Search results for: mental images

Authors: Nuseiba M. Altarawneh, Suhuai Luo, Brian Regan, Guijin Tang

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Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity and specificity.

Keywords: Bhattacharyya distance, distance regularized level set (DRLS) model, liver segmentation, level set method

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Authors: Zin Mar Lwin

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Brain Computer Interface (BCI) Systems have developed for people who suffer from severe motor disabilities and challenging to communicate with their environment. BCI allows them for communication by a non-muscular way. For communication between human and computer, BCI uses a type of signal called Electroencephalogram (EEG) signal which is recorded from the human„s brain by means of an electrode. The electroencephalogram (EEG) signal is an important information source for knowing brain processes for the non-invasive BCI. Translating human‟s thought, it needs to classify acquired EEG signal accurately. This paper proposed a typical EEG signal classification system which experiments the Dataset from “Purdue University.” Independent Component Analysis (ICA) method via EEGLab Tools for removing artifacts which are caused by eye blinks. For features extraction, the Time and Frequency features of non-stationary EEG signals are extracted by Matching Pursuit (MP) algorithm. The classification of one of five mental tasks is performed by Multi_Class Support Vector Machine (SVM). For SVMs, the comparisons have been carried out for both 1-against-1 and 1-against-all methods.

Keywords: BCI, EEG, ICA, SVM

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Authors: R. R. Ramsheeja, R. Sreeraj

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For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

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Authors: Mohamad Shariff Nurasikin, Paul Crawford, Nicola Wright

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People with any mental disorder can get benefit from the spiritual aspects of life for recovery, particularly in searching for the meaning of life and engaging in meaningful activities. However, little is known about such effects in the population of bipolar disorder. The concepts of spirituality are highly contestable, as they are too broad and removed from the original religious understanding. The concepts are more notable as encompassing multi-dimensional aspects of people’s lives such as social, emotional, and psychological. Viewing that Western or secular worldview dominates most of the literature in spirituality, it is time to explore the concept of spirituality from the Eastern and religious worldview, such as the Malaysian view. Thus, the aim of this study is to provide a conceptual understanding of people with bipolar disorder with a religious affiliation in Malaysia. This study employs a Grounded Theory and explores the narratives from the interviews of 25 participants. The narratives strongly suggest the salient resources or can be referred to as various forms of capital, as in the capital theory, namely, religious, social, psychological, and medicinal. More important is how these capitals are the enablers for recovery in mental health and well-being, where the participants in the sample engage in a more meaningful life and positive adaptations. This study also extends the Bourdieusian spiritual capital, in which the salient resources are termed as the capital bundle. More significant is how the capital bundles are working contiguously in building and accumulating the spiritual capital. This process is conducive to recovery within the social life of people with bipolar disorder or perhaps other mental disorders.

Keywords: bipolar, Bourdeau, recovery, spiritual

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Authors: Urwah Ali

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The aim of this study is to carry out a meta-analysis in order to establish an overall international figure and to summarize the evidence relating to the possible relationship between child sexual abuse and subsequent mental and physical health outcomes. A systematic review was conducted using the HEC Digital Library, Pub Med, PsycINFO and SAHIL databases published after 2010 containing empirical data pertaining to CSA. Out of 124 articles assessed for eligibility, 32 studies provided evidence of a relationship between sexual child maltreatment and various health outcomes for use in subsequent meta-analyses. Statistical significance associations were observed between childhood sexual victimization and psychological problems in their adulthood [odds ratio (OR) = 1.5; 95%Cl 3.07–4.43]. For most studies included for meta-analysis, the odds ratio falls above 1.00, indicating that patients having history of childhood sexual victimization were more likely to develop psychological disorders.

Keywords: abuse, sexual abuse, childhood sexual abuse, mental health

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Authors: Mona Masood, Norshazlina Shaik Othman

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The purpose of this study was to investigate graduate students’ visual attention and perceptions of a Prezi presentation. Ten post-graduate master students were presented with a Prezi presentation at the Centre for Instructional Technology and Multimedia, Universiti Sains Malaysia (USM). The eye movement indicators such as dwell time, average fixation on the areas of interests, heat maps and focus maps were abstracted to indicate the students’ visual attention. Descriptive statistics was employed to analyze the students’ perception of the Prezi presentation in terms of text, slide design, images, layout and overall presentation. The result revealed that the students paid more attention to the text followed by the images and sub heading presented through the Prezi presentation.

