Search results for: incomplete count data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25165

Search results for: incomplete count data

24205 Interpretation of Two Indices for the Prediction of Cardiovascular Risk in Pediatric Obesity

Authors: Mustafa M. Donma, Orkide Donma

Abstract:

Obesity and weight gain are associated with increased risk of developing cardiovascular diseases and the progression of liver fibrosis. Aspartate transaminase–to-platelet count ratio index (AST-to-PLT, APRI) and fibrosis-4 (FIB-4) were primarily considered as the formulas capable of differentiating hepatitis from cirrhosis. Recently, they have found clinical use as measures of liver fibrosis and cardiovascular risk. However, their status in children has not been evaluated in detail yet. The aim of this study is to determine APRI and FIB-4 status in obese (OB) children and compare them with values found in children with normal body mass index (N-BMI). A total of sixty-eight children examined in the outpatient clinics of the Pediatrics Department in Tekirdag Namik Kemal University Medical Faculty were included in the study. Two groups were constituted. In the first group, thirty-five children with N-BMI, whose age- and sex-dependent BMI indices vary between 15 and 85 percentiles, were evaluated. The second group comprised thirty-three OB children whose BMI percentile values were between 95 and 99. Anthropometric measurements and routine biochemical tests were performed. Using these parameters, values for the related indices, BMI, APRI, and FIB-4, were calculated. Appropriate statistical tests were used for the evaluation of the study data. The statistical significance degree was accepted as p<0.05. In the OB group, values found for APRI and FIB-4 were higher than those calculated for the N-BMI group. However, there was no statistically significant difference between the N-BMI and OB groups in terms of APRI and FIB-4. A similar pattern was detected for triglyceride (TRG) values. The correlation coefficient and degree of significance between APRI and FIB-4 were r=0.336 and p=0.065 in the N-BMI group. On the other hand, they were r=0.707 and p=0.001 in the OB group. Associations of these two indices with TRG have shown that this parameter was strongly correlated (p<0.001) both with APRI and FIB-4 in the OB group, whereas no correlation was calculated in children with N-BMI. Triglycerides are associated with an increased risk of fatty liver, which can progress to severe clinical problems such as steatohepatitis, which can lead to liver fibrosis. Triglycerides are also independent risk factors for cardiovascular disease. In conclusion, the lack of correlation between TRG and APRI as well as FIB-4 in children with N-BMI, along with the detection of strong correlations of TRG with these indices in OB children, was the indicator of the possible onset of the tendency towards the development of fatty liver in OB children. This finding also pointed out the potential risk for cardiovascular pathologies in OB children. The nature of the difference between APRI vs FIB-4 correlations in N-BMI and OB groups (no correlation versus high correlation), respectively, may be the indicator of the importance of involving age and alanine transaminase parameters in addition to AST and PLT in the formula designed for FIB-4.

Keywords: APRI, children, FIB-4, obesity, triglycerides

Procedia PDF Downloads 339
24204 Haemoperitoneum in a Case of Dengue Fever

Authors: Sagarjyoti Roy

Abstract:

Dengue is an arboviral infection, belonging to family flaviviridae, comprising of four serotypes; DENV1, DENV2, DENV3 and DENV4. All four serotypes are capable of causing full-spectrum of clinical features, ranging from self-limiting fever to severe dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS). Complications may affect any organ system, including those involving gastrointestinal system and serositis. We report a case, of a 28 years, non-alcoholic male, presenting with a 7 day history of fever and malaise followed by abdominal pain and distension, from 4th day of fever. He was admitted in medicine department of RG KAR medical college hospital. Dengue fever was confirmed by NS1 and dengue IgM positivity. Platelet count was 30,000/cc (1.5- 4 lac/cc) and haematocrit was 52% (38- 50% for men). Clinicoradiological findings revealed bilateral pleural effusion, ascites and splenomegaly. Ascitic fluid was hemorrhagic in nature, with a high protein and RBC content. Liver function tests revealed mild transaminitis with normal coagulation profile. Patient was managed conservatively. A diagnosis of dengue fever complicated by serositis and spontaneous haemoperitoneum was made. The symptoms subsided after a hospital stay of 10 days. The case highlights haemorrhage into peritoneal cavity as a possible complication of dengue fever. Although a definite explanation requires more detailed studies, platelet or endothelial cell dysfunction might be contributory.

