Search results for: health data

Authors: E. Happ, A. Albert Tóth

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The aim of the research is to investigate the forms of the demands of leisure tourism in a West-Hungarian industrial city, Győr. Today, Győr is still a traditional industrial city, its industry is mainly based on vehicle industry, but the role of tourism is increasing in the life of the city as well. Because of the industrial nature and the strong economy of the city, the ratio of business tourists is high. It can be stated that MICE tourism is dominating in Győr. Developments of the last decade can help the city with new tourism products to increase the leisure tourism. The new types of tourism – besides business tourism – can help the providers to increase the occupancy rates and the demand at the weekends. The research demonstrates the theoretical background of the topic, and it shows the present situation of the tourism in Győr with secondary data. The secondary research contains statistical data from the Hungarian Statistical Office and the city council, and it is based on the providers’ data. The next part of the paper shows the potential types of leisure tourism with the help of primary research. The primary research contains the results of an online questionnaire with a sample of 1000 potential customers. It is completed with 10 in-depth interviews with tourism experts, who explained their opinions about the opportunities of leisure tourism in Győr from the providers’ side. The online questionnaire was filled out in spring 2017 by customers, who have already stayed in Győr or plan to visit the city. At the same time in-depth interviews were made with hotel managers, head of touristic institutions and employees at the council. Based on the research it can be stated that the touristic supply of Győr allows the increase of the leisure tourism ratio in the city. Primarily, the cultural and health tourism show potential development, but the supply side of touristic services can be developed in order to increase the number of guest nights. The tourism marketing needs to be strengthened in the city, and a distinctive marketing activity - from other cities - is needed as well. To conclude, although Győr is an industrial city, it has a transforming industrial part, and tourism is also strongly present in its economy. Besides the leading role of business tourism, different types of leisure tourism have the opportunity to take place in the city.

Keywords: business tourism, Győr, industrial city, leisure tourism, touristic demand

Procedia PDF Downloads 281

Authors: Bharat P. Modi, Jayesh M. Patel

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Mobile Internet is acting as a major source of data. As the number of web pages continues to grow the Mobile web provides the data miners with just the right ingredients for extracting information. In order to cater to this growing need, a special term called Mobile Web mining was coined. Mobile Web mining makes use of data mining techniques and deciphers potentially useful information from web data. Web Usage mining deals with understanding the behavior of users by making use of Mobile Web Access Logs that are generated on the server while the user is accessing the website. A Web access log comprises of various entries like the name of the user, his IP address, a number of bytes transferred time-stamp etc. A variety of Log Analyzer tools exists which help in analyzing various things like users navigational pattern, the part of the website the users are mostly interested in etc. The present paper makes use of such log analyzer tool called Mobile Web Log Expert for ascertaining the behavior of users who access an astrology website. It also provides a comparative study between a few log analyzer tools available.

Keywords: mobile web access logs, web usage mining, web server, log analyzer

Procedia PDF Downloads 366

Authors: Natnicha Wareesamarn, Waruntorn Jongrungrotsakul, Anon Wisutthananon

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Occupational illnesses and injuries are the partial results of unsafe work behaviors. Safety training, an occupational health and safety standard, could either reduce or prevent such illnesses and injuries. This quasi-experimental research aimed to examine the effect of integrated safety training on safety work behaviors among 54 waste collectors working in the Su-ngai Kolok and Muang districts in Narathiwat Province. The workers were equally divided into an experimental or a control group (27 in each). The study was implemented from September to November 2021. The research instruments consisted of 1) an integrated safety promotion program on safety work behaviors which was developed based on the literature review, and 2) a questionnaire on safe working behaviors among waste collectors modified from a safety work behaviors questionnaire by Sitthichai Jaikhan et al. (2019). The content validity of the questionnaire was confirmed by experts with a content validity index of 0.97, while reliability was at an acceptable level (0.86 - 0.90). Data were analyzed using descriptive statistics and a t-test. The findings showed that after receiving the integrated safety promotion program on safety work behaviors, the mean scores for safety work behaviors among the experimental group (x ̅ = 73.89, S.D.=1.12) were significantly higher than those of the control group (x ̅ = 47.93, S.D.= 2.45) (p<.001). Furthermore, it was found that the mean score for safety work behaviors among the experimental group after receiving the integrated safety promotion program (x ̅=73.89, S.D.= 2.45) was significantly higher than that before receiving the program (x ̅=47.85, S.D.= 2.16) (p<.001). These findings indicate that occupational health nurses and related staff should place great concern on the application of integrated safety promotion programs into their own work. This is anticipated to enhance safe work behaviors, thereby reducing occupational illnesses and injuries, as well as enhancing the quality of working life among waste collectors.

