Search results for: healthcare data security

Authors: Ali Rashash Alzahrani, Elizabeth Stojanovski

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Data on various aspects of education are collected at the institutional and government level regularly. In Australia, for example, students at various levels of schooling undertake examinations in numeracy and literacy as part of NAPLAN testing, enabling longitudinal assessment of such data as well as comparisons between schools and states within Australia. Another source of educational data collected internationally is via the PISA study which collects data from several countries when students are approximately 15 years of age and enables comparisons in the performance of science, mathematics and English between countries as well as ranking of countries based on performance in these standardised tests. As well as student and school outcomes based on the tests taken as part of the PISA study, there is a wealth of other data collected in the study including parental demographics data and data related to teaching strategies used by educators. Overall, an abundance of educational data is available which has the potential to be used to help improve educational attainment and teaching of content in order to improve learning outcomes. A multivariate assessment of such data enables multiple variables to be considered simultaneously and will be used in the present study to help develop profiles of students based on performance in mathematics using data obtained from the PISA study.

Keywords: cluster analysis, education, mathematics, profiles

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Authors: Sijuade A. A., Oguntoye J. P., Awodoye O. O., Adedapo O. A., Wahab W. B., Okediran O. O., Omidiora E. O., Olabiyisi S. O.

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Electronic voting systems have been introduced to improve the efficiency, accuracy, and transparency of the election process in many countries around the world, including Nigeria. However, concerns have been raised about the security and integrity of these systems. One way to address these concerns is through the implementation of electronic forensic election audit systems. This study aims to evaluate voters' intention to the adoption of electronic forensic election audit systems using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. In the study, the UTAUT model which is a widely used model in the field of information systems to explain the factors that influence individuals' intention to use a technology by integrating performance expectancy, effort expectancy, social influence, facilitating conditions, cost factor and privacy factor to voters’ behavioural intention was proposed. A total of 294 sample data were collected from a selected population of electorates who had at one time or the other participated in at least an electioneering process in Nigeria. The data was then analyzed statistically using Partial Least Square Structural Equation Modeling (PLS-SEM). The results obtained show that all variables have a significant effect on the electorates’ behavioral intention to adopt the development and implementation of an electronic forensic election audit system in Nigeria.

Keywords: election Audi, voters, UTAUT, performance expectancy, effort expectancy, social influence, facilitating condition social influence, facilitating conditions, cost factor, privacy factor, behavioural intention

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Authors: Sairoel Amertet, Girma Gebresenbet

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Smart mechatronics systems in agriculture can be traced back to the mid-1980s, when research into automated fruit harvesting systems began in Japan, Europe, and the United States. Since then, impressive advances have been made in smart mechatronics systems. Furthermore, smart mechatronics systems are promising areas, and as a result, we were intrigued to learn more about them. Consequently, the purpose of this study was to examine the smart mechatronic systems that have been applied to agricultural areas so far, with inspiration from the smart mechatronic system in other sectors. To get an overview of the current state of the art, benefits and drawbacks of smart mechatronics systems, various approaches were investigated. Moreover, smart mechatronic modules and various networks applied in agriculture processing were examined. Finally, we explored how the data retrieved using the one-way analysis of variance related to each other. The result showed that there were strongly related keywords for different journals. With the virtually limited use of sophisticated mechatronics in the agricultural industry and, at the same time, the low production rate, the demand for food security has fallen dramatically. Therefore, the application of smart mechatronics systems in agricultural sectors would be taken into consideration in order to overcome these issues.

Keywords: mechatronics, robotic, robotic system, automation, agriculture mechanism

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Authors: Frezer Okubay Weldegebriel