Keywords: eye tracking, Prezi, visual attention, visual perception

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Kaveh Shahi, Helmi Z. M. Shafri, Ebrahim Taherzadeh

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In remote sensing, shadow causes problems in many applications such as change detection and classification. It is caused by objects which are elevated, thus can directly affect the accuracy of information. For these reasons, it is very important to detect shadows particularly in urban high spatial resolution imagery which created a significant problem. This paper focuses on automatic shadow detection based on a new spectral index for multispectral imagery known as Shadow Detection Index (SDI). The new spectral index was tested on different areas of World-View 2 images and the results demonstrated that the new spectral index has a massive potential to extract shadows effectively and automatically.

Keywords: spectral index, shadow detection, remote sensing images, World-View 2

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Authors: Navid Nasrolah Mazandarani, Faezeh Mohammadi Tahrodi, Jr., Norshida Ujang, Richard Jan Pech

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Human evolution has designed us to be dependent on social and natural settings, but designed of our modern cities often ignore this fact. It is evident that high-rise buildings dominate most metropolitan city centers. As a result urban parks are very limited and in many cases are not socially responsive to our social needs in these urban ‘jungles’. This paper emphasizes the functions of urban morphology in supporting socialization in Lake Garden, one of the main urban parks in Kuala Lumpur, Malaysia. It discusses two relevant theories; first the concept of users’ experience coined by Kevin Lynch (1960) which states that way-finding is related to the process of forming mental maps of environmental surroundings. Second, the concept of social activity coined by Jan Gehl (1987) which holds that urban public spaces can be more attractive when they provide welcoming places in which people can walk around and spend time. Until recently, research on socio-spatial behavior mainly focused on social ties, place attachment and human well-being; with less focus on the spatial dimension of social behavior. This paper examines the socio-spatial behavior within the spatial structure of the urban park by exploring the relationship between way-finding and social activity. The urban structures defined by the paths and nodes were analyzed as the fundamental topological structure of space to understand their effects on the social engagement pattern. The study uses a photo questionnaire survey to inspect the spatial dimension in relation to the social activities within paths and nodes. To understand the legibility of the park, spatial cognition was evaluated using sketch maps produced by 30 participants who visited the park. The results of the sketch mapping indicated that a spatial image has a strong interrelation with socio-spatial behavior. Moreover, an integrated spatial structure of the park generated integrated use and social activity. It was found that people recognized and remembered the spaces where they engaged in social activities. They could experience the park more thoroughly, when they found their way continuously through an integrated park structure. Therefore, the benefits of both perceptual and social dimensions of planning and design happened simultaneously. The findings can assist urban planners and designers to redevelop urban parks by considering the social quality design that contributes to clear mental images of these places.

Keywords: spatial structure, social activities, sketch map, urban park, way-finding

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Authors: Dhananjay W. Bansod, Santosh Phad

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Non-Communicable Diseases (NCD) are major contributing factors to the disease burden in the world as well as in India. With a growing proportion of older persons in India gives rise to several challenges. With the advancement of age, elderly is exposed to various kinds of health problems more specifically NCDs. Therefore, an effort has been made to examine the prevalence of NCDs among older persons and its treatment-seeking behaviour, also it is tried to explore the association between the NCDs and its effect on the overall wellbeing of older persons. Data used from “Building Knowledge Base of Population Ageing Survey” conducted in 2011 in seven states of India. Six chronic diseases used (non-communicable diseases) namely Arthritis, Hypertension, Cataract, Diabetes, Asthma and Heart diseases to understand the issues related to NCDs. Also seen the effect of NCDs on the wellbeing of the elderly, the subjective well-being consists of nine questions from which SUBI score generated for mental health status, which ranges from 9 to 27. This Index indicates that lower the score better is the mental health status. Further, this index modified and generated three categories of Better (9-15), Average (16-20) and Worse (21-27). The reliability analysis is carried out with the coefficient (Cronbach’s alpha) of the scale was 0.8884. The result shows that Orthopedic / musculoskeletal ailments involving arthritis, rheumatism and osteoarthritis are the most common type of ailment followed by hypertension. Two-thirds of the elderly reported suffering from at least one chronic ailment. Most chronic illness conditions received some form of treatment and mainly depend on public health facilities. Financial insecurity is the primary obstruction in seeking treatment for most of the chronic ailments which typically require a longer duration of medication and repeated medical consultations, both having significant economic implications. According to SUBI index, only 15 per cent of the elderly are in Better mental health status, and one-third of the elderly are with the worse score. Elderly with the ailments like Cataract, Asthma and Arthritis have worse mental health. It depicts that the burden of disease is more among the elderly and it is directly affecting the overall wellbeing of older persons.

