Search results for: mental health detection

Authors: Jaskaran Singh Sidhu

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Aim: The purpose of this study is to find the relationship between wellness among sportsmen and non sportsmen. Methodology: The present study is an experimental study for 80 senior secondary volleyball players of 16-19 years of age from Ludhiana District of Punjab (India), and 80 non-sportsperson were taken from senior secondary school of Ludhiana district. The sample for this study was taken through a random sampling technique. Tools: A five point scale havinf 50 items was used to acess the wellness Statistical Analysis: To find out the relationship among the variables exists or not, a t-test was used to test the significance of the difference between the means. Statistics for each characteristic were calculated; Mean, Standard deviation, Standard error of Mean. Data were analyzed using SPSS (statistical package for the social sciences). Statistical significance was set at p < 0.05. Results: Substantial deviations were noted at p<0.5 in the totality of wellness. Sportsmen show significant differences exist at p<0.5 in three parameters of wellness i.e., physical wellness, mental wellness, and social wellness. In spiritual and emotional wellness attributes, non-sportsmen shows significant difference at p<0.5. Conclusion: From the data interpretation it reflects that overall wellness can be improved by participation in sports. It further noted in study that participation in sports promote the attributes of wellness i.e., physical wellness, mental wellness, emotional wellness and social wellness.

Keywords: physical, mental, social, emotional, wellness, spiritual

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Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara

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Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.

Keywords: attention-based fully convolutional network, optic disc detection and segmentation, retinal fundus image, screening of ocular diseases

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Authors: Khin Mar Yee, Mu Mu Than, Kyi Lint, Aye Aye Oo, Chan Mya Hmway, Khin Zar Chi Winn

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The dynamic changes of Land Use and Land Cover (LULC) changes in Yangon have generally resulted the improvement of human welfare and economic development since the last twenty years. Making map of LULC is crucially important for the sustainable development of the environment. However, the exactly data on how environmental factors influence the LULC situation at the various scales because the nature of the natural environment is naturally composed of non-homogeneous surface features, so the features in the satellite data also have the mixed pixels. The main objective of this study is to the calculation of accuracy based on change detection of LULC changes by Support Vector Machines (SVMs). For this research work, the main data was satellite images of 1996, 2006 and 2015. Computing change detection statistics use change detection statistics to compile a detailed tabulation of changes between two classification images and Support Vector Machines (SVMs) process was applied with a soft approach at allocation as well as at a testing stage and to higher accuracy. The results of this paper showed that vegetation and cultivated area were decreased (average total 29 % from 1996 to 2015) because of conversion to the replacing over double of the built up area (average total 30 % from 1996 to 2015). The error matrix and confidence limits led to the validation of the result for LULC mapping.

Keywords: land use and land cover change, change detection, image processing, support vector machines

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Authors: Boudemagh Naime

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Automatic radar detection requires some methods of adapting to variations in the background clutter in order to control their false alarm rate. The problem becomes more complicated in non-Gaussian environment. In fact, the conventional approach in real time applications requires a complex statistical modeling and much computational operations. To overcome these constraints, we propose another approach based on artificial neural network (ANN-CMLD-CFAR) using a Back Propagation (BP) training algorithm. The considered environment follows a log-normal distribution in the presence of multiple Rayleigh-targets. To evaluate the performances of the considered detector, several situations, such as scale parameter and the number of interferes targets, have been investigated. The simulation results show that the ANN-CMLD-CFAR processor outperforms the conventional statistical one.

Keywords: radat detection, ANN-CMLD-CFAR, log-normal clutter, statistical modelling

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Authors: Ravinder Singh, Pratima Syal