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The tourism sector in Ethiopia plays a significant role in the national economy. The government is granting its pledge and readiness to develop this sector through various initiatives since to eradicate poverty and encourage economic development of the country is one of the Millennium Development plans. The tourism sector has been identified as one of the priority economic sectors by many countries, and the Government of Ethiopia has planned to make Ethiopia among the top five African destinations by 2020. Nevertheless, the international tourism demand for Ethiopia currently lags behind other African countries such as South Africa, Egypt, Morocco, Tanzania, and Kenya. Meanwhile, the number of international tourists’ arrival in Ethiopia is recently increasing even if it cannot be competitive with other African countries. Therefore, to offer demand-driven tourism products, the Ethiopian government, Tourism planners, Tour & Travel operators need to understand the important factors, which affect international tourists’ decision to visit Ethiopian destinations. This study was intended to analyze Italian Tourists Demand towards Ethiopian destination. The researcher aimed to identify the demand for Italian tourists’ preference to Ethiopian destinations comparing to the top East African countries. This study uses both qualitative and quantitative research methodology, and the data is manipulating through primary data collection method using questionnaires, interviews, and secondary data by reviewing books, journals, magazines, past researches, and websites. An active and potential Italian tourist cohort, five well-functioning tour operators based in Ethiopia for Italian tourists and professionals from Ethiopian Ministry of Tourism and Culture participated. Based on the analysis of the data collected through the questionnaire, interviews, and reviews of different materials, the study disclosed that the majority of Italian tourists have a high demand on Ethiopian Tourist destination. Historical and cultural interest, safety and security, the hospitality of the people and affordable accommodation coast are the main reason for them. However, some Italian tourists prefer to visit Kenya, Tanzania, and Uganda due to the fact that they are fascinated by adventure, safari and beaches, while Ethiopia cannot provide these attractions. Most Italian tourists have little information and practical experiences on Ethiopian tourism possibilities via a tour and travel companies. Moreover, the insufficient marketing campaign and promotion by Ethiopian Government and Ministry of Tourism could also contribute to the failure of Ethiopian tourism.

Keywords: The demand of Italian tourists, Ethiopia economy, Ethiopia tourism destination, promoting Ethiopia tourism

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Authors: Truong H. Le, Ngoc M. To, Quang N. Tran, Luu T. Cao, Chi V. Le

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Introduction: In Vietnam, the current monitoring and treatment for ordinary diabetic patient mostly based on glucose monitoring with HbA1c test for every three months (recommended goal is HbA1c < 6.5%~7%). For diabetes in pregnant women or Gestational diabetes mellitus (GDM), glycemic control until the time of delivery is extremly important because it could reduce significantly medical implications for both the mother and the child. Besides, GDM requires continuos glucose monitoring at least every two weeks and therefore an alternative marker of glycemia for short-term control is considering a potential tool for the healthcare providers. There are published studies have indicated that the glycosylated serum protein is a better indicator than glycosylated hemoglobin in GDM monitoring. Based on the actual practice in Vietnam, this study was designed to evaluate the role of serum fructosamine as a monitoring tool in GDM treament and its correlations with fasting blood glucose (G0), 2-hour postprandial glucose (G2) and glycosylated hemoglobin (HbA1c). Methods: A cohort study on pregnant women diagnosed with GDM by the 75-gram oralglucose tolerance test was conducted at Endocrinology Department, Cho Ray hospital, Vietnam from June 2014 to March 2015. Cho Ray hospital is the final destination for GDM patient in the southern of Vietnam, the study population has many sources from other pronvinces and therefore researchers belive that this demographic characteristic can help to provide the study result as a reflection for the whole area. In this study, diabetic patients received a continuos glucose monitoring method which consists of bi-weekly on-site visit every 2 weeks with glycosylated serum protein test, fasting blood glucose test and 2-hour postprandial glucose test; HbA1c test for every 3 months; and nutritious consultance for daily diet program. The subjects still received routine treatment at the hospital, with tight follow-up from their healthcare providers. Researchers recorded bi-weekly health conditions, serum fructosamine level and delivery outcome from the pregnant women, using Stata 13 programme for the analysis. Results: A total of 500 pregnant women was enrolled and follow-up in this study. Serum fructosamine level was found to have a light correlation with G0 ( r=0.3458, p < 0.001) and HbA1c ( r=0.3544, p < 0.001), and moderately correlated with G2 ( r=0.4379, p < 0.001). During study timeline, the delivery outcome of 287 women were recorded with the average age of 38.5 ± 1.5 weeks, 9% of them have macrosomia, 2.8% have premature birth before week 35th and 9.8% have premature birth before week 37th; 64.8% of cesarean section and none of them have perinatal or neonatal mortality. The study provides a reference interval of serum fructosamine for GDM patient was 112.9 ± 20.7 μmol/dL. Conclusion: The present results suggests that serum fructosamine is as effective as HbA1c as a reflection of blood glucose control in GDM patient, with a positive result in delivery outcome (0% perinatal or neonatal mortality). The reference value of serum fructosamine measurement provided a potential monitoring utility in GDM treatment for hospitals in Vietnam. Healthcare providers in Cho Ray hospital is considering to conduct more studies to test this reference as a target value in their GDM treatment and monitoring.

