Search results for: data center

Authors: Suzan Arslanturk, Mohammad-Reza Siadat, Theophilus Ogunyemi, Ananias Diokno

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Missing data is a common challenge in statistical analyses of most clinical survey datasets. A variety of methods have been developed to enable analysis of survey data to deal with missing values. Imputation is the most commonly used among the above methods. However, in order to minimize the bias introduced due to imputation, one must choose the right imputation technique and apply it to the correct type of missing data. In this paper, we have identified different types of missing values: missing data due to skip pattern (SPMD), undetermined missing data (UMD), and genuine missing data (GMD) and applied rough set imputation on only the GMD portion of the missing data. We have used rough set imputation to evaluate the effect of such imputation on prediction by generating several simulation datasets based on an existing epidemiological dataset (MESA). To measure how well each dataset lends itself to the prediction model (logistic regression), we have used p-values from the Wald test. To evaluate the accuracy of the prediction, we have considered the width of 95% confidence interval for the probability of incontinence. Both imputed and non-imputed simulation datasets were fit to the prediction model, and they both turned out to be significant (p-value < 0.05). However, the Wald score shows a better fit for the imputed compared to non-imputed datasets (28.7 vs. 23.4). The average confidence interval width was decreased by 10.4% when the imputed dataset was used, meaning higher precision. The results show that using the rough set method for missing data imputation on GMD data improve the predictive capability of the logistic regression. Further studies are required to generalize this conclusion to other clinical survey datasets.

Keywords: rough set, imputation, clinical survey data simulation, genuine missing data, predictive index

Procedia PDF Downloads 168

Authors: Vibha Kriti

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Background: Polycystic ovary syndrome (PCOS) is a common endocrine disorder generally found in reproductive women. It is associated with significant reproductive, metabolic, cosmetic, and psychological consequences. Objective: There is a high prevalence of PCOS found among reproductive-age women, therefore, the major objective of the present study is to identify the illness perception of PCOS women and to explore the relationship between illness perception and health-related quality of life (HRQoL). Material and Method: A cross-sectional study was conducted in a university tertiary-care center, Sir Sunder Lal Hospital, Banaras Hindu University (B.H.U). Tools used for data collection were self-structured, which included socio-demographic status, illness perception questionnaire (revised version), and short-form 36 for assessing illness perception and health-related quality of life, respectively. Statistical analysis was done by SPSS version ‘24’. Results: The results of correlation analyses indicated that there is a strong relationship between strong illness perception and HRQoL. Stepwise regression indicated that illness identity, long illness duration, and severe consequences were associated with the worse outcome on emotional functioning and on social functioning. A high score on the controllability of the disease and seeking social support was significantly related to better functioning. Conclusion: Illness perception is an important factor in self-care behaviors in PCOS females and has a strong association with health-related quality of life and has a profound effect on it.

Keywords: polycystic ovary syndrome, illness perception, quality of life, young females, mental health

Procedia PDF Downloads 93

Authors: Srivatsav Sanjay Sridhar, Asvitha Raja, Prathit Kalra, Soni Gupta

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Database management is a system that keeps track of details about a person in an organisation. Not a lot of orphanages these days are shifting to a computer and program-based system, but unfortunately, most have only pen and paper-based records, which not only consumes space but it is also not eco-friendly. It comes as a hassle when one has to view a record of a person as they have to search through multiple records, and it will consume time. This program will organise all the data and can pull out any information about anyone whose data is entered. This is also a safe way of storage as physical data gets degraded over time or, worse, destroyed due to natural disasters. In this developing world, it is only smart enough to shift all data to an electronic-based storage system. The program comes with all features, including creating, inserting, searching, and deleting the data, as well as printing them.