Keywords: integrated safety promotion program, safety work behaviors, waste collectors, safety training

Procedia PDF Downloads 121

Authors: Sumattana Glangkarn, Vorapoj Promasatayaprot

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Background: Proportion of population ageing in Thailand has been increased rapidly in the past decades according to living longer and the fertility rates have decreased. The most important challenge related to this situation is to consider how to improve quality and years of healthy of life. This study aimed to implement the older persons’ long term care (LTC) system for elderly care by family and community. Method: The Consolidated Framework for Implementation Research (CFIR) was employed for guiding and evaluating an implementation process in ageing care. The CFIR composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Results: most elderly participants were couples, educating primary school and living with children and grandchildren. More than half of them had chronic diseases such as diabetes mellitus and hypertension. Factor analysis revealed factors related to health care of older participants which consisted of exercise, diet, accidental prevention, relaxation, self-care capacity, joyfulness, family relationship, and personal hygiene. A pre-implementation phase showed intervention characteristics included facilities and services of the LTC policy from the Ministry of Public Health. The complexities of the LTC and relative advantages were explained. Community leaders, public health volunteers, care givers and health professionals had participated in the LTC activities. Outer and inner settings consisted of context of community, culture, and readiness. Characteristics of the individuals related to knowledge, self-efficacy, perceptions, and believes. The process consisted of planning, acting, observing, and reflecting. The implementation outcomes and service outcomes had been evaluated during-implementation phase. Conclusion: the participation of caregivers, community leaders, public health volunteers, and health professionals had supported the LTC services. Thus, family and community care could improve quality of life of the ageing.

Keywords: ageing, CFIR, long term care, implementation

Procedia PDF Downloads 180

Authors: Patricia Calvo, Francisco M. Sánchez, María J. Rodríguez

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Nowadays, food intake is becoming more irregular due to changes in family organization and lifestyle. Snacking is part of the day-to-day lives of people, however, most of the snacks have a high saturated fat, salt and refined sugar content; these dietary factors are believed to have negative health consequences. For this reason, there has been an increase in consumer demand for healthy, natural and convenient foods, so the development of a significant portion of new products focuses on improving the nutritional value of food snacks through modification its nutritional composition. In this paper, a new product made from vegetables has been designed. This new product would be an ideal food format to include ingredients with positive health benefits.

Keywords: healthy, pepper, dried, carotenes, polyphenols

Procedia PDF Downloads 382

Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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Authors: K. A. Gladkova, N. P. Babushkina, E. Y. Bragina

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Purpose: Tuberculosis (TB), caused by Mycobacterium tuberculosis, is one of the major public health problems worldwide. It is clear that the immune response to M. tuberculosis infection is a relationship between inflammatory and anti-inflammatory responses in which Tumour Necrosis Factor-α (TNF-α) plays key roles as a pro-inflammatory cytokine. TNF-α involved in various cell immune responses via binding to its two types of membrane-bound receptors, TNFRSF1A and TNFRSF1B. Importantly, some variants of the TNFRSF1B gene have been considered as possible markers of host susceptibility to TB. However, the possible impact of such TNF-α and its receptor genes polymorphism on TB cases in Tomsk is missing. Thus, the purpose of our study was to investigate polymorphism of TNF-α (rs1800629) and its receptor TNFRSF1B (rs652625 and rs525891) genes in population of Tomsk and to evaluate their possible association with the development of pulmonary TB. Materials and Methods: The population distribution features of genes polymorphisms were investigated and made case-control study based on group of people from Tomsk. Human blood was collected during routine patients examination at Tomsk Regional TB Dispensary. Altogether, 234 TB-positive patients (80 women, 154 men, average age is 28 years old) and 205 health-controls (153 women, 52 men, average age is 47 years old) were investigated. DNA was extracted from blood plasma by phenol-chloroform method. Genotyping was carried out by a single-nucleotide-specific real-time PCR assay. Results: First, interpopulational comparison was carried out between healthy individuals from Tomsk and available data from the 1000 Genomes project. It was found that polymorphism rs1800629 region demonstrated that Tomsk population was significantly different from Japanese (P = 0.0007), but it was similar with the following Europeans subpopulations: Italians (P = 0.052), Finns (P = 0.124) and British (P = 0.910). Polymorphism rs525891 clear demonstrated that group from Tomsk was significantly different from population of South Africa (P = 0.019). However, rs652625 demonstrated significant differences from Asian population: Chinese (P = 0.03) and Japanese (P = 0.004). Next, we have compared healthy individuals versus patients with TB. It was detected that no association between rs1800629, rs652625 polymorphisms, and positive TB cases. Importantly, AT genotype of polymorphism rs525891 was significantly associated with resistance to TB (odds ratio (OR) = 0.61; 95% confidence interval (CI): 0.41-0.9; P < 0.05). Conclusion: To the best of our knowledge, the polymorphism of TNFRSF1B (rs525891) was associated with TB, while genotype AT is protective [OR = 0.61] in Tomsk population. In contrast, no significant correlation was detected between polymorphism TNF-α (rs1800629) and TNFRSF1B (rs652625) genes and alveolar TB cases among population of Tomsk. In conclusion, our data expands the molecular particularities associated with TB. The study was supported by the grant of the Russia for Basic Research #15-04-05852.

