Search results for: healthcare data security

Authors: Manas Tripathi, Arunabha Mukhopadhyay

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In Cloud computing environment, cloud servers, sometimes may crash after receiving huge amount of request and cloud services may stop which can create huge loss to users of that cloud services. This situation is called Denial of Service (DoS) attack. In Distributed Denial of Service (DDoS) attack, an attacker targets multiple network paths by compromising various vulnerable systems (zombies) and floods the victim with huge amount of request through these zombies. There are many solutions to mitigate this challenge but most of the methods allows the attack traffic to arrive at Cloud Service Provider (CSP) and then only takes actions against mitigation. Here in this paper we are rather focusing on preventive mechanism to deal with these attacks. We analyze network topology and find most vulnerable paths beforehand without waiting for the traffic to arrive at CSP. We have used Dijkstra's and Yen’s algorithm. Finally, risk assessment of these paths can be done by multiplying the probabilities of attack for these paths with the potential loss.

Keywords: cloud computing, DDoS, Dijkstra, Yen’s k-shortest path, network security

Procedia PDF Downloads 274

Authors: Mohammad Bakhshandeh

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Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: structural health monitoring (SHM), bridge health monitoring (BHM), sensor-based methods, machine-learning algorithms, and model-based techniques, sensor placement, data acquisition, data analysis

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Authors: Abdulkadir Magaji

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This study analyzes and compares the actual measured and simulated performance of a 3.2 kwP grid-connected photovoltaic system. The system is located at the Outdoor Facility of Government Day secondary School Katsina State, which lies approximately between coordinate of 12°15′N 7°30′E. The system consists of 14 Mono crystalline silicon modules connected in two strings of 7 series-connected modules, each facing north at a fixed tilt of 340. The data presented in this study were measured in the year 2015, where the system supplied a total of 4628 kWh to the local electric utility grid. The performance of the system was simulated using PVsyst software using measured and Meteonorm derived climate data sets (solar radiation, ambient temperature and wind speed). The comparison between measured and simulated energy yield are discussed. Although, both simulation results were similar, better comparison between measured and predicted monthly energy yield is observed with simulation performed using measured weather data at the site. The measured performance ratio in the present study shows 58.4% is higher than those reported elsewhere as compared in the study.

Keywords: performance, evaluation, grid connection, photovoltaic system

Procedia PDF Downloads 177

Authors: Najmeh Jafari, Sona Rostampour Yasouri

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Crimean-Congo hemorrhagic fever (CCHF) is an acute hemorrhagic disease. This disease is one of the common diseases between humans and animals, transmitted through tick bites or contact with the blood and secretions or carcasses of infected animals and humans. CCHF is more common in people who work with livestock, such as ranchers, butchers, farmers, slaughterhouse workers, healthcare workers, etc. Its hospital prevalence is also very high. Considering that CCHF can be transmitted through the consumption of food such as beef and sheep meat, this study aims to quickly identify and diagnose the Crimean-Congo fever virus in suspected patients through real-time PCR technique. In the summer of 1402, 20 blood samples were collected separately from Ahvaz and Gilan hospitals. An extraction kit was used to extract the virus RNA. Primers and probes were designed based on the S genomic region, the conserved region in CCHFV. Then, a real-time PCR technique was performed with specific primers and probes. It should be noted that the mentioned technique was repeated several times. The number of 4 samples from the examined samples was determined positive by real-time PCR. This technique has high sensitivity and specificity and the possibility of rapid detection of CCHFV. Therefore, the above method is a good candidate for quick disease diagnosis. By diagnosing the disease, the treatment process can be done faster, and the best prevention methods can be used to control the disease and prevent the death of patients.

Keywords: ahvaz, crimean-congo hemorrhagic fever, gilan, real time PCR

Procedia PDF Downloads 69

Authors: Moses E. Emetere, M. L. Akinyemi

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Agricultural activities in the South–West Nigeria are mitigated by the global increase in temperature. The unpredictive surface temperature of the area had increased health challenges amongst other social influence. The satellite data of surface temperatures were compared with the ground station Davis weather station. The differential heating of the lower atmosphere were represented mathematically. A numerical predictive model was propounded to forecast future surface temperature.

Keywords: numerical predictive model, surface temperature, satellite date, ground data