Keywords: database, orphans, programming, C⁺⁺

Procedia PDF Downloads 157

Authors: Ki Woong Lee

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The Center for Axion and Precision Physics Research is studying the search for dark matter using 12 tesla superconducting magnets. A dilution refrigerator is being used for search experiments, and superconducting magnets, superconducting cavities. The dilution refrigerator requires a stable cryogenic environment using liquid helium. Accordingly, a cryogenic system for a stable supply of liquid helium is to be established. This cryogenic system includes the liquefying, supply, storage, and purification of liquid helium. This article presents the basic design, construction, and operation plans for building cryogenic systems.

Keywords: cryogenic system, dilution refrigerator, superconducting magnet, helium recovery system

Procedia PDF Downloads 121

Authors: Abdulrahman Algaeed

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The Ophthalmic Ultrasound is the easiest method of early diagnosing Retinoblastoma after clinical examination. It can be done with ease without sedation. King Khaled Eye Specialist Hospital is a tertiary care center where Retinoblastoma patients are often seen and treated there. The first modality to rule out the disease is Ophthalmic Ultrasound. Classic Retinoblastoma is easily diagnosed by using the conventional 10MHz Ophthalmic Ultrasound probe in the regular clinic setup. Retinal lesion with multiple, very highly reflective surfaces within lesion typical of Calcium deposits. The use of Standardized A-scan is very useful where internal reflectivity is classified as very highly reflective. Color Doppler is extremely useful as well to show the blood flow within lesion/s. In conclusion: Ophthalmic Ultrasound should be the first tool to be used to diagnose Retinoblastoma after clinical examination. The accuracy of the Exam is very high.

Keywords: doppler, retinoblastoma, reflectivity, ultrasound

Procedia PDF Downloads 113

Authors: Marwa Hussein Mohamed, Mohamed Helmy Khafagy, Samah Ahmed Senbel

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Map Reduce is a programming model used to handle and support massive data sets. Rapidly increasing in data size and big data are the most important issue today to make an analysis of this data. map reduce is used to analyze data and get more helpful information by using two simple functions map and reduce it's only written by the programmer, and it includes load balancing , fault tolerance and high scalability. The most important operation in data analysis are join, but map reduce is not directly support join. This paper explains two-way map-reduce join algorithm, semi-join and per split semi-join, and proposes new algorithm hash semi-join that used hash table to increase performance by eliminating unused records as early as possible and apply join using hash table rather than using map function to match join key with other data table in the second phase but using hash tables isn't affecting on memory size because we only save matched records from the second table only. Our experimental result shows that using a hash table with hash semi-join algorithm has higher performance than two other algorithms while increasing the data size from 10 million records to 500 million and running time are increased according to the size of joined records between two tables.

Keywords: map reduce, hadoop, semi join, two way join

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Authors: Slah Alsaleh

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In the recent years and with popularity of internet and technology, e-learning became a major part of majority of education systems. One of the advantages the e-learning systems provide is the large amount of information available about the students' behavior while communicating with the e-learning system. Such information is very rich and it can be used to improve the capability and efficiency of e-learning systems. This paper discusses how e-learning can benefit from implicit data in different ways including; creating homogeneous groups of student, evaluating students' learning, creating behavior profiles for students and identifying the students through their behaviors.

Keywords: e-learning, implicit data, user behavior, data mining

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Authors: Ilija Plecas, Dalibor Arbutina

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The leaching rate of 60Co from spent mix bead (anion and cation) exchange resins in a cement-bentonite matrix has been studied. Transport phenomena involved in the leaching of a radioactive material from a cement-bentonite matrix are investigated using three methods based on theoretical equations. These are: the diffusion equation for a plane source, an equation for diffusion coupled to a first order equation and an empirical method employing a polynomial equation. The results presented in this paper are from a 25-year mortar and concrete testing project that will influence the design choices for radioactive waste packaging for a future Serbian radioactive waste disposal center.

