Search results for: hand movement recognition
6556 Fetal Movement Study Using Biomimics of the Maternal March
Authors: V. Diaz, B. Pardo , D. Villegas
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In premature births most babies have complications at birth, these complications can be reduced, if an atmosphere of relaxation is provided and is also similar to intrauterine life, for this, there are programs where their mothers lull and sway them; however, the conditions in which they do so and the way in they do it may not be the indicated. Here we describe an investigation based on the biomimics of the kinematics of human fetal movement, which consists of determining the movements that the fetus experiences and the deformations of the components that surround the fetus during a gentle walk at week 32 of the gestation stage. This research is based on a 3D model that has the anatomical structure of the pelvis, fetus, muscles, uterus and its most important supporting elements (ligaments). Normal load conditions are applied to this model according to the stage of gestation and the kinematics of a gentle walk of a pregnant mother, which focuses on the pelvic bone, this allows to receive a response from the other elements of the model. To accomplish this modeling and subsequent simulation Solidworks software was used. From this analysis, the curves that describe the movement of the fetus at three different points were obtained. Additionally, we could found the deformation of the uterus and the ligaments that support it, showing the characteristics that these tissues can have in the face of the support of the fetus. These data can be used for the construction of artifacts that help the normal development of premature infants.Keywords: simulation, biomimic, uterine model, fetal movement study
Procedia PDF Downloads 1656555 On the Network Packet Loss Tolerance of SVM Based Activity Recognition
Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir
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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss
Procedia PDF Downloads 4776554 The Social Justice of Movement: Undocumented Immigrant Coalitions in the United States
Authors: Libia Jiménez Chávez
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This is a study of freedom riders and their courageous journey for civil rights, but the year was not 1961. It was 2003. This paper chronicles the emergence of a new civil rights movement for immigrant rights through an oral history of the 2003 U.S. Immigrant Workers Freedom Ride (IWFR). During the height of the post-9/11 immigrant repression, a bloc of organizations inspired by the Civil Rights Movement of the 1960s mobilized 900 multinational immigrants and their allies in the fight for legal status, labor protections, family reunification, and civil rights. The activists visited over 100 U.S. cities, met with Congressional leaders in the nation’s capital, and led a rally of over 50,000 people in New York City. This unified effort set the groundwork for the national May Day immigration protests of 2006. Movements can be characterized in two distinct ways: physical movement and social movements. In the past, historians have considered immigrants both as people and as participants in social movements. In contrast, studies of recent migrants tend to say little about their involvement in immigrant political mobilizations. The dominant literature on immigration portrays immigrants as objects of exclusion, border enforcement, detention, and deportation instead of strategic political actors. This paper aims to change this perception. It considers the Freedom Riders both as immigrants who were literally on the move and as participants in a social movement. Through interviews with participants and archival video footage housed at the University of California Los Angeles, it is possible to study this mobile protest as a movement. This contemporary immigrant struggle is an opportunity to explore the makeup and development of a heterogenous immigrant coalition and consider the relationship between population movements and social justice. In addition to oral histories and archival research, the study will utilize social movement literature, U.S. immigration and labor history, and Undocumented Critical Theory to expand the historiography of immigrant social movements in America.Keywords: civil rights, immigrant social movements, undocumented communities, undocumented critical theory
Procedia PDF Downloads 1746553 Application of Lean Manufacturing in Brake Shoe Manufacturing Plant: A Case Study
Authors: Anees K. Ahamed, Aakash Kumar R. G., Raj M. Mohan