Keywords: polymorphism, tuberculosis, TNF-α, TNFRSF1B gene

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Authors: Zyra Cheska Hidalgo, Joehiza Mae Renon, Kzarina Buen, Girlie Mitrado

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ABSTRACT: The global coronavirus disease (COVID-19) has dramatically impacted the lives of many, including education and our economy. Thus, it presents a massive challenge for medical education as instructors are mandated to deliver their lectures virtually to ensure the continuity of the medical education process and ensure students' safety. The purpose of this research paper is to determine the lived experiences of paramedical students who are engaged in virtual hands-on learning and to determine the different coping strategies they used to deal with virtual hands-on learning. The researchers used the survey method of descriptive research design to determine the lived experiences and coping strategies of twenty (20) paramedical students from Lorma Colleges (particularly the College of Medicine Department). The data were collected through online questionnaires, particularly with the use of google forms. This study shows technical issues, difficulty in adapting styles, distractions and time management issues, mental and physical health issues, and lack of interest and motivation are the most common problems and challenges experienced by paramedical students. On the other hand, the coping strategies used by paramedical students to deal with those challenges include time management, engagement in leisure activities, acceptance of responsibilities, studying, and adapting. With the data gathered, the researchers concluded that virtual hands-on learning effectively increases the knowledge of paramedical students. However, teaching and learning barriers must have to be considered to implement virtual hands-on learning successfully.

Keywords: virtual hands-on learning, E-learning, paramedical students, medical education

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Authors: Vineetha Bettaiah, Heggere S. Ranganath

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This paper presents a Hierarchical Piecewise Linear Approximation (HPLA) for the representation of time series data in which the time series is treated as a curve in the time-amplitude image space. The curve is partitioned into segments by choosing perceptually important points as break points. Each segment between adjacent break points is recursively partitioned into two segments at the best point or midpoint until the error between the approximating line and the original curve becomes less than a pre-specified threshold. The HPLA representation achieves dimensionality reduction while preserving prominent local features and general shape of time series. The representation permits course-fine processing at different levels of details, allows flexible definition of similarity based on mathematical measures or general time series shape, and supports time series data mining operations including query by content, clustering and classification based on whole or subsequence similarity.

Keywords: data mining, dimensionality reduction, piecewise linear representation, time series representation

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Authors: Hary Aprianto Wijaya Siahaan, Bayu Edo Pratama

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Sea fishery's potential to become one of the nation's assets which very contributed to Indonesia's economy. This fishery potential not in spite of the availability of the chlorophyll in the territorial waters of Indonesia. The research was conducted using three methods, namely: statistics, comparative and analytical. The data used include MODIS sea temperature data imaging results in Aqua satellite with a resolution of 4 km in 2002-2015, MODIS data of chlorophyll-a imaging results in Aqua satellite with a resolution of 4 km in 2002-2015, and Imaging results data ASCAT on MetOp and NOAA satellites with 27 km resolution in 2002-2015. The results of the processing of the data show that the incidence of upwelling in the south of East Java Sea began to happen in June identified with sea surface temperature anomaly below normal, the mass of the air that moves from the East to the West, and chlorophyll-a concentrations are high. In July the region upwelling events are increasingly expanding towards the West and reached its peak in August. Chlorophyll-a concentration prediction using multiple linear regression equations demonstrate excellent results to chlorophyll-a concentrations prediction in 2002 until 2015 with the correlation of predicted chlorophyll-a concentration indicate a value of 0.8 and 0.3 with RMSE value. On the chlorophyll-a concentration prediction in 2016 indicate good results despite a decline in the value of the correlation, where the correlation of predicted chlorophyll-a concentration in the year 2016 indicate a value 0.6, but showed improvement in RMSE values with 0.2.