Keywords: ascites, dengue, haemoperitoneum, serositis

Procedia PDF Downloads 252
24203 On the Network Packet Loss Tolerance of SVM Based Activity Recognition

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

Abstract:

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 464
24202 GIS Data Governance: GIS Data Submission Process for Build-in Project, Replacement Project at Oman electricity Transmission Company

Authors: Rahma Saleh Hussein Al Balushi

Abstract:

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 113
24201 Efects of Data Corelation in a Sparse-View Compresive Sensing Based Image Reconstruction

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

Abstract:

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

Procedia PDF Downloads 457
24200 Fuzzy Wavelet Model to Forecast the Exchange Rate of IDR/USD

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

Abstract:

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 551
24199 Humanising Digital Healthcare to Build Capacity by Harnessing the Power of Patient Data

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

Abstract:

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 71
24198 Use of Machine Learning in Data Quality Assessment

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

Abstract:

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

Procedia PDF Downloads 138
24197 Exploring Data Leakage in EEG Based Brain-Computer Interfaces: Overfitting Challenges

Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

Abstract:

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

Procedia PDF Downloads 144
24196 Increasing Redness and Microbial Stability of Low Nitrite Chicken Sausage by Encapsulated Tomato Pomace Extract

Authors: Bung-Orn Hemung, Nachayut Chanshotigul, Koo Bok Chin

Abstract:

Tomato pomace (TP) is the waste from tomato processing plants and its utilization as food ingredient may provide sustainable industry by reducing waste. TP was extracted by ethanol using microwave-assisted method at 180W for 90s. The ethanol was evaporated out, and an extract was encapsulated with maltodextrin (1:10) by spray drying to obtain an encapsulated TP extract (ETPE). The redness (a value) of ETPE powder was 6.5±0.05, and it was used as natural ingredient in the low-nitrite chicken sausage. Chicken emulsion sausage was prepared at 25 mg/kg of nitrite for being control. Effect of ETPE (1.0%) was evaluated along with the reference (150 mg/kg of nitrite without ETPE). The redness (a value) of sausage with ETPE was found at 6.8±0.03, which was higher than those of reference and control, which were at 4.8±.022 and 5.1±0.15, respectively. However, hardness, expressible moisture content and cooking yield values were reduced slightly. During storage at 10 °C in the air packed condition for 1 week, changes in color, pH, redness, and thiobarbituric acid reactive substances value were not significantly different. However, total microbial count of sausage samples with ETPE was lower than control for a 1 log cycle, suggesting microbial stability. Therefore, the addition of ETPE could be an alternative strategy to utilize TP as a natural colorant and antimicrobial agent to extend the shelf life of low-nitrite chicken sausage.

Keywords: antimicrobial ingredient, chicken sausage, ethanolic extract, low-nitrite sausage, tomato pomace

Procedia PDF Downloads 193
24195 Dogmatic Instrumant in Financing Micro Project

Authors: Adel Fatima Zohra, Guendouz Abdelkader

Abstract:

The solitary sector seems to appear nowadays as a third sector along the private and public ones, because of their ineptitude to take in charge the social exigency of the society regarding the lack in their local assets and the weakness of their financial institutions. The role of this sector is promoting a set of activities in the field of the charity, without aiming neither the individual profit nor a power practice. With the rise in the need of domestic resources, it is possible to count on the Zakat funding to realize some investment projects in order to develop the local society in many sectors as health, agriculture … etc. In the Islamic financial system, the Zakat is likely one of the most important instruments in financing the local development with the respect of the “Charia” rules: the amount of the Zakat is 2.5% of a wealth equivalent of each 85 gr of gold possessed since one year at least. In Algeria a fund of Zakat, was created since 2003 as an alternative to the public finding of development. This fund is a religious and social institution under the supervision of the ministry of religious affairs. This supervision covers two tasks: the first is traditional witch concern the distribution and the forwarding of the zakat to the poor people, and the second is modern concerning the financing of microcredits in the aim to enhance social and economic development. In this paper, we try to highlight the main role of the Zakat fund and its impact on the both social and economic development in Algeria.

Keywords: dogmatic instrument, solidary sector, zakat fund, micro project

Procedia PDF Downloads 259
24194 Nuclear Decay Data Evaluation for 217Po

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

Abstract:

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

Procedia PDF Downloads 422
24193 Geographic Information System Using Google Fusion Table Technology for the Delivery of Disease Data Information

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 118
24192 Inclusive Practices in Health Sciences: Equity Proofing Higher Education Programs

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 52
24191 An Analysis of Sequential Pattern Mining on Databases Using Approximate Sequential Patterns

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 327
24190 Medical Knowledge Management since the Integration of Heterogeneous Data until the Knowledge Exploitation in a Decision-Making System

Authors: Nadjat Zerf Boudjettou, Fahima Nader, Rachid Chalal

Abstract:

Knowledge management is to acquire and represent knowledge relevant to a domain, a task or a specific organization in order to facilitate access, reuse and evolution. This usually means building, maintaining and evolving an explicit representation of knowledge. The next step is to provide access to that knowledge, that is to say, the spread in order to enable effective use. Knowledge management in the medical field aims to improve the performance of the medical organization by allowing individuals in the care facility (doctors, nurses, paramedics, etc.) to capture, share and apply collective knowledge in order to make optimal decisions in real time. In this paper, we propose a knowledge management approach based on integration technique of heterogeneous data in the medical field by creating a data warehouse, a technique of extracting knowledge from medical data by choosing a technique of data mining, and finally an exploitation technique of that knowledge in a case-based reasoning system.

Keywords: data warehouse, data mining, knowledge discovery in database, KDD, medical knowledge management, Bayesian networks

Procedia PDF Downloads 380
24189 Electrocatalysts for Lithium-Sulfur Energy Storage Systems

Authors: Mirko Ante, Şeniz Sörgel, Andreas Bund

Abstract:

Li-S- (Lithium-Sulfur-) battery systems provide very high specific gravimetric energy (2600 Wh/kg) and volumetric energy density (2800Wh/l). Hence, Li-S batteries are one of the key technologies for both the upcoming electromobility and stationary applications. Furthermore, the Li-S battery system is potentially cheap and environmentally benign. However, the technical implementation suffers from cycling stability, low charge and discharge rates and incomplete understanding of the complex polysulfide reaction mechanism. The aim of this work is to develop an effective electrocatalyst for the polysulfide reactions so that the electrode kinetics of the sulfur half-cell will be improved. Accordingly, the overvoltage will be decreased, and the efficiency of the cell will be increased. An enhanced electroactive surface additionally improves the charge and discharge rates. To reach this goal, functionalized electrocatalytic coatings are investigated to accelerate the kinetics of the polysulfide reactions. In order to determine a suitable electrocatalyst, apparent exchange current densities of a variety of materials (Ni, Co, Pt, Cr, Al, Cu, ITO, stainless steel) have been evaluated in a polysulfide containing electrolyte by potentiodynamic measurements and a Butler-Volmer fit including diffusion limitation. The samples have been examined by Scanning Electron Microscopy (SEM) after the potentiodynamic measurements. Up to now, our work shows that cobalt is a promising material with good electrocatalytic properties for the polysulfide reactions and good chemical stability in the system. Furthermore, an electrodeposition from a modified Watt’s nickel electrolyte with a sulfur source seems to provide an autocatalytic effect, but the electrocatalytic behavior decreases after several cycles of the current-potential-curve.

