Search results for: data loss

Authors: Richard Okyere Boadu, Judith Obiri-Yeboah, Kwame Adu Okyere Boadu, Nathan Kumasenu Mensah, Grace Amoh-Agyei

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Routine health information system (RHIS) quality assurance has become an important issue, not only because of its significance in promoting a high standard of patient care but also because of its impact on government budgets for the maintenance of health services. A routine health information system comprises healthcare data collection, compilation, storage, analysis, report generation, and dissemination on a routine basis in various healthcare settings. The data from RHIS give a representation of health status, health services, and health resources. The sources of RHIS data are normally individual health records, records of services delivered, and records of health resources. Using reliable information from routine health information systems is fundamental in the healthcare delivery system. Quality assurance practices are measures that are put in place to ensure the health data that are collected meet required quality standards. Routine health information system quality assurance practices ensure that data that are generated from the system are fit for use. This study considered quality assurance practices in the RHIS processes. Methods: A cross-sectional study was conducted in eight health facilities in Tarkwa Sub-Municipal Health Service in the western region of Ghana. The study involved routine quality assurance practices among the 90 health staff and management selected from facilities in Tarkwa Sub-Municipal who collected or used data routinely from 24th December 2019 to 20th January 2020. Results: Generally, Tarkwa Sub-Municipal health service appears to practice quality assurance during data collection, compilation, storage, analysis and dissemination. The results show some achievement in quality control performance in report dissemination (77.6%), data analysis (68.0%), data compilation (67.4%), report compilation (66.3%), data storage (66.3%) and collection (61.1%). Conclusions: Even though the Tarkwa Sub-Municipal Health Directorate engages in some control measures to ensure data quality, there is a need to strengthen the process to achieve the targeted percentage of performance (90.0%). There was a significant shortfall in quality assurance practices performance, especially during data collection, with respect to the expected performance.

Keywords: quality assurance practices, assessment of routine health information system quality, routine health information system, data quality

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Authors: Muhammad Saqlain, Nazar Abbas Saqib, Muazzam A. Khan

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Heart Failure (HF) has become the major health problem in our society. The prevalence of HF has increased as the patient’s ages and it is the major cause of the high mortality rate in adults. A successful identification and progression of HF can be helpful to reduce the individual and social burden from this syndrome. In this study, we use a real data set of cardiac patients to propose a classification model for the identification and progression of HF. The data set has divided into three age groups, namely young, adult, and old and then each age group have further classified into four classes according to patient’s current physical condition. Contemporary Data Mining classification algorithms have been applied to each individual class of every age group to identify the HF. Decision Tree (DT) gives the highest accuracy of 90% and outperform all other algorithms. Our model accurately diagnoses different stages of HF for each age group and it can be very useful for the early prediction of HF.

Keywords: decision tree, heart failure, data mining, classification model

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Authors: Tanuj Joshi

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Smart transportation is fast emerging as a solution to modern cities’ approach mobility issues, delayed emergency response rate and high congestion on streets. Present day scenario with Google Maps, Waze, Yelp etc. demonstrates how information and communications technologies controls the intelligent transportation system. This intangible and invisible infrastructure is largely guided by the big data analytics. On the other side, the exponential increase in Indian urban population has intensified the demand for better services and infrastructure to satisfy the transportation needs of its citizens. No doubt, India’s huge internet usage is looked as an important resource to guide to achieve this. However, with a projected number of over 40 billion objects connected to the Internet by 2025, the need for systems to handle massive volume of data (big data) also arises. This research paper attempts to identify the ways of exploiting the big data variables which will aid commuters on Indian tracks. This study explores real life inputs by conducting survey and interviews to identify which gaps need to be targeted to better satisfy the customers. Several experts at Mumbai Metropolitan Region Development Authority (MMRDA), Mumbai Metro and Brihanmumbai Electric Supply and Transport (BEST) were interviewed regarding the Information Technology (IT) systems currently in use. The interviews give relevant insights and requirements into the workings of public transportation systems whereas the survey investigates the macro situation.

