Search results for: daily activity recognition
9704 Human Gait Recognition Using Moment with Fuzzy
Authors: Jyoti Bharti, Navneet Manjhi, M. K.Gupta, Bimi Jain
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A reliable gait features are required to extract the gait sequences from an images. In this paper suggested a simple method for gait identification which is based on moments. Moment values are extracted on different number of frames of gray scale and silhouette images of CASIA database. These moment values are considered as feature values. Fuzzy logic and nearest neighbour classifier are used for classification. Both achieved higher recognition.Keywords: gait, fuzzy logic, nearest neighbour, recognition rate, moments
Procedia PDF Downloads 7529703 An excessive Screen Time of High School Students in Their Free Time Promotes Our Young People’s Risk of Obesity
Authors: Susana Aldaba Yaben, Marga Echauri Ozcoidi, Rosario Osinaga Cenoz
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It was decided to make a diagnosis with students of Berriozar High School between 12 and 15 years (both included) for their lifestyles in relation to eating habits, BMI (Body Mass Index), physical activity, drugs, interpersonal relationships and screen time. The aim of this survey is identifying needs of this population and depending on the results, we could program socio-educational activities. This action is part of the Community Health Promotion Programme and healthy lifestyles in childhood and youth of Berriozar. The eating habits, a lack of physical activity and an excessive screen time are causes of 26,75% of obese or overweight young people. First of all, many of them have got a diet enriched in saturated fats and sugars. Secondly, most of them do not practise physical exercise daily and finally, their screen time are higher than the recommendation (until 2 hours a day).Keywords: lifestyle, diet, BMI, physical activity, screen time, education, youth
Procedia PDF Downloads 5699702 A Conglomerate of Multiple Optical Character Recognition Table Detection and Extraction
Authors: Smita Pallavi, Raj Ratn Pranesh, Sumit Kumar
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Information representation as tables is compact and concise method that eases searching, indexing, and storage requirements. Extracting and cloning tables from parsable documents is easier and widely used; however, industry still faces challenges in detecting and extracting tables from OCR (Optical Character Recognition) documents or images. This paper proposes an algorithm that detects and extracts multiple tables from OCR document. The algorithm uses a combination of image processing techniques, text recognition, and procedural coding to identify distinct tables in the same image and map the text to appropriate the corresponding cell in dataframe, which can be stored as comma-separated values, database, excel, and multiple other usable formats.Keywords: table extraction, optical character recognition, image processing, text extraction, morphological transformation
Procedia PDF Downloads 1389701 Recognition of Cursive Arabic Handwritten Text Using Embedded Training Based on Hidden Markov Models (HMMs)
Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss
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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.Keywords: recognition, handwriting, Arabic text, HMMs, embedded training
Procedia PDF Downloads 3469700 Eating Habits of Children Aged 10-15 Years in Reference to Nutrition Status
Authors: M. Hetmańczyk, R. Polaniak, K. Brukało, E. Grochowska-Niedworok
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Eating behaviours of people are determined by knowledge gained at different stages of life. Children’s diet is especially important. They have to eat meals regularly. Meals should consist of protein, carbohydrates and fat, and drinking the right amount of water. Mistakes in children’s diets affect their health and may lead to health issues such as diabetes, overweight, obesity or malnutrition. The aim of the study was to assess the eating habits among 10-15-year-old children. To achieve this aim, the study included children aged 10-15 years living in Silesia Province, Poland; the participants consisted of 52.08% girls and 47.92% boys. Authorial questionnaire contains 28 questions about eating habits. The results of 192 students were subjected to analysis. The results show that half of the surveyed students participated in physical activity every day. Most children ate 4-5 meals every day, but the breaks between them were too long (four and more hours). Children generally ate cooked meals. Most children ate first breakfast every day, but only one third of studied children ate a second breakfast daily, while 93.75% ate vegetables at least once a day, 94.79% ate fruit at least once a day, and 79.17% drink a daily glass of milk or more. The study found that the eating behaviours of the surveyed children were unsatisfying. While the children did not participate in physical activity often enough, girls took part slightly more often. Children eat second breakfast not often enough. Younger children (10-12 years old) are doing it more often than the older children (13-15 years old). Gender is not a determinant of the frequency of second breakfast consumption.Keywords: eating habits, children, diet, nutrition status
Procedia PDF Downloads 1619699 Words Spotting in the Images Handwritten Historical Documents
Authors: Issam Ben Jami