Keywords: electrocatalyst, energy storage, lithium sulfur battery, sulfur electrode materials

Procedia PDF Downloads 356
24188 Mean Shift-Based Preprocessing Methodology for Improved 3D Buildings Reconstruction

Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

Abstract:

In this work we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift

Procedia PDF Downloads 307
24187 GIS Data Governance: GIS Data Submission Process for Build-in Project, Replacement Project at Oman Electricity Transmission Company

Authors: Rahma Al Balushi

Abstract:

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 dept. This paper will describe in detail the GIS data submission process and the journey to develop the current process. 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, 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) 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 salso aided to reduce the missing attributes of GIS transmission data. A considerable difference in Geodatabase (GDB) completeness percentage was observed between the year 2017 and the year 2021. Overall, concluding that by governance, asset information & GIS department can control GIS data process; collect, properly record, and manage asset data and information within OETC network. This control extends to other applications and systems integrated with/related to GIS systems.

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

Procedia PDF Downloads 199
24186 Importance of Ethics in Cloud Security

Authors: Pallavi Malhotra

Abstract:

This paper examines the importance of ethics in cloud computing. In the modern society, cloud computing is offering individuals and businesses an unlimited space for storing and processing data or information. Most of the data and information stored in the cloud by various users such as banks, doctors, architects, engineers, lawyers, consulting firms, and financial institutions among others require a high level of confidentiality and safeguard. Cloud computing offers centralized storage and processing of data, and this has immensely contributed to the growth of businesses and improved sharing of information over the internet. However, the accessibility and management of data and servers by a third party raise concerns regarding the privacy of clients’ information and the possible manipulations of the data by third parties. This document suggests the approaches various stakeholders should take to address various ethical issues involving cloud-computing services. Ethical education and training is key to all stakeholders involved in the handling of data and information stored or being processed in the cloud.

Keywords: IT ethics, cloud computing technology, cloud privacy and security, ethical education

Procedia PDF Downloads 313
24185 The Feminism of Data Privacy and Protection in Africa

Authors: Olayinka Adeniyi, Melissa Omino

Abstract:

The field of data privacy and data protection in Africa is still an evolving area, with many African countries yet to enact legislation on the subject. While African Governments are bringing their legislation to speed in this field, how patriarchy pervades every sector of African thought and manifests in society needs to be considered. Moreover, the laws enacted ought to be inclusive, especially towards women. This, in a nutshell, is the essence of data feminism. Data feminism is a new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Feminising data privacy and protection will involve thinking women, considering women in the issues of data privacy and protection, particularly in legislation, as is the case in this paper. The line of thought of women inclusion is not uncommon when even international and regional human rights specific for women only came long after the general human rights. The consideration is that these should have been inserted or rather included in the original general instruments in the first instance. Since legislation on data privacy is coming in this century, having seen the rights and shortcomings of earlier instruments, then the cue should be taken to ensure inclusive wholistic legislation for data privacy and protection in the first instance. Data feminism is arguably an area that has been scantily researched, albeit a needful one. With the spate of increase in the violence against women spiraling in the cyber world, compounding the issue of COVID-19 and the needful response of governments, and the effect of these on women and their rights, fast forward, the research on the feminism of data privacy and protection in Africa becomes inevitable. This paper seeks to answer the questions, what is data feminism in the African context, why is it important in the issue of data privacy and protection legislation; what are the laws, if any, existing on data privacy and protection in Africa, are they women inclusive, if not, why; what are the measures put in place for the privacy and protection of women in Africa, and how can this be made possible. The paper aims to investigate the issue of data privacy and protection in Africa, the legal framework, and the protection or provision that it has for women if any. It further aims to research the importance and necessity of feminizing data privacy and protection, the effect of lack of it, the challenges or bottlenecks in attaining this feat and the possibilities of accessing data privacy and protection for African women. The paper also researches the emerging practices of data privacy and protection of women in other jurisprudences. It approaches the research through the methodology of review of papers, analysis of laws, and reports. It seeks to contribute to the existing literature in the field and is explorative in its suggestion. It suggests a draft of some clauses to make any data privacy and protection legislation women inclusive. It would be useful for policymaking, academic, and public enlightenment.

