line with the writing center literature. The benefits of this study include insights into how such analyses can be used to better prepare and equip the tutors (usually postgraduate students appointed as part-time tutors in the writing center) for the work they do on a daily basis.

Keywords: writing center, academic writing, positive politeness, tutor

Procedia PDF Downloads 215
2229 Recruitment Strategies and Migration Regulations for International Students in the United States and Canada: A Comparative Study

Authors: Aynur Charkasova

Abstract:

The scientific and economic contributions of international students cannot be underestimated. International education continues to be a competitive global industry, and many countries are seeking to recruit the best and the brightest to reinforce scientific innovations, boost intercultural learning, and bring more funding to universities and colleges. Substantial changes in international educational policies and migration regulations have been made in the hopes of recruiting global talent. This paper explores and compares recruitment strategies, employment opportunities, and a legal path to permanent residency policies related to international students in the United States of America and Canada. This study will utilize the legal information available from the government websites of both countries and peer-reviewed scholarly articles and will highlight which approach promises a better path in recruiting and retention of international students. The findings from the study will be discussed and recommendations will be provided.

Keywords: International students, current immigration policies, STEM, employability, visa reforms for international students, Canadian recruitment policy

Procedia PDF Downloads 75
2228 Performance of Neural Networks vs. Radial Basis Functions When Forming a Metamodel for Residential Buildings

Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies

Abstract:

With the world climate projected to warm and major cities in developing countries becoming increasingly populated and polluted, governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of an adaptable model of these risks. Simulations are performed using the EnergyPlus building physics software. An accurate metamodel is formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) are compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.

Keywords: neural networks, radial basis functions, metamodelling, python machine learning libraries

Procedia PDF Downloads 447
2227 The Role of Artificial Intelligence in Concrete Constructions

Authors: Ardalan Tofighi Soleimandarabi

Abstract:

Artificial intelligence has revolutionized the concrete construction industry and improved processes by increasing efficiency, accuracy, and sustainability. This article examines the applications of artificial intelligence in predicting the compressive strength of concrete, optimizing mixing plans, and improving structural health monitoring systems. Artificial intelligence-based models, such as artificial neural networks (ANN) and combined machine learning techniques, have shown better performance than traditional methods in predicting concrete properties. In addition, artificial intelligence systems have made it possible to improve quality control and real-time monitoring of structures, which helps in preventive maintenance and increases the life of infrastructure. Also, the use of artificial intelligence plays an effective role in sustainable construction by optimizing material consumption and reducing waste. Although the implementation of artificial intelligence is associated with challenges such as high initial costs and the need for specialized training, it will create a smarter, more sustainable, and more affordable future for concrete structures.

Keywords: artificial intelligence, concrete construction, compressive strength prediction, structural health monitoring, stability

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2226 Heterogeneous-Resolution and Multi-Source Terrain Builder for CesiumJS WebGL Virtual Globe

Authors: Umberto Di Staso, Marco Soave, Alessio Giori, Federico Prandi, Raffaele De Amicis

Abstract:

The increasing availability of information about earth surface elevation (Digital Elevation Models DEM) generated from different sources (remote sensing, Aerial Images, Lidar) poses the question about how to integrate and make available to the most than possible audience this huge amount of data. In order to exploit the potential of 3D elevation representation the quality of data management plays a fundamental role. Due to the high acquisition costs and the huge amount of generated data, highresolution terrain surveys tend to be small or medium sized and available on limited portion of earth. Here comes the need to merge large-scale height maps that typically are made available for free at worldwide level, with very specific high resolute datasets. One the other hand, the third dimension increases the user experience and the data representation quality, unlocking new possibilities in data analysis for civil protection, real estate, urban planning, environment monitoring, etc. The open-source 3D virtual globes, which are trending topics in Geovisual Analytics, aim at improving the visualization of geographical data provided by standard web services or with proprietary formats. Typically, 3D Virtual globes like do not offer an open-source tool that allows the generation of a terrain elevation data structure starting from heterogeneous-resolution terrain datasets. This paper describes a technological solution aimed to set up a so-called “Terrain Builder”. This tool is able to merge heterogeneous-resolution datasets, and to provide a multi-resolution worldwide terrain services fully compatible with CesiumJS and therefore accessible via web using traditional browser without any additional plug-in.