Keywords: cement, concrete, immobilization, leaching, permeability, radioactivity, waste

Procedia PDF Downloads 323

Authors: Changfeng Fu

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Sustainable urban development has been widely accepted a common sense in the modern urban planning and design. However, the measurement and assessment of urban sustainability, especially the quantitative assessment have been always an issue obsessing planning and design professionals. This paper will present an on-going research on the principles and technologies to develop a quantitative urban sustainability assessment principles and techniques which aim to integrate indicators, geospatial and geo-reference data, and assessment techniques together into a mechanism. It is based on the principles and techniques of geospatial analysis with GIS and statistical analysis methods. The decision-making technologies and methods such as AHP and SMART are also adopted to address overall assessment conclusions. The possible interfaces and presentation of data and quantitative assessment results are also described. This research is based on the knowledge, situations and data sources of UK, but it is potentially adaptable to other countries or regions. The implementation potentials of the mechanism are also discussed.

Keywords: urban sustainability assessment, quantitative analysis, sustainability indicator, geospatial data, big data

Procedia PDF Downloads 359

Authors: Lilian Ijomah

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Restorative justice practices continue to gain recognition globally in the criminal and juvenile justice systems and schools. Despite considerable research, little is known about how juvenile detention center staff members’ knowledge, beliefs, and attitudes affect implementation. As with many interventions, effective implementation relies on the staff members who must do the daily work. This phenomenological study aimed to add to the existing literature by examining staff knowledge, beliefs, and attitudes on restorative justice practices, barriers to effective implementation, and potential differences in knowledge, beliefs, and attitudes between education staff and juvenile detention officers at the research site. The present study used semi-structured interviews and focus groups of both types of staff members who work with the youth in a juvenile justice facility to answer three research questions: (1) To what extent are staff members knowledgeable about the principles behind restorative approach to discipline and about how the approach should be carried out?; (2) What are staff member beliefs and attitudes toward the restorative justice program and its implementation in a juvenile justice setting?; and (3) What similarities and differences are there between (a) knowledge and (b) beliefs and attitudes of the educators and juvenile detention officers? A total of 28 staff members participated, nine educators, and 19 detention officers. The findings for the first research question indicated that both groups (educators and juvenile detention officers) were knowledgeable about two of the three principles of restorative justice: repairing the harm done by the offender and reducing risks for future occurrence; but did not show clear knowledge of one principle, active involvement from all stakeholders. For research question 2, staff beliefs and attitudes were categorized into two types, positive beliefs and attitudes (e.g., that restorative justice is more appropriate than the use of punitive measures) and negative beliefs and attitudes (e.g., that restorative justice is ‘just another program that creates extra work for staff’). When the two staff groups were compared to answer research question 3, both groups were found to have similar knowledge (showing knowledge of two of the three principles) and somewhat different beliefs and attitudes – both groups showed a mix of positive and negative, but the educators showed somewhat more on the positive side. Both groups also identified barriers to implementation such as the perception of restorative justice as ‘soft’, lack of knowledge and exposure to restorative justice, shortage of resources and staff, and difficulty sustaining the restorative justice approach. The findings of this study are largely consistent with current literature but also extend the literature by studying staff knowledge, attitudes, and beliefs in a juvenile detention center and comparing the two staff groups. Recommendations include assessing staff knowledge and attitudes toward restorative justice during the hiring process, ensuring adequate staff training, communicating clearly to build positive attitudes and beliefs, providing adequate staffing, and building a sense of community.

Keywords: juvenile justice, restorative justice, restorative practices, staff attitudes and beliefs

Procedia PDF Downloads 134

Authors: A. Ishag Mohamed, A. A. Rabah

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The objective of this research is to develop a generalized correlation for the prediction of thermal conductivity of n-Alkanes and Alkenes. There is a minority of research and lack of correlation for thermal conductivity of liquids in the open literature. The available experimental data are collected covering the groups of n-Alkanes and Alkenes.The data were assumed to correlate to temperature using Filippov correlation. Nonparametric regression of Grace Algorithm was used to develop the generalized correlation model. A spread sheet program based on Microsoft Excel was used to plot and calculate the value of the coefficients. The results obtained were compared with the data that found in Perry's Chemical Engineering Hand Book. The experimental data correlated to the temperature ranged "between" 273.15 to 673.15 K, with R2 = 0.99.The developed correlation reproduced experimental data that which were not included in regression with absolute average percent deviation (AAPD) of less than 7 %. Thus the spread sheet was quite accurate which produces reliable data.