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Background: The rising prevalence and incidence of Acute Pancreatitis (AP) and its associated metabolic variables known as metabolic syndrome (MetS) are common medical conditions with catastrophic consequences and substantial treatment costs. The correlation between MetS and AP, as well as their impact on Health Related Quality of Life (HRQoL) is uncertain, and because there are so few published studies, further research is needed. As a result, we planned this study to determine the relationship between MetS components impact on HRQoL in AP patients. Patients and Methods: A prospective, observational study involving the recruitment of patients with AP with and without MetS was carried out in tertiary care hospital of North India. Patients were classified with AP if they were diagnosed with two or more components of the following criteria, abdominal pain, serum amylase and lipase levels two or more times normal, imaging trans-abdominal ultrasound, computed tomography, or magnetic resonance. The National Cholesterol Education Program–Adult Treatment Panel III (NCEP-ATP III) criterion was used to diagnose the MetS. The various socio-demographic variables were also taken into consideration for the calculation of statistical significance (P≤.05) in AP patients. Finally, the correlation between AP and MetS, along with their impact on HRQoL was assessed using Student's t test, Pearson Correlation Coefficient, and Short Form-36 (SF-36). Results: AP with MetS (n = 100) and AP without MetS (n = 100) patients were divided into two groups. Gender, Age, Educational Status, Tobacco use, Body Mass Index (B.M.I), and Waist Hip Ratio (W.H.R) were the socio-demographic parameters found to be statistically significant (P≤.05) in AP patients with MetS. Also, all the metabolic variables were also found to statistically significant (P≤.05) and found to be increased in patients with AP with MetS as compared to AP without MetS except HDL levels. Using the SF-36 form, a greater significant decline was observed in physical component summary (PCS) and mental component summary (MCS) in patients with AP with MetS as compared to patients without MetS (P≤.05). Furthermore, a negative association between all metabolic variables with the exception of HDL, and AP was found to be producing deterioration in PCS and MCS. Conclusion: The study demonstrated that patients with AP with MetS had a worse overall HRQOL than patients with AP without MetS due to number of socio-demographic and metabolic variables having direct correlation impacting physical and mental health of patients.

Keywords: metabolic disorers, QOL, cost effectiveness, pancreatitis

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Authors: Simplejit Kaur Dhanoa, Manmohan Singh

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This study was done with the primary objective to evaluate the motor and mental developmental delays among children having neonatal Jaundice. A total sample of 300 neonates were collected; out of them, 150 were preterm neonates, and 150 were full term neonates from the hospital setting and follow up study was done with the help of the Developmental Assessment scale of the Indian Infant. The registered samples were assessed up to 2.6 years with a gap of 6 months. The outcomes of this study reveal that developmental delays were present among children who had preterm neonatal jaundice as compare to full term normal babies. Further, It was reported that both motor and mental development is affected due to neonatal hyperbilirubinemia in addition to preterm birth.

Keywords: hyperbinirubinemia, preterm neonates, developmental delays, preterm

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Authors: Sungsoo Na, Chanho Park

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Lung cancer is one of the most common severe diseases driving to the death of a human. Lung cancer can be divided into two cases of small-cell lung cancer (SCLC) and non-SCLC (NSCLC), and about 80% of lung cancers belong to the case of NSCLC. From several studies, the correlation between epidermal growth factor receptor (EGFR) and NSCLCs has been investigated. Therefore, EGFR inhibitor drugs such as gefitinib and erlotinib have been used as lung cancer treatments. However, the treatments result showed low response (10~20%) in clinical trials due to EGFR mutations that cause the drug resistance. Patients with resistance to EGFR inhibitor drugs usually are positive to KRAS mutation. Therefore, assessment of EGFR and KRAS mutation is essential for target therapies of NSCLC patient. In order to overcome the limitation of conventional therapies, overall EGFR and KRAS mutations have to be monitored. In this work, the only detection of EGFR will be presented. A variety of techniques has been presented for the detection of EGFR mutations. The standard detection method of EGFR mutation in ctDNA relies on real-time polymerase chain reaction (PCR). Real-time PCR method provides high sensitive detection performance. However, as the amplification step increases cost effect and complexity increase as well. Other types of technology such as BEAMing, next generation sequencing (NGS), an electrochemical sensor and silicon nanowire field-effect transistor have been presented. However, those technologies have limitations of low sensitivity, high cost and complexity of data analyzation. In this report, we propose a label-free and high-sensitive detection method of lung cancer using quartz crystal microbalance based platform. The proposed platform is able to sense lung cancer mutant DNA with a limit of detection of 1nM.

