Search results for: daily activity recognition

Authors: Mikhail S. Zastrozhin, Valery V. Smirnov, Dmitry A. Sychev, Ludmila M. Savchenko, Evgeny A. Bryun, Mark O. Nechaev

Abstract:

Cytochrome P-450 isoenzyme 3A4 takes part in the biotransformation of medical drugs. The activity of CYP isoenzymes depends on genetic (polymorphisms of genes which encoded it) and phenotypic factors (a kind of food, a concomitant drug therapy). The aim of the study was to evaluate a carbamazepine effect on the CYP3A4 activity in patients with alcohol addiction. The study included 25 men with alcohol dependence, who received haloperidol during the exacerbation of the addiction. CYP3A4 activity was assessed by urinary 6-beta-hydroxycortisol/cortisol ratios measured by high performance liquid chromatography with mass spectrometry. The study modeled a graph and an equation of the logarithmic regression, that reflects the dependence of CYP3A4 activity on a dose of carbamazepine: y = 5,5 * 9,1 * 10-5 * x2. The study statistically significant demonstrates the effect of carbamazepine on CYP2D6 isozyme activity in patients with alcohol addiction.

Keywords: CYP3A4, biotransformation, carbamazepine, alcohol abuse

Procedia PDF Downloads 252

Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

Abstract:

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 473

Authors: S. Krimat, T. Dob, L. Lamari, H. Metidji

Abstract:

The aim of this study is to evaluate the antioxidant and antimicrobial activity of hydromethanolic extract of selected Algerian medicinal flora. The antioxidant activity of extract was evaluated in terms of radical scavenging potential (DPPH) and β-carotene bleaching assay. Total phenolic contents and flavonoid contents were also measured. Antimicrobial activity of these plants was tested against five microorganisms Pseu-domonas aeruginosa Bacillus subtilis, Escherichia coli, Staphylococcus aureus, and Candida albicans. The results showed that Pistacia lentiscus showed the highest antioxidant capacities using DPPH assay (IC50 = 4.60 μg/ml), while Populus trimula had the highest antioxidant activity in β-carotene/linolaic acid assay. The most interesting antimicrobial activity was obtained from Sysimbrium officinalis, Rhamnus alaternus, Origanum glandulosum, Cupressus sempervirens, Pinus halipensis and Centaurea calcitrapa. The results indicate that the plants tested may be potential sources for isolation of natural antioxidant and antimicrobial compounds.

Keywords: Algerian medicinal plants, antimicrobial activity, antioxidant activity, disc diffusion method

Procedia PDF Downloads 318

Authors: Heng Yang, Tao Luo, Yakun Zhang, Kai Wang, Wei Qin, Liang Xie, Ye Yan, Erwei Yin

Abstract:

Recent years have seen that audio-visual recognition has shown great potential in a strong noise environment. The existing method of audio-visual recognition has explored methods with ResNet and feature fusion. However, on the one hand, ResNet always occupies a large amount of memory resources, restricting the application in engineering. On the other hand, the feature merging also brings some interferences in a high noise environment. In order to solve the problems, we proposed an effective framework with bidirectional distillation. At first, in consideration of the good performance in extracting of features, we chose the light model, Efficientnet as our extractor of spatial features. Secondly, self-distillation was applied to learn more information from raw data. Finally, we proposed a bidirectional distillation in decision-level fusion. In more detail, our experimental results are based on a multi-model dataset from 24 volunteers. Eventually, the lipreading accuracy of our framework was increased by 2.3% compared with existing systems, and our framework made progress in audio-visual fusion in a high noise environment compared with the system of audio recognition without visual.

