Search results for: deep acting
1218 Flood Simulation and Forecasting for Sustainable Planning of Response in Municipalities
Authors: Mariana Damova, Stanko Stankov, Emil Stoyanov, Hristo Hristov, Hermand Pessek, Plamen Chernev
Abstract:
We will present one of the first use cases on the DestinE platform, a joint initiative of the European Commission, European Space Agency and EUMETSAT, providing access to global earth observation, meteorological and statistical data, and emphasize the good practice of intergovernmental agencies acting in concert. Further, we will discuss the importance of space-bound disruptive solutions for improving the balance between the ever-increasing water-related disasters coming from climate change and minimizing their economic and societal impact. The use case focuses on forecasting floods and estimating the impact of flood events on the urban environment and the ecosystems in the affected areas with the purpose of helping municipal decision-makers to analyze and plan resource needs and to forge human-environment relationships by providing farmers with insightful information for improving their agricultural productivity. For the forecast, we will adopt an EO4AI method of our platform ISME-HYDRO, in which we employ a pipeline of neural networks applied to in-situ measurements and satellite data of meteorological factors influencing the hydrological and hydrodynamic status of rivers and dams, such as precipitations, soil moisture, vegetation index, snow cover to model flood events and their span. ISME-HYDRO platform is an e-infrastructure for water resources management based on linked data, extended with further intelligence that generates forecasts with the method described above, throws alerts, formulates queries, provides superior interactivity and drives communication with the users. It provides synchronized visualization of table views, graphviews and interactive maps. It will be federated with the DestinE platform.Keywords: flood simulation, AI, Earth observation, e-Infrastructure, flood forecasting, flood areas localization, response planning, resource estimation
Procedia PDF Downloads 291217 Algorithm Research on Traffic Sign Detection Based on Improved EfficientDet
Authors: Ma Lei-Lei, Zhou You
Abstract:
Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.Keywords: convolutional neural network, transformer, feature pyramid networks, loss function
Procedia PDF Downloads 1021216 Strengthening of Reinforced Concrete Beams Using Steel Plates
Authors: Ghusen al-Kafri, Mohammed Ali Abdallah Elsageer, Ahmed Mohamed Hadya Alsdaai, Abdeimanam Salhien Salih Khalifa
Abstract:
In this paper, external reinforcement to enhance a reinforced concrete structure performance has been done using externally bonded steel plate. This technique has been reported effective in enhancing the strength of reinforced concrete beam, a study to determine the effectiveness of steel plate as an external reinforcement was carried out. A total of two groups of beams and one group content five beams, each 750 mm long, 150 mm wide, and 150 mm deep were cast, strengthened and tested till failure under two point loads. One beam was act as a control beam without strengthening and other four beams were strengthened with steel plate at a different arrangement. Other group beams were strengthened with steel plate in shear zone and also strengthened at bottom as first group. The behaviours of the strengthened beams were studied through their load-deflection characteristic upon bending, cracking and mode of failure. The results confirmed that all steel plate arrangements enhanced the strength of the reinforced concrete beam, the positioning of the steel plate affect the moment carrying capacity of the beam.Keywords: beams, bending, beflection, steel plates
Procedia PDF Downloads 4201215 Application of Neural Network in Portfolio Product Companies: Integration of Boston Consulting Group Matrix and Ansoff Matrix
Authors: M. Khajezadeh, M. Saied Fallah Niasar, S. Ali Asli, D. Davani Davari, M. Godarzi, Y. Asgari
Abstract:
This study aims to explore the joint application of both Boston and Ansoff matrices in the operational development of the product. We conduct deep analysis, by utilizing the Artificial Neural Network, to predict the position of the product in the market while the company is interested in increasing its share. The data are gathered from two industries, called hygiene and detergent. In doing so, the effort is being made by investigating the behavior of top player companies and, recommend strategic orientations. In conclusion, this combination analysis is appropriate for operational development; as well, it plays an important role in providing the position of the product in the market for both hygiene and detergent industries. More importantly, it will elaborate on the company’s strategies to increase its market share related to a combination of the Boston Consulting Group (BCG) Matrix and Ansoff Matrix.Keywords: artificial neural network, portfolio analysis, BCG matrix, Ansoff matrix
Procedia PDF Downloads 1471214 A Topological Approach for Motion Track Discrimination
Authors: Tegan H. Emerson, Colin C. Olson, George Stantchev, Jason A. Edelberg, Michael Wilson
Abstract:
Detecting small targets at range is difficult because there is not enough spatial information present in an image sub-region containing the target to use correlation-based methods to differentiate it from dynamic confusers present in the scene. Moreover, this lack of spatial information also disqualifies the use of most state-of-the-art deep learning image-based classifiers. Here, we use characteristics of target tracks extracted from video sequences as data from which to derive distinguishing topological features that help robustly differentiate targets of interest from confusers. In particular, we calculate persistent homology from time-delayed embeddings of dynamic statistics calculated from motion tracks extracted from a wide field-of-view video stream. In short, we use topological methods to extract features related to target motion dynamics that are useful for classification and disambiguation and show that small targets can be detected at range with high probability.Keywords: motion tracks, persistence images, time-delay embedding, topological data analysis