Keywords: N-Alkanes, N-Alkenes, nonparametric, regression

Procedia PDF Downloads 654

Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

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Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: big data, social networks, sentiment analysis, twitter

Procedia PDF Downloads 576

Authors: A. Nurgiartiningsih, G. Ciptadi, S. B. Siswijono

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This research was done to identify the performance and breeding potency of Local Buffalo in Kangean Island, Sumenep, East Java, Indonesia. Materials used were buffalo and farmer in Kangean Island. Method used was survey with purposive sampling method. Qualitative trait and existing breeding system including the type of production system were directly observed. Quantitative trait consisted of chest girth, body weight and wither height were measured and recorded. Data were analyzed using analysis of variance applying software GENSTAT 14. Results showed the purposes of buffalo breeding in Kangean Island were for production of calves, saving, religion tradition, and buffalo racing. The combination between grazing and cut and carry system were applied in Kangean Island. Forage, grass and agricultural waste product were available abundantly especially, during the wet season. Buffalo in Kangean Island was categorized as swamp buffalo with 48 chromosomes. Observation on qualitative trait indicated that there were three skin color types: gray (81.25%), red (10.42%) and white/albino (8.33%). Analysis on quantitative trait showed that there was no significant difference between male and female buffalo. The performance of male buffalo was 132.56 cm, 119.33 cm and 174.11 cm, for the mean of body length, whither height and chest girth, respectively. The performance of female buffalo were 129.8 cm, 114.0 cm and 166.2 cm, for mean of body length, wither height and chest girth (CG), respectively. The performance of local buffalo in Kangean Island was categorized well. Kangean Island could be promoted as center of buffalo breeding and conservation. For optimal improvement of population number and its genetics value, government policy in buffalo breeding program should be implemented.

Keywords: chromosome, qualitative trait, quantitative trait, swamp buffalo

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Authors: Ladislav Kristoufek, Helen Susannah Moat, Tobias Preis

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Data on the number of people who have committed suicide tends to be reported with a substantial time lag of around two years. We examine whether online activity measured by Google searches can help us improve estimates of the number of suicide occurrences in England before official figures are released. Specifically, we analyse how data on the number of Google searches for the terms “depression” and “suicide” relate to the number of suicides between 2004 and 2013. We find that estimates drawing on Google data are significantly better than estimates using previous suicide data alone. We show that a greater number of searches for the term “depression” is related to fewer suicides, whereas a greater number of searches for the term “suicide” is related to more suicides. Data on suicide related search behaviour can be used to improve current estimates of the number of suicide occurrences.

Keywords: nowcasting, search data, Google Trends, official statistics

Procedia PDF Downloads 357

Authors: Amenah Galo, Mohammed Farid, Kareem Alsharkawy, Robert Warner, Karthikeyan Srinivasan, Haitham Khalil, Ruth Waters