Keywords: cancer DNA, resonance frequency, quartz crystal microbalance, lung cancer

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Authors: Neda Seyyedi, Reza Berangi

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Voice over IP (VOIP) network, also known as Internet telephony, is growing increasingly having occupied a large part of the communications market. With the growth of each technology, the related security issues become of particular importance. Taking advantage of this technology in different environments with numerous features put at our disposal, there arises an increasing need to address the security threats. Being IP-based and playing a signaling role in VOIP networks, Session Initiation Protocol (SIP) lets the invaders use weaknesses of the protocol to disable VOIP service. One of the most important threats is denial of service attack, a branch of which in this article we have discussed as flooding attacks. These attacks make server resources wasted and deprive it from delivering service to authorized users. Distributed denial of service attacks and attacks with a low rate can mislead many attack detection mechanisms. In this paper, we introduce a mechanism which not only detects distributed denial of service attacks and low rate attacks, but can also identify the attackers accurately. We detect and prevent flooding attacks in SIP protocol using Shannon (FDP-S), Renyi (FDP-R) and Tsallis (FDP-T) entropy. We conducted an experiment to compare the percentage of detection and rate of false alarm messages using any of the Shannon, Renyi and Tsallis entropy as a measure of disorder. Implementation results show that, according to the parametric nature of the Renyi and Tsallis entropy, by changing the parameters, different detection percentages and false alarm rates will be gained with the possibility to adjust the sensitivity of the detection mechanism.

Keywords: VOIP networks, flooding attacks, entropy, computer networks

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Authors: Jae-Neung Lee, Keun-Chang Kwak

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This paper describes an analysis of Yacht Simulator international trends and also explains about Yacht. Examples of yacht Simulator using Yacht Simulator include image processing for totaling the total number of vehicles, edge/target detection, detection and evasion algorithm, image processing using SIFT (scale invariant features transform) matching, and application of median filter and thresholding.

Keywords: yacht simulator, simulator, trends analysis, SIFT

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Authors: Priyanka R. Sagar

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Social economic status (SES) is a variable that denotes the social standing of a person in society, and quality of life is a measure of health, happiness, and comfort of an individual. During early 2020, the world was stuck by the blow of the COVID-19 pandemic resulting in minimal or no economic activities to takes place. The present research paper is an attempt to analyze the socioeconomic status and quality of life of construction workers dwelling in the sub-urban areas of Hoskote located in the Bengaluru rural district pre and post-COVID-19. It also tries to analyze the difference in these variables pre and post-COVID-19. The study uses a retrospective design and data collected through a questionnaire survey from the respondents of Hoskote. A total of 100 samples were collected, out of which 73% were men and 27% were women. The mean age group of the participants is 41.04 ± 6.97 years. The overall analysis of the study shows that there is a significant difference in the socioeconomic status of construction workers pre and post-COVID-19. The study shows SES of the workers pre-pandemic is higher than post-pandemic. The other variable is quality of life which consists of physical health, psychological health, social relationships, and environmental domains. The study depicts that the psychological domain alone has been impacted by the pandemic; workers had better mental health pre-COVID-19. The other domains, i.e., physical health, social relationship, and environment, remain unaffected.

Keywords: socio-economic status, quality of life, construction workers, COVID-19

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Authors: Anucha Taiwong, Nirobol Kanogsunthornrat

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This predictive research aimed to investigate the symptom clusters that influence the quality of life among patients with chronic kidney disease, as indicated in the Theory of Unpleasant Symptoms. The purposive sample consisted of 150 patients with stage 3-4 chronic kidney disease who received care at an outpatient chronic kidney disease clinic of a tertiary hospital in Roi-Et province. Data were collected from January to March 2016 by using a patient general information form, unpleasant symptom form, and quality of life (SF-36) and were analyzed by using descriptive statistics, factor analysis, and multiple regression analysis. Findings revealed six core symptom clusters including symptom cluster of the mental and emotional conditions, peripheral nerves abnormality, fatigue, gastro-intestinal tract, pain and, waste congestion. Significant predictors for quality of life were the two symptom clusters of pain (Beta = -.220; p < .05) and the mental and emotional conditions (Beta=-.204; p<.05) which had predictive value of 19.10% (R2=.191, p<.05). This study indicated that the symptom cluster of pain and the mental and emotional conditions would worsen the patients’ quality of life. Nurses should be attentive in managing the two symptom clusters to facilitate the quality of life among patients with chronic kidney disease.