Procedia PDF Downloads 1171213 Transfer Learning for Protein Structure Classification at Low Resolution
Authors: Alexander Hudson, Shaogang Gong
Abstract:
Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.Keywords: transfer learning, protein distance maps, protein structure classification, neural networks
Procedia PDF Downloads 1431212 Helping the Helper: Impact of Teaching Assistantship Program among Psychology Alumni
Authors: Clarissa Delariarte
Abstract:
With the aim of helping the poorest of the poor achieve quality education, Psychology students supported and served as teacher assistants to its Early Childhood Education Center in two barangays since the program began in 1999. Making use of qualitative approach, the impact of the program to 29 alumni who served as teacher assistants between 2000-2014 was assessed. Results show that the impact to the alumni is in cognitive as well as social-emotional in terms of feelings of deep satisfaction and sense of volunteerism which is being carried out in their respective workspaces. They also expressed positive feelings of inspiration, gratefulness and happiness. A wider perspective in life, being confident, creative and resourceful was also articulated as concrete impacts. It is concluded that the program had an impact on helping the helper and is a concrete manifestation of the academe being successful in its commitment of forming individuals into becoming integrated and compassionate in the service of the Church and Society. It implies that more opportunities of helping others be provided to students since, in the final analysis, is actually an opportunity of helping the helper be of better service to others.Keywords: applied psychology, life skill, qualitative research, quality education
Procedia PDF Downloads 1881211 Financial Investment of a Wine Cavein Greece
Authors: Stamataki Erofili Nellie, Benardos Andreas
Abstract:
Winemaking and aging in Greece has been performed so far in special facilities, designed either as above ground or shallow underground buildings. The latter are well-known in Santorini as “canaves,” dating back to the 1700s. Canaves were mainly used for wine storage and aging, although occasionally, they included a winepress to complete there the whole wine production. On the other hand, wine caves are subterranean caves of the same use as canaves in the wine manufacturing industry, but they are excavated at a much greater depth of more than 53 meters or 175 feet. Whereas canaves or a typical wine cellar is around 10 feet deep, with is equivalent to almost 3 meters. This paper discusses the advantages and the disadvantages of creating a wine cave for the vinification of a winery in Greece and the financial investment or risk that has to be taken. The data presented and analysed are given from wineries in Greece and especially from those located in Santorini island. The estimation of the cost for the excavation of the model selected as a wine cave will be compared with the financial budget of the existing premises and facilities above ground in Greek wineries. In order to show whether it is viable for a greek winery to invest in a wine cave.Keywords: underground space use, subterranean winery, wine cave, underground winery, greece
Procedia PDF Downloads 1821210 ROOP: Translating Sequential Code Fragments to Distributed Code Fragments Using Deep Reinforcement Learning
Authors: Arun Sanjel, Greg Speegle
Abstract:
Every second, massive amounts of data are generated, and Data Intensive Scalable Computing (DISC) frameworks have evolved into effective tools for analyzing such massive amounts of data. Since the underlying architecture of these distributed computing platforms is often new to users, building a DISC application can often be time-consuming and prone to errors. The automated conversion of a sequential program to a DISC program will consequently significantly improve productivity. However, synthesizing a user’s intended program from an input specification is complex, with several important applications, such as distributed program synthesizing and code refactoring. Existing works such as Tyro and Casper rely entirely on deductive synthesis techniques or similar program synthesis approaches. Our approach is to develop a data-driven synthesis technique to identify sequential components and translate them to equivalent distributed operations. We emphasize using reinforcement learning and unit testing as feedback mechanisms to achieve our objectives.Keywords: program synthesis, distributed computing, reinforcement learning, unit testing, DISC
Procedia PDF Downloads 1141209 Time and Cost Efficiency Analysis of Quick Die Change System on Metal Stamping Industry
Authors: Rudi Kurniawan Arief
Abstract:
Manufacturing cost and setup time are the hot topics to improve in Metal Stamping industry because material and components price are always rising up while costumer requires to cut down the component price year by year. The Single Minute Exchange of Die (SMED) is one of many methods to reduce waste in stamping industry. The Japanese Quick Die Change (QDC) dies system is one of SMED systems that could reduce both of setup time and manufacturing cost. However, this system is rarely used in stamping industries. This paper will analyze how deep the QDC dies system could reduce setup time and the manufacturing cost. The research is conducted by direct observation, simulating and comparing of QDC dies system with conventional dies system. In this research, we found that the QDC dies system could save up to 35% of manufacturing cost and reduce 70% of setup times. This simulation proved that the QDC die system is effective for cost reduction but must be applied in several parallel production processes.Keywords: press die, metal stamping, QDC system, single minute exchange die, manufacturing cost saving, SMED