Keywords: gestational diabetes mellitus, monitoring tool, serum fructosamine, Vietnam

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Authors: Malak M. Shatnawi

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Infrastructure is the fundamental facility that plays an important part in socio-economic development for modern societies, if such sector is well planned, managed by decision makers in a way that is compatible with the population growth, safety, and national security needs; it will enrich progress, prosperity, awareness, social and economic welfare for any country. Infrastructure is the most important aspect of life because it can provide materials, products, and services that will improve and facilitate living conditions and maintain sustainability at the same time, and in order to study critical infrastructure, in general, we must think sustainability. Otherwise there will be a significant gap. The planning processes for sustainability include urban infrastructure and public transportation are considered the most important sectors for economic development for both developed and developing countries as they are linked to the civilizational and urban development, meanwhile, choosing the appropriate transportation mode that will provide a good level of service, and increase the satisfaction of the potential users is a difficult task. This research paper tries to assess where is Jordan located vs. each transportation sustainability dimensions in aspects related to social, economic and environmental dimensions based on (Zietsman et al. 2006) adopted model for sustainability transportation infrastructure. Measures of performance indicators for each dimensional goal were traced and supported with needed data, figures and statistical findings. The study uses analytical, descriptive style and methodology based on different references and previous studies from secondary data sources to support the case. Recommendations for enhancing sustainability were concluded, and future reform directions were proposed which can be applied to Jordan and generalized for other developing countries with similar circumstances.

Keywords: infrastructure transportation sustainability, economic, social, environmental

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Authors: Sakda Loetpiparwanich, Preecha Vichitthamaros

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Nowadays, poor data quality is considered one of the majority costs for a data project. The data project with data quality awareness almost as much time to data quality processes while data project without data quality awareness negatively impacts financial resources, efficiency, productivity, and credibility. One of the processes that take a long time is defining the expectations and measurements of data quality because the expectation is different up to the purpose of each data project. Especially, big data project that maybe involves with many datasets and stakeholders, that take a long time to discuss and define quality expectations and measurements. Therefore, this study aimed at developing meaningful indicators to describe overall data quality for each dataset to quick comparison and priority. The objectives of this study were to: (1) Develop a practical data quality indicators and measurements, (2) Develop data quality dimensions based on statistical characteristics and (3) Develop Composite Indicator that can describe overall data quality for each dataset. The sample consisted of more than 500 datasets from public sources obtained by random sampling. After datasets were collected, there are five steps to develop the Dataset Quality Index (SDQI). First, we define standard data quality expectations. Second, we find any indicators that can measure directly to data within datasets. Thirdly, each indicator aggregates to dimension using factor analysis. Next, the indicators and dimensions were weighted by an effort for data preparing process and usability. Finally, the dimensions aggregate to Composite Indicator. The results of these analyses showed that: (1) The developed useful indicators and measurements contained ten indicators. (2) the developed data quality dimension based on statistical characteristics, we found that ten indicators can be reduced to 4 dimensions. (3) The developed Composite Indicator, we found that the SDQI can describe overall datasets quality of each dataset and can separate into 3 Level as Good Quality, Acceptable Quality, and Poor Quality. The conclusion, the SDQI provide an overall description of data quality within datasets and meaningful composition. We can use SQDI to assess for all data in the data project, effort estimation, and priority. The SDQI also work well with Agile Method by using SDQI to assessment in the first sprint. After passing the initial evaluation, we can add more specific data quality indicators into the next sprint.

Keywords: data quality, dataset quality, data quality management, composite indicator, factor analysis, principal component analysis

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Authors: Ameur Abdelkader, Abed Bouarfa Hafida

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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: predictive analysis, big data, predictive analysis algorithms, CART algorithm

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Authors: Agata Zakrzewska, Dominik Kopeć, Adrian Ochtyra

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The growing number of new cameras, sensors, and research methods allow for a broader application of thermal data in remote sensing vegetation studies. The aim of this research was to check whether it is possible to use thermal infrared data with a spectral range (3.6-4.9 μm) obtained during the day and the night to assess the health condition of selected species of deciduous trees in an urban environment. For this purpose, research was carried out in the city center of Warsaw (Poland) in 2020. During the airborne data acquisition, thermal data, laser scanning, and orthophoto map images were collected. Synchronously with airborne data, ground reference data were obtained for 617 studied species (Acer platanoides, Acer pseudoplatanus, Aesculus hippocastanum, Tilia cordata, and Tilia × euchlora) in different health condition states. The results were as follows: (i) healthy trees are cooler than trees in poor condition and dying both in the daytime and nighttime data; (ii) the difference in the canopy temperatures between healthy and dying trees was 1.06oC of mean value on the nighttime data and 3.28oC of mean value on the daytime data; (iii) condition classes significantly differentiate on both daytime and nighttime thermal data, but only on daytime data all condition classes differed statistically significantly from each other. In conclusion, the aerial thermal data can be considered as an alternative to hyperspectral data, a method of assessing the health condition of trees in an urban environment. Especially data obtained during the day, which can differentiate condition classes better than data obtained at night. The method based on thermal infrared and laser scanning data fusion could be a quick and efficient solution for identifying trees in poor health that should be visually checked in the field.