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Introduction: The cessation of elective surgery, particularly breast reconstruction, continue to be affected by the COVID-19 pandemic. The restructuring of medical services and staff redeployment severely affected the ability to return to normality for surgical specialties. The aim of this study is to determine the decline in breast reconstruction affected by the COVID-19 pandemic in a tertiary center. Methods: A retrospective review of breast reconstruction cases (autologous, non-autologous) or mastectomies Pre- COVID (March 2019-March 2020) and during COVID (March 2020- March 2021) at Queen Elizabeth Hospital, Birmingham, were collated. Data included patient demographics, BMI, previous and recent reconstruction, length of hospital stay, and mastectomies, including risk-reducing. Results: The number of patients who had breast reconstruction was significantly lower during COVID (n=62) compared to pre-COVID (n=199). The mean age (pre-COVID 51, COVID 59 years), BMI (Pre-COVID and COVID = 27), previous reconstruction (pre-COVID n=101, 51%, COVID n=33, 53%) and length hospital stay was less during COVID (3 days) compared to Pre-COVID (4 days). The proportion of risk-reducing mastectomies and reconstruction during COVID (32%, n=20) were higher than pre-COVID (21%, n=41). A higher proportion rate of autologous reconstruction (DIEP 56, TRAM 17) Pre-COVID compared to COVID (DIEP 22, TRAM 7). Implant reconstructions were higher during COVID (n=19, 31%) than pre-COVID (n=31, 16%). Conclusion: The lack of regular provision for breast reconstruction continues to decline during the pandemic. This will have a tremendous impact on waiting lists without a timeline for reconstruction to offer patients. An international survey highlights the disparities in offering breast reconstruction and strategies to rectify this issue.

Keywords: breast reconstruction, COVID-19 pandemic, mastectomy, autologous, implant

Procedia PDF Downloads 221

Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

Procedia PDF Downloads 475

Authors: Pallavi Singh

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Developing library knowledge centres involves transforming traditional library spaces into dynamic, interactive environments that support collaborative learning, digital literacy, and access to various resources. Knowledge centres, also known as knowledge hubs or centres of excellence, play a crucial role in organizations and communities by serving as repositories of expertise and information. The Energy and Resources Institute (TERI) is a research organisation dedicated to sustainable community solutions. TERI Knowledge Resource Center is also aligned with the objective of the host organization within TERI; there are several specialized knowledge centers dedicated to various aspects of sustainability, energy, climate change, environmental management, green mobility, etc.

Keywords: knowledge centres, environmental management, green mobility, energy

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Authors: Rinat Gabbay-Benziv, Merav Ben-Natan, Ariel Roguin, Benyamine Abbou, Anna Ofir, Adi Klein, Dikla Dahan-Shriki, Mordechai Hallak, Boris Kessel, Mickey Dudkiewicz

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Introduction: Over recent decades, technology has become integral to healthcare, with electronic health records and advanced medical equipment now standard. However, this reliance has made healthcare systems increasingly vulnerable to ransomware attacks. On October 13, 2021, Hillel Yaffe Medical Center experienced a severe ransomware attack that disrupted all IT systems, including electronic health records, laboratory services, and staff communications. The attack, carried out by the group DeepBlueMagic, utilized advanced encryption to lock the hospital's systems and demanded a ransom. This incident caused significant operational and patient care challenges, particularly impacting the obstetrics department. Objective: The objective is to describe the challenges facing the obstetric division following a cyberattack and discuss ways of preparing for and overcoming another one. Methods: A retrospective descriptive study was conducted in a mid-sized medical center. Division activities, including the number of deliveries, cesarean sections, emergency room visits, admissions, maternal-fetal medicine department occupancy, and ambulatory encounters, from 2 weeks before the attack to 8 weeks following it (a total of 11 weeks), were compared with the retrospective period in 2019 (pre-COVID-19). In addition, we present the challenges and adaptation measures taken at the division and hospital levels leading up to the resumption of full division activity. Results: On the day of the cyberattack, critical decisions were made. The media announced the event, calling on patients not to come to our hospital. Also, all elective activities other than cesarean deliveries were stopped. The number of deliveries, admissions, and both emergency room and ambulatory clinic visits decreased by 5%–10% overall for 11 weeks, reflecting the decrease in division activity. Nevertheless, in all stations, there were sufficient activities and adaptation measures to ensure patient safety, decision-making, and workflow of patients were accounted for. Conclusions: The risk of ransomware cyberattacks is growing. Healthcare systems at all levels should recognize this threat and have protocols for dealing with them once they occur.

