Search results for: style classification

Authors: Da Tao, Tieyan Wang, Mingfu Qin

Abstract:

While social robots have been increasingly developed and rapidly applied in our daily life, how robots should interact with humans is still an urgent problem to be explored. Appropriate use of interactive behavior is likely to create a good user experience in human-robot interaction situations, which in turn can improve people’s acceptance of robots. This paper aimed to systematically and quantitatively examine the effects of several important situational factors (i.e., interaction distance, interaction posture, and feedback style) on user experience during human-robot interaction. A three-factor mixed designed experiment was adopted in this study, where subjects were asked to interact with a social robot in different interaction situations by combinations of varied interaction distance, interaction posture, and feedback style. A set of data on users’ behavioral performance, subjective perceptions, and eye movement measures were tracked and collected, and analyzed by repeated measures analysis of variance. The results showed that the three situational factors showed no effects on behavioral performance in tasks during human-robot interaction. Interaction distance and feedback style yielded significant main effects and interaction effects on the proportion of fixation times. The proportion of fixation times on the robot is higher for negative feedback compared with positive feedback style. While the proportion of fixation times on the robot generally decreased with the increase of the interaction distance, it decreased more under the positive feedback style than under the negative feedback style. In addition, there were significant interaction effects on pupil diameter between interaction distance and posture. As interaction distance increased, mean pupil diameter became smaller in side interaction, while it became larger in frontal interaction. Moreover, the three situation factors had significant interaction effects on user acceptance of the interaction mode. The findings are helpful in the underlying mechanism of user experience in human-robot interaction situations and provide important implications for the design of robot behavioral expression and for optimal strategies to improve user experience during human-robot interaction.

Keywords: social robots, human-robot interaction, interaction posture, interaction distance, feedback style, user experience

Procedia PDF Downloads 93

Authors: Antonietta Maoloni, Federica Cardinali, Vesna Milanović, Andrea Osimani, Ilario Ferrocino, Maria Rita Corvaglia, Luca Cocolin, Lucia Aquilanti

Abstract:

Table olives (Olea europaea L.) are among the most important fermented vegetables all over the world, while sea fennel (Crithmum maritimum L.) is an emerging food crop with interesting nutritional and sensory traits. Both of them are characterized by the presence of several bioactive compounds with potential beneficial health effects, thus representing two valuable substrates for the manufacture of innovative vegetable-based preserves. Given these premises, the present study was aimed at exploring the co-fermentation of table olives and sea fennel to produce new high-value preserves. Spanish style or Greek style processing method and the use of a multiple strain starter were explored. The preserves were evaluated for their microbial dynamics and key sensory traits. During the fermentation, a progressive pH reduction was observed. Mesophilic lactobacilli, mesophilic lactococci, and yeasts were the main microbial groups at the end of the fermentation, whereas Enterobacteriaceae decreased during fermentation. An evolution of the microbiota was revealed by metataxonomic analysis, with Lactiplantibacillus plantarum dominating in the late stage of fermentation, irrespective of processing method and use of the starter. Greek style preserves resulted in more crunchy and less fibrous than Spanish style one and were preferred by trained panelists.

Keywords: lactic acid bacteria, Lactiplantibacillus plantarum, metataxonomy, panel test, rock samphire

Procedia PDF Downloads 101

Authors: Rika Uchida

Abstract:

Claude Debussy's piano works can be divided into three categories in terms of style characteristics. The first category includes works which are strongly impressionistic, evoking a mood or an atmosphere, rather than making a direct, clear statement. These works often depict nature, and they are descriptive and sensitive in their character. Harmonic vocabulary is often complex, and the sense of tonality is often ambiguous in those works. Examples which belong to this category are ‘Clair de lune’ from Suite Bergamasque, Deux Arabesques, and ‘Reflets dans l'eau’ from Images Book 2. The second category shows little or no trace of impressionism. Works are not descriptive; rather, they are classical or absolute. Examples which belong to this category are Pour le Piano, ‘Hommage à Rameau’ and ‘Movement’ from Images Book 1 and Etudes. The third category can be called exotic. Debussy had a great interest in foreign lands such as the Far and Near East, and Spain. He employs pentatonic and quartal harmonies to describe the Orient, occasionally using the effect of the Javanese gamelan, which impressed him at the Paris Exhibition. His compositions in the Spanish style evoke the atmosphere of Spain. Though he borrowed some techniques from Spanish composers whom he knew, the tonal experimentation which occurs in these works sets them apart. Examples which belong to this category are ‘Pagodes’ and ‘la Soiree dans Grenade’ from Estampes, ‘la Puerta del Vino’ from Preludes Book 2.

