Search results for: internet data science

Authors: Orhun Vural, Oguz Bayat, Rustu Akay, Osman N. Ucan

Abstract:

This study presents a new parallel approach clustering of GPS data. Evaluation has been made by comparing execution time of various clustering algorithms on GPS data. This paper aims to propose a parallel based on neighborhood K-means algorithm to make it faster. The proposed parallelization approach assumes that each GPS data represents a vehicle and to communicate between vehicles close to each other after vehicles are clustered. This parallelization approach has been examined on different sized continuously changing GPS data and compared with serial K-means algorithm and other serial clustering algorithms. The results demonstrated that proposed parallel K-means algorithm has been shown to work much faster than other clustering algorithms.

Keywords: parallel k-means algorithm, parallel clustering, clustering algorithms, clustering on flowing data

Procedia PDF Downloads 222

Authors: Mukhtarkhanova Ainagul Madievna, Imanbek Karakoz

Abstract:

The development and implementation of active forms and methods of extracurricular work in biology are carried out, assistance to people in determining sustainable interests in a particular field of science, expanding pupil's knowledge and horizons during in–depth study of program issues that go beyond the curriculum where considered, but accessible to the understanding of people; the development of interest in the subject, independence, creative activity. The purpose of this study is to open interest through extracurricular activities for teaching biology. The purpose of the presented work is to arouse people's interest in biology lessons in the modern world through extracurricular activities. First, the level of people was determined in the traditional style of teaching lessons, for which special tests and evaluation criteria were compiled. The level of pupils' knowledge of biology was determined by a questionnaire. Samples of extracurricular work were presented, and practices were conducted in the educational process. At the next stage, the level of pupils after the experiment was compared. The results of the work were discussed, and recommendations were developed.

Keywords: extracurricular activities, modern world, teaching, method, excursions, laboratory experiments, science fairs

Procedia PDF Downloads 104

Authors: Stefan Werrlich, Phuc-Anh Nguyen, Kai Nitsche, Gunther Notni

Abstract:

Augmented Reality (AR) is a strong growing research topic. This innovative technology is interesting for several training domains like education, medicine, military, sports and industrial use cases like assembly and maintenance tasks. AR can help to improve the efficiency, quality and transfer of training tasks. Due to these reasons, AR becomes more interesting for big companies and researchers because the industrial domain is still an unexplored field. This paper presents the research proposal of a PhD thesis which is done in cooperation with the BMW Group, aiming to explore head-mounted display (HMD) based training in industrial environments. We give a short introduction, describing the motivation, the underlying problems as well as the five formulated research questions we want to clarify along this thesis. We give a brief overview of the current assembly training in industrial environments and present some AR-based training approaches, including their research deficits. We use the Design Science Research (DSR) framework for this thesis and describe how we want to realize the seven guidelines, mandatory from the DSR. Furthermore, we describe each methodology which we use within that framework and present our approach in a comprehensive figure, representing the entire thesis.

Keywords: assembly, augmented reality, research proposal, training

Procedia PDF Downloads 246

Authors: R. Abdulrahman, A. Eardley, A. Soliman

Abstract:

The proliferation in the development of mobile learning (m-learning) has played a vital role in the rapidly growing electronic learning market. This relatively new technology can help to encourage the development of in learning and to aid knowledge transfer a number of areas, by familiarizing students with innovative information and communications technologies (ICT). M-learning plays a substantial role in the deployment of learning methods for nursing students by using the Internet and portable devices to access learning resources ‘anytime and anywhere’. However, acceptance of m-learning by students is critical to the successful use of m-learning systems. Thus, there is a need to study the factors that influence student’s intention to use m-learning. This paper addresses this issue. It outlines the outcomes of a study that evaluates the unified theory of acceptance and use of technology (UTAUT) model as applied to the subject of user acceptance in relation to m-learning activity in nurse education. The model integrates the significant components across eight prominent user acceptance models. Therefore, a standard measure is introduced with core determinants of user behavioural intention. The research model extends the UTAUT in the context of m-learning acceptance by modifying and adding individual innovativeness (II) and quality of service (QoS) to the original structure of UTAUT. The paper goes on to add the factors of previous experience (of using mobile devices in similar applications) and the nursing students’ readiness (to use the technology) to influence their behavioural intentions to use m-learning. This study uses a technique called ‘convenience sampling’ which involves student volunteers as participants in order to collect numerical data. A quantitative method of data collection was selected and involves an online survey using a questionnaire form. This form contains 33 questions to measure the six constructs, using a 5-point Likert scale. A total of 42 respondents participated, all from the Nursing Institute at the Armed Forces Hospital in Saudi Arabia. The gathered data were then tested using a research model that employs the structural equation modelling (SEM), including confirmatory factor analysis (CFA). The results of the CFA show that the UTAUT model has the ability to predict student behavioural intention and to adapt m-learning activity to the specific learning activities. It also demonstrates satisfactory, dependable and valid scales of the model constructs. This suggests further analysis to confirm the model as a valuable instrument in order to evaluate the user acceptance of m-learning activity.

