Search results for: mental images

Authors: Faraji Sepideh

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Nowadays, purchase rate of the smart device is increasing and user authentication is one of the important issues in information security. Alphanumeric strong passwords are difficult to memorize and also owners write them down on papers or save them in a computer file. In addition, text password has its own flaws and is vulnerable to attacks. Graphical password can be used as an alternative to alphanumeric password that users choose images as a password. This type of password is easier to use and memorize and also more secure from pervious password types. In this paper we have designed a more secure graphical password system to prevent shoulder surfing, smudge and brute force attack. This scheme is a combination of two types of graphical passwords recognition based and Cued recall based. Evaluation the usability and security of our proposed scheme have been explained in conclusion part.

Keywords: brute force attack, graphical password, shoulder surfing attack, smudge attack

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Authors: Rocio Murad, Marcela Sanchez, Mariana Calderon Jaramillo, Danny Rivera, Angela Cifuentes, Daniela Roldán, Juan Carlos Rivillas

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Women and girls have specific health needs, but during health pandemics such as COVID19 they are less likely to have access to quality essential health information, commodities and services, or insurance coverage for routine and catastrophic health expenses, especially in rural and marginalized communities. This is compounded by multiple or intersecting inequalities, such as ethnicity, socioeconomic status, disability, age, geographic location, and sexual orientation, among others. Despite concerted collective action, there is a lack of information on the situation of women, adolescents and youth, including gender inequalities exacerbated by the pandemic. Much more needs to be done to amplify the lived realities of women and adolescents in global and national advocacy and policy responses. The COVID 19 pandemic reflects the need for systematic advocacy policies based on the lived experiences of women and adolescents, underpinned by human rights. This research is part of the initiative of Profamilia Association (Solidarity Study), and its objective is twofold: i) to analyze the behavioral changes and immediate expectations of Colombians during the stage of relaxation of the confinement measures decreed by the national government; and ii) to identify the needs, experiences and resilient practices of adolescents and young women during the COVID-19 crisis in Colombia. Descriptive analysis of data collected by Profamilia through the Solidaridad study, an exploratory cross-sectional descriptive study that used subnational level data from a nonprobabilistic sample survey conducted to 1735 adults, between September 01 and 11, 2020. Interviews were conducted with key stakeholders about their experiences during COVID19, under three key axes: i) main challenges for adolescents and young women; ii) examples of what has worked well in responding to the challenge; and iii) how/what services are/should be provided during COVID-19 (and beyond) to address the challenge. Interviewees were selected based on prior mapping of social groups of interest. In total, 23 adolescents and young women participated in the interviews. The results show that people adopted behavioral changes such as wearing masks, avoiding people with symptoms, and reducing mobility, but there was also a doubling of concerns for many reasons, from effects on mental health, sexual health, and unattended reproductive health to the burden of care and working at home. The favorable perception that people had at the beginning of the quarantine about the response and actions of the national and local government to control Covid-19 decreased over the course of the quarantine. The challenges and needs of adolescents and young women were highlighted during the most restrictive measures to contain the COVID-19 pandemic, which resulted in disruptions to daily activities, education and work, as well as restrictions to mobility and social interaction. Concerns raised by participants included: impact on mental health and wellbeing due to disruption of daily life; limitations in access to formal and informal education; food insecurity; migration; loss of livelihoods; lack of access to health information and services; limitations to sexual and reproductive health and rights; insecurity problems; and problems in communication and treatment among household members.