Keywords: chronic kidney disease, symptom clusters, predictors of quality of life, pre-dialysis

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Authors: Samuel B. Dulay, Sandra Julich, Herbert Tomaso, Ciara K. O'Sullivan

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An early, rapid and definite detection for the presence of biowarfare agents, pathogens, viruses and toxins is required in different situations which include civil rescue and security units, homeland security, military operations, public transportation securities such as airports, metro and railway stations due to its harmful effect on the human population. In this work, an electrochemical genosensor array that allows simultaneous detection of different biowarfare agents within an integrated microsystem that provides an easy handling of the technology which combines a microfluidics setup with a multiplexing genosensor array has been developed and optimised for the following targets: Bacillus anthracis, Brucella abortis and melitensis, Bacteriophage lambda, Francisella tularensis, Burkholderia mallei and pseudomallei, Coxiella burnetii, Yersinia pestis, and Bacillus thuringiensis. The electrode array was modified via co-immobilisation of a 1:100 (mol/mol) mixture of a thiolated probe and an oligoethyleneglycol-terminated monopodal thiol. PCR products from these relevant biowarfare agents were detected reproducibly through a sandwich assay format with the target hybridised between a surface immobilised probe into the electrode and a horseradish peroxidase-labelled secondary reporter probe, which provided an enzyme based electrochemical signal. The potential of the designed microsystem for multiplexed genosensor detection and cross-reactivity studies over potential interfering DNA sequences has demonstrated high selectivity using the developed platform producing high-throughput.

Keywords: biowarfare agents, genosensors, multipled detection, microsystem

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Authors: Freda Sinclair

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The purpose of this paper is to examine the impact of IPV on the family and how to best provide services for this population who suffer in silence from PTSD, medical and mental health issues and living in fear of their partner who is causing them harm. Although this is a societal issue, those in the underserved communities face even greater implications due to lack of education, language barriers, housing and financial insecurity, and overall fear of systems that seem to punish and re-traumatize them when seeking help. This paper examines the systems that treat the underserved and fail them due to their lack of knowledge, implicit biases, and failure to provide adequate time and patience to observe and provide what the family needs when they come to service providers seeking assistance and support. The methodology used examines a qualitative and quantitative study of homeless women and their families seeking safe shelter away from their partners who are causing harm. The study examines ways in which they became known to the system by way of medical, mental health, substance abuse or child welfare authorities. Found that due to the myriad of families facing countless needs, research has found that using trained therapists along with promising practice and/or evidence-based practice models best supports the needs of the families while addressing their trauma and meeting their concrete needs. The implications are that we need more trained clinicians who are sympathetic to this population and are willing to maintain up to date information to help them best serve their community and provide the best possible care. The findings give insight into how this study can be examined on a broader scale and give policy implications of how to serve best all people who are exposed to IPV, trauma, and PTSD and feel as if they are overlooked by society. There are greater implications for needed research to better support all people who live in fear of the people who harm them and best practice, support and outreach that can give best practice care to those who are in need at the most vulnerable times of their lives.

Keywords: trauma, PTSD, IPV, EBP

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Authors: Soo-Bi Lee, Jun Young Jeong, Zehgn Lin, Chenminxi

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Background: In South Korea, a problematic phenomenon has recently arisen whereby adult children continue to receive parentalcaregivingin some cases. These phenomena has been shown to affect the mental health of mothers. Study Goals: The purposes of this study are to verify whether the mediating effects of stress on the relationship between a woman’s care burden for their adult children and depression are moderated by their satisfaction about their husbands’ sharing of the caregiving. Methodology: This study analyzed 3,053 married women with adult children using the most recent data from the “Korean Longitudinal Survey of Women & Families 7th(2018)" conducted at the national level. The analysis was conducted using the SPSS Process Macro Model 7 to verify the moderated mediating effects and subsequently confirm their significance based on the bootstrapping method. Results and Implications: (1) Stress was identified a mediating factor in the relationship between the care burden for adult children and depression; and (2) the mediating effects of stress on depression from the burden of caring for adult children are modulated by the woman's satisfaction with her husband’s sharing of the care burden. In other words, the higher the caring burden of adult children, the higher the mother's stress, which increases depression. At this time, the higher the their satisfaction with the husband's share of care in the path of mother's care burden and stress, the lower the mother's stress and, ultimately, the depression be alleviated. Conclusion: Programs that promote the mental health of married women heavily with the caring burden for their adult children, as well as those that improve social awareness regarding husbands' sharing of the care burden, should be implemented. Also, social welfare policy alternatives are needed at the national level to reduce the caring burden caused by adult children.

