Search results for: mental health detection

Authors: Maleh Yassine, Ezzati Abdellah

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Wireless Sensor Networks (WSNs) are currently used in different industrial and consumer applications, such as earth monitoring, health related applications, natural disaster prevention, and many other areas. Security is one of the major aspects of wireless sensor networks due to the resource limitations of sensor nodes. However, these networks are facing several threats that affect their functioning and their life. In this paper we present security attacks in wireless sensor networks, and we focus on a review and analysis of the recent Intrusion Detection schemes in WSNs.

Keywords: wireless sensor networks, security attack, denial of service, IDS, cluster-based model, signature based IDS, hybrid IDS

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Authors: Amer Dawoud, Jesy Motchaalangaram, Arati Biswakarma, Wujan Mio, Karl Wallace

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The development of an embedded miniaturized drone-based system for remote detection of Chemical Warfare Agents (CWA) is proposed. The paper focuses on the software/hardware system design of the electrochemical Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV) signal processing for future deployment on drones. The paper summarizes the progress made towards hardware and electrochemical signal processing for signature detection of CWA. Also, the miniature potentiostat signal is validated by comparing it with the high-end lab potentiostat signal.

Keywords: drone-based, remote detection chemical warfare agents, miniaturized, potentiostat

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Authors: Waqqas-ur-Rehman Butt, Martin Servin, Marion Pause

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In recent years, object detection has gained much attention and very encouraging research area in the field of computer vision. The robust object boundaries detection in an image is demanded in numerous applications of human computer interaction and automated surveillance systems. Many methods and approaches have been developed for automatic object detection in various fields, such as automotive, quality control management and environmental services. Inappropriately, to the best of our knowledge, object detection under illumination with shadow consideration has not been well solved yet. Furthermore, this problem is also one of the major hurdles to keeping an object detection method from the practical applications. This paper presents an approach to automatic object detection in images under non-standardized environmental conditions. A key challenge is how to detect the object, particularly under uneven illumination conditions. Image capturing conditions the algorithms need to consider a variety of possible environmental factors as the colour information, lightening and shadows varies from image to image. Existing methods mostly failed to produce the appropriate result due to variation in colour information, lightening effects, threshold specifications, histogram dependencies and colour ranges. To overcome these limitations we propose an object detection algorithm, with pre-processing methods, to reduce the interference caused by shadow and illumination effects without fixed parameters. We use the Y CrCb colour model without any specific colour ranges and predefined threshold values. The segmented object regions are further classified using morphological operations (Erosion and Dilation) and contours. Proposed approach applied on a large image data set acquired under various environmental conditions for wood stack detection. Experiments show the promising result of the proposed approach in comparison with existing methods.

Keywords: image processing, illumination equalization, shadow filtering, object detection

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Authors: Samaneh Abedini, Diana Coholic

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The transition from adolescence into adulthood involves many changes that result in increased vulnerability to psychological challenges. This developmental stage can be especially stressful for female youth living in underserviced regions. If mental health problems are left untreated in socially marginalized youth, these challenges can extend into adulthood. We know that a lack of access to mental health services and supports can influence adolescents’ psycho-social development and well-being, while resilience and emotion regulation can help them cope with these challenges. Feasible therapeutic programs can play a significant role in assisting youth in developing these characteristics and skills. Mindfulness-Based Cognitive Therapy for Children (MBCT-C) and Holistic Art-Based Program (HAP) are two examples of mindfulness-based interventions (MBIs) that address emotion regulation, coping strategies, and resilience in marginalized youth. While each program’s beneficial effects have been documented, there is a lack of research comparing MBIs with youth, within underserviced geographical locations, and across different cultures. In this study, the sample was 42 female youth between the ages of 12 and 17 years from Iran. 42 female youth from the Elm o Honar High School, located in rural parts of Iran, Isfahan province, have been enrolled in the study. The participants were assigned to one of the MBIs (three MBCT-C experimental groups (n=20) and three HAP experimental groups (n=22)). All participants completed measures including the Child and Youth Resilience Measure-28 (CYRM-28), Child and Adolescent Mindfulness Measure (CAMM), and Difficulties in Emotion Regulation Scale (DERS) at baseline and post-intervention. At the end of intervention, the MBCT-C and HAP experimental groups showed significant changes in resilience and emotion regulation. However, the changes in resilience in HAP groups were not significant; the participants in MBCT-C experimental groups showed significant improvement in resilience. The study provided initial evidence that mindfulness-based intervention can be potentially beneficial for improving mental health status in marginalized Iranian female youth living in the middle east culture.

