Search results for: emotional recognition

Authors: Si Chen, Quanhong Jiang

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In the increasingly mature posture recognition technology, human movement information is widely used in sports rehabilitation, human-computer interaction, medical health, human posture assessment, and other fields today; this project uses the most original ideas; it is proposed to use the collection equipment for the collection of myoelectric data, reflect the muscle posture change on a degree of freedom through data processing, carry out data-muscle three-dimensional model joint adjustment, and realize basic pose recognition. Based on this, bionic aids or medical rehabilitation equipment can be further developed with the help of robotic arms and cutting-edge technology, which has a bright future and unlimited development space.

Keywords: pose recognition, 3D animation, electromyography, machine learning, bionics

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Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: Fariba Dortaj, H. Bashir Nejad, Akram Dortaj,

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Investigate the Effectiveness of Mindfulness Education on Emotional, Psychological, and Social Well-being in 12th grade students in Tehran city is the aim of present study. The research method is semi-experimental with pretest-posttest design with control group. The statistical population of the study includes all 12th grade students of the 12th district of Tehran city in the academic year of 2017 to 2018. From the mentioned population, 60 students had earned low scores in three dimensions of Subjective Well-Being Questionnaire of Keyes and Magyar-Moe (2003) by using random sampling method and they were selected and randomly assigned into 2 experimental and control groups. Then experimental groups were received a Mindfulness protocol in 8 sessions during 2 hours. After completion of the sessions, all subjects were re-evaluated. Data were analyzed by using multivariate analysis of covariance. The findings of this study showed that in the emotional well-being aspect with the components of positive emotional affection (P < 0.025, F = 17/80) and negative emotions (P <0.025, F = 5/41), in the psychological well-being of the components Self-esteem (P < 0.008, F = 25.26), life goal (P < 0.008, F = 38.19), environmental domination (P <0.008, F=82.82), relationships with others (P < 0.008, F = 19.12), personal development with (P < 0.008, F = 87.38), and in the social well-being aspect, the correlation coefficients with (P<0.01, F=12/21), admission and acceptability with (P <0.01, F =18.09) and realism with (P <0.01, F = 11.30), there was a significant difference between the experimental and control groups and it can be said that the education of mindfulness affects the improvement of components of psychological, social and emotional well-being in students.

Keywords: mindfulness, emotional well-being, psychological well-being, social well-being

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Authors: S. Da Costa, D. Páez, F. Sánchez

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We examine the causal role of positive affect on creativity, the association of creativity or innovation in the ideation phase with functional emotional regulation, successful adjustment to stress and dispositional emotional creativity, as well as the predictive role of creativity for positive emotions and social adjustment. The study examines the effects of modification of positive affect on creativity. Participants write three poems, narrate an infatuation episode, answer a scale of personal growth after this episode and perform a creativity task, answer a flow scale after creativity task and fill a dispositional emotional creativity scale. High and low positive effect was induced by asking subjects to write three poems about high and low positive connotation stimuli. In a neutral condition, tasks were performed without previous affect induction. Subjects on the condition of high positive affect report more positive and less negative emotions, more personal growth (effect size r = .24) and their last poem was rated as more original by judges (effect size r = .33). Mediational analysis showed that positive emotions explain the influence of the manipulation on personal growth - positive affect correlates r = .33 to personal growth. The emotional creativity scale correlated to creativity scores of the creative task (r = .14), to the creativity of the narration of the infatuation episode (r = .21). Emotional creativity was also associated, during performing the creativity task, with flow (r = .27) and with affect balance (r = .26). The mediational analysis showed that emotional creativity predicts flow through positive affect. Results suggest that innovation in the phase of ideation is associated with a positive affect balance and satisfactory performance, as well as dispositional emotional creativity is adaptive.

Keywords: affectivity, creativity, induction, innovation, psychological factors

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Authors: Khaled Mohammed

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This paper presents novel face recognition and identification approaches for the real-time attendance management problem in large companies/factories and government institutions. The proposed uses the Minimum Ratio (MR) approach for employee identification. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the Previous approaches at a rate between 2% to 5%. In addition, it decreased the time two times if compared with the Previous techniques, such as Extreme Learning Machine (ELM) & Multi-Scale Structural Similarity index (MS-SSIM). Finally, it achieved an accuracy of 99%.