Keywords: smart transportation, mobility issue, Mumbai transportation, big data, data analysis

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Authors: Hyuk Sung Yoon, In-Lee Choi, Mohammad Zahirul Islam, Jun Pill Baek, Ho-Min Kang

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The strawberry ‘Maehyang’ cultivated in South Korea has been increased to export to Southeast Asia. The degradation of quality often occurs in strawberries during short export period. Botrytis cinerea has been known to cause major damage to the export strawberries and the disease was caused during shipping and distribution. This study was conducted to find out the sterilized effect of chlorine dioxide(ClO2) gas and high concentration of CO2 gas injection for ‘Maehyang’ strawberry and it was packaged with oxygen transmission rate (OTR) films. The strawberry was harvested at 80% color changed stage and packaged with OTR film and perforated film (control). The treatments were a MAP used by with 20,000 cc·m-2·day·atm OTR film and gas injection in packages. The gas type of ClO2 and CO2 were injected into OTR film packages, and treatments were 6 mg/L ClO2, 15% CO2, and they were combined. The treated strawberries were stored at 3℃ for 30 days. Fresh weight loss rate was less than 1% in all OTR film packages but it was more than 15% in a perforated film treatment that showed severe deterioration of visual quality during storage. Carbon dioxide concentration within a package showed approximately 15% of the maximum CO2 concentration in all treatments except control until the 21st day, it was the tolerated range of maximum CO2 concentration of strawberry in recommended CA or MA conditions. But, it increased to almost 50% on the 30th day. Oxygen concentration showed a decrease down to approximately 0% in all treatments except control for 25 days. Ethylene concentration was shown to be steady until the 17th day, but it quickly increased on the 17th day and dropped down on the final storage day (30th day). All treatments did not show any significant differences in gas treatments. Firmness increased in CO2 (15%) and ClO2 (6mg/L) + CO2 (15%) treatments during storage. It might be the effect of high concentration CO2 known by reducing decay and cell wall degradation. The soluble solid decreased in all treatments during storage. These results were caused to use up the sugar by the increase of respiration during storage. The titratable acidity showed a similarity in all treatments. Incidence of fungi was 0% in CO2 (15%) and ClO2 (6mg/L)+ CO2 (15%), but was more than 20% in a perforated film treatment. Consequently, The result indicates that Chloride Dioxide(ClO2) and high concentration of CO2 inhibited fungi growth. Due to the fact that fresh weight loss rate and incidence of fungi were lower, the ClO2(6mg/L)+ CO2(15%) prove to be most efficient in sterilization. These results suggest that Chloride Dioxide (ClO2) and high concentration of CO2 gas injection treatments were an effective decontamination technique for improving the safety of strawberries.

Keywords: chloride dioxide, high concentration of CO2, modified atmosphere condition, oxygen transmission rate films

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Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

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Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

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Authors: Alexandru George Vaduva, Adriana Vlad, Bogdan Badea

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In this research, we conduct a Monte Carlo analysis on a two-dimensional χ2 test, which is used to determine the minimum distance required for independent sampling in the context of chaotic signals. We investigate the impact of transforming initial data sets from any probability distribution to new signals with a uniform distribution using the Spearman rank correlation on the χ2 test. This transformation removes the randomness of the data pairs, and as a result, the observed distribution of χ2 test values differs from the expected distribution. We propose a solution to this problem and evaluate it using another chaotic signal.

Keywords: chaotic signals, logistic map, Pearson’s test, Chi Square test, bivariate distribution, statistical independence

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Authors: Adil Loya, Ali Haider, Arslan A. Ghaffor, Abubaker Siddique

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Simulation and modelling of Unmanned Aero Vehicle (UAV) has gained wide popularity in front of aerospace community. The demand of designing and modelling optimized control system for UAV has increased ten folds since last decade. The reason is next generation warfare is dependent on unmanned technologies. Therefore, this research focuses on the simulation of nonlinear UAV dynamics on Simulink and its integration with Flightgear. There has been lots of research on implementation of optimizing control using Simulink, however, there are fewer known techniques to simulate these dynamics over Flightgear and a tedious technique of acquiring data has been tackled in this research horizon. Sending data to Flightgear is easy but receiving it from Simulink is not that straight forward, i.e. we can only receive control data on the output. However, in this research we have managed to get the data out from the Flightgear by implementation of level 2 s-function block within Simulink. Moreover, the results captured from Flightgear over a Universal Datagram Protocol (UDP) communication are then compared with the attitude signal that were sent previously. This provide useful information regarding the difference in outputs attained from Simulink to Flightgear. It was found that values received on Simulink were in high agreement with that of the Flightgear output. And complete study has been conducted in a discrete way.