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The main objective is to apply lean tools to identify and eliminate waste in and among the work stations so as to improve the process speed and quality. From the top seven wastes in the lean concept, we consider the movement of materials, defects, and inventory for the improvement since these cause the major impact on the performance measures. The layout was improved to reduce the movement of materials. It also quantifies the reduction in movement among the work stations. Value stream mapping has been used for identification of waste. Cause and effect diagram and 5W analysis are used to identify the reasons for defects and to provide the counter measures. Some cycle time reduction techniques also proposed to improve the productivity. Lean Audit check sheet was also used to identify the current position of the industry and to identify the gap to make the industry Lean.Keywords: cause and effect diagram, cycle time reduction, defects, lean, waste reduction
Procedia PDF Downloads 3866552 Keyframe Extraction Using Face Quality Assessment and Convolution Neural Network
Authors: Rahma Abed, Sahbi Bahroun, Ezzeddine Zagrouba
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Due to the huge amount of data in videos, extracting the relevant frames became a necessity and an essential step prior to performing face recognition. In this context, we propose a method for extracting keyframes from videos based on face quality and deep learning for a face recognition task. This method has two steps. We start by generating face quality scores for each face image based on the use of three face feature extractors, including Gabor, LBP, and HOG. The second step consists in training a Deep Convolutional Neural Network in a supervised manner in order to select the frames that have the best face quality. The obtained results show the effectiveness of the proposed method compared to the methods of the state of the art.Keywords: keyframe extraction, face quality assessment, face in video recognition, convolution neural network
Procedia PDF Downloads 2346551 The Creation of Micromedia on Social Networking Sites as a Social Movement Strategy: The Case of Migration Aid, a Hungarian Refugee Relief Group
Authors: Zsofia Nagy, Tibor Dessewffy
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The relationship between social movements and the media that represents them comprises both of the media representation of movements on the one hand, and the media strategies employed by movements on the other. A third possible approach is to connect the two and look at the interactions connecting the two sides. This relationship has been affected by the emergence of social networking sites (SNS) that have a transformative effect on both actors. However, the extent and direction of these changes needs to be investigated. Empirical case studies that focus on newly enabled forms of social movements can contribute to these debates in an analytically fruitful way. Therefore in our study, we use the case of Migration Aid, a Hungarian Facebook-based grassroots relief organization that gained prominence during the refugee crisis that unfolded in Hungary in 2015. Migration Aid formed without the use of traditional mobilizational agents, and that took over roles traditionally occupied by formal NGOs or the state. Analyzing different movement strategies towards the media - we find evidence that while effectively combining these strategies, SNSs also create affordances for movements to shift their strategy towards creating alternatives, their own micromedia. Beyond the practical significance of this – the ability to disseminate alternative information independently from traditional media – it also allowed the group to frame the issue in their own terms and to replace vertical modes of communication with horizontal ones. The creation of micromedia also shifts the relationship between social movements and the media away from an asymmetrical and towards a more symbiotic co-existence. We provide four central factors – project identity, the mobilization potential of SNSs, the disruptiveness of the event and selectivity in the construction of social knowledge – that explain this shift. Finally, we look at the specific processes that contribute to the creation of the movement’s own micromedia. We posit that these processes were made possible by the rhizomatic structure of the group and a function of SNSs we coin the Social Information Thermostat function. We conclude our study by positioning our findings in relation with the broader context.Keywords: social networking sites, social movements, micromedia, media strategies
Procedia PDF Downloads 2646550 Toward a Radical/Populist Democracy from the Dialectical Tensions between Transgender Movement and Gay Movement in Taiwan: A Rhetorical Analysis
Authors: Hsiao-Yung Wang