Keywords: satellite, sea surface temperature, upwelling, wind stress

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Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

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In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

Procedia PDF Downloads 390

Authors: Gizem Kodak

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The Strait of Çanakkale, together with the Strait of Istanbul and the Sea of Marmara, form the Turkish Straits System. In other words, the Strait of Çanakkale is the southern gate of the system that connects the Black Sea countries with the other countries of the world. Due to the heavy maritime traffic, it is important to scientifically examine the accident characteristics in the region. In particular, the results indicated by the descriptive statistics are of critical importance in order to strengthen the safety of navigation. At this point, exploratory data analysis offers strategic outputs in terms of defining the problem and knowing the strengths and weaknesses against possible accident risk. The study aims to determine the accident characteristics in the Strait of Çanakkale with temporal and spatial analysis of historical data, using Exploratory Data Analysis (EDA) as the research method. The study's results will reveal the general characteristics of maritime accidents in the region and form the infrastructure for future studies. Therefore, the text provides a clear description of the research goals and methodology, and the study's contributions are well-defined.

Keywords: maritime accidents, EDA, Strait of Çanakkale, navigational safety

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Authors: Saima Nazir, Mustansar Ali Ghazanfar, Sanay Muhammad Umar Saeed, Muhammad Awais Azam, Saad Ali Alahmari

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Terrorism is an important and challenging concern. The entire world is threatened by only few sophisticated terrorist groups and especially in Gulf Region and Pakistan, it has become extremely destructive phenomena in recent years. Predicting the pattern of attack type, attack group and target type is an intricate task. This study offers new insight on terrorist group’s attack type and its chosen target. This research paper proposes a framework for prediction of terrorist attacks using the historical data and making an association between terrorist group, their attack type and target. Analysis shows that the number of attacks per year will keep on increasing, and Al-Harmayan in Saudi Arabia, Al-Qai’da in Gulf Region and Tehreek-e-Taliban in Pakistan will remain responsible for many future terrorist attacks. Top main targets of each group will be private citizen & property, police, government and military sector under constant circumstances.

Keywords: data mining, counter terrorism, machine learning, SVM

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Authors: Sonam Sandal, Susan Verghese P.

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The phrase "environmental tobacco smoke" (ETS) refers to exposure to tobacco smoke that isn't from your own smoking but instead is caused by being in close proximity to someone else's cigar, cigarette, or pipe smoke. Environmental cigarette smoke is one of the main contributors to indoor air pollution (IAP), which is exceedingly harmful to human health and results in millions of deaths each year, according to the World Health Organization. Sidestream smoke (SS), which is discharged from a cigarette's burning end in between puffs, is the primary cause of ETS. The bulk of the ETS residue is composed of gases that are produced while smoking through the cigarette paper, mainstream smoke (MS) ingested, and side stream smoke emitted while inhaling a puff from the burning end. Each of these mixtures—SS, ETS, and MS—is an aerosol composed of an IAP-causing vapor phase and a particle phase. Therefore, indoor air-cleaning equipment designed to remove particles will not significantly alter nicotine exposure but will alter the concentrations of other dangerous substances, including particulate matter (PM), PM 2.5, and PM 10. In conclusion, indoor airborne contaminants pose serious risks to human health. ETS degrades the air quality, and when someone breathes this bad air, it weakens their lungs and makes them more susceptible to COVID-19.

Keywords: pm 10, covid-19, indoor air pollution, cigarette smoke., pm 2.5

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Authors: Alejandra Cardenas, Ona Flores, Fabiola Gretzinger

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Since the 1990s, legal strategies for the promotion and protection of maternal health rights have achieved significant gains. Successful litigation in courts around the world have shown that these rights can be judicially enforceable. Governments and international organizations have acknowledged the importance of a human rights-based approach to maternal mortality and morbidity, and obstetric violence has been recognized as a human rights issue. Despite the progress made, maternal mortality has worsened in some regions of the world, while progress has stagnated elsewhere, and mistreatment in maternal care is reported almost universally. In this context, issues of maternal autonomy and decision-making during pregnancy, labor, and delivery as a critical barrier to access quality maternal health have been largely overlooked. Indeed, despite the principles of autonomy and informed consent in medical interventions being well-established in international and regional norms, how they are applied particularly during childbirth and pregnancy remains underdeveloped. National and global legal standards and decisions related to maternal health were reviewed and analyzed to determine how maternal autonomy and decision-making during pregnancy, labor, and delivery have been protected (or not) by international and national courts. The results of this legal research and analysis lead to the conclusion that a few standards have been set by courts regarding pregnant people’s rights to make choices during pregnancy and birth; however, most undermine the agency of pregnant people. These decisions recognize obstetric violence and gender-based discrimination, but fail to protect pregnant people’s autonomy, privacy, and their right to informed consent. As current human rights standards stand today, maternal health is the only field in medicine and law in which informed consent can be overridden, and patients can be forced to submit to treatments against their will. Unconsented treatment and loss of agency during pregnancy and childbirth can have long-term physical and mental impacts, reduce satisfaction and trust in health systems, and may deter future health-seeking behaviors. This research proposes a path forward that focuses on the pregnant person as an independent agent, relying on the doctrine of self-determination during pregnancy and childbirth, which includes access to the necessary conditions to enable autonomy and choice throughout pregnancy and childbirth as a critical step towards our approaches to reduce maternal mortality, morbidity, and mistreatment, and realize the promise of access to quality maternal health as a human right.