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Information retrieval in digital libraries is very important because most famous historical documents occupy a significant value. The word spotting in historical documents is a very difficult notion, because automatic recognition of such documents is naturally cursive, it represents a wide variability in the level scale and translation words in the same documents. We first present a system for the automatic recognition, based on the extraction of interest points words from the image model. The extraction phase of the key points is chosen from the representation of the image as a synthetic description of the shape recognition in a multidimensional space. As a result, we use advanced methods that can find and describe interesting points invariant to scale, rotation and lighting which are linked to local configurations of pixels. We test this approach on documents of the 15th century. Our experiments give important results.Keywords: feature matching, historical documents, pattern recognition, word spotting
Procedia PDF Downloads 2699698 Recognition of Tifinagh Characters with Missing Parts Using Neural Network
Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui
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In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN
Procedia PDF Downloads 3259697 Impact of Integrated Signals for Doing Human Activity Recognition Using Deep Learning Models
Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo
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Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps
Procedia PDF Downloads 899696 Exploratory Analysis of A Review of Nonexistence Polarity in Native Speech
Authors: Deawan Rakin Ahamed Remal, Sinthia Chowdhury, Sharun Akter Khushbu, Sheak Rashed Haider Noori
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Native Speech to text synthesis has its own leverage for the purpose of mankind. The extensive nature of art to speaking different accents is common but the purpose of communication between two different accent types of people is quite difficult. This problem will be motivated by the extraction of the wrong perception of language meaning. Thus, many existing automatic speech recognition has been placed to detect text. Overall study of this paper mentions a review of NSTTR (Native Speech Text to Text Recognition) synthesis compared with Text to Text recognition. Review has exposed many text to text recognition systems that are at a very early stage to comply with the system by native speech recognition. Many discussions started about the progression of chatbots, linguistic theory another is rule based approach. In the Recent years Deep learning is an overwhelming chapter for text to text learning to detect language nature. To the best of our knowledge, In the sub continent a huge number of people speak in Bangla language but they have different accents in different regions therefore study has been elaborate contradictory discussion achievement of existing works and findings of future needs in Bangla language acoustic accent.Keywords: TTR, NSTTR, text to text recognition, deep learning, natural language processing
Procedia PDF Downloads 1229695 Developing a Secure Iris Recognition System by Using Advance Convolutional Neural Network
Authors: Kamyar Fakhr, Roozbeh Salmani
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Alphonse Bertillon developed the first biometric security system in the 1800s. Today, many governments and giant companies are considering or have procured biometrically enabled security schemes. Iris is a kaleidoscope of patterns and colors. Each individual holds a set of irises more unique than their thumbprint. Every single day, giant companies like Google and Apple are experimenting with reliable biometric systems. Now, after almost 200 years of improvements, face ID does not work with masks, it gives access to fake 3D images, and there is no global usage of biometric recognition systems as national identity (ID) card. The goal of this paper is to demonstrate the advantages of iris recognition overall biometric recognition systems. It make two extensions: first, we illustrate how a very large amount of internet fraud and cyber abuse is happening due to bugs in face recognition systems and in a very large dataset of 3.4M people; second, we discuss how establishing a secure global network of iris recognition devices connected to authoritative convolutional neural networks could be the safest solution to this dilemma. Another aim of this study is to provide a system that will prevent system infiltration caused by cyber-attacks and will block all wireframes to the data until the main user ceases the procedure.Keywords: biometric system, convolutional neural network, cyber-attack, secure
Procedia PDF Downloads 2119694 ANAC-id - Facial Recognition to Detect Fraud
Authors: Giovanna Borges Bottino, Luis Felipe Freitas do Nascimento Alves Teixeira
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This article aims to present a case study of the National Civil Aviation Agency (ANAC) in Brazil, ANAC-id. ANAC-id is the artificial intelligence algorithm developed for image analysis that recognizes standard images of unobstructed and uprighted face without sunglasses, allowing to identify potential inconsistencies. It combines YOLO architecture and 3 libraries in python - face recognition, face comparison, and deep face, providing robust analysis with high level of accuracy.Keywords: artificial intelligence, deepface, face compare, face recognition, YOLO, computer vision
Procedia PDF Downloads 1489693 Effects of Recognition of Customer Feedback on Relationships between Emotional Labor and Job Satisfaction: Focusing On Call Centers That Offer Professional Services