Keywords: feminism, women, law, data, Africa

Procedia PDF Downloads 185
24184 Need of Medicines Information OPD in Tertiary Health Care Settings: A Cross Sectional Study

Authors: Swanand Pathak, Kiran R. Giri, Reena R. Giri, Kamlesh Palandurkar, Sangita Totade, Rajesh Jha, S. S. Patel

Abstract:

Background: Population burden, illiteracy, availability of few doctors for larger group of population leads to many unanswered questions left in a patient’s mind. Incomplete information results into noncompliance, therapeutic failure, and adverse drug reactions (ADR). It is very important to establish a system which will provide noncommercial, independent, unbiased source of medicine information. Medicines Info OPD is a concept and step towards safe and appropriate use of medicines. Objective: (1) to assess the present status of knowledge about the medicines in the patients and its correlation with education; (2) to assess the medicine information dispensing modalities, their use and sufficiency from the patients view point; (3) to assess the overall need for Medicines Information OPD in present scenario. Materials and Methods: A pre-validated questionnaire based study was conducted amongst 500 patients of tertiary health care hospital. The questionnaire consisted of specific questions regarding understanding of prescription, knowledge about adverse drug reaction, view about self-medication and opinion regarding the need of Medicines Info OPD. Results: Significantly large proportion of patients opined that doctors do not have sufficient time in current Indian healthcare to explain the prescription and they are not aware of adverse drug reactions, expiry date or use the package inserts etc. Conclusion: Clinically relevant, up to date, user specific, independent, objective and unbiased Medicines Info OPD is essential for appropriate drug use and can help in a big way to common public to address many problems faced by them.

Keywords: information, prescription, unbiased, clinically relevant

Procedia PDF Downloads 431
24183 Evaluation of Practicality of On-Demand Bus Using Actual Taxi-Use Data through Exhaustive Simulations

Authors: Jun-ichi Ochiai, Itsuki Noda, Ryo Kanamori, Keiji Hirata, Hitoshi Matsubara, Hideyuki Nakashima

Abstract:

We conducted exhaustive simulations for data assimilation and evaluation of service quality for various setting in a new shared transportation system, called SAVS. Computational social simulation is a key technology to design recent social services like SAVS as new transportation service. One open issue in SAVS was to determine the service scale through the social simulation. Using our exhaustive simulation framework, OACIS, we did data-assimilation and evaluation of effects of SAVS based on actual tax-use data at Tajimi city, Japan. Finally, we get the conditions to realize the new service in a reasonable service quality.

Keywords: on-demand bus sytem, social simulation, data assimilation, exhaustive simulation

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24182 Case Report: Clinical Improvement of Forbrain Neurologic Signs in 3- Month- Old Persian Mastiff Dog with Calvarial Hyperostosis Syndrome after Corticosteroid, Antiepileptic and Antibiotic Therapy

Authors: Hamidreza Jahani, Zahra Salehzadeh, Ehsan Amini, Mohsen Tohidifar

Abstract:

Calvarial Hyperostosis Syndrome (CHS) is a benign bone disease of the skull. It is a non-neoplastic and proliferative bone disease, and the main feature of the disease is progressive and asymmetrical bone involvement. CHS is mostly reported in young male and female bullmastiff dogs and less frequently in other breeds. The etiology of CHS is unknown. This is the first case report of CHS in Iran. A 3-month-old male Persian Mastiff was presented with chief complaints of multiple episodes of seizure, pacing, bizarre behavior, delayed growth, head pressing, and difficulty in opening the mouth. Central blindness and open fontanelles were observed in clinical examination. No abnormality was found in the complete blood count and routine blood biochemical tests. CT scan findings include cortical thickening of frontal and parietal bones and enlargement of the left retropharyngeal lymph node. For treatment, oral clindamycin for two weeks, prednisolone and phenobarbital for one month, respectively, were administrated, and the case showed improvement after a week and recovered after one month.