Keywords: married women, adult children care burden, stress, depression, satisfaction with husbands sharing of the care

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Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

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Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

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Authors: McKenzie S. Braley, Lesley Jessiman

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If language reveals internal psychological processing, then it is also likely that language use in autobiographical memory transcripts may be used as a window into attachment style and related personality features. The current study, therefore, examined the possible associations between attachment style, negative affectivity, social inhibition, and linguistic features extracted from autobiographical memory transcripts. Young adult participants (n = 61) filled out attachment and personality questionnaires, and orally reported a relationship-related memory. Memories were audio-recorded and later transcribed verbatim. Using a computerized linguistic extraction tool, positive affect words, negative affect words, and cognition words were extracted. Spearman’s rank correlation coefficients revealed that attachment anxiety was negatively correlated with cognition words (r2 = -0.26, p = 0.047) and that negative affectivity was negatively correlated with positive affect words (r2 = -0.32, p = 0.012). The findings suggest that attachment style and personality are associated with speech styles indicative of both emotionality and depth of processing. Because attachment styles, negative affectivity, and social inhibition are associated with poor mental health outcomes, analyses of key linguistics features in autobiographical memory narratives may provide reliable screening tools for mental wellbeing.

Keywords: attachment style, autobiographical memory, language, negative affectivity, social inhibition

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Authors: Ireen Manase Kabembo, Patrick Chanda

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Background: Substance use disorders are among the chronic conditions that affect all age groups. Worldwide, there is an increase in young people affected by SUDs, which implies that more family members are transitioning into the caregiver role. Family caregivers play a buffering role in the formal healthcare system due to their involvement in caring for persons with acute and chronic conditions in the home setting. Family carers of youth with problematic alcohol and marijuana use experience myriad challenges in managing daily care for this medically vulnerable group. In addition, the poor health-seeking behaviours of youth with SUDs characterized by eluding treatment and runaway tendencies coupled with the effects of the pandemic made caregiving a daunting task for most family caregivers. Issues such as limited and unavailable psychotropic medications, social stigma and discrimination, financial hurdles, systemic barriers in adolescent and young adult mental healthcare services, and the lack of a perceived vulnerability to Covid-19 by youth with SUDs are experiences of family caretakers. Methods: A qualitative study with 30 family caregivers of youth aged 16-24 explored their lived experiences and subjective meanings using two in-depth semi-structured interviews, a caregiving timeline, and participant observation. Findings: Results indicate that most family caregivers had challenges managing care for treatment elusive youth, let alone having them adhere to Covid-19 regulations. However, youth who utilized healthcare services and adhered to treatment regimens had positive outcomes and sustained recovery. The effects of the pandemic, such as job losses and the closure of businesses, further exacerbated the financial challenges experienced by family caregivers, making it difficult to purchase needed medications and daily necessities for the youth. The unabated stigma and discrimination of families of substance-dependent youth in Zambian communities further isolated family caregivers, leaving them with limited support. Conclusion: Since young people with SUDs have a compromised mental capacity due to the cognitive impairments that come with continued substance abuse, they often have difficulties making sound judgements, including the need to utilize SUD recovery services. Also, their tendency to not adhere to the Covid-19 pandemic requirements places them at a higher risk for adverse health outcomes in the (post) pandemic era. This calls for urgent implementation of robust youth mental health services that address prevention and recovery for these emerging adults grappling with substance use disorders. Support for their family caregivers, often overlooked, cannot be overemphasized.

Keywords: chronic care management, Covid-19 pandemic, family caregivers, youth with substance use disorders

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Authors: Huang Chiung Chiu

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This article is about the nursing experience of assisting an outpatient with premature menopause, osteoporosis and sarcopenia through a multi-discipline care model. The nursing period is from September 22nd, 2020, to December 7th, 2020, collecting data through interviews with the patient, observation, and physical assessment. It was found that the main health problems were insufficient nutrition, less physical need, insomnia, and potentially dangerous falls. As an outpatient nurse, the author observed that in recent years, the age group of women with premature menopause, osteoporosis and sarcopenia had shifted downward. Integrated multi-disciplinary interventions were provided upon the initial diagnosis of osteoporosis and sarcopenia. Under the outpatient care setting, the collaborative team works between the doctors, nutritionists, osteoporosis educators, rehabilitates, physical therapists and other specialized teams were applied to provide individualized, integrated multi-disciplinary care. Through empathy and the establishment of attentive care, companionship and trust, we discussed care plans and treatment guidelines with the case, providing accurate, complete disease information and feedback education to strengthen the patient’s knowledge and motivation for exercise. Nursing guidance regarding the dietary nutrition and adjustment of daily routine was provided to increase the self-care ability, improve the health problems of muscle weakness and insomnia, and prevent falls. For patients with postmenopausal osteoporosis and sarcopenia, it is recommended that the nurses coordinate the multi-discipline integrated care model, adjust patients’ lifestyle and diet, and establish a regular exercise plan so that the cases can be evaluated holistically to improve the quality of care and physical and mental comfort.

