Search results for: healthcare data security
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 27833

Search results for: healthcare data security

22373 Navigating Complex Communication Dynamics in Qualitative Research

Authors: Kimberly M. Cacciato, Steven J. Singer, Allison R. Shapiro, Julianna F. Kamenakis

Abstract:

This study examines the dynamics of communication among researchers and participants who have various levels of hearing, use multiple languages, have various disabilities, and who come from different social strata. This qualitative methodological study focuses on the strategies employed in an ethnographic research study examining the communication choices of six sets of parents who have Deaf-Disabled children. The participating families varied in their communication strategies and preferences including the use of American Sign Language (ASL), visual-gestural communication, multiple spoken languages, and pidgin forms of each of these. The research team consisted of two undergraduate students proficient in ASL and a Deaf principal investigator (PI) who uses ASL and speech as his main modes of communication. A third Hard-of-Hearing undergraduate student fluent in ASL served as an objective facilitator of the data analysis. The team created reflexive journals by audio recording, free writing, and responding to team-generated prompts. They discussed interactions between the members of the research team, their evolving relationships, and various social and linguistic power differentials. The researchers reflected on communication during data collection, their experiences with one another, and their experiences with the participating families. Reflexive journals totaled over 150 pages. The outside research assistant reviewed the journals and developed follow up open-ended questions and prods to further enrich the data. The PI and outside research assistant used NVivo qualitative research software to conduct open inductive coding of the data. They chunked the data individually into broad categories through multiple readings and recognized recurring concepts. They compared their categories, discussed them, and decided which they would develop. The researchers continued to read, reduce, and define the categories until they were able to develop themes from the data. The research team found that the various communication backgrounds and skills present greatly influenced the dynamics between the members of the research team and with the participants of the study. Specifically, the following themes emerged: (1) students as communication facilitators and interpreters as barriers to natural interaction, (2) varied language use simultaneously complicated and enriched data collection, and (3) ASL proficiency and professional position resulted in a social hierarchy among researchers and participants. In the discussion, the researchers reflected on their backgrounds and internal biases of analyzing the data found and how social norms or expectations affected the perceptions of the researchers in writing their journals. Through this study, the research team found that communication and language skills require significant consideration when working with multiple and complex communication modes. The researchers had to continually assess and adjust their data collection methods to meet the communication needs of the team members and participants. In doing so, the researchers aimed to create an accessible research setting that yielded rich data but learned that this often required compromises from one or more of the research constituents.

Keywords: American Sign Language, complex communication, deaf-disabled, methodology

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22372 Using Discriminant Analysis to Forecast Crime Rate in Nigeria

Authors: O. P. Popoola, O. A. Alawode, M. O. Olayiwola, A. M. Oladele

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This research work is based on using discriminant analysis to forecast crime rate in Nigeria between 1996 and 2008. The work is interested in how gender (male and female) relates to offences committed against the government, against other properties, disturbance in public places, murder/robbery offences and other offences. The data used was collected from the National Bureau of Statistics (NBS). SPSS, the statistical package was used to analyse the data. Time plot was plotted on all the 29 offences gotten from the raw data. Eigenvalues and Multivariate tests, Wilks’ Lambda, standardized canonical discriminant function coefficients and the predicted classifications were estimated. The research shows that the distribution of the scores from each function is standardized to have a mean O and a standard deviation of 1. The magnitudes of the coefficients indicate how strongly the discriminating variable affects the score. In the predicted group membership, 172 cases that were predicted to commit crime against Government group, 66 were correctly predicted and 106 were incorrectly predicted. After going through the predicted classifications, we found out that most groups numbers that were correctly predicted were less than those that were incorrectly predicted.

Keywords: discriminant analysis, DA, multivariate analysis of variance, MANOVA, canonical correlation, and Wilks’ Lambda

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22371 Implementation of Algorithm K-Means for Grouping District/City in Central Java Based on Macro Economic Indicators

Authors: Nur Aziza Luxfiati

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Clustering is partitioning data sets into sub-sets or groups in such a way that elements certain properties have shared property settings with a high level of similarity within one group and a low level of similarity between groups. . The K-Means algorithm is one of thealgorithmsclustering as a grouping tool that is most widely used in scientific and industrial applications because the basic idea of the kalgorithm is-means very simple. In this research, applying the technique of clustering using the k-means algorithm as a method of solving the problem of national development imbalances between regions in Central Java Province based on macroeconomic indicators. The data sample used is secondary data obtained from the Central Java Provincial Statistics Agency regarding macroeconomic indicator data which is part of the publication of the 2019 National Socio-Economic Survey (Susenas) data. score and determine the number of clusters (k) using the elbow method. After the clustering process is carried out, the validation is tested using themethodsBetween-Class Variation (BCV) and Within-Class Variation (WCV). The results showed that detection outlier using z-score normalization showed no outliers. In addition, the results of the clustering test obtained a ratio value that was not high, namely 0.011%. There are two district/city clusters in Central Java Province which have economic similarities based on the variables used, namely the first cluster with a high economic level consisting of 13 districts/cities and theclustersecondwith a low economic level consisting of 22 districts/cities. And in the cluster second, namely, between low economies, the authors grouped districts/cities based on similarities to macroeconomic indicators such as 20 districts of Gross Regional Domestic Product, with a Poverty Depth Index of 19 districts, with 5 districts in Human Development, and as many as Open Unemployment Rate. 10 districts.

