Search results for: cognitive image dimension

Authors: Hui-Yi Wang, Shu-Mei Chen, Mei-Fang Liu

Abstract:

Background and purpose: Providing clinical experience in medical education is an important discipline method where students can gradually apply their academic knowledge to clinical situations. The purpose of this study was to establish self-assessment questionnaires for students to assess their learning outcomes for two fields of physical therapy, orthopedic physical therapy, and pediatric physical therapy, in a clinical fieldwork course. Methods: The questionnaires were developed based on the core competence dimensions of the course. The content validity of the questionnaires was evaluated and established by expert meetings. Among the third-year undergraduate students who took the clinical fieldwork course, there were 49 students participated in this study. Teachers arranged for the students to study two professional fields, and each professional field conducted a three-week clinical lesson. The students filled out the self-assessment questionnaires before and after each three-week lesson. Results: The self-assessment questionnaires were established by expert meetings that there were six core competency dimensions in each of the two fields, with 20 and 21 item-questions, respectively. After each three-week clinical fieldwork, the self-rating scores in each core competency dimension were higher when compared to those before the course, indicating having better clinical abilities after the lessons. The best self-rating scores were the dimension of attitude and humanistic literacy, and the two lower scores were the dimensions of professional knowledge and skills and problem-solving critical thinking. Conclusions: This study developed questionnaires for clinical fieldwork courses to reflect students' learning outcomes, including the performance of professional knowledge, practice skills, and professional attitudes. The use of self-assessment of learning performance can help students build up their reflective competencies. Teachers can guide students to pay attention to the performance of abilities in each core dimension to enhance the effectiveness of learning through self-reflection and improvement.

Keywords: physical therapy, clinical fieldwork course, learning outcomes assessment, medical education, self-reflection ability

Procedia PDF Downloads 116

Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

Abstract:

The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

Procedia PDF Downloads 429

Authors: J. A. Abiona, O. O. Fabinu, O. O. Ehimiyein, A. O. Ladokun, M. O. Abioja, J. O. Daramola, O. E. Oke, O. A. Osinowo, O. M. Onagbesan

Abstract:

A study was conducted on the effect of Moringa oleifera on liveweight and reproductive tract dimension of Giant African Land Snail (Archachatina marginata). Thirty two snails (32) with weight range of 100 – 150 g were used for this study. Eight snails (8) were subjected to each of the four treatments which were: Concentrate only, concentrate + 100g of Moringa oleifera, concentrate + 200g of Moringa oleifera and concentrate + 300g of Moringa oleifera. Parameters monitored were: Shell length, shell width, shell circumference and weekly live weight. Reproductive tract dimension taken include: Organ weight (ORGWT), reproductive tract weight (REPTWT), reproductive tract length (REPTLNT), ovo-tesis weight (OVOWT), edible part weight (EDPTWT), albumen weight (ALBWT) and albumen length (ALBLNT). Shell dimensions and the live weight were measured and recorded on a weekly basis with a tape rule and a sensitive weighing scale. After nine weeks, six snails were randomly selected from each treatment and dissected. Their reproductive tracts were removed and dimensions were taken. The result showed that ORGWT, OVOWT, ALBWT, ALBLNT, REPTLNT and REPTWT were not significantly affected (P>0.05) by different levels of Moringa oleifera inclusions with concentrate. However, Moringa oleifera inclusion with concentrate at different levels had significant effect (P<0.001) on Live weight, shell length and shell diameters of the animal. Snails given 300 g of Moringa oleifera per kilogramme of concentrate gave the highest live weight and shell length together with shell diameter. It was however recommended from this study that inclusion of Moringa oleifera leave meal into snail feed at 300 g per kg of concentrate would enhance live weight and shell parameters (length and width).