Keywords: COVID-19, changes in behavior, adolescents, women

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Authors: U.B Mahadevswamy UBM, Siraj Ahmed Siraj

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As the title of the paper indicates about brainwaves and its uses for various applications based on their frequencies and different parameters which can be implemented as real time application with the title a smart brain wave sensor system for paralyzed patients. Brain wave sensing is to detect a person's mental status. The purpose of brain wave sensing is to give exact treatment to paralyzed patients. The data or signal is obtained from the brainwaves sensing band. This data are converted as object files using Visual Basics. The processed data is further sent to Arduino which has the human's behavioral aspects like emotions, sensations, feelings, and desires. The proposed device can sense human brainwaves and detect the percentage of paralysis that the person is suffering. The advantage of this paper is to give a real-time smart sensor device for paralyzed patients with paralysis percentage for their exact treatment. Keywords:-Brainwave sensor, BMI, Brain scan, EEG, MCH.

Keywords: Keywords:-Brainwave sensor , BMI, Brain scan, EEG, MCH

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Authors: Jeewan Rai, Kinzang, Yeshi Jigme Choden

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Accumulation of dust on solar panels impacts the overall efficiency and the amount of energy they produce. While various techniques exist for detecting dust to schedule cleaning, many of these methods use MATLAB image processing tools and other licensed software, which can be financially burdensome. This study will investigate the efficiency of a free open-source computer vision library using the YOLO algorithm. The proposed approach has been tested on images of solar panels with varying dust levels through an experiment setup. The experimental findings illustrated the effectiveness of using the YOLO-based image classification method and the overall dust detection approach with an accuracy of 90% in distinguishing between clean and dusty panels. This open-source solution provides a cost effective and accessible alternative to commercial image processing tools, offering solutions for optimizing solar panel maintenance and enhancing energy production.

Keywords: YOLO, openCV, dust detection, solar panels, computer vision, image processing

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Authors: Saleh H. Abud, Z. Hassan, F. K. Yam

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Characteristics of MSM photodetector based on a porous In0.08Ga0.92N thin film were reported. Nanoporous structures of n-type In0.08Ga0.92N/AlN/Si thin films were synthesized by photoelectrochemical (PEC) etching at a ratio of 1:4 of HF:C2H5OH solution for 15 min. The structural and optical properties of pre- and post-etched thin films were investigated. Field emission scanning electron microscope and atomic force microscope images showed that the pre-etched thin film has a sufficiently smooth surface over a large region and the roughness increased for porous film. Blue shift has been observed in photoluminescence emission peak at 300 K for porous sample. The photoluminescence intensity of the porous film indicated that the optical properties have been enhanced. A high work function metals (Pt and Ni) were deposited as a metal contact on the porous films. The rise and recovery times of the devices were investigated at 390 nm chopped light. Finally, the sensitivity and quantum efficiency were also studied.

Keywords: porous InGaN, photoluminescence, SMS photodetector, atomic force microscopy

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Authors: Jinshuo Zhang

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Lucid dreams(LD) are the mental states in which people are aware that they are dreaming, which is a rising interdisciplinary topic among psychologists, neuroscientists and spiritual practitioners. From a phenomenological perspective, this research explores the self-consciousness structure in lucid dreams, particularly focusing on the self-reference structure between lucidity(the observer) and the dream ego(the observed). The main argument of this paper is that the self-structure in lucid dreams is a single-level paradigm. In this paper, the phenomenological characteristics of lucidity in LD are carefully unfolded. The appearance of lucidity is the most significant part of understanding the self-structure and the consciousness in dreams, which is also related to the “Six Bardos practices” in Tibetan Buddhism. In the second section, this research investigates the referential relationship between"lucidity" and "the dream ego" using the phenomenological resource of subjectivity theory, as well as referring to many cases in the psychological labs. Despite the appearance of various consciousness layers in lucid dreams, according to this paper, they are all part of a single-level consciousness paradigm. Dream ego is transparent, and dream lucidity can grasp it directly and thoroughly during LD. This research also responds to some potential criticisms and engages in current debates about the self-structure issue in lucid dreams, as well as discussing some future research prospects for dreams and lucid dreams.