Keywords: mobile learning, nursing institute students’ acceptance of m-learning activity in Saudi Arabia, unified theory of acceptance and use of technology model (UTAUT), structural equation modelling (SEM)

Procedia PDF Downloads 188

Authors: Ryan A. Black, Stacey A. McCaffrey

Abstract:

Over the past few decades, great strides have been made towards improving the science in the measurement of psychological constructs. Item Response Theory (IRT) has been the foundation upon which statistical models have been derived to increase both precision and accuracy in psychological measurement. These models are now being used widely to develop and refine tests intended to measure an individual's level of academic achievement, aptitude, and intelligence. Recently, the field of clinical psychology has adopted IRT models to measure psychopathological phenomena such as depression, anxiety, and addiction. Because advances in IRT measurement models are being made so rapidly across various fields, it has become quite challenging for psychologists and other behavioral scientists to keep abreast of the most recent developments, much less learn how to employ and decide which models are the most appropriate to use in their line of work. In the same vein, IRT measurement models vary greatly in complexity in several interrelated ways including but not limited to the number of item-specific parameters estimated in a given model, the function which links the expected response and the predictor, response option formats, as well as dimensionality. As a result, inferior methods (a.k.a. Classical Test Theory methods) continue to be employed in efforts to measure psychological constructs, despite evidence showing that IRT methods yield more precise and accurate measurement. To increase the use of IRT methods, this study endeavors to provide a comprehensive overview of binary IRT models; that is, measurement models employed on test data consisting of binary response options (e.g., correct/incorrect, true/false, agree/disagree). Specifically, this study will cover the most basic binary IRT model, known as the 1-parameter logistic (1-PL) model dating back to over 50 years ago, up until the most recent complex, 4-parameter logistic (4-PL) model. Binary IRT models will be defined mathematically and the interpretation of each parameter will be provided. Next, all four binary IRT models will be employed on two sets of data: 1. Simulated data of N=500,000 subjects who responded to four dichotomous items and 2. A pilot analysis of real-world data collected from a sample of approximately 770 subjects who responded to four self-report dichotomous items pertaining to emotional consequences to alcohol use. Real-world data were based on responses collected on items administered to subjects as part of a scale-development study (NIDA Grant No. R44 DA023322). IRT analyses conducted on both the simulated data and analyses of real-world pilot will provide a clear demonstration of how to construct, evaluate, and compare binary IRT measurement models. All analyses will be performed using the new IRT procedure in SAS 9.4. SAS code to generate simulated data and analyses will be available upon request to allow for replication of results.

Keywords: instrument development, item response theory, latent trait theory, psychometrics

Procedia PDF Downloads 357

Authors: Iván García-Magariño, Javier Bravo-Agapito, Marta López-Fernández

Abstract:

Online judges have proven their utility in partial auto-evaluation of programming short exercises in the last decades. UnitJudge online judge has the advantage of facilitating the evaluation of separate units to provide more segregate and meaningful feedback to students in complex exercises and practices. This paper discusses the use of UnitUdge in advanced Java object-oriented programming exercises and web development practices. This later usage has been proposed by means of the Selenium Java library and classes to provide the web address. Consequently, UnitJudge is an online judge system that can be applied in several subjects, and therefore, many other students would take advantage of self-testing their exercises. This paper presents the experiments with a Java programming exercise for learning Java object-oriented classes with a generic type. Considering 10 students who voluntarily used UnitJudge, 80% successfully learned this concept, passing the judge exercise with correct results.

Keywords: online judges, programming skills, computer science education, auto-evaluation

Procedia PDF Downloads 101

Authors: Umar Sheikh Tahir

Abstract:

Before al-Ghazālī, Islamic scholars perceived logic as an intrusive knowledge. The knowledge therefore, did not receive ample attention among scholars on how it should be adapted into Islamic sciences. General scholarship in that period rejects logic as an instrumental knowledge. This attitude became unquestionable to the scholars from different perspectives with diversification of suggestions in the pre-al-Ghazālī’s period. However, al-Ghazālī proclaimed with new perspective that transform Logic from ‘intrusive knowledge’ to a useful tool for Islamic sciences. This study explores the contributions of al-Ghazālī to epistemology regarding the use and the relevance of Logic. The study applies qualitative research methodology dealing strictly with secondary data from medieval age and contemporary sources. The study concludes that al-Ghazālī’s contributions which supported the transformation of Logic to useful tool in the Muslim world were drawn from his experience within Islamic tradition. He succeeded in reconciling Islamic tradition with the wisdom of Greek sciences.

Keywords: Al-Ghazālī, classical logic, epistemology, Islamdom and Islamic sciences

Procedia PDF Downloads 250

Authors: Darusalam, Jorish Hulstijn, Marijn Janssen

Abstract:

Media has revealed a variety of corruption cases in the regional and local governments all over the world. Many governments pursued many anti-corruption reforms and have created a system of checks and balances. Three types of corruption are faced by citizens; administrative corruption, collusion and extortion. Accountability is one of the benchmarks for building transparent government. The public sector is required to report the results of the programs that have been implemented so that the citizen can judge whether the institution has been working such as economical, efficient and effective. Open Data is offering solutions for the implementation of good governance in organizations who want to be more transparent. In addition, Open Data can create transparency and accountability to the community. The objective of this paper is to build a framework of open data for accountability to combating corruption. This paper will investigate the relationship between open data, and accountability as part of anti-corruption initiatives. This research will investigate the impact of open data implementation on public organization.