Keywords: NCD, well-being, older person, India

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Authors: Marie Alaghband, Niloofar Yousefi, Ivan Garibay

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Facial expressions are important parts of both gesture and sign language recognition systems. Despite the recent advances in both fields, annotated facial expression datasets in the context of sign language are still scarce resources. In this manuscript, we introduce an annotated sequenced facial expression dataset in the context of sign language, comprising over 3000 facial images extracted from the daily news and weather forecast of the public tv-station PHOENIX. Unlike the majority of currently existing facial expression datasets, FePh provides sequenced semi-blurry facial images with different head poses, orientations, and movements. In addition, in the majority of images, identities are mouthing the words, which makes the data more challenging. To annotate this dataset we consider primary, secondary, and tertiary dyads of seven basic emotions of "sad", "surprise", "fear", "angry", "neutral", "disgust", and "happy". We also considered the "None" class if the image’s facial expression could not be described by any of the aforementioned emotions. Although we provide FePh as a facial expression dataset of signers in sign language, it has a wider application in gesture recognition and Human Computer Interaction (HCI) systems.

Keywords: annotated facial expression dataset, gesture recognition, sequenced facial expression dataset, sign language recognition

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Authors: Mahdi Salarian, Xi Xu, Rashid Ansari

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Accurate localization of mobile devices based on camera-acquired visual media information usually requires a search over a very large GPS-referenced image database. This paper proposes an efficient method for limiting the search space for image retrieval engine by extracting and leveraging additional media information about Estimated Positional Error (EP E) to address complexity and accuracy issues in the search, especially to be used for compensating GPS location inaccuracy in dense urban areas. The improved performance is achieved by up to a hundred-fold reduction in the search area used in available reference methods while providing improved accuracy. To test our procedure we created a database by acquiring Google Street View (GSV) images for down town of Chicago. Other available databases are not suitable for our approach due to lack of EP E for the query images. We tested the procedure using more than 200 query images along with EP E acquired mostly in the densest areas of Chicago with different phones and in different conditions such as low illumination and from under rail tracks. The effectiveness of our approach and the effect of size and sector angle of the search area are discussed and experimental results demonstrate how our proposed method can improve performance just by utilizing a data that is available for mobile systems such as smart phones.

Keywords: localization, retrieval, GPS uncertainty, bag of word

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Authors: B. Körner

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This paper compares deviant behaviour in two different readings: 1) as symptomatic for so-called ‘mental illness’ and 2) as part of artistic creation. It analyses works of performance art in the respective frames of psychiatric evaluation and performance studies. This speculative comparison offers an alternative interpretation of mad behaviour beyond pathologisation. It questions the distinction of psychiatric diagnosis, which can contribute to reducing the stigmatisation of mad people. The stigma associated with madness entails exclusion, prejudice, and systemic oppression. Symptoms of psychiatric diagnoses can be considered as behaviour exceptional to the psychological norm. This deviant behaviour constitutes an outsider role which is also defining for the societal role of ‘the artist’, whose transgressions of the norm are expected and celebrated. The research proposes the term ‘artistic exceptionalism’ for this phenomenon. In this study, a set of performance artworks are analysed within the frame of an art-theoretical interpretation and as if they were the basis of a psychiatric assessment. This critical comparison combines the perspective on ‘mental illness’ of mad studies with methods of interpretation used in performance studies. The research employs auto theory and artistic research; interweaving lived experience with scientific theory building through the double role of the author as both performance artist and survivor researcher. It is a distinctly personal and mad thought experiment. The research proposes three major categories of artistic strategies approaching madness: (a) confronting madness (processing and publicly addressing one's own experiences with mental distress through artistic creation), (b) creating critical conditions (conscious or unconscious, voluntary or involuntary creation of crisis situations in order to create an intense experience for a work of art), and (c) symptomatic strategies. This paper focuses on the last of the three categories: symptomatic strategies. These can be described as artistic methods with parallels to forms of coping with and/or symptoms of ‘mental disorders.’ These include, for example feverish activity, a bleak worldview, additional perceptions, an urge for order, and the intensification of emotional experience. The proposed categories are to be understood as a spectrum of approaches that are not mutually exclusive. This research does not aim to diagnose or pathologise artists or their strategies; disease value is neither sought nor assumed. Neither does it intend to belittle psychological suffering, implying that it cannot be so bad if it is productive for artists. It excludes certain approaches that romanticise and/or exoticise mental distress, for example, artistic portrayal of people in mental crisis (e.g., documentary-observational or exoticising depictions) or the deliberate and exaggerated imitation of their forms of expression and behaviour as ‘authentic’ (e.g., Art Brut). These are based on the othering of the Mad and thus perpetuate the social stigma to which they are subjected. By noting that the same deviant behaviour can be interpreted as the opposite in different contexts, this research offers an alternative approach to madness beyond the confines of psychiatry. It challenges the distinction of psychiatric diagnosis and exposes its social constructedness. Hereby, it aims to empower survivors and reduce the stigmatisation of madness.