Keywords: lipreading, audio-visual, Efficientnet, distillation

Procedia PDF Downloads 109

Authors: Paulo Fernando Silva Filho, Elcio Hideiti Shiguemori

Abstract:

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 256

Authors: Linna Li

Abstract:

The capability to move around places is doubtless very important for individuals to maintain good health and social functions. People’s activities in space and time have long been a research topic in behavioral and socio-economic studies, particularly focusing on the highly dynamic urban environment. By analyzing groups of people who share similar activity patterns, many socio-economic and socio-demographic problems and their relationships with individual behavior preferences can be revealed. Los Angeles, known for its large population, ethnic diversity, cultural mixing, and entertainment industry, faces great transportation challenges such as traffic congestion, parking difficulties, and long commuting. Understanding people’s travel behavior and movement patterns in this metropolis sheds light on potential solutions to complex problems regarding urban mobility. This project visualizes people’s trajectories in Greater Los Angeles (L.A.) Area over a period of two months using Twitter data. A Python script was used to collect georeferenced tweets within the Greater L.A. Area including Ventura, San Bernardino, Riverside, Los Angeles, and Orange counties. Information associated with tweets includes text, time, location, and user ID. Information associated with users includes name, the number of followers, etc. Both aggregated and individual activity patterns are demonstrated using various geovisualization techniques. Locations of individual Twitter users were aggregated to create a surface of activity hot spots at different time instants using kernel density estimation, which shows the dynamic flow of people’s movement throughout the metropolis in a twenty-four-hour cycle. In the 3D geovisualization interface, the z-axis indicates time that covers 24 hours, and the x-y plane shows the geographic space of the city. Any two points on the z axis can be selected for displaying activity density surface within a particular time period. In addition, daily trajectories of Twitter users were created using space-time paths that show the continuous movement of individuals throughout the day. When a personal trajectory is overlaid on top of ancillary layers including land use and road networks in 3D visualization, the vivid representation of a realistic view of the urban environment boosts situational awareness of the map reader. A comparison of the same individual’s paths on different days shows some regular patterns on weekdays for some Twitter users, but for some other users, their daily trajectories are more irregular and sporadic. This research makes contributions in two major areas: geovisualization of spatial footprints to understand travel behavior using the big data approach and dynamic representation of activity space in the Greater Los Angeles Area. Unlike traditional travel surveys, social media (e.g., Twitter) provides an inexpensive way of data collection on spatio-temporal footprints. The visualization techniques used in this project are also valuable for analyzing other spatio-temporal data in the exploratory stage, thus leading to informed decisions about generating and testing hypotheses for further investigation. The next step of this research is to separate users into different groups based on gender/ethnic origin and compare their daily trajectory patterns.

Keywords: geovisualization, human mobility pattern, Los Angeles, social media

Procedia PDF Downloads 98

Authors: Albert Perez-Bellmunt, Eila Rivera, Aida Valls, Berta Estragues, Sara Ortiz, Roberto Seijas, Pedro Alvarez

Abstract:

INTRODUCTION: Physical and sports activity on a regular basis present numerous health benefits such as the prevention of cardiovascular and metabolic diseases. Also, there is a relation between sport and the psychological or the cognitive process of children and young people. The objective of the present study is to know if the sports practice has any positive influence on the university academic performance. MATERIALS AND METHODS: The level of the physical activity of 220 students of different degrees in health science was evaluated and compared with the academic results (grades). To assess the level of physical and sports activity, the Global Physical Activity Questionnaire (to calculate the sporting level in a general way) and the International Physical Activity Questionnaire (to estimate the physical activity carried out during the days leading up to the academic exams) were used. RESULTS: The students that realized an average level of sports activity the days before the exam obtained better grades than the rest of their classmate and the result was statistically significant. Controversially, if the sports level was analyzed in a general way, no relationship was observed between academic performance and the level of sport realized. CONCLUSION: A moderate physical activity, on the days leading up to an assessment, can be a positive factor for the university academic performance. Despite the fact that a regular sports activity improves many cognitive and physiological processes, the present study did not observe a direct relationship between sport/physical activity and academic performance.