Procedia PDF Downloads 1731208 Aerodynamic Design Optimization Technique for a Tube Capsule That Uses an Axial Flow Air Compressor and an Aerostatic Bearing
Authors: Ahmed E. Hodaib, Muhammed A. Hashem
Abstract:
High-speed transportation has become a growing concern. To increase high-speed efficiencies and minimize power consumption of a vehicle, we need to eliminate the friction with the ground and minimize the aerodynamic drag acting on the vehicle. Due to the complexity and high power requirements of electromagnetic levitation, we make use of the air in front of the capsule, that produces the majority of the drag, to compress it in two phases and inject a proportion of it through small nozzles to make a high-pressure air cushion to levitate the capsule. The tube is partially-evacuated so that the air pressure is optimized for maximum compressor effectiveness, optimum tube size, and minimum vacuum pump power consumption. The total relative mass flow rate of the tube air is divided into two fractions. One is by-passed to flow over the capsule body, ensuring that no chocked flow takes place. The other fraction is sucked by the compressor where it is diffused to decrease the Mach number (around 0.8) to be suitable for the compressor inlet. The air is then compressed and intercooled, then split. One fraction is expanded through a tail nozzle to contribute to generating thrust. The other is compressed again. Bleed from the two compressors is used to maintain a constant air pressure in an air tank. The air tank is used to supply air for levitation. Dividing the total mass flow rate increases the achievable speed (Kantrowitz limit), and compressing it decreases the blockage of the capsule. As a result, the aerodynamic drag on the capsule decreases. As the tube pressure decreases, the drag decreases and the capsule power requirements decrease, however, the vacuum pump consumes more power. That’s why Design optimization techniques are to be used to get the optimum values for all the design variables given specific design inputs. Aerodynamic shape optimization, Capsule and tube sizing, compressor design, diffuser and nozzle expander design and the effect of the air bearing on the aerodynamics of the capsule are to be considered. The variations of the variables are to be studied for the change of the capsule velocity and air pressure.Keywords: tube-capsule, hyperloop, aerodynamic design optimization, air compressor, air bearing
Procedia PDF Downloads 3301207 Local Boundary Analysis for Generative Theory of Tonal Music: From the Aspect of Classic Music Melody Analysis
Authors: Po-Chun Wang, Yan-Ru Lai, Sophia I. C. Lin, Alvin W. Y. Su
Abstract:
The Generative Theory of Tonal Music (GTTM) provides systematic approaches to recognizing local boundaries of music. The rules have been implemented in some automated melody segmentation algorithms. Besides, there are also deep learning methods with GTTM features applied to boundary detection tasks. However, these studies might face constraints such as a lack of or inconsistent label data. The GTTM database is currently the most widely used GTTM database, which includes manually labeled GTTM rules and local boundaries. Even so, we found some problems with these labels. They are sometimes discrepancies with GTTM rules. In addition, since it is labeled at different times by multiple musicians, they are not within the same scope in some cases. Therefore, in this paper, we examine this database with musicians from the aspect of classical music and relabel the scores. The relabeled database - GTTM Database v2.0 - will be released for academic research usage. Despite the experimental and statistical results showing that the relabeled database is more consistent, the improvement in boundary detection is not substantial. It seems that we need more clues than GTTM rules for boundary detection in the future.Keywords: dataset, GTTM, local boundary, neural network
Procedia PDF Downloads 1511206 A Simple Colorimetric Assay for Paraquat Detection Using Negatively Charged Silver Nanopaticles
Authors: Weena Siangphro, Orawon Chailapakul, Kriangsak Songsrirote
Abstract:
A simple, rapid, sensitive, and economical method based on colorimetry for the determination of paraquat, a widely used herbicide, was developed. Citrate-coated silver nanoparticles (AgNPs) were synthesized as colorimetric probe. The mechanism of the assay is related to aggregation of negatively charged AgNPs induced by positively-charged paraquat resulting from coulombic attraction which causes the color change from deep greenish yellow to pale yellow upon the concentrations of paraquat. Silica gel was exploited as paraquat adsorbent for purification and pre-concentration prior to the direct determination with negatively charged AgNPs without elution step required. The validity of the proposed approach was evaluated by spiking standard paraquat in water and plant samples. Recoveries of paraquat in water samples were 93.6-95.4%, while those in plant samples were 86.6-89.5% by using the optimized extraction procedure. The absorbance of AgNPs at 400 nm was linearly related to the concentration of paraquat over the range of 0.05-50 mg/L with detection limits of 0.05 ppm for water samples, and 0.10 ppm for plant samples.Keywords: colorimetric assay, paraquat, silica gel, silver nanoparticles
Procedia PDF Downloads 2401205 Breeding Biology of Priacanthus hamrur (Forsskal) off Mangalore Coast, Karnataka, India
Authors: H. N. Anjanayappa, S. Benakappa, A. T. Ramachandra Naik, P. Nayana, D. P. Rajesh
Abstract:
Fishes of the family Priacanthidae, popularly called big eye or bulls eye. Priacanthus hamrur is an important deep-water inhabitant of great commercial value. High percentage of landings of Priancanthids used as raw material for surimi, sausage and other fishery by-products. Presently, it has great demand in Singapore Thailand, Taiwan, Hong Kong and other countries. For the maturation studies, samples were collected from commercial landing centre, Mangalore. Studies on reproductive biology showed that Priacanthus hamrur spawns twice in a year, the spawning season extending from March to May and October to November. Based on the percentage occurrence of mature fishes in various size group it was inferred that male attained maturity at smaller size than female. This study will enable us to understand the spawning periodicity, cyclic morphological changes in male, female gonads and also it helps to improve stock size by enforcing fishing ban in particular season by assessing spawning periodicity.Keywords: breeding biology, Mangalore, morphological changes, Priacanthus hamrur
Procedia PDF Downloads 2981204 Deep Learning-Based Channel Estimation for Reconfigurable Intelligent Surface-Assisted Unmanned Aerial Vehicle-Enabled Wireless Communication System
Authors: Getaneh Berie Tarekegn
Abstract:
Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles
Procedia PDF Downloads 1211203 Disabled Young People’s Hopes and Dreams in a Rapidly Changing Society: Co-Production Peer Research
Authors: Tillie Curran
Abstract:
This co-production project aimed for an expansive exploration of disabled young people’s hopes and dreams in the context of unprecedented societal changes. The research questions developed with disabled young people acting as peer researchers, ask ‘what does a good life look like now, and, what are your hopes and dreams for the future?’ Disabled children’s childhood studies and an asset-based approach placed the voice of disabled young people at the centre of the research process and inviting participants to ‘think big’! Over 18 months, academics, members of a Centre for Independent Living and peer researchers, came together to facilitate knowledge cafes with fifty disabled young people aged between 14 and 25 in a college and youth club setting. Methods used included trigger questions, photos voice, video, and cartooning. The peer researchers also investigated how house robots and connected autonomous vehicles might support their future aspirations and sense of freedom in this new era with a trip to the university robotic laboratory. Key themes arising from participants’ hopes and dream were about ‘being responsible’, ‘loving’, ‘freedom and happiness’ and a ‘strong sense of self and togetherness’ and suggest alternative narratives and rich visions of the future possibilities for disabled young people. The five key messages peer researchers produced for the report emphasised freedom to define their futures, desires to make the world a better place, to belong and have the chance of their own family life. Thematic analysis, production of the report and impact activities were all co-produced and as the project progressed peer researchers increasingly demonstrated a role as ‘change makers’ and have formed a young people’s co-production group going on into the future. Discussion of the project highlights the factors that made these processes successful and the ethical dilemmas encountered in the context of normalcy. Finally, we consider the implications for all involved as we rethink ‘the future’, not in terms of normative ideals or trajectories, or seeing service ‘transition’ as an end, but in terms of disabled young people’s contribution, participation, freedoms, and possibilities.Keywords: co-production, disability, robotic, youth
Procedia PDF Downloads 1351202 Improving Junior Doctor Induction Through the Use of Simple In-House Mobile Application
Authors: Dmitriy Chernov, Maria Karavassilis, Suhyoun Youn, Amna Izhar, Devasenan Devendra
Abstract:
Introduction and Background: A well-structured and comprehensive departmental induction improves patient safety and job satisfaction amongst doctors. The aims of our Project were as follows: 1. Assess the perceived preparedness of junior doctors starting their rotation in Acute Medicine at Watford General Hospital. 2. Develop a supplemental Induction Guide and Pocket reference in the form of an iOS mobile application. 3. To collect feedback after implementing the mobile application following a trial period of 8 weeks with a small cohort of junior doctors. Materials and Methods: A questionnaire was distributed to all new junior trainees starting in the department of Acute Medicine to assess their experience of current induction. A mobile Induction application was developed and trialled over a period of 8 weeks, distributed in addition to the existing didactic induction session. After the trial period, the same questionnaire was distributed to assess improvement in induction experience. Analytics data were collected with users’ consent to gauge user engagement and identify areas of improvement of the application. A feedback survey about the app was also distributed. Results: A total of 32 doctors used the application during the 8-week trial period. The application was accessed 7259 times in total, with the average user spending a cumulative of 37 minutes 22 seconds on the app. The most used section was Clinical Guidelines, accessed 1490 times. The App Feedback survey revealed positive reviews: 100% of participants (n=15/15) responded that the app improved their overall induction experience compared to other placements; 93% (n=14/15) responded that the app improved overall efficiency in completing daily ward jobs compared to previous rotations; and 93% (n=14/15) responded that the app improved patient safety overall. In the Pre-App and Post-App Induction Surveys, participants reported: a 48% improvement in awareness of practical aspects of the job; a 26% improvement of awareness on locating pathways and clinical guidelines; a 40% reduction of feelings of overwhelmingness. Conclusions and recommendations: This study demonstrates the importance of technology in Medical Education and Clinical Induction. The mobile application average engagement time equates to over 20 cumulative hours of on-the-job training delivered to each user, within an 8-week period. The most used and referred to section was clinical guidelines. This shows that there is high demand for an accessible pocket guide for this type of material. This simple mobile application resulted in a significant improvement in feedback about induction in our Department of Acute Medicine, and will likely impact workplace satisfaction. Limitations of the application include: post-app surveys had a small number of participants; the app is currently only available for iPhone users; some useful sections are nested deep within the app, lacks deep search functionality across all sections; lacks real time user feedback; and requires regular review and updates. Future steps for the app include: developing a web app, with an admin dashboard to simplify uploading and editing content; a comprehensive search functionality; and a user feedback and peer ratings system.Keywords: mobile app, doctor induction, medical education, acute medicine