Authors: Kiyoko Yoshimura, Yasunobu Kino
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Focusing on professional call centers where workers with expertise perform services, this study aims to clarify the relationships between emotional labor and job satisfaction and the effects of recognition of customer feedback. Since the professional call center operators consist of professional license holders (qualification holders) and those who do not (non-holders), the following three points are analyzed in the two groups by using covariance structure analysis and simultaneous multi-population analysis: 1) The relationship between emotional labor and job satisfaction, 2) customer feedback and job satisfaction, and 3) The intermediation effect between the emotional labor of customer feedback and job satisfaction. The following results are obtained: i) no direct effect is found between job satisfaction and emotional labor for qualification holders and non-holders, ii) for qualification holders and non-holders, recognition of positive feedback and recognition of negative feedback had positive and negative effects on job satisfaction, respectively, iii) for qualification and non-holders, "consideration for colleagues" influences job satisfaction by recognizing positive feedback, and iv) only for qualification holders, the factors "customer-oriented emotional expression" and "emotional disharmony" have a positive and negative effect on job satisfaction, respectively, through recognition of positive feedback and recognition of negative feedback.Keywords: call center, emotional labor, professional service, job satisfaction, customer feedback
Procedia PDF Downloads 949692 Distorted Document Images Dataset for Text Detection and Recognition
Authors: Ilia Zharikov, Philipp Nikitin, Ilia Vasiliev, Vladimir Dokholyan
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With the increasing popularity of document analysis and recognition systems, text detection (TD) and optical character recognition (OCR) in document images become challenging tasks. However, according to our best knowledge, no publicly available datasets for these particular problems exist. In this paper, we introduce a Distorted Document Images dataset (DDI-100) and provide a detailed analysis of the DDI-100 in its current state. To create the dataset we collected 7000 unique document pages, and extend it by applying different types of distortions and geometric transformations. In total, DDI-100 contains more than 100,000 document images together with binary text masks, text and character locations in terms of bounding boxes. We also present an analysis of several state-of-the-art TD and OCR approaches on the presented dataset. Lastly, we demonstrate the usefulness of DDI-100 to improve accuracy and stability of the considered TD and OCR models.Keywords: document analysis, open dataset, optical character recognition, text detection
Procedia PDF Downloads 1649691 A Randomized, Controlled Trial to Test Behavior Change Techniques to Improve Low Intensity Physical Activity in Older Adults
Authors: Ciaran Friel, Jerry Suls, Mark Butler, Patrick Robles, Samantha Gordon, Frank Vicari, Karina W. Davidson
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Physical activity guidelines focus on increasing moderate-intensity activity for older adults, but adherence to recommendations remains low. This is despite the fact that scientific evidence supports that any increase in physical activity is positively correlated with health benefits. Behavior change techniques (BCTs) have demonstrated effectiveness in reducing sedentary behavior and promoting physical activity. This pilot study uses a Personalized Trials (N-of-1) design to evaluate the efficacy of using four BCTs to promote an increase in low-intensity physical activity (2,000 steps of walking per day) in adults aged 45-75 years old. The 4 BCTs tested were goal setting, action planning, feedback, and self-monitoring. BCTs were tested in random order and delivered by text message prompts requiring participant engagement. The study recruited health system employees in the target age range, without mobility restrictions and demonstrating interest in increasing their daily activity by a minimum of 2,000 steps per day for a minimum of five days per week. Participants were sent a Fitbit® fitness tracker with an established study account and password. Participants were recommended to wear the Fitbit device 24/7 but were required to wear it for a minimum of ten hours per day. Baseline physical activity was measured by Fitbit for two weeks. In the 8-week intervention phase of the study, participants received each of the four BCTs, in random order, for a two-week period. Text message prompts were delivered daily each morning at a consistent time. All prompts required participant engagement to acknowledge receipt of the BCT message. Engagement is dependent upon the BCT message and may have included recording that a detailed plan for walking has been made or confirmed a daily step goal (action planning, goal setting). Additionally, participants may have been directed to a study dashboard to view their step counts or compare themselves to their baseline average step count (self-monitoring, feedback). At the end of each two-week testing interval, participants were asked to complete the Self-Efficacy for Walking Scale (SEW_Dur), a validated measure that assesses the participant’s confidence in walking incremental distances, and a survey measuring their satisfaction with the individual BCT that they tested. At the end of their trial, participants received a personalized summary of their step data in response to each individual BCT. The analysis will examine the novel individual-level heterogeneity of treatment effect made possible by N-of-1 design and pool results across participants to efficiently estimate the overall efficacy of the selected behavioral change techniques in increasing low-intensity walking by 2,000 steps, five days per week. Self-efficacy will be explored as the likely mechanism of action prompting behavior change. This study will inform the providers and demonstrate the feasibility of an N-of-1 study design to effectively promote physical activity as a component of healthy aging.Keywords: aging, exercise, habit, walking