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This paper aims to elaborate the rhetorical strategies and its inherent dialectical tensions between transgender movement and gay movement in Taiwan; thereby, a radical/populist democratic model will be reproblematized for theorizing the internal dialogicity of the 'umbrella metaphor' of the so-called 'LGBT' label. Firstly, it examined how the representative gay community in Taiwan defined the category of 'LGBT' by its visual rhetoric of pride parade during the last two decades, and how the imaginary of 'transgender' was systematically precluded or even silenced by 'cisgender privilege' or 'cisnormativity' of the gay community in general. Secondly, it employed Laclau & Mouffe’s (1985) perspective of 'empty signifier' which derives from their radical democratic theorization and populist reason, to explore the rhetorical strategies and language tactics on which transgender activists relied for arguing or mapping both the cooperative and competitive relationship with cisgender allies intentionally. Based on research findings, this paper argued that a relationship between rather than an amalgamation of sexual orientation and gender identity should be recognized. Moreover, that resisting defining transgender as other and everyone else as normal could be the critical issue of LGBT community as a whole, especially while it proceeds toward to a radical/populist democracy.Keywords: empty signifier, LGBT, populist reason, radical democracy, rhetoric, transgender
Procedia PDF Downloads 1716549 Automatic Number Plate Recognition System Based on Deep Learning
Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi
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In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.Keywords: ANPR, CS, CNN, deep learning, NPL
Procedia PDF Downloads 3076548 New Formula for Revenue Recognition Likely to Change the Prescription for Pharma Industry
Authors: Shruti Hajirnis
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In May 2014, FASB issued Accounting Standards Update (ASU) 2014-09, Revenue from Contracts with Customers (Topic 606), and the International Accounting Standards Board (IASB) issued International Financial Reporting Standards (IFRS) 15, Revenue from Contracts with Customers that will supersede virtually all revenue recognition requirements in IFRS and US GAAP. FASB and the IASB have basically achieved convergence with these standards, with only some minor differences such as collectability threshold, interim disclosure requirements, early application and effective date, impairment loss reversal and nonpublic entity requirements. This paper discusses the impact of five-step model prescribed in new revenue standard on the entities operating in Pharma industry. It also outlines the considerations for these entities while implementing the new standard.Keywords: revenue recognition, pharma industry, standard, requirements
Procedia PDF Downloads 4456547 Effects of Whole Body Vibration on Movement Variability Performing a Resistance Exercise with Different Ballasts and Rhythms
Authors: Sílvia tuyà Viñas, Bruno Fernández-Valdés, Carla Pérez-Chirinos, Monica Morral-Yepes, Lucas del Campo Montoliu, Gerard Moras Feliu
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Some researchers stated that whole body vibration (WBV) generates postural destabilization, although there is no extensive research. Therefore, the aim of this study was to analyze movement variability when performing a half-squat with a different type of ballasts and rhythms with (V) and without (NV) WBV in male athletes using entropy. Twelve experienced in strength training males (age: 21.24 2.35 years, height: 176.83 5.80 cm, body mass: 70.63 8.58 kg) performed a half-squat with weighted vest (WV), dumbbells (D), and a bar with the weights suspended with elastic bands (B), in V and NV at 40 bpm and 60 bpm. Subjects performed one set of twelve repetitions of each situation, composed by the combination of the three factors. The movement variability was analyzed by calculating the Sample Entropy (SampEn) of the total acceleration signal recorded at the waist. In V, significant differences were found between D and WV (p<0.001; ES: 2.87 at 40 bpm; p<0.001; ES: 3.17 at 60 bpm) and between the B and WV at both rhythms (p<0.001; ES: 3.12 at 40 bpm; p<0.001; ES: 2.93 at 60 bpm) and a higher SampEn was obtained at 40 bpm with all ballasts (p<0.001; ES of WV: 1.22; ES of D: 4.49; ES of B: 4.03). No significant differences were found in NV. WBV is a disturbing and destabilizing stimulus. Strength and conditioning coaches should choose the combination of ballast and rhythm of execution according to the level and objectives of each athlete.Keywords: accelerometry, destabilization, entropy, movement variability, resistance training
Procedia PDF Downloads 1796546 Automatic Product Identification Based on Deep-Learning Theory in an Assembly Line
Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez
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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.Keywords: deep-learning, image classification, image identification, industrial engineering.