Keywords: middle wave infrared, thermal imagery, tree discoloration, urban trees

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Authors: Walid Abdallah, Noureddine Boudriga

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Wireless sensor networks have shown their effectiveness in the deployment of many critical applications especially in the military domain. Border surveillance is one of these applications where a set of wireless sensors are deployed along a country border line to detect illegal intrusion attempts to the national territory and report this to a control center to undergo the necessary measures. Regarding its nature, this wireless sensor network can be the target of many security attacks trying to compromise its normal operation. Particularly, in this application the deployment and location of sensor nodes are of great importance for detecting and tracking intruders. This paper proposes a location-based authentication and key distribution mechanism to secure wireless sensor networks intended for border surveillance where the key establishment is performed using elliptic curve cryptography and identity-based public key scheme. In this scheme, the public key of each sensor node will be authenticated by keys that depend on its position in the monitored area. Before establishing a pairwise key between two nodes, each one of them must verify the neighborhood location of the other node using a message authentication code (MAC) calculated on the corresponding public key and keys derived from encrypted beacon messages broadcast by anchor nodes. We show that our proposed public key authentication and key distribution scheme is more resilient to node capture and node replication attacks than currently available schemes. Also, the achievement of the key distribution between nodes in our scheme generates less communication overhead and hence increases network performances.

Keywords: wireless sensor networks, border surveillance, security, key distribution, location-based

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Authors: Hamid Yasinian

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Random epistemologies and hash tables have garnered minimal interest from both security experts and experts in the last several years. In fact, few information theorists would disagree with the evaluation of expert systems. In our research, we discover how flip-flop gates can be applied to the study of superpages. Though such a hypothesis at first glance seems perverse, it is derived from known results.

Keywords: synthesis, multi-processors, interactive model, moor’s law

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Authors: Annie Singh, Ishaan Singh

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Background: Transgenders are people who have a gender identity different from their sex assigned at birth. Their gender behaviour doesn’t match their body anatomy. The community faces discrimination due to their gender identity all across the world. The term transgender is an umbrella term for many people non-conformal to their biological identity; note that the term transgender is different from gender dysphoria, which is a DSM-5 disorder defined as problems faced by an individual due to their non-conforming gender identity. Transgender people have been a part of Indian culture for ages yet have continued to face exclusion and discrimination in society. This has led to the low socio-economic status of the community. Various studies done across the world have established the role of discrimination, harassment and exclusion in the development of psychological disorders. The study is aimed to assess the frequency of stress and anxiety in the transgender population and understand the various factors affecting the same. Methodology: A cross-sectional survey of self consenting transgender individuals above the age of 18 residing in Delhi was done to assess their socioeconomic status and experiential ecology. Recruitment of participants was done with the help of NGOs. The survey was constructed GAD-7 and PSS-10, two well-known scales were used to assess the stress and anxiety levels. Medians, means and ranges are used for reporting continuous data wherever required, while frequencies and percentages are used for categorical data. For associations and comparison between groups in categorical data, the Chi-square test was used, while the Kruskal-Wallis H test was employed for associations involving multiple ordinal groups. SPSS v28.0 was used to perform the statistical analysis for this study. Results: The survey showed that the frequency of stress and anxiety is high in the transgender population. A demographic survey indicates a low socio-economic background. 44% of participants reported facing discrimination on a daily basis; the frequency of discrimination is higher in transwomen than in transmen. Stress and anxiety levels are similar among both transmen and transwomen. Only 34.5% of participants said they had receptive family or friends. The majority of participants (72.7%) reported a positive or neutral experience with healthcare workers. The prevalence of discrimination is significantly lower in the higher educated groups. Analysis of data shows a positive impact of acceptance and reception on mental health, while discrimination is correlated with higher levels of stress and anxiety. Conclusion: The prevalence of widespread transphobia and discrimination faced by the transgender community has culminated in high levels of stress and anxiety in the transgender population and shows variance according to multiple socio-demographic factors. Educating people about the LGBT community formation of support groups, policies and laws are required to establish trust and promote integration.

Keywords: transgender, gender, stress, anxiety, mental health, discrimination, exclusion

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Authors: Anita Puspawati

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A failure in obtaining informed consent from patient occurs because there is not effective communication skill in doctors. Therefore, the language is very important in communication between doctor and patient. This study uses descriptive analysis method, that is a method used mainly in researching the status of a group of people, an object, a condition, a system of thought or a class of events in the present. The result of this study indicates that the communicative language between doctors and patients will increase the trust of patients to their doctors and accordingşy, patients will provide the informed consent voluntarily.