Keywords: reproductive tract, giant African land snails, Moringa oleifera, live weight, shell dimension

Procedia PDF Downloads 485

Authors: Nicholas V. Scott, Jack McCarthy

Abstract:

Military, law enforcement, and counter terrorism organizations are often tasked with target detection and image characterization of scenes containing explosive materials in various types of environments where light scattering intensity is high. Mitigation of this photonic noise using classical digital filtration and signal processing can be difficult. This is partially due to the lack of robust image processing methods for photonic noise removal, which strongly influence high resolution target detection and machine learning-based pattern recognition. Such analysis is crucial to the delivery of reliable intelligence. Polarization filters are a possible method for ambient glare reduction by allowing only certain modes of the electromagnetic field to be captured, providing strong scene contrast. An experiment was carried out utilizing a polarization lens attached to a hyperspectral imagery camera for the purpose of exploring the degree to which an imaged polarized scene of potassium, phosphorus, and nitrogen mixture allows for improved target detection and image segmentation. Preliminary imagery results based on the application of machine learning algorithms, including competitive leaky learning and distance metric analysis, to polarized hyperspectral imagery, suggest that polarization filters provide a slight advantage in image segmentation. The results of this work have implications for understanding the presence of explosive material in dry, desert areas where reflective glare is a significant impediment to scene characterization.

Keywords: explosive material, hyperspectral imagery, image segmentation, machine learning, polarization

Procedia PDF Downloads 142

Authors: Lara Bruno, Ilaria Tipà, Franco Delogu

Abstract:

Simultaneous interpreting (SI) is a demanding language task which includes the contemporary activation of different cognitive processes. This complex activity requires interpreters not only to be proficient in their working languages; but also to have a great ability in focusing attention and controlling anxiety during their performance. Effects of Qigong meditation techniques have a positive impact on several cognitive functions, including attention and anxiety control. This study aims at exploring the influence of Qigong meditation on the quality of simultaneous interpreting. 20 interpreting students, divided into two groups, were trained for 8 days in Qigong meditation practice. Before and after training, a brief simultaneous interpreting task was performed. Language combinations of group A and group B were respectively English-Italian and Chinese-Italian. Students’ performances were recorded and rated by independent evaluators. Assessments were based on 12 different parameters, divided into 4 macro-categories: content, form, delivery and anxiety control. To determine if there was any significant variation between the pre-training and post-training SI performance, ANOVA analyses were conducted on the ratings provided by the independent evaluators. Main results indicate a significant improvement of the interpreting performance after the meditation training intervention for both groups. However, group A registered a higher improvement compared to Group B. Nonetheless, positive effects of meditation have been found in all the observed macro-categories. Meditation was not only beneficial for speech delivery and anxiety control but also for cognitive and attention abilities. From a cognitive and pedagogical point of view, present results open new paths of research on the practice of meditation as a tool to improve SI performances.

Keywords: cognitive science, interpreting studies, Qigong meditation, simultaneous interpreting, training

Procedia PDF Downloads 160

Authors: Elham Azimzadeh, Fahimeh Khorshidi, Alireza Farsi

Abstract:

Balance impairment and fear of falling in older adults may reduce their quality of life. Reactive balance training could improve rapid postural responses and fall prevention in the elderly during daily tasks. Performing postural training and simultaneously cognitive dual tasks could be similar to the daily circumstances. Purpose: This study aimed to determine the effect of balance training on stable and unstable surfaces under dual cognitive task conditions on postural control and fear of falling in the elderly. Methods: Thirty non-fallers of older adults (65-75 years) were randomly assigned to two training groups: stable-surface (n=10), unstable-surface (n=10), or a control group (n=10). The intervention groups underwent six weeks of balance training either on a stable (balance board) or an unstable (wobble board) surface while performing a cognitive dual task. The control group received no balance intervention. COP displacements in the anterioposterior (AP) and mediolateral (ML) directions using a computerized balance board, functional balance using TUG, and fear of falling using FES-I were measured in all participants before and after the interventions. Summary of Results: Mixed ANOVA (3 groups * 2 times) with repeated measures and post hoc test showed a significant improvement in both intervention groups in AP index (F= 11/652, P= 0/0002) and functional balance (F= 9/961, P= 0/0001). However, the unstable surface training group had more improvement. However, the fear of falling significantly improved after training on an unstable surface (p= 0/035). All groups had no significant improvement in the ML index (p= 0/817). In the present study, there was an improvement in the AP index after balance training. Conclusion: Unstable surface training may reduce reaction time in posterior ankle muscle activity. Furthermore, focusing attention on cognitive tasks can lead to maintaining balance unconsciously. Most of the daily activities need attention distribution among several activities. So, balance training concurrent to a dual cognitive task is challenging and more similar to the real world. According to the specificity of the training principle, it may improve functional independence and fall prevention in the elderly.