Procedia PDF Downloads 1626545 Development and Application of the Proctoring System with Face Recognition for User Registration on the Educational Information Portal
Authors: Meruyert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova, Madina Ermaganbetova
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This research paper explores the process of creating a proctoring system by evaluating the implementation of practical face recognition algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As an outcome, a proctoring system will be created, enabling the conduction of tests and ensuring academic integrity checks within the system. Due to the correct operation of the system, test works are carried out. The result of the creation of the proctoring system will be the basis for the automation of the informational, educational portal developed by machine learning.Keywords: artificial intelligence, education portal, face recognition, machine learning, proctoring
Procedia PDF Downloads 1276544 Unsupervised Learning with Self-Organizing Maps for Named Entity Recognition in the CONLL2003 Dataset
Authors: Assel Jaxylykova, Alexnder Pak
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This study utilized a Self-Organizing Map (SOM) for unsupervised learning on the CONLL-2003 dataset for Named Entity Recognition (NER). The process involved encoding words into 300-dimensional vectors using FastText. These vectors were input into a SOM grid, where training adjusted node weights to minimize distances. The SOM provided a topological representation for identifying and clustering named entities, demonstrating its efficacy without labeled examples. Results showed an F1-measure of 0.86, highlighting SOM's viability. Although some methods achieve higher F1 measures, SOM eliminates the need for labeled data, offering a scalable and efficient alternative. The SOM's ability to uncover hidden patterns provides insights that could enhance existing supervised methods. Further investigation into potential limitations and optimization strategies is suggested to maximize benefits.Keywords: named entity recognition, natural language processing, self-organizing map, CONLL-2003, semantics
Procedia PDF Downloads 506543 2.5D Face Recognition Using Gabor Discrete Cosine Transform
Authors: Ali Cheraghian, Farshid Hajati, Soheila Gheisari, Yongsheng Gao
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In this paper, we present a novel 2.5D face recognition method based on Gabor Discrete Cosine Transform (GDCT). In the proposed method, the Gabor filter is applied to extract feature vectors from the texture and the depth information. Then, Discrete Cosine Transform (DCT) is used for dimensionality and redundancy reduction to improve computational efficiency. The system is combined texture and depth information in the decision level, which presents higher performance compared to methods, which use texture and depth information, separately. The proposed algorithm is examined on publically available Bosphorus database including models with pose variation. The experimental results show that the proposed method has a higher performance compared to the benchmark.Keywords: Gabor filter, discrete cosine transform, 2.5d face recognition, pose
Procedia PDF Downloads 3286542 Parkinson’s Disease Hand-Eye Coordination and Dexterity Evaluation System
Authors: Wann-Yun Shieh, Chin-Man Wang, Ya-Cheng Shieh
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This study aims to develop an objective scoring system to evaluate hand-eye coordination and hand dexterity for Parkinson’s disease. This system contains three boards, and each of them is implemented with the sensors to sense a user’s finger operations. The operations include the peg test, the block test, and the blind block test. A user has to use the vision, hearing, and tactile abilities to finish these operations, and the board will record the results automatically. These results can help the physicians to evaluate a user’s reaction, coordination, dexterity function. The results will be collected to a cloud database for further analysis and statistics. A researcher can use this system to obtain systematic, graphic reports for an individual or a group of users. Particularly, a deep learning model is developed to learn the features of the data from different users. This model will help the physicians to assess the Parkinson’s disease symptoms by a more intellective algorithm.Keywords: deep learning, hand-eye coordination, reaction, hand dexterity
Procedia PDF Downloads 676541 Hidden Markov Movement Modelling with Irregular Data
Authors: Victoria Goodall, Paul Fatti, Norman Owen-Smith
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Hidden Markov Models have become popular for the analysis of animal tracking data. These models are being used to model the movements of a variety of species in many areas around the world. A common assumption of the model is that the observations need to have regular time steps. In many ecological studies, this will not be the case. The objective of the research is to modify the movement model to allow for irregularly spaced locations and investigate the effect on the inferences which can be made about the latent states. A modification of the likelihood function to allow for these irregular spaced locations is investigated, without using interpolation or averaging the movement rate. The suitability of the modification is investigated using GPS tracking data for lion (Panthera leo) in South Africa, with many observations obtained during the night, and few observations during the day. Many nocturnal predator tracking studies are set up in this way, to obtain many locations at night when the animal is most active and is difficult to observe. Few observations are obtained during the day, when the animal is expected to rest and is potentially easier to observe. Modifying the likelihood function allows the popular Hidden Markov Model framework to be used to model these irregular spaced locations, making use of all the observed data.Keywords: hidden Markov Models, irregular observations, animal movement modelling, nocturnal predator