Keywords: attendance management system, face detection and recognition, live face recognition, minimum ratio

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Authors: Jyoti Bharti, Navneet Manjhi, M. K.Gupta, Bimi Jain

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A reliable gait features are required to extract the gait sequences from an images. In this paper suggested a simple method for gait identification which is based on moments. Moment values are extracted on different number of frames of gray scale and silhouette images of CASIA database. These moment values are considered as feature values. Fuzzy logic and nearest neighbour classifier are used for classification. Both achieved higher recognition.

Keywords: gait, fuzzy logic, nearest neighbour, recognition rate, moments

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Authors: Smita Pallavi, Raj Ratn Pranesh, Sumit Kumar

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Information representation as tables is compact and concise method that eases searching, indexing, and storage requirements. Extracting and cloning tables from parsable documents is easier and widely used; however, industry still faces challenges in detecting and extracting tables from OCR (Optical Character Recognition) documents or images. This paper proposes an algorithm that detects and extracts multiple tables from OCR document. The algorithm uses a combination of image processing techniques, text recognition, and procedural coding to identify distinct tables in the same image and map the text to appropriate the corresponding cell in dataframe, which can be stored as comma-separated values, database, excel, and multiple other usable formats.

Keywords: table extraction, optical character recognition, image processing, text extraction, morphological transformation

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Authors: Agastya Pratap Singh

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Generative Adversarial Networks (GANs) have emerged as powerful tools in the fields of image recognition and anomaly detection due to their ability to model complex data distributions and generate realistic images. This systematic review explores recent advancements and applications of GANs in both image recognition and anomaly detection tasks. We discuss various GAN architectures, such as DCGAN, CycleGAN, and StyleGAN, which have been tailored to improve accuracy, robustness, and efficiency in visual data analysis. In image recognition, GANs have been used to enhance data augmentation, improve classification models, and generate high-quality synthetic images. In anomaly detection, GANs have proven effective in identifying rare and subtle abnormalities across various domains, including medical imaging, cybersecurity, and industrial inspection. The review also highlights the challenges and limitations associated with GAN-based methods, such as instability during training and mode collapse, and suggests future research directions to overcome these issues. Through this review, we aim to provide researchers with a comprehensive understanding of the capabilities and potential of GANs in transforming image recognition and anomaly detection practices.

Keywords: generative adversarial networks, image recognition, anomaly detection, DCGAN, CycleGAN, StyleGAN, data augmentation

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Authors: Yulina E. Riany, Divna Haslam, Matthew Sanders

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This cross-cultural study aims to compare the level of parental depression and stress, parenting style use, and child emotional and behavioural problems between parents in Australia as an example of a Western country and parents in Indonesia as an example of Asian culture. A series of hierarchical regressions were undertaken to determine two models examining the factors that predict child problems residing in Australia (Model 1) and in Indonesia (Model 2). The online survey was completed by 179 parents in Australia and 448 parents in Indonesia. Results indicated that Australian parents reported higher levels of depression, authoritative parenting and higher levels of child misbehaviours compared to Indonesian parents. In comparison, Indonesian parents reported higher authoritarian parenting. Analyses performed to examine Model 1 and 2 revealed that parental negative emotional states and parenting style predicted child emotional and behavioural problems in both countries.

Keywords: cross-cutural study, parental stress, parenting, child misbehaviour

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Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

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Authors: Seyyedeh Mahdis Mousavi, Masoud Maghsoudi, Zahra Vahed

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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

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Authors: Mehar Pruthi, Manjula V.

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For the longest time, Indian households have been hosts to a variety of domestic evils such as intimate partner violence, physical abuse, sexual assaults, and more commonly gender-based violence. The prevalence of such heinous acts against women is often swept under the carpet of patriarchy and leaves women scarred. Many times, these wounds are caused by more insidious and subtle acts of violence. For this study, the choice of term for these acts is Emotional Abuse. The ill effects of emotional abuse on the victim’s sense of self and psychological health have been widely established. The current study takes a qualitative approach to explore women’s experiences at the brunt of emotional abuse. To this end, six participants (N=6) were identified using purposive and snowball sampling which was followed by a pre-screening form to assess for the presence of emotional abuse. A semi-structured interview guide was employed to investigate the victim’s perception of emotional abuse, the manifestation of emotional abuse in a patriarchal society, and the reasons women remain in abusive relationships. Each interview lasted about 50-60 mins and was accompanied by extensive note-making. A preliminary analysis of the interviews was done using the Interpretative Phenomenological Approach. Initial findings reveal the emergence of themes such as feelings of loneliness, intergenerational transmission of violence, denial, justifying the partner’s behavior, staying because of children, hoping things would change, and faith in God. The study is instrumental in conceptualizing the patterns of emotional abuse keeping in mind the patriarchal context of the Indian society. It has implications for professionals in the mental health field who work with this population so they can better understand their plight. Future research could focus on rebuilding relationships for those partners who decide to sustain such relationships and focus on various coping mechanisms with special emphasis on religious beliefs.