Procedia PDF Downloads 901201 Links between Moral Distress of Registered Nurses and Factors Related to Patient Care at the End of Their Life: A Cross Sectional Survey
Authors: L. Laurs, A. Blazeviciene, D. Milonas
Abstract:
Introduction: Nursing as a profession is grounded in moral obligation. Nursing practice is grounded in ethical standards: to not harm, to promote justice, to be accountable, and to provide safe and competent care. The nature of the nurse-patient therapeutic relationship requires acting on the patient's behalf. Moral distress consists of negative stress symptoms that occur in situations that involve ethical situations that the nurse perceives as discordant with their professional values. Aim of the Study: The purpose of this study was to assess links between moral distress of registered nurses and factors related to patient care at the end of their life. Methods and Sample: A descriptive, cross-sectional, correlational design was applied in this study. Registered nurses were recruited from seven municipal multi-profile hospitals providing both general and specialized healthcare services in Lithuania (N=1055). Research instruments included two questionnaires: Obstacles and Facilitating at the End of Life Care and Moral Distress Scale (revised). Results: Spearman’s correlation analysis was performed to assess the relationship between nurses' attitudes towards patient care at the end of life and the experienced moral distress. A statistically significant correlation between moral distress and the following factors related to patient end-of-life care has been identified: conversations with physicians on patient end-of-life problems have a positive impact on job satisfaction; some patients may be excluded from decisions about their treatment and nursing because they are questioned about their ability to assess the situation. These situations increased moral distress. Patient consciousness should not be permanently suppressed by calming medications, and the patient should be provided with all nursing care services and moral distress. Conclusions: The moral distress of nurses is significantly related to the end-of-life care of patients and their determinants: moral distress increased due to lack of discussion with doctors about problem-solving and exclusion of patients from decision-making. And it diminished by refusing calming medications to permanently suppress a patient's consciousness and providing good care for patients.Keywords: moral distress, registered nurses, end of life, care
Procedia PDF Downloads 1141200 Machine Learning Based Gender Identification of Authors of Entry Programs
Authors: Go Woon Kwak, Siyoung Jun, Soyun Maeng, Haeyoung Lee
Abstract:
Entry is an education platform used in South Korea, created to help students learn to program, in which they can learn to code while playing. Using the online version of the entry, teachers can easily assign programming homework to the student and the students can make programs simply by linking programming blocks. However, the programs may be made by others, so that the authors of the programs should be identified. In this paper, as the first step toward author identification of entry programs, we present an artificial neural network based classification approach to identify genders of authors of a program written in an entry. A neural network has been trained from labeled training data that we have collected. Our result in progress, although preliminary, shows that the proposed approach could be feasible to be applied to the online version of entry for gender identification of authors. As future work, we will first use a machine learning technique for age identification of entry programs, which would be the second step toward the author identification.Keywords: artificial intelligence, author identification, deep neural network, gender identification, machine learning
Procedia PDF Downloads 3251199 Biodiversity of Pathogenic and Toxigenic Fungi Associated with Maize Grains Sampled across Egypt
Authors: Yasser Shabana, Khaled Ghoneem, Nehal Arafat, Younes Rashad, Dalia Aseel, Bruce Fitt, Aiming Qi, Benjamine Richard
Abstract:
Providing food for more than 100 million people is one of Egypt's main challenges facing development. The overall goal is to formulate strategies to enhance food security in light of population growth. Two hundred samples of maize grains from 25 governates were collected. For the detection of seed-borne fungi, the deep-freezing blotter method (DFB) and washing method (ISTA 1999) were used. A total of 41 fungal species was recovered from maize seed samples. Weather data from 30 stations scattered all over Egypt and covering the major maize growing areas were obtained. Canonical correspondence analysis of data for the obtained fungal genera with temperature, relative humidity, precipitation, wind speed, or solar radiation revealed that relative humidity, temperature and wind speed were the most influential weather variables.Keywords: biodiversity, climate change, maize, seed-borne fungi
Procedia PDF Downloads 1661198 In-Situ Defect Detection of Additive Manufactured Parts
Authors: Aswin T. M., Dhinnesh S., Guru Prasath K. S., Hasina M., Rajamani R.