Keywords: benefits, female, marginalized, mindfulness, youth

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Authors: Hung-Chun Lin, Tzu-Yuan Chao

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As the population aging has become an inevitable trend globally, issues of improving the well-being of elderly people in urban areas have been a challenging task for urban planners. Recent studies of ageing trend have also expended to explore the relationship between the built environment and mental condition of elderly people. These studies have proved that even though the built environment may not necessarily play the decisive role in affecting mental health, it can have positive impacts on individual mental health by promoting social linkages and social networks among older adults. There has been a great amount of relevant research examined the impact of the built environment attributes on depression in the elderly; however, most were conducted in the Western countries. Little attention has been paid in Asian cities with contrarily high density and mix-use urban contexts such as Taiwan regarding how the built environment attributes related to depression in elderly people. Hence, more empirical cross-principle studies are needed to explore the possible impacts of Asia urban characteristics on older residents’ mental condition. This paper intends to focus on Tainan city, the fourth biggest metropolis in Taiwan. We first analyze with data from National Health Insurance Research Database to pinpoint the empirical study area where residing most elderly patients, aged over 65, with depressive disorders. Secondly, we explore the relationship between specific attributes of the built environment collected from previous studies and elderly individuals who suffer from depression, under different socio-cultural and networking circumstances. To achieve the results, the research methods adopted in this study include questionnaire and database analysis, and the results will be proceeded by correlation analysis. In addition, through literature review, by generalizing the built environment factors that have been used in Western research to evaluate the relationship between built environment and older individuals with depressive disorders, a set of local evaluative indicators of the built environment for future studies will be proposed as well. In order to move closer to develop age-friendly cities and improve the well-being for the elderly in Taiwan, the findings of this paper can provide empirical results to grab planners’ attention for how built environment makes the elderly feel and to reconsider the relationship between them. Furthermore, with an interdisciplinary topic, the research results are expected to make suggestions for amending the procedures of drawing up an urban plan or a city plan from a different point of view.

Keywords: built environment, depression, elderly, Tainan

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Authors: Mahmut Yildirim

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This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

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Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

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The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

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Authors: Yuki Matsumoto, Yuma Ishimoto

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Cognitive Behavior Therapy (CBT) with children has shown effective application to various problems such as anxiety and depression. Although there are barriers to access to mental health services including lack of professional services in communities and parental concerns about stigma, school has a significant role to address children’s health problems. Schools are regarded as a suitable arena for prevention and early intervention of mental health problems. In this line, CBT can be adaptable to school education and useful to enhance students’ social and emotional skills. However, Japanese school curriculum is rigorous so as to limit available time for implementation of CBT in schools. This paper describes Brief Cognitive Behavior Therapy (BCBT) with children in a Japanese school setting. The program has been developed in order to facilitate acceptability of CBT in schools and aimed to enhance students’ skills to manage anxiety and difficult behaviors. The present research used a single arm design in which 30 students aged 9-10 years old participated. The authors provided teachers a CBT training workshop (two hours) at two primary schools in Tokyo metropolitan area and recruited participants in the research. A homeroom teacher voluntarily delivered a 6-session BCBT program (15 minutes each) in classroom periods which is called as Kaerinokai, a meeting before leaving school. Students completed a questionnaire sheet at pre- and post-periods under the supervision of the teacher. The sheet included the Spence Child Anxiety Scale (SCAS), the Depression Self-Rating Scale for Children (DSRS), and the Strengths and Difficulties Questionnaire (SDQ). The teacher was asked for feedback after the completion. Significant positive changes were found in the total and five of six sub-scales of the SCAS and the total difficulty scale of the SDQ. However, no significant changes were seen in Physical Injury Fear sub-scale of the SCAS, in the DSRS or the Prosocial sub-scale of the SDQ. The effect sizes are mostly between small and medium. The teacher commented that the program was easy to use and found positive changes in classroom activities and personal relationships. This preliminary research showed the feasibility of the BCBT in a school setting. The results suggest that the BCBT offers effective treatment for reduction in anxiety and in difficult behaviors. There is a good prospect of the BCBT suggesting that BCBT may be easier to be delivered than CBT by Japanese teachers to promote child mental health. The study has limitations including no control group, small sample size, or a short teacher training. Future research should address these limitations.