Keywords: academic performance, academic results, global physical activity questionnaire, physical activity questionnaire, sport, sport practice

Procedia PDF Downloads 171

Authors: Abdulrahman M. Alhowikan, Nadra E. Elamin, Sarah S. Aldayel, Sara A. AlSiddiqi, Fai S. Alrowais, Laila Y. Al-Ayadhi

Abstract:

Background: A growing body of research has suggested that physical activities (PA) have important implications for improving the performance of ASD children. They revealed that the physiological, cognitive, psychological, and behavioral functioning had improved after performing some physical activities. Methods: We compared the sedentary behavior and physical activities between children with autism spectrum disorder (n=21) and age-matched control group (n=30), using the ActiGraph GT3X+ for the assessments. Results: Our results revealed that the total time spent in sedentary activity and the total sedentary activity counts were highly significant in the control group compared to the ASD group (p < 0.001, p=0.001, respectively). ASD spent a significantly longer time than the controls engaging on vigorous physical activity (VPA) (p=0.017). The results also indicated that there were no significant differences between both groups for the total counts and time spent in light physical activity (LPA) and moderate physical activity (MPA). Conclusion: The finding highlights the importance of physical activity intervention for ASD children, using accurate and precise measurement tools to record all activities.

Keywords: Autism spectrum disorders, motor skills, physical activity, ActiGraph GT3X+, moderate-to vigorous-intensity physical activity

Procedia PDF Downloads 117

Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

Abstract:

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 216

Authors: Sasitorn Chetanont

Abstract:

The objectives of this study are to find out the approaches to promote healthy recreation activities for elderly tourists and develop Bang Nam Phueng Floating Market to be a health tourism attraction. The research methodology was to analyze internal and external situations according to MP-MF and the MC-STEPS principles. As for the results of this study the researcher found that the healthy recreational activities for elderly tourists could be divided in 7 groups; travelling Bang Nam Phueng Floating Market activity, homestay relaxation, arts center platform activity, healthy massage activity, paying homage to a Buddha image activity, herbal joss-stick home activity, making local desserts and food activity.

Keywords: elderly tourists, recreation activities, Bang Nam Phueng Floating Market, health tourism

Procedia PDF Downloads 400

Authors: Saeedeh Barzegar Khalilsaraei, Manoocheher Kelarestaghi, Farshad Eshghi

Abstract:

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 58

Authors: Sandhya Baskaran, Hari Kumar Nagabushanam

Abstract:

Sarcasm sentiment recognition is an area of natural language processing that is being probed into in the recent times. Even with the advancements in NLP, typical translations of words, sentences in its context fail to provide the exact information on a sentiment or emotion of a user. For example, if something bad happens, the statement ‘That's just what I need, great! Terrific!’ is expressed in a sarcastic tone which could be misread as a positive sign by any text-based analyzer. In this paper, we are presenting a unique real time ‘word with its tone’ spotting technique which would provide the sentiment analysis for a tone or pitch of a voice in combination with the words being expressed. This hybrid approach increases the probability for identification of special sentiment like sarcasm much closer to the real world than by mining text or speech individually. The system uses a tone analyzer such as YIN-FFT which extracts pitch segment-wise that would be used in parallel with a speech recognition system. The clustered data is classified for sentiments and sarcasm score for each of it determined. Our Simulations demonstrates the improvement in f-measure of around 12% compared to existing detection techniques with increased precision and recall.

Keywords: sarcasm recognition, tone-word spotting, natural language processing, pitch analyzer

Procedia PDF Downloads 273

Authors: Isaac Yeboah

Abstract:

Physical activity (PA) is considered the best preventative tool for maintaining physical health and extending lifespan because it offers a range of benefits. However, for people to benefit from physical activity, it must be done at a level that can enhance fitness, health, and overall well-being. Therefore, this study aimed to determine the link between physical activity participation levels and cardiorespiratory fitness (CRF). The study employed the descriptive correlational design. The census sampling technique included all 190 teaching staff from the two senior high schools in the Dormaa East District. An adapted International Physical Activity Questionnaire (IPAQ) and standardized physical fitness tests were used for data collection. Descriptive statistics of frequency counts and percentages were used to answer the research questions, while inferential statistics of Pearson Product Moment Correlation and the independent sample t-test were used to test hypotheses one and two, respectively. A moderately negative (r = -.156) relationship existed between physical activity participation levels and CRF. Female teachers demonstrated a statistically significant value (p = .045) than males. The study concluded that the reported physical activity levels of the teachers did not reflect their CRF. The implication is that either the participants overestimated their physical activity participation levels or the intensity of the activities was not high enough to affect physiological changes. For the teachers' CRF to improve, it was suggested, among other things, that regular physical activity sessions of the appropriate mixes of FITT be organized.

Keywords: physical activity, participation levels, cardiorespiratory fitness, sedentary lifestyle, teachers

Procedia PDF Downloads 42

Authors: Saurabh Farkya, Govinda Surampudi

Abstract:

Optical Character Recognition is one of the current major research areas. This paper is focussed on recognition of Devanagari script and its sound generation. This Paper consists of two parts. First, Optical Character Recognition of Devnagari handwritten Script. Second, speech synthesis of the recognized text. This paper shows an implementation of support vector machines for the purpose of Devnagari Script recognition. The Support Vector Machines was trained with Multi Domain features; Transform Domain and Spatial Domain or Structural Domain feature. Transform Domain includes the wavelet feature of the character. Structural Domain consists of Distance Profile feature and Gradient feature. The Segmentation of the text document has been done in 3 levels-Line Segmentation, Word Segmentation, and Character Segmentation. The pre-processing of the characters has been done with the help of various Morphological operations-Otsu's Algorithm, Erosion, Dilation, Filtration and Thinning techniques. The Algorithm was tested on the self-prepared database, a collection of various handwriting. Further, Unicode was used to convert recognized Devnagari text into understandable computer document. The document so obtained is an array of codes which was used to generate digitized text and to synthesize Hindi speech. Phonemes from the self-prepared database were used to generate the speech of the scanned document using concatenation technique.

Keywords: Character Recognition (OCR), Text to Speech (TTS), Support Vector Machines (SVM), Library of Support Vector Machines (LIBSVM)

Procedia PDF Downloads 472

Authors: Qaiser Akram, Ahsan Naeem, Hafiz Muhammad Rizwan, Waqas Ahmad, Rubeena Yasmeen

Abstract:

Aspergillus has good secretory potential for phytases. Morphologically and microscopically identified Aspergillus terreus (A. terreus) (n=20) were screened for phytase production and non-toxicity. Phytases produced by non-toxigenic A. terreus under optimum conditions were quantified. Phytases of highest producer A. terreus were evaluated for stability after exposure to temperature (35, 55, 75 and 95ºC) and pH (2, 4, 6 and 8). Effect of metal ions (Fe⁺³, Ba⁺², Ca⁺², Cu⁺², Mg⁺², Mn⁺², K⁺¹ and Na⁺¹) was assessed on phytase activity. Log reduction in phytase activity was calculated. The highest activity units of phytase produced by A. terreus were 271.49 ± 8.14 phytase unit / mL (FTU/ mL). The lowest reduction in phytase activity was 50.20 ± 7.36 (18.5%) and 68.22 ± 10.3 FTU/mL (25.13%) at 35ºC and pH 6, respectively for 15 minutes. The highest reduction 259 ± 0.84 (95.5%) and 211.99 ± 4.39 FTU/mL (78.1%) was recorded at 95ºC for 60 minutes and pH 2.0 for 45 minutes exposure, respectively. All metal ions negatively affected phytase activity. Phytase activity was inhibited minimum (45.32 ± 28.54 FTU/mL, 16.69%) by K⁺¹(1 mM) and maximum (231.48 ± 3.68 FTU/mL, 80.8%) by Cu⁺² (10 mM). It was concluded that A. terreus phytase stability and activity was dependent on physio-chemical factors.