Keywords: calvarial hyperostosis, Persian Mastiff, frontal bone, seizure

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24181 A Preliminary Study of the Reconstruction of Urban Residential Public Space in the Context of the “Top-down” Construction Model in China: Based on Research of TianZiFang District in Shanghai and Residential Space in Hangzhou

Authors: Wang Qiaowei, Gao Yujiang

Abstract:

With the economic growth and rapid urbanization after the reform and openness, some of China's fast-growing cities have demolished former dwellings and built modern residential quarters. The blind, incomplete reference to western modern cities and the one-off construction lacking feedback mechanism have intensified such phenomenon, causing the citizen gradually expanded their living scale with the popularization of car traffic, and the peer-to-peer lifestyle gradually settled. The construction of large-scale commercial centers has caused obstacles to small business around the residential areas, leading to space for residents' interaction has been compressed. At the same time, the advocated Central Business District (CBD) model even leads to the unsatisfactory reconstruction of many historical blocks such as the Hangzhou Southern Song Dynasty Imperial Street. However, the popularity of historical spaces such as Wuzhen and Hongcun also indicates the collective memory and needs of the street space for Chinese residents. The evolution of Shanghai TianZiFang also proves the importance of the motivation of space participants in space construction in the context of the “top-down” construction model in China. In fact, there are frequent occurrences of “reconstruction”, which may redefine the space, in various residential areas. If these activities can be selectively controlled and encouraged, it will be beneficial to activate the public space as well as the residents’ intercourse, so that the traditional Chinese street space can be reconstructed in the context of modern cities.

Keywords: rapid urbanization, traditional street space, space re-construction, bottom-up design

Procedia PDF Downloads 100
24180 Physico-Chemical and Phytoplankton Analyses of Kazaure Dam, Jigawa State, Nigeria

Authors: Aminu Musa Muhammad, Muhammad Kabiru Abubakar

Abstract:

Monthly changes in Phytoplankton periodicity, nutrient levels, temperature, pH, suspended solids, dissolved solids, conductivity, dissolved oxygen and biochemical oxygen demand of Kazaure Dam, Jigawa State, Nigeria were studied for a period of six months (July-Dec.-2011). Physico-chemical result showed that temperature and pH ranged between17-25˚C and 5.5-7.5, while dissolved solids and suspended solids ranged between 95-155 mg/L and 0.13-112 mg/L respectively. Dissolved oxygen (DO), Biochemical oxygen demand (BOD), Chemical oxygen demand (COD), conductivity, nitrate, phosphate and sulphate ion concentrations were within the ranges of 3.5-3.6 mg/L, 4.8-7.2 mg/L, 8.10-12.30 mg/L, 21-58µΩ/cm, 0.2-8.1 mg/L, 2.4-18.1 mg/L, and 1.22-15.60 mg/L respectively. A total of 4514 Org/L phytoplankton were recorded, of which four classes of algae were identified. These comprised of Chlorophyta (44.1%), Cyanophyta(30.62%), Bacillariophyta(3.2%), Euglenophyta (32.1%). Descriptive statistics of the result showed that phytoplankton count varied with variation of physico-chemical parameters at 5% level during the study period. The abundance and distribution of the algae varied with the variation in the physico-chemical parameters. Pearson correlation showed that temperature and nutrients were significantly correlated with phytoplankton, while DO, sulphate and pH were insignificantly correlated, while there was no significant correlation with COD and phytoplankton.