Keywords: artistic research, mad studies, mental health, performance art, psychiatric stigma

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Authors: Vartan Agopian

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Millions of Syrian families have been displaced since the beginning of the Syrian war, and the negative effects of post-war trauma have shown detrimental effects on the mental health of refugee children. While educational strategies have focused on vocational training and academic achievement, little has been done to include music in the school curriculum to help these children improve their mental health. The literature of music education and psychology, on the other hand, shows the positive effects of music on traumatized children, especially when it comes to dealing with stress. This paper presents a brief literature review of trauma, music therapy, and music in the classroom, after having introduced the Syrian war and refugee situation. Furthermore, the paper highlights the benefits of using music with traumatized children from the literature and offers strategies for teachers (such as singing, playing an instrument, songwriting, and others) to include music in their classrooms to help Syrian refugee children deal with post-war trauma.

Keywords: children, music, refugees, Syria, war

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Authors: Yeimy L. Quintana, Juan G. Zuluaga, Sandra S. Arango

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The comet assay is a method based on electrophoresis that is used to measure DNA damage in cells and has shown important results in the identification of substances with a potential risk to the human population as innumerable physical, chemical and biological agents. With this technique is possible to obtain images like a comet, in which the tail of these refers to damaged fragments of the DNA. One of the main problems is that the image has unequal luminosity caused by the fluorescence microscope and requires different processing to condition it as well as to know how many optimal comets there are per sample and finally to perform the measurements and determine the percentage of DNA damage. In this paper, we propose the design and implementation of software using Image Processing Toolbox-MATLAB that allows the automation of image processing. The software chooses the optimum comets and measuring the necessary parameters to detect the damage.

Keywords: artificial vision, comet assay, DNA damage, image processing

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Authors: Bülent Kantar, Numan Ünaldı

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This paper presents a new method which includes robust and invisible digital watermarking on images that is colored. Colored images are used as watermark. Frequency region is used for digital watermarking. Discrete wavelet transform and discrete stationary wavelet transform are used for frequency region transformation. Low, medium and high frequency coefficients are obtained by applying the two-level discrete wavelet transform to the original image. Low frequency coefficients are obtained by applying one level discrete stationary wavelet transform separately to all frequency coefficient of the two-level discrete wavelet transformation of the original image. For every low frequency coefficient obtained from one level discrete stationary wavelet transformation, watermarks are added. Watermarks are added to all frequency coefficients of two-level discrete wavelet transform. Totally, four watermarks are added to original image. In order to get back the watermark, the original and watermarked images are applied with two-level discrete wavelet transform and one level discrete stationary wavelet transform. The watermark is obtained from difference of the discrete stationary wavelet transform of the low frequency coefficients. A total of four watermarks are obtained from all frequency of two-level discrete wavelet transform. Obtained watermark results are compared with real watermark results, and a similarity result is obtained. A watermark is obtained from the highest similarity values. Proposed methods of watermarking are tested against attacks of the geometric and image processing. The results show that proposed watermarking method is robust and invisible. All features of frequencies of two level discrete wavelet transform watermarking are combined to get back the watermark from the watermarked image. Watermarks have been added to the image by converting the binary image. These operations provide us with better results in getting back the watermark from watermarked image by attacking of the geometric and image processing.

Keywords: watermarking, DWT, DSWT, copy right protection, RGB

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Authors: Boukhatem Mohammed Belkaid, Lahdir Mourad

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In this paper, we propose a new encryption system for security issues meteorological images from Meteosat Second Generation (MSG), which generates 12 images every 15 minutes. The hybrid encryption scheme is based on AES and RSA algorithms to validate the three security services are authentication, integrity and confidentiality. Privacy is ensured by AES, authenticity is ensured by the RSA algorithm. Integrity is assured by the basic function of the correlation between adjacent pixels. Our system generates a unique password every 15 minutes that will be used to encrypt each frame of the MSG meteorological basis to strengthen and ensure his safety. Several metrics have been used for various tests of our analysis. For the integrity test, we noticed the efficiencies of our system and how the imprint cryptographic changes at reception if a change affects the image in the transmission channel.

Keywords: AES, RSA, integrity, confidentiality, authentication, satellite MSG, encryption, decryption, key, correlation

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Authors: Dina Farran, Mark Ashworth, Fiona Gaughran