Keywords: aerospace, flight control, flightgear, communication, Simulink

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Authors: Ali Noorian

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Crude oil contains various compounds of hydrocarbons but low concentrations of inorganic compounds or metals. Vanadium and Nickel are the most common metals in crude oil. These metals usually exist in solution in the oil and residual fuel oil in the refining process is condensed. Deleterious effects of metals in petroleum have been known for some time. These metals do not only contaminate the product but also cause intoxication and loss of catalyst and corrosion to equipment. In this study, removal of heavy metals and petroleum residues were investigated. These methods include physical, chemical and biological treatment processes. For example, processes such as solvent extraction and hydro-catalytic and catalytic methods are effective and practical methods, but typically often have high costs and cause environmental pollution. Furthermore, biological methods that do not cause environmental pollution have been discussed in recent years, but these methods have not yet been industrialized.

Keywords: removal, metal, heavy oil, nickel, vanadium

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Authors: Fangliang Chen, Yihe Huang, Tejav Deganyar, Anselm Boehm, Hamid Batoul

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With growing population density and further urbanization, the average noise level in cities is increasing. Excessive noise is not only annoying but also leads to a negative impact on human health. To deal with the increasing city noise, environmental regulations bring up higher standards on acoustic comfort in buildings by mitigating the noise transmission from building envelope exterior to interior. Framed window, door and façade systems are the leading choice for modern fenestration construction, which provides demonstrated quality of weathering reliability, environmental efficiency, and installation ease. The overall sound insulation of such systems depends both on glasses and frames, where glass usually covers the majority of the exposed surfaces, thus it is the main source of sound energy transmission. While frames in modern façade systems become slimmer for aesthetic appearance, which contribute to a minimal percentage of exposed surfaces. Nevertheless, frames might provide substantial transmission paths for sound travels through because of much less mass crossing the path, thus becoming more critical in limiting the acoustic performance of the whole system. There are various methodologies and numerical programs that can accurately predict the acoustic performance of either glasses or frames. However, due to the vast variance of size and dimension between frame and glass in the same system, there is no satisfactory theoretical approach or affordable simulation tool in current practice to access the over acoustic performance of a whole façade system. For this reason, laboratory test turns out to be the only reliable source. However, laboratory test is very time consuming and high costly, moreover different lab might provide slightly different test results because of varieties of test chambers, sample mounting, and test operations, which significantly constrains the early phase design of framed façade systems. To address this dilemma, this study provides an effective analytical methodology to predict the acoustic performance of framed façade systems, based on vast amount of acoustic test results on glass, frame and the whole façade system consist of both. Further test results validate the current model is able to accurately predict the overall sound transmission loss of a framed system as long as the acoustic behavior of the frame is available. Though the presented methodology is mainly developed from façade systems with aluminum frames, it can be easily extended to systems with frames of other materials such as steel, PVC or wood.

Keywords: city noise, building facades, sound mitigation, sound transmission loss, framed façade system

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Authors: Janusz Bedkowski, Grzegorz Kisala, Michal Wlasiuk, Piotr Pokorski

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Ground-truth data is essential for VO (Visual Odometry) and SLAM (Simultaneous Localization and Mapping) quantitative evaluation using e.g. ATE (Absolute Trajectory Error) and RPE (Relative Pose Error). Many open-access data sets provide raw and ground-truth data for benchmark purposes. The issue appears when one would like to validate Visual Odometry and/or SLAM approaches on data captured using the device for which the algorithm is targeted for example mobile phone and disseminate data for other researchers. For this reason, we propose an open source, open hardware groundtruth system that provides an accurate and precise trajectory with a 3D point cloud. It is based on LiDAR Livox Mid-360 with a non-repetitive scanning pattern, on-board Raspberry Pi 4B computer, battery and software for off-line calculations (camera to LiDAR calibration, LiDAR odometry, SLAM, georeferencing). We show how this system can be used for the evaluation of various the state of the art algorithms (Stella SLAM, ORB SLAM3, DSO) in typical indoor monocular VO/SLAM.