Keywords: clustering, K-Means algorithm, macroeconomic indicators, inequality, national development

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22370 Drug-related Problems and Associated Factors among Adult Psychiatric Inpatients in Northwest Ethiopia: Multicenter Cross-Sectional Study

Authors: Ephrem Mebratu Dagnew, Mohammed Biset Ayalew, Gizework Alemnew Mekonnen, Alehegn Bishaw Geremew, Ousman Abubeker Abdela

Abstract:

Objective: To assess the prevalence of drug-related problems and associated factors among adult psychiatric inpatients. Method: Hospital-based multicenter cross-sectional observational study was conducted from April to July 2021 at five randomly selected hospitals in North-west Ethiopia. A total of 325 consecutively sampled patients participated in the study. Clinical pharmacists assessed the DRPs based on clinical judgment supported by updated evidence-based diseases guidelines. A Medscape drug-interactions checker was used to check drug-drug interactions. The results were summarized using descriptive statistics, including frequency, mean, and standard deviation. Odds ratio (OR) with 95% confidence interval were also computed for each variable for the corresponding P-value. The value of P ≤ 0.05 was considered statistically significant. Result : From the total of 325 study participants, more than half of them (52.9%) were females and the mean age ± (standard deviation) was 30.8±11.3 years. At least one drug-related problem was recorded from 60.9%, 95% CI (55.7-65.8) of study participants with a mean of 0.6±0.49 per patient. Need additional drug therapy was the most common DRP (22.8%), followed by non-adherence to medicine (20.6%) and adverse drug reactions (11%), respectively. Factors independently associated with drug-related problems were rural residence [AOR=1.96,95%CI:1.01-2.84, P-value=0.046], self-employed [AOR=6.0 ,95% CI: 1.0-36.9, P-value=0.035] and alcohol drinkers [AOR=6.40,95%CI:1.12-37.5, p-value=0.034]. Conclusion: The prevalence of drug-related problems among adult psychiatric patients admitted to psychiatric wards was high. Healthcare providers give more attention to tackling these problems. Being a rural residence, self-employed, and Alcohol drinkers were associated with drug-related problems.

Keywords: psychiatric patients, drug-relatedproblems, multicenter, Ethiopia

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22369 A Study of Behavioral Phenomena Using an Artificial Neural Network

Authors: Yudhajit Datta

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Will is a phenomenon that has puzzled humanity for a long time. It is a belief that Will Power of an individual affects the success achieved by an individual in life. It is thought that a person endowed with great will power can overcome even the most crippling setbacks of life while a person with a weak will cannot make the most of life even the greatest assets. Behavioral aspects of the human experience such as will are rarely subjected to quantitative study owing to the numerous uncontrollable parameters involved. This work is an attempt to subject the phenomena of will to the test of an artificial neural network. The claim being tested is that will power of an individual largely determines success achieved in life. In the study, an attempt is made to incorporate the behavioral phenomenon of will into a computational model using data pertaining to the success of individuals obtained from an experiment. A neural network is to be trained using data based upon part of the model, and subsequently used to make predictions regarding will corresponding to data points of success. If the prediction is in agreement with the model values, the model is to be retained as a candidate. Ultimately, the best-fit model from among the many different candidates is to be selected, and used for studying the correlation between success and will.

Keywords: will power, will, success, apathy factor, random factor, characteristic function, life story

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22368 The Effect of Fetal Movement Counting on Maternal Antenatal Attachment

Authors: Esra Güney, Tuba Uçar

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Aim: This study has been conducted for the purpose of determining the effects of fetal movement counting on antenatal maternal attachment. Material and Method: This research was conducted on the basis of the real test model with the pre-test /post-test control groups. The study population consists of pregnant women registered in the six different Family Health Centers located in the central Malatya districts of Yeşilyurt and Battalgazi. When power analysis is done, the sample size was calculated for each group of at least 55 pregnant women (55 tests, 55 controls). The data were collected by using Personal Information Form and MAAS (Maternal Antenatal Attachment Scale) between July 2015-June 2016. Fetal movement counting training was given to pregnant women by researchers in the experimental group after the pre-test data collection. No intervention was applied to the control group. Post-test data for both groups were collected after four weeks. Data were evaluated with percentage, chi-square arithmetic average, chi-square test and as for the dependent and independent group’s t test. Result: In the MAAS, the pre-test average of total scores in the experimental group is 70.78±6.78, control group is also 71.58±7.54 and so there was no significant difference in mean scores between the two groups (p>0.05). MAAS post-test average of total scores in the experimental group is 78.41±6.65, control group is also is 72.25±7.16 and so the mean scores between groups were found to have statistically significant difference (p<0.05). Conclusion: It was determined that fetal movement counting increases the maternal antenatal attachments.

Keywords: antenatal maternal attachment, fetal movement counting, pregnancy, midwifery

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22367 Investigating the Relationship between Service Quality and Amount of Violations in Community Pharmacies with Their Type of Ownership

Authors: Afshin Azari, Farzad Peiravian, Nazila Yousefi

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Introduction: Community pharmacies have been always played an important role in public health. Therefore, having a decent service provided by these pharmacies is of paramount importance for the healthcare system. The issue of pharmacy ownership and its possible impact on the quality of services and amount of violations has been argued for many years, and there are different opinions around this debate. Since, so far, no scientific research has been performed to investigate this issue in Iran, this study aimed to examine the differences between these two types of pharmacies ownership in terms of violations and service quality. Method: This study investigates the impact of two different kinds of pharmacy ownership (pharmacists and non-pharmacist’s ownership) on the pharmacies’ amount of violations and services quality. Pharmacies’ amount of violations was examined using “pharmacy inspection reports” between September 2018 and September 2019, in their distinguishable categories: minor, major and critical violations. Then, service quality was examined using a questionnaire from the perspective of pharmacy customers. Results: Considering violations, there was no evidence to prove a significant relationship between critical violations and major violations with the type of pharmacy ownership. However, in minor violations, the average of violations was higher in pharmacies owned by pharmacists in comparison to their non-pharmacist owned counterparts. Regarding service quality, the results showed that there is no significant relationship between the quality of service and the type of pharmacy ownership. Discussion and Conclusion: In this study, no significant relationship was found between the amount of violations and the type of pharmacy ownership. This could indicate that the pharmacy ownership would not influence the rate of violations. Considering that more inspections have been carried out in non-pharmacist owned pharmacies, it can be concluded that these pharmacies are more under control, and in fact, this monitoring has reduced violations in these pharmacies. The quality of services in the two types of pharmacies were not significantly different from each other, and this shows that non-pharmacist-owned pharmacies also try to maintain the desired level of service in competition with their competitors.