Keywords: open data, accountability, anti-corruption, framework

Procedia PDF Downloads 337

Authors: Rubai M. Ochieng

Abstract:

Cancer, which accounts for 7 percent of deaths per year in Kenya, is the third highest cause of death after infectious and cardiovascular diseases. Awareness Campaigns have tended to focus on leading cancers including breast and cervical for women as well as prostrate and Esophageal for men. Consequently, less common cancers such as Acute Myeloid Leukemia (AML) are rarely properly understood by the general population and a section of the medical fraternity. Diagnoses of AML in patients who may not have heard about it sometimes results in shock, denial and confusion not just to the diagnosed, but also to their family and friends. The diagnosed and caregivers are bound to receive a lot of contradicting information about prognosis, care and treatment of AML. This information, which often comes from diverse sources including doctors, friends, internet and social media platforms, causes further confusion and panic. The situation is handled differently by different people. Religious people sometimes resort to prayer. This paper, written from the perspective of a care giver, is based on data collected from a case of Acute Myeloid Leukemia diagnosed in a 32 year old male who lost his life within six weeks of diagnosis. The sample constitutes of 16 people who participated in prayers. Out of this total, 5 were males including the diagnosed and 11 were females. All the 16 were Christians of protestant orientation including Anglicans, Quakers and Church of God members. Data was collected by the researcher herself through participant of observation. Findings discuss how the 16 participants prayed individually at different times, together in an overnight prayer meeting and every morning through a group social media platform. They shared songs and words of encouragement from the bible. The group prayed for healing, peace and strength to the diagnosed and family, financial breakthrough and doctors’ work and decisions, among other challenges that came with the situation. The paper reveals the immense benefits of prayer to the diagnosed and his close relatives and friends. They include acceptance of the condition and a positive attitude in handling the challenges that arose from the disease and treatment processes. The challenges arising from the prayer approach of handling the situation are also discussed. The paper concludes that prayer as therapy goes a long way in cancer management.

Keywords: acute myeloid leukemia, Kenya, participant observation, prayer

Procedia PDF Downloads 162

Authors: Stephen V. Crowder, Jonathan W. Lane

Abstract:

With short production development times, there is an increased need to demonstrate product reliability relatively quickly with minimal testing. In such cases there may be few if any observed failures. Thus it may be difficult to assess reliability using the traditional reliability test plans that measure only time (or cycles) to failure. For many components, degradation measures will contain important information about performance and reliability. These measures can be used to design a minimal test plan, in terms of number of units placed on test and duration of the test, necessary to demonstrate a reliability goal. In this work we present a case study involving an electronic component subject to degradation. The data, consisting of 42 degradation paths of cycles to failure, are first used to estimate a reliability function. Bootstrapping techniques are then used to perform power studies and develop a minimal reliability test plan for future production of this component.

Keywords: degradation measure, time to failure distribution, bootstrap, computational science

Procedia PDF Downloads 532

Authors: Goran Begović

Abstract:

In recent years, many researchers are focusing on non-intrusive measuring methods when it comes to human biosignals. These methods provide solutions for everyday use, whether it’s health monitoring or finessing the workout routine. One of the biggest issues with these solutions is that the sensors’ accuracy is highly variable due to many factors, such as ambiental light, skin color diversity, etc. That is why we wanted to explore different outcomes under those kinds of circumstances in order to find the most optimal algorithm(s) for extracting heart rate (HR) information. The optimization of such algorithms can benefit the wider, cheaper, and safer application of home health monitoring, without having to visit medical professionals as often when it comes to observing heart irregularities. In this study, we explored the accuracy of infrared (IR), red, and green LED sensorics in a controlled environment and compared the results with a medically accurate ECG monitoring device.

Keywords: data science, ECG, heart rate, holter monitor, LED sensors

Procedia PDF Downloads 127

Authors: Michael Nthabiseng Moeti, Makhulu Relebogile Langa, Joey Jansen van Vuuren

Abstract:

This paper examines the utilization of personal electronic devices like laptops, tablets, and smartphones for professional duties within a financial organization. This phenomenon is known as bring your own device (BYOD). BYOD accords employees the freedom to use their personal devices to access corporate resources from anywhere in the world with Internet access. BYOD arrangements introduce significant security risks for both organizations and users. These setups change the threat landscape for enterprises and demand unique security strategies, as conventional tools tailored for safeguarding managed devices fall short in adequately protecting enterprise assets without active user cooperation. This paper applies protection motivation theory (PMT) to highlight behavioral risks from BYOD users that may impact the security of financial institutions. Thematic analysis was applied to gain a comprehensive understanding of how users perceive this phenomenon. These findings demonstrates that the existence of a security policy does not ensure that all employees will take measures to protect their personal devices. Active promotion of BYOD security policies is crucial for financial institution employees and management. This paper developed a BYOD security model which is useful for understanding compliant behaviors. Given that BYOD security is becoming a major concern across financial sector, it is important. The paper recommends that future research could expand the number of universities from which data is collected.