Keywords: emotional abuse, gender-based violence, intimate partner violence, marriage, patriarchy

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Authors: Seyed Ali Kimiaei, Reza Pishghadam, Fatemeh Hajizadeh, Marjan Entezari

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The aim of this study was to investigate the effectiveness of the Minnesota Spouses Communication Skills Program on reducing emotional harassment and adjusting the marital expectations of married women. The research method was quasi-experimental with pretest-posttest design with waiting list group and follow-up period. The statistical population of the study consisted of married women referring to counseling and psychology centers in Mashhad, from which 30 people were selected as a sample by examining the entry criteria and questionnaire scores, and randomly divided into two experimental groups (15 people) and the waiting list group (15 people) were replaced. The experimental group was given 8 sessions of communication skills program of spouses. The emotional harassment and marital expectations questionnaire was used to collect data. The results showed a significant difference between the experimental group and the waiting list group, so that the communication skills training of the spouses reduced emotional harassment and adjusted marital expectations, and these effects continued in the follow-up period. Therefore, we can conclude that teaching the husband's communication skills program in the Minnesota method reduces emotional harassment and modifies women's marital expectations.

Keywords: spouses communication skills program, emotional harassment, marital expectations, women

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Authors: Zixuan Xu, Yichun Lou, Yang Song, Zihuai Lin

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MediaPipe is an open-source machine learning computer vision framework that can be ported into a multi-platform environment, which makes it easier to use it to recognize the human activity. Based on this framework, many human recognition systems have been created, but the fundamental issue is the recognition of human behavior and posture. In this paper, two methods are proposed to recognize human gestures based on MediaPipe, the first one uses the Adaptive Boosting algorithm to recognize a series of fitness gestures, and the second one uses the Fast Dynamic Time Warping algorithm to recognize 413 continuous fitness actions. These two methods are also applicable to any human posture movement recognition.

Keywords: computer vision, MediaPipe, adaptive boosting, fast dynamic time warping

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Authors: Issam Ben Jami

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Information retrieval in digital libraries is very important because most famous historical documents occupy a significant value. The word spotting in historical documents is a very difficult notion, because automatic recognition of such documents is naturally cursive, it represents a wide variability in the level scale and translation words in the same documents. We first present a system for the automatic recognition, based on the extraction of interest points words from the image model. The extraction phase of the key points is chosen from the representation of the image as a synthetic description of the shape recognition in a multidimensional space. As a result, we use advanced methods that can find and describe interesting points invariant to scale, rotation and lighting which are linked to local configurations of pixels. We test this approach on documents of the 15th century. Our experiments give important results.

Keywords: feature matching, historical documents, pattern recognition, word spotting

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Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui

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In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.

Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN

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Authors: G. H. Vakhitova, E. P. Leontyev

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\Modern children experience a huge impact on their psycho-emotional state due to globalization, comprehensive informatization and digitalization. This situation aggravates the problem of children's communication. In a constantly changing world, it is quite difficult for today’s child to maintain emotional well-being, especially in the process of communicating with various participants in communication. Despite the many works of scientists considering various aspects of communication and emotional well-being, the problem remains open, discussed from various angles by philosophers, teachers, psychologists, and sociologists. The article examines the causes of emerging communication difficulties in the context of “child–adult,” and “child-parent” since it is in this logic that the experience of common emotional experiences is formed, which is the basis not only for living together but also for the full development of personality. In this case, it is important to pay special attention to the need to ensure the emotional well-being of the child, first of all, by parents who, due to their busy lives, notice less and less the changes occurring with their children. At the same time, children need constructive dialogue, but often adults do not have the patience to choose the right emotions without breaking into shouting and insults if the child displays behavior that differs from the desired one. The reason for communication difficulties, as shown by the results of the survey and long-term observations of the authors, maybe adults ignoring the characteristics of children. These features manifest themselves in children in different ways: for example, inadequate self-esteem is associated with either excessive timidity or aggressiveness. Such children, as a rule, fearing ridicule not only from their peers but even from adults, live with distrust of the world; they lack initiative, often being rude or, on the contrary, mocking others. In addition, modern children are different, not the same as their peers were twenty to twenty-five years ago. Today, the concept of “digital children” and “clip-based” children has become firmly established in the description of children. This circumstance cannot be ignored when building their communication. The authors note that only if the capabilities and originality of modern children are taken into account is it possible to ensure their emotional well-being in the process of communication.