Procedia PDF Downloads 464

Authors: John E. Foley, Martin Miele, Raul Fonda, Jon Jacobson

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This paper presents development and implementation of new and innovative data collection and analysis methodologies based on deployment of total field magnetometer arrays. Our research has focused on the development of a vertically-integrated suite of platforms all utilizing common data acquisition, data processing and analysis tools. These survey platforms include low-altitude helicopters and ground-based vehicles, including robots, for terrestrial mapping applications. For marine settings the sensor arrays are deployed from either a hydrodynamic bottom-following wing towed from a surface vessel or from a towed floating platform for shallow-water settings. Additionally, sensor arrays are deployed from tethered remotely operated vehicles (ROVs) for underwater settings where high maneuverability is required. While the primary application of these systems is the detection and mapping of unexploded ordnance (UXO), these system are also used for various infrastructure mapping and geologic investigations. For each application, success is driven by the integration of magnetometer arrays, accurate geo-positioning, system noise mitigation, and stable deployment of the system in appropriate proximity of expected targets or features. Each of the systems collects geo-registered data compatible with a web-enabled data management system providing immediate access of data and meta-data for remote processing, analysis and delivery of results. This approach allows highly sophisticated magnetic processing methods, including classification based on dipole modeling and remanent magnetization, to be efficiently applied to many projects. This paper also briefly describes the initial development of magnetometer-based detection systems deployed from low-altitude helicopter platforms and the subsequent successful transition of this technology to the marine environment. Additionally, we present examples from a range of terrestrial and marine settings as well as ongoing research efforts related to sensor miniaturization for unmanned aerial vehicle (UAV) magnetic field mapping applications.

Keywords: dipole modeling, magnetometer mapping systems, sub-surface infrastructure mapping, unexploded ordnance detection

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Authors: Eid Alharbi, Yaser Miaji

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The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology

Procedia PDF Downloads 395

Authors: Eid Alharbi, Yaser Miaji

Abstract:

The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology

Procedia PDF Downloads 385

Authors: Meenal Badki

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We address the issue of active feature determination, where the objective is to determine the set of examples on which additional data (such as lab tests) needs to be gathered, given a large number of examples with some features (such as demographics) and some examples with all the features (such as the complete Electronic Health Record). We note that certain features may be more costly, unique, or laborious to gather. Our proposal is a general active learning approach that is independent of classifiers and similarity metrics. It allows us to identify examples that differ from the full data set and obtain all the features for the examples that match. Our comprehensive evaluation shows the efficacy of this approach, which is driven by four authentic clinical tasks.

Keywords: feature determination, classification, active learning, sample-efficiency

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Authors: Allison Herlene Du Plessis, Dalena (R.M.) Van Rooyen, Wilma Ten Ham-Baloyi, Sihaam Jardien-Baboo

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Introduction: Women die in pregnancy and childbirth for five main reasons—severe bleeding, infections, unsafe abortions, hypertensive disorders (pre-eclampsia and eclampsia), and medical complications including cardiac disease, diabetes, or HIV/AIDS complicated by pregnancy. In 2015, WHO classified sepsis as the third highest cause for maternal mortalities in the world. Chorioamnionitis is a clinical syndrome of intrauterine infection during any stage of the pregnancy and it refers to ascending bacteria from the vaginal canal up into the uterus, causing infection. While the incidence rates for chorioamnionitis are not well documented, complications related to chorioamnionitis are well documented and midwives still struggle to identify this condition in time due to its complex nature. Few diagnostic methods are available in public health services, due to escalated laboratory costs. Often the affordable biomarkers, such as C-reactive protein CRP, full blood count (FBC) and WBC, have low significance in diagnosing chorioamnionitis. A lack of screening impacts on effective and timeous management of chorioamnionitis, and early identification and management of risks could help to prevent neonatal complications and reduce the subsequent series of morbidities and healthcare costs of infants who are health foci of perinatal infections. Objective: This integrative literature review provides an overview of current best research evidence on the screening of women at risk for chorioamnionitis. Design: An integrative literature review was conducted using a systematic electronic literature search through EBSCOhost, Cochrane Online, Wiley Online, PubMed, Scopus and Google. Guidelines, research studies, and reports in English related to chorioamnionitis from 2008 up until 2020 were included in the study. Findings: After critical appraisal, 31 articles were included. More than one third (67%) of the literature included ranked on the three highest levels of evidence (Level I, II and III). Data extracted regarding screening for chorioamnionitis was synthesized into four themes, namely: screening by clinical signs and symptoms, screening by causative factors of chorioamnionitis, screening of obstetric history, and essential biomarkers to diagnose chorioamnionitis. Key conclusions: There are factors that can be used by midwives to identify women at risk for chorioamnionitis. However, there are a paucity of established sociological, epidemiological and behavioral factors to screen this population. Several biomarkers are available to diagnose chorioamnionitis. Increased Interleukin-6 in amniotic fluid is the better indicator and strongest predictor of histological chorioamnionitis, whereas the available rapid matrix-metalloproteinase-8 test requires further testing. Maternal white blood cells count (WBC) has shown poor selectivity and sensitivity, and C-reactive protein (CRP) thresholds varied among studies and are not ideal for conclusive diagnosis of subclinical chorioamnionitis. Implications for practice: Screening of women at risk for chorioamnionitis by health care providers providing care for pregnant women, including midwives, is important for diagnosis and management before complications arise, particularly in resource-constraint settings.