Keywords: lucid dream, self-awareness, phenomenological perspective, high-order theory, one-level consciousness

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Authors: Malkin Valery, Rogaleva Liudmila

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During the last 50-60 years the sports psychology has become firmly established in sports. At the same time, the sport practice brings evidence that it is only beginning to solve some of the most important problems in sports. It is untimely to say that the sports psychology has become a compulsory and efficient part of the sportsman’s preparation. It seems that the further development of the sports psychology can be seen, on the one hand, in the re-orientation of the psychologists from the regulation of the sportsman’s mentality to the process of forming the subject of the sport activity able to take the overall responsibility for the result of the sport activity, able to independently set objectives and to overcome the psychological difficulties that arise in the process of attaining these objectives. In its turn, it will require the change in the very approach to the psychologist’s work. The psychologist and the couch will turn from the specialists in correcting the negative manifestations of the sportsman’s mentality to the specialists in forming the subjects of the sport activity. It will require the creation of the technologies that can form the subjects on all the age-specific stages of the sport activity, that can form the most important psychological qualities (psychological stability, mental reliability, etc.). Getting these technologies will enable the couch to change from the consumer of the psychological knowledge to the immediate participant of the psychological process.

Keywords: sports psychology, subject, sportsman’s preparation, psychological knowledge

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Authors: Zayar Phyo, Ei Chaw Htoon

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In a New-LSB based Steganography method, the Fisher-Yates algorithm is used to permute an existing array randomly. However, that algorithm performance became slower and occurred memory overflow problem while processing the large dimension of images. Therefore, the Text-Based Shuffling algorithm aimed to select only necessary pixels as hiding characters at the specific position of an image according to the length of the input text. In this paper, the enhanced text-based shuffling algorithm is presented with the powered of GPU to improve more excellent performance. The proposed algorithm employs the OpenCL Aparapi framework, along with XORShift Kernel including the Pseudo-Random Number Generator (PRNG) Kernel. PRNG is applied to produce random numbers inside the kernel of OpenCL. The experiment of the proposed algorithm is carried out by practicing GPU that it can perform faster-processing speed and better efficiency without getting the disruption of unnecessary operating system tasks.

Keywords: LSB based steganography, Fisher-Yates algorithm, text-based shuffling algorithm, OpenCL, XORShiftKernel

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Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

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Authors: Salim Ouchtati, Aissa Belmeguenai, Mouldi Bedda

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In this study, we propose an offline system for the recognition of the fragmented handwritten numeric chains. Firstly, we realized a recognition system of the isolated handwritten digits, in this part; the study is based mainly on the evaluation of neural network performances, trained with the gradient backpropagation algorithm. The used parameters to form the input vector of the neural network are extracted from the binary images of the isolated handwritten digit by several methods: the distribution sequence, sondes application, the Barr features, and the centered moments of the different projections and profiles. Secondly, the study is extended for the reading of the fragmented handwritten numeric chains constituted of a variable number of digits. The vertical projection was used to segment the numeric chain at isolated digits and every digit (or segment) was presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits).

Keywords: features extraction, handwritten numeric chains, image processing, neural networks

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Authors: Lan Du, Yan Wang, Hui Dai

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Synthetic aperture radar (SAR) image change detection has recently become a challenging problem owing to the existence of speckle noises. In this paper, an unsupervised distribution-free change detection for SAR image based on scale-invariant feature transform (SIFT) keypoints and segmentation is proposed. Firstly, the noise-robust SIFT keypoints which reveal the blob-like structures in an image are extracted in the log-ratio image to reduce the detection range. Then, different from the traditional change detection which directly obtains the change-detection map from the difference image, segmentation is made around the extracted keypoints in the two original multitemporal SAR images to obtain accurate changed region. At last, the change-detection map is generated by comparing the two segmentations. Experimental results on the real SAR image dataset demonstrate the effectiveness of the proposed method.