Keywords: autonomy in childbirth and pregnancy, choice, informed consent, jurisprudential analysis

Procedia PDF Downloads 58

Authors: Elisenda Camprecios, Alicia Macarrila, Montse Albiol, Neus Garriga Garriga

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The loss of a child during pregnancy, or shortly after birth, is not a common occurrence, but it is a prevalent fact in our society. When this loss happens, life and death walk together. The grief that parents experience following a perinatal loss is a devastating experience. Professionals are aware that the quality of care offered during this first period is crucial to support the families experiencing a perinatal loss and meet their needs. However, it is not always easy for the health care professionals to know what to say and what to do in these difficult circumstances. Given the complexity of the Health, painful process that a family must face when is affected by such loss, we believe that the creation of a protocol that pays special attention to the emotional needs of those couples can be a very valuable tool for the professionals. The short documentary named ‘When the illusion vanished’ was created as part of the material of this protocol, which focuses on the emotional needs of the families who have suffered a perinatal loss. This video is designed to see what impact has a perinatal death and to raise awareness among professionals working in this field. The methodology is based on interviews with couples who have experienced perinatal death and to professionals who accompany families suffering from perinatal loss. The use of sensitive and empathized words, being encouraged to express feelings, respect the time, appropriate training for the professionals are some of the issues reflected in this documentary. We believe that this video has contributed to help health care professionals to empathize and understand the need to be able to accompany these families with the appropriate care, respectful, empathetic attitude and professionalism so that they can start the path to a ‘healthy’ mourning.

Keywords: neonatal loss, midwifery, perinatal bereavement, perinatal loss

Procedia PDF Downloads 154

Authors: Frazer McDonald Ng'oma

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Online Learning in Malawi has only immersed in recent years due to the need to increase access to higher education, the need to accommodate upgrading students who wish to study on a part time basis while still continuing their work, and the COVID-19 pandemic, which forced the closure of schools resulting in academic institutions seeking alternative modes of teaching and Learning to ensure continued teaching and Learning. Realizing that this mode of Learning is becoming a norm, institutions of higher Learning have started pioneering online post-graduate programs from which they can draw lessons before fully implementing it in undergraduate programs. Online learning pedagogy has not been fully grasped and institutions are still experimenting with this mode of Learning until online Learning guiding policies are created and its standards improved. This single case descriptive qualitative research study sought to investigate online postgraduate students’ perceptions and experiences with Student to student interactive pedagogy in their programs. The results of the study are to inform institutions and educators how to structure their programs to ensure that their students get the full satisfaction. 25 Masters students in 3 recently introduced online programs at Kamuzu University of Health Sciences (KUHES), were engaged; 19 were interviewed and 6 responded to questionnaires. The findings from the students were presented and categorized in themes and subthemes that emerged from the qualitative data that was collected and analysed following Colaizzi’s framework for data analysis that resulted in themes formulation. Findings revealed that Student to student interactions occurred in the online programme during live sessions, on class Whatsapp group, in discussion boards as well as on emails. Majority of the students (n=18) felt the level of students’ interaction initiated by the institution was too much, referring to mandatory interactions activities like commenting in discussion boards and attending to live sessons. Some participants (n=7) were satisfied with the level of interaction and also pointed out that they would be fine with more program-initiated student–to–student interactions. These participants attributed having been out of school for some time as a reason for needing peer interactions citing that it is already difficult to get back to a traditional on-campus school after some time, let alone an online class where there is no physical interaction with other students. In general, majority of the participants (n=18) did not value Student to student interaction in online Learning. The students suggested that having intensive student-to-student interaction in postgraduate online studies does not need to be a high priority for the institution and they further recommended that if a lecturer decides to incorporate student-to-student activities into a class, they should be optional.