Keywords: ransomware attack, healthcare cybersecurity, obstetrics challenges, IT system disruption

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Authors: Rahma Saleh Hussein Al Balushi

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Oman Electricity Transmission Company's (OETC) vision is to be a renowned world-class transmission grid by 2025, and one of the indications of achieving the vision is obtaining Asset Management ISO55001 certification, which required setting out a documented Standard Operating Procedures (SOP). Hence, documented SOP for the Geographical information system data process has been established. Also, to effectively manage and improve OETC power transmission, asset data and information need to be governed as such by Asset Information & GIS department. This paper will describe in detail the current GIS data submission process and the journey for developing it. The methodology used to develop the process is based on three main pillars, which are system and end-user requirements, Risk evaluation, data availability, and accuracy. The output of this paper shows the dramatic change in the used process, which results subsequently in more efficient, accurate, and updated data. Furthermore, due to this process, GIS has been and is ready to be integrated with other systems as well as the source of data for all OETC users. Some decisions related to issuing No objection certificates (NOC) for excavation permits and scheduling asset maintenance plans in Computerized Maintenance Management System (CMMS) have been made consequently upon GIS data availability. On the Other hand, defining agreed and documented procedures for data collection, data systems update, data release/reporting and data alterations has also contributed to reducing the missing attributes and enhance data quality index of GIS transmission data. A considerable difference in Geodatabase (GDB) completeness percentage was observed between the years 2017 and year 2022. Overall, concluding that by governance, asset information & GIS department can control the GIS data process; collect, properly record, and manage asset data and information within the OETC network. This control extends to other applications and systems integrated with/related to GIS systems.

Keywords: asset management ISO55001, standard procedures process, governance, CMMS

Procedia PDF Downloads 125

Authors: Sajid Abas, Jon Pyo Hong, Jung-Ryun Le, Seungryong Cho

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Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.

Keywords: computed tomography, computed laminography, compressive sending, low-dose

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Authors: Ram Sharan Mehta, Sanjeev Sharma

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Introduction: Haemodialysis (HD) is a mechanical process of removing waste products from the blood and replacing essential substances in patients with renal failure. First artificial kidney developed in Netherlands in 1943 AD First successful treatment of CRF reported in 1960AD, life-saving treatment begins for CRF in 1972 AD. In 1973 AD Medicare took over financial responsibility for many clients and after that method become popular. BP Koirala institute of health science is the only center outside the Kathmandu, where HD service is available. In BPKIHS PD started in Jan.1998, HD started in August 2002 till September 2003 about 278 patients received HD. Day by day the number of HD patients is increasing in BPKIHS as with institutional growth. No such type of study was conducted in past hence there is lack of valid & reliable baseline data. Hence, the investigators were interested to conduct the study on " Profile of the Renal Failure patients under Haemodialysis at B.P. Koirala Institute of Health Sciences Nepal". Objectives: The objectives of the study were: to find out the Socio-demographic characteristics of the patients, to explore the knowledge of the patients regarding disease process and Haemodialysis and to identify the problems encountered by the patients. Methods: It is a hospital-based exploratory study. The population of the study was the clients under HD and the sampling method was purposive. Fifty-four patients undergone HD during the period of 17 July 2012 to 16 July 2013 of complete one year were included in the study. Structured interview schedule was used for collect data after obtaining validity and reliability. Results: Total 54 subjects had undergone for HD, having age range of 5-75 years and majority of them were male (74%) and Hindu (93 %). Thirty-one percent illiterate, 28% had agriculture their occupation, 80% of them were from very poor community, and about 30% subjects were unaware about the disease they suffering. Majority of subjects reported that they had no complications during dialysis (61%), where as 20% reported nausea and vomiting, 9% Hypotension, 4% headache and 2%chest pain during dialysis. Conclusions: CRF leading to HD is a long battle for patients, required to make major and continuous adjustment, both physiologically and psychologically. The study suggests that non-compliance with HD regimen were common. The socio-demographic and knowledge profile will help in the management and early prevention of disease and evaluate aspects that will influence care and patients can select mode of treatment themselves properly.