Keywords: music, piano, Debussy, style

Procedia PDF Downloads 118

Authors: Najoua El Hajjaji El Idrissi, Necip Gokhan Kasapoglu

Abstract:

Polarimetric Synthetic Aperture Radar-based imaging is a powerful technique used for earth observation and classification of surfaces. Forest evolution has been one of the vital areas of attention for the remote sensing experts. The information about forest areas can be achieved by remote sensing, whether by using active radars or optical instruments. However, due to several weather constraints, such as cloud cover, limited information can be recovered using optical data and for that reason, Polarimetric Synthetic Aperture Radar (PolSAR) is used as a powerful tool for forestry inventory. In this [14paper, we applied support vector machine (SVM) and Mahalanobis distance to the fully polarimetric AIRSAR P, L, C-bands data from the Nezer forest areas, the classification is based in the separation of different tree ages. The classification results were evaluated and the results show that the SVM performs better than the Mahalanobis distance and SVM achieves approximately 75% accuracy. This result proves that SVM classification can be used as a useful method to evaluate fully polarimetric SAR data with sufficient value of accuracy.

Keywords: classification, synthetic aperture radar, SAR polarimetry, support vector machine, mahalanobis distance

Procedia PDF Downloads 104

Authors: Salma Hussein, Hadia Aziz

Abstract:

Entrepreneurship plays a significant and imperative role in economic and social growth, and therefore, is stimulated and encouraged by governments and academics as a mean of creating job opportunities, innovation, and wealth. Indicative of its importance, it is essential to identify factors that encourage and promote entrepreneurial behavior. This is particularly true for developing countries where the need for entrepreneurial development is high and the resources are scarce, thus, there is a need to maximize the outcomes of investing in entrepreneurial development. Entrepreneurial education has been the center of attention and interest among researchers as it is believed to be one of the most critical factors in promoting entrepreneurship over the long run. Accordingly, the urgency to encourage entrepreneurship education and develop an enterprise culture is now a main concern in Egypt. Researchers have postulated that cognition has the potential to make a significant contribution to the study of entrepreneurship. One such contribution that future studies need to consider in entrepreneurship research is the cognitive processes that occur within the individual such as cognitive style. During the past decade, there has been an increasing interest in cognitive style among researchers and practitioners specifically in innovation and entrepreneurship field. Limited studies pay attention to study the antecedent dynamics that fuel entrepreneurial cognition to better understand its role in entrepreneurship. Moreover, while many studies were conducted on entrepreneurship education, scholars are still hesitant regarding the teachability of entrepreneurship due to the lack of clear evidence of its impact. Furthermore, the relation between cognitive style and entrepreneurial intentions, has yet to be discovered. Hence, this research aims to test the impact of entrepreneurship education on cognitive style and subsequent intention in order to evaluate whether student’s and potential entrepreneur’s cognitive styles are affected by entrepreneurial education and in turn affect their intentions. Understanding the impact of Entrepreneurship Education on ways of thinking and intention is critical for the development of effective education and training in entrepreneurship field. It is proposed that students who are exposed to entrepreneurship education programs will have a more balanced thinking style compared to those students who are not exposed. Moreover, it is hypothesized that students having a balanced cognitive style will exhibit higher levels of entrepreneurial intentions than students having an intuitive or analytical cognitive style. Finally, it is proposed that non-formal entrepreneurship education will be more positively associated with entrepreneurial intentions than will formal entrepreneurship education. The proposed methodology is a pre and post Experimental Design. The sample will include young adults, their age range from 18 till 35 years old including both students enrolled in formal entrepreneurship education programs in private universities as well as young adults who are willing to participate in a Non-Formal entrepreneurship education programs in Egypt. Attention is now given on how far individuals are analytical or intuitive in their cognitive style, to what extent it is possible to have a balanced thinking style and whether or not this can be aided by training or education. Therefore, there is an urge need for further research on entrepreneurial cognition in educational contexts.