Keywords: correlation, phytoplankton, physico chemical, kazaure dam

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24179 Optimal Pricing Based on Real Estate Demand Data

Authors: Vanessa Kummer, Maik Meusel

Abstract:

Real estate demand estimates are typically derived from transaction data. However, in regions with excess demand, transactions are driven by supply and therefore do not indicate what people are actually looking for. To estimate the demand for housing in Switzerland, search subscriptions from all important Swiss real estate platforms are used. These data do, however, suffer from missing information—for example, many users do not specify how many rooms they would like or what price they would be willing to pay. In economic analyses, it is often the case that only complete data is used. Usually, however, the proportion of complete data is rather small which leads to most information being neglected. Also, the data might have a strong distortion if it is complete. In addition, the reason that data is missing might itself also contain information, which is however ignored with that approach. An interesting issue is, therefore, if for economic analyses such as the one at hand, there is an added value by using the whole data set with the imputed missing values compared to using the usually small percentage of complete data (baseline). Also, it is interesting to see how different algorithms affect that result. The imputation of the missing data is done using unsupervised learning. Out of the numerous unsupervised learning approaches, the most common ones, such as clustering, principal component analysis, or neural networks techniques are applied. By training the model iteratively on the imputed data and, thereby, including the information of all data into the model, the distortion of the first training set—the complete data—vanishes. In a next step, the performances of the algorithms are measured. This is done by randomly creating missing values in subsets of the data, estimating those values with the relevant algorithms and several parameter combinations, and comparing the estimates to the actual data. After having found the optimal parameter set for each algorithm, the missing values are being imputed. Using the resulting data sets, the next step is to estimate the willingness to pay for real estate. This is done by fitting price distributions for real estate properties with certain characteristics, such as the region or the number of rooms. Based on these distributions, survival functions are computed to obtain the functional relationship between characteristics and selling probabilities. Comparing the survival functions shows that estimates which are based on imputed data sets do not differ significantly from each other; however, the demand estimate that is derived from the baseline data does. This indicates that the baseline data set does not include all available information and is therefore not representative for the entire sample. Also, demand estimates derived from the whole data set are much more accurate than the baseline estimation. Thus, in order to obtain optimal results, it is important to make use of all available data, even though it involves additional procedures such as data imputation.

Keywords: demand estimate, missing-data imputation, real estate, unsupervised learning

Procedia PDF Downloads 275
24178 Humanistic Psychology Workshop to Increase Psychological Well-Being

Authors: Nidia Thalia Alva Rangel, Ferran Padros Blazquez, Ma. Ines Gomez Del Campo Del Paso

Abstract:

Happiness has been since antiquity a concept of interest around the world. Positive psychology is the science that begins to study happiness in a more precise and controlled way, obtaining wide amount of research which can be applied. One of the central constructs of Positive Psychology is Carol Ryff’s psychological well-being model as eudaimonic happiness, which comprehends six dimensions: autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-acceptance. Humanistic psychology is a clear precedent of Positive Psychology, which has studied human development topics and it features a great variety of intervention techniques nevertheless has little evidence with controlled research. Therefore, the present research had the aim to evaluate the efficacy of a humanistic intervention program to increase psychological well-being in healthy adults through a mixed methods study. Before and after the intervention, it was applied Carol Ryff’s psychological well-being scale (PWBS) and the Symptom Check List 90 as pretest and posttest. In addition, a questionnaire of five open questions was applied after each session. The intervention program was designed in experiential workshop format, based on the foundational attitudes defined by Carl Rogers: congruence, unconditional positive regard and empathy, integrating humanistic intervention strategies from gestalt, psychodrama, logotherapy and psychological body therapy, with the aim to strengthen skills in the six dimensions of psychological well-being model. The workshop was applied to six volunteer adults in 12 sessions of 2 hours each. Finally, quantitative data were analyzed with Wilcoxon statistic test through the SPSS program, obtaining as results differences statistically significant in pathology symptoms between prettest and postest, also levels of dimensions of psychological well-being were increased, on the other hand for qualitative strand, by open questionnaires it showed how the participants were experiencing the techniques and changing through the sessions. Thus, the humanistic psychology program was effective to increase psychological well-being. Working to promote well-being prompts to be an effective way to reduce pathological symptoms as a secondary gain. Experiential workshops are a useful tool for small groups. There exists the need for research to count with more evidence of humanistic psychology interventions in different contexts and impulse the application of Positive Psychology knowledge.