Keywords: stability, phytase, aspergillus terreus, physio-chemical factors and metal ions

Procedia PDF Downloads 259

Authors: Karina Marie G. Nicolas, Kimberly M. Visaya, Emmanuel R. Cauinian

Abstract:

A comparative study on the antihyperglycemic activity of aqueous extracts of Serpentina (Andrographis paniculata) and Papait (Mollugo oppositifolia linn) administered at 400mg/kg body weight per orem twice daily for 14 days was investigated using 24 alloxan-induced diabetic male, 6-8 weeks old ICR mice and Metformin as standard control. The blood glucose levels of all the animals in the treatment groups were not reduced to < 200mg/dl so as to consider them as non-diabetic but Papait showed a consistent blood glucose lowering effect from day 0 to 14 causing 36.07% reduction as compared to Serpentina which was observed to cause a fluctuating effect on blood glucose levels and a reduction of only 22.53% while the Metformin treated animals exhibited the highest reduction at 45.29%. The blood glucose levels at day 14 of animals treated with Papait (322.93 mg/dl) had comparable blood glucose levels (p<0.05) with the Metformin treated groups (284.50 mg/dl). Also, all the animals in the three treatment groups were still hypercholesterolemic with an observed consistent weight loss and a decrease in feed intake except for Serpentina which recorded a slight increase. Results of the study showed a superior antihyperglycemic activity of Papait compared with Serpentina.

Keywords: antihyperglycemic, diabetes, hypercholesterolemic, papait, serpentina

Procedia PDF Downloads 343

Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

Abstract:

Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

Procedia PDF Downloads 110

Authors: Koray U. Erbas

Abstract:

Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

Procedia PDF Downloads 235

Authors: Kanda Wongwailikhit

Abstract:

Copper (I) oxide microparticles with the morphology of cubic and hollow sphere were synthesized with the assistance of a surfactant as the shape controller. Both particles were then subjected to a study of the catalytic activity and the results of shape effects of catalysts on rate of catalytic reaction was observed. The decolorizing reaction of crystal violet and sodium hydroxide was chosen and the decrease of reactant with respect to time was measured using a spectrophotometer. The result revealed that morphology of the crystal had no effect on the catalytic activity for the crystal violet reaction but contributed to total surface area predominantly.

Keywords: copper (I) oxide, catalytic activity, crystal violet

Procedia PDF Downloads 478

Authors: Carlos Vera, Tetyana Baydyk, Ernst Kussul, Graciela Velasco, Miguel Aparicio

Abstract:

This article describes the Random Subspace Neural Classifier (RSC) for the recognition of meteors in the night sky. We used images of meteors entering the atmosphere at night between 8:00 p.m.-5: 00 a.m. The objective of this project is to classify meteor and star images (with stars as the image background). The monitoring of the sky and the classification of meteors are made for future applications by scientists. The image database was collected from different websites. We worked with RGB-type images with dimensions of 220x220 pixels stored in the BitMap Protocol (BMP) format. Subsequent window scanning and processing were carried out for each image. The scan window where the characteristics were extracted had the size of 20x20 pixels with a scanning step size of 10 pixels. Brightness, contrast and contour orientation histograms were used as inputs for the RSC. The RSC worked with two classes and classified into: 1) with meteors and 2) without meteors. Different tests were carried out by varying the number of training cycles and the number of images for training and recognition. The percentage error for the neural classifier was calculated. The results show a good RSC classifier response with 89% correct recognition. The results of these experiments are presented and discussed.

Keywords: contour orientation histogram, meteors, night sky, RSC neural classifier, stars

Procedia PDF Downloads 122

Authors: Dyah Titisari Widyastuti

Abstract:

Rail-station area development that is based on the concept of TOD (Transit Oriented Development) is principally oriented to pedestrian accessibility for daily mobility. The aim of this research is elaborating how far the existing physical elements of a rail-station district could facilitate pedestrian mobility and establish a pedestrian friendly district toward implementation of a TOD concept. This research was conducted through some steps: (i) mapping the rail-station area pedestrian sidewalk and pedestrian network as well as activity nodes and transit nodes, (ii) assessing the level of pedestrian sidewalk connectivity joining trip origin and destination. The research area coverage in this case is limited to walking distance of the rail station (around 500 meters or 10-15 minutes walking). The findings of this research on the current condition of the street and pedestrian sidewalk network and connectivity, show good preference for the foot modal share (more than 50%) is achieved. Nevertheless, it depends on the distance from the trip origin to destination.