Keywords: communicative, language, doctor, patient

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Authors: Z. Abdullah, A. R. Hamdan

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Clustering is a process of grouping objects and data into groups of clusters to ensure that data objects from the same cluster are identical to each other. Clustering algorithms in one of the areas in data mining and it can be classified into partition, hierarchical, density based, and grid-based. Therefore, in this paper, we do a survey and review for four major hierarchical clustering algorithms called CURE, ROCK, CHAMELEON, and BIRCH. The obtained state of the art of these algorithms will help in eliminating the current problems, as well as deriving more robust and scalable algorithms for clustering.

Keywords: clustering, unsupervised learning, algorithms, hierarchical

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Authors: Alfiah Hasanah, Silvia Mendolia, Oleg Yerokhin

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This paper explores the impacts of adult child migration on the health of elderly parents left behind. The maternal and children health are a priority of health-related policy in most low and middle-income country, and so there is lack of evidence on the health of older population particularly in Indonesia. With increasing life expectancy and limited access to social security and social services for the elderly in this country, the consequences of increasing number of out-migration of adult children to parent health are important to investigate. This study use Indonesia Family Life Survey (IFLS), the only large-scale continuing longitudinal socioeconomic and health survey that based on a sample of households representing about 83 percent of the Indonesian population in its first wave. Using four waves of IFLS including the recent wave of 2014, several indicators of the self-rated health status, interviewer-rated health status and days of illness are used to estimate the impact of labour out-migration of adult children on parent health status. Incorporate both individual fixed effects to control for unobservable factors in migrant and non-migrant households and the ordered response of self-rated health, this study apply the ordered logit of “Blow-up and Cluster” (BUC ) estimator. The result shows that labour out-migration of adult children significantly improves the self-rated health status of the elderly parent left behind. Findings of this study are consistent with the view that migration increases family resources and contribute to better health care and nutrition of the family left behind.

Keywords: aging, migration, panel data, self-rated health

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Authors: K. Umbleja, M. Ichino

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Symbolic data mining has been developed to analyze data in very large datasets. It is also useful in cases when entry specific details should remain hidden. Symbolic data mining is quickly gaining popularity as datasets in need of analyzing are becoming ever larger. One type of such symbolic data is a histogram, which enables to save huge amounts of information into a single variable with high-level of granularity. Other types of symbolic data can also be described in histograms, therefore making histogram a very important and general symbolic data type - a method developed for histograms - can also be applied to other types of symbolic data. Due to its complex structure, analyzing histograms is complicated. This paper proposes a method, which allows to compare two histogram-valued variables and therefore find a dissimilarity between two histograms. Proposed method uses the Ichino-Yaguchi dissimilarity measure for mixed feature-type data analysis as a base and develops a dissimilarity measure specifically for histogram data, which allows to compare histograms with different number of bins and bin widths (so called general histogram). Proposed dissimilarity measure is then used as a measure for clustering. Furthermore, linkage method based on weighted averages is proposed with the concept of cluster compactness to measure the quality of clustering. The method is then validated with application on real datasets. As a result, the proposed dissimilarity measure is found producing adequate and comparable results with general histograms without the loss of detail or need to transform the data.

Keywords: dissimilarity measure, hierarchical clustering, histograms, symbolic data analysis

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Authors: Majid Mokhtarnia, Alireza Amini

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Mobile operators deal with increasing in the data traffic as a critical issue. As a result, a vital responsibility of the operators is to deal with such a trend in order to create added values. This paper addresses a bundling method in a Canvas business model in a WiFi Data Offloading (WDO) strategy by which some elements of the model may be affected. In the proposed method, it is supposed to sell a number of data packages for subscribers in which there are some packages with a free given volume of data-offloaded WiFi complimentary. The paper on hands analyses this method in the views of attractiveness and profitability. The results demonstrate that the quality of implementation of the WDO strongly affects the final result and helps the decision maker to make the best one.

Keywords: bundling, canvas business model, telecommunication, WiFi data offloading

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Authors: Memar Ayalew Demeke, Solomon Gebreyohans Gebru

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In Africa, Regional Economic Communities (RECs) were initially established to tackle the economic challenges of the continent. However, overtime, they expanded their mandate to deal with the security threats of the continent such as terrorism. In fact, the fight against terrorism has been internationalized following the September 9/11 terrorist attack in the U.S.A. Since then, RECs have been giving considerable attention to preventing and combating terrorism in their respective regions. Similarly, IGAD has been involved in preventing and combating terrorism. So far, however, little has been done with regard to what IGAD has performed in fighting terrorism. Therefore, this study was intended to describe and analyze the legal and practical activities carried out by IGAD in its fight against terrorism in the region general and in Somalia in particular. Both descriptive and analytical methods were employed and data were analyzed through qualitative approach. Finally, based on the findings, the study argues that, instead of over-reliance on hard power as a means of fighting terrorism, IGAD should invest more on the political and socio-economic problems of its member states so as to address the root causes.