Keywords: chorioamnionitis, guidelines, best evidence, screening, diagnosis, pregnant women

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Authors: Mohan Ramasundaram, Amutha Prabakar Muniyandi

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Remote user authentication is one of the important tasks for any kind of remote server applications. Several remote authentication schemes are proposed by the researcher for Telecare Medicine Information System (TMIS). Most of the existing techniques have limitations, vulnerable to various kind attacks, lack of functionalities, information leakage, no perfect forward security and ineffectiveness. Authentication is a process of user verification mechanism for allows him to access the resources of a server. Nowadays, most of the remote authentication protocols are using two-factor authentications. We have made a survey of several remote authentication schemes using three factors and this survey shows that the most of the schemes are inefficient and subject to several attacks. We observed from the experimental evaluation; the proposed scheme is very secure against various known attacks that include replay attack, man-in-the-middle attack. Furthermore, the analysis based on the communication cost and computational cost estimation of the proposed scheme with related schemes shows that our proposed scheme is efficient.

Keywords: Telecare Medicine Information System, elliptic curve cryptography, three-factor, biometric, random oracle

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Authors: Kara Rosenblatt, Kevin Badgett, James Eldridge

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There is a preponderance of information regarding the overall effectiveness of charter schools and their ability to increase academic achievement compared to traditional district schools. Most research on the topic is focused on comparing long and short-term outcomes, academic achievement in mathematics and reading, and locale (i.e., urban, v. Rural). While the lingering unanswered questions regarding effectiveness continue to loom for school leaders, data on charter schools suggests that enrollment increases by 10% annually and that charter schools educate more than 2 million U.S. students across 40 states each year. Given the increasing share of U.S. students educated in charter schools, it is important to better understand possible differences in student achievement defined in multiple ways for students in charter schools and for those in Independent School District (ISD) settings in the state of Texas. Data were retrieved from the Texas Education Agency’s (TEA) repository that includes data organized annually and available on the TEA website. Specific data points and definitions of achievement were based on characterizations of achievement found in the relevant literature. Specific data points include but were not limited to graduation rate, student performance on standardized testing, and teacher-related factors such as experience and longevity in the district. Initial findings indicate some similarities with the current literature on long-term student achievement in English/Language Arts; however, the findings differ substantially from other recent research related to long-term student achievement in social studies. There are a number of interesting findings also related to differences between achievement for students in charters and ISDs and within different types of charter schools in Texas. In addition to findings, implications for leadership in different settings will be explored.

Keywords: charter schools, ISDs, student achievement, implications for PK-12 school leadership

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Authors: Muhammad Luqman, Yusuf Kurniawan

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S-Boxes is one of the linear parts of the cryptographic algorithm. The existence of S-Box in the cryptographic algorithm is needed to maintain non-linearity of the algorithm. Nowadays, modern cryptographic algorithms use an S-Box as a part of algorithm process. Despite the fact that several cryptographic algorithms today reuse theoretically secure and carefully constructed S-Boxes, there is an evaluation characteristic that can measure security properties of S-Boxes and hence the corresponding primitives. Analysis of an S-Box usually is done using manual mathematics calculation. Several S-Boxes are presented as a Truth Table without any mathematical background algorithm. Then, it’s rather difficult to determine the strength of Truth Table S-Box without a mathematical algorithm. A comprehensive analysis should be applied to the Truth Table S-Box to determine the characteristic. Several important characteristics should be owned by the S-Boxes, they are Nonlinearity, Balancedness, Algebraic degree, LAT, DAT, differential delta uniformity, correlation immunity and global avalanche criterion. Then, a comprehensive tool will be present to automatically calculate the characteristics of S-Boxes and determine the strength of S-Box. Comprehensive analysis is done on a deterministic process to produce a sequence of S-Boxes characteristic and give advice for a better S-Box construction.

Keywords: cryptographic properties, Truth Table S-Boxes, S-Boxes characteristic, deterministic process

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Authors: Md Shafiqul Bari, Md Shafiqul Islam Sikdar