Keywords: change detection, Synthetic Aperture Radar (SAR), Scale-Invariant Feature Transformation (SIFT), segmentation

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Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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Authors: Parisa Javid

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In architecture, daylight contributes to humans' mental and physical well-being and reduces the consumption of fossil fuels. Accordingly, Iran's rich architecture has valuable achievements and experiences that should be recognized and introduced to the Iranian and international architecture communities. There are many ways to reduce energy consumption in buildings, but electricity accounts for a large part of that consumption. Lighting up spaces with natural light is a significant factor in reducing energy consumption and preventing electricity dissipation. Aside from being expensive, electric lighting systems cause excessive heat and physical injury (eyes). This study is based on library records and documents. Modern lighting systems are used to reduce energy consumption in the interior of a building to allow for optimal transmission of natural light. It discusses how to use natural light in architecture and the benefits of natural light in buildings. Solar energy can be used more efficiently, and electrical power can be saved in residential, administrative, commercial, and educational buildings by using new methods such as light tubes and mirror directors. Modern lighting systems, natural light, and reduced energy consumption are keywords for these systems, which quickly return their investment.

Keywords: modern lighting systems, natural light, reduced energy consumption

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Authors: Danielle Page

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Foregoing studies, statistics, and medical evaluations have established a relationship between Posttraumatic stress disorder (PTSD) and criminal justice involvement in Vietnam veterans. War is highly trauma inducing and can leave combat veterans with mental disorders ranging from psychopathic thoughts to suicidal ideation. The majority of those suffering are unaware that they have PTSD, and as a coping mechanism, they often turn to self isolation. Beyond isolation, many veterans with symptomatic PTSD turn to aggression and substance abuse to cope with their internal agony. The most common crimes committed by veterans with PTSD fall into the assault and drug/alcohol abuse categories. Thus, a relationship is established between veteran populations and the criminal justice system. This dissertation aims to define the relationship between PTSD and criminal justice involvement in veterans, explore the mediating factors in this relationship, and analyze numerous court cases in this subject area. Further, it will examine the ways in which crime rates can be reduced for veterans with symptoms of PTSD. This ranges from the improvement of healthcare systems to the implementation of special courts to handle veteran cases.

Keywords: psychotraumatology, forensic psychology, PTSD, vietnam veterans

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Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

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The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8

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Authors: Eiji Nakamachi, Tsuyoshi Eguchi, Sayo Yamamoto, Yusuke Morita, H. Sakamoto

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In this study, we aim to reveal the relationship between the meniscal tearing and the articular cartilage injury of knee joint by using the dynamic explicit finite element (FE) method. Meniscal injuries reduce its functional ability and consequently increase the load on the articular cartilage of knee joint. In order to prevent the induction of osteoarthritis (OA) caused by meniscal injuries, many medical treatment techniques, such as artificial meniscus replacement and meniscal regeneration, have been developed. However, it is reported that these treatments are not the comprehensive methods. In order to reveal the fundamental mechanism of OA induction, the mechanical characterization of meniscus under the condition of normal and injured states is carried out by using FE analyses. At first, a FE model of the human knee joint in the case of normal state – ‘intact’ - was constructed by using the magnetron resonance (MR) tomography images and the image construction code, Materialize Mimics. Next, two types of meniscal injury models with the radial tears of medial and lateral menisci were constructed. In FE analyses, the linear elastic constitutive law was adopted for the femur and tibia bones, the visco-hyperelastic constitutive law for the articular cartilage, and the visco-anisotropic hyperelastic constitutive law for the meniscus, respectively. Material properties of articular cartilage and meniscus were identified using the stress-strain curves obtained by our compressive and the tensile tests. The numerical results under the normal walking condition revealed how and where the maximum compressive stress occurred on the articular cartilage. The maximum compressive stress and its occurrence point were varied in the intact and two meniscal tear models. These compressive stress values can be used to establish the threshold value to cause the pathological change for the diagnosis. In this study, FE analyses of knee joint were carried out to reveal the influence of meniscal injuries on the cartilage injury. The following conclusions are obtained. 1. 3D FE model, which consists femur, tibia, articular cartilage and meniscus was constructed based on MR images of human knee joint. The image processing code, Materialize Mimics was used by using the tetrahedral FE elements. 2. Visco-anisotropic hyperelastic constitutive equation was formulated by adopting the generalized Kelvin model. The material properties of meniscus and articular cartilage were determined by curve fitting with experimental results. 3. Stresses on the articular cartilage and menisci were obtained in cases of the intact and two radial tears of medial and lateral menisci. Through comparison with the case of intact knee joint, two tear models show almost same stress value and higher value than the intact one. It was shown that both meniscal tears induce the stress localization in both medial and lateral regions. It is confirmed that our newly developed FE analysis code has a potential to be a new diagnostic system to evaluate the meniscal damage on the articular cartilage through the mechanical functional assessment.