Keywords: multi-discipline care model, premature menopause, osteoporosis, sarcopenia, insomnia

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Authors: Jocelyn B. Barbosa, Angeli L. Magbaril, Mariel T. Sabanal, John Paul T. Galario, Mikka P. Baldovino

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The use of technology has become ubiquitous in different areas of business today. With the advent of digital imaging and database technology, business owners have been motivated to integrate technology to their business operation ranging from small, medium to large enterprises. Technology has been found to have brought many benefits that can make a business grow. Hog or swine raising, for example, is a very popular enterprise in the Philippines, whose challenges in production monitoring can be addressed through technology integration. Swine production monitoring can become a tedious task as the enterprise goes larger. Specifically, problems like delayed and inconsistent reports are most likely to happen if counting of swine per pen of which building is done manually. In this study, we present iCount, which aims to ensure efficient swine detection and counting that hastens the swine production monitoring task. We develop a system that automatically detects and counts swine based on Sobel filter and ellipse fitting model, given the still photos of the group of swine captured in a pen. We improve the Sobel filter detection result through 8-neigbhorhood rule implementation. Ellipse fitting technique is then employed for proper swine detection. Furthermore, the system can generate periodic production reports and can identify the specific consumables to be served to the swine according to schedules. Experiments reveal that our algorithm provides an efficient way for detecting swine, thereby providing a significant amount of accuracy in production monitoring.

Keywords: automatic swine counting, swine detection, swine production monitoring, ellipse fitting model, sobel filter

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Authors: Hang Yang, Jichao Li, Kewei Yang, Tianyang Lei

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Multivariate time series anomaly detection is a significant research topic in the field of data mining, encompassing a wide range of applications across various industrial sectors such as traffic roads, financial logistics, and corporate production. The inherent spatial dependencies and temporal characteristics present in multivariate time series introduce challenges to the anomaly detection task. Previous studies have typically been based on the assumption that all variables belong to the same spatial hierarchy, neglecting the multi-level spatial relationships. To address this challenge, this paper proposes a multi-scale spatial and unified temporal feature fusion network, denoted as MSUT-Net, for multivariate time series anomaly detection. The proposed model employs a multi-level modeling approach, incorporating both temporal and spatial modules. The spatial module is designed to capture the spatial characteristics of multivariate time series data, utilizing an adaptive graph structure learning model to identify the multi-level spatial relationships between data variables and their attributes. The temporal module consists of a unified temporal processing module, which is tasked with capturing the temporal features of multivariate time series. This module is capable of simultaneously identifying temporal dependencies among different variables. Extensive testing on multiple publicly available datasets confirms that MSUT-Net achieves superior performance on the majority of datasets. Our method is able to model and accurately detect systems data with multi-level spatial relationships from a spatial-temporal perspective, providing a novel perspective for anomaly detection analysis.

Keywords: data mining, industrial system, multivariate time series, anomaly detection

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Authors: Ilana Margalith, Adaya Meirowitz, Sigalit Cohavi