Keywords: cognitive dual task, elderly, fear of falling, postural control, unstable surface

Procedia PDF Downloads 63

Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

Abstract:

Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: texture classification, texture descriptor, SIFT, SURF, ORB

Procedia PDF Downloads 371

Authors: Purnima K Bajre, Rujula Talloo

Abstract:

A variety of vehicles are driven on roads such as private vehicles, commercial vehicles, public vehicles, and emergency service vehicles (EMV). Drivers driving different vehicles can have attitude differences towards emergency service vehicles which in turn affects their likelihood to give way to them. The present review aims to understand the factors that mediate this yielding behavior of drivers towards EMVs. Through extensive review of available literature, factors such as effects of lights and sirens, cognitive load, age of the driver, driving general experience, traffic load, drivers’ experience and training with EMVs and drivers’ attitude towards EMV drivers, have emerged as mediating factors. Whereas cognitive load is the most researched area and is observed to be associated negatively with on road drivers’ attitudes towards EMVs, there is a paucity of research to understand the relationships between empathy, pro-social skills, and on road drivers’ attitude towards EMVs.

Keywords: cognitive load, emergency service vehicle, empathy, traffic load

Procedia PDF Downloads 34

Authors: M. G. R. S. Perera, B. S. Weerakoon, L. P. G. Sherminie, M. L. Jayatilake, R. D. Jayasinghe, W. Huang

Abstract:

The aim of this study was to measure and evaluate the Longitudinal Relaxation Times (T1) in bone marrow of an Acute Myeloid Leukaemia (AML) patient in order to explore the potential for a prognostic biomarker using Magnetic Resonance Imaging (MRI) which will be a non-invasive prognostic approach to AML. MR image data were collected in the DICOM format and MATLAB Simulink software was used in the image processing and data analysis. For quantitative MRI data analysis, Region of Interests (ROI) on multiple image slices were drawn encompassing vertebral bodies of L3, L4, and L5. T1 was evaluated using the T1 maps obtained. The estimated bone marrow mean value of T1 was 790.1 (ms) at 3T. However, the reported T1 value of healthy subjects is significantly (946.0 ms) higher than the present finding. This suggests that the T1 for bone marrow can be considered as a potential prognostic biomarker for AML patients.

Keywords: acute myeloid leukaemia, longitudinal relaxation time, magnetic resonance imaging, prognostic biomarker.

Procedia PDF Downloads 531

Authors: Khelifi Mustapha, A. Moulay lakhdar, I. Elawady

Abstract:

We will study the unequal error protection for VQ image. We have used the Reed Solomon (RS) Codes as Channel coding because they offer better performance in terms of channel error correction over a binary output channel. One such channel (binary input and output) should be considered if it is the case of the application layer, because it includes all the features of the layers located below and on the what it is usually not feasible to make changes.

Keywords: vector quantization, channel error correction, Reed-Solomon channel coding, application

Procedia PDF Downloads 365

Authors: John Paul Q. Tomas, Mark Wilson L. de los Reyes, Kirsten Joyce P. Vasquez

Abstract:

The most frequent type of fracture is a wrist fracture, which often makes it difficult for medical professionals to find and locate. In this study, fractures in wrist x-ray pictures were located and identified using deep learning and computer vision. The researchers used image filtering, masking, morphological operations, and data augmentation for the image preprocessing and trained the RetinaNet and Faster R-CNN models with ResNet50 backbones and Adam optimizers separately for each image filtering technique and projection. The RetinaNet model with Anisotropic Diffusion Smoothing filter trained with 50 epochs has obtained the greatest accuracy of 99.14%, precision of 100%, sensitivity/recall of 98.41%, specificity of 100%, and an IoU score of 56.44% for the Posteroanterior projection utilizing augmented data. For the Lateral projection using augmented data, the RetinaNet model with an Anisotropic Diffusion filter trained with 50 epochs has produced the highest accuracy of 98.40%, precision of 98.36%, sensitivity/recall of 98.36%, specificity of 98.43%, and an IoU score of 58.69%. When comparing the test results of the different individual projections, models, and image filtering techniques, the Anisotropic Diffusion filter trained with 50 epochs has produced the best classification and regression scores for both projections.