Keywords: Terrain Builder, WebGL, Virtual Globe, CesiumJS, Tiled Map Service, TMS, Height-Map, Regular Grid, Geovisual Analytics, DTM

Procedia PDF Downloads 426
2225 The Effectiveness of Adaptive Difficulty Adjustment in Touch Tablet App on Young Children's Spatial Problem Solving Development

Authors: Chenchen Liu, Jacques Audran

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Using tablet apps with a certain educational purpose to promote young children’s cognitive development, is quite common now. Developing an educational app on an Ipad like tablet, especially for a young child (age 3-5) requires an optimal level of challenge to continuously attract children’s attention and obtain an educational effect. Adaptive difficulty adjustment, which could dynamically set the difficulty in the challenge according to children’s performance, seems to be a good solution. Since space concept plays an important role in young children’s cognitive development, we made an experimental comparison in a French kindergarten between one group of 23 children using an educational app ‘Debout Ludo’ with adaptive difficulty settings and another group of 20 children using the previous version of ‘Debout Ludo’ with a classic incremental difficulty adjustment. The experiment results of spatial problem solving indicated that a significantly higher learning outcome was acquired by the young children who used the adaptive version of the app.

Keywords: adaptive difficulty, spatial problem solving, tactile tablet, young children

Procedia PDF Downloads 444
2224 Towards a Measuring Tool to Encourage Knowledge Sharing in Emerging Knowledge Organizations: The Who, the What and the How

Authors: Rachel Barker

Abstract:

The exponential velocity in the truly knowledge-intensive world today has increasingly bombarded organizations with unfathomable challenges. Hence organizations are introduced to strange lexicons of descriptors belonging to a new paradigm of who, what and how knowledge at individual and organizational levels should be managed. Although organizational knowledge has been recognized as a valuable intangible resource that holds the key to competitive advantage, little progress has been made in understanding how knowledge sharing at individual level could benefit knowledge use at collective level to ensure added value. The research problem is that a lack of research exists to measure knowledge sharing through a multi-layered structure of ideas with at its foundation, philosophical assumptions to support presuppositions and commitment which requires actual findings from measured variables to confirm observed and expected events. The purpose of this paper is to address this problem by presenting a theoretical approach to measure knowledge sharing in emerging knowledge organizations. The research question is that despite the competitive necessity of becoming a knowledge-based organization, leaders have found it difficult to transform their organizations due to a lack of knowledge on who, what and how it should be done. The main premise of this research is based on the challenge for knowledge leaders to develop an organizational culture conducive to the sharing of knowledge and where learning becomes the norm. The theoretical constructs were derived and based on the three components of the knowledge management theory, namely technical, communication and human components where it is suggested that this knowledge infrastructure could ensure effective management. While it is realised that it might be a little problematic to implement and measure all relevant concepts, this paper presents effect of eight critical success factors (CSFs) namely: organizational strategy, organizational culture, systems and infrastructure, intellectual capital, knowledge integration, organizational learning, motivation/performance measures and innovation. These CSFs have been identified based on a comprehensive literature review of existing research and tested in a new framework adapted from four perspectives of the balanced score card (BSC). Based on these CSFs and their items, an instrument was designed and tested among managers and employees of a purposefully selected engineering company in South Africa who relies on knowledge sharing to ensure their competitive advantage. Rigorous pretesting through personal interviews with executives and a number of academics took place to validate the instrument and to improve the quality of items and correct wording of issues. Through analysis of surveys collected, this research empirically models and uncovers key aspects of these dimensions based on the CSFs. Reliability of the instrument was calculated by Cronbach’s a for the two sections of the instrument on organizational and individual levels.The construct validity was confirmed by using factor analysis. The impact of the results was tested using structural equation modelling and proved to be a basis for implementing and understanding the competitive predisposition of the organization as it enters the process of knowledge management. In addition, they realised the importance to consolidate their knowledge assets to create value that is sustainable over time.

Keywords: innovation, intellectual capital, knowledge sharing, performance measures

Procedia PDF Downloads 195
2223 Trip Reduction in Turbo Machinery

Authors: Pranay Mathur, Carlo Michelassi, Simi Karatha, Gilda Pedoto

Abstract:

Industrial plant uptime is top most importance for reliable, profitable & sustainable operation. Trip and failed start has major impact on plant reliability and all plant operators focussed on efforts required to minimise the trips & failed starts. The performance of these CTQs are measured with 2 metrics, MTBT(Mean time between trips) and SR (Starting reliability). These metrics helps to identify top failure modes and identify units need more effort to improve plant reliability. Baker Hughes Trip reduction program structured to reduce these unwanted trip 1. Real time machine operational parameters remotely available and capturing the signature of malfunction including related boundary condition. 2. Real time alerting system based on analytics available remotely. 3. Remote access to trip logs and alarms from control system to identify the cause of events. 4. Continuous support to field engineers by remotely connecting with subject matter expert. 5. Live tracking of key CTQs 6. Benchmark against fleet 7. Break down to the cause of failure to component level 8. Investigate top contributor, identify design and operational root cause 9. Implement corrective and preventive action 10. Assessing effectiveness of implemented solution using reliability growth models. 11. Develop analytics for predictive maintenance With this approach , Baker Hughes team is able to support customer in achieving their Reliability Key performance Indicators for monitored units, huge cost savings for plant operators. This Presentation explains these approach while providing successful case studies, in particular where 12nos. of LNG and Pipeline operators with about 140 gas compressing line-ups has adopted these techniques and significantly reduce the number of trips and improved MTBT

Keywords: reliability, availability, sustainability, digital infrastructure, weibull, effectiveness, automation, trips, fail start

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2222 Creation of a Trust-Wide, Cross-Speciality, Virtual Teaching Programme for Doctors, Nurses and Allied Healthcare Professionals

Authors: Nelomi Anandagoda, Leanne J. Eveson

Abstract:

During the COVID-19 pandemic, the surge in in-patient admissions across the medical directorate of a district general hospital necessitated the implementation of an incident rota. Conscious of the impact on training and professional development, the idea of developing a virtual teaching programme was conceived. The programme initially aimed to provide junior doctors, specialist nurses, pharmacists, and allied healthcare professionals from medical specialties and those re-deployed from other specialties (e.g., ophthalmology, GP, surgery, psychiatry) the knowledge and skills to manage the deteriorating patient with COVID-19. The programme was later developed to incorporate the general internal medicine curriculum. To facilitate continuing medical education whilst maintaining social distancing during this period, a virtual platform was used to deliver teaching to junior doctors across two large district general hospitals and two community hospitals. Teaching sessions were recorded and uploaded to a common platform, providing a resource for participants to catch up on and re-watch teaching sessions, making strides towards reducing discrimination against the professional development of less than full-time trainees. Thus, creating a learning environment, which is inclusive and accessible to adult learners in a self-directed manner. The negative impact of the pandemic on the well-being of healthcare professionals is well documented. To support the multi-disciplinary team, the virtual teaching programme evolved to included sessions on well-being, resilience, and work-life balance. Providing teaching for learners across the multi-disciplinary team (MDT) has been an eye-opening experience. By challenging the concept that learners should only be taught within their own peer groups, the authors have fostered a greater appreciation of the strengths of the MDT and showcased the immense wealth of expertise available within the trust. The inclusive nature of the teaching and the ease of joining a virtual teaching session has facilitated the dissemination of knowledge across the MDT, thus improving patient care on the frontline. The weekly teaching programme has been running for over eight months, with ongoing engagement, interest, and participation. As described above, the teaching programme has evolved to accommodate the needs of its learners. It has received excellent feedback with an appreciation of its inclusive, multi-disciplinary, and holistic nature. The COVID-19 pandemic provided a catalyst to rapidly develop novel methods of working and training and widened access/exposure to the virtual technologies available to large organisations. By merging pedagogical expertise and technology, the authors have created an effective online learning environment. Although the authors do not propose to replace face-to-face teaching altogether, this model of virtual multidisciplinary team, cross-site teaching has proven to be a great leveler. It has made high-quality teaching accessible to learners of different confidence levels, grades, specialties, and working patterns.

Keywords: cross-site, cross-speciality, inter-disciplinary, multidisciplinary, virtual teaching

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2221 Development and Validation of Research Process for Enhancing Humanities Competence of Medical Students

Authors: S. J. Yune, K. H. Park

Abstract:

The purpose of this study was to examine the validity of the research process for enhancing the humanities competence of the medical students. The research process was developed to be operated as a core subject course of 3 semesters. Among them, the research process for enhancing humanities capacity consisted of humanities and societies (6 teams) and education-psychology (2teams). The subjects of this study were 88-second grade students and 22 professors who participated in the research process. Among them, 13 professors participated in the study of humanities and 37 students. In the validity test, the professors were more likely to have more validity in the research process than the students in all areas of logic (p = .001), influence (p = .037), process (p = .001). The validity of the professor was higher than that of the students. The professors highly evaluated the students' learning outcomes and showed the most frequency to the prize group. As a result of analyzing the agreement between the students and the professors through the Kappa coefficient, the agreement degree of communication and cooperation competence was moderate to .430. Problem-solving ability was .340, which showed a fair degree of agreement. However, other factors showed only a slight degree of agreement of less than .20.