Keywords: pharmacy ownership, quality of service, violation, community pharmacy

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22366 The Endocrinology of Obesity and Dejenerative Joint Disease

Authors: Kebret Kebede, Anthony Scinta

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Obesity is the most prevalent global problem that continues to rise at alarming rates both in the industrialized and developing countries. Adipose tissue is an endocrine tissue that secretes numerous chemical signals, hormones, lipids, cytokines and coagulation factors as well as prompting insulin resistance which is a primary contributor to Type II Diabetes- one of its most common adverse effects on health. Other hormones whose levels are linked to obesity and nutritional state are leptin, IGF-1, and adiponectin. Several studies indicate that obesity is the leading cause of high levels of cholesterol that leads to fatty liver disease, gallstones, hypertension, increased risk for cancer and degenerative joint disease that primarily affects the weight bearing joints of the lower extremities. The activation of inflammatory pathways promotes synovial pathology that results in accelerated degeneration of the joints. The study examines the prevalence of obesity in the US female population in comparison to that of the developing world and its emergence as a significant and potentially modifiable risk factor in degenerative disease of the hip and knee joints that has resulted in staggering healthcare cost. Studies have shown that as the prevalence of obesity rises, we continue to see a rise in degenerative joint disease. The percentage of arthritis cases linked directly to obesity has risen from 3 percent in 1971 to 18 percent in 2002. A person with obesity is around 60 percent more likely to develop arthritis than someone of normal body weight. In women, obesity is associated with increased mortality from breast, cervical, endometrial and ovarian cancer that may accompany debilitating joint diseases and restricted mobility.

Keywords: obesity, endocrine, degenerative, mortality, joint diseases, cancer, debilitating, mobility

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22365 Wearable Monitoring and Treatment System for Parkinson’s Disease

Authors: Bulcha Belay Etana, Benny Malengier, Janarthanan Krishnamoorthy, Timothy Kwa, Lieva Vanlangenhove

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Electromyography measures the electrical activity of muscles using surface electrodes or needle electrodes to monitor various disease conditions. Recent developments in the signal acquisition of electromyograms using textile electrodes facilitate wearable devices, enabling patients to monitor and control their health status outside of healthcare facilities. Here, we have developed and tested wearable textile electrodes to acquire electromyography signals from patients suffering from Parkinson’s disease and incorporated a feedback-control system to relieve muscle cramping through thermal stimulus. In brief, the textile electrodes made of stainless steel was knitted into a textile fabric as a sleeve, and their electrical characteristic, such as signal-to-noise ratio, was compared with traditional electrodes. To relieve muscle cramping, a heating element made of stainless-steel conductive yarn sewn onto a cotton fabric, coupled with a vibration system, was developed. The system integrated a microcontroller and a Myoware muscle sensor to activate the heating element as well as the vibration motor when cramping occurred. At the same time, the element gets deactivated when the muscle cramping subsides. An optimum therapeutic temperature of 35.5°C is regulated and maintained continuously by a heating device. The textile electrode exhibited a signal-to-noise ratio of 6.38dB, comparable to that of the traditional electrode’s value of 7.05 dB. For a given 9 V power supply, the rise time for the developed heating element was about 6 minutes to reach an optimum temperature.

Keywords: smart textile system, wearable electronic textile, electromyography, heating textile, vibration therapy, Parkinson’s disease

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22364 Semi-Supervised Learning Using Pseudo F Measure

Authors: Mahesh Balan U, Rohith Srinivaas Mohanakrishnan, Venkat Subramanian

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Positive and unlabeled learning (PU) has gained more attention in both academic and industry research literature recently because of its relevance to existing business problems today. Yet, there still seems to be some existing challenges in terms of validating the performance of PU learning, as the actual truth of unlabeled data points is still unknown in contrast to a binary classification where we know the truth. In this study, we propose a novel PU learning technique based on the Pseudo-F measure, where we address this research gap. In this approach, we train the PU model to discriminate the probability distribution of the positive and unlabeled in the validation and spy data. The predicted probabilities of the PU model have a two-fold validation – (a) the predicted probabilities of reliable positives and predicted positives should be from the same distribution; (b) the predicted probabilities of predicted positives and predicted unlabeled should be from a different distribution. We experimented with this approach on a credit marketing case study in one of the world’s biggest fintech platforms and found evidence for benchmarking performance and backtested using historical data. This study contributes to the existing literature on semi-supervised learning.

Keywords: PU learning, semi-supervised learning, pseudo f measure, classification

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22363 Attachment Systems and Psychotherapy: An Internal Secure Caregiver to Heal and Protect the Parts of Our Clients: InCorporer Method

Authors: Julien Baillet

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In light of 30 years of scientific research, InCorporer Method was created in 2019 as a new approach to heal traumatic, developmental, and dissociative injuries. Following natural nervous system functions, InCorporer aims to heal, develop, and update the different defensive mammalian subsystems: fight, flight, freeze, feign death, cry for help, & energy regulator. The dimensions taken into account are: (i) Heal the traumatic injuries who are still bleeding, (ii) Develop the systems that never received the security, attention, and affection they needed. (iii) Update the parts that stayed stuck in the past, ignoring for too long that they are out of danger now. Through the Present Part and its caregiving skills, InCorporer method enables a balanced, soothed, and collaborative personality system. To be as integrative as possible, InCorporer method has been designed according to several fields of research, such as structural dissociation theory, attachment theory, and information processing theory. In this paper, the author presents how the internal caregiver is developed and trained to heal all the different parts/subsystems of our clients through mindful attention and reflex movement integration.