Keywords: finite element analysis, hyperelastic constitutive law, knee joint injury, meniscal tear, stress concentration

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Authors: Luo Jin China, Jin Fang

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Countryside has been generally recognized and regarded as a characteristic symbol which presents in human memory for a long time. As a result of the change of times, because of it’s failure to meet the growing needs of the growing life and mental decline, the vast rural area began to decline. But their history feature image which accumulated by the ancient tradition provides people with the origins of existence on the spiritual level, such as "identity" and "belonging", makes people closer to the others in the spiritual and psychological aspects of a common experience about the past, thus the sense of a lack of culture caused by the losing of memory symbols is weakened. So, in the modernization process, how to repair its vitality and transform and planning it in a sustainable way has become a hot topics in architectural and urban planning. This paper aims to break the constraints of disciplines, from the perspective of interdiscipline, using the research methods of systems science to analyze and discuss the theories and methods of rural form factors, which based on the viewpoint of memory in psychology. So, we can find a right way to transform the Rural to give full play to the role of the countryside in the actual use and the shape of history spirits.

Keywords: rural, sustainable renovation, restoration, psychology, memory

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Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina

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Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.

Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle

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Authors: Ali Dulla

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This paper introduces a new dataset (and the methodology used to generate it) based on a wide range of historical Arabic documents containing clean data simple and homogeneous-page layouts. The experiments are implemented on printed and handwritten documents obtained respectively from some important libraries such as Qatar Digital Library, the British Library and the Library of Congress. We have gathered and commented on 150 archival document images from different locations and time periods. It is based on different documents from the 17th-19th century. The dataset comprises differing page layouts and degradations that challenge text line segmentation methods. Ground truth is produced using the Aletheia tool by PRImA and stored in an XML representation, in the PAGE (Page Analysis and Ground truth Elements) format. The dataset presented will be easily available to researchers world-wide for research into the obstacles facing various historical Arabic documents such as geometric correction of historical Arabic documents.

Keywords: dataset production, ground truth production, historical documents, arbitrary warping, geometric correction

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Authors: Nagwa Abouserie Soliman

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The Victorian era, which started with the reign of Queen Victoria from June 1837 to January 1901, could be considered as one of the most significant eras that had a crucial impact which formed contemporary British life despite the fact that with the rise of the British empire many negative aspects surfaced, namelysocial inequalities such as class differences, child labor, population increase and poverty due to the industrial revolution. Charles Dickens was one of the most prominent writers of the Victorian era who perceived the hypocrisy of the Victorian mores. The appropriate researchstyle that was chosen for this literary analysis is a qualitative research method in which the researcher used the conceptual approach to analyse theDickensian characterisation andwriting style through diction, narrative voice, and images. The aim of this paper is to argue that Charles Dickens inGreat Expectations (1861) was highly satirical of the Victorian mores, as he uses a lot of sharp irony-to satirize various Victorian traditions such as class divisions, the justice system, the poor working class, and the upper-class snobbery that he thought are inhumane and unjust.