Keywords: cognitive style, entrepreneurial intention, entrepreneurship education, experimental design

Procedia PDF Downloads 176

Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

Abstract:

Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

Procedia PDF Downloads 117

Authors: Michelle Sánchez de León Brajkovich, Nuria Martí Audi

Abstract:

The envelope is one of the most important elements when one analyzes the operation of the building in terms of sustainability. Taking this into consideration, this research focuses on setting a classification system of the envelopes opaque systems, crossing the knowledge and parameters of construction systems with requirements in terms of sustainability that they may have, to have a better understanding of how these systems work with respect to their sustainable contribution to the building. Therefore, this paper evaluates the importance of the envelope design on the building sustainability. It analyses the parameters that make the construction systems behave differently in terms of sustainability. At the same time it explains the classification process generated from this analysis that results in a classification where all opaque vertical envelope construction systems enter.

Keywords: sustainable, exterior walls, envelope, facades, construction systems, energy efficiency

Procedia PDF Downloads 539

Authors: Bandhan Dey, Muhsina Bintoon Yiasha, Gulam Sulaman Choudhury

Abstract:

Chest disease is one of the most problematic ailments in our regular life. There are many known chest diseases out there. Diagnosing them correctly plays a vital role in the process of treatment. There are many methods available explicitly developed for different chest diseases. But the most common approach for diagnosing these diseases is through X-ray. In this paper, we proposed a multi-classification deep learning model for diagnosing COVID-19, lung cancer, pneumonia, tuberculosis, and atelectasis from chest X-rays. In the present work, we used the transfer learning method for better accuracy and fast training phase. The performance of three architectures is considered: InceptionV3, VGG-16, and VGG-19. We evaluated these deep learning architectures using public digital chest x-ray datasets with six classes (i.e., COVID-19, lung cancer, pneumonia, tuberculosis, atelectasis, and normal). The experiments are conducted on six-classification, and we found that VGG16 outperforms other proposed models with an accuracy of 95%.

Keywords: deep learning, image classification, X-ray images, Tensorflow, Keras, chest diseases, convolutional neural networks, multi-classification

Procedia PDF Downloads 60

Authors: Zahra Ahmed Al-zadjali

Abstract:

The influence of Islam on arts can be found primarily in calligraphy, arabesque designs and architecture. Also, geometric designs were used quite extensively. Muslim craftsmen produced stunning designs based on simple geometric principles and traditional motifs which were used to decorate many surfaces. The idea of interlacing simple rectilinear lines to form the patterns impressed Arabs. Nomads of Persia, Turks and Mongols were equally impressed with the designs so they begin to use them in their homes in carpet weaving. Islamic designs, motifs and colours which were used became common place and served to influence people’s tastes. Modern life style and contemporary products have changed the style of people’s daily lives, however, people still long for the nomadic way of life. This is clearly reflected in people’s homes. In a great many Muslim homes, Islamic decorative motifs can be seen along with traditional ‘Bedouin’ style furnishing, especially in homes of the Arabian Peninsula.

Keywords: art, craft, design, Oman, weaving

Procedia PDF Downloads 440

Authors: Bharatendra Rai

Abstract:

The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

Procedia PDF Downloads 89

Authors: Seyyedeh Mahdis Mousavi, Masoud Maghsoudi, Zahra Vahed

Abstract:

The purpose of this paper is to examine the relationship between emotional intelligence as conceptualized in Goleman’s competency model, and decision making styles in levels of management. To conduct this study, different level managers in Iran Broadcasting Organization completed a questionnaire on emotional intelligence and decision making styles. Researcher used descriptive and inferential statistics to describe data and analyze the two variables relationship in managers of three levels. Results revealed significant relationships for rational, dependent, avoidant, and spontaneous styles. No significant relationship was found for intuitive style. Yet the results indicate that avoidant style has negative relation to EI. Furthermore, EI has direct and strong relation to rational style.

Keywords: emotional intelligence (EI), decision making styles, Islamic Republic of Iran Broadcasting (IRIB), Iranian manager

Procedia PDF Downloads 343

Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

Abstract:

Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

Procedia PDF Downloads 489

Authors: Xiaoli Zhang, Xiongfei Li, Yuncong Feng

Abstract:

ROC curves, as a widely used evaluating tool in machine learning field, are the tradeoff of true positive rate and negative rate. However, they are blamed for ignoring some vital information in the evaluation process, such as the amount of information about the target that each instance carries, predicted score given by each classification model to each instance. Hence, in this paper, a new classification performance method is proposed by extending the Receiver Operator Characteristic (ROC) curves to 3D space, which is denoted as 3D ROC Histogram. In the histogram, the

Keywords: classification, performance evaluation, receiver operating characteristic histogram, hardness prediction