Keywords: emotional well-being, communication, emotional comfort, emotions, communication difficulties, constructive communication, dialogue

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Authors: Deawan Rakin Ahamed Remal, Sinthia Chowdhury, Sharun Akter Khushbu, Sheak Rashed Haider Noori

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Native Speech to text synthesis has its own leverage for the purpose of mankind. The extensive nature of art to speaking different accents is common but the purpose of communication between two different accent types of people is quite difficult. This problem will be motivated by the extraction of the wrong perception of language meaning. Thus, many existing automatic speech recognition has been placed to detect text. Overall study of this paper mentions a review of NSTTR (Native Speech Text to Text Recognition) synthesis compared with Text to Text recognition. Review has exposed many text to text recognition systems that are at a very early stage to comply with the system by native speech recognition. Many discussions started about the progression of chatbots, linguistic theory another is rule based approach. In the Recent years Deep learning is an overwhelming chapter for text to text learning to detect language nature. To the best of our knowledge, In the sub continent a huge number of people speak in Bangla language but they have different accents in different regions therefore study has been elaborate contradictory discussion achievement of existing works and findings of future needs in Bangla language acoustic accent.

Keywords: TTR, NSTTR, text to text recognition, deep learning, natural language processing

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Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

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Authors: Kamyar Fakhr, Roozbeh Salmani

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Alphonse Bertillon developed the first biometric security system in the 1800s. Today, many governments and giant companies are considering or have procured biometrically enabled security schemes. Iris is a kaleidoscope of patterns and colors. Each individual holds a set of irises more unique than their thumbprint. Every single day, giant companies like Google and Apple are experimenting with reliable biometric systems. Now, after almost 200 years of improvements, face ID does not work with masks, it gives access to fake 3D images, and there is no global usage of biometric recognition systems as national identity (ID) card. The goal of this paper is to demonstrate the advantages of iris recognition overall biometric recognition systems. It make two extensions: first, we illustrate how a very large amount of internet fraud and cyber abuse is happening due to bugs in face recognition systems and in a very large dataset of 3.4M people; second, we discuss how establishing a secure global network of iris recognition devices connected to authoritative convolutional neural networks could be the safest solution to this dilemma. Another aim of this study is to provide a system that will prevent system infiltration caused by cyber-attacks and will block all wireframes to the data until the main user ceases the procedure.

Keywords: biometric system, convolutional neural network, cyber-attack, secure

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Authors: Giovanna Borges Bottino, Luis Felipe Freitas do Nascimento Alves Teixeira

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This article aims to present a case study of the National Civil Aviation Agency (ANAC) in Brazil, ANAC-id. ANAC-id is the artificial intelligence algorithm developed for image analysis that recognizes standard images of unobstructed and uprighted face without sunglasses, allowing to identify potential inconsistencies. It combines YOLO architecture and 3 libraries in python - face recognition, face comparison, and deep face, providing robust analysis with high level of accuracy.

Keywords: artificial intelligence, deepface, face compare, face recognition, YOLO, computer vision

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Authors: Ilia Zharikov, Philipp Nikitin, Ilia Vasiliev, Vladimir Dokholyan

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With the increasing popularity of document analysis and recognition systems, text detection (TD) and optical character recognition (OCR) in document images become challenging tasks. However, according to our best knowledge, no publicly available datasets for these particular problems exist. In this paper, we introduce a Distorted Document Images dataset (DDI-100) and provide a detailed analysis of the DDI-100 in its current state. To create the dataset we collected 7000 unique document pages, and extend it by applying different types of distortions and geometric transformations. In total, DDI-100 contains more than 100,000 document images together with binary text masks, text and character locations in terms of bounding boxes. We also present an analysis of several state-of-the-art TD and OCR approaches on the presented dataset. Lastly, we demonstrate the usefulness of DDI-100 to improve accuracy and stability of the considered TD and OCR models.