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This paper summarizes the current knowledge on Agroforestry practices in the Barind tract of Bangladesh. The part of greater Rajshahi, Dinajpur, Rangpur and Bogra district of Bangladesh is geographically identified as the Barind tract. The hard red soil of these areas is very significant in comparison to that of the other parts of the country. A typical dry climate with comparatively high temperature prevails in the Barind area. Scanty rainfall and excessive extraction of groundwater have created an alarming situation among the Barind people and others about irrigation to the rice field. In addition, the situation may cause an adverse impact on the people whose livelihood largely depends on agriculture. The groundwater table has been declined by at least 10 to 15 meters in some areas of the Barind tract during the last 20 years. Due to absent of forestland in the Barind tract, the soil organic carbon content can decrease more rapidly because of the higher rate of decomposition. The Barind soils are largely carbon depleted but can be brought back to carbon-carrying capacity by bringing under suitable Agroforestry systems. Agroforestry has tremendous potential for carbon sequestration not only in above C biomass but also root C biomass in deeper soil depths. Agroforestry systems habitually conserve soil organic carbon and maintain a great natural nutrient pool. Cultivation of trees with arable crops under Agroforestry systems help in improving soil organic carbon content and sequestration carbon, particularly in the highly degraded Barind lands. Agroforestry systems are a way of securing the growth of cash crops that may constitute an alternative source of income in moments of crisis. Besides being a source of fuel wood, a greater presence of trees in cropping system contributes to decreasing temperatures and to increasing rainfall, thus contrasting the negative environmental impact of climate changes. In order to fulfill the objectives of this study, two experiments were conducted. The first experiment was survey on the impact of existing agroforestry system on the livelihood security in the Barind tract of Bangladesh and the second one was the role of agroforestry system on the improvement of soil properties in a multilayered coconut orchard. Agroforestry systems have been generated a lot of employment opportunities in the Barind area. More crops mean involvement of more people in various activities like involvements in dairying, sericulture, apiculture and additional associated agro-based interventions. Successful adoption of Agroforestry practices in the Barind area has shown that the Agroforestry practitioners of this area were very sound positioned economically, and had added social status too. However, from the findings of the present study, it may be concluded that the majority rural farmers of the Barind tract of Bangladesh had a very good knowledge and medium extension contact related to agroforestry production system. It was also observed that 85 per cent farmers followed agroforestry production system and received benefits to a higher extent. Again, from the research study on orchard based mutistoried agroforestry cropping system, it was evident that there was an important effect of agroforestry cropping systems on the improvement of soil chemical properties. As a result, the agroforestry systems may be helpful to attain the development objectives and preserve the biosphere core.

Keywords: agroforestry systems, Barind tract, carbon sequestration, climate changes

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Authors: Abdorreza Rabiee, Shahla Mohammad Hoseini Mirzaei

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The advantages of distributed generations (DGs) based on renewable energy sources (RESs) leads to high penetration level of DGs in distribution network. With incorporation of DGs in distribution systems, the system reliability and security, as well as voltage profile, is improved. However, the protection of such systems is still challenging. In this paper, at first, the related papers are reviewed and then a practical scheme is proposed for coordination of OCRs in distribution system with DGs. The coordination problem is formulated as a nonlinear programming (NLP) optimization problem with the object function of minimizing total operating time of OCRs. The proposed method is studied based on a simple test system. The optimization problem is solved by General Algebraic Modeling System (GAMS) to calculate the optimal time dial setting (TDS) and also pickup current setting of OCRs. The results show the effectiveness of the proposed method and its applicability.

Keywords: distributed generation, DG, distribution network, over current relay, OCR, protection coordination, pickup current, time dial setting, TDS

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Authors: Lassi Lehto, Jaakko Kahkonen, Juha Oksanen, Tapani Sarjakoski

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The use of raster-formatted data sets in geospatial analysis is increasing rapidly. At the same time, geographic data are being introduced into disciplines outside the traditional domain of geoinformatics, like climate change, intelligent transport, and immigration studies. These developments call for better methods to deliver raster geodata in an efficient and easy-to-use manner. Data cube technologies have traditionally been used in the geospatial domain for managing Earth Observation data sets that have strict requirements for effective handling of time series. The same approach and methodologies can also be applied in managing other types of geospatial data sets. A cloud service-based geodata cube, called GeoCubes Finland, has been developed to support online delivery and analysis of most important geospatial data sets with national coverage. The main target group of the service is the academic research institutes in the country. The most significant aspects of the GeoCubes data repository include the use of multiple resolution levels, cloud-optimized file structure, and a customized, flexible content access API. Input data sets are pre-processed while being ingested into the repository to bring them into a harmonized form in aspects like georeferencing, sampling resolutions, spatial subdivision, and value encoding. All the resolution levels are created using an appropriate generalization method, selected depending on the nature of the source data set. Multiple pre-processed resolutions enable new kinds of online analysis approaches to be introduced. Analysis processes based on interactive visual exploration can be effectively carried out, as the level of resolution most close to the visual scale can always be used. In the same way, statistical analysis can be carried out on resolution levels that best reflect the scale of the phenomenon being studied. Access times remain close to constant, independent of the scale applied in the application. The cloud service-based approach, applied in the GeoCubes Finland repository, enables analysis operations to be performed on the server platform, thus making high-performance computing facilities easily accessible. The developed GeoCubes API supports this kind of approach for online analysis. The use of cloud-optimized file structures in data storage enables the fast extraction of subareas. The access API allows for the use of vector-formatted administrative areas and user-defined polygons as definitions of subareas for data retrieval. Administrative areas of the country in four levels are available readily from the GeoCubes platform. In addition to direct delivery of raster data, the service also supports the so-called virtual file format, in which only a small text file is first downloaded. The text file contains links to the raster content on the service platform. The actual raster data is downloaded on demand, from the spatial area and resolution level required in each stage of the application. By the geodata cube approach, pre-harmonized geospatial data sets are made accessible to new categories of inexperienced users in an easy-to-use manner. At the same time, the multiresolution nature of the GeoCubes repository facilitates expert users to introduce new kinds of interactive online analysis operations.