Keywords: regional economic communities, IGAD, terrorism, treaties, conventions

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Authors: Li Jiuen Ong, Magdalin Cheong, Sri Rahayu, Lek Alexander, Pei Ting Tan

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Background: Previous programme evaluations from the diabetes training programme conducted in Changi General Hospital revealed that healthcare professionals (HCPs) are keen to receive advance diabetes training and education, specifically in medical, nutritional therapy. HCPs also expressed a preference for interactive activities over didactic teaching methods to enhance their learning. Since the War on Diabetes was initiated by MOH in 2016, HCPs are challenged to be actively involved in continuous education to be better equipped to reduce the growing burden of diabetes. Hence, streamlining training to incorporate an element of fun is of utmost importance. Aim: The nutrition programme incorporates game play using an interactive board game that aims to provide a more conducive and less stressful environment for learning. The board game could be adapted for training of community HCPs, health ambassadors or caregivers to cope with the increasing demand of diabetes care in the hospital and community setting. Methodology: Stages for game’s conception (Jaffe, 2001) were adopted in the development of the interactive board game ‘Sweet Score™ ’ Nutrition concepts and topics in diabetes self-management are embedded into the game elements of varying levels of difficulty (‘Easy,’ ‘Medium,’ ‘Hard’) including activities such as a) Drawing/ sculpting (Pictionary-like) b)Facts/ Knowledge (MCQs/ True or False) Word definition) c) Performing/ Charades To study the effects of game play on knowledge acquisition and perceived experiences, participants were randomised into two groups, i.e., lecture group (control) and game group (intervention), to test the difference. Results: Participants in both groups (control group, n= 14; intervention group, n= 13) attempted a pre and post workshop quiz to assess the effectiveness of knowledge acquisition. The scores were analysed using paired T-test. There was an improvement of quiz scores after attending the game play (mean difference: 4.3, SD: 2.0, P<0.001) and the lecture (mean difference: 3.4, SD: 2.1, P<0.001). However, there was no significance difference in the improvement of quiz scores between gameplay and lecture (mean difference: 0.9, 95%CI: -0.8 to 2.5, P=0.280). This suggests that gameplay may be as effective as a lecture in terms of knowledge transfer. All the13 HCPs who participated in the game rated 4 out of 5 on the likert scale for the favourable learning experience and relevance of learning to their job, whereas only 8 out of 14 HCPs in the lecture reported a high rating in both aspects. 16. Conclusion: There is no known board game currently designed for diabetes training for HCPs.Evaluative data from future training can provide insights and direction to improve the game format and cover other aspects of diabetes management such as self-care, exercise, medications and insulin management. Further testing of the board game to ensure learning objectives are met is important and can assist in the development of awell-designed digital game as an alternative training approach during the COVID-19 pandemic. Learning through gameplay increases opportunities for HCPs to bond, interact and learn through games in a relaxed social setting and potentially brings more joy to the workplace.

Keywords: active learning, game, diabetes, nutrition

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Authors: Madre Paarlber, Alwiena Blignaut

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Background: Medication administration errors remains a global patient safety problem targeted by the WHO (World Health Organization), yet research on this matter is sparce within the South African context. Objective: The aim was to explore and describe nurses’ (medication administrators) perceptions regarding medication administration safety-related culture, incidence, causes, and reporting in the Gauteng Province of South Africa, and to determine any relationships between perceived variables concerned with medication safety (safety culture, incidences, causes, reporting of incidences, and reasons for non-reporting). Method: A quantitative research design was used through which self-administered online surveys were sent to 768 nurses (medication administrators) (n=217). The response rate was 28.26%. The survey instrument was synthesised from the Agency of Healthcare Research and Quality (AHRQ) Hospital Survey on Patient Safety Culture, the Registered Nurse Forecasting (RN4CAST) survey, a survey list prepared from a systematic review aimed at generating a comprehensive list of medication administration error causes and the Medication Administration Error Reporting Survey from Wakefield. Exploratory and confirmatory factor analyses were used to determine the validity and reliability of the survey. Descriptive and inferential statistical data analysis were used to analyse quantitative data. Relationships and correlations were identified between items, subscales and biographic data by using Spearmans’ Rank correlations, T-Tests and ANOVAs (Analysis of Variance). Nurses reported on their perceptions of medication administration safety-related culture, incidence, causes, and reporting in the Gauteng Province. Results: Units’ teamwork deemed satisfactory, punitive responses to errors accentuated. “Crisis mode” working, concerns regarding mistake recording and long working hours disclosed as impacting patient safety. Overall medication safety graded mostly positively. Work overload, high patient-nurse ratios, and inadequate staffing implicated as error-inducing. Medication administration errors were reported regularly. Fear and administrative response to errors effected non-report. Non-report of errors’ reasons was affected by non-punitive safety culture. Conclusions: Medication administration safety improvement is contingent on fostering a non-punitive safety culture within units. Anonymous medication error reporting systems and auditing nurses’ workload are recommended in the quest of improved medication safety within Gauteng Province private hospitals.