Procedia PDF Downloads 869690 Recognition and Enforcement of Foreign Decree Divorces in India with Special Reference to the Hindu Marriage Act, 1955
Authors: Poonamdeep kaur
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With the increase in number of Non-Resident Indian marriages there is also increase in foreign decree divorces which inevitably causes the problem of recognition and enforcement of foreign judgments in India. The Hindus in India are governed by the Hindu Marriage Act, 1956. According to the said Act the courts in India have jurisdiction to try the matrimonial dispute if the marriage is performed in India or the parties to the marriage have domicile in India irrespective of their nationality status. But, sometimes one of the parties to the marriage whose marriage is solemnized in India obtains divorce in foreign courts and prays for the recognition and enforcement of such divorce in India. In such case section 13 of the Indian Civil Procedure Code, 1908, comes into play for the recognition and enforcement of foreign divorces in India. The section makes a foreign judgment conclusive in India subject to the fulfilment of certain conditions. Even if a foreign decree divorce is given on personal connecting factors of the parties to the matrimonial dispute like domicile, such divorce may still be refused recognition in India by virtue of section 13 of the Indian Civil Procedure Code, 1908. It is a universal truth that municipal law of countries is not the same throughout the world. Comity plays an important role in recognition and enforcing a foreign judgment, but, now in India the principle is not applied mechanically as the divorce matter is dealt strictly with regard to Indian Law. So in this paper there will be deep analysis of Indian case laws relating to recognition and enforcement of foreign divorces and based on this a comparative study will be made with the laws of Canada and England on the same subject to find out whether the Indian law on recognition and Enforcement of foreign judgment are in line with the laws of Canada and England and whether in recent years the Indian courts have evolved some new principles of private international law to deal with limping marriages. At last conclusions will be drawn out from the comparative study and suggestions would be given to make the rules of recognition and enforcement of foreign judgments on divorce more certain.Keywords: divorce, foreign decree, private international law, recognition and enforcement of foreign judgment
Procedia PDF Downloads 1879689 Optimal Feature Extraction Dimension in Finger Vein Recognition Using Kernel Principal Component Analysis
Authors: Amir Hajian, Sepehr Damavandinejadmonfared
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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)
Procedia PDF Downloads 3599688 Arabic Handwriting Recognition Using Local Approach
Authors: Mohammed Arif, Abdessalam Kifouche
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Optical character recognition (OCR) has a main role in the present time. It's capable to solve many serious problems and simplify human activities. The OCR yields to 70's, since many solutions has been proposed, but unfortunately, it was supportive to nothing but Latin languages. This work proposes a system of recognition of an off-line Arabic handwriting. This system is based on a structural segmentation method and uses support vector machines (SVM) in the classification phase. We have presented a state of art of the characters segmentation methods, after that a view of the OCR area, also we will address the normalization problems we went through. After a comparison between the Arabic handwritten characters & the segmentation methods, we had introduced a contribution through a segmentation algorithm.Keywords: OCR, segmentation, Arabic characters, PAW, post-processing, SVM
Procedia PDF Downloads 519687 Cells Detection and Recognition in Bone Marrow Examination with Deep Learning Method
Authors: Shiyin He, Zheng Huang
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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet
Procedia PDF Downloads 1789686 A Study on the Influence of Aswan High Dam Reservoir Loading on Earthquake Activity
Authors: Sayed Abdallah Mohamed Dahy