Keywords: BYOD, information security, protection motivation theory, security risks, thematic analysis

Procedia PDF Downloads 31

Authors: Samah Senbel

Abstract:

Database Design is a fundamental part of the Computer Science and Information technology curricula in any school, as well as in the study of management, business administration, and data analytics. In this study, we compare the performance of two groups of students studying the same database design and implementation course at Sacred Heart University in the fall of 2018. Both courses used the same textbook and were taught by the same professor, one for seven graduate students and one for 26 undergraduate students (juniors). The undergraduate students were aged around 20 years old with little work experience, while the graduate students averaged 35 years old and all were employed in computer-related or management-related jobs. The textbook used was 'Database Systems, Design, Implementation, and Management' by Coronel and Morris, and the course was designed to follow the textbook roughly a chapter per week. The first 6 weeks covered the design aspect of a database, followed by a paper exam. The next 6 weeks covered the implementation aspect of the database using SQL followed by a lab exam. Since the undergraduate students are on a 16 week semester, we spend the last three weeks of the course covering NoSQL. This part of the course was not included in this study. After the course was over, we analyze the results of the two groups of students. An interesting discrepancy was observed: In the database design part of the course, the average grade of the graduate students was 92%, while that of the undergraduate students was 77% for the same exam. In the implementation part of the course, we observe the opposite: the average grade of the graduate students was 65% while that of the undergraduate students was 73%. The overall grades were quite similar: the graduate average was 78% and that of the undergraduates was 75%. Based on these results, we concluded that having both classes follow the same time schedule was not beneficial, and an adjustment is needed. The graduates could spend less time on design and the undergraduates would benefit from more design time. In the fall of 2019, 30 students registered for the undergraduate course and 15 students registered for the graduate course. To test our conclusion, the undergraduates spend about 67% of time (eight classes) on the design part of the course and 33% (four classes) on the implementation part, using the exact exams as the previous year. This resulted in an improvement in their average grades on the design part from 77% to 83% and also their implementation average grade from 73% to 79%. In conclusion, we recommend using two separate schedules for teaching the database design course. For undergraduate students, it is important to spend more time on the design part rather than the implementation part of the course. While for the older graduate students, we recommend spending more time on the implementation part, as it seems that is the part they struggle with, even though they have a higher understanding of the design component of databases.

Keywords: computer science education, database design, graduate and undergraduate students, pedagogy

Procedia PDF Downloads 121

Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

Abstract:

Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

Procedia PDF Downloads 116

Authors: Malika Turganova, Aigul Abduldayeva

Abstract:

Modern conditions require nursing innovations at the primary ambulatory stage in the health system of Kazakhstan. There is a growing need for nurses involved in before-doctor attendance for preventive interview with a female population about reproductive health. We conducted questionnaire survey of the population of Astana in 2015. Questionnaires were drawn up according to the criteria of sexual health of World Health Organization. 3593 respondents out of 8000 questionnaires agreed to answer the questions anonymously, mM=±2,1. The average age of women comprised 37,4±11,2, Ме=31,7 years of age. Analysis of awareness about marriage hygiene revealed that 72,7% of respondents did not receive information about marriage hygiene and 89,1% respondents consider it more advisable before marriage. 45,9% of respondents specified the internet as a source of information on marriage hygiene issues, 24,5% of respondents pointed out friends, and 21,5% specified doctor. Comparing female age groups under and after 40 years old we see that proportion of cases when parents provide information about marriage hygiene issues comprises 4.3% (χ2 =9.8, p<0.05). The most important factor of preservation of women reproductive health is handling a problem of unwanted pregnancy. The responsibility lies equally in men and women. Data analysis of contraceptive methods by ranking showed three most frequently used methods: contraception sheath – 29.3%, then coitus interruptus – 18.7% and hormonal preparations – 16.9%. The most important factor of women's reproductive health preservation is a solving of the problem of unwanted pregnancy, and in this respect, the responsibility lies equally in men and women. Analyzing obtained data on contraceptive methods by ranking three of the most frequently used methods are condoms – 29,3%, then coitus interruptus – 18,7% and hormonal preparations – 16,9%. Additional oral survey of the population showed a low level of informational support of female population by family physicians, health care professionals of educational organizations (schools, universities, and colleges) about hormonal contraceptive. Females of both age groups used to think that hormonal contraceptives cause collateral damage such as blastoma, cancer, increased body weight, varix dilatation of lower limbs. Satisfaction with the frequency of sexual relations of the respondents comprised 57,6%. At that, women under 40 years of age are the most satisfied women among age groups (χ2 =5,8, p<0,05).

Keywords: nurse, public health service of Kazakhstan, reproductive and sexual health, trust of population

Procedia PDF Downloads 273

Authors: Yuyun Wabula, B. J. Dewancker

Abstract:

In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.

Keywords: geolocation, Twitter, distribution analysis, human mobility

Procedia PDF Downloads 314

Authors: Rezaei Hachesu Peyman, Oliyaee Azadeh, Salahzadeh Zahra, Alizadeh Somayyeh, Safaei Naser

Abstract:

Coronary Artery Disease (CAD) is one major cause of disability in adults and one main cause of death in developed. In this study, data mining techniques including Decision Trees, Artificial neural networks (ANNs), and Support Vector Machine (SVM) analyze CAD data. Data of 4948 patients who had suffered from heart diseases were included in the analysis. CAD is the target variable, and 24 inputs or predictor variables are used for the classification. The performance of these techniques is compared in terms of sensitivity, specificity, and accuracy. The most significant factor influencing CAD is chest pain. Elderly males (age > 53) have a high probability to be diagnosed with CAD. SVM algorithm is the most useful way for evaluation and prediction of CAD patients as compared to non-CAD ones. Application of data mining techniques in analyzing coronary artery diseases is a good method for investigating the existing relationships between variables.