Keywords: online learning, interactions, student interactions, post graduate students

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Authors: Merad Boudia Omar Rafik, Feham Mohammed

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Data aggregation in wireless sensor networks (WSNs) provides a great reduction of energy consumption. The limited resources of sensor nodes make the choice of an encryption algorithm very important for providing security for data aggregation. Asymmetric cryptography involves large ciphertexts and heavy computations but solves, on the other hand, the problem of key distribution of symmetric one. The latter provides smaller ciphertexts and speed computations. Also, the recent researches have shown that achieving the end-to-end confidentiality and the end-to-end integrity at the same is a challenging task. In this paper, we propose (SA-SPKC), a novel security protocol which addresses both security services for WSNs, and where only the base station can verify the individual data and identify the malicious node. Our scheme is based on stateful public key encryption (StPKE). The latter combines the best features of both kinds of encryption along with state in order to reduce the computation overhead. Our analysis

Keywords: secure data aggregation, wireless sensor networks, elliptic curve cryptography, homomorphic encryption

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Authors: Brock Liden, Eric Janowitz

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Introduction: Diabetic peripheral neuropathy (DPN) affects 70% of individuals with diabetes1. DPN causes a loss of protective sensation, which can lead to tissue damage and diabetic foot ulcer (DFU) formation2. These ulcers can result in infections and lower-extremity amputations of toes, the entire foot, and the lower leg. Even after a DFU is healed, recurrence is common, with 49% of DFU patients developing another ulcer within a year and 68% within 5 years3. This case series examines the use of sensory insoles and newly available plantar data (pressure, temperature, step count, adherence) and remote patient monitoring in patients at risk of DFU. Methods: Participants were provided with custom-made sensory insoles to monitor plantar pressure, temperature, step count, and daily use and were provided with real-time cues for pressure offloading as they went about their daily activities. The sensory insoles were used to track subject compliance, ulceration, and response to feedback from real-time alerts. Patients were remotely monitored by a qualified healthcare professional and were contacted when areas of concern were seen and provided coaching on reducing risk factors and overall support to improve foot health. Results: Of the 40 participants provided with the sensory insole system, 4 presented with a DFU. Based on flags generated from the available plantar data, patients were contacted by the remote monitor to address potential concerns. A standard clinical escalation protocol detailed when and how concerns should be escalated to the provider by the remote monitor. Upon escalation to the provider, patients were brought into the clinic as needed, allowing for any issues to be addressed before more serious complications might arise. Conclusion: This case series explores the use of innovative sensory technology to collect plantar data (pressure, temperature, step count, and adherence) for DFU detection and early intervention. The results from this case series suggest the importance of sensory technology and remote patient monitoring in providing proactive, preventative care for patients at risk of DFU. This robust plantar data, with the addition of remote patient monitoring, allow for patients to be seen in the clinic when concerns arise, giving providers the opportunity to intervene early and prevent more serious complications, such as wounds, from occurring.

Keywords: diabetic foot ulcer, DFU prevention, digital therapeutics, remote patient monitoring

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Authors: Ahmed N. Shmroukh, Gamal Tag Abdel-Jaber, Rashed D. Aldughpassi

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The feasibility of improving the performance of the proposed solar still unit which operated in very hot climate is investigated numerically and verified with experimental data. This solar desalination unit with proposed auxiliary device as seawater preheating system using petrol based textherm oil was used to produce pure fresh water from seawater. The effective evaporation area of basin is about 1 m². The unit was tested in two main operation modes which are normal and with seawater preheating system. The results showed that, there is good agreement between the theoretical data and the experimental data; this means that the numerical model can be accurately dependable for predicting the proposed solar still performance and design parameters. The results also showed that the fresh water productivity of the solar still in the modified preheating case which is higher than normal case, leads to an increase in productivity of 42%.

Keywords: improving productivity, seawater desalination, solar stills, theoretical model

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Authors: Merve Kadioğlu, Nevin H. Şahin

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Purpose: This research is organized to determine the influence of the web-based learning program. The program has been developed to gain information about normal delivery skill that is one of the topics of nursing students who take the woman health and illness. Material and Methods: The methodology of this study was applied as pre-test post-test single-group quasi-experimental. The pilot study consisted of 28 nursing student study groups who agreed to participate in the study. The findings were gathered via web-based technologies: student information form, information evaluation tests, Web Based Training Material Evaluation Scale and web-based learning environment feedback form. In the analysis of the data, the percentage, frequency and Wilcoxon Signed Ranks Test were used. The Web Based Instruction Program was developed in the light of full learning model, Mayer's research-based multimedia development principles and Gagne's Instructional Activities Model. Findings: The average scores of it was determined in accordance with the web-based educational material evaluation scale: ‘Instructional Suitability’ 4.45, ‘Suitability to Educational Program’ 4.48, ‘Visual Adequacy’ 4.53, ‘Programming Eligibility / Technical Adequacy’ 4.00. Also, the participants mentioned that the program is successful and useful. A significant difference was found between the pre-test and post-test results of the seven modules (p < 0.05). Results: According to pilot study data, the program was rated ‘very good’ by the study group. It was also found to be effective in increasing knowledge about normal labor.