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Violence against health professionals by patients and their families have recently become a disturbing phenomenon worldwide, exacting psychological as well as economic tolls. Health workplaces in Israel (e.g. hospitals and H.M.O clinics) provide workshops for their employees, supplying them with coping strategies. However, these workshops do not focus on nursing students, who are also subjected to this violence. Their learning environment is no longer as protective as it used to be. Furthermore, coping with violence was not part of the curriculum for Israeli nursing students. Thus, based on human aggression theories which depict the pivotal role of the professional's correct response in preventing the onset of an aggressive response or the escalation of violence, a workshop was developed for undergraduate nursing students at the Clalit Nursing Academy, Rabin Campus (Dina), Israel. The workshop aimed at reducing students' anxiety vis a vis the aggressive patient or family in addition to strengthening their ability to cope with such situations. The students practiced interpersonal skills, especially relevant to early detection of potential violence, as well as ‘a correct response’ reaction to the violence, thus developing the necessary steps to be implemented when encountering violence in the workplace. In order to assess the efficiency of the workshop, the participants filled out a questionnaire comprising knowledge and self-efficacy scales. Moreover, the replies of the 23 participants in this workshop were compared with those of 24 students who attended a standard course on interpersonal communication. Students' self-efficacy and knowledge were measured in both groups before and after the course. A statistically significant interaction was found between group (workshop/standard course) and time (before/after) as to the influence on students' self-efficacy (p=0.004) and knowledge (p=0.007). Nursing students, who participated in this ‘coping with workplace violence’ workshop, gained knowledge, confidence and a sense of self-efficacy with regard to workplace violence. Early detection of signs of imminent violence amongst patients or families and the prevention of its escalation, as well as the ability to manage the threatening situation when occurring, are acquired skills. Encouraging nursing students to learn and practice these skills may enhance their ability to cope with these unfortunate occurrences.

Keywords: early detection of violence, nursing students, patient aggression, self-efficacy, workplace violence

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Authors: Najma Najam, Rukhsana Kausar, Rabia Hussain Kanwal, Saira Batool, Anum Javed

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In Pakistan, elderly population though increasing but it has been neglected by the researchers and policy makers which resulted in compromised quality of life of the ageing population. Two regions, Punjab and Gilgit-Baltistan (GB) were selected for comparison as Lahore and Multan (Punjab) are highly urbanized, large cities whereas Gilgit and Skardu are remote and mountain bounded valleys in GB. This study focuses on psychological and emotional functioning of elderly and a series of measures translated and adapted in Urdu language was used to assess quality of life, psychological and mental well-being, actual and perceived social support, attachment patterns, forgiveness, affects, geriatric depression, and emotional disturbance patterns (depression, anxiety, and stress) in elderly. A gender-equated sample of 201 elderly participants, 93 from GB (60 from Gilgit, 33 from Skardu) and 108 from Punjab (61 from Lahore, 47 from Multan) with over 60 years age was collected from the multiethnic community of Punjab and GB through purposive convenient sampling technique. Findings revealed that elderly from Multan have better psychological and emotional functioning, higher levels of social support, tendency to forgive, better mental wellbeing and quality of life and lower levels of stress, anxiety, depression, negative affect and attachment avoidance and anxiety related to partner as compared to the elderly from Lahore. Furthermore, both elderly male of Gilgit & Skardu have adequate mental well-being including subjective well-being and psychological functioning which showed positive aspects of mental health but elderly female are more attached to their home and neighbourhood which shows their social and environmental mastery. Gilgiti elderly male reported more degree of positive affect such as enthusiasm, active, alertness, excitement and strong whereas among elderly from Skardu shows more negative affect i.e. aversive mood states, irritability, hostility, and general distress. The need of psychosocial therapy and family counseling for the elderly in urban areas has been identified, which can facilitate in reducing or preventing the depressive and stressful tendencies. The findings are expected to have implications for improving quality of life of the elderly, designing interventions, support system and rehabilitation services to help them. However, findings may attract attention of policy makers and researchers as currently this is the most neglected population in Pakistan.

Keywords: psychological, emotional, aging, elderly, quality of life

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Authors: Esther Moraleda Sepúlveda, Soraya Delgado Matute, Paula Salido Escudero, Raquel Mimoso García, M Cristina Alcón Lancho

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Although there is some consensus when it comes to establishing the lexicon as one of the strengths of language in people with Down Syndrome (DS), little is known about its evolution throughout development and changes based on age. The objective of this study was to find out if there are differences in receptive vocabulary between adolescence and adulthood. In this research, 30 people with DS between 11 and 40 years old, divided into two age ranges (11-18; 19 - 30) and matched in mental age, were evaluated through the Peabody Vocabulary Test. The results show significant differences between both groups in favor of the group with the oldest chronological age and a direct correlation between chronological age and receptive vocabulary development, regardless of mental age. These data support the natural evolution of the passive lexicon in people with DS.