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Atrial fibrillation (AF), the most prevalent cardiac arrhythmia, is associated with an increased risk of stroke, contributing to heart failure and death. In this project, we aim to improve patient safety by screening for stroke risk among people with AF and co-morbid mental illness. To do so, we started by conducting a systematic review and meta-analysis on prevalence, management, and outcomes of AF in people with Serious Mental Illness (SMI) versus the general population. We then evaluated oral anticoagulation (OAC) prescription trends in people with AF and co-morbid SMI in King’s College Hospital. We also evaluated the association between mental illness severity and OAC prescription in eligible patients in South London and Maudsley (SLaM) NHS Foundation Trust. Next, we implemented an electronic clinical decision support system (eCDSS) consisting of a visual prompt on patient electronic Personal Health Records to screen for AF-related stroke risk in three Mental Health of Older Adults wards at SLaM. Finally, we assessed the feasibility and acceptability of the eCDSS by qualitatively investigating clinicians’ perspectives of the potential usefulness of the eCDSS (pre-intervention) and their experiences and their views regarding its impact on clinicians and patients (post-intervention). The systematic review showed that people with SMI had low reported rates of AF. AF patients with SMI were less likely to receive OAC than the general population. When receiving warfarin, people with SMI, particularly bipolar disorder, experienced poor anticoagulation control compared to the general population. Meta-analysis showed that SMI was not significantly associated with an increased risk of stroke or major bleeding when adjusting for underlying risk factors. The main findings of the first observational study were that among AF patients having a high stroke risk, those with co-morbid SMI were less likely than non-SMI to be prescribed any OAC, particularly warfarin. After 2019, there was no significant difference between the two groups. In the second observational study, patients with AF and co-morbid SMI were less likely to be prescribed any OAC compared to those with dementia, substance use disorders, or common mental disorders, adjusting for age, sex, stroke, and bleeding risk scores. Among AF patients with co-morbid SMI, warfarin was less likely to be prescribed to those having alcohol or substance dependency, serious self-injury, hallucinations or delusions, and activities of daily living impairment. In the intervention, clinicians were asked to confirm the presence of AF, clinically assess stroke and bleeding risks, record risk scores in clinical notes, and refer patients at high risk of stroke to OAC clinics. Clinicians reported many potential benefits for the eCDSS, including improving clinical effectiveness, better identification of patients at risk, safer and more comprehensive care, consistency in decision making and saving time. Identified potential risks included rigidity in decision-making, overreliance, reduced critical thinking, false positive recommendations, annoyance, and increased workload. This study presents a unique opportunity to quantify AF patients with mental illness who are at high risk of severe outcomes using electronic health records. This has the potential to improve health outcomes and, therefore patients' quality of life.

Keywords: atrial fibrillation, stroke, mental health conditions, electronic clinical decision support systems

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Authors: Selina Lin, Justin M Fan, Vincent Zhang, Cindy Chen, Daniel Lam, Jason Yan, Ning Zhang

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Depression is one of the most common mental disorders in the United States, and past studies have shown a concerning increase in the rates of depression in youth populations over time. Furthermore, depression is an especially important issue for Asian Americans because of the anti-Asian violence taking place during the COVID-19 pandemic. While Asian American adolescents are reluctant to seek help for mental health issues, past research has found a prevalence of depressive symptoms in them that have yet to be fully investigated. There have been studies conducted to understand and observe the impacts of multifarious factors influencing the mental well-being of Asian American adolescents; however, they have been generally limited to qualitative investigation, and very few have attempted to quantitatively evaluate the relationship between depression levels and a comprehensive list of factors for those levels at the same time. To better quantify these relationships, this project investigated the prevalence of depression in Asian American teenagers mainly from the Greater Philadelphia Region, aged 12 to 19, and, with an anonymous survey, asked participants 48 multiple-choice questions pertaining to demographic information, daily behaviors, school life, family life, depression levels (quantified by the PHQ-9 assessment), school and family support against depression. Each multiple-choice question was assigned as a factor and variable for statistical and dominance analysis to determine the most influential factors on depression levels of Asian American adolescents. The results were validated via Bootstrap analysis and t-tests. While certain influential factors identified in this survey are consistent with the literature, such as parent-child relationship and peer pressure, several dominant factors were relatively overlooked in the past. These factors include the parents’ relationship with each other, the satisfaction with body image, sex identity, support from the family and support from the school. More than 25% of participants desired more support from their families and schools in handling depression issues. This study implied that it is beneficial for Asian American parents and adolescents to take programs on parents’ relationships with each other, parent-child communication, mental health, and sexual identity. A culturally inclusive school environment and more accessible mental health services would be helpful for Asian American adolescents to combat depression. This survey-based study paved the way for further investigation of effective approaches for helping Asian American adolescents against depression.