Keywords: document analysis, open dataset, optical character recognition, text detection

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Authors: Wan-Chun Chang, Yi-Jung Lee

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Due to cultural factors, expressing emotions may not be encouraged in collectivist cultures, which emphasize the needs of the group over the needs of the individual. This phenomenon is more prominent for children of migratory families. Due to the absence of one parent, children were often parentified by adults, which then impacted on their self-differentiation process. It made them more difficult to express their needs and emotions freely and openly. This study aimed to investigate the meditation effect of self-differentiation between parentification, and ambivalence over emotional expression for children of migratory families in Taiwan. Participants included 460 (326 females, 134 males) Taiwanese adults (age 18-25 years). The data were collected through questionnaires and analyzed using descriptive statistics and multiple regression analysis. The questionnaire included informed consent form, 'Filial Responsibility Scale-Adult', 'Chinese version of the Differentiation of Self Inventory', 'Ambivalence over Emotion Expressiveness Questionnaire', and the demographic sheet. Results indicated that self-differentiation mediated the relationship between parentified experience and ambivalence over emotional expression. In other words, parentified experience itself does not have the power to affect ambivalence over emotional expression. Only by affecting self-differentiation can it make an actual difference. The results were as expected and confirmed the hypothesis. Implications for clinical practice, research, and training were discussed.

Keywords: ambivalence over emotional expression, children of migratory families, parentification, self-differentiation

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Authors: Michael Alsop, Hannah Heitz, Prathiba Natesan Batley, Marion Hambrick, Jason Immekus

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The impacts of cultural engagement on individuals’ health and well-being have been well documented. The purposes of this study were to create an instrument to measure wellbeing constructs, including cultural wellbeing, and explore the relationships between cultural wellbeing and other wellbeing constructs (e.g., emotional, social, physical, spiritual). A sample of 358 participants attending concerts performed by a civic orchestra in the southeastern United States completed a questionnaire designed to measure eight wellbeing constructs. Split-half exploratory, confirmatory factor analyses resulted in the retention of four wellbeing constructs: general, emotional, financial, and cultural. Structural equation modeling showed statistically significant relationships between cultural wellbeing and other wellbeing constructs. In addition to the indirect effect of financial wellbeing on emotional and general wellbeing through cultural wellbeing, there were also direct statistically significant relationships (i.e., moderator). This highlights the importance of removing financial barriers to cultural engagement and the relationship between cultural wellbeing on emotional and general wellbeing. Additionally, the retained cultural wellbeing items focused primarily on community features, indicating the value of community-based cultural engagement opportunities.

Keywords: cultural wellbeing, cultural engagement, factor analysis, structural equation modeling

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Authors: Poonamdeep kaur

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With the increase in number of Non-Resident Indian marriages there is also increase in foreign decree divorces which inevitably causes the problem of recognition and enforcement of foreign judgments in India. The Hindus in India are governed by the Hindu Marriage Act, 1956. According to the said Act the courts in India have jurisdiction to try the matrimonial dispute if the marriage is performed in India or the parties to the marriage have domicile in India irrespective of their nationality status. But, sometimes one of the parties to the marriage whose marriage is solemnized in India obtains divorce in foreign courts and prays for the recognition and enforcement of such divorce in India. In such case section 13 of the Indian Civil Procedure Code, 1908, comes into play for the recognition and enforcement of foreign divorces in India. The section makes a foreign judgment conclusive in India subject to the fulfilment of certain conditions. Even if a foreign decree divorce is given on personal connecting factors of the parties to the matrimonial dispute like domicile, such divorce may still be refused recognition in India by virtue of section 13 of the Indian Civil Procedure Code, 1908. It is a universal truth that municipal law of countries is not the same throughout the world. Comity plays an important role in recognition and enforcing a foreign judgment, but, now in India the principle is not applied mechanically as the divorce matter is dealt strictly with regard to Indian Law. So in this paper there will be deep analysis of Indian case laws relating to recognition and enforcement of foreign divorces and based on this a comparative study will be made with the laws of Canada and England on the same subject to find out whether the Indian law on recognition and Enforcement of foreign judgment are in line with the laws of Canada and England and whether in recent years the Indian courts have evolved some new principles of private international law to deal with limping marriages. At last conclusions will be drawn out from the comparative study and suggestions would be given to make the rules of recognition and enforcement of foreign judgments on divorce more certain.