Keywords: normal delivery, web-based learning, nursing students, e-learning

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Authors: Khadidja Belbachir, Hafida Belbachir

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subsequently the expansion of the physical supports storage and the needs ceaseless to accumulate several data, the sequential algorithms of associations’ rules research proved to be ineffective. Thus the introduction of the new parallel versions is imperative. We propose in this paper, a parallel version of a sequential algorithm “Partition”. This last is fundamentally different from the other sequential algorithms, because it scans the data base only twice to generate the significant association rules. By consequence, the parallel approach does not require much communication between the sites. The proposed approach was implemented for an experimental study. The obtained results, shows a great reduction in execution time compared to the sequential version and Count Distributed algorithm.

Keywords: association rules, distributed data mining, partition, parallel algorithms

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Authors: Mohamad Kassab, Amal El Fallah Seghrouchni, Frederic Barbaresco, Raed Abu Zitar

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Detecting objects such as drones is a challenging task as their relative size and maneuvering capabilities deceive machine learning models and cause them to misclassify drones as birds or other objects. In this work, we investigate applying several deep learning techniques to benchmark real data sets of flying drones. A deep learning paradigm is proposed for the purpose of mitigating the complexity of those systems. The proposed paradigm consists of a hybrid between the AdderNet deep learning paradigm and the Single Shot Detector (SSD) paradigm. The goal was to minimize multiplication operations numbers in the filtering layers within the proposed system and, hence, reduce complexity. Some standard machine learning technique, such as SVM, is also tested and compared to other deep learning systems. The data sets used for training and testing were either complete or filtered in order to remove the images with mall objects. The types of data were RGB or IR data. Comparisons were made between all these types, and conclusions were presented.

Keywords: drones detection, deep learning, birds versus drones, precision of detection, AdderNet

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Authors: S. Kurian, S. Satpathy, S. K. Gupta, S. Arya, D. K. Sharma

Abstract:

Advances in the use of health care technology have resulted in increased adverse events (AEs) related to the use of medical devices. The study focused on the existing reporting systems. This study was conducted in a tertiary care public sector hospital. Devices included Syringe infusion pumps, Cardiac monitors, Pulse oximeters, Ventilators and Defibrillators. A total of 211 respondents were recruited. Interviews were held with 30 key informants. Medical records were scrutinized. Relevant statistical tests were used. Resident doctors reported maximum frequency of AEs, followed by nurses; and least by consultants. A significant association was found between the cadre of health care personnel and awareness that the patients and bystanders have a risk of sustaining AE. Awareness regarding reporting of AEs was low, and it was generally done verbally. Other critical findings are discussed in the light of the barriers to reporting, reasons for non-compliance, recording system, and so on.

Keywords: adverse events, health care technology, medical devices, public sector hospital, reporting systems

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Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

Abstract:

Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

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Authors: Benyapa Thitimapong, Najwa Niyomdecha

Abstract:

This qualitative descriptive research aimed to explore the self-care experiences during pregnancy of Muslim adolescents. Twenty participants were first-time Muslim mothers who had pregnancy experienceห under 20 years of age in three Southern border provinces of Thailand. Participants were selected by purposive sampling with inclusion criteria. Data were collected from the in-depth interview and analyzed using content analysis. The findings revealed that Muslim pregnant adolescents take care of themselves in the context of combining self-care in an Islamic way and conventional medicine. There are 2 subthemes: 1) antenatal care with Tok Bidan and 2) health promotion during pregnancy. The finding will help to understand self-care during pregnancy of Muslim adolescents among three Southern border provinces and can apply to nurse educators as a guide to educate and manage an appropriate self-care program for Muslim pregnant adolescents based on cultural diversity.

Keywords: adolescents, muslim, pregnancy, selfcare

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Authors: U. Waqas, M. F. Ahmed, A. Mehmood, M. A. Rashid

Abstract:

In geophysical exploration surveys, the quality of acquired data holds significant importance before executing the data processing and interpretation phases. In this study, 2D seismic reflection survey data of Fort Abbas area, Cholistan Desert, Pakistan was taken as test case in order to assess its quality on statistical bases by using normalized root mean square error (NRMSE), Cronbach’s alpha test (α) and null hypothesis tests (t-test and F-test). The analysis challenged the quality of the acquired data and highlighted the significant errors in the acquired database. It is proven that the study area is plain, tectonically least affected and rich in oil and gas reserves. However, subsurface 3D modeling and contouring by using acquired database revealed high degrees of structural complexities and intense folding. The NRMSE had highest percentage of residuals between the estimated and predicted cases. The outcomes of hypothesis testing also proved the biasness and erraticness of the acquired database. Low estimated value of alpha (α) in Cronbach’s alpha test confirmed poor reliability of acquired database. A very low quality of acquired database needs excessive static correction or in some cases, reacquisition of data is also suggested which is most of the time not feasible on economic grounds. The outcomes of this study could be used to assess the quality of large databases and to further utilize as a guideline to establish database quality assessment models to make much more informed decisions in hydrocarbon exploration field.