Keywords: classification, coronary artery disease, data-mining, knowledge discovery, extract

Procedia PDF Downloads 657

Authors: Abha Cherkani Hassani, Imane Ghanname, Nezha Mouane

Abstract:

Background: This is the first systematic review summarizing 43 years of research from 36 countries in the assessment of cadmium in breast milk; a suitable matrix in human biomonitoring. Objectives: To report from the published literature the levels of cadmium in breast milk and the affecting factors causing the increase of cadmium concentrations; also to gather several quantitative data which might be useful to evaluate the international degrees of maternal and infant exposure. Methods: We reviewed the literature for studies reporting quantitative data about cadmium levels in human breast milk in the world that have been published between 1971 and 2014 and that are available on Pubmed, Science direct and Google scholar. The aim of the study, country, period of samples collection, size of samples, sampling method, time of lactation, mother’s age, area of residence, cadmium concentration and other information were extracted. Results: 67 studies were selected and included in this systematic review. Some concentrations greatly exceed the limit of the WHO, However about 50% of the studies had less than 1 µg/l cadmium concentration (the recommendation of the WHO); as well many factors have shown their implication in breast milk contamination by Cadmium as lactation stage, smoking, diet, supplement intake, interaction with other mineral elements, age of mothers, parity and other parameters. Conclusion: Breast milk is a pathway of maternal excretion of cadmium. It is also a biological indicator of the degree of environmental pollution and cadmium exposure of the lactating women and the nourished infant. Therefore preventive measures and continuous monitoring are necessary.

Keywords: breast milk, cadmium level, factors, systematic review

Procedia PDF Downloads 524

Authors: Chimmoe Fomo Michelle Larissa

Abstract:

The challenges of cybersecurity in Africa are increasingly significant as the continent undergoes rapid digital transformation. With the rise of internet connectivity, mobile phone usage, and digital financial services, Africa faces unique cybersecurity threats. The significance of this study lies in understanding these threats and the multifaceted challenges that hinder effective cybersecurity measures across the continent. The methodologies employed in this study include a comprehensive analysis of existing cybersecurity frameworks in various African countries, surveys of key stakeholders in the digital ecosystem, and case studies of cybersecurity incidents. These methodologies aim to provide a detailed understanding of the current cybersecurity landscape, identify gaps in existing policies, and evaluate the effectiveness of implemented security measures. Major findings of the study indicate that Africa faces numerous cybersecurity challenges, including inadequate regulatory frameworks, insufficient cybersecurity awareness, and a shortage of skilled professionals. Additionally, the prevalence of cybercrime, such as financial fraud, data breaches, and ransomware attacks, exacerbates the situation. The study also highlights the role of international cooperation and regional collaboration in addressing these challenges and improving overall cybersecurity resilience. In conclusion, addressing cybersecurity challenges in Africa requires a multifaceted approach that involves strengthening regulatory frameworks, enhancing public awareness, and investing in cybersecurity education and training. The study underscores the importance of regional and international collaboration in building a robust cybersecurity infrastructure capable of mitigating the risks associated with the continent's digital growth.

Keywords: Africa, cybersecurity, challenges, digital infrastructure, cybercrime

Procedia PDF Downloads 41

Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

Abstract:

Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

Procedia PDF Downloads 83

Authors: Hung-Jen Lin, Chien-Hao Wang, Chien-Peng Huang, Yu-Sheng Tseng, En-Cheng Yang, Joe-Air Jiang

Abstract:

Bees’ incoming and outgoing behavior is a decisive index which can indicate the health condition of a colony. Traditional methods for monitoring the behavior of honey bees (Apis mellifera) take too much time and are highly labor-intensive, and the lack of automation and synchronization disables researchers and beekeepers from obtaining real-time information of beehives. To solve these problems, this study proposes to use an Internet of Things (IoT)-based system for counting honey bees’ incoming and outgoing activities using an infrared interruption technique, while environmental factors are recorded simultaneously. The accuracy of the established system is verified by comparing the counting results with the outcomes of manual counting. Moreover, this highly -accurate device is appropriate for providing quantitative information regarding honey bees’ incoming and outgoing behavior. Different statistical analysis methods, including one-way ANOVA and two-way ANOVA, are used to investigate the influence of environmental factors, such as temperature, humidity, illumination and ambient pressure, on bees’ incoming and outgoing behavior. With the real-time data, a standard model is established using the outcomes from analyzing the relationship between environmental factors and bees’ incoming and outgoing behavior. In the future, smart control systems, such as a temperature control system, can also be combined with the proposed system to create an appropriate colony environment. It is expected that the proposed system will make a considerable contribution to the apiculture and researchers.