Keywords: Asian American adolescents, depression, dominance analysis, t-test, bootstrap analysis

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Authors: Nikk Leavitt, Peter Kellett, Cheryl Currie, Richard Larouche

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Background: Masculinity has been associated with poor mental health outcomes in adult men and is colloquially referred to as toxic. Masculinity is traditionally measured using the Male Role Norms Inventory, which examines behaviors that may be common in men but that are themselves associated with poor mental health regardless of gender (e.g., aggressiveness). The purpose of this study was to examine if masculinity is associated with generalized anxiety among men using this inventory vs. a man’s personal definition of it. Method: An online survey collected data from 1,200 men aged 18-65 across Canada in July 2022. Masculinity was measured using: 1) the Male Role Norms Inventory Short Form and 2) by asking men to self-define what being masculine means. Men were then asked to rate the extent they perceived themselves to be masculine on a scale of 1 to 10 based on their definition of the construct. Generalized anxiety disorder was measured using the GAD-7. Multiple linear regression was used to examine associations between each masculinity score and anxiety score, adjusting for confounders. Results: The masculinity score measured using the inventory was positively associated with increased anxiety scores among men (β = 0.02, p < 0.01). Masculinity subscales most strongly correlated with higher anxiety were restrictive emotionality (β = 0.29, p < 0.01) and dominance (β = 0.30, p < 0.01). When traditional masculinity was replaced by a man’s self-rated masculinity score in the model, the reverse association was found, with increasing masculinity resulting in a significantly reduced anxiety score (β = -0.13, p = 0.04). Discussion: These findings highlight the need to revisit the ways in which masculinity is defined and operationalized in research to better understand its impacts on men’s mental health. The findings also highlight the importance of allowing participants to self-define gender-based constructs, given they are fluid and socially constructed.

Keywords: masculinity, generalized anxiety disorder, race, intersectionality

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Authors: Gabriel G. Gaft, Xayvinay Xiong, Amanda Sunday

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The emergent pandemic from COVID-19 virus has forced people to adjust to major changes. These changes include all elements of family and work life and required people to engage in novel behaviors. For many people, the social norms to which they have been accustomed no longer prevail. Not surprisingly, such enormous changes in daily life have been associated with greater problems in mental health; and research regarding ways in which mental health professionals can support people is more necessary than ever before. It is often useful to assess people’s reactions through surveys and utilize quantitative data to answer questions about coping strategies etc. It is also likely, however, that a host of individual factors are going to contribute to what might be considered 'good' or 'bad' coping mechanisms to a worldwide pandemic. To this end, qualitative studies—where the individual’s subjective experience is highlighted—are likely to provide more vital information for mental health professionals interested in supporting the particular person in front of them. This study reports on qualitative data, where X participants were asked questions about social distancing, coping strategies, and general attitudes towards social changes resulting from the COVID-19 pandemic. Informal interviews were conducted during the months of June-July 2020. Data were analyzed using Interpretative Phenomenological Analyses. Themes were identified first for each participant and then compared across different individual participants. Several findings emerged. First, all participants understood major health messages being imparted by governing bodies such as the CDC and WHO. The researchers feel this finding is important as it suggests health messages are at least being effectively communicated. Second, there was a clear trend for themes which highlighted the conflicting emotions participants felt about the changes they were expected to endure: positive and negative elements were identified, although a participant who had pre-existing conditions placed greater emphasis on the negative elements. One participant who was particularly interested in impression management also exclusively emphasized negative emotions. Third, participants who were able to reevaluate priorities—what Lazarus might call secondary appraisals—experienced social distancing as a positive rather than negative phenomenon. Finally, participants who were able to develop specific strategies—such as boundaries for work and self-care—reported themes of adjustment and contentment. Taken together, these findings suggest mental health practitioners can assist people to adjust more positively through specific techniques focusing on re-evaluation of life priorities and strategic coping skills.

Keywords: COVID-19, pandemic, phenomenology, virus

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Authors: Chueh Chang, Chia-jung Hsieh, Fu-yu Yu, Yu-Hwa Lin

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Background:The majority of women diagnosed with breast cancer undergo treatment involving surgery and radiotherapy or chemotherapy, or both. With these major advances in breast cancer management, many patients still have to deal with short or long-term side effects and psychological distress related to the disease and treatment, which have a substantial impact on their quality of life. The Laughing Qigong Program (LQP) is an interactive laughter program that combines the physical and physiological benefits of laughter with the mental benefits of Chinese qigong. Purpose: In order to improve the quality of life for breast cancer women in the community as well as echoing the WHO 2004 “Promoting Mental Health” for every one. This study focused on how to promote the positive mental health for women of breast cancer through the “laughter program” in Taiwan. During the presentation, how to practice Laughing Qigong will be demonstrated. Method: Using nonequivalent pretest-posttest design, ix-one breast cancer patients were volunteered to enroll in this study from the Taiwan Breast Cancer Alliance (TBCA). Thirty patients were assigned to the experimental group and the other 31 patients were assigned to the control group. The women who were assigned to the experimental group received laughter program one hour per session, once a week, totally 12 sessions. All subjects were tested before and after the intervention on the following: Self-Esteem scale (RSE), Face Scale (FS), Anxiety and pain experience were measured as psychological markers; saliva cortisol (CS) as an immunological marker; blood pressure (BP), heart rate (HR),and heart rate variability (HRV) as physiological markers of the body’s response to stress. Results: After comparing the experimental and control groups, the results revealed that those breast cancer women with “laughing program” their sense of humor were improved, less uncomfortable on self report physical conditions, more positive attitudes toward stress management by using laughter, and had emotional improvement according to the face scale.