Keywords: cloud service, geodata cube, multiresolution, raster geodata

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Authors: Vilas Warudkar, Dinkar Janghel, Siraj Ahmed

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Rapid development experienced by India requires huge amount of energy. Actual supply capacity additions have been consistently lower than the targets set by the government. According to World Bank 40% of residences are without electricity. In 12th five year plan 30 GW grid interactive renewable capacity is planned in which 17 GW is Wind, 10 GW is from solar and 2.1 GW from small hydro project, and rest is compensated by bio gas. Renewable energy (RE) and energy efficiency (EE) meet not only the environmental and energy security objectives, but also can play a crucial role in reducing chronic power shortages. In remote areas or areas with a weak grid, wind energy can be used for charging batteries or can be combined with a diesel engine to save fuel whenever wind is available. India according to IEC 61400-1 belongs to class IV Wind Condition; it is not possible to set up wind turbine in large scale at every place. So, the best choice is to go for small scale wind turbine at lower height which will have good annual energy production (AEP). Based on the wind characteristic available at MANIT Bhopal, rotor for small scale wind turbine is designed. Various Aero foil data is reviewed for selection of airfoil in the Blade Profile. Airfoil suited of Low wind conditions i.e. at low Reynold’s number is selected based on Coefficient of Lift, Drag and angle of attack. For designing of the rotor blade, standard Blade Element Momentum (BEM) Theory is implanted. Performance of the Blade is estimated using BEM theory in which axial induction factor and angular induction factor is optimized using iterative technique. Rotor performance is estimated for particular designed blade specifically for low wind Conditions. Power production of rotor is determined at different wind speeds for particular pitch angle of the blade. At pitch 15o and velocity 5 m/sec gives good cut in speed of 2 m/sec and power produced is around 350 Watts. Tip speed of the Blade is considered as 6.5 for which Coefficient of Performance of the rotor is calculated 0.35, which is good acceptable value for Small scale Wind turbine. Simple Load Model (SLM, IEC 61400-2) is also discussed to improve the structural strength of the rotor. In SLM, Edge wise Moment and Flap Wise moment is considered which cause bending stress at the root of the blade. Various Load case mentioned in the IEC 61400-2 is calculated and checked for the partial safety factor of the wind turbine blade.

Keywords: annual energy production, Blade Element Momentum Theory, low wind Conditions, selection of airfoil

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Authors: I Dewa Gede Arya Putra

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Principal Component Analysis (PCA) is a mathematical procedure that uses orthogonal transformation techniques to change a set of data with components that may be related become components that are not related to each other. This can have an impact on clustering wind speed characteristics in Indonesia. This study uses data daily wind speed observations of the Site Meteorological Station network for 30 years. Multicollinearity tests were also performed on all of these data before doing clustering with PCA. The results show that the four main components have a total diversity of above 80% which will be used for clusters. Division of clusters using Ward's method obtained 3 types of clusters. Cluster 1 covers the central part of Sumatra Island, northern Kalimantan, northern Sulawesi, and northern Maluku with the climatological pattern of wind speed that does not have an annual cycle and a weak speed throughout the year with a low-speed ranging from 0 to 1,5 m/s². Cluster 2 covers the northern part of Sumatra Island, South Sulawesi, Bali, northern Papua with the climatological pattern conditions of wind speed that have annual cycle variations with low speeds ranging from 1 to 3 m/s². Cluster 3 covers the eastern part of Java Island, the Southeast Nusa Islands, and the southern Maluku Islands with the climatological pattern of wind speed conditions that have annual cycle variations with high speeds ranging from 1 to 4.5 m/s².

Keywords: PCA, cluster, Ward's method, wind speed

Procedia PDF Downloads 191

Authors: Zanib Nafees, Amir Razaghizad, Ibtisam Mahmoud, Abhinav Sharma, Renzo Cecere

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More than one million surgeries are performed each year in Canada, resulting in more than 100,000 associated serious adverse events (SAEs) per year. These are defined as unintended injuries or complications that adversely affect the well-being of patients. In recent years, there has been a proliferation of digital health interventions that have the potential to assist, monitor, and educate patients—facilitating self-care following post-operative discharge. Among digital health, interventions are interactive-voice response technologies (IVRs), which have been shown to be highly effective in certain medical settings. Although numerous IVR-based interventions have been developed, their effectiveness and utility remain unclear, notably in post-operative settings. To the best of our knowledge, no systematic or scoping reviews have evaluated this topic to date. Thus, the objective of this scoping review protocol is to systematically map and explore the literature and evidence describing and examining IVR tools, implementation, evaluation, outcome, and experience for post-operative patients. The focus will be primarily on the evaluation of baseline performance status, clinical assessment, treatment outcomes, and patient management, including self-management and self-monitoring. The objective of this scoping review is to assess the extent of the literature to direct future research efforts by identifying gaps and limitations in the literature and to highlight relevant determinants of positive outcomes in the emerging field of IVR monitoring for health outcomes in post-operative patients.