Keywords: profile, haemodialysis, Nepal, patients, treatment

Procedia PDF Downloads 375

Authors: Tri Wijayanti Septiarini, Agus Maman Abadi, Muhammad Rifki Taufik

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The exchange rate of IDR/USD can be the indicator to analysis Indonesian economy. The exchange rate as a important factor because it has big effect in Indonesian economy overall. So, it needs the analysis data of exchange rate. There is decomposition data of exchange rate of IDR/USD to be frequency and time. It can help the government to monitor the Indonesian economy. This method is very effective to identify the case, have high accurate result and have simple structure. In this paper, data of exchange rate that used is weekly data from December 17, 2010 until November 11, 2014.

Keywords: the exchange rate, fuzzy mamdani, discrete wavelet transforms, fuzzy wavelet

Procedia PDF Downloads 571

Authors: Durhane Wong-Rieger, Kawaldip Sehmi, Nicola Bedlington, Nicole Boice, Tamás Bereczky

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Patient-generated health data should be seen as the expression of the experience of patients, including the outcomes reflecting the impact a treatment or service had on their physical health and wellness. We discuss how the healthcare system can reach a place where digital is a determinant of health - where data is generated by patients and is respected and which acknowledges their contribution to science. We explore the biggest barriers facing this. The International Experience Exchange with Patient Organisation’s Position Paper is based on a global patient survey conducted in Q3 2021 that received 304 responses. Results were discussed and validated by the 15 patient experts and supplemented with literature research. Results are a subset of this. Our research showed patient communities want to influence how their data is generated, shared, and used. Our study concludes that a reasonable framework is needed to protect the integrity of patient data and minimise abuse, and build trust. Results also demonstrated a need for patient communities to have more influence and control over how health data is generated, shared, and used. The results clearly highlight that the community feels there is a lack of clear policies on sharing data.

Keywords: digital health, equitable access, humanise healthcare, patient data

Procedia PDF Downloads 82

Authors: Bruno Pinto Vieira, Marco Antonio Calijorne Soares, Armando Sérgio de Aguiar Filho

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Nowadays, a massive amount of information has been produced by different data sources, including mobile devices and transactional systems. In this scenario, concerns arise on how to maintain or establish data quality, which is now treated as a product to be defined, measured, analyzed, and improved to meet consumers' needs, which is the one who uses these data in decision making and companies strategies. Information that reaches low levels of quality can lead to issues that can consume time and money, such as missed business opportunities, inadequate decisions, and bad risk management actions. The step of selecting, identifying, evaluating, and selecting data sources with significant quality according to the need has become a costly task for users since the sources do not provide information about their quality. Traditional data quality control methods are based on user experience or business rules limiting performance and slowing down the process with less than desirable accuracy. Using advanced machine learning algorithms, it is possible to take advantage of computational resources to overcome challenges and add value to companies and users. In this study, machine learning is applied to data quality analysis on different datasets, seeking to compare the performance of the techniques according to the dimensions of quality assessment. As a result, we could create a ranking of approaches used, besides a system that is able to carry out automatically, data quality assessment.

Keywords: machine learning, data quality, quality dimension, quality assessment

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Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

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In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

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Authors: Fawzia Al-Sakeer, Hassan Aldeeb

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Development in the communications field is proceeding at an amazing speed, which has led researchers to improve and develop electronic circuits by increasing their efficiency and reducing their size to reduce the weight of electronic devices. One of the most important of these circuits is the band-pass filter, which is what made us carry out this research, which aims to use an alternate technology to design a dual band-pass filter by using a stepped impedance microstrip transmission line. We designed a filter that works at two center frequency bands by designing with the ADS program, and the results were excellent, as we obtained the two design frequencies, which are 1 and 3GHz, and the values of insertion loss S11, which was more than 21dB with a small area.