Keywords: Artificial Intelligence, Computer Vision, Wrist Fracture, Deep Learning

Procedia PDF Downloads 74

Authors: A. Buruzs, M. F. Hatwágner, L. T. Kóczy

Abstract:

The aim of the present paper is to develop an integrated method that may provide assistance to decision makers during system planning, design, operation and evaluation. In order to support the realization of Circular Economy (CE), it is essential to evaluate local needs and conditions which help to select the most appropriate system components and resource needs. Each of these activities requires careful planning, however, the model of CE offers a comprehensive interdisciplinary framework. The aim of this research was to develop and to introduce a practical methodology for evaluation of local and regional opportunities to promote CE.

Keywords: circular economy, factors, fuzzy cognitive map, model reduction, sustainability

Procedia PDF Downloads 246

Authors: Teja Sai Puligadda

Abstract:

Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

Procedia PDF Downloads 161

Authors: Hind Hassan Arruwaite

Abstract:

Conceptual metaphor is a cognitive semantic tool that provides access to people's conceptual systems. The correlation in the human conceptual system surpasses limited time and specific cultures. The universal associations provide universal schemas that organize people's conceptualization of the world. The study aims to explore how the cultural associations used in conceptual metaphors create commonalities and harmony between people of the world. In the research methodology, the researcher implemented Critical Metaphor Analysis, Metaphor Candidate Identification and Metaphor Identification Procedure models to deliver qualitative and descriptive findings. The semantic tension was the key criterion in identifying metaphorically used words in the headlines. The research materials are the oil trade conceptual metaphors used in the headlines of Arab News and Saudi Gazette Newspapers. The data will be uploaded to the self-constructed corpus to examine electronic lists for identifying conceptual metaphors. The study investigates the types of conceptual metaphors used in the headlines of the newspapers, the cultural associations identified in the conceptual metaphors, and whether the identified cultural associations in conceptual metaphors create universal conceptual schemas. The study aligned with previous seminal works on conceptual metaphor theory in emphasizing the distinctive power of conceptual metaphors in exposing the cultural associations that unify people's perceptions. The correlation of people conceptualization provides universal schemas that involve elements of human sensorimotor experiences. The study contributes to exposing the shared cultural associations that ensure the commonality of all humankind's thinking mechanism.

Keywords: critical discourse analysis, critical metaphor analysis, conceptual metaphor theory, primary and specific metaphors, corpus-driven approach, universal associations, image schema, sensorimotor experience, oil trade

Procedia PDF Downloads 204

Authors: Zihan Geng, L. Quentin Dixon

Abstract:

It has been proposed that early bilingual experience confers a number of advantages in the development of executive control mechanisms. Although the literature provides empirical evidence for bilingual benefits, some studies also reported null or mixed results. To make sense of these contradictory findings, the current review synthesize recent empirical studies investigating bilingual effects on children’s executive function and attention control. The publication time of the studies included in the review ranges from 2010 to 2017. The key searching terms are bilingual, bilingualism, children, executive control, executive function, and attention. The key terms were combined within each of the following databases: ERIC (EBSCO), Education Source, PsycINFO, and Social Science Citation Index. Studies involving both children and adults were also included but the analysis was based on the data generated only by the children group. The initial search yielded 137 distinct articles. Twenty-eight studies from 27 articles with a total of 3367 participants were finally included based on the selection criteria. The selective studies were then coded in terms of (a) the setting (i.e., the country where the data was collected), (b) the participants (i.e., age and languages), (c) sample size (i.e., the number of children in each group), (d) cognitive outcomes measured, (e) data collection instruments (i.e., cognitive tasks and tests), and (f) statistic analysis models (e.g., t-test, ANOVA). The results show that the majority of the studies were undertaken in western countries, mainly in the U.S., Canada, and the UK. A variety of languages such as Arabic, French, Dutch, Welsh, German, Spanish, Korean, and Cantonese were involved. In relation to cognitive outcomes, the studies examined children’s overall planning and problem-solving abilities, inhibition, cognitive complexity, working memory (WM), and sustained and selective attention. The results indicate that though bilingualism is associated with several cognitive benefits, the advantages seem to be weak, at least, for children. Additionally, the nature of the cognitive measures was found to greatly moderate the results. No significant differences are observed between bilinguals and monolinguals in overall planning and problem-solving ability, indicating that there is no bilingual benefit in the cooperation of executive function components at an early age. In terms of inhibition, the mixed results suggest that bilingual children, especially young children, may have better conceptual inhibition measured in conflict tasks, but not better response inhibition measured by delay tasks. Further, bilingual children showed better inhibitory control to bivalent displays, which resembles the process of maintaining two language systems. The null results were obtained for both cognitive complexity and WM, suggesting no bilingual advantage in these two cognitive components. Finally, findings on children’s attention system associate bilingualism with heightened attention control. Together, these findings support the hypothesis of cognitive benefits for bilingual children. Nevertheless, whether these advantages are observable appears to highly depend on the cognitive assessments. Therefore, future research should be more specific about the cognitive outcomes (e.g., the type of inhibition) and should report the validity of the cognitive measures consistently.