Procedia PDF Downloads 2496540 Earthquake Risk Assessment Using Out-of-Sequence Thrust Movement
Authors: Rajkumar Ghosh
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Earthquakes are natural disasters that pose a significant risk to human life and infrastructure. Effective earthquake mitigation measures require a thorough understanding of the dynamics of seismic occurrences, including thrust movement. Traditionally, estimating thrust movement has relied on typical techniques that may not capture the full complexity of these events. Therefore, investigating alternative approaches, such as incorporating out-of-sequence thrust movement data, could enhance earthquake mitigation strategies. This review aims to provide an overview of the applications of out-of-sequence thrust movement in earthquake mitigation. By examining existing research and studies, the objective is to understand how precise estimation of thrust movement can contribute to improving structural design, analyzing infrastructure risk, and developing early warning systems. The study demonstrates how to estimate out-of-sequence thrust movement using multiple data sources, including GPS measurements, satellite imagery, and seismic recordings. By analyzing and synthesizing these diverse datasets, researchers can gain a more comprehensive understanding of thrust movement dynamics during seismic occurrences. The review identifies potential advantages of incorporating out-of-sequence data in earthquake mitigation techniques. These include improving the efficiency of structural design, enhancing infrastructure risk analysis, and developing more accurate early warning systems. By considering out-of-sequence thrust movement estimates, researchers and policymakers can make informed decisions to mitigate the impact of earthquakes. This study contributes to the field of seismic monitoring and earthquake risk assessment by highlighting the benefits of incorporating out-of-sequence thrust movement data. By broadening the scope of analysis beyond traditional techniques, researchers can enhance their knowledge of earthquake dynamics and improve the effectiveness of mitigation measures. The study collects data from various sources, including GPS measurements, satellite imagery, and seismic recordings. These datasets are then analyzed using appropriate statistical and computational techniques to estimate out-of-sequence thrust movement. The review integrates findings from multiple studies to provide a comprehensive assessment of the topic. The study concludes that incorporating out-of-sequence thrust movement data can significantly enhance earthquake mitigation measures. By utilizing diverse data sources, researchers and policymakers can gain a more comprehensive understanding of seismic dynamics and make informed decisions. However, challenges exist, such as data quality difficulties, modelling uncertainties, and computational complications. To address these obstacles and improve the accuracy of estimates, further research and advancements in methodology are recommended. Overall, this review serves as a valuable resource for researchers, engineers, and policymakers involved in earthquake mitigation, as it encourages the development of innovative strategies based on a better understanding of thrust movement dynamics.Keywords: earthquake, out-of-sequence thrust, disaster, human life
Procedia PDF Downloads 786539 Hand Motion and Gesture Control of Laboratory Test Equipment Using the Leap Motion Controller
Authors: Ian A. Grout
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In this paper, the design and development of a system to provide hand motion and gesture control of laboratory test equipment is considered and discussed. The Leap Motion controller is used to provide an input to control a laboratory power supply as part of an electronic circuit experiment. By suitable hand motions and gestures, control of the power supply is provided remotely and without the need to physically touch the equipment used. As such, it provides an alternative manner in which to control electronic equipment via a PC and is considered here within the field of human computer interaction (HCI).Keywords: control, hand gesture, human computer interaction, test equipment
Procedia PDF Downloads 3166538 Evaluation of Features Extraction Algorithms for a Real-Time Isolated Word Recognition System
Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas
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This paper presents a comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in the speaker-dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signals to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients give best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose, the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfies the real-time requirements and is suitable for applications in embedded systems.Keywords: isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW
Procedia PDF Downloads 4976537 The Influence of Social Media to Trends Design at Restaurant in Urban Area of Yogyakarta Province, Indonesia
Authors: Suparwoko, M. Hardyan Prastyanto, Aisah Azhari Marwangi
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Today, we face with some paradoxical tendencies. In the field of culture, on the one hand, we are witnessing the emergence of ethnic and religious fervor that is becoming stronger, but on the other hand, we are also witnessing a new ideology that characterized the flow of transnationalism, globalism, and secularism. Through social media, the globalization movement is accommodated to spread all over the world. Globalization also requires the commercialization of many fields, including architecture. In the architecture of commercial buildings, the appeal of the building is an important aspect for the function of the building. That theory is the basis for research of this study. This study aimed to know the influence of social media on the changing trends in the design of restaurant in urban areas of Yogyakarta Province. This study is using observation (survey) method to restaurants in Yogyakarta and surrounding areas to collect data, then the assessment of data by using the theory of the social media Path and Instagram that provide trend information from interior and building facades of the restaurant. By using social media Path and Instagram based survey methods, it can be seen that the intensity of social media users who publish or promote restaurant that has been chosen. Generally, conventional character of the restaurant have changed into a material and visually conceptual restaurant.Keywords: influence, social media, changes, architecture trend
Procedia PDF Downloads 3196536 The Effect of Fetal Movement Counting on Maternal Antenatal Attachment
Authors: Esra Güney, Tuba Uçar
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Aim: This study has been conducted for the purpose of determining the effects of fetal movement counting on antenatal maternal attachment. Material and Method: This research was conducted on the basis of the real test model with the pre-test /post-test control groups. The study population consists of pregnant women registered in the six different Family Health Centers located in the central Malatya districts of Yeşilyurt and Battalgazi. When power analysis is done, the sample size was calculated for each group of at least 55 pregnant women (55 tests, 55 controls). The data were collected by using Personal Information Form and MAAS (Maternal Antenatal Attachment Scale) between July 2015-June 2016. Fetal movement counting training was given to pregnant women by researchers in the experimental group after the pre-test data collection. No intervention was applied to the control group. Post-test data for both groups were collected after four weeks. Data were evaluated with percentage, chi-square arithmetic average, chi-square test and as for the dependent and independent group’s t test. Result: In the MAAS, the pre-test average of total scores in the experimental group is 70.78±6.78, control group is also 71.58±7.54 and so there was no significant difference in mean scores between the two groups (p>0.05). MAAS post-test average of total scores in the experimental group is 78.41±6.65, control group is also is 72.25±7.16 and so the mean scores between groups were found to have statistically significant difference (p<0.05). Conclusion: It was determined that fetal movement counting increases the maternal antenatal attachments.Keywords: antenatal maternal attachment, fetal movement counting, pregnancy, midwifery
Procedia PDF Downloads 2736535 Gaussian Mixture Model Based Identification of Arterial Wall Movement for Computation of Distension Waveform
Authors: Ravindra B. Patil, P. Krishnamoorthy, Shriram Sethuraman
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This work proposes a novel Gaussian Mixture Model (GMM) based approach for accurate tracking of the arterial wall and subsequent computation of the distension waveform using Radio Frequency (RF) ultrasound signal. The approach was evaluated on ultrasound RF data acquired using a prototype ultrasound system from an artery mimicking flow phantom. The effectiveness of the proposed algorithm is demonstrated by comparing with existing wall tracking algorithms. The experimental results show that the proposed method provides 20% reduction in the error margin compared to the existing approaches in tracking the arterial wall movement. This approach coupled with ultrasound system can be used to estimate the arterial compliance parameters required for screening of cardiovascular related disorders.Keywords: distension waveform, Gaussian Mixture Model, RF ultrasound, arterial wall movement
Procedia PDF Downloads 5076534 Automatic Landmark Selection Based on Feature Clustering for Visual Autonomous Unmanned Aerial Vehicle Navigation
Authors: Paulo Fernando Silva Filho, Elcio Hideiti Shiguemori