Keywords: ANOVA, environmental factors, honey bee, incoming and outgoing behavior

Procedia PDF Downloads 368

Authors: Paulo Roberto Vasconcellos-Silva

Abstract:

The "Janeiro Roxo" (Purple January) campaign in Brazil aims to promote awareness of leprosy and its early symptoms. The COVID-19 pandemic has adversely affected institutional campaigns, mostly considering leprosy a neglected disease by the media. Google Trends (GT) is a tool that tracks user searches on Google, providing insights into the popularity of specific search terms. Our prior research has categorized online searches into two types: "Reactive searches," driven by transient campaign-related stimuli, and "Proactive searches," driven by personal interest in early symptoms and self-diagnosis. Using GT we studied: (i) the impact of "Janeiro Roxo" on public interest in leprosy (assessed through reactive searches) and its early symptoms (evaluated through proactive searches) over the past five years; (ii) changes in public interest during and after the COVID-19 pandemic; (iii) patterns in the dynamics of reactive and proactive searches Methods: We used GT's "Relative Search Volume" (RSV) to gauge public interest on a scale from 0 to 100. "HANSENÍASE" (HAN) was a proxy for reactive searches, and "HANSENÍASE SINTOMAS" (leprosy symptoms) (H.SIN) for proactive searches (interest in leprosy or in self-diagnosis). We analyzed 261 weeks of data from 2018 to 2023, using polynomial trend lines to model trends over this period. Analysis of Variance (ANOVA) was used to compare weekly RSV, monthly (MM) and annual means (AM). Results: Over a span of 261 weeks, there was consistently higher Relative Search Volume (RSV) for HAN compared to H.SIN. Both search terms exhibited their highest (MM) in January months during all periods. COVID-19 pandemic: a decline was observed during the pandemic years (2020-2021). There was a 24% decrease in RSV for HAN and a 32.5% decrease for H.SIN. Both HAN and H.SIN regained their pre-pandemic search levels in January 2022-2023. Breakpoints indicated abrupt changes - in the 26th week (February 2019), 55th and 213th weeks (September 2019 and 2022) related to September regional campaigns (interrupted in 2020-2021). Trend lines for HAN exhibited an upward curve between 33rd-45th week (April to June 2019), a pandemic-related downward trend between 120th-136th week (December 2020 to March 2021), and an upward trend between 220th-240th week (November 2022 to March 2023). Conclusion: The "Janeiro Roxo" campaign, along with other media-driven activities, exerts a notable influence on both reactive and proactive searches related to leprosy topics. Reactive searches, driven by campaign stimuli, significantly outnumber proactive searches. Despite the interruption of the campaign due to the pandemic, there was a subsequent resurgence in both types of searches. The recovery observed in reactive and proactive searches post-campaign interruption underscores the effectiveness of such initiatives, particularly at the national level. This suggests that regional campaigns aimed at leprosy awareness can be considered highly successful in stimulating proactive public engagement. The evaluation of internet-based campaign programs proves valuable not only for assessing their impact but also for identifying the needs of vulnerable regions. These programs can play a crucial role in integrating regions and highlighting their needs for assistance services in the context of leprosy awareness.

Keywords: health communication, leprosy, health campaigns, information seeking behavior, Google Trends, reactive searches, proactive searches, leprosy early identification

Procedia PDF Downloads 61

Authors: Meng-Fei Cheng, Wei Fneg

Abstract:

New Taiwan high school standards emphasize employing scientific models and modeling practices in physics learning. However, to our knowledge. Few studies address how scientific models and modeling are approached in current science teaching, and they do not examine the views of scientific models portrayed in the textbooks. To explore the views of scientific models and modeling in textbooks, this study investigated the atomic unit in different textbook versions as an example and provided suggestions for modeling curriculum. This study adopted a quantitative analysis of qualitative data in the atomic units of four mainstream version of Taiwan high school physics textbooks. The models were further analyzed using five dimensions of the views of scientific models (nature of models, multiple models, purpose of the models, testing models, and changing models); each dimension had three levels (low, medium, high). Descriptive statistics were employed to compare the frequency of describing the five dimensions of the views of scientific models in the atomic unit to understand the emphasis of the views and to compare the frequency of the eight scientific models’ use to investigate the atomic model that was used most often in the textbooks. Descriptive statistics were further utilized to investigate the average levels of the five dimensions of the views of scientific models to examine whether the textbooks views were close to the scientific view. The average level of the five dimensions of the eight atomic models were also compared to examine whether the views of the eight atomic models were close to the scientific views. The results revealed the following three major findings from the atomic unit. (1) Among the five dimensions of the views of scientific models, the most portrayed dimension was the 'purpose of models,' and the least portrayed dimension was 'multiple models.' The most diverse view was the 'purpose of models,' and the most sophisticated scientific view was the 'nature of models.' The least sophisticated scientific view was 'multiple models.' (2) Among the eight atomic models, the most mentioned model was the atomic nucleus model, and the least mentioned model was the three states of matter. (3) Among the correlations between the five dimensions, the dimension of 'testing models' was highly related to the dimension of 'changing models.' In short, this study examined the views of scientific models based on the atomic units of physics textbooks to identify the emphasized and disregarded views in the textbooks. The findings suggest how future textbooks and curriculum can provide a thorough view of scientific models to enhance students' model-based learning.

Keywords: atomic models, textbooks, science education, scientific model

Procedia PDF Downloads 158

Authors: Shreyansh Adesara, Sneha Pandiya

Abstract:

The mobile ad-hoc network (MANET) is an important and open area research for the examination and determination of the performance evolution. Temporary ordered routing algorithm (TORA) is adaptable and distributed MANET routing algorithm which is totally dependent on internet MANET Encapsulation protocol (IMEP) for the detection of the link and sensing of the link. If IMEP detect the wrong link failure then the network suffer from congestion and unnecessary route maintenance. Thus, the improvement in link detection method of TORA is introduced by various methods on IMEP by different perspective from different person. There are also different reactive routing protocols like AODV, TORA and DSR has been compared for the knowledge of the routing scenario for different parameter and using different model.