Keywords: attention, bilingual advantage, children, executive function

Procedia PDF Downloads 185

Authors: Despoina Christodoulopoulou

Abstract:

The current research study investigated how connection with Korean celebrities may impact Greek and South Korean young adults’ body image perception given Korea’s distinct appearance norms. The study employed a qualitative methodology and semi-structured interviews were used for the gathering of data. Greek participants resided in Thessaloniki, Greece, whereas South Korean participants lived in Gwangju, South Korea. The study was approved by The American College of Thessaloniki’s (ACT) Institutional Review Board. Face-to-face interviews were conducted with the Greek sample, and online interviews with the South Korean sample. Thematic analysis was utilized to determine the findings. Findings illustrated that a close bond with Korean celebrities can impact participants’ body image perception. The Greek sample’s body image was positively influenced by their connection with Korean celebrities, whereas Korean sample’s was negatively influenced. Such distinction is due to celebrities’ nationality and their adherence to culturally acceptable standards of slimness, muscularity and facial appeal. It also appeared that Korean male celebrities promote body positivity more than their female counterparts. Findings showed that Korean culture appearance norms constitute a risk factor influencing Korean young adults’ body dissatisfaction. Thus, Korean mental health professionals might be informed from this paper on preserving Korea’s youth mental health.

Keywords: parasocial relationships, celebrity worship, Korean wave, body image concerns, body dissatisfaction, Greek young adults, South Korean young adults

Procedia PDF Downloads 6

Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

Abstract:

Recently, an increasing number of researchers have been focusing on working out realistic solutions to sustainability problems. As sustainability issues gain higher importance for organisations, the management of such decisions becomes critical. Knowledge representation is a fundamental issue of complex knowledge based systems. Many types of sustainability problems would benefit from models based on experts’ knowledge. Cognitive maps have been used for analyzing and aiding decision making. A cognitive map can be made of almost any system or problem. A fuzzy cognitive map (FCM) can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behavior of any system. Integrated waste management systems (IWMS) are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall decision process of the system. The goal of the present paper is to construct an efficient IWMS which considers various factors. The authors’ intention is to propose an expert based system design approach for implementing expert decision support in the area of IWMSs and introduces an appropriate methodology for the development and analysis of group FCM. A framework for such a methodology consisting of the development and application phases is presented.

Keywords: factors, fuzzy cognitive map, group decision, integrated waste management system

Procedia PDF Downloads 277

Authors: Misha Alexander, S. B. Waykar

Abstract:

Visual Cryptography is a special unbreakable encryption technique that transforms the secret image into random noisy pixels. These shares are transmitted over the network and because of its noisy texture it attracts the hackers. To address this issue a Natural Visual Secret Sharing Scheme (NVSS) was introduced that uses natural shares either in digital or printed form to generate the noisy secret share. This scheme greatly reduces the transmission risk but causes distortion in the retrieved secret image through variation in settings and properties of digital devices used to capture the natural image during encryption / decryption phase. This paper proposes a new NVSS scheme that extracts the secret key from randomly selected unaltered multiple natural images. To further improve the security of the shares data hiding techniques such as Steganography and Alpha channel watermarking are proposed.

Keywords: decryption, encryption, natural visual secret sharing, natural images, noisy share, pixel swapping

Procedia PDF Downloads 407

Authors: Salah Eddine Ben Fadhel

Abstract:

Lev Vygotsky (1896–1934) was one of the most significant psychologists of the twentieth century despite his short life. His cultural-historical theory is still inspiring many researchers today. At the same time, we observe in many studies a lack of understanding of his thoughts. Vygotsky poses in this theory the contribution of society to individual development and learning. Thus, it suggests that human learning is largely a social and cultural process, further mentioning the influence of interactions between people and the culture in which they live. In this presentation, we highlight, on the one hand, the strong points of the theory by highlighting the major questions it raises and its contribution to developmental psychology in general. On the other hand, we will demonstrate what Vygotsky's theory brings today to the understanding of the cognitive development of children and adolescents. The major objective is to better understand the cognitive mechanisms involved in the learning process in children and adolescents and, therefore, demonstrate the complex nature of psychological development. The main contribution is to provide conceptual insight, which allows us to better understand the importance of the theory and its major pedagogical implications.