Keywords: research process, medical school, humanities competence, validity verification

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2220 Rising Levels of Greenhouse Gases: Implication for Global Warming in Anambra State South Eastern Nigeria

Authors: Chikwelu Edward Emenike, Ogbuagu Uchenna Fredrick

Abstract:

About 34% of the solar radiant energy reaching the earth is immediately reflected back to space as incoming radiation by clouds, chemicals, dust in the atmosphere and by the earth’s surface. Most of the remaining 66% warms the atmosphere and land. Most of the incoming solar radiation not reflect away is degraded into low-quality heat and flows into space. The rate at which this energy returns to space as low-quality heat is affected by the presence of molecules of greenhouse gases. Gaseous emission was measured with the aid of Growen gas Analyzer with a digital readout. Total measurements of eight parameters of twelve selected sample locations taken at two different seasons within two months were made. The ambient air quality investigation in Anambra State has shown the overall mean concentrations of gaseous emission at twelve (12) locations. The mean gaseous emissions showed (NO2=0.66ppm, SO2=0.30ppm, CO=43.93ppm, H2S=2.17ppm, CH4=1.27ppm, CFC=1.59ppb, CO2=316.33ppm, N2O=302.67ppb and O3=0.37ppm). These values do not conform to the National Ambient Air Quality Standard (NAAQS) and thus contribute significantly to the global warming. Because some of these gaseous emissions (SO2, NO2) are oxidizing agents, they act as irritants that damage delicate tissues in the eyes and respiratory passages. These can impair lung function and trigger cardiovascular problems as the heart tries to compensate for lack of Oxygen by pumping faster and harder. The major sources of air pollution are transportation, industrial processes, stationary fuel combustion and solid waste disposal, thus much is yet to be done in a developing country like Nigeria. Air pollution control using pollution-control equipment to reduce the major conventional pollutants, relocating people who live very close to dumpsites, processing and treatment of gases to produce electricity, heat, fuel and various chemical components should be encouraged.

Keywords: ambient air, atmosphere, greenhouse gases, anambra state

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2219 Inferential Reasoning for Heterogeneous Multi-Agent Mission

Authors: Sagir M. Yusuf, Chris Baber

Abstract:

We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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2218 Thulium Laser Vaporisation and Enucleation of Prostate in Patients on Anticoagulants and Antiplatelet Agents

Authors: Abdul Fatah, Naveenchandra Acharya, Vamshi Krishna, T. Shivaprasad, Ramesh Ramayya

Abstract:

Background: Significant number of patients with bladder outlet obstruction due to BPH are on anti-platelets and anticoagulants. Prostate surgery in this group of patients either in the form of TURP or Open prostatectomy is associated with increased risk of bleeding complications requiring transfusions, packing of the prostatic fossa or ligation or embolization of internal iliac arteries. Withholding of antiplatelets and anticoagulants may be associated with cardiac and other complications. Efficacy of Thulium Laser in the above group of patients was evaluated in terms of peri-operative, postoperative and delayed bleeding complications as well as cardiac events in peri-operative and immediate postoperative period. Methods: 217 patients with a mean age of 68.8 years were enrolled between March 2009 and March 2013 (36 months), and treated for BPH with ThuLEP. Every patient was evaluated at base line according to: Digital Rectal Examination (DRE), prostate volume, Post-Voided volume (PVR), International Prostate Symptoms Score (I-PSS), PSA values, urine analysis and urine culture, uroflowmetry. The post operative complications in the form of drop in hemoglobin level, transfusion rates, post –operative cardiac events within a period of 30 days, delayed hematuria and events like deep vein thrombosis and pulmonary embolism were noted. Results: Our data showed a better post-operative outcome in terms of, postoperative bleeding requiring intervention 7 (3.2%), transfusion rate 4 (1.8%) and cardiac events within a period of 30 days 4(1.8%), delayed hematuria within 6 months 2(0.9 %) compared other series of prostatectomies. Conclusion: The thulium LASER prostatectomy is a safe and effective option for patients with cardiac comorbidties and those patients who are on antiplatelet agents and anticoagulants. The complication rate is less as compared to larger series reported with open and transurethral prostatectomies.

Keywords: thulium laser, prostatectomy, antiplatelet agents, bleeding

Procedia PDF Downloads 393