Keywords: incidence, medication administration errors, medication safety, reporting, safety culture

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Authors: Fehmeen Anwar, Ujala Liaqat

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For over half a century, U.S. and the Soviet Union have been at daggers drawn with each other. Both leading powers of the world have been struggling hard to surpass each other in military and other technological fields. This neck-to-neck competition turned in favour of U.S. in the early 1990s when USSR had to face economic stagnation and later dismemberment of several of its states. The predominance of U.S. is still evident to date, rather it continues to grow. With this proposed defence program i.e. Anti-Ballistic Missile System, the U.S. will have a considerable chance of intercepting any nuclear strike by Russia, which re-asserts U.S. dominance in the region and creating a security dilemma for Russia and other states. The question is whether America’s recent nuclear deterrence project is merely to counter nuclear threats from Iran and North Korea or is it purely directed towards Russia, thus ensuring complete military supremacy in the world. Although U.S professes to direct its Anti-Ballistic Missile System (ABMS) against the axis of evil (Iran and North Korea), yet the deployment of this system in the East European territory undermines the Russian nuclear strategic capability, as this enables U.S. to initiate an attack and guard itself from retaliatory strike, thus disturbing the security equilibrium in Europe. The implications of this program can lead to power imbalance which can lead to the emergence of fundamentally different paradigm of international politics.

Keywords: Anti-Ballistic Missile System (ABMS), cold-war, axis of evil, power dynamics

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Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung

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In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.

Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining

Procedia PDF Downloads 438

Authors: Kashyap L. Mokariya, Varsha A. Shah, Makarand M. Lokhande

Abstract:

As the current status and growth of Indian automobile industry is remarkable, transportation sectors are the main concern in terms of Energy security and climate change. Rising demand of fuel and its dependency on other countries affects the GDP of nation. So in this context if the 10 percent of vehicle got operated in Electrical mode how much saving in terms of Rs and in terms of liters is achieved has been analyzed which is also a part of Nations Electric mobility mission plan. Analysis is also done for converting unit consumption of Electricity of Electric vehicle into equivalent fuel consumption in liters which shows that at present tariff rate Electrical operated vehicles are far more beneficial. It also gives benchmark to the authorities to set the tariff rate for Electrical vehicles. Current situation of Indian grid is shown and how the Gap between Generation and Demand can be reduced is analyzed in terms of increasing generation capacity and Energy Conservation measures. As the certain regions of country is facing serious deficit than how to take energy conservation measures in Industry and especially in rural areas where generally Energy Auditing is not carried out that is analyzed in context of Electric vehicle penetration in near future. Author was a part of Vishvakarma yojna where in 255 villages of Gujarat Energy losses were measured and solutions were given to mitigate them and corresponding report to the authorities of villages was delivered.

Keywords: vehiclepenetration, feasibility, Energyconservation, future grid, Energy security, pf controller

Procedia PDF Downloads 363

Authors: Philipp Ruf, Massiwa Chabbi, Christoph Reich, Djaffar Ould-Abdeslam

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In recent years, convolutional neural networks (CNN) have demonstrated high performance in image analysis, but oftentimes, there is only structured data available regarding a specific problem. By interpreting structured data as images, CNNs can effectively learn and extract valuable insights from tabular data, leading to improved predictive accuracy and uncovering hidden patterns that may not be apparent in traditional structured data analysis. In applying a single neural network for analyzing multimodal data, e.g., both structured and unstructured information, significant advantages in terms of time complexity and energy efficiency can be achieved. Converting structured data into images and merging them with existing visual material offers a promising solution for applying CNN in multimodal datasets, as they often occur in a medical context. By employing suitable preprocessing techniques, structured data is transformed into image representations, where the respective features are expressed as different formations of colors and shapes. In an additional step, these representations are fused with existing images to incorporate both types of information. This final image is finally analyzed using a CNN.