Keywords: vygotsky, society, culture, history

Procedia PDF Downloads 66

Authors: Marawan Abd Elbaset Mohamed, Hanan A. Ogaly, Rehab F. Abdel-Rahman, Ahmed-Farid O.A., Marwa S. Khattab, Reham M. Abd-Elsalam

Abstract:

Liver fibrosis is a severe worldwide health concern due to various chronic liver disorders. Hepatic encephalopathy (HE) is one of its most common complications affecting liver and brain cognitive function. Beta-Carotene (B-Car) is an organic, strongly colored red-orange pigment abundant in fungi, plants, and fruits. The study attempted to know B-Car neuroprotective potential against thioacetamide (TAA)-induced neurotoxicity and cognitive decline in HE in rats. Hepatic encephalopathy was induced by TAA (100 mg/kg, i.p.) three times per week for two weeks. B-Car was given orally (10 or 20 mg/kg) daily for two weeks after TAA injections. Organ body weight ratio, Serum transaminase activities, liver’s antioxidant parameters, ammonia, and liver histopathology were assessed. Also, the brain’s mitogen-activated protein kinase (MAPK), nuclear factor kappa B (NF-κB), antioxidant parameters, adenosine triphosphate (ATP), adenosine monophosphate (AMP), norepinephrine (NE), dopamine (DA), serotonin (5-HT), 5-hydroxyindoleacetic acid (5-HIAA) cAMP response element-binding protein (CREB) expression and B-cell lymphoma 2 (Bcl-2) expression were measured. The brain’s cognitive functions (Spontaneous locomotor activity, Rotarod performance test, Object recognition test) were assessed. B-Car prevented alteration of the brain’s cognitive function in a dose-dependent manner. The histopathological outcomes supported these biochemical evidences. Based on these results, it could be established that B-Car could be assigned to treat the brain’s neurotoxicity consequences of HE via downregualtion of MAPK/NF-κB signaling pathways.

Keywords: beta-carotene, liver injury, MAPK, NF-κB, rat, thioacetamide

Procedia PDF Downloads 154

Authors: Durjoy Lahiri, Vishal Madhukar Sawale, Ashwani Bhat, Souvik Dubey, Gautam Das, Biman Kanti Roy, Suparna Chatterjee, Goutam Gangopadhyay

Abstract:

Crossed aphasia has been an area of considerable interest for cognitive researchers as it offers a fascinating insight into cerebral lateralization for language function. We conducted an observational study in the stroke unit of a tertiary care neurology teaching hospital in eastern India on subjects with crossed aphasia over a period of four years. During the study period, we detected twelve cases of crossed aphasia in strongly right-handed patients, caused by ischemic stroke. The age, gender, vernacular language and educational status of the patients were noted. Aphasia type and severity were assessed using Bengali version of Western Aphasia Battery (validated). Computed tomography, magnetic resonance imaging and angiography were used to evaluate the location and extent of the ischemic lesion in brain. Our series of 12 cases of crossed aphasia included 7 male and 5 female with mean age being 58.6 years. Eight patients were found to have Broca’s aphasia, 3 had trans-cortical motor aphasia and 1 patient suffered from global aphasia. Nine patients were having very severe aphasia and 3 suffered from mild aphasia. Mirror-image type of crossed aphasia was found in 3 patients, whereas 9 had anomalous variety. In our study crossed aphasia was found to be more frequent in males. Anomalous pattern was more common than mirror-image. Majority of the patients had motor-type aphasia and no patient was found to have pure comprehension deficit. We hypothesize that in Bengali-speaking right-handed population, lexical-semantic system of the language network remains loyal to the left hemisphere even if the phonological output system is anomalously located in the right hemisphere.