Keywords: PTSD, attachment, dissociation, part work

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22362 Implementing the Quality of Care Partnership to Reduce the Cost of Screenings for Sexually Transmitted Infections on a Southeastern College Campus

Authors: Amy Guidera, Steven Busby, Christian Williams, David Phillippi

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College students are a priority preventative healthcare population that can engage in high-risk behaviors which may concurrently increase the potential for unsafe sexual practices, including contracting sexually transmitted infections (STIs). Early education, screening, treatment, and partner notification are important interventions for breaking the chain of transmission and recurrence in relation to preventing poor health outcomes and mitigating college dropout rates. The aim of this quality improvement project was to determine if the reduction in STI screening costs for college students (aged 18-30 years old) would increase the amount of STI screenings conducted at a university health center over the course of an academic semester while evaluating our ability to achieve an improved quality of care at a reduced cost, along with improved STI reporting and documentation. This study was conducted through retrospective chart reviews of STI-related visits and utilized the RADAR matrix to provide a guiding, iterative mechanism to continuously reassess goals and outcomes defined in a memorandum of agreement (MOA) between a university health center and the state department of health (DOH) laboratory. The project failed to increase the amount of STI screenings, most likely due to the emergence of COVID-19, but resulted in improved quality of care for students, improved STI-related visit documentation and reporting, and significantly reduced costs for STI screening for collegiate students at a southeastern private university campus.

Keywords: college health, college students, preventive health, reproductive health, sexually transmitted infections, young adults

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22361 Islamic Banking and Finance in Nigeria: Challenges and Opportunities

Authors: Ya'u Saidu

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The introduction of the non-interest banking system in Nigeria was part of the regulators efforts to increase the inclusion of other stakeholders into the financial sector who have stayed out of the sector for some reasons. However, the concept has been misunderstood by various stakeholders within the country where some view it as a Muslim affair which exclude the non-Muslims from gaining despite its existence in advance countries of the world. This paper attempts to fill-in the gap created by the literature especially with regards to the proper education and enlightenment of the Nigerian citizens. Survey research method was employed where primary data was collected using questionnaire and convenience sampling was used to select 100 respondents. The data was analysed using Chi-square. It was found that lack of knowledge on Islamic banking has significant effect on its prospects.

Keywords: finance, non-interest, sustainability, enlightenment

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22360 Modeling Residual Modulus of Elasticity of Self-Compacted Concrete Using Artificial Neural Networks

Authors: Ahmed M. Ashteyat

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Artificial Neural Network (ANN) models have been widely used in material modeling, inter-correlations, as well as behavior and trend predictions when the nonlinear relationship between system parameters cannot be quantified explicitly and mathematically. In this paper, ANN was used to predict the residual modulus of elasticity (RME) of self compacted concrete (SCC) damaged by heat. The ANN model was built, trained, tested and validated using a total of 112 experimental data sets, gathered from available literature. The data used in model development included temperature, relative humidity conditions, mix proportions, filler types, and fiber type. The result of ANN training, testing, and validation indicated that the RME of SCC, exposed to different temperature and relative humidity levels, could be predicted accurately with ANN techniques. The reliability between the predicated outputs and the actual experimental data was 99%. This show that ANN has strong potential as a feasible tool for predicting residual elastic modulus of SCC damaged by heat within the range of input parameter. The ANN model could be used to estimate the RME of SCC, as a rapid inexpensive substitute for the much more complicated and time consuming direct measurement of the RME of SCC.

Keywords: residual modulus of elasticity, artificial neural networks, self compacted-concrete, material modeling

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22359 Capacity Loss of Urban Arterial Roads under the Influence of Bus Stop

Authors: Sai Chand, Ashish Dhamaniya, Satish Chandra

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Curbside bus stops are provided on urban roads when sufficient land is not available to construct bus bays. The present study demonstrates the effect of curbside bus stops on midblock capacity of an urban arterial road. Data were collected on seven sections of 6-lane urban arterial roads in New Delhi. Three sections were selected without any side friction to estimate the base value of capacity. Remaining four sections were with curbside bus stop. Speed and volume data were collected in field and these data were used to estimate the capacity of a section. The average base midblock capacity of a 6–lane divided urban road was found to be 6314 PCU/hr which was further referred as base capacity. Effect of curbside bus stop on midblock capacity of urban road was evaluated by comparing the capacity of a section with curbside bus stop with that of the base capacity. Finally, a mathematical relation has been developed between bus frequency and capacity loss. Also a relation has been suggested between dwell time and capacity loss. The developed relations would be very useful for practising engineers to estimate capacity loss due to bus stop.

Keywords: bus frequency, bus stops, capacity loss, urban arterial

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22358 An Analysis of the Relation between Need for Psychological Help and Psychological Symptoms

Authors: İsmail Ay

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In this study, it was aimed to determine the relations between need for psychological help and psychological symptoms. The sample of the study consists of 530 university students getting educated in University of Atatürk in 2015-2016 academic years. Need for Psychological Help Scale and Brief Symptom Inventory were used to collect data in the study. In data analysis, correlation analysis and structural equation model with latent variables were used. Normality and homogeneity analyses were used to analyze the basic conditions of parametric tests. The findings obtained from the study show that as the psychological symptoms increase, need for psychological help also increases. The findings obtained through the study were approached according to the literature.

Keywords: psychological symptoms, need for psychological help, structural equation model, correlation

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22357 Advancing Early Intervention Strategies for United States Adolescents and Young Adults with Schizophrenia in the Post-COVID-19 Era