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Aswan High Dam Reservoir extends for 500 km along the Nile River; it is a vast reservoir in southern Egypt and northern Sudan. It was created as a result of the construction of the Aswan High Dam between 1958 and 1970; about 95% of the main water resources for Egypt are from it. The purpose of this study is to discuss and understand the effect of the fluctuation of the water level in the reservoir on natural and human-induced environmental like earthquakes in the Aswan area, Egypt. In summary, the correlation between the temporal variations of earthquake activity and water level changes in the Aswan reservoir from 1982 to 2014 are investigated and analyzed. This analysis confirms a weak relation between the fluctuation of the water level and earthquake activity in the area around Aswan reservoir. The result suggests that the seismicity in the area becomes active during a period when the water level is decreasing from the maximum to the minimum. Behavior of the water level in this reservoir characterized by a special manner that is the unloading season extends to July or August, and the loading season starts to reach its maximum in October or November every year. Finally, daily rate of change in the water level did not show any direct relation with the size of the earthquakes, hence, it is not possible to be used as a single tool for prediction.Keywords: Aswan high dam reservoir, earthquake activity, environmental, Egypt
Procedia PDF Downloads 3729685 Kannada HandWritten Character Recognition by Edge Hinge and Edge Distribution Techniques Using Manhatan and Minimum Distance Classifiers
Authors: C. V. Aravinda, H. N. Prakash
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In this paper, we tried to convey fusion and state of art pertaining to SIL character recognition systems. In the first step, the text is preprocessed and normalized to perform the text identification correctly. The second step involves extracting relevant and informative features. The third step implements the classification decision. The three stages which involved are Data acquisition and preprocessing, Feature extraction, and Classification. Here we concentrated on two techniques to obtain features, Feature Extraction & Feature Selection. Edge-hinge distribution is a feature that characterizes the changes in direction of a script stroke in handwritten text. The edge-hinge distribution is extracted by means of a windowpane that is slid over an edge-detected binary handwriting image. Whenever the mid pixel of the window is on, the two edge fragments (i.e. connected sequences of pixels) emerging from this mid pixel are measured. Their directions are measured and stored as pairs. A joint probability distribution is obtained from a large sample of such pairs. Despite continuous effort, handwriting identification remains a challenging issue, due to different approaches use different varieties of features, having different. Therefore, our study will focus on handwriting recognition based on feature selection to simplify features extracting task, optimize classification system complexity, reduce running time and improve the classification accuracy.Keywords: word segmentation and recognition, character recognition, optical character recognition, hand written character recognition, South Indian languages
Procedia PDF Downloads 4889684 Beyond Cooking and Food Preparation: Examining the Material Culture of Medieval Cuisine in the Middle East
Authors: Shurouq Munzer
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This study investigates methods for inferring the presence of cooking activity at an archaeological site through the study of cooking tools, contextual evidence, and food preparation techniques. This paper examines the patterns of cooking utensils and categorizes the morphological features as well as the types of clay utilized in manufacturing such cooking utensils. Despite challenges in accessing such evidence due to its limited availability in books and excavations. The excavation results provide the point for evaluating progress in daily life and underscore the cultural, social, and economic significance of studying cooking activity at archaeological sites within their archaeological contexts.Keywords: coarse ware, cooking utensils, ḥisba, waqif, muḥtasib, foodways, practice, cuisine, food preparation
Procedia PDF Downloads 679683 Electroencephalography Activity during Sensory Organization Balance Test
Authors: Tariq Ali Gujar, Anita Hökelmann
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Postural balance plays essential role throughout life in daily activities. Somatosensory, visual and vestibular inputs play the fundamental role in maintaining body equilibrium to balance the posture. The aim of this study was to find out electroencephalography (EEG) responses during balance activity of young people during Sensory Organization Balance Test. The outcome of this study will help to create the fitness and neurorehabilitation plan. 25 young people (25 ± 3.1 years) have been analyzed on Balance Master NeuroCom® with the coupling of Brain Vision 32 electrode wireless EEG system during the Sensory Organization Test. From the results it has been found that the balance score of samples is significantly higher under the influence of somatosensory input as compared to visual and vestibular input (p < 0.05). The EEG between somatosensory and visual input to balance the posture showed significantly higher (p < 0.05) alpha and beta activities during somatosensory input in somatosensory, attention and visual functions of the cortex whereas executive and motor functions of the cerebral cortex showed significantly higher (p < 0.05) alpha EEG activity during the visual input. The results suggest that somatosensory and attention function of the cerebral cortex has alpha and beta activity, respectively high during somatosensory and vestibular input in maintaining balance. In patients with balance impairments both physical and cognitive training, including neurofeedback will be helpful to improve balance abilities.Keywords: balance, electroencephalography activity, somatosensory, visual, vestibular