Keywords: aphasia, crossed, lateralization, language function, vascular

Procedia PDF Downloads 192

Authors: Ankur Dixit, Hiroaki Wagatsuma

Abstract:

The crack detection on a concrete bridge is an important and constant task in civil engineering. Chronically, humans are checking the bridge for inspection of cracks to maintain the quality and reliability of bridge. But this process is very long and costly. To overcome such limitations, we have used a drone with a digital camera, which took some images of bridge deck and these images are processed by morphological component analysis (MCA). MCA technique is a very strong application of sparse coding and it explores the possibility of separation of images. In this paper, MCA has been used to decompose the image into coarse and fine components with the effectiveness of two dictionaries namely anisotropic diffusion and wavelet transform. An anisotropic diffusion is an adaptive smoothing process used to adjust diffusion coefficient by finding gray level and gradient as features. These cracks in image are enhanced by subtracting the diffused coarse image into the original image and the results are treated by Sobel edge detector and binary filtering to exhibit the cracks in a fine way. Our results demonstrated that proposed MCA framework using anisotropic diffusion followed by Sobel operator and binary filtering may contribute to an automation of crack detection even in open field sever conditions such as bridge decks.

Keywords: anisotropic diffusion, coarse component, fine component, MCA, Sobel edge detector and wavelet transform

Procedia PDF Downloads 175

Authors: Ching-Yi Huang, Pi-Fen Cheng, Hui-Zhu Chen, Shi Ting Huang, Heng-Hua Wang

Abstract:

This is a case of oral cancer after extensive resection and modified right lateral neck lymph node dissection followed by reconstruction with a skin flap. The nursing period lasted From September 25 to October 3, 2017, through observation, interview, physical assessment, and medical record review, the author identified the following nursing problems: acute pain, impaired oral mucous membrane, and body image change. During the nursing period, the author provided individual and overall nursing care and established mutual trust through the use of empathy. Author listened and eased the patient's physical indisposition, such as wound pain, we use medications and acupuncture massage to relieve pain. However, for oral mucosa change caused by surgery, provide continuous and complete oral care and oral exercise training to improve oral mucosal healing and restore swallowing function. In the body-image changes, guided him to express his feeling after the body-image change, and enhanced support and from the family, and encouraged him to attend head and neck cancer survivor alliance which allowed the patient to accept the altered body image and reaffirm self-worth. Hopefully, through sharing this nursing experience will help to the nursing care quality of nursing care for oral cancer patients after extensive resection and modified right lateral neck lymph node dissection followed by reconstruction with a skin flap.

Keywords: oral cancer, acute pain, impaired oral mucous membrane, body image change

Procedia PDF Downloads 188

Authors: Hamza A. Al-Sewadi, Akram N. A. Aldakari

Abstract:

Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods, and hence, it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted in embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods), and a fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.

Keywords: steganography, watermarking, time complexity measurements, private keys

Procedia PDF Downloads 144

Authors: David Jurado, Carlos Ávila

Abstract:

Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

Procedia PDF Downloads 84

Authors: Syeda Shawana Mahasan, Muhammad Farooq Akhtar

Abstract:

The objective of this study is to analyze the influence of the green marketing mix strategy and corporate social responsibility (CSR) on the performance of an organization, taking into account the mediating effect of corporate image. The impact of frugal innovation and corporate activism is being examined. The data was gathered from executives at various levels of management, including top, middle, and lower-level managers, from a total of 550 manufacturing enterprises of different sizes, ranging from small to medium to large. The collected replies are processed and analyzed using SMART PLS version 4.0.0.0. The application of PLS-SEM demonstrates that the green marketing mix strategy and corporate social responsibility have a significant impact on organizational performance. Therefore, it is imperative for organizations to effectively adopt environmentally sustainable and socially conscious methods within their operations. The results indicate that the corporate image has a key role in mediating the relationship between the green marketing mix strategy, corporate social responsibility, and organizational performance. This demonstrates the imperative for organizations to actively enhance their favorable reputation among stakeholders. The combination of frugal innovation and corporate activism enhances the connection between corporate image and organizational performance. The current study assists managers in recognizing the significance of these particular constructs in maintaining the long-term performance of the organization.