Keywords: down syndrome, language, receptive vocabulary, adolescents, adults

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Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

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Authors: Arwa Alzughaibi

Abstract:

Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

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Authors: Joanne M. Emmens

Abstract:

This paper makes use of the case notes of a single psychoanalytically informed psychotherapy of a now 72-year-old man over a four-year period to explore the potential of qualitative data to be incorporated into a research methodology that can contribute theory and knowledge to the wider professional community involved in mental health care. The clinical material arising out of any psychoanalysis provides a potentially rich source of clinical data that could contribute valuably to our historical understanding of both individual and societal traumata. As psychoanalysis is primarily an investigation, it is argued that clinical case material is a rich source of qualitative data which has relevance for sociological and historical understandings and that it can potentially aluminate important ‘gaps’ and collective blind spots that manifest unconsciously and are a contributing factor in the transmission of trauma, silently across generations. By attending to this case material the hope is to illustrate the value of using a psychoanalytic centred methodology. It is argued that the study of individual defences and the manner in which they come into consciousness, allows an insight into group defences and the unconscious forces that contribute to the silencing or un-noticing of important sources (or originators) of mental suffering.

Keywords: dream furniture (Bion) and psychotic functioning, reverie, screen memories, selected fact

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Authors: Sahar Esmaeili, Ramezanali Ghaderi sanavi, Masoomeh Maarefvand, Samaneh Hosseinzadeh

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Introduction: Conducted researches reveal that nowadays, 60 percent of women around the world are the households. The adverse economic condition causes female-headed households and their children to be the most vulnerable people against social harm. Mainly a symptoms of mental illness such as depression, anxiety, obsession and aggression can be seen in female-headed households and their children are potentially exposed to issues such as crime-work, child labor in the black and informal jobs, education deprivation and malnutrition. The aim of this study is to evaluate the effect of Orem self-care education with the FGC technique on the public health of female-headed households. Methods: Sixty-four Female-headed householders who were supported by Saleh Foundation participated in a clinical trial study and were assigned to the case (n=32) and control (n=32) groups. The case group received 4-session Orem’s self-care education with family group conferencing technique. Data were collected using the demographic questionnaire and General Health Questionnaire (GHQ-28) prior to intervention and post-intervention. ANOVA was used to evaluate outcomes. Results: The results showed significant improvement of the intervention group in GHQ (P<0.001) and subscales of Physical Health (P<0.001) Agitation and Insomnia (P<0.001) and Social disorder (P<0.001) and Depression (P<0.001) compared with the control group after the intervention. Conclusion: The intervention of Orem’s self-care education with family group conferencing technique was effective in improving the General Health of Female-headed households

Keywords: orem’s self-care, female-headed households, general health, group

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Authors: S. Korkut, M. S. Kilic, E. Erhan

Abstract:

In order to detect and quantify the phenolic contents of a wastewater with biosensors, two working electrodes based on modified Poly (Pyrrole) films were fabricated. Enzyme horseradish peroxidase was used as biomolecule of the prepared electrodes. Various phenolics were tested at the biosensor. Phenol detection was realized by electrochemical reduction of quinones produced by enzymatic activity. Analytical parameters were calculated and the results were compared with each other.

Keywords: carbon nanotube, phenol biosensor, polypyrrole, poly (glutaraldehyde)

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Authors: A. Nachour, L. Ouzizi, Y. Aoura

Abstract:

Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: edge detection, medical MRImages, multi-agent systems, vector field convolution

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Authors: Retno Supriyanti, Ahmad Chuzaeri, Yogi Ramadhani, A. Haris Budi Widodo

Abstract:

The use of ultrasonography in the medical world has been very popular including the diagnosis of pregnancy. In determining pregnancy, ultrasonography has many roles, such as to check the position of the fetus, abnormal pregnancy, fetal age and others. Unfortunately, all these things still need to analyze the role of the obstetrician in the sense of image raised by ultrasonography. One of the most striking is the determination of gestational age. Usually, it is done by measuring the length of the fetus manually by obstetricians. In this study, we developed a computer-aided diagnosis for the determination of gestational age by measuring the length of the fetus automatically using edge detection method and image morphology. Results showed that the system is sufficiently accurate in determining the gestational age based image processing.

Keywords: computer aided diagnosis, gestational age, and diameter of uterus, length of fetus, edge detection method, morphology image

Procedia PDF Downloads 299