Keywords: happiness, humanistic psychology, positive psychology, psychological well-being, workshop

Procedia PDF Downloads 405
24177 Unlocking the Puzzle of Borrowing Adult Data for Designing Hybrid Pediatric Clinical Trials

Authors: Rajesh Kumar G

Abstract:

A challenging aspect of any clinical trial is to carefully plan the study design to meet the study objective in optimum way and to validate the assumptions made during protocol designing. And when it is a pediatric study, there is the added challenge of stringent guidelines and difficulty in recruiting the necessary subjects. Unlike adult trials, there is not much historical data available for pediatrics, which is required to validate assumptions for planning pediatric trials. Typically, pediatric studies are initiated as soon as approval is obtained for a drug to be marketed for adults, so with the adult study historical information and with the available pediatric pilot study data or simulated pediatric data, the pediatric study can be well planned. Generalizing the historical adult study for new pediatric study is a tedious task; however, it is possible by integrating various statistical techniques and utilizing the advantage of hybrid study design, which will help to achieve the study objective in a smoother way even with the presence of many constraints. This research paper will explain how well the hybrid study design can be planned along with integrated technique (SEV) to plan the pediatric study; In brief the SEV technique (Simulation, Estimation (using borrowed adult data and applying Bayesian methods)) incorporates the use of simulating the planned study data and getting the desired estimates to Validate the assumptions.This method of validation can be used to improve the accuracy of data analysis, ensuring that results are as valid and reliable as possible, which allow us to make informed decisions well ahead of study initiation. With professional precision, this technique based on the collected data allows to gain insight into best practices when using data from historical study and simulated data alike.

Keywords: adaptive design, simulation, borrowing data, bayesian model

Procedia PDF Downloads 65
24176 Juridically Secure Trade Mechanisms for Alternative Dispute Resolution in Transnational Business Negotiations

Authors: Linda Frazer

Abstract:

A pluralistic methodology focuses on promoting an understanding that an alternative juridical framework for the regulation of transnational business negotiations (TBN) between private business parties is fundamentally required. This paper deals with the evolving assessment of the doctoral research of the author which demonstrated that due to insufficient juridical tools, negotiations are commonly misunderstood within the complexity of pluralistic and conflicting legal regimes. This inadequacy causes uncertainty in the enforcement of legal remedies, leaving business parties surprised. Consequently, parties cannot sufficiently anticipate when and how legal rights and obligations are created, often counting on oral or incomplete agreements which may lead to the misinterpretation of the extent of their legal rights and obligations. This uncertainty causes threats to business parties for fear of creating unintended legal obligations or, conversely, that law will not enforce intended agreements for failure to pass the tests of contractual validity. A need to find a manner to set default standards of communications and standards of conduct to monitor our evolving global trade would aid law to provide the security, predictability and foreseeability during alternative dispute resolution required by TBN parties. The conclusion of this study includes a proposal of new trade mechanisms, termed 'Bills of Negotiations' (BON) to enhance party autonomy and promote the ability for TBN parties to self-regulate within the boundaries of law. BON will be guided by a secure juridical institutionalized setting that caters to guiding communications during TBN and resolving disputes that arise along the negotiation processes on a fast track basis.

Keywords: alternative resolution disputes, ADR, good faith, good faith, juridical security, legal regulation, trade mechanisms, transnational business negotiations

Procedia PDF Downloads 135