Keywords: band pass filter, dual band band-pass filter, ADS, microstrip filter, stepped impedance

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Authors: S. S. Nafee, A. M. Al-Ramady, S. A. Shaheen

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Evaluated nuclear decay data for the 217Po nuclide ispresented in the present work. These data include recommended values for the half-life T1/2, α-, β--, and γ-ray emission energies and probabilities. Decay data from 221Rn α and 217Bi β—decays are presented. Q(α) has been updated based on the recent published work of the Atomic Mass Evaluation AME2012. In addition, the logft values were calculated using the Logft program from the ENSDF evaluation package. Moreover, the total internal conversion electrons has been calculated using Bricc program. Meanwhile, recommendation values or the multi-polarities have been assigned based on recently measurement yield a better intensity balance at the 254 keV and 264 keV gamma transitions.

Keywords: nuclear decay data evaluation, mass evaluation, total converison coefficients, atomic mass evaluation

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Authors: I. Nyoman Mahayasa Adiputra

Abstract:

Data in the field of health can be useful for the purposes of data analysis, one example of health data is disease data. Disease data is usually in a geographical plot in accordance with the area. Where the data was collected, in the city of Denpasar, Bali. Disease data report is still published in tabular form, disease information has not been mapped in GIS form. In this research, disease information in Denpasar city will be digitized in the form of a geographic information system with the smallest administrative area in the form of district. Denpasar City consists of 4 districts of North Denpasar, East Denpasar, West Denpasar and South Denpasar. In this research, we use Google fusion table technology for map digitization process, where this technology can facilitate from the administrator and from the recipient information. From the administrator side of the input disease, data can be done easily and quickly. From the receiving end of the information, the resulting GIS application can be published in a website-based application so that it can be accessed anywhere and anytime. In general, the results obtained in this study, divided into two, namely: (1) Geolocation of Denpasar and all of Denpasar districts, the process of digitizing the map of Denpasar city produces a polygon geolocation of each - district of Denpasar city. These results can be utilized in subsequent GIS studies if you want to use the same administrative area. (2) Dengue fever mapping in 2014 and 2015. Disease data used in this study is dengue fever case data taken in 2014 and 2015. Data taken from the profile report Denpasar Health Department 2015 and 2016. This mapping can be useful for the analysis of the spread of dengue hemorrhagic fever in the city of Denpasar.

Keywords: geographic information system, Google fusion table technology, delivery of disease data information, Denpasar city

Procedia PDF Downloads 129

Authors: Mitzi S. Brammer

Abstract:

Given that the cultural make-up of programs of study in institutions of higher learning is becoming increasingly diverse, much has been written about cultural diversity from a university-level perspective. However, there are little data in the way of specific programs and how they address inclusive practices when teaching and working with marginalized populations. This research study aimed to discover baseline knowledge and attitudes of health sciences faculty, instructional staff, and students related to inclusive teaching/learning and interactions. Quantitative data were collected via an anonymous online survey (one designed for students and another designed for faculty/instructional staff) using a web-based program called Qualtrics. Quantitative data were analyzed amongst the faculty/instructional staff and students, respectively, using descriptive and comparative statistics (t-tests). Additionally, some participants voluntarily engaged in a focus group discussion in which qualitative data were collected around these same variables. Collecting qualitative data to triangulate the quantitative data added trustworthiness to the overall data. The research team analyzed collected data and compared identified categories and trends, comparing those data between faculty/staff and students, and reported results as well as implications for future study and professional practice.

Keywords: inclusion, higher education, pedagogy, equity, diversity

Procedia PDF Downloads 67

Authors: J. Suneetha, Vijayalaxmi

Abstract:

Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

Procedia PDF Downloads 344