Keywords: brief cognitive behavior therapy, cognitive behavior therapy, mental health services in schools, teacher training workshop

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Authors: Jianrong Wu, Xuan Fu, Akihiro Higashi, Zhiming Tan

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CMOS image sensors with a rolling shutter are used broadly in the digital cameras embedded in mobile devices. The rolling shutter suffers the flicker artifacts from the fluorescent lamp, and it could be observed easily. In this paper, the characteristics of illumination flicker in motion case were analyzed, and two efficient detection methods based on matching fragment selection were proposed. According to the experimental results, our methods could achieve as high as 100% accuracy in static scene, and at least 97% in motion scene.

Keywords: illumination flicker, embedded camera, rolling shutter, detection

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Authors: Ryan Tehini

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The purpose of this paper is to explore the value of practical experience with Autism Spectrum Disorder (ASD) as a microcosm of mental disorders, in psychology students’ attempt to fully understand it in all of its intricacies. The study follows a one-year program where students of psychology volunteer at a school for Autistic children of ages 3-18. The individual levels of experience with, and theoretical understanding of, ASD varies measurably amongst the volunteers; these volunteers are then intermittently interviewed, observed and surveyed throughout the program in order to determine any decline or growth in their understanding of Autism Spectrum Disorder. A panel of professionals all of whom are active in the world of ASD (headmasters of Autistic schools, psychologists, child development specialists, special needs teachers, parents of autistic children and Occupational Therapists) were used specifically for this study, in order to develop the guideline for understanding ASD that will be used comparatively against the information gained from the volunteers in order to establish the individual results. The paper concludes by illustrating how psychology has a responsibility to the community to understand disorders past what is academic and theoretical, and how increasing student experience with a disorder can aid in a more holistic psychological approach to mental disorders in the future.

Keywords: autism, mental disorders, practical experience, psychology

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Authors: R. Rezaeipour, A. R. Mehrabi

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Recent increase of the DGs and microgrids in distribution systems, disturbs the tradition structure of the system. Coordination between protection devices in such a system becomes the concern of the network operators. This paper presents a new method for fault location detection in the active distribution networks, independent of the fault type or its resistance. The method uses synchronized voltage and current measurements at the interconnection of DG units and is able to adapt to changes in the topology of the system. The method has been tested on a 38-bus distribution system, with very encouraging results.

Keywords: fault location detection, active distribution system, micro grids, network operators

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Authors: Jianuo Sun, Jinghan Wang, Sirui Zhang, Chenhan Xu, Hongxia Hao, Hong Zhou