Authors: Peggy M. Randon, Lisa Randon

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Introduction: The post-COVID-19 era has presented unique challenges for addressing complex mental health issues, particularly due to exacerbated stress, increased social isolation, and disrupted continuity of care. This article outlines relevant health disparities and policy implications within the context of the United States while maintaining international relevance. Methods: A comprehensive literature review (including studies, reports, and policy documents) was conducted to examine concerns related to childhood-onset schizophrenia and the impact on patients and their families. Qualitative and quantitative data were synthesized to provide insights into the complex etiology of schizophrenia, the effects of the pandemic, and the challenges faced by socioeconomically disadvantaged populations. Case studies were employed to illustrate real-world examples and areas requiring policy reform. Results: Early intervention in childhood is crucial for preventing or mitigating the long-term impact of complex psychotic disorders, particularly schizophrenia. A comprehensive understanding of the genetic, environmental, and physiological factors contributing to the development of schizophrenia is essential. The COVID-19 pandemic worsened symptoms and disrupted treatment for many adolescent patients with schizophrenia, emphasizing the need for adaptive interventions and the utilization of virtual platforms. Health disparities, including stigma, financial constraints, and language or cultural barriers, further limit access to care, especially for socioeconomically disadvantaged populations. Policy implications: Current US health policies inadequately support patients with schizophrenia. The limited availability of longitudinal care, insufficient resources for families, and stigmatization represent ongoing policy challenges. Addressing these issues necessitates increased research funding, improved access to affordable treatment plans, and cultural competency training for healthcare providers. Public awareness campaigns are crucial to promote knowledge, awareness, and acceptance of mental health disorders. Conclusion: The unique challenges faced by children and families in the US affected by schizophrenia and other psychotic disorders have yet to be adequately addressed on institutional and systemic levels. The relevance of findings to an international audience is emphasized by examining the complex factors contributing to the onset of psychotic disorders and their global policy implications. The broad impact of the COVID-19 pandemic on mental health underscores the need for adaptive interventions and global responses. Addressing policy challenges, improving access to care, and reducing the stigma associated with mental health disorders are crucial steps toward enhancing the lives of adolescents and young adults with schizophrenia and their family members. The implementation of virtual platforms can help overcome barriers and ensure equitable access to support and resources for all patients, enabling them to lead healthy and fulfilling lives.

Keywords: childhood, schizophrenia, policy, United, States, health, disparities

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22356 Comparative Analysis of Change in Vegetation in Four Districts of Punjab through Satellite Imagery, Land Use Statistics and Machine Learning

Authors: Mirza Waseem Abbas, Syed Danish Raza

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For many countries agriculture is still the major force driving the economy and a critically important socioeconomic sector, despite exceptional industrial development across the globe. In countries like Pakistan, this sector is considered the backbone of the economy, and most of the economic decision making revolves around agricultural outputs and data. Timely and accurate facts and figures about this vital sector hold immense significance and have serious implications for the long-term development of the economy. Therefore, any significant improvements in the statistics and other forms of data regarding agriculture sector are considered important by all policymakers. This is especially true for decision making for the betterment of crops and the agriculture sector in general. Provincial and federal agricultural departments collect data for all cash and non-cash crops and the sector, in general, every year. Traditional data collection for such a large sector i.e. agriculture, being time-consuming, prone to human error and labor-intensive, is slowly but gradually being replaced by remote sensing techniques. For this study, remotely sensed data were used for change detection (machine learning, supervised & unsupervised classification) to assess the increase or decrease in area under agriculture over the last fifteen years due to urbanization. Detailed Landsat Images for the selected agricultural districts were acquired for the year 2000 and compared to images of the same area acquired for the year 2016. Observed differences validated through detailed analysis of the areas show that there was a considerable decrease in vegetation during the last fifteen years in four major agricultural districts of the Punjab province due to urbanization (housing societies).

Keywords: change detection, area estimation, machine learning, urbanization, remote sensing

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22355 EMS Providers' Ability and Willingness to Respond to Bioterrorism

Authors: Ryan Houser

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Introduction: Previous studies have found that public health systems within the United States are inadequately prepared for an act of biological terrorism. As the COVID-19 pandemic continues, few studies have evaluated bioterrorism preparedness of Emergency Medical Services, even in the accelerating environment of biothreats. Methods: This study utilized an Internet-based survey to assess the level of preparedness and willingness to respond to a bioterrorism attack and identify factors that predict preparedness and willingness among Nebraska EMS (Emergency Medical Services ) providers. The survey was available for one month in 2021, during which 190 EMS providers responded to the survey. Results: Only 56.8% of providers were able to recognize an illness or injury as potentially resulting from exposure to a CBRN agent. The provider Clinical Competency levels range from a low of 13.6% (ability to initiate patient care within his/her professional scope of practice and arrange for prompt referral appropriate to the identified condition(s)) to a high of 74% (the ability to respond to an emergency within the emergency management system of his/her practice, institution and community). Only 10% of the respondents are both willing and able to effectively function in a bioterror environment. Discussion: In order to effectively prepare for and respond to a bioterrorist attack, all levels of the healthcare system need to have the clinical skills, knowledge, and abilities necessary to treat patients exposed. Policy changes and increased focus on training and drills are needed to ensure a prepared EMS system which is crucial to a resilient state. EMS entities need to be aware of the extent of their available workforce so that the country can be prepared for the increasing threat of bioterrorism or other novel emerging infectious disease outbreaks. A resilient nation relies on a prepared set of EMS providers who are willing to respond to biological terrorism events.

Keywords: bioterrorism, prehospital, EMS, disaster, emergency, medicine, preparedness, policy

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22354 Determinants of Access to Finance to All Enterprise

Authors: Dilang Thouk Tharjiath

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This study seeks to examine determinants of access to finance: the case of micro and small enterprises in bonga town. It identifies the sector as the key to unlocking the economic potentials of the country. For the achievement of the objective of the study simple random and stratified sampling has been used to select 179 respondents, primary and secondary data were used, primary data were collected through face to face interview and preparing questionnaire and secondary data were collected through reviewing firms record and reports, quantitative research approach were used and the data obtained were analyzed using descriptive research design. Access to finance is one of the key obstacles of MSE’s not only when starting the business project but also when operating. Identifying the major determinants of access to finance is therefore quite crucial. Based on descriptive result the financiers specially formal financiers tend to grant credit easily for enterprises which are located near to town, having operators with higher educational level, experienced and with a positive attitudes towards or fulfill their lending procedures, and a firm having collateralized asset, prepare business plan, maintain accounting practice ,large and old enough. Finally the study recommended that As Educational level of entrepreneurs has significant effect on access to credit from bank and the managers or owners education level is low in Bonga town the concerned bodies of both the government and non-governmental institutions in collaboration with Bonga town MSE development office are recommended to create awareness and facilitate the provision of additional training for those with lower educational level.