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The selection of specific landmarks for an Unmanned Aerial Vehicles’ Visual Navigation systems based on Automatic Landmark Recognition has significant influence on the precision of the system’s estimated position. At the same time, manual selection of the landmarks does not guarantee a high recognition rate, which would also result on a poor precision. This work aims to develop an automatic landmark selection that will take the image of the flight area and identify the best landmarks to be recognized by the Visual Navigation Landmark Recognition System. The criterion to select a landmark is based on features detected by ORB or AKAZE and edges information on each possible landmark. Results have shown that disposition of possible landmarks is quite different from the human perception.Keywords: clustering, edges, feature points, landmark selection, X-means
Procedia PDF Downloads 2826533 The Effect of a 12 Week Rhythmic Movement Intervention on Selected Biomotor Abilities on Academy Rugby Players
Authors: Jocelyn Solomons, Kraak
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Rhythmic movement, also referred to as “dance”, involves the execution of different motor skills as well as the integration and sequencing of actions between limbs, timing and spatial precision. The aim of this study was therefore to investigate and compare the effect of a 16-week rhythmic movement intervention on flexibility, dynamic balance, agility, power and local muscular endurance of academy rugby players in the Western Cape, according to positional groups. Players (N ¼ 54) (age 18.66 0.81 years; height 1.76 0.69 cm; weight 76.77 10.69 kg), were randomly divided into a treatment-control [TCA] (n ¼ 28) and a control-treatment [CTB] (n ¼ 26) group. In this crossover experimental design, the interaction effect of the treatment order and the treatment time between the TCA and CTB group, was determined. Results indicated a statistically significant improvement (p < 0.05) in agility2 (p ¼ 0.06), power2 (p ¼ 0.05), local muscular endurance1 (p ¼ 0.01) & 3 (p ¼ 0.01) and dynamic balance (p < 0.01). Likewise, forwards and backs also showed statistically significant improvements (p < 0.05) per positional groups. Therefore, a rhythmic movement intervention has the potential to improve rugby-specific bio-motor skills and furthermore, improve positional specific skills should it be designed with positional groups in mind. Future studies should investigate, not only the effect of rhythmic movement on improving specific rugby bio-motor skills, but the potential of its application as an alternative training method during off- season (or detraining phases) or as a recovery method.Keywords: agility, dance, dynamic balance, flexibility, local muscular endurance, power, training
Procedia PDF Downloads 626532 Optimization of the Dental Direct Digital Imaging by Applying the Self-Recognition Technology
Authors: Mina Dabirinezhad, Mohsen Bayat Pour, Amin Dabirinejad
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This paper is intended to introduce the technology to solve some of the deficiencies of the direct digital radiology. Nowadays, digital radiology is the latest progression in dental imaging, which has become an essential part of dentistry. There are two main parts of the direct digital radiology comprised of an intraoral X-ray machine and a sensor (digital image receptor). The dentists and the dental nurses experience afflictions during the taking image process by the direct digital X-ray machine. For instance, sometimes they need to readjust the sensor in the mouth of the patient to take the X-ray image again due to the low quality of that. Another problem is, the position of the sensor may move in the mouth of the patient and it triggers off an inappropriate image for the dentists. It means that it is a time-consuming process for dentists or dental nurses. On the other hand, taking several the X-ray images brings some problems for the patient such as being harmful to their health and feeling pain in their mouth due to the pressure of the sensor to the jaw. The author provides a technology to solve the above-mentioned issues that is called “Self-Recognition Direct Digital Radiology” (SDDR). This technology is based on the principle that the intraoral X-ray machine is capable to diagnose the location of the sensor in the mouth of the patient automatically. In addition, to solve the aforementioned problems, SDDR technology brings out fewer environmental impacts in comparison to the previous version.Keywords: Dental direct digital imaging, digital image receptor, digital x-ray machine, and environmental impacts
Procedia PDF Downloads 1386531 Sports Fans and Non-Interested Public Recognition of the Problems of Sports in Egypt through Caricature
Authors: Alaaeldin Hamdy Ahmed Mohammed
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Introduction: This study examines sports’ fans and non-interested public perception and recognition of the problems that have negative impacts upon the Egyptian sports, particularly football, through caricatures. Eight caricature paintings were designed to express eight problems affecting the Egyptian sports and its development. These paintings were distributed on two groups of the fans and the non-interested public. Methods: The study was limited to eight caricatures representing the eight issues which are: the impact of stopping the sports activity on athletes, the effect of clubs’ disagreement, fanaticism between the members of the ultras of different clubs, the negative impact of the mingling of politics into sports, the negative role of the clubs affects the professionalism of the promising players, the conflict between the national organization responsible for sports, the breaking in of the fans to the playgrounds, the impact of the lack of planning on the national team. The Results: The results showed that both sports fans and those who are not interested in sports recognized the problems that the caricatures refer to and criticizes exaggeration although the rate was higher for the fans. These caricatures contributed also in their recognition of the danger of the negative impact of these problems on the Egyptian sports, particularly football which is the most common at the Egyptian sports fans. Discussion: This finding echoes the conclusion that caricatures are distinctive in the adults’ facial stimuli that are either systematically exaggerated recognition of them.Keywords: caricature, fans, football, sports