Keywords: divorce, foreign decree, private international law, recognition and enforcement of foreign judgment

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Authors: Sony Subedi, Colleen Davison, Susan Bartels

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Objective: The aim of this study is to i) investigate the socio-demographics and living conditions of households in Haiti pre- and post 2010 earthquake, ii) determine the household prevalence of emotional and physical abuse in children (aged 2-14) after the earthquake, and iii) explore the association between earthquake-related loss and experience of emotional and physical child abuse in the household while considering potential confounding variables and the interactive effects of a number of social, economic, and demographic factors. Methods: A nationally representative sample of Haitian households from the 2005/6 and 2012 phases of the Demographic and Health Surveys (DHS) was used. Descriptive analysis was summarized using frequencies and measures of central tendency. Chi-squared and independent t-tests were used to compare data that was available pre-earthquake and post-earthquake. The association between experiences of earthquake-related loss and emotional and physical child abuse was assessed using log-binomial regression models. Results: Comparing pre-post-earthquake, noteworthy improvements were observed in the educational attainment of the household head (9.1% decrease in “no education” category) and in possession of the following household items: electricity, television, mobile-phone, and radio post-earthquake. Approximately 77.0% of children aged 2-14 experienced at least one form of physical abuse and 78.5% of children experienced at least one form of emotional abuse one month prior to the 2012 survey period. Analysis regarding the third objective (association between experiences of earthquake-related loss and emotional and physical child abuse) is in progress. Conclusions: The extremely high prevalence of emotional and physical child abuse in Haiti indicates an immediate need for improvements in the enforcement of existing policies and interventions aimed at decreasing child abuse in the household.

Keywords: Haiti earthquake, physical abuse, emotional abuse, natural disasters, children

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Authors: Amir Hajian, Sepehr Damavandinejadmonfared

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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

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Authors: Mohammed Arif, Abdessalam Kifouche

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Optical character recognition (OCR) has a main role in the present time. It's capable to solve many serious problems and simplify human activities. The OCR yields to 70's, since many solutions has been proposed, but unfortunately, it was supportive to nothing but Latin languages. This work proposes a system of recognition of an off-line Arabic handwriting. This system is based on a structural segmentation method and uses support vector machines (SVM) in the classification phase. We have presented a state of art of the characters segmentation methods, after that a view of the OCR area, also we will address the normalization problems we went through. After a comparison between the Arabic handwritten characters & the segmentation methods, we had introduced a contribution through a segmentation algorithm.

Keywords: OCR, segmentation, Arabic characters, PAW, post-processing, SVM

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Authors: Shiyin He, Zheng Huang

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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

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Authors: C. V. Aravinda, H. N. Prakash

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In this paper, we tried to convey fusion and state of art pertaining to SIL character recognition systems. In the first step, the text is preprocessed and normalized to perform the text identification correctly. The second step involves extracting relevant and informative features. The third step implements the classification decision. The three stages which involved are Data acquisition and preprocessing, Feature extraction, and Classification. Here we concentrated on two techniques to obtain features, Feature Extraction & Feature Selection. Edge-hinge distribution is a feature that characterizes the changes in direction of a script stroke in handwritten text. The edge-hinge distribution is extracted by means of a windowpane that is slid over an edge-detected binary handwriting image. Whenever the mid pixel of the window is on, the two edge fragments (i.e. connected sequences of pixels) emerging from this mid pixel are measured. Their directions are measured and stored as pairs. A joint probability distribution is obtained from a large sample of such pairs. Despite continuous effort, handwriting identification remains a challenging issue, due to different approaches use different varieties of features, having different. Therefore, our study will focus on handwriting recognition based on feature selection to simplify features extracting task, optimize classification system complexity, reduce running time and improve the classification accuracy.

Keywords: word segmentation and recognition, character recognition, optical character recognition, hand written character recognition, South Indian languages

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