Keywords: CNN, image processing, tabular data, mixed dataset, data transformation, multimodal fusion

Procedia PDF Downloads 125

Authors: Botshelo Rachel Sebola

Abstract:

Unintended pregnancy often results in pregnancy termination. Most countries have legalised the termination of a pregnancy and pregnant adolescents can visit designated clinics without their parents’ consent. In most African and Asian countries, certain cultural practices are performed following any form of childbirth, including abortion, and such practices are ingrained in societies. The aim of this paper was to understand how women who terminated a pregnancy during adolescence coped by embracing cultural practices. A descriptive multiple case study design was adopted for the study. In-depth, semi-structured interviews and reflective diaries were used for data collection. Thirteen women aged 25 to 35 who had terminated a pregnancy in adolescence participated in the study. Three women kept their soiled sanitary pads, burned them to ash and waited for the rainy season to scatter the ash in a flowing stream. This ritual was performed to appease the ancestors, ask them for forgiveness and as a send-off for the aborted foetus. Five women secretly consulted Sangoma (traditional healers) to perform certain rituals. Three women isolated themselves to perform herbal cleansings, and the last two chose not to engage in any sexual activity for one year, which led to the loss of their partners. This study offers a unique contribution to understanding the solitary journey of women who terminated a pregnancy. The study challenges healthcare professionals who work in clinics that offer pregnancy termination services to look beyond releasing the foetus to advocating and providing women with the necessary care and support in performing cultural practices.

Keywords: adolescence, cultural practices, case study, pregnancy

Procedia PDF Downloads 134

Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

Abstract:

This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: data mining, textile production, decision trees, classification

Procedia PDF Downloads 356

Authors: Juhan Kim, Jinsoo Kim

Abstract:

South Korea cannot import natural gas in any form other than LNG because of the division of South and North Korea. Further, the high proportion of natural gas in the national energy mix makes this resource crucial for energy security in Korea. Expansion of Panama Canal will allow for reducing the cost of shipping between the Far East and U.S East. Panama Canal expansion can have significant impacts on South Korea. Due to this situation, we review the natural gas optimal portfolio by considering the uniqueness of the Korean Natural gas market and expansion of Panama Canal. In order to assess Korea’s natural gas optimal portfolio, we developed natural gas portfolio model. The model comprises two steps. First, to obtain the optimal long-term spot contract ratio, the study examines the price level and the correlation between spot and long-term contracts by using the Markowitz, portfolio model. The optimal long-term spot contract ratio follows the efficient frontier of the cost/risk level related to this price level and degree of correlation. Second, by applying the obtained long-term contract purchase ratio as the constraint in the linear programming portfolio model, we determined the natural gas optimal import portfolio that minimizes total intangible and tangible costs. Using this model, we derived the optimal natural gas portfolio considering the expansion of Panama Canal. Based on these results, we assess the portfolio for natural gas import to Korea from the perspective of energy security and present some relevant policy proposals.

Keywords: natural gas, Panama Canal, portfolio analysis, South Korea

Procedia PDF Downloads 294

Authors: Jaweriya Aftab, Madho Mal, Hamida Memon

Abstract:

The first case of coronavirus disease 2019 (COVID-19) in Pakistan was recorded on February 26th, 2020. While the country went through various phases of lockdowns, the importance of proper sensitization campaigns was highlighted by healthcare workers to combat misinformation. Past studies via Google trends analysis have shown a rise in public interest in multiple COVID-19-related symptoms as well as cardiovascular symptoms. As there is a paucity of data related to the trends in Pakistan, we conducted a retrospective analysis to bridge further information. Methods: As per the recommendations from past studies, a Google trend analysis was conducted for various symptoms, including ‘Fever’, ‘Chest Pain’, ‘Shortness of Breath’, and ‘Cough’ between 1st January 2019 to 31st December 2021. The trends in various search results were analyzed and modeled. Results: Our analysis found various rises in public interest in the various symptoms (fever, chest pain, shortness of breath, and cough) that correspond closely to the wave of the virus's spread in the country. Conclusion: Our study confirms similar trends in Pakistan as previously reported in studies from India, USA, and UK, whereby the public interest in various COVID-19 symptoms rose with the number of cases. This further highlights the need for a strong approach to combat misinformation during such a critical period.

Keywords: covid, trend, Pakistan, public

Procedia PDF Downloads 43

Authors: Raymond Xu, Cindy Jingru Wang

Abstract:

Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

Procedia PDF Downloads 265

Authors: Ashima Anurag Sharma

Abstract:

Optical fiber based networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This research paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparison between various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

Procedia PDF Downloads 530