Procedia PDF Downloads 289

Authors: Zenaide Carvalho da Silva, Leandro Rodrigues Ferreira, Andrey Ricardo Pimentel

Abstract:

Learning styles (LS) refer to the ways and forms that the student prefers to learn in the teaching and learning process. Each student has their own way of receiving and processing information throughout the learning process. Therefore, knowing their LS is important to better understand their individual learning preferences, and also, understand why the use of some teaching methods and techniques give better results with some students, while others it does not. We believe that knowledge of these styles enables the possibility of making propositions for teaching; thus, reorganizing teaching methods and techniques in order to allow learning that is adapted to the individual needs of the student. Adapting learning would be possible through the creation of online educational resources adapted to the style of the student. In this context, this article presents the structure of a learning object interface adaptation based on the LS. The structure created should enable the creation of the adapted learning object according to the student's LS and contributes to the increase of student’s motivation in the use of a learning object as an educational resource.

Keywords: adaptation, interface, learning object, learning style

Procedia PDF Downloads 373

Authors: Boukari Nassim

Abstract:

This paper describes the use of odd pair autoregressive coefficients (Yule _Walker and Burg) for the feature extraction of electroencephalogram (EEG) signals. In the classification: the radial basis function neural network neural network (RBFNN) is employed. The RBFNN is described by his architecture and his characteristics: as the RBF is defined by the spread which is modified for improving the results of the classification. Five types of EEG signals are defined for this work: Set A, Set B for normal signals, Set C, Set D for interictal signals, set E for ictal signal (we can found that in Bonn university). In outputs, two classes are given (AC, AD, AE, BC, BD, BE, CE, DE), the best accuracy is calculated at 99% for the combined odd pair autoregressive coefficients. Our method is very effective for the diagnosis of epileptic EEG signals.

Keywords: epilepsy, EEG signals classification, combined odd pair autoregressive coefficients, radial basis function neural network

Procedia PDF Downloads 322

Authors: Vaishali Chaurasia

Abstract:

Ageing is the universal phenomenon that is associated with deteriorating health status. As the human becomes old, certain changes take place in an organism leading to morbidities, disabilities, and event death. Furthermore, older people are more vulnerable for the various kinds of diseases and health problem. Due to the some unhealthy conventions like smoking, drinking and unhealthy foods is the genesis of the lifestyle diseases. These diseases associated with the way a person or group of people lives. The main purpose of the study is to determine the prevalence of lifestyle diseases and its association with physical activity as well as the risk factors associated with it among the adult population in India. Longitudinal Aging Study in India and Study on Global Aging and Adult Health in India were used in the study. We will take population aged 50 and older, began in 1935, and regularly refreshed at younger ages with new birth cohorts. Life style diseases are more prominent in 65+ age group. The study finds an association between prevalence of life style diseases and life style risk factors. The lifestyle disease prevalence is more among higher age group people, female, richest quintile, and doing lesser physical activity. A higher prevalence of lifestyle diseases associated with the multiple risk factors. The occurrence of three and four risk factors was more prevalent in India. The frequency of different type of life style disease is higher among those who hardly or never do any physical activity as compare to those who do physical activity every day. The pattern remains the same in Moderate as well as vigorous physical activity. Those who are regularly doing physical activities have lesser percentage of having any disease and those who hardly ever or never do any physical activities and equally involve with some risk factors have higher percentage of having all type of diseases.

Keywords: lifestyle disease, morbidity, disability, physical activity

Procedia PDF Downloads 316

Authors: Amal Mohammed Alqahatni

Abstract:

This paper is a non-empirical analysis of existing literature on digital leadership competency, data-driven organizations, and dealing with AI technology (big data). This paper will provide insights into the importance of developing the leader’s analytical skills and style to be more effective for high-quality decision-making in a data-driven organization and achieve creativity during the organization's transformation to be digitalized. Despite the enormous potential that big data has, there are not enough experts in the field. Many organizations faced an issue with leadership style, which was considered an obstacle to organizational improvement. It investigates the obstacles to leadership style in this context and the challenges leaders face in coaching and development. The leader's lack of analytical skill with AI technology, such as big data tools, was noticed, as was the lack of understanding of the value of that data, resulting in poor communication with others, especially in meetings when the decision should be made. By acknowledging the different dynamics of work competency and organizational structure and culture, organizations can make the necessary adjustments to best support their leaders. This paper reviews prior research studies and applies what is known to assist with current obstacles. This paper addresses how analytical leadership will assist in overcoming challenges in a data-driven organization's work environment.