Keywords: digital healthcare technologies, post-surgery, interactive voice technology, interactive voice response

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Authors: Shilpa Murthy, Hazlina Binti Abu Bakar, Juliet Mathew, Chandrashekhar Thummala Hlly Sreerama Reddy, Pathiyil Ravi Shankar

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Simulation is defined as a technique that replaces or expands real experiences with guided experiences that interactively imitate real-world processes or systems. Simulation enables learners to train in a safe and non-threatening environment. For decades, simulation has been considered an integral part of clinical teaching and learning strategy in medical education. The several types of simulation used in medical education and the clinical environment can be applied to several models, including full-body mannequins, task trainers, standardized simulated patients, virtual or computer-generated simulation, or Hybrid simulation that can be used to facilitate learning. Simulation allows healthcare practitioners to acquire skills and experience while taking care of patient safety. The recent COVID pandemic has also led to an increase in simulation use, as there were limitations on medical student placements in hospitals and clinics. The learning is tailored according to the educational needs of students to make the learning experience more valuable. Simulation in the pre-clinical years has challenges with resource constraints, effective curricular integration, student engagement and motivation, and evidence of educational impact, to mention a few. As instructors, we may have more reliance on the use of simulation for pre-clinical students while the students’ confidence levels and perceived competence are to be evaluated. Our research question was whether the implementation of simulation-based learning positively influences preclinical medical students' confidence levels and perceived competence. This study was done to align the teaching activities with the student’s learning experience to introduce more low-fidelity simulation-based teaching sessions for pre-clinical years and to obtain students’ input into the curriculum development as part of inclusivity. The study was carried out at International Medical University, involving pre-clinical year (Medical) students who were started with low-fidelity simulation-based medical education from their first semester and were gradually introduced to medium fidelity, too. The Student Satisfaction and Self-Confidence in Learning Scale questionnaire from the National League of Nursing was employed to collect the responses. The internal consistency reliability for the survey items was tested with Cronbach’s alpha using an Excel file. IBM SPSS for Windows version 28.0 was used to analyze the data. Spearman’s rank correlation was used to analyze the correlation between students’ satisfaction and self-confidence in learning. The significance level was set at p value less than 0.05. The results from this study have prompted the researchers to undertake a larger-scale evaluation, which is currently underway. The current results show that 70% of students agreed that the teaching methods used in the simulation were helpful and effective. The sessions are dependent on the learning materials that are provided and how the facilitators engage the students and make the session more enjoyable. The feedback provided inputs on the following areas to focus on while designing simulations for pre-clinical students. There are quality learning materials, an interactive environment, motivating content, skills and knowledge of the facilitator, and effective feedback.

Keywords: low-fidelity simulation, pre-clinical simulation, students satisfaction, self-confidence

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Authors: Vignesh Ratnaraj, Jaewon Chang

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Background: Frailty is associated with poorer outcomes in cardiac surgery, but the heterogeneity in frailty assessment tools makes it difficult to ascertain its true impact in cardiac surgery. Slow gait speed is a simple, validated, and reliable marker of frailty. We performed a systematic review and meta-analysis to examine the effect of slow gait speed on postoperative cardiac surgical patients. Methods: PubMED, MEDLINE, and EMBASE databases were searched from January 2000 to August 2021 for studies comparing slow gait speed and “normal” gait speed. The primary outcome was in-hospital mortality. Secondary outcomes were composite mortality and major morbidity, AKI, stroke, deep sternal wound infection, prolonged ventilation, discharge to a healthcare facility, and ICU length of stay. Results: There were seven eligible studies with 36,697 patients. Slow gait speed was associated with an increased likelihood of in-hospital mortality (risk ratio [RR]: 2.32; 95% confidence interval [CI]: 1.87–2.87). Additionally, they were more likely to suffer from composite mortality and major morbidity (RR: 1.52; 95% CI: 1.38–1.66), AKI (RR: 2.81; 95% CI: 1.44–5.49), deep sternal wound infection (RR: 1.77; 95% CI: 1.59–1.98), prolonged ventilation >24 h (RR: 1.97; 95% CI: 1.48–2.63), reoperation (RR: 1.38; 95% CI: 1.05–1.82), institutional discharge (RR: 2.08; 95% CI: 1.61–2.69), and longer ICU length of stay (MD: 21.69; 95% CI: 17.32–26.05). Conclusion: Slow gait speed is associated with poorer outcomes in cardiac surgery. Frail patients are twofold more likely to die during hospital admission than non-frail counterparts and are at an increased risk of developing various perioperative complications.