Keywords: accessibility of daily mobility, pedestrian-friendly district, rail-station district, transit oriented development

Procedia PDF Downloads 218

Authors: Sidi Ahmed Maouloud, Cheikh Ba

Abstract:

Much of West Africa’s cultural heritage is written in the Al-Soudani Arabic script, which was widely used in West Africa before the time of European colonization. This Al-Soudani Arabic script is an African version of the Maghrebi script, in particular, the Al-Mebssout script. However, the local African qualities were incorporated into the Al-Soudani script in a way that gave it a unique African diversity and character. Despite the existence of several Arabic datasets in Oriental script, allowing for the analysis, layout, and recognition of texts written in these calligraphies, many Arabic scripts and written traditions remain understudied. In this paper, we present a dataset of words from Al-Soudani calligraphy scripts. This dataset consists of 100 images selected from three different manuscripts written in Al-Soudani Arabic script by different copyists. The primary source for this database was the libraries of Boston University and Cambridge University. This dataset highlights the unique characteristics of the Al-Soudani Arabic script as well as the new challenges it presents in terms of automatic word recognition of Arabic manuscripts. An HTR system based on a hybrid ANN (CRNN-CTC) is also proposed to test this dataset. SAMRA is a dataset of annotated Arabic manuscript words in the Al-Soudani script that can help researchers automatically recognize and analyze manuscript words written in this script.

Keywords: dataset, CRNN-CTC, handwritten words recognition, Al-Soudani Arabic script, HTR, manuscripts

Procedia PDF Downloads 89

Authors: Ippei Kamihira, Takashi Nakajima, Taiyo Matsumura, Hikaru Miura, Takashi Ono

Abstract:

In this research, the goal was construction of a system by which multiple sensors were used to observe the daily life behavior of persons living alone (while respecting their privacy). Using this information to judge such conditions as a bad physical condition or falling in the home, etc., so that these abnormal conditions can be made known to relatives and third parties. The daily life patterns of persons living alone are expressed by the number of responses of sensors each time that a set time period has elapsed. By comparing data for the prior two weeks, it was possible to judge a situation as 'normal' when the person was in a good physical condition or as 'abnormal' when the person was in a bad physical condition.

Keywords: sensors, elderly living alone, abnormality detection, iifestyle habit

Procedia PDF Downloads 233

Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

Abstract:

In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, prior distribution and approximate posterior distribution, KTH dataset

Procedia PDF Downloads 329

Authors: Daming Xu, Yuanyuan Wang

Abstract:

Abstract: Under the trend of rapid expansion of urbanization, the motorized urban characteristics become more and more obvious, and the walkability of urban space is seriously affected. The construction of walkability of space, as the main mode of travel for the elderly in their daily lives, has become more and more important in the current social context of serious aging. Settlement is the most basic living unit of residents, and daily shopping, medical care, and other daily trips are closely related to the daily life of the elderly. Therefore, it is of great practical significance to explore the impact of built environment on elderly people's daily walking trips at the settlement level for the construction of pedestrian-friendly settlements for the elderly. The study takes three typical settlements in Harbin Daoli District in three different periods as examples and obtains data on elderly people's walking trips and built environment characteristics through field research, questionnaire distribution, and internet data acquisition. Finally, correlation analysis and multinomial logistic regression model were applied to analyze the influence mechanism of built environment on elderly people's walkability based on the control of personal attribute variables in order to provide reference and guidance for the construction of walkability for elderly people in built environment in the future.