Keywords: victorian, child labour, poverty, class division, snobbery

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Authors: Melasurej C. Francisco, Sophia D. Rusit

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Old age is a record of one’s own life; this is the crucial phase for most. However, there are individuals who believe that old people retain self-efficacy and self-worth throughout their existence. Geriatric institutions focus on the health of elderly, in which they have been supported with medicines and therapies by clinician thus, indicating that these may suffice physical, emotional, and mental health of the elderly. This study focuses on (1) Describing the level or degree of self-efficacy; (2) Recognizing the extent of self-worth; (3) Determining the significant relationship between self-efficacy and self-worth. It is a mixed method design. A combination of correlational research and in-depth interview. Purposive sampling technique was used to select participants, considering that this assay focused on elderly in geriatric institutions, it follows that respondents and participants are at least sixty years of age and must be living inside the institution. 121 senior citizens took part in this study. Scores from both General Self-Efficacy Scale (GSE) and Rosenberg Self-Esteem Scale (RSES) showed varying levels of self-efficacy and self-worth. SE had μ=28.099, σ=6.6262, σ²=43.9067 while; SW had μ=14.9669, σ=5.3789, σ²28.9322 which denotes that rₒbₜ (121)=0.3164 is higher than rcᵢₜ which is 0.150. Although this exhibits the positive moderate correlation between SE and SW, the relationship between variables is weak. Likewise, the pᵥₐₗᵤₑ (pᵥₐₗᵤₑ=0.000406) is lower than the significance level alpha=0.01, thus, rejecting the null hypothesis, and accepting the alternative hypothesis.

Keywords: elderly, geriatric, self-efficacy, self-worth

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Authors: Shweta Jha, Nandita Chaube

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The concept of self has a major role to play in the study of personality which drives the current study in its present form. This is a case of Miss S, a 17-year-old Hindu, currently in eleventh standard, with no family history of mental illness but with a past history of inability to manage relationships, multiple emotional and sexual relationships, repeated self harming behaviour, and sexual abuse over a period of 2 months at the age of 10 years. She comes with a psychiatric history of one episode of dissociative fall followed by a stressful event which left the patient with many psychological disturbances matching the criterion of Cluster B and C traits. Current episode precipitated due to the relationship failure, predisposing factor is her personality traits, and poor social and family support. Considering the patient’s aspiration for positivity and demand of the therapy, ventilation sessions were carried out which made her capable of understanding and dealing with her negative emotions, also strengthened mother child bond, helped her maintain meaningful and healthy relationships, also helped her increase her problem solving ability and adaptive coping skills making her feel more positive and acceptable towards herself, family members and others.

Keywords: cluster B and C traits, personality, therapy, self

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Authors: Jessie Fazel, Kristen Smith

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Human trafficking is a multi-billion-dollar criminal industry that affects 24.9 million people around the world. There are several different types of trafficking, the most common being sex trafficking, labor trafficking, and domestic servitude. Survival sex is common in the pediatric population, as they engage in sex for food, a place to sleep, or other basic needs. Statistics show that health care workers are at a unique advantage to help identify victims and get them the help they need, as 88% of trafficked victims encounter a health care worker while being trafficked. Unfortunately, victims don’t usually self-identify that they are being trafficked and the situations they face can vary dramatically. It is imperative to remember that traditional red flags are not always present in the pediatric population. Risk factors and red flags with their history and physical exam are one of the best indicators that health care providers need to be vigilant in looking at. There are numerous barriers for disclosure in the healthcare setting. Periods of time before and after disclosure are often emotionally difficult and could be dangerous for the victim. It is extremely important to have a plan in place for intervention if the victim does disclose trafficking. A trauma informed approach to medical and mental health interventions, that focus on safety, are vital in this population. This is happening where you live and you can make a difference in their lives.