Procedia PDF Downloads 5759682 The Study of Solar Activity during Sun Eclipse and Its Relation to Earthquake
Authors: Hanieh Sadat Jannesari. Rahelehossadat Abtahi, Kourosh Bamzadeh, Alireza Nadimi
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The earthquake is one of the most devastating natural hazards, in which hundreds of thousands have lost their lives as a result of it. So far, experts have tried to use precursors to identify the earthquake before it occurs in order to alert and save people, a part of which relates to solar activity and earthquakes. The purpose of this article is to investigate solar activity during the solar eclipse as a precursor to pre-earthquake awareness. Information from this article is derived from the Influences and USGS Daily Data Center. During solar activity, electric interactions between the solar wind and the celestial bodies are formed, and then gravitational lenses are formed. If, during this event, there is also an eclipse, the dispersed waves in space (in accordance with the theory of general relativity of Einstein) in contact with plasma-gravitational lenses in space will move in a straight line toward the earth. In addition to forming the focal point, these gravitational lenses reflect the source image either at their focal length or farther away. The image reflected in the earth by ionized particles in the form of energy transmission lines can cause material collapse and earthquakes. In this study, the correlation between solar winds and the celestial bodies during the solar eclipse is about 76% of the location of large earthquakes.Keywords: earthquake, plasma-gravitational lens, solar eclipse, solar spots
Procedia PDF Downloads 79681 An Automatic Speech Recognition Tool for the Filipino Language Using the HTK System
Authors: John Lorenzo Bautista, Yoon-Joong Kim
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This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition
Procedia PDF Downloads 4739680 Evaluation of Total Phenolic Content and Antioxidant Activity in Amaranth Seeds Grown in Latvia
Authors: Alla Mariseva, Ilze Beitane
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Daily intake of products rich in antioxidants that scavenge free radicals in cell membranes is an effective way to combat oxidative stress. Last year there was noticed higher interest towards the identification and utilization of plants rich in antioxidant compounds as they may behave as preventive medicine. Amaranth seeds due to polyphenols, anthocyanins, flavonoids, and tocopherols are characterized by high antioxidant activity. The study aimed to evaluate the total phenolic content and radical scavenging activity of amaranth seeds cultivated in 2020 in two farms in Latvia. One sample of amaranth seeds came from an organic farm, the other – from a conventional farm. The total phenol content of amaranth seed extracts was measured with the Folin-Ciocalte spectrophotometric method. The total phenols were expressed as gallic acid equivalents (GAE) per 100 g dry weight (DW) of the samples. The antioxidant activity of amaranth seed extracts was calculated based on scavenging activities of the stable 2.2-diphenyl-1-picrylhydrazyl (DPPH˙) radical, the radical scavenging capacity (ABTS) was demonstrated as Trolox mM equivalents (TE) per 100 g-1 dry weight. Three parallel measurements were performed on all samples. There were significant differences between organic and conventional amaranth seeds in terms of total phenolic content and antioxidant activity. Organic amaranth seeds showed higher total phenolic content compared to conventional amaranth seeds, 65.4±6.0 mg GAE 100 g⁻¹ DW and 43.4±7.8 mg GAE 100 g⁻¹ DW respectively. Organic amaranth seeds were also characterized by higher DPPH radical scavenging activity (7.9±0.4 mM TE 100 g⁻¹ of dry matter) and ABTS radical scavenging capacity (13.2±1.5 mM TE 100 g⁻¹ of dry matter). The results obtained on total phenolic content and antioxidant activity of amaranth seeds grown in Latvia confirmed that the samples have a high biological value; therefore, it would be necessary to promote their consumption by including them in various food products, including vegan products, increasing their nutritional value.Keywords: ABTS, amaranth seeds, antioxidant activity, DPPH, total phenolic content
Procedia PDF Downloads 2169679 MarginDistillation: Distillation for Face Recognition Neural Networks with Margin-Based Softmax
Authors: Svitov David, Alyamkin Sergey
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The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.Keywords: ArcFace, distillation, face recognition, margin-based softmax
Procedia PDF Downloads 1419678 A Longitudinal Study to Develop an Emotional Design Framework for Physical Activity Interventions
Authors: Stephanie Hewitt, Leila Sheldrick, Weston Baxter