Keywords: mental health promotion, breast cancer, laughing Qigong, women

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Authors: Seynabou Toure, Oumar Diop, Kidiyo Kpalma, Amadou S. Maiga

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Color and texture are the two most determinant elements for perception and recognition of the objects in an image. For this reason, color and texture analysis find a large field of application, for example in image classification and segmentation. But, the pioneering work in texture analysis was conducted on grayscale images, thus discarding color information. Many grey-level texture descriptors have been proposed and successfully used in numerous domains for image classification: face recognition, industrial inspections, food science medical imaging among others. Taking into account color in the definition of these descriptors makes it possible to better characterize images. Color texture is thus the subject of recent work, and the analysis of color texture images is increasingly attracting interest in the scientific community. In optical remote sensing systems, sensors measure separately different parts of the electromagnetic spectrum; the visible ones and even those that are invisible to the human eye. The amounts of light reflected by the earth in spectral bands are then transformed into grayscale images. The primary natural colors Red (R) Green (G) and Blue (B) are then used in mixtures of different spectral bands in order to produce RGB images. Thus, good color texture discrimination can be achieved using RGB under controlled illumination conditions. Some previous works investigate the effect of using different color space for color texture classification. However, the selection of the best performing color space in land-sea segmentation is an open question. Its resolution may bring considerable improvements in certain applications like coastline detection, where the detection result is strongly dependent on the performance of the land-sea segmentation. The aim of this paper is to present the results of a study conducted on different color spaces in order to show the best-performing color space for land-sea segmentation. In this sense, an experimental analysis is carried out using five different color spaces (RGB, XYZ, Lab, HSV, YCbCr). For each color space, the Haar wavelet decomposition is used to extract different color texture features. These color texture features are then used for Fusion of Over Segmentation (FOOS) based classification; this allows segmentation of the land part from the sea one. By analyzing the different results of this study, the HSV color space is found as the best classification performance while using color and texture features; which is perfectly coherent with the results presented in the literature.

Keywords: classification, coastline, color, sea-land segmentation

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Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit

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In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.

Keywords: image processing technique, feature detections, surface registrations, capturing multi-view images, Production costs and Manufacturing processes

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Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

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Authors: Sakshi Chopra, Harsimarpreet Kaur, Ashima Nehra

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Objectives: Malingering is fabricating or exaggerating the symptoms of mental or physical disorders for a variety of secondary gains or motives, which may include financial compensation; avoiding work; getting lighter criminal sentences; or simply to attract attention or sympathy. Malingering is different from somatization disorder and factitious disorder. The prevalence of malingering is unknown and difficult to determine. In an estimated study in forensic population, it can reach up to 17% cases. But the accuracy of such estimates is questionable as successful malingerers are not detected and thus, not included. Methods: The case study of a 58 years old, right handed, graduate, pre-morbidly working in a national company with reported history of stroke leading to head injury; cerebral infarction/facial palsy and dementia. He was referred for disability certification so that his job position can be transferred to his son as he could not work anymore. A series of Neuropsychological tests were administered. Results: With a mental age of < 2.5 years; social adaptive functioning was overall < 20 showing profound Mental Retardation, less than 1 year social age in abilities of self-help, eating, dressing, locomotion, occupation, communication, self-direction, and socialization; severely impaired verbal and performance ability, 96% impairment in Activities of Daily Living, with an indication of very severe depression. With inconsistent and fluctuating medical findings and problem descriptions to different health professionals forming the board for his disability, it was concluded that this patient was malingering. Conclusions: Even though it can be easily defined, malingering can be very challenging to diagnosis. Cases of malingering impose a substantial economic burden on the health care system and false attribution of malingering imposes a substantial burden of suffering on a significant proportion of the patient population. Timely, tactful diagnosis and management can help ease this patient burden on the healthcare system. Malingering can be detected by only trained mental health professionals in the clinical setting.