Keywords: digital leadership, big data, leadership style, digital leadership challenge

Procedia PDF Downloads 39

Authors: Abdelkhalek Bakkari

Abstract:

Image segmentation is a critical step in image processing and pattern recognition. In this paper, we proposed a new robust automatic image classification based on a dynamic fuzzy c-means algorithm and mathematical morphology. The proposed segmentation algorithm (DFCM_MM) has been applied to MR perfusion images. The obtained results show the validity and robustness of the proposed approach.

Keywords: segmentation, classification, dynamic, fuzzy c-means, MR image

Procedia PDF Downloads 443

Authors: M. Safa, A. Sabet, S. MacGillivray, M. Davidson, K. Kaczmarczyk, C. T. Haas, G. E. Gibson, D. Rayside

Abstract:

To address construction project requirements and specifications, scholars and practitioners need to establish a taxonomy according to a scheme that best fits their need. While existing characterization methods are continuously being improved, new ones are devised to cover project properties which have not been previously addressed. One such method, the Project Definition Rating Index (PDRI), has received limited consideration strictly as a classification scheme. Developed by the Construction Industry Institute (CII) in 1996, the PDRI has been refined over the last two decades as a method for evaluating a project's scope definition completeness during front-end planning (FEP). The main contribution of this study is a review of practical project classification methods, and a discussion of how PDRI can be used to classify projects based on their readiness in the FEP phase. The proposed model has been applied to 59 construction projects in Ontario, and the results are discussed.

Keywords: project classification, project definition rating index (PDRI), risk, project goals alignment

Procedia PDF Downloads 652

Authors: Ouafae Baida, Najma Hamzaoui, Maha Akbib, Abdelfettah Sedqui, Abdelouahid Lyhyaoui

Abstract:

Numerous scientific works present various methods to analyze the data for several domains, specially the comparison of classifications. In our recent work, we presented a new approach to help the user choose the best classification method from the results obtained by every method, by basing itself on the distances between the trees of classification. The result of our approach was in the form of a dendrogram contains methods as a succession of connections. This approach is much needed in phylogeny analysis. This discipline is intended to analyze the sequences of biological macro molecules for information on the evolutionary history of living beings, including their relationship. The product of phylogeny analysis is a phylogenetic tree. In this paper, we recommend the use of a new method of construction the phylogenetic tree based on comparison of different classifications obtained by different molecular genes.

Keywords: hierarchical classification, classification methods, structure of tree, genes, phylogenetic analysis

Procedia PDF Downloads 476

Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

Abstract:

In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: power spectral density, 3D EEG model, brain balancing, kNN

Procedia PDF Downloads 455

Authors: Syamsul Syafiq, Maslina Daud, Hafizah Hasan, Ahmad Zairi, Shazil Imri, Ezaini Akmar, Norbazilah Rahim

Abstract:

Over recent years, web development has changed significantly. Driven largely by the rise of trends like mobiles, the world of development is rapidly evolving. The rise of the Internet makes web applications crucial nowadays. The web application has been an interface for a company and one of the ways they present their portfolio to the client. On the other hand, the web has become part of the file management system which takes over the role of paper. Due to high demand in web applications, developers are required to develop a web application that are cost-effective, secure and well coded. A framework has been proposed to develop an application rather than using library style development. The framework is helping the developer in creating the structure of a web automatically. This paper will compare the advantages and disadvantages of web development using framework against library-style development. This comparison is based on a previous research paper focusing on two main indicators, which are the impact to management and impact to the developer.

Keywords: framework, library style development, web application development, traditional web, static web, dynamic web

Procedia PDF Downloads 198

Authors: Pierre Nicole Patriarca

Abstract:

This study examined the attachment styles, parent-child relationship, and romantic relationship quality of five illegitimate emerging adults aged 18 to 23 years old. The researcher used self-report measures, inventory of parent and peer attachment, attachment style questionnaire, and network of relationship – relationship quality version in obtaining data. A semi-structured interview was also used to acquire qualitative data about the detailed perception and experiences on the attachment styles and parent-child relationship. Common themes of each variable were identified through thematic analysis. Results showed that four out of five participants depicted positive relationship to their fathers, while all of them reported to have positive relationship to their mothers. It was also found that four participants have preoccupied attachment style, while the other one has fearful attachment style. Common themes in describing their relationship with their mother include being close, influential to participants’ life, unbounded communication, favorable reason of trusting, and sometimes being inattentive. On the other hand, having distant relationship, limited communication about romantic relationship, uninfluential to participant’s life, and favorable reason of trusting were the common themes in describing relationship with father. Lastly, less trusting, being dependent, and emphasis on valuing intimacy were the common themes in describing their style of attachment.