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Multidisciplinary by nature, design research brings together varying research fields to answer globally significant questions. Emotional design, a field which helps us create products that influence people’s behaviour, and sports psychology, containing a growing field of recent research which focuses on understanding the emotions experienced through sport and the effects this has on our health and wellbeing, are two research fields that can be combined through design research to tackle global physical inactivity. The combination of these research fields presents an opportunity to build new tools and methods that could help designers create new interventions to promote positive behaviour change in the form of physical activity uptake, ultimately improving people’s health and wellbeing. This paper proposes a framework that can be used to develop new products and services that focus on not only improving the uptake and upkeep of physical activity but also helping people have a healthy emotional relationship with exercise. To develop this framework, a set of comprehensive maps exploring the relationship between human emotions and physical activity across a range of factors was created. These maps were then further evolved through in-depth interviews, which analysed the reasons behind the emotions felt, how physical activity fits into the daily routine and how important regular exercise is to people. Finally, to progress these findings into a design framework, a longitudinal study was carried out to explore further the emotional relationship people of varying sporting abilities have overtime with physical activity. This framework can be used to design more successful interventions that help people to not only become more active initially but implement long term changes to ensure they stay active.Keywords: design research, emotional design, emotions, intervention, physical activity, sport psychology
Procedia PDF Downloads 1289677 A Machine Learning Approach for Earthquake Prediction in Various Zones Based on Solar Activity
Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Saifur Rahman Sabuj
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This paper examines relationships between solar activity and earthquakes; it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to affect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth.Keywords: k-nearest neighbour, support vector regression, random forest regression, long short-term memory network, earthquakes, solar activity, sunspot number, solar wind, solar flares
Procedia PDF Downloads 679676 Assessment of the Physical Activity Level and the Nutritional Status among Students in Bowen University, Iwo, Osun State, Nigeria
Authors: Fakunle Egbo, Kammalchukwu A., Akinremi T.
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Physical activity and nutritional status influence the health status and cognition of young adults. Lack of physical activity increases the likelihood of developing obesity which leads to the risk of heart diseases and other risk factors like high blood pressure, high blood cholesterol, diabetes etc. The study employed a cross-sectional study design. The study used a multi stage sampling technique multi- stage sampling technique; Purposive, for the selection of colleges that would be used, stratified random sampling for stratifying the colleges into departments and the simple random sampling for the selection of each respondent from the departments. Structured questionnaires were used to obtain data from the respondents and pre-tested anthropometric instruments were used to get the weight and height of the respondents and statistically analyzed using SPSS version 22.0 and the TDA (Total dietary allowance) software which was used to analyze the nutrient intake of the respondents. This study showed that they comprised of 50.1% males and 40.9% females. Slightly above average 51.8% were between ages of 15-19 with mean age being 19.57 years; ages 20-24 were slightly below average at 45.7%. The male students 58.7% had vigorous physical activity, whereas majority of females 76.5% had light physical activity level. 39.1% of the male students carried out physical activity 2-3 times per week while One third of the female students (38.3%) carried out physical activity 6-7 times per week. Majority of the respondents had Inadequate Protein- 63.8%, Carbohydrate- 60.2%, and Dietary fiber- 88.8. 36% eat rice 4-6 times per week. Majority of the respondents had inadequate fruit and vegetables (Efo, Banana,) at 47.7%, 40.6% respectively. Using Body mass index, (63.2%) have normal weight. 22.9% are overweight, 6.8% are underweight, 5.4% have grade 1 obesity and 1.6% have grade II obesity. There was a statistically significant association between the physical activity of the respondents with their nutritional status (p=0.037), physical activity and sex (p=0.000), nutritional status and amount spent on food daily (p=0.007). The study concluded that the physical activity level of the respondents, most especially the females were low; One third of the students were malnourished therefore, there should be an urgent need for improving the overall health status of students by providing the students with well-equipped gyms and other sporting equipment’s that would make them participate actively and keep fit.Keywords: physical activity, nutritional status, undergraduates, dietary pattern
Procedia PDF Downloads 629675 Hand Gesture Recognition Interface Based on IR Camera
Authors: Yang-Keun Ahn, Kwang-Soon Choi, Young-Choong Park, Kwang-Mo Jung
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Vision based user interfaces to control TVs and PCs have the advantage of being able to perform natural control without being limited to a specific device. Accordingly, various studies on hand gesture recognition using RGB cameras or depth cameras have been conducted. However, such cameras have the disadvantage of lacking in accuracy or the construction cost being large. The proposed method uses a low cost IR camera to accurately differentiate between the hand and the background. Also, complicated learning and template matching methodologies are not used, and the correlation between the fingertips extracted through curvatures is utilized to recognize Click and Move gestures.Keywords: recognition, hand gestures, infrared camera, RGB cameras
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