Procedia PDF Downloads 3186530 Water Efficiency: Greywater Recycling
Authors: Melissa Lubitz
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Water scarcity is one of the crucial challenges of our time. There needs to be a focus on creating a society where people and nature flourish, regardless of climatic conditions. One of the solutions we can look to is decentralized greywater recycling. The vision is simple. Every building has its own water source being greywater from the bath, shower, sink and washing machine. By treating this in the home, you can save 25-45% of potable water use and wastewater production, a reduction in energy consumption and CO2 emissions. This reusable water is clean, and safe to be used for toilet flushing, washing machine, and outdoor irrigation. Companies like Hydraloop have been committed to the greywater recycle-ready building concept for years. This means that drinking water conservation and water reuse are included as standards in the design of all new buildings. Sustainability and renewal go hand in hand. This vision includes not only optimizing water savings and waste reduction but also forging strong partnerships that bring this ambition to life. Together with regulators, municipalities and builders, a sustainable and water-conscious future is pursued. This is an opportunity to be part of a movement that is making a difference. By pushing this initiative forward, we become part of a growing community that resists dehydration, believes in sustainability, and is committed to a living environment at the forefront of change: sustainable living, where saving water is the norm and where we shape the future together.Keywords: greywater, wastewater treatment, water conservation, circular water society
Procedia PDF Downloads 636529 A Speeded up Robust Scale-Invariant Feature Transform Currency Recognition Algorithm
Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim
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All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.Keywords: currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features
Procedia PDF Downloads 2356528 The Psychological Impact of Acute Occupational Hand Trauma
Authors: Michelle Roesler, Ian Glendon, Francis O'Callaghan
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This study expands on recent findings and offers a new perspective on recovery from injury and return to work (RTW) after an acute traumatic occupational hand injury. Recovery is a complex medical and psychosocial process. A number of predictor variables were studied simultaneously to identify the bio-psychosocial variables that impede recovery. An unexpected phenomenon to emerge from this study was the high incidence of complications within the hand-injured patient sample. Twenty six percent (n = 71) of the total sample (N = 263) required a second operation due to complications. This warranted further investigation. Results confirmed that complications not only significantly delayed the RTW outcome but also had a profound psychological impact on the individuals affected. Research has found that surgical complications are usually the result of incorrect early assessment and management. A strategic plan needs to be implemented to ensure the optimal level of surgical care is provided for managing acute traumatic hand injuries to avoid such complications.Keywords: occupational hand trauma, psychological recovery, return to work, psychology
Procedia PDF Downloads 5116527 An Ensemble-based Method for Vehicle Color Recognition
Authors: Saeedeh Barzegar Khalilsaraei, Manoocheher Kelarestaghi, Farshad Eshghi
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The vehicle color, as a prominent and stable feature, helps to identify a vehicle more accurately. As a result, vehicle color recognition is of great importance in intelligent transportation systems. Unlike conventional methods which use only a single Convolutional Neural Network (CNN) for feature extraction or classification, in this paper, four CNNs, with different architectures well-performing in different classes, are trained to extract various features from the input image. To take advantage of the distinct capability of each network, the multiple outputs are combined using a stack generalization algorithm as an ensemble technique. As a result, the final model performs better than each CNN individually in vehicle color identification. The evaluation results in terms of overall average accuracy and accuracy variance show the proposed method’s outperformance compared to the state-of-the-art rivals.Keywords: Vehicle Color Recognition, Ensemble Algorithm, Stack Generalization, Convolutional Neural Network
Procedia PDF Downloads 85