Keywords: human trafficking, public health, emergency medicine, sexual health

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Tran Trong Thang, Nguyen Phan Kien, Trinh Quang Duc

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The phased-array ultrasound transducer types are utilities for medical ultrasonography as well as optical imaging. However, their discontinuity characteristic limits the applications due to the artifacts contaminated into the reconstructed images. Because of the effects of the ultrasound pressure field pattern to the echo ultrasonic waves as well as the optical modulated signal, the side lobes of the focused ultrasound beam induced by discontinuity of the phased-array ultrasound transducer might the reason of the artifacts. In this paper, a simple method in approach of numerical simulation was used to investigate the limitation of discontinuity of the elements in phased-array ultrasound transducer and their effects to the ultrasound pressure field. Take into account the change of ultrasound pressure field patterns in the conditions of variation of the pitches between elements of the phased-array ultrasound transducer, the appropriated parameters for phased-array ultrasound transducer design were asserted quantitatively.

Keywords: phased-array ultrasound transducer, sound pressure pattern, discontinuous sound field, numerical visualization

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Authors: Hooshmand Kalayeh

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The human brain consists of reptilian, mammalian, and thinking brain. And mind consists of conscious, subconscious, and unconscious parallel neural-net programs. The primary objective of this paper is to propose a methodology for quantitative analysis of neural-nets associated with these mental activities in the neocortex. The secondary objective of this paper is to suggest a methodology for quantitative analysis of presence; the proposed methodologies can be used as a first-step to measure, monitor, and understand consciousness and presence. This methodology is based on Neural-Networks (NN), number of neuron in each NN associated with consciousness, subconsciouness, and unconsciousness, and number of neurons in neocortex. It is assumed that the number of neurons in each NN is correlated with the associated area and volume. Therefore, online and offline visualization techniques can be used to identify these neural-networks, and online and offline measurement methods can be used to measure areas and volumes associated with these NNs. So, instead of the number of neurons in each NN, the associated area or volume also can be used in the proposed methodology. This quantitative analysis and associated online and offline measurements and visualizations of different Neural-Networks enable us to rewire the connections in our brain for a more balanced living.

Keywords: brain, mind, consciousness, presence, sub-consciousness, unconsciousness, skills, concentrations, attention

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Authors: Noah Erskine, Jaime Barratt, John Cairney

Abstract:

The current study aims to provide an in-depth analysis and extension of the Environmental Stress Hypothesis (ESH) framework, focusing on the complex interplay between poor motor skills and internalising problems like anxiety and depression. Using an integrative research review methodology, this study synthesizes findings from 38 articles, both empirical and theoretical, building upon the foundational work of the model. The hypothesis posits that poor motor skills serve as a primary stressor, leading to internalising problems through various secondary stressors. A rigorous comparison of data was conducted, considering study design, findings, and methodologies - while giving special attention to variables such as age, sex, and comorbidities. The study also enhances the ESH framework by introducing resource buffers, including optimism and familial support, as additional influencing factors. This multi-level approach yields a more nuanced and comprehensive ESH framework, highlighting the need for future studies to consider intersectional variables and how they may vary across various life stages.

Keywords: motor coordination, mental health, developmental coordination disorders, paediatric comorbidities, obesity, peer problems

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Authors: Godwin Makaudze

Abstract:

The majority of women in contemporary Zimbabwe continue to hold marginalised and insignificant positions in society and to be accorded negative and stereotyped images in literature. In light of this, government and civic organisations and even writers channel many resources, time, and efforts towards the emancipation of the female gender. Using the Africana womanist and socio-historical literary theories and focussing on two post-colonial novels, this paper re-engages the dis-empowerment of women in contemporary Zimbabwe, examining the believed causes and suggested solutions. The paper observes that the writers whip the already whipped by blaming patriarchy, African men and cultural practices as the underlying causes of such a sorry state of affairs while at the same time celebrating war against all these, as well as education, unity among women, Christianity and single motherhood as panaceas to the problem. The paper concludes that the writers’ anger is misdirected as they have fallen trap to the very popular yet mythical victim-blame motif espoused by many writers who focus on Shona people’s problems.