Keywords: built environment, elderly, walkability, multinomial logistic regression model

Procedia PDF Downloads 55

Authors: Vicki R. Voskuil, Jorgie M. Watson

Abstract:

Despite the well-established health benefits of physical activity (PA), most adolescents do not meet guidelines recommending 60 minutes of moderate to vigorous physical activity (MVPA) each day. Adolescent girls engage in less PA than boys, a difference that increases with age. By the 9th grade, only 20% of girls report meeting recommendations for PA with lower percentages for black and Hispanic girls compared to white girls. The purpose of the study was to explore the physical activity (PA) behavior and needs of adolescent girls. Study aims included assessment of adolescent girls’ PA behavior; facilitators of and barriers to PA, PA needs, and acceptability of the Fitbit-Flex 2 activity tracker. This exploratory study used a qualitative and quantitative approach. The qualitative approach involved a focus group using a semi-structured interview technique. PA was measured using the Fitbit-Flex 2 activity tracker. Steps, distance, and active minutes were recorded for one week. A Fitbit survey was also administered to assess acceptability. SPSS Version 22.0 and ATLAS.ti Version 8 were used to analyze data. Girls in the ninth grade were recruited from a high school in the Midwest (n=11). Girls were excluded if they were involved in sports or other organized PA ≥ 3 days per week, had a health condition that prevented or limited PA, or could not read and write English. Participants received a Fitbit-Flex 2 activity tracker to wear for one week. At the end of the week, girls returned the Fitbit and participated in a focus group. Girls responded to open-ended questions regarding their PA behavior and shared their ideas for future intervention efforts aimed at increasing PA among adolescents. Girls completed a survey assessing their perceptions of the Fitbit. Mean age of the girls was 15.3 years (SD=0.44). On average girls took 6,520 steps and walked 2.73 miles each day. Girls stated their favorite types of PA were walking, riding bike, and running. Most girls stated they did PA for 30 minutes or more at a time once a day or every other day. The top 3 facilitators of PA reported by girls were friends, family, and transportation. The top 3 barriers included health issues, lack of motivation, and weather. Top intervention ideas were community service projects, camps, and using a Fitbit activity tracker. Girls felt the best timing of a PA program would be in the summer. Fitbit survey results showed 100% of girls would use a Fitbit on most days if they had one. Ten (91%) girls wore the Fitbit on all days. Seven (64%) girls used the Fitbit app and all reported they liked it. Findings indicate that PA participation for this sample is consistent with previous studies. Adolescent girls are not meeting recommended daily guidelines for PA. Fitbit activity trackers were positively received by all participants and could be used in future interventions aimed at increasing PA for adolescent girls. PA interventions that take place in the summer with friends and include community service projects may increase PA and be well received by this population.

Keywords: adolescents, girls, interventions, physical activity

Procedia PDF Downloads 211

Authors: Ravi J. Shah

Abstract:

The present study deals with the synthesis of novel spiro[azetidine-2, 3’-indole]-2’, 4(1’H)-dione derivative from the reactions of 3-(phenylimino)-1,3-dihydro-2H-indol-2-one derivatives with chloracetyl chloride in presence of triethyl amine (TEA). All the compounds were characterized using IR, 1H NMR, MS and elemental analysis. They were screened for their antibacterial and antifungal activities. Results revealed that, compounds (7a), (7b), (7c), (7d) and (7e) showed very good activity with MIC value of 6.25-12.5 μg/ml against three evaluated bacterial strains and the remaining compounds showed good to moderate activity comparable to standard drugs as antibacterial agents. Compounds (7c) and (7h) displayed equipotent antifungal activity in comparison to standard drugs. Structure-activity relationship study of the compounds showed that the presence of electron withdrawing group substitution at 5’ and 7’ positions of indoline ring and on ortho or para position of phenyl ring increases both antibacterial and antifungal activity of the compound. Henceforth, our findings will have a good impact on chemists and biochemists for further investigations in search of bromine containing spiro fused antimicrobial agents.