Keywords: Data quality, Null hypothesis, Seismic lines, Seismic reflection survey

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Authors: Derick M. Rakgoale, Topside E. Mathonsi, Vusumuzi Malele

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Cloud computing offers distributed online and on-demand computational services from anywhere in the world. Cloud computing services have grown immensely over the past years, especially in the past year due to the Coronavirus pandemic. Cloud computing has changed the working environment and introduced work from work phenomenon, which enabled the adoption of technologies to fulfill the new workings, including cloud services offerings. The increased cloud computing adoption has come with new challenges regarding data privacy and its integrity in the cloud environment. Previously advanced encryption algorithms failed to reduce the memory space required for cloud computing performance, thus increasing the computational cost. This paper reviews the existing encryption algorithms used in cloud computing. In the future, artificial neural networks (ANN) algorithm design will be presented as a security solution to ensure data integrity, confidentiality, privacy, and availability of user data in cloud computing. Moreover, MATLAB will be used to evaluate the proposed solution, and simulation results will be presented.

Keywords: cloud computing, data integrity, confidentiality, privacy, availability

Procedia PDF Downloads 142

Authors: Asma Ahmed, Farah Khalid, Sahlah Sohail, Saira Banusokwalla, Sabiha Banu, Inaara Akbar, Safia Awan, Syed Iqbal Azam

Abstract:

Background and Objectives: The level of knowledge regarding obesity as a disease condition and health-seeking behavior regarding its management is grossly lacking. We present data from our multidisciplinary obesity clinic at the large tertiary care facility in Karachi, Pakistan, to provide baseline profiles and outcomes of patients attending these clinics. Methods: 260 who attended the obesity clinic between June 2018 to March 2020 were enrolled in this study. The analysis included descriptive and ROC analysis to identify the best cut-offs of theanthropometric measurements to diagnose obesity-related comorbid conditions. Results: The majority of the studied population were women (72.3%) and employed(43.7%) with a mean age of 35.5 years. Mean BMIwas 37.4, waist circumference was 112.4 cm, visceral fat was 11.7%, and HbA1C was 6.9%. The most common comorbidities were HTN & D.M (33 &31%, respectively). The prevalence of MetS was 16.3% in patients and was slightly higher in males. Visceral fat was the main factor in predicting D.M (0.750; 95% CI: 0.665, 0.836) and MetS (0.709; 95% CI: 0.590, 0.838) compared to total body fat, waist circumference, and BMI. The risk of predicting DM &MetS for the visceral fat above 9.5% in women had the highest sensitivity (80% for D.M & 79% for MetS) and an NPV (92.75% for D.M & 95% for MetS). Conclusions: This study describes and establishes characteristics of these obese individuals, which can help inform clinical practices. These practices may involve using visceral fat for earlier identification and counseling-based interventions to prevent more severe surgical interventions down the line.

Keywords: obesity, metabolic syndrome, tertiary care facility, BMI, waist circumference, visceral fat

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Authors: John Ahluwalia

Abstract:

As an affluent first-world nation, Canada took swift and comprehensive action during the outbreak of the SARS-CoV-2 (COVID-19) pandemic compared to other countries in the same socio-economic cohort. The United States has stumbled to overcome obstacles most developed nations have faced, which has led to significantly more per capita cases and deaths. The initial outbreaks of COVID-19 occurred in the US and Canada within days of each other and posed similar potentially catastrophic threats to public health, the economy, and governmental stability. On a macro level, events that take place in the US have a direct impact on Canada. For example, both countries tend to enter and exit economic recessions at approximately the same time, they are each other’s largest trading partners, and their currencies are inexorably linked. Variables intrinsic to Canada’s national infrastructure have been instrumental in the country’s efforts to flatten the curve of COVID-19 cases and deaths. Canada’s coordinated multi-level governmental effort has allowed it to create and enforce policies related to COVID-19 at both the national and provincial levels. Canada’s policy of universal health care is another variable. Health care and public health measures are enforced on a provincial level, and it is within each province’s jurisdiction to dictate standards for public safety based on scientific evidence. Rather than introducing confusion and the possibility of competition for resources such as PPE and vaccines, Canada’s multi-level chain of government authority has provided consistent policies supporting national public health and local delivery of medical care. This paper will demonstrate that the coordinated efforts on provincial and federal levels have been the linchpin in Canada’s relative success in containing the deadly spread of the COVID-19 virus.

Keywords: COVID-19, canada, GIS, geospatial analysis

Procedia PDF Downloads 74