Keywords: credit, entrepreneur, enterprise, manager

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22353 Reliability Analysis of Geometric Performance of Onboard Satellite Sensors: A Study on Location Accuracy

Authors: Ch. Sridevi, A. Chalapathi Rao, P. Srinivasulu

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The location accuracy of data products is a critical parameter in assessing the geometric performance of satellite sensors. This study focuses on reliability analysis of onboard sensors to evaluate their performance in terms of location accuracy performance over time. The analysis utilizes field failure data and employs the weibull distribution to determine the reliability and in turn to understand the improvements or degradations over a period of time. The analysis begins by scrutinizing the location accuracy error which is the root mean square (RMS) error of differences between ground control point coordinates observed on the product and the map and identifying the failure data with reference to time. A significant challenge in this study is to thoroughly analyze the possibility of an infant mortality phase in the data. To address this, the Weibull distribution is utilized to determine if the data exhibits an infant stage or if it has transitioned into the operational phase. The shape parameter beta plays a crucial role in identifying this stage. Additionally, determining the exact start of the operational phase and the end of the infant stage poses another challenge as it is crucial to eliminate residual infant mortality or wear-out from the model, as it can significantly increase the total failure rate. To address this, an approach utilizing the well-established statistical Laplace test is applied to infer the behavior of sensors and to accurately ascertain the duration of different phases in the lifetime and the time required for stabilization. This approach also helps in understanding if the bathtub curve model, which accounts for the different phases in the lifetime of a product, is appropriate for the data and whether the thresholds for the infant period and wear-out phase are accurately estimated by validating the data in individual phases with Weibull distribution curve fitting analysis. Once the operational phase is determined, reliability is assessed using Weibull analysis. This analysis not only provides insights into the reliability of individual sensors with regards to location accuracy over the required period of time, but also establishes a model that can be applied to automate similar analyses for various sensors and parameters using field failure data. Furthermore, the identification of the best-performing sensor through this analysis serves as a benchmark for future missions and designs, ensuring continuous improvement in sensor performance and reliability. Overall, this study provides a methodology to accurately determine the duration of different phases in the life data of individual sensors. It enables an assessment of the time required for stabilization and provides insights into the reliability during the operational phase and the commencement of the wear-out phase. By employing this methodology, designers can make informed decisions regarding sensor performance with regards to location accuracy, contributing to enhanced accuracy in satellite-based applications.

Keywords: bathtub curve, geometric performance, Laplace test, location accuracy, reliability analysis, Weibull analysis

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22352 The Impact of a Lower Health Literacy in the Self-Management of Patients with a Multiple Sclerosis: A Literature Review

Authors: Helga Martins, Idália Matias

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Background:Multiple sclerosis is a chronic inflammatory autoimmune demyelinating disease that affects young adults. Multiple sclerosis is a chronic disease in which the patient needs to self-manage the disease and the therapeutic regimen. Consequently, the promotion of health literacy assumes a relevant role for the accessibility, understanding, and use of information in order to promote and maintain the health of patients with multiple sclerosis. Aim: To determine the impact of lower health literacy in the self-management of patients with a multiple sclerosis. Methods: Literature review based on a search on the following electronic databases: CINAHLand MEDLINE; comprising all results published between September 2016 and September 2021. The search strategy was: (“Self-management [MeSH]” AND “Multiple sclerosis[MeSH]”AND “Health literacy[MeSH]”). The inclusion criteria were: original papers reporting about multiple sclerosis patients; participants with age above 18 years old, written in English, Spanish, French, or Portuguese. Two independent reviewers have done the screening and analysis of the results. 38 citations were identified, and after duplicates removal, a total of 25 results were screened; 14 were included after the application of the inclusion criteria. Results: The lower health literacy in the self-management of patients with a multiple sclerosis is related toless healthy choices, riskier health behavior, poor health outcomes, decreased of adhering to the therapeutic regimen after discharge, less self-management of chronic illness, and increased the time of hospitalization. Conclusion: Inadequate levels of health literacy contribute to poor health outcomes, unsuccessful self-management of chronic illness, and inadequate adherence to the therapeutic regimen. Therefore, health literacy is important for health policy and the healthcare services, as it can be understood as a mediator of self-management of multiple sclerosis disease.

Keywords: health literacy, multiple sclerosis, review, self-management

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22351 An Econometric Analysis of the Flat Tax Revolution

Authors: Wayne Tarrant, Ethan Petersen

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The concept of a flat tax goes back to at least the Biblical tithe. A progressive income tax was first vociferously espoused in a small, but famous, pamphlet in 1848 (although England had an emergency progressive tax for war costs prior to this). Within a few years many countries had adopted the progressive structure. The flat tax was only reinstated in some small countries and British protectorates until Mart Laar was elected Prime Minister of Estonia in 1992. Since Estonia’s adoption of the flat tax in 1993, many other formerly Communist countries have likewise abandoned progressive income taxes. Economists had expectations of what would happen when a flat tax was enacted, but very little work has been done on actually measuring the effect. With a testbed of 21 countries in this region that currently have a flat tax, much comparison is possible. Several countries have retained progressive taxes, giving an opportunity for contrast. There are also the cases of Czech Republic and Slovakia, which have adopted and later abandoned the flat tax. Further, with over 20 years’ worth of economic history in some flat tax countries, we can begin to do some serious longitudinal study. In this paper we consider many economic variables to determine if there are statistically significant differences from before to after the adoption of a flat tax. We consider unemployment rates, tax receipts, GDP growth, Gini coefficients, and market data where the data are available. Comparisons are made through the use of event studies and time series methods. The results are mixed, but we draw statistically significant conclusions about some effects. We also look at the different implementations of the flat tax. In some countries there are equal income and corporate tax rates. In others the income tax has a lower rate, while in others the reverse is true. Each of these sends a clear message to individuals and corporations. The policy makers surely have a desired effect in mind. We group countries with similar policies, try to determine if the intended effect actually occurred, and then report the results. This is a work in progress, and we welcome the suggestion of variables to consider. Further, some of the data from before the fall of the Iron Curtain are suspect. Since there are new ruling regimes in these countries, the methods of computing different statistical measures has changed. Although we first look at the raw data as reported, we also attempt to account for these changes. We show which data seem to be fictional and suggest ways to infer the needed statistics from other data. These results are reported beside those on the reported data. Since there is debate about taxation structure, this paper can help inform policymakers of change the flat tax has caused in other countries. The work shows some strengths and weaknesses of a flat tax structure. Moreover, it provides beginnings of a scientific analysis of the flat tax in practice rather than having discussion based solely upon theory and conjecture.