Keywords: antibacterial activity, antifungal activity, 2-Azetidinone, indoline

Procedia PDF Downloads 469

Authors: Kritin K. Verma, Bailey Duhon, Patrick W. Slater

Abstract:

Objective: To introduce the possible etiological role that the Labyrinthine Venous Vasculature (LVV) has in venous congestion of the cochlear system in Sudden Sensorineural Hearing Loss (SSNHL) patients. Patients: Two patients (62-year-old female, 50-year-old male) presented within twenty-four hours of onset of SSNHL. Intervention: Following failed conservative and salvage techniques, the patients underwent ablation of the labyrinthine venous vasculature ipsilateral to the side of the loss. Main Outcome Measures: Improvement of sudden SSNHL based on an improvement of pure-tone audiometric (PTA) low-tone scoring averages at 250, 500, and 1000 Hz. Word recognition scoring using the NU-6 word list was used to assess quality of life. Results: Case 1 experienced a 51.7 dB increase in low-tone PTA and an increased word recognition scoring of 90%. Case 2 experienced a 33.4 dB increase in low-tone PTA and 60% increase in word recognition score. No major complications noted. Conclusion: Two patients experienced significant improvement in their low-tone PTA and word recognition scoring following the labyrinthine venous vasculature ablation.

Keywords: case report, sudden sensorineural hearing loss, venous congestion, vascular ablation

Procedia PDF Downloads 116

Authors: Hamza Iftikhar

Abstract:

The research study focuses on the transgender community's gender recognition challenges. It is one of the issues for the transgender community, interacting directly with the difficulties of gender identity and the lives of these people who are facing gender disapproval from society. This study investigates the major flaws of the transgender act. The study's goal is to look into the strange implications of self-perceived identity as a policy tool for transgender recognition. This policy tool jeopardises the rights of Pakistan's indigenous gender-variant people as well as the country's legal and social framework. Qualitative research using semi structured interviews will be carried out. This study proposes developing a scheme for mainstreaming gender-variant people on the basis of the Pakistani Constitution, Supreme Court guidelines, and internationally recognised principles of law. This would necessitate a thorough review of current law using a new approach and reference point.

Keywords: transgender act, self perceived identity, gender variant, policy tool

Procedia PDF Downloads 99

Authors: Kuni Vergauwen, Ivan P. J. Huijnen, Astrid Depuydt, Jasmine Van Regenmortel, Mira Meeus

Abstract:

A lower activity level and imbalanced activity pattern are frequently observed in persons with chronic fatigue syndrome (CFS) / myalgic encephalomyelitis (ME) due to debilitating fatigue and post-exertional malaise (PEM). Identification of measurement instruments to evaluate the activity level and pattern is therefore important. The objective is to identify measurement instruments suited to evaluate the activity level and/or pattern in patients with CFS/ME and review their psychometric properties. A systematic literature search was performed in the electronic databases PubMed and Web of Science until 12 October 2016. Articles including relevant measurement instruments were identified and included for further analysis. The psychometric properties of relevant measurement instruments were extracted from the included articles and rated based on the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist. The review was performed and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A total of 49 articles and 15 unique measurement instruments were found, but only three instruments were evaluated in patients with CFS/ME: the Chronic Fatigue Syndrome-Activity Questionnaire (CFS-AQ), Activity Pattern Interview (API) and International Physical Activity Questionnaire-Short Form (IPAQ-SF), three self-report instruments measuring the physical activity level. The IPAQ-SF, CFS-AQ and API are all equally capable of evaluating the physical activity level, but none of the three measurement instruments are optimal to use. No studies about the psychometric properties of activity monitors in patients with CFS/ME were found, although they are often used as the gold standard to measure the physical activity pattern. More research is needed to evaluate the psychometric properties of existing instruments, including the use of activity monitors.

Keywords: chronic fatigue syndrome, data collection, physical activity, psychometrics

Procedia PDF Downloads 208