Keywords: cardiac surgery, gait speed, recovery, frailty

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Authors: Mahda Foroughi, Bruno de Anderade, Ana Pereira Roders

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Social media platforms have been increasingly used by locals and tourists to express their opinions about buildings, cities, and built heritage in particular. Most recently, scholars have been using social media to conduct innovative research on built heritage and heritage management. Still, the application of artificial intelligence (AI) methods to analyze social media data for heritage management is seldom explored. This paper investigates the potential of short texts (sentences and hashtags) shared through social media as a data source and artificial intelligence methods for data analysis for revealing the cultural significance (values and attributes) of built heritage. The city of Yazd, Iran, was taken as a case study, with a particular focus on windcatchers, key attributes conveying outstanding universal values, as inscribed on the UNESCO World Heritage List. This paper has three subsequent phases: 1) state of the art on the intersection of public participation in heritage management and social media research; 2) methodology of data collection and data analysis related to coding people's voices from Instagram and Twitter into values of windcatchers over the last ten-years; 3) preliminary findings on the comparison between opinions of locals and tourists, sentiment analysis, and its association with the values and attributes of windcatchers. Results indicate that the age value is recognized as the most important value by all interest groups, while the political value is the least acknowledged. Besides, the negative sentiments are scarcely reflected (e.g., critiques) in social media. Results confirm the potential of social media for heritage management in terms of (de)coding and measuring the cultural significance of built heritage for windcatchers in Yazd. The methodology developed in this paper can be applied to other attributes in Yazd and also to other case studies.

Keywords: social media, artificial intelligence, public participation, cultural significance, heritage, sentiment analysis

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Authors: Erin Lynne Plettenberg, Jeremy Vickery

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In an access-control situation, the role of a user determines whether a data request is appropriate. This paper combines vetted web mining and logic modeling to build a lightweight system for determining the role of a health care provider based only on their prior authorized requests. The model identifies provider roles with 100% recall from very little data. This shows the value of vetted web mining in AI systems, and suggests the impact of the ICD classification on medical practice.

Keywords: electronic medical records, information extraction, logic modeling, ontology, vetted web mining

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Authors: Hiba Naccache

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The present research investigated whether gender differences affect performance in a simple math quiz in statistics course. Participants of this study comprised a sample of 567 statistics students in two different universities in Lebanon. Data were collected through a simple math quiz. Analysis of quantitative data indicated that there wasn’t a significant difference in math performance between males and females. The results suggest that improvements in student performance may depend on improved mastery of basic algebra especially for females. The implications of these findings and further recommendations were discussed.

Keywords: gender, education, math, statistics

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Authors: David Nogueiras Blanco, Amir Alwash, Arnaud Gaudinat, René Schneider

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At a time when the access to and the sharing of information are crucial in the world of research, the use of technologies such as persistent identifiers (PIDs), Current Research Information Systems (CRIS), and ontologies may create platforms for information sharing if they respond to the need of disambiguation of their data by assuring interoperability inside and between other systems. INCIPIT-CRIS is a continuation of the former INCIPIT project, whose goal was to set up an infrastructure for a low-cost attribution of PIDs with high granularity based on Archival Resource Keys (ARKs). INCIPIT-CRIS can be interpreted as a logical consequence and propose a research information management system developed from scratch. The system has been created on and around the Schema.org ontology with a further articulation of the use of ARKs. It is thus built upon the infrastructure previously implemented (i.e., INCIPIT) in order to enhance the persistence of URIs. As a consequence, INCIPIT-CRIS aims to be the hinge between previously separated aspects such as CRIS, ontologies and PIDs in order to produce a powerful system allowing the resolution of disambiguation problems using a combination of an ontology such as Schema.org and unique persistent identifiers such as ARK, allowing the sharing of information through a dedicated platform, but also the interoperability of the system by representing the entirety of the data as RDF triplets. This paper aims to present the implemented solution as well as its simulation in real life. We will describe the underlying ideas and inspirations while going through the logic and the different functionalities implemented and their links with ARKs and Schema.org. Finally, we will discuss the tests performed with our project partner, the Swiss Institute of Bioinformatics (SIB), by the use of large and real-world data sets.

Keywords: current research information systems, linked data, ontologies, persistent identifier, schema.org, semantic web

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Authors: Thomas Trouton, Sebastian Tanner, Manvir Sandher

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The use of simulation in undergraduate and postgraduate medical curricula is ever-growing, is a useful addition to the traditional apprenticeship model of learning within medical education, and better prepares graduates for the team-based approach to healthcare seen in real-life clinical practice. As a learning tool, however, undergraduate medical students often have little understanding of the theory behind the use of medical simulation and have little experience in planning and delivering their own simulated teaching sessions. We designed and implemented a student-selected component (SSC) as part of the undergraduate medical curriculum at the University of Buckingham Medical School to introduce students to the concepts behind the use of medical simulation in education and allow them to plan and deliver their own simulated medical scenario to their peers. The SSC took place over a 2-week period in the 3rd year of the undergraduate course. There was a mix of lectures, seminars and interactive group work sessions, as well as hands-on experience in the simulation suite, to introduce key concepts related to medical simulation, including technical considerations in simulation, human factors, debriefing and troubleshooting scenarios. We evaluated the success of our SSC using “Net Promotor Scores” (NPS) to assess students’ confidence in planning and facilitating a simulation-based teaching session, as well as leading a debrief session. In all three domains, we showed an increase in the confidence of the students. We also showed an increase in confidence in the management of common medical emergencies as a result of the SSC. Overall, the students who chose our SSC had the opportunity to learn new skills in medical education, with a particular focus on the use of simulation-based teaching, and feedback highlighted that a number of students would take these skills forward in their own practice. We demonstrated an increase in confidence in several domains related to the use of medical simulation in education and have hopefully inspired a new generation of medical educators.