Keywords: flat tax, financial markets, GDP, unemployment rate, Gini coefficient

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22350 Attendance Management System Implementation Using Face Recognition

Authors: Zainab S. Abdullahi, Zakariyya H. Abdullahi, Sahnun Dahiru

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Student attendance in schools is a very important aspect in school management record. In recent years, security systems have become one of the most demanding systems in school. Every institute have its own method of taking attendance, many schools in Nigeria use the old fashion way of taking attendance. That is writing the students name and registration number in a paper and submitting it to the lecturer at the end of the lecture which is time-consuming and insecure, because some students can write for their friends without the lecturer’s knowledge. In this paper, we propose a system that takes attendance using face recognition. There are many automatic methods available for this purpose i.e. biometric attendance, but they all waste time, because the students have to follow a queue to put their thumbs on a scanner which is time-consuming. This attendance is recorded by using a camera attached in front of the class room and capturing the student images, detect the faces in the image and compare the detected faces with database and mark the attendance. The principle component analysis was used to recognize the faces detected with a high accuracy rate. The paper reviews the related work in the field of attendance system, then describe the system architecture, software algorithm and result.

Keywords: attendance system, face detection, face recognition, PCA

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22349 Temporal Delays along the Neurosurgical Care Continuum for Traumatic Brain Injury Patients in Mulago Hospital in Kampala Uganda

Authors: Silvia D. Vaca, Benjamin J. Kuo, Joao Ricardo N. Vissoci, Catherine A. Staton, Linda W. Xu, Michael Muhumuza, Hussein Ssenyonjo, John Mukasa, Joel Kiryabwire, Henry E. Rice, Gerald A. Grant, Michael M. Haglund

Abstract:

Background: While delays to care exist in resource rich settings, greater delays are seen along the care continuum in low- and middle-income countries (LMICs) largely due to limited healthcare capacity to address the disproportional rates of traumatic brain injury (TBI) in Sub Saharan Africa (SSA). While many LMICs have government subsidized systems to offset surgical costs, the burden of securing funds by the patients for medications, supplies, and CT diagnostics poses a significant challenge to timely surgical interventions. In Kampala Uganda, the challenge of obtaining timely CT scans is twofold. First, due to a lack of a functional CT scanner at the tertiary hospital, patients need to arrange their own transportation to the nearby private facility for CT scans. Second, self-financing for the private CT scans ranges from $80 - $130, which is near the average monthly income in Kampala. These bottlenecks contribute significantly to the care continuum delays and are associated with poor TBI outcomes. Objective: The objectives of this study are to 1) describe the temporal delays through a modified three delays model that fits the context of neurosurgical interventions for TBI patients in Kampala and 2) investigate the association between delays and mortality. Methods: Prospective data were collected for 563 TBI patients presenting to a tertiary hospital in Kampala from 1 June – 30 November 2016. Four time intervals were constructed along five time points: injury, hospital arrival, neurosurgical evaluation, CT results, and definitive surgery. Time interval differences among mild, moderate and severe TBI and their association with mortality were analyzed. Results: The mortality rate of all TBI patients presenting to MNRH was 9.6%, which ranged from 4.7% for mild and moderate TBI patients receiving surgery to 81.8% for severe TBI patients who failed to receive surgery. The duration from injury to surgery varied considerably across TBI severity with the largest gap seen between mild TBI (174 hours) and severe TBI (69 hours) patients. Further analysis revealed care continuum differences for interval 3 (neurosurgical evaluation to CT result) and 4 (CT result to surgery) between severe TBI patients (7 hours for interval 3 and 24 hours for interval 4) and mild TBI patients (19 hours for interval 3, and 96 hours for interval 4). These post-arrival delays were associated with mortality for mild (p=0.05) and moderate TBI (p=0.03) patients. Conclusions: To our knowledge, this is the first analysis using a modified ‘three delays’ framework to analyze the care continuum of TBI patients in Uganda from injury to surgery. We found significant associations between delays and mortality for mild and moderate TBI patients. As it currently stands, poorer outcomes were observed for these mild and moderate TBI patients who were managed non-operatively or failed to receive surgery while surgical services were shunted to more severely ill patients. While well intentioned, high mortality rates were still observed for the severe TBI patients managed surgically. These results suggest the need for future research to optimize triage practices, understand delay contributors, and improve pre-hospital logistical referral systems.

Keywords: care continuum, global neurosurgery, Kampala Uganda, LMIC, Mulago, prospective registry, traumatic brain injury

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22348 Status of the European Atlas of Natural Radiation

Authors: G. Cinelli, T. Tollefsen, P. Bossew, V. Gruber, R. Braga, M. A. Hernández-Ceballos, M. De Cort

Abstract:

In 2006, the Joint Research Centre (JRC) of the European Commission started the project of the 'European Atlas of Natural Radiation'. The Atlas aims at preparing a collection of maps of Europe displaying the levels of natural radioactivity caused by different sources (indoor and outdoor radon, cosmic radiation, terrestrial radionuclides, terrestrial gamma radiation, etc). The overall goal of the project is to estimate, in geographical resolution, the annual dose that the public may receive from natural radioactivity, combining all the information from the different radiation components. The first map which has been developed is the European map of indoor radon (Rn) since in most cases Rn is the most important contribution to exposure. New versions of the map are realised when new countries join the project or when already participating countries send new data. We show the latest status of this map which currently includes 25 European countries. Second, the JRC has undertaken to map a variable which measures 'what earth delivers' in terms of Rn. The corresponding quantity is called geogenic radon potential (RP). Due to the heterogeneity of data sources across the Europe there is need to develop a harmonized quantity which at the one hand adequately measures or classifies the RP, and on the other hand is suited to accommodate the variety of input data used to estimate this target quantity. Candidates for input quantities which may serve as predictors of the RP, and for which data are available across Europe, to different extent, are Uranium (U) concentration in rocks and soils, soil gas radon and soil permeability, terrestrial gamma dose rate, geological information and indoor data from ground floor. The European Geogenic Radon Map gives the possibility to characterize areas, on European geographical scale, for radon hazard where indoor radon measurements are not available. Parallel to ongoing work on the European Indoor Radon, Geogenic Radon and Cosmic Radiation Maps, we made progress in the development of maps of terrestrial gamma radiation and U, Th and K concentrations in soil and bedrock. We show the first, preliminary map of the terrestrial gamma dose rate, estimated using the data of ambient dose equivalent rate available from the EURDEP system (about 5000 fixed monitoring stations across Europe). Also, the first maps of U, Th, and K concentrations in soil and bedrock are shown in the present work.

Keywords: Europe, natural radiation, mapping, indoor radon

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22347 Jurisdiction of Military Court for Military Members Who Committed General Crimes in Indonesia's Military Justice System and Comparison with Another Countries

Authors: Dini Dewi Heniarti

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Military Court which is a judicial institution within the military institution has a heavy duty. Military court has to ensuring a fair legal process for military personnel (due process of law) and enforces military discipline. Military justice must also ensure protects the rights of military personnel. In Indonesia tren of military court changes in vision. The debate is happened on the jurisdiction of military court that allegedly has the potential existence of impunity. The Decree of People’s Consultative Assembly Number VII/MPR/2000 which states that the army general who committed the crime should not be tried in military court is one that underlies the proposed amendment limits the jurisdiction of military court. For the identify of the background in a specific format that is limited to juridical review. The goals this research is to gain knowledge, deep understanding and the concept of jurisdiction of military courts for military members who committed general crimes in adjudication procedure from the perspective of legal reform as alternative to establish independency of military judiciary. This research using Rule of Law as Grand Theory, Development Legal Theory as a Middle Theory and Criminal Justice System and concept of jurisdiction as supporting as Applied Theory. This study using a normative juridical approach, and equipped by primary data juridical approach of historical and comparative approach. The author uses descriptive analytical specifications. The main data used in this research is secondary data, which includes primary legal materials, secondary legal material and legal materials tertiary. Analysis primary data and qualitative data is done legally. Technique checking the validity of the data in this study used multiple methods with the research triangulation. This paper will demonstrate the problems concerning the jurisdiction of military courts for military personnel who committed general crimes in perspective of military justice reform Indonesia and adjudication procedures for military member who committed general crimes in the military justice system in Indonesia, as alternative to establish independency of judiciary in military justice in Indonesia. Comparative approached the military justice system from another countries is aimed to development military justice in Indonesia.

Keywords: jurisdiction, military courts, military justice, independency of judiciary

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22346 Impact of Hashtags in Tweets Regarding COVID-19 on the Psyche of Pakistanis: A Critical Discourse Analytical Study

Authors: Muhammad Hamza

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This study attempts to analyze the social media reports regarding Covid-19 that impacted the psyche of Pakistanis. This Study is delimited to hashtags from Tweets on a social media platform. During Covid-19, it has been observed that it affected the psychological conditions of Pakistanis. With the application of the three-dimensional model presented by Fairclough, together with a data analytic software “FireAnt” i.e., social media and data analysis toolkit, which is used to filter, identify, report and export data from social media accurately. A detailed and explicit exploration of the various hashtags by users from different fields was conducted. This study conducted a quantitative as well as qualitative methods of analysis. The study examined the perspectives of the Pakistanis behind the use of various hashtags with the lenses of Critical Discourse Analysis (CDA). While conducting this research, CDA was helpful to reveal the connection between the psyche of the people and the Covid-19 pandemic. It was found that how different Pakistanis used social media and how Covid-19 impacted their psyche. After collecting and analyzing the hashtags from twitter it was concluded that majority of people received negative impact from social media reports, while, some people used their hashtags positively and were found positive during Covid-19, and some people were found neutral.

Keywords: Covid, Covid-19, psyche, Covid Pakistan

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22345 Fair Federated Learning in Wireless Communications

Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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22344 Reflectance Imaging Spectroscopy Data (Hyperspectral) for Mineral Mapping in the Orientale Basin Region on the Moon Surface

Authors: V. Sivakumar, R. Neelakantan

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Mineral mapping on the Moon surface provides the clue to understand the origin, evolution, stratigraphy and geological history of the Moon. Recently, reflectance imaging spectroscopy plays a significant role in identifying minerals on the planetary surface in the Visible to NIR region of the electromagnetic spectrum. The Moon Mineralogy Mapper (M3) onboard Chandrayaan-1 provides unprecedented spectral data of lunar surface to study about the Moon surface. Here we used the M3 sensor data (hyperspectral imaging spectroscopy) for analysing mineralogy of Orientale basin region on the Moon surface. Reflectance spectrums were sampled from different locations of the basin and continuum was removed using ENvironment for Visualizing Images (ENVI) software. Reflectance spectra of unknown mineral composition were compared with known Reflectance Experiment Laboratory (RELAB) spectra for discriminating mineralogy. Minerals like olivine, Low-Ca Pyroxene (LCP), High-Ca Pyroxene (HCP) and plagioclase were identified. In addition to these minerals, an unusual type of spectral signature was identified, which indicates the probable Fe-Mg-spinel lithology in the basin region.

Keywords: chandryaan-1, moon mineralogy mapper, mineral, mare orientale, moon

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