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In recent years, the diversification and industrialization of drug-related crimes have posed significant threats to public health and safety globally. The widespread and increasingly younger demographics of drug users and the persistence of drug-impaired driving incidents underscore the urgency of this issue. Drug detection, a specialized forensic activity, is pivotal in identifying and analyzing substances involved in drug crimes. It relies on pharmacological and chemical knowledge and employs analytical chemistry and modern detection techniques. However, current drug detection methods are limited by their inability to perform semi-quantitative, real-time field analyses. They require extensive, complex laboratory-based preprocessing, expensive equipment, and specialized personnel and are hindered by long processing times. This study introduces an alternative approach using nucleic acid aptamers and Aggregation-Induced Emission (AIE) technology. Nucleic acid aptamers, selected artificially for their specific binding to target molecules and stable spatial structures, represent a new generation of biosensors following antibodies. Rapid advancements in AIE technology, particularly in tetraphenyl ethene-based luminous, offer simplicity in synthesis and versatility in modifications, making them ideal for fluorescence analysis. This work successfully synthesized, isolated, and purified an AIE molecule and constructed a probe comprising the AIE molecule, nucleic acid aptamers, and exonuclease for cocaine detection. The probe demonstrated significant relative fluorescence intensity changes and selectivity towards cocaine over other drugs. Using 4-Butoxytriethylammonium Bromide Tetraphenylethene (TPE-TTA) as the fluorescent probe, the aptamer as the recognition unit, and Exo I as an auxiliary, the system achieved rapid detection of cocaine within 5 mins in aqueous and urine, with detection limits of 1.0 and 5.0 µmol/L respectively. The probe-maintained stability and interference resistance in urine, enabling quantitative cocaine detection within a certain concentration range. This fluorescent sensor significantly reduces sample preprocessing time, offers a basis for rapid onsite cocaine detection, and promises potential for miniaturized testing setups.

Keywords: drug detection, aggregation-induced emission (AIE), nucleic acid aptamer, exonuclease, cocaine

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Authors: Zhongfei Cai, Hui He, Changsheng Li

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This paper studied in the automatic repeat request (ARQ) transmission technique in Mars detection telecommunications system. An ARQ method applied to proximity-1 space link protocol was proposed by this paper. In order to ensure the efficiency of data reliable transmission, this ARQ method combined these different ARQ maneuvers characteristics. Considering the Mars detection communication environments, this paper analyzed the characteristics of the saturation throughput rate, packet dropping probability, average delay and energy efficiency with different ARQ algorithms. Combined thus results with the theories of ARQ transmission technique, an ARQ transmission project in Mars detection telecommunications system was established. The simulation results showed that this algorithm had excellent saturation throughput rate and energy efficiency with low complexity.

Keywords: ARQ, mars, CCSDS, proximity-1, deepspace

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Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: A. Sacko, H. Nyoni, T. A. M. Msagati, B. Ntsendwana

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Carbon based materials to target environmental pollutants have become increasingly recognized in science. Electrochemical methods using carbon based materials are notable methods for high sensitive detection of organic pollutants in air. It is therefore in this light that exfoliated graphite electrode was fabricated for electrochemical analysis of PAHs in urban atmospheric air. The electrochemical properties of the graphite electrode were studied using CV and EIS in the presence of acetate buffer supporting electrolyte with 2 Mm ferricyanide as a redox probe. The graphite electrode showed enhanced current response which confirms facile kinetics and enhanced sensitivity. However, the peak to peak (DE) separation increased as a function of scan rate. The EIS showed a high charger transfer resistance. The detection phenanthrene on the exfoliated graphite was studied in the presence of acetate buffer solution at PH 3.5 using DPV. The oxidation peak of phenanthrene was observed at 0.4 V. Under optimized conditions (supporting electrolyte, pH, deposition time, etc.). The detection limit observed was at 5x 10⁻⁸ M. Thus the results demonstrate with further optimization and modification lower concentration detection can be achieved.

Keywords: electrochemical detection, exfoliated graphite, PAHs (polycyclic aromatic hydrocarbons), urban air

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Authors: Yu-Kuei Hsu, Yan-Gu Lin

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A facile and simple fabrication of copper(II) oxide (CuO) nanosheet on copper foil as nanoelectrode for H2O2 sensing application was proposed in this study. The spontaneous formation of CuO nanosheets by immersing the copper foil into 0.1 M NaOH aqueous solution for 48 hrs was carried out at room temperature. The sheet-like morphology with several ten nanometers in thickness and ~500 nm in width was observed by SEM. Those nanosheets were confirmed the monoclinic-phase CuO by the structural analysis of XRD and Raman spectra. The directly grown CuO nanosheets film is mechanically stable and offers an excellent electrochemical sensing platform. The CuO nanosheets electrode shows excellent electrocatalytic response to H2O2 with significantly lower overpotentials for its oxidation and reduction and also exhibits a fast response and high sensitivity for the amperometric detection of H2O2. The novel spontaneously grown CuO nanosheets electrode is readily applicable to other analytes and has great potential applications in the electrochemical detection.