Keywords: simulation, SSC, teaching, medical students

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Authors: Muhammad Bilal Qadir, Danish Umer, Amir Shahzad

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The use of conductive materials in smart and interactive textiles is gaining significant importance for creating value addition, innovation, and functional product development. These products find their potential applications in health monitoring, military, protection, communication, sensing, monitoring, actuation, fashion, and lifestyles. The materials which are most commonly employed in such type of interactive textile include intrinsically conducting polymers, conductive inks, and metallic coating on textile fabrics and inherently conducting metallic fibre yarns. In this study, silver coated polyester filament yarn is explored for the development of multifunctional interactive gloves. The composite yarn was developed by covering the silver coated polyester filament around the polyester spun yarn using hollow spindle technique. The electrical and tensile properties of the yarn were studied. This novel yarn was used to manufacture a smart glove to explore the antibacterial, functional, and interactive properties of the yarn. The change in electrical resistance due to finger movement at different bending positions and antimicrobial properties were studied. This glove was also found useful as an interactive tool to operate the commonly used touch screen devices due to its conductive nature. The yarn can also be used to develop the sensing elements like stretch, strain, and piezoresistive sensors. Such sensor can be effectively used in medical and sports textile for performance monitoring, vital signs monitoring and development of antibacterial textile for healthcare and hygiene.

Keywords: conductive yarn, interactive textiles, piezoresistive sensors, smart gloves

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Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: Suriya

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Rapid socio-economic development and urbanization have led to an increasingly serious air pollution problem in Ulaanbaatar (UB), the capital of Mongolia. PM₂.₅ pollution has become the most pressing aspect of UB air pollution. Therefore, monitoring and predicting PM₂.₅ concentration in UB is of great significance for the health of the local people and environmental management. As of yet, very few studies have used models to predict PM₂.₅ concentrations in UB. Using data from 0:00 on June 1, 2018, to 23:00 on April 30, 2020, we proposed two deep learning models based on Bayesian-optimized LSTM (Bayes-LSTM) and CNN-LSTM. We utilized hourly observed data, including Himawari8 (H8) aerosol optical depth (AOD), meteorology, and PM₂.₅ concentration, as input for the prediction of PM₂.₅ concentrations. The correlation strengths between meteorology, AOD, and PM₂.₅ were analyzed using the gray correlation analysis method; the comparison of the performance improvement of the model by using the AOD input value was tested, and the performance of these models was evaluated using mean absolute error (MAE) and root mean square error (RMSE). The prediction accuracies of Bayes-LSTM and CNN-LSTM deep learning models were both improved when AOD was included as an input parameter. Improvement of the prediction accuracy of the CNN-LSTM model was particularly enhanced in the non-heating season; in the heating season, the prediction accuracy of the Bayes-LSTM model slightly improved, while the prediction accuracy of the CNN-LSTM model slightly decreased. We propose two novel deep learning models for PM₂.₅ concentration prediction in UB, Bayes-LSTM, and CNN-LSTM deep learning models. Pioneering the use of AOD data from H8 and demonstrating the inclusion of AOD input data improves the performance of our two proposed deep learning models.

Keywords: deep learning, AOD, PM2.5, prediction, Ulaanbaatar

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Authors: Majno Ajbani

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Difficulties in teaching and learning English pronunciation in Sindh province, Pakistan Abstract Sindhi language is widely spoken in Sindh province, and it is one of the difficult languages of the world. Sindhi language has fifty-two alphabets which have caused a serious issue in learning and teaching of English pronunciation for teachers and students of Colleges and Universities. This study focuses on teachers’ and students’ need for extensive training in the pronunciation that articulates the real pronunciation of actual words. The study is set to contribute in the sociolinguistic studies of English learning communities in this region. Data from 200 English teachers and students was collected by already tested structured questionnaire. The data was analysed using SPSS 20 software. The data analysis clearly demonstrates the higher range of inappropriate pronunciations towards English learning and teaching. The anthropogenic responses indicate 87 percentages teachers and students had an improper pronunciation. This indicates the substantial negative effects on academic and sociolinguistic aspects. It is suggested an improper speaking of English, based on rapid changes in geopolitical and sociocultural surroundings.

Keywords: alphabets, pronunciation, sociolinguistic, anthropogenic, imprudent, malapropos

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