Keywords: illegitimate, emerging adult, attachment, parent-child relationship, relationship quality

Procedia PDF Downloads 377

Authors: Tazvin Ijaz, Aisha Shahid Sheikh

Abstract:

The current study was conducted to explore the relationship between body dissatisfaction and the perceived parenting styles of women. For the purpose of study a sample of adult women (N=308) was drawn through the process of stratified random sampling. The sample consisted of women belonging to different categories which were based on their occupation. Two instruments, the Body Dissatisfaction Scale (BDSS) and Perceived Parenting Styles (PPSS) were used in the study to find the relationship between the two variables. The results showed that the controlling parenting style in father led to higher body dissatisfaction while the nurturing parenting style lead to lesser symptoms of body dissatisfaction. The results also proved that the controlling parenting style in mother also lead to high symptoms of body dissatisfaction as well. It was revealed that the women with high education showed more body dissatisfaction than women with lower education. It was also seen that there was a significant difference in the body dissatisfaction of working and the non-working women.

Keywords: body dissatisfaction, perceived parenting styles, Pakistani women, gender

Procedia PDF Downloads 297

Authors: Radesh Palakurthi

Abstract:

The purpose of this study was to determine the impact of experiential learning on learning outcomes in hospitality education. This paper presents the results of an online survey of students from the U.S. studying abroad and their self-reported change in learning outcomes as assessed using the Core Competencies Model for the Hospitality Industry developed by Employment and Training Development Office of the U.S. Department of Labor. The impact of student learning styles on learning outcomes is also evaluated in this study. Kolb’s Learning Styles Inventory Model was used to assess students’ learning style. The results show that students reported significant improvements in their learning outcomes because of engaging in study abroad experiential learning programs. The learning styles of the students had significant effect on one of core learning outcomes- personal effectiveness.

Keywords: hospitality competencies, hospitality education, Kolb’s learning style inventory, learning outcomes, study abroad

Procedia PDF Downloads 196

Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

Abstract:

Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

Procedia PDF Downloads 131

Authors: Yiannis G. Smirlis

Abstract:

The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.

Keywords: data envelopment analysis, interval DEA, efficiency classification, efficiency prediction

Procedia PDF Downloads 142

Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

Abstract:

Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

Procedia PDF Downloads 314

Authors: Siti Dewi Aisyah

Abstract:

The rise of the Internet in the late twentieth century rapidly gains information and understands the world through screens. The digital way of communication through the Internet becomes an ordinary daily pattern. In the digital era, Fashion has been tremendously shared on social media platform especially because of the emergence of #OOTD (Outfit of the Day). Fashion cannot survive without the media. The media have played a vital role in shaping fashion into the complex cultural phenomenon it has become, and fashion has become an intrinsic part of today’s visual culture, and vice versa. Islamic Muslim Fashion has become a trend in Indonesia. It is said that social media has a huge impact in its development. Indonesia is ranked among the most users of social media. That is why people who wear hijab also use social media for different purposes, one of this is to introduce hijab fashion. Consequently, they are becoming famous in social media. Social media has become a tool for communicating their beliefs as a Muslim as well as personal branding as a good hijabi yet with a fashionable style. This study will examine how social media especially Blog and Instagram can lead the movement of Islamic Modest Fashion in Indonesia, how it triggers the consumer culture to hijabi, how they visualize their style in their social media. This research had been conducted through in-depth interviews with several bloggers who created Hijabers Community who have made a new trend in Islamic fashion and also Instagrammers who made their feeds as a style inspiration. This research is based on empirical research with qualitative methods (text and picture analysis). The methodology used for this research is by analyzing Blog and Instagram through visual analysis on the social media especially about the Islamic Modest Fashion trend. This research also contains a literature review of a diverse group of works on topics related to the study. This research will be examined through several theoretical frameworks including the study of social media, visual analysis and consumer culture. Fashion and consumer culture are also two main topics because fashion furthermore leads to consumer culture. The benefit of this research is for gaining the insight how social media can visualize the trend in hijab fashion style of Indonesian people.

Keywords: blog, consumer culture, hijab fashion, instagram, style, visual analysis

Procedia PDF Downloads 297

Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

Abstract:

This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

Procedia PDF Downloads 32