Keywords: CuO, nanosheets, H2O2 detection, Cu foil

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Authors: Sun H. Hwang, Young E. Lee, Yunhan Ga, Gilwon Yoon

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EEG is a very complex signal with noises and other bio-potential interferences. EOG is the most distinct interfering signal when EEG signals are measured and analyzed. It is very important how to process raw EEG signals in order to obtain useful information. In this study, the EEG signal processing techniques such as EOG filtering and outlier removal were examined to minimize unwanted EOG signals and other noises. The two different mental states of resting and focusing were examined through EEG analysis. A focused state was induced by letting subjects to watch a red dot on the white screen. EEG data for 32 healthy subjects were measured. EEG data after 60-Hz notch filtering were processed by a commercially available EOG filtering and our presented algorithm based on the removal of outliers. The ratio of beta wave to theta wave was used as a parameter for determining the degree of focusing. The results show that our algorithm was more appropriate than the existing EOG filtering.

Keywords: EEG, focus, mental state, outlier, signal processing

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Authors: Javad Yarmahmoudi, Alireza Mirzaee

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Many active and passive structural health monitoring (SHM) techniques have been developed for detection of the defects of plates. Generally, riveted joints hold the plates together and their failure may create accidents. In this study, well known active and passive methods were modified for the evaluation of the health of the riveted joints between the plates. The active method generated Lamb waves and monitored their propagation by using lead zirconate titanate (PZT) disks. The signal was analyzed by using the wavelet transformations. The passive method used the Fiber Bragg Grating (FBG) sensors and evaluated the spectral characteristics of the signals by using Fast Fourier Transformation (FFT). The results indicated that the existing methods designed for the evaluation of the health of individual plates may be used for inspection of riveted joints with software modifications.

Keywords: structural health monitoring, SHM, active SHM, passive SHM, fiber bragg grating sensor, lead zirconate titanate, PZT

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Authors: Karen Chad, Louise Humbert, Kenzie Friesen, Dave Sandomirsky

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Background: The pandemic of COVID-19 presented many historical challenges to the sporting community. For organizations and individuals, sport was put on hold resulting in social, economic, physical, and mental health consequences for all involved. High school sports are seen as an effective and accessible pathway for students to receive health, social, and academic benefits. Studies examining sport cessation due to COVID-19 found substantial negative outcomes on the physical and mental well-being of participants in the high school setting. However, the pandemic afforded an opportunity to examine sport participation and the value people place upon their engagement in high school sport. Study objectives: (1) Examine the experiences of students, parents, administrators, officials, and coaches during a year without high school sports; (2) Understand why participants are involved in high school sports; and (3) Learn what supports are needed for future involvement. Methodology: A mixed method design was used, including semi-structured interviews and a survey (SurveyMonkey software), which was disseminated electronically to high school students, coaches, school administrators, parents, and officials. Results: 1222 respondents completed the survey. Findings showed: (1) 100% of students participate in high school sports to improve their mental health, with >95% said it keeps them active and healthy, helps them make friends and teaches teamwork, builds confidence and positive self-perceptions, teaches resiliency, enhances connectivity to their school, and supports academic learning; (2) Top three reasons teachers coach is their desire to make a difference in the lives of students, enjoyment, and love of the sport, and to give back. Teachers said what they enjoy most is contributing to and watching athletes develop, direct involvement with student sport success, and the competitiveatmosphere; (3) 90% of parents believe playing sports is a valuable experience for their child, 95% said it enriches student academic learning and educational experiences, and 97% encouraged their child to play school sports; (4) Officials participate because of their enjoyment and love of the sport, experience, and expertise, desire to make a difference in the lives of children, the competitive/sporting atmosphere and growing the sport. 4% of officials said it was financially motivated; (5) 100% of administrators said high school sports are important for everyone. 80% believed the pandemic will decrease teachers coaching and increase student mental health and well-being. When there was no sport, many athletes got a part-time job and tried to stay active, with limited success. Coaches, officials, and parents spent more time with family. All participants did little physical activity, were bored; and struggled with mental health and poor physical health. Respondents recommended better communication, promotion, and branding of high school sport benefits, equitable funding for all sports, athlete development, compensation and recognition for coaching, and simple processes to strengthen the high school sport model. Conclusions: High school sport is an effective vehicle for athletes, parents, coaches, administrators, and officials to derive many positive outcomes. When it is taken away, serious consequences prevail. Paying attention to important success factors will be important for the effectiveness of high school sports.