Keywords: IMEP, mobile ad-hoc network, protocol, TORA

Procedia PDF Downloads 442

Authors: Abbas Sheikhtaheri, Nasim Hashemi

Abstract:

Health information systems have great benefits for clinical and managerial processes of health care organizations. However, identifying and removing constraints and barriers of implementing and using health information systems before any implementation is essential. Physicians are one of the main users of health information systems, therefore, identifying the causes of their resistance and concerns about the barriers of the implementation of these systems is very important. So the purpose of this study was to determine the barriers of the development and implementation of health information systems in terms of the Iranian physicians’ perspectives. In this study conducted in 8 selected hospitals affiliated to Tehran and Iran Universities of Medical Sciences, Tehran, Iran in 2014, physicians (GPs, residents, interns, specialists) in these hospitals were surveyed. In order to collect data, a research made questionnaire was used (Cronbach’s α = 0.95). The instrument included 25 about organizational (9), personal (4), moral and legal (3) and technical barriers (9). Participants were asked to answer the questions using 5 point scale Likert (completely disagree=1 to completely agree=5). By using a simple random sampling method, 200 physicians (from 600) were invited to study that eventually 163 questionnaires were returned. We used mean score and t-test and ANOVA to analyze the data using SPSS software version 17. 52.1% of respondents were female. The mean age was 30.18 ± 7.29. The work experience years for most of them were between 1 to 5 years (80.4 percent). The most important barriers were organizational ones (3.4 ± 0.89), followed by ethical (3.18 ± 0.98), technical (3.06 ± 0.8) and personal (3.04 ± 1.2). Lack of easy access to a fast Internet (3.67±1.91) and the lack of exchanging information (3.61±1.2) were the most important technical barriers. Among organizational barriers, the lack of efficient planning for the development and implementation systems (3.56±1.32) and was the most important ones. Lack of awareness and knowledge of health care providers about the health information systems features (3.33±1.28) and the lack of physician participation in planning phase (3.27±1.2) as well as concerns regarding the security and confidentiality of health information (3.15 ± 1.31) were the most important personal and ethical barriers, respectively. Women (P = 0.02) and those with less experience (P = 0.002) were more concerned about personal barriers. GPs also were more concerned about technical barriers (P = 0.02). According to the study, technical and ethics barriers were considered as the most important barriers however, lack of awareness in target population is also considered as one of the main barriers. Ignoring issues such as personal and ethical barriers, even if the necessary infrastructure and technical requirements were provided, may result in failure. Therefore, along with the creating infrastructure and resolving organizational barriers, special attention to education and awareness of physicians and providing solution for ethics concerns are necessary.

Keywords: barriers, development health information systems, implementation, physicians

Procedia PDF Downloads 345

Authors: Elizabeta Krstić Vukelja

Abstract:

Digitization of personal data is a consequence of the development of information and communication technologies that create a new work environment with many advantages and challenges, but also potential threats to privacy and personal data protection. Regulation (EU) 2016/679 of the European Parliament and of the Council is becoming a law and obligation that should address the issues of personal data protection and information security. The existence of the Regulation leads to the conclusion that national legislation in the field of virtual environment, protection of the rights of EU citizens and processing of their personal data is insufficiently effective. In the health system, special emphasis is placed on the processing of special categories of personal data, such as health data. The healthcare industry is recognized as a particularly sensitive area in which a large amount of medical data is processed, the digitization of which enables quick access and quick identification of the health insured. The protection of the individual requires quality IT solutions that guarantee the technical protection of personal categories. However, the real problems are the technical and human nature and the spatial limitations of the application of the Regulation. Some conclusions will be drawn by analyzing the implementation of the basic principles of the Regulation on the example of the Croatian health care system and comparing it with similar activities in other EU member states.

Keywords: regulation, healthcare system, personal dana protection, quality data assurance

Procedia PDF Downloads 39

Authors: Nagi Mekhiel

Abstract:

Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory Organization, Parallel Processors, Serial Code, Vector Processing

Procedia PDF Downloads 270

Authors: Li Chun Zhao, Zhi Chao Hu, Xi Qiang Liu, Man Lai Lee, Chak Shing Yeung, Man Fei Xu, Yuen Yee Kwan, Alan H. M. Ho, Nickie W. K. Chan, Bin Deng, Zhong Zhen Zhao, Min Xu

Abstract:

Background: Chuangxiong Rhizoma (Chuangxion, CX) is one of the most frequently used herbs in Chinese medicine because of its wide therapeutic effects such as vasorelaxation and anti-inflammation. Aim: The purposes of this study are (1) to perform non-targeted / targeted analyses of CX methanol extract and water extract, and compare the present data with previously LC-MS or GC-MS fingerprints; (2) to examine the difference between CX methanol extract and water extract for preliminarily evaluating whether current compound markers of methanol extract from crude CX materials could be suitable for quality control of CX water extract. Method: CX methanol extract was prepared according to the Hong Kong Chinese Materia Medica Standards. DG water extract was prepared by boiling with pure water for three times (one hour each). UHPLC-Q-TOF-MS/MS fingerprint analysis was performed by C18 column (1.7 µm, 2.1 × 100 mm) with Agilent 1290 Infinity system. Experimental data were analyzed by Agilent MassHunter Software. A database was established based on 13 published LC-MS and GC-MS CX fingerprint analyses. Total 18 targeted compounds in database were selected as markers to compare present data with previous data, and these markers also used to compare CX methanol extract and water extract. Result: (1) Non-targeted analysis indicated that there were 133 compounds identified in CX methanol extract, while 325 compounds in CX water extract that was more than double of CX methanol extract. (2) Targeted analysis further indicated that 9 in 18 targeted compounds were identified in CX methanol extract, while 12 in 18 targeted compounds in CX water extract that showed a lower lose-rate of water extract when compared with methanol extract. (3) By comparing CX methanol extract and water extract, Senkyunolide A (+1578%), Ferulic acid (+529%) and Senkyunolide H (+169%) were significantly higher in water extract when compared with methanol extract. (4) Other bioactive compounds such as Tetramethylpyrazine were only found in CX water extract. Conclusion: Many new compounds in both CX methanol and water extracts were found by using UHPLC Q-TOF MS/MS analysis when compared with previous published reports. A new standard reference including non-targeted compound profiling and targeted markers functioned especially for quality control of CX water extract (herbal decoction) should be established in future. (This project was supported by Hong Kong Baptist University (FRG2/14-15/109) & Natural Science Foundation of Guangdong Province (2014A030313414)).

Keywords: Chuanxiong rhizoma, fingerprint analysis, targeted analysis, quality control

Procedia PDF Downloads 496

Authors: Tammy Wee, Detlev Remy, Arif Perdana

Abstract:

In the recent years, data analytics has become the buzzword in the hospitality industry. The hospitality industry is another example of a data-rich industry that has yet fully benefited from the insights of data analytics. Effective use of data analytics can change how hotels operate, market and position themselves competitively in the hospitality industry. However, at the moment, the data obtained by individual hotels remain under-utilized. This research is a preliminary research on data analytics in the hospitality industry, using an in-depth face-to-face interview on one hotel as a start to a multi-level research. The main case study of this research, hotel A, is a chain brand of international hotel that has been systematically gathering and collecting data on its own customer for the past five years. The data collection points begin from the moment a guest book a room until the guest leave the hotel premises, which includes room reservation, spa booking, and catering. Although hotel A has been gathering data intelligence on its customer for some time, they have yet utilized the data to its fullest potential, and they are aware of their limitation as well as the potential of data analytics. Currently, the utilization of data analytics in hotel A is limited in the area of customer service improvement, namely to enhance the personalization of service for each individual customer. Hotel A is able to utilize the data to improve and enhance their service which in turn, encourage repeated customers. According to hotel A, 50% of their guests returned to their hotel, and 70% extended nights because of the personalized service. Apart from using the data analytics for enhancing customer service, hotel A also uses the data in marketing. Hotel A uses the data analytics to predict or forecast the change in consumer behavior and demand, by tracking their guest’s booking preference, payment preference and demand shift between properties. However, hotel A admitted that the data they have been collecting was not fully utilized due to two challenges. The first challenge of using data analytics in hotel A is the data is not clean. At the moment, the data collection of one guest profile is meaningful only for one department in the hotel but meaningless for another department. Cleaning up the data and getting standards correctly for usage by different departments are some of the main concerns of hotel A. The second challenge of using data analytics in hotel A is the non-integral internal system. At the moment, the internal system used by hotel A do not integrate with each other well, limiting the ability to collect data systematically. Hotel A is considering another system to replace the current one for more comprehensive data collection. Hotel proprietors recognized the potential of data analytics as reported in this research, however, the current challenges of implementing a system to collect data come with a cost. This research has identified the current utilization of data analytics and the challenges faced when it comes to implementing data analytics.

Keywords: data analytics, hospitality industry, customer relationship management, hotel marketing

Procedia PDF Downloads 180

Authors: Enido Fabiano de Ramos, Ieda Kanashiro Makiya, Francisco I. Giocondo Cesar

Abstract:

This study presents an analysis of the Digital Twin concept applied to the academic environment, focusing on the development of a Digital Twin Smart Campus Framework. Using bibliometric analysis methodologies and literature review, the research investigates the evolution and applications of the Digital Twin in educational contexts, comparing these findings with the advances of Industry 4.0. It was identified gaps in the existing literature and highlighted the need to adapt Digital Twin principles to meet the specific demands of a smart campus. By integrating Industry 4.0 concepts such as automation, Internet of Things, and real-time data analytics, we propose an innovative framework for the successful implementation of the Digital Twin in academic settings. The results of this study provide valuable insights for university campus managers, allowing for a better understanding of the potential applications of the Digital Twin for operations, security, and user experience optimization. In addition, our framework offers practical guidance for transitioning from a digital campus to a digital twin smart campus, promoting innovation and efficiency in the educational environment. This work contributes to the growing literature on Digital Twins and Industry 4.0, while offering a specific and tailored approach to transforming university campuses into smart and connected spaces, high demanded by Society 5.0 trends. It is hoped that this framework will serve as a basis for future research and practical implementations in the field of higher education and educational technology.

Keywords: smart campus, digital twin, industry 4.0, education trends, society 5.0

Procedia PDF Downloads 59