Keywords: cultural practices, female dis-empowerment, patriarchy, Shona novel, solutions, Zimbabwe

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Authors: Saba Hasanvandi, Molok Khademi Ashkezari, Niloofar Esmaieli

Abstract:

The research purpose was to assess the effectiveness of metacognitive therapy in metacognitive beliefs, anxiety and social phobia of male students studying in the high schools of Dargaz City. The sample comprised 30 students who were randomly selected and assigned to the experimental and control groups. The kind of this study was experimental study with pre-ops and follow-up stages. Subjects filled out metacognitive beliefs, anxiety and social phobia questionnaires. The experimental group underwent 10 sessions of therapeutic metacognitive sessions. The group therapy was conducted for ten, weekly, 90-minute sessions. Mankova analysis was utilized to analyze the data. Results revealed that metacognitive group therapy decreased metacognitive beliefs (P=0.007), anxiety (P<0.001) and social phobia (P=<0.017) in the experimental group as compared to the control group. Furthermore, the effectiveness of group metacognitive therapy was stable and consistent after one month of time interval. The results of present study can be effective for mental health professional in reaching a better understanding of anxiety and social phobia.

Keywords: group metacognitive therapy, metacognitive beliefs, anxiety, social phobia, high school students

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Authors: Eleni Karasavvidou

Abstract:

Social and anthropological research, parallel to Gender Studies, highlighted the relationship between social structures and symbolic forms as an important field of interaction and recording of 'social trends.' Since the study of representations can contribute to the understanding of the social functions and power relations, they encompass. This ‘mirage,’ however, has not only to do with the representations themselves but also with the ways they are received and the film or critical narratives that are established as dominant or alternative. Cinema and the criticism of its cultural products are no exception. Even in the rapidly changing media landscape of the 21st century, movies remain an integral and widespread part of popular culture, making films an extremely powerful means of 'legitimizing' or 'delegitimizing' visions of domination and commonsensical gender stereotypes throughout society. And yet it is film criticism, the 'language per se,' that legitimizes, reinforces, rewards and reproduces (or at least ignores) the stereotypical depictions of female roles that remain common in the realm of film images. This creates the need for this issue to have emerged (also) in academic research questioning gender criteria in film reviews as part of the effort for an inclusive art and society. Qualitative content analysis is used to examine female roles in selected Oscar-nominated films against their reviews from leading websites and newspapers. This method was chosen because of the complex nature of the depictions in the films and the narratives they evoke. The films were divided into basic scenes depicting social functions, such as love and work relationships, positions of power and their function, which were analyzed by content analysis, with borrowings from structuralism (Gennette) and the local/universal images of intercultural philology (Wierlacher). In addition to the measurement of the general ‘representation-time’ by gender, other qualitative characteristics were also analyzed, such as: speaking time, sayings or key actions, overall quality of the character's action in relation to the development of the scenario and social representations in general, as well as quantitatively (insufficient number of female lead roles, fewer key supporting roles, relatively few female directors and people in the production chain and how they might affect screen representations. The quantitative analysis in this study was used to complement the qualitative content analysis. Then the focus shifted to the criteria of film criticism and to the rhetorical narratives that exclude or highlight in relation to gender identities and functions. In the criteria and language of film criticism, stereotypes are often reproduced or allegedly overturned within the framework of apolitical "identity politics," which mainly addresses the surface of a self-referential cultural-consumer product without connecting it more deeply with the material and cultural life. One of the prime examples of this failure is the Bechtel Test, which tracks whether female characters speak in a film regardless of whether women's stories are represented or not in the films analyzed. If perceived unbiased male filmmakers still fail to tell truly feminist stories, the same is the case with the criteria of criticism and the related interventions.

Keywords: representations, context analysis, reviews, sexist stereotypes

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