Abstract:
Fused Deposition Modelling (FDM), a widely used Additive Manufacturing (AM) process, often faces challenges in the quality of the part, such as the formation of defects. The most common defects in FDM are stringing, dimensional inaccuracy, layer shifting, warping, and poor bridging. This work presents the summary of research work carried out in the field of AM, optimization of 3D printing process parameters, and techniques used for identifying defects. Also, an attempt is made to integrate machine vision with a deep learning model to continuously monitor the printing process. The system captures and analyzes layer-by-layer data of the printed part, detecting defects such as stringing, warping, and dimensional inaccuracy. FDM is extensively utilized across various sectors, including aerospace, automotive, healthcare, and consumer goods. In industries such as aerospace, where high precision and reliability are paramount, even minor defects can lead to component failures that compromise safety and performance. This highlights the critical need for real-time identification of defects produced during the printing process.Keywords: FDM, defect detection, machine vision, CNN
Procedia PDF Downloads 121197 Optimization of Tundish Geometry for Minimizing Dead Volume Using OpenFOAM
Authors: Prateek Singh, Dilshad Ahmad
Abstract:
Growing demand for high-quality steel products has inspired researchers to investigate the unit operations involved in the manufacturing of these products (slabs, rods, sheets, etc.). One such operation is tundish operation, in which a vessel (tundish) acts as a buffer of molten steel for the solidification operation in mold. It is observed that tundish also plays a crucial role in the quality and cleanliness of the steel produced, besides merely acting as a reservoir for the mold. It facilitates removal of dissolved oxygen (inclusions) from the molten steel thus improving its cleanliness. Inclusion removal can be enhanced by increasing the residence time of molten steel in the tundish by incorporation of flow modifiers like dams, weirs, turbo-pad, etc. These flow modifiers also help in reducing the dead or short circuit zones within the tundish which is significant for maintaining thermal and chemical homogeneity of molten steel. Thus, it becomes important to analyze the flow of molten steel in the tundish for different configuration of flow modifiers. In the present work, effect of varying positions and heights/depths of dam and weir on the dead volume in tundish is studied. Steady state thermal and flow profiles of molten steel within the tundish are obtained using OpenFOAM. Subsequently, Residence Time Distribution analysis is performed to obtain the percentage of dead volume in the tundish. Design of Experiment method is then used to configure different tundish geometries for varying positions and heights/depths of dam and weir, and dead volume for each tundish design is obtained. A second-degree polynomial with two-term interactions of independent variables to predict the dead volume in the tundish with positions and heights/depths of dam and weir as variables are computed using Multiple Linear Regression model. This polynomial is then used in an optimization framework to obtain the optimal tundish geometry for minimizing dead volume using Sequential Quadratic Programming optimization.Keywords: design of experiments, multiple linear regression, OpenFOAM, residence time distribution, sequential quadratic programming optimization, steel, tundish
Procedia PDF Downloads 2091196 Impacts of Tillage on Biodiversity of Microarthropod Communities in Two Different Crop Systems
Authors: Leila Ramezani, Mohammad Saeid Mossadegh
Abstract:
Different uses of land by humans alter the physico chemical characteristics of the soil and affect the soil microhabitat. The objective of this study was to evaluate the influence of tillage in three different human land uses on microarthropods biodiversity in Khuzestan province, southwest of Iran. Three microhabitats including a permanent grassland with old Date-Palms around and no till system, and two wheat fields, one with conservative agricultural practices and low till system and the other with conventional agricultural practices (deep tillage), were compared for the biodiversity of the two main groups of soil microarthropods (Oribatida and Collembola). Soil samples were collected from the top to a depth of 15 cm bimonthly during a period of two years. Significant differences in the biodiversity index of microarthropods were observed between the different tillage systems (F = 36.748, P =0.000). Indeed, analysis of species diversity showed that the diversity index at the conservative field with low till (2.58 ± 0.01) was higher (p < 0.05) than the conventional tilled field (2.45 ± 0.08) and the diversity of natural grassland was the highest (2.79 ± 0.19, p < 0.05). Indeed, the index of biodiversity and population abundance differed significantly in different seasons (p < 0.00).Keywords: biodiversity, Collembola, microarthropods, Oribatida
Procedia PDF Downloads 1811195 A 'German Europe' Emerged from the Euro Crisis: A Study through the Portuguese Quality Press
Authors: Ana Luísa Mouro
Abstract:
When the financial crisis exploded in 2008 in the United States, unleashed by the collapse of Lehman Brothers, and contaminated the economies of the European periphery, Germany appeared as the anchor of the stability of all European institutions and countries in difficulty. The solutions provided by the German government have triggered a deep political debate about the key position Germany has conquered at the heart of Europe - a new “German question” has been created. Some say Germany has achieved by peaceful means what was not able to get through military conquest - the domination of Europe – and many fear Germany’s economic power. This debate about the new role of Germany in Europe has received special attention in the European media and Portugal has not been the exception. The present study has been based on the survey, selection and critical analysis of news reporting, opinion articles, interviews and editorials, published in the weekly Expresso and in the daily Público, between 2008 and 2015 (year of the 25th anniversary of Germany’s unification). The findings of this study will show the paradox of German power and its relevance for Europe’s future.Keywords: Euro crises, German Europe, intercultural hermeneutics, Portuguese quality press
Procedia PDF Downloads 2461194 Improved Feature Extraction Technique for Handling Occlusion in Automatic Facial Expression Recognition
Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade
Abstract:
The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.Keywords: automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection
Procedia PDF Downloads 1741193 Artificial Intelligence for Cloud Computing
Authors: Sandesh Achar
Abstract:
Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things
Procedia PDF Downloads 1121192 Blended Learning Instructional Approach to Teach Pharmaceutical Calculations
Authors: Sini George
Abstract:
Active learning pedagogies are valued for their success in increasing 21st-century learners’ engagement, developing transferable skills like critical thinking or quantitative reasoning, and creating deeper and more lasting educational gains. 'Blended learning' is an active learning pedagogical approach in which direct instruction moves from the group learning space to the individual learning space, and the resulting group space is transformed into a dynamic, interactive learning environment where the educator guides students as they apply concepts and engage creatively in the subject matter. This project aimed to develop a blended learning instructional approach to teaching concepts around pharmaceutical calculations to year 1 pharmacy students. The wrong dose, strength or frequency of a medication accounts for almost a third of medication errors in the NHS therefore, progression to year 2 requires a 70% pass in this calculation test, in addition to the standard progression requirements. Many students were struggling to achieve this requirement in the past. It was also challenging to teach these concepts to students of a large class (> 130) with mixed mathematical abilities, especially within a traditional didactic lecture format. Therefore, short screencasts with voice-over of the lecturer were provided in advance of a total of four teaching sessions (two hours/session), incorporating core content of each session and talking through how they approached the calculations to model metacognition. Links to the screencasts were posted on the learning management. Viewership counts were used to determine that the students were indeed accessing and watching the screencasts on schedule. In the classroom, students had to apply the knowledge learned beforehand to a series of increasingly difficult set of questions. Students were then asked to create a question in group settings (two students/group) and to discuss the questions created by their peers in their groups to promote deep conceptual learning. Students were also given time for question-and-answer period to seek clarifications on the concepts covered. Student response to this instructional approach and their test grades were collected. After collecting and organizing the data, statistical analysis was carried out to calculate binomial statistics for the two data sets: the test grade for students who received blended learning instruction and the test grades for students who received instruction in a standard lecture format in class, to compare the effectiveness of each type of instruction. Student response and their performance data on the assessment indicate that the learning of content in the blended learning instructional approach led to higher levels of student engagement, satisfaction, and more substantial learning gains. The blended learning approach enabled each student to learn how to do calculations at their own pace freeing class time for interactive application of this knowledge. Although time-consuming for an instructor to implement, the findings of this research demonstrate that the blended learning instructional approach improves student academic outcomes and represents a valuable method to incorporate active learning methodologies while still maintaining broad content coverage. Satisfaction with this approach was high, and we are currently developing more pharmacy content for delivery in this format.Keywords: active learning, blended learning, deep conceptual learning, instructional approach, metacognition, pharmaceutical calculations
Procedia PDF Downloads 1761191 Family and Community Care for the Elderly: An Implementation Research in Local Community, Thailand
Authors: Sumattana Glangkarn, Vorapoj Promasatayaprot
Abstract:
Background: Proportion of population ageing in Thailand has been increased rapidly in the past decades according to living longer and the fertility rates have decreased. The most important challenge related to this situation is to consider how to improve quality and years of healthy of life. This study aimed to implement the older persons’ long term care (LTC) system for elderly care by family and community. Method: The Consolidated Framework for Implementation Research (CFIR) was employed for guiding and evaluating an implementation process in ageing care. The CFIR composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Results: most elderly participants were couples, educating primary school and living with children and grandchildren. More than half of them had chronic diseases such as diabetes mellitus and hypertension. Factor analysis revealed factors related to health care of older participants which consisted of exercise, diet, accidental prevention, relaxation, self-care capacity, joyfulness, family relationship, and personal hygiene. A pre-implementation phase showed intervention characteristics included facilities and services of the LTC policy from the Ministry of Public Health. The complexities of the LTC and relative advantages were explained. Community leaders, public health volunteers, care givers and health professionals had participated in the LTC activities. Outer and inner settings consisted of context of community, culture, and readiness. Characteristics of the individuals related to knowledge, self-efficacy, perceptions, and believes. The process consisted of planning, acting, observing, and reflecting. The implementation outcomes and service outcomes had been evaluated during-implementation phase. Conclusion: the participation of caregivers, community leaders, public health volunteers, and health professionals had supported the LTC services. Thus, family and community care could improve quality of life of the ageing.Keywords: ageing, CFIR, long term care, implementation
Procedia PDF Downloads 1791190 Motivating EFL Students to Speak English through Flipped Classroom Implantation
Authors: Mohamad Abdullah
Abstract:
Recent Advancements in technology have stimulated deep change in the language learning classroom. Flipped classroom as a new pedagogical method is at the center of this change. It turns the classroom into a student-centered environment and promotes interactive and autonomous learning. The present study is an attempt to examine the effectiveness of the Flipped Classroom Model (FCM) on students’ motivation level in English speaking performance. This study was carried out with 27 undergraduate female English majors who enrolled in the course of Advanced Communication Skills (ENGL 154) at Buraimi University College (BUC). Data was collected through Motivation in English Speaking Performance Questionnaire (MESPQ) which has been distributed among the participants of this study pre and post the implementation of FCM. SPSS was used for analyzing data. The Paired T-Test which was carried out on the pre-post of (MESPQ) showed a significant difference between them (p < .009) that revealed participants’ tendency to increase their motivation level in English speaking performance after the application of FCM. In addition, respondents of the current study reported positive views about the implementation of FCM.Keywords: english speaking performance, motivation, flipped classroom model, learner-contentedness
Procedia PDF Downloads 1361189 Femoropatellar Groove: An Anatomical Study
Authors: Mamatha Hosapatna, Anne D. Souza, Vrinda Hari Ankolekar, Antony Sylvan D. Souza
Abstract:
Introduction: The lower extremity of the femur is characterized by an anterior groove in which patella is held during motion. This groove separates the two lips of the trochlea (medial and lateral), prolongation of the two condyles. In humans, the lateral trochlear lip is more developed than the medial one, creating an asymmetric groove that is also specific to the human body. Because of femoral obliquity, contraction of quadriceps leads to a lateral dislocation stress on the patella, and the more elevated lateral side of the patellar groove helps the patella stays in its correct place, acting as a wall against lateral dislocation. This specific shape fits an oblique femur. It is known that femoral obliquity is not genetically determined but comes with orthostatism and biped walking. Material and Methodology: To measure the various dimensions of the Femoropatellar groove (FPG) and femoral condyle using digital image analyser. 37 dried adult femora (22 right,15 left) were used for the study. End on images of the lower end of the femur was taken. Various dimensions of the Femoropatellar groove and FP angle were measured using image J software. Results were analyzed statistically. Results: Maximum of the altitude of medial condyle of the right femur is 4.98± 0.35 cm and of the left femur is 5.20±.16 cm. Maximum altitude of lateral condyle is 5.44±0.4 and 5.50±0.14 on the right and left side respectively. Medial length of the groove is 1.30±0.38 cm on the right side and on the left side is 1.88±0.16 cm. The lateral length of the groove on the right side is 1.900±.16 cm and left side is 1.88±0.16 cm. Femoropatellar angle is 136.38◦±2.59 on the right side and on the left side it is 142.38◦±7.0 Angle and dimensions of the femoropatellar groove on the medial and lateral sides were measured. Asymmetry in the patellar groove was observed. The lateral lip was found to be wider and bigger which correlated with the previous studies. An asymmetrical patellar groove with a protruding lateral side associated with an oblique femur is a specific mark of bipedal locomotion. Conclusion: Dimensions of FPG are important in maintaining the stability of patella and also in knee replacement surgeries. The implants used in to replace the patellofemoral compartment consist of a metal groove to fit on the femoral end and a plastic disc that attaches to the undersurface of the patella. The location and configuration of the patellofemoral groove of the distal femur are clinically significant in the mechanics and pathomechanics of the patellofemoral articulation.Keywords: femoral patellar groove, femoro patellar angle, lateral condyle, medial condyle
Procedia PDF Downloads 407