Keywords: physical activity, high school, sports, pandemic

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Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

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Real-time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Therefore, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Canny edge detection is one of the common blocks in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: high level synthesis, canny edge detection, hardware accelerators, computer vision

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Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

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Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

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Authors: Kenji Gwee

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The Mental Capacity Act is a new legislation that allows for lasting powers of attorney and court-appointed deputies, in respect of people who lack legal capacity. While the UK Act, after which the Singapore Act is modeled, has been shown to be therapeutic to donors, the Singapore Act differs from its UK counterpart and it is unclear if the Singapore Act can be beneficial to donors as purported. The purpose of this study was to determine what the perceptions of three groups of stakeholders (patients, caregivers and psychiatrists) are about the aspects of the Mental Capacity Act that are therapeutic to donors. In addition, ways to increase the therapeutic value of the Act to donors are sought. A qualitative methodology was used and the research was guided by two theoretical frameworks: therapeutic jurisprudence and an interpretive constructive framework. Interviews with 12 psychiatrists, and focus groups with twenty three patients and seven caregivers showed agreement that, allowing donors to nominate more than one decision- maker, and whistle-blowing mechanisms for recourse for abuse, were therapeutic to donors. To further increase the therapeutic value of the Act, 2 suggestions were made: the Act should provide for (i) advanced healthcare directives- allowing donors to make advance decisions to refuse treatment, or cease existing treatment, and (ii) independent advocacy services- to have a case worker to represent people who have no family or friends and are thus unable to find suitable donees.

Keywords: Mental Capacity Act, therapeutic jurisprudence, qualitative methodology, the UK Act

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Authors: Ahmadu Maidorawa, Idrissa Djibo, Muhammad Tella

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This paper presents a method for detecting flow chart and figure plagiarism based on shape of image processing and multimedia retrieval. The method managed to retrieve flowcharts with ranked similarity according to different matching sets. Plagiarism detection is well known phenomenon in the academic arena. Copying other people is considered as serious offense that needs to be checked. There are many plagiarism detection systems such as turn-it-in that has been developed to provide these checks. Most, if not all, discard the figures and charts before checking for plagiarism. Discarding the figures and charts result in look holes that people can take advantage. That means people can plagiarize figures and charts easily without the current plagiarism systems detecting it. There are very few papers which talks about flowcharts plagiarism detection. Therefore, there is a need to develop a system that will detect plagiarism in figures and charts.

Keywords: flowchart, multimedia retrieval, figures similarity, image comparison, figure retrieval

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Authors: Ahmad H. Abdelgwad, Ahmed A. Nashat

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Landmine detection is an important and yet challenging problem remains to be solved. Ground Penetrating Radar (GPR) is a powerful and rapidly maturing technology for subsurface threat identification. The detection methodology of GPR depends mainly on the contrast of the dielectric properties of the searched target and its surrounding soil. This contrast produces a partial reflection of the electromagnetic pulses that are being transmitted into the soil and then being collected by the GPR.  One of the most critical hardware components for the performance of GPR is the antenna system. The current paper explores the design and simulation of a pyramidal horn antenna operating at L-band frequencies (1- 2 GHz) to detect a landmine. A prototype model of the GPR system setup is developed to simulate full wave analysis of the electromagnetic fields in different soil types. The contrast in the dielectric permittivity of the landmine and the sandy soil is the most important parameter to be considered for detecting the presence of landmine. L-band horn antenna is proved to be well-versed in the investigation of landmine detection.