Keywords: disability, India, malingering, neuropsychological assessment

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Authors: Elizabeth O'Brien, Raegan Murphy

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Research suggests that high levels of empathy in individuals with partners with mental health difficulties can lead to improved outcomes for their partner while compromising their own mental health. Specifically, it is proposed that the affective dimension of empathy diminishes resilience to the distress of a partner, whereas cognitive empathy (CE) enhances it. The relationship between different empathy dimensions and psychological resilience measures has not been investigated in partners of people with depression. Psychological inflexibility (PI) is a construct that can be understood as distress intolerance and is suggested to be an important feature of psychological resilience. The current study, therefore, aimed to investigate the differential role of dispositional empathy dimensions in PI for people living with a partner with depression. A cross-sectional design was employed in which 148 participants living with a partner with depression and 45 participants for a comparison sample were recruited using online platforms. Participants completed online surveys with measures relating to demographics, empathy, and PI. Scores were compared between the study and comparison samples. The study sample scored significantly lower for CE and affective empathy (AE) and significantly higher for PI than the comparison sample. Exploratory and regression analyses were run to examine associations between variables within the study sample. Analyses revealed that CE predicted the resilience outcome whilst AE did not. These results suggest that interventions for partners of people with depression that bolster the CE dimension alone may improve mental health outcomes for both members of the couple relationship.

Keywords: affective empathy, cognitive empathy, depression, partners, psychological inflexibility

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Authors: Sabri Serkan Gulluoglu

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It is possible with Geographic Information Systems (GIS) that the information about all natural and artificial resources on the earth is obtained taking advantage of satellite images are obtained by remote sensing techniques. However, determination of unknown sources, mapping of the distribution and efficient evaluation of resources are defined may not be possible with the original image. For this reasons, some process steps are needed like transformation, pre-processing, image enhancement and classification to provide the most accurate assessment numerically and visually. Many studies which present the phases of obtaining and processing of the satellite images have examined in the literature study. The research showed that the determination of the process steps may be followed at this subject with the existence of a common whole may provide to progress the process rapidly for the necessary and possible studies which will be.

Keywords: remote sensing, satellite imaging, gis, computer science, information

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Authors: Helen Coronel, Will Brewer, Peggy Bergeron, Clarissa Hall, Victoria Casson

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Simulation-based training provides the nurse practitioner (NP) student with a safe and controlled environment in which they can practice a real-life scenario. This type of learning fosters critical thinking skills essential to practice. The expectation of this study was that students would have an increase in their competency and confidence after performing the simulation. Approximately 8.4% of Americans suffer from depression. The state of Alabama is ranked 47th out of 50 for access to mental health care. As a result of this significant shortage of mental health providers, primary care providers are frequently put in the position of screening for and treating mental health conditions, such as depression. Family nurse practitioners are often utilized as primary care providers, making their ability to assess, diagnose and treat these disorders a necessary skill. The expected outcome of this simulation is an increase in confidence, competency and the empowerment of the nurse practitioner student’s ability to assess, diagnose and treat a common mood disorder they may encounter in practice. The Kirkpatrick Module was applied for this study. A non-experimental design using descriptive statistical analysis was utilized. The simulation was based on a common psychiatric mood disorder frequently observed in primary care and mental health clinics. Students were asked to watch a voiceover power point presentation prior to their on-campus simulation. The presentation included training on the assessment, diagnosis, and treatment of a patient with depression. Prior to the simulation, the students completed a pre-test, then participated in the simulation, and completed a post-test when done. Apple iPads were utilized to access a simulated health record. Major findings of the study support an increase in students’ competency and confidence when assessing, diagnosing, and treating an adult patient with depression.

Keywords: advanced practice, nurse practitioner, simulation, primary care, depression

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Authors: Joshi Manisha, Shivaram, Anand Vinekar, Tanya Susan Mathews, Yeshaswini Nagaraj

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Retinopathy of prematurity (ROP) is abnormal blood vessel development in the retina of the eye in a premature infant. The principal object of the invention is to provide a technique for detecting demarcation line and ridge detection for a given ROP image that facilitates early detection of ROP in stage 1 and stage 2. The demarcation line is an indicator of Stage 1 of the ROP and the ridge is the hallmark of typically Stage 2 ROP. Thirty Retcam images of Asian Indian infants obtained during routine ROP screening have been used for the analysis. A graphical user interface has been developed to detect demarcation line/ridge and to extract ground truth. This novel algorithm uses multilevel vessel enhancement to enhance tubular structures in the digital ROP images. It has been observed that the orientation of the demarcation line/ridge is normal to the direction of the blood vessels, which is used for the identification of the ridge/ demarcation line. Quantitative analysis has been presented based on gold standard images marked by expert ophthalmologist. Image based analysis has been based on the length and the position of the detected ridge. In image based evaluation, average sensitivity and positive predictive value was found to be 92.30% and 85.71% respectively. In pixel based evaluation, average sensitivity, specificity, positive predictive value and negative predictive value achieved were 60.38%, 99.66%, 52.77% and 99.75% respectively.

Keywords: ROP, ridge, multilevel vessel enhancement, biomedical

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