Keywords: green marketing mix strategy, CSR, corporate image, organizational performance, frugal innovation, corporate activism

Procedia PDF Downloads 41

Authors: M. A. Barros, M. V. Barros

Abstract:

The aim of this work is to analyze the discursive dynamics of preservice teachers during the implementation of a didactic sequence on topics of Quantum Mechanics for High School. Our research methodology was qualitative, case study type, in which we selected two prospective teachers on the Physics Teacher Training Course of the Sao Carlos Institute of Physics, at the University of Sao Paulo/Brazil. The set of modes of communication analyzed were the intentions and interventions of the teachers, the established communicative approach, the patterns and the contents of the interactions between teachers and students. Data were collected through video recording, interviews and questionnaires conducted before and after an 8 hour mini-course, which was offered to a group of 20 secondary students. As teaching strategy we used an active learning methodology, called: Peer Instruction. The episodes pointed out that both future teachers used interactive dialogic and authoritative communicative approaches to mediate the discussion between peers. In the interactive dialogic dimension the communication pattern was predominantly I-R-F (initiation-response-feedback), in which the future teachers assisted the students in the discussion by providing feedback to their initiations and contributing to the progress of the discussions between peers. Although the interactive dialogic dimension has been preferential during the use of the Peer Instruction method the authoritative communicative approach was also employed. In the authoritative dimension, future teachers used predominantly the type I-R-E (initiation-response-evaluation) communication pattern by asking the students several questions and leading them to the correct answer. Among the main implications the work contributes to the improvement of the practices of future teachers involved in applying active learning methodologies in classroom by identifying the types of communicative approaches and communication patterns used, as well as researches on curriculum innovation in physics in high school.

Keywords: curricular innovation, high school, physics teaching, discursive dynamics

Procedia PDF Downloads 183

Authors: Kumar Kanudkuri, A. Sandhya

Abstract:

Typically, in a MRI clinical setting, there are several protocols run, each indicated for a specific anatomy and disease condition. However, these protocols or parameters within them can change over time due to changes to the recommendations by the physician groups or updates in the software or by the availability of new technologies. Most of the time, the changes are performed by the MRI technologist to account for either time, coverage, physiological, or Specific Absorbtion Rate (SAR ) reasons. However, giving properly guidelines to MRI technologist is important so that they do not change the parameters that negatively impact the image quality. Typically a standard American College of Radiology (ACR) MRI phantom is used for Quality Control (QC) in order to guarantee that the primary objectives of MRI are met. The visual evaluation of quality depends on the operator/reviewer and might change amongst operators as well as for the same operator at various times. Therefore, overcoming these constraints is essential for a more impartial evaluation of quality. This makes quantitative estimation of image quality (IQ) metrics for MRI quality control is very important. So in order to solve this problem, we proposed that there is a need for a robust, open-source, and automated MRI image control tool. The Designed and developed an automatic analysis tool for measuring MRI image quality (IQ) metrics like Signal to Noise Ratio (SNR), Signal to Noise Ratio Uniformity (SNRU), Visual Information Fidelity (VIF), Feature Similarity (FSIM), Gray level co-occurrence matrix (GLCM), slice thickness accuracy, slice position accuracy, High contrast spatial resolution) provided good accuracy assessment. A standardized quality report has generated that incorporates metrics that impact diagnostic quality.

Keywords: ACR MRI phantom, MRI image quality metrics, SNRU, VIF, FSIM, GLCM, slice thickness accuracy, slice position accuracy

Procedia PDF Downloads 173

Authors: Adilla Anggraeni

Abstract:

The purpose of the paper is to investigate the effects of religiosity and subjective knowledge towards initial trust that a consumer has towards a product manufacturer. Since globalization enters the point of no return, it should be acknowledged that further exploration of country of origin image, its influences and possible limiting factors is imperative. This model aims to broaden COO-related research, especially related to different product categories based on the perception of consumers in emerging markets. The study employs quantitative method, aiming to involve 200 Indonesian respondents to evaluate different product categories (food/apparel). Relationships between variables are evaluated using structural equation modeling. It is expected that subjective knowledge will have significant influence towards initial trust that an individual possesses towards food products. A major contribution of this study will be the inclusion of religiosity and subjective knowledge in the country of origin study’s body of knowledge. Companies are also expected to benefit from the study as the acceleration of globalization may again repose the question of whether companies should market their product using similar strategies across different countries or different ones. Religiosity dimension is expected to add values to international marketing literature concerning emerging economies in particular, as many companies view the emerging economies as promising markets.

Keywords: country of origin, subjective knowledge, initial trust, emerging economy, Indonesia

Procedia PDF Downloads 290

Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

Abstract:

Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

Procedia PDF Downloads 141