Keywords: full wave analysis, ground penetrating radar, horn antenna design, landmine detection

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Authors: Garima Singh

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Objectives: Behavioral Crisis Center (BCC) is a community solution to a community problem. There has been an exponential increase in the incidence and prevalence of mental health crises around the world. The effects of the crisis negatively impact our patients and their families and strain the law enforcement and emergency room. The goal of the multi-disciplinary care model is to break the crisis cycle and provide 24-7 rapid access to an acre and crisis stabilization. We initiated our first BCC care center in 2020 in the midst of the COVID pandemic and have seen a remarkable improvement in patient ‘care and positive financial outcome. Background: Mental illnesses are common in the United States. Nearly one in five U.S. adults live with a mental illness (52.9 million in 2020). This number represented 21.0% of all U.S. adults. To address some of these challenges and help our community, In May 2020, we opened our first Behavioral crisis center (BCC). Since then, we have served more than 2500 patients and is the first southwest Missouri’s first 24/7 facility for crisis–level behavioral health and substance use needs. It has been proven to be a more effective place than emergency departments, jails, or local law enforcement. Methods: BCC was started in 2020 to serve the unmet need of the community and provide access to behavioral health and substance use services identified in the community. Funding was possible with significant investment from the county and Missouri Foundation for Health, with contributions from medical partners. It is a multi-disciplinary care center consisting of Physicians, nurse practitioners, nurses, behavioral technicians, peer support specialists, clinical intake specialists, and clinical coordinators and hospitality specialists. The center provides services including psychiatry care, outpatient therapy, community support services, primary care, peer support and engagement. It is connected to a residential treatment facility for substance use treatment for continuity of care and bridging the gap, which has resulted in the completion of treatment and better outcomes. Results: BCC has proven to be a great resource to the community and the Missouri Health Coalition is providing funding to replicate the model in other regions and work on a similar model for children and adolescents. Overall, 29% of the patients seen at BCC are stabilized and discharged with outpatient care. 50% needed acute stabilization in a hospital setting and 21% required long-term admission, mostly for substance use treatment. The local emergency room had a 42% reduction in behavioral health encounters compared to the previous 3 years. Also, by a quick transfer to BCC, the average stay in ER was reduced by 10 hours and time to follow up behavioral health assessment decreased by an average of 4 hours. Uninsured patients are also provided Medicaid application assistance which has benefited 55% of individuals receiving care at BCC. Conclusions: BCC is impacting community health and improving access to quality care and substance use treatment. It is a great investment for our patients and families.

Keywords: BCC, behvaioral health, community health care, addiction treatment

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Authors: Clesse C., Lighezzolo-Alnot J., De Lavergne S.

Abstract:

Considered as the most common surgical procedure worldwide, episiotomy can be defined as an incision around the vulva performed to enlarge it, in the aim of preventing the traumatic rupture of the perineum during childbirth. Rather mediatized, this practice raises many questions in the field of mental health, relayed by different users and health professionals. Today, is topicality is moderately hectic since many queries about the prophylactic exercise of episiotomy are subject to a relative consensus, particularly since WHO advocated in 1996 that only 10% of childbirths should involve an episiotomy. This indicator appeared after the publication of numerous results from randomized clinical trials. Unfortunately, these papers seem mostly centered about somatic impacts of episiotomy. From the side of psychological studies, they mostly integrate a major clinical methodological bias, especially considering that every primiparous woman is identical to the others face to the experience of parturition. In the aim to fill this lack of knowledge, we developed a longitudinal research starting in the 7th month of pregnancy and ending one year after delivery. We are studying in a comparative way different possible psychological consequences inherent to the use of episiotomy. To do this, we use a standardized methodology which combines semi-structured clinical interviews (IRMAG, IRMAN ...), free clinical interviews, a projective test (Rorschach) and five questionnaires (QIC, EPDS, CPQ WOMBLSQ4, SF36). Therefore, we can comprehend with shrewdness the question of psychic impacts of episiotomy in a qualitative and quantitative way by comparing it to other obstetric interventions. In this paper, we will present the first results obtained about a population of twenty-two primiparous women by focusing on body image, sexuality, quality of life, depressive affects, post-traumatic stress disorder and investment of the maternal role. Finally, we will consider the different implications and perspectives of this research which could improve the public health policies in the field of perinatal care.

Keywords: assessment, episiotomy, mental health, psychical impacts

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Authors: Liu Linxin

Abstract:

As system complexity increases, log parsing and anomaly detection become more and more important in ensuring system stability. However, traditional methods often face the problems of insufficient adaptability and decreasing accuracy when dealing with rapidly changing log contents and unknown domains. To this end, this paper proposes an approach LogRAG, which combines RAG (Retrieval Augmented Generation) technology with Prompt Engineering for Large Language Models, applied to log analysis tasks to achieve dynamic parsing of logs and intelligent anomaly detection. By combining real-time information retrieval and prompt optimisation, this study significantly improves the adaptive capability of log analysis and the interpretability of results. Experimental results show that the method performs well on several public datasets, especially in the absence of training data, and significantly outperforms traditional methods. This paper provides a technical path for log parsing and anomaly detection, demonstrating significant theoretical value and application potential.

Keywords: log parsing, anomaly detection, retrieval-augmented generation, prompt engineering, LLMs

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Authors: Belkacem Soundes, Guezouli Larbi

Abstract:

This paper presents a robust and accurate method for text detection and localization over lecture videos. Frame regions are classified into text or background based on visual feature analysis. However, lecture video shows significant degradation mainly related to acquisition conditions, camera motion and environmental changes resulting in low quality videos. Hence, affecting feature extraction and description efficiency. Moreover, traditional text detection methods cannot be directly applied to lecture videos. Therefore, robust feature extraction methods dedicated to this specific video genre are required for robust and accurate text detection and extraction. Method consists of a three-step process: Slide region detection and segmentation; Feature extraction and non-text filtering. For robust and effective features extraction moment functions are used. Two distinct types of moments are used: orthogonal and non-orthogonal. For orthogonal Zernike Moments, both Pseudo Zernike moments are used, whereas for non-orthogonal ones Hu moments are used. Expressivity and description efficiency are given and discussed. Proposed approach shows that in general, orthogonal moments show high accuracy in comparison to the non-orthogonal one. Pseudo Zernike moments are more effective than Zernike with better computation time.

Keywords: text detection, text localization, lecture videos, pseudo zernike moments

Procedia PDF Downloads 155

Authors: Sakshi Ghai

Abstract:

The word ‘emotion’ has been microscopically studied through psychological, anthropological and biological lenses and have indubitably been one of the most researched concepts as, in all situations and reactions that constitute human life, emotions form the very niche of our mutual existence. While understanding the social aspects of cognition, one can realize that emotions are deeply interwoven with language and thereby are pivotal in inducing human actions and behavior. The society or the outward social structure is the result of the inward psychological structure of our human relationships, for the individual is the result of the total experience, knowledge and conduct of man. The aim of this paper is threefold: first, to establish the relation between mental representations of emotions and its neuropsychological connection with language on a conscious and sub-conscious level; secondly, to describe how innate, basic and higher cognitive emotions affect the constantly changing state of an agent and peruse its assistance in determining the moral compass within all beings. Lastly, in the course of this paper, the concept of the architecture of mind is explored considering how it has developed an ability to display adaptive emotional states and responses, which are in sync with the language of thought. For every response to the social environment is so deeply determined by the very social milieu in which one is situated, language has a fundamental role in constructing emotions and articulating behavior. Being linguistic beings, we tend to associate emotion, feelings and other aspects of inwards mental states intrinsically with the language we use. This paper aims to devise a discursive approach to understand how emotions are fabricated, intertwined with the mental constructs further expressed and communicated through the various units of language.

Keywords: mental representation, emotion, language, psychology

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Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

Abstract:

Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

Procedia PDF Downloads 360