Keywords: SLAM, ground truth, navigation, LiDAR, visual odometry, mapping

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Authors: Reza Zakerinejad

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Gully erosion is a serious problem that threading the sustainability of agricultural area and rangeland and water in a large part of Iran. This type of water erosion is the main source of sedimentation in many catchment areas in the north of Iran. Since in many national assessment approaches just qualitative models were applied the aim of this study is to predict the spatial distribution of gully erosion processes by means of detail terrain analysis and GIS -based logistic regression in the loess deposition in a case study in the Golestan Province. This study the DEM with 25 meter result ion from ASTER data has been used. The Landsat ETM data have been used to mapping of land use. The TreeNet model as a stochastic modeling was applied to prediction the susceptible area for gully erosion. In this model ROC we have set 20 % of data as learning and 20 % as learning data. Therefore, applying the GIS and satellite image analysis techniques has been used to derive the input information for these stochastic models. The result of this study showed a high accurate map of potential for gully erosion.

Keywords: TreeNet model, terrain analysis, Golestan Province, Iran

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Authors: In-Gun Kim, Hyun-Seok Hong, Dong-Woo Kang, Ju Lee

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An Inverter type arc-welding machine is inclined to be designed for higher frequency in order to reduce the size and cost. The need of the core material reconsideration for high frequency pulse transformer is more important since core loss grows as the frequency rises. An arc welding machine’s pulse transformer is designed using an Area Product (Ap) method and is considered margin air gap core design in order to prevent the burning of the IGBT by the inrush current. Finally, the reduction of the core weight and the core size are compared according to different materials for 30kW inverter type arc welding machine.

Keywords: pulse transformers, welding, inrush current, air gaps

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Authors: Avi Shrivastava

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In 2021, two heart-wrenching scenes, shown live on television screens across countries, painted a grim picture of refugees. One of them was of people clinging onto an airplane's wings in their desperate attempt to flee war-torn Afghanistan. They ultimately fell to their death. The other scene was the U.S. government authorities separating children from their parents or guardians to deter migrants/refugees from coming to the U.S. These events show the desperation refugees feel when they are trying to leave their homes in disaster zones. However, data paints a grave picture of the current refugee situation. It also indicates that a bleak future lies ahead for the refugees across the globe. Data and information are the two threads that intertwine to weave the shimmery fabric of modern society. Data and information are often used interchangeably, but they differ considerably. For example, information analysis reveals rationale, and logic, while data analysis, on the other hand, reveals a pattern. Moreover, patterns revealed by data can enable us to create the necessary tools to combat huge problems on our hands. Data analysis paints a clear picture so that the decision-making process becomes simple. Geopolitical and economic data can be used to predict future refugee hotspots. Accurately predicting the next refugee hotspots will allow governments and relief agencies to prepare better for future refugee crises. The refugee crisis does not have binary answers. Given the emotionally wrenching nature of the ground realities, experts often shy away from realistically stating things as they are. This hesitancy can cost lives. When decisions are based solely on data, emotions can be removed from the decision-making process. Data also presents irrefutable evidence and tells whether there is a solution or not. Moreover, it also responds to a nonbinary crisis with a binary answer. Because of all that, it becomes easier to tackle a problem. Data science and A.I. can predict future refugee crises. With the recent explosion of data due to the rise of social media platforms, data and insight into data has solved many social and political problems. Data science can also help solve many issues refugees face while staying in refugee camps or adopted countries. This paper looks into various ways data science can help solve refugee problems. A.I.-based chatbots can help refugees seek legal help to find asylum in the country they want to settle in. These chatbots can help them find a marketplace where they can find help from the people willing to help. Data science and technology can also help solve refugees' many problems, including food, shelter, employment, security, and assimilation. The refugee problem seems to be one of the most challenging for social and political reasons. Data science and machine learning can help prevent the refugee crisis and solve or alleviate some of the problems that refugees face in their journey to a better life. With the explosion of data in the last decade, data science has made it possible to solve many geopolitical and social issues.

Keywords: refugee crisis, artificial intelligence, data science, refugee camps, Afghanistan, Ukraine

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Authors: Dmytro Zubov, Francesco Volponi

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In this paper, D-Wave quantum computing Ising model is used for the forecasting of positive extremes of daily mean air temperature. Forecast models are designed with two to five qubits, which represent 2-, 3-, 4-, and 5-day historical data respectively. Ising model’s real-valued weights and dimensionless coefficients are calculated using daily mean air temperatures from 119 places around the world, as well as sea level (Aburatsu, Japan). In comparison with current methods, this approach is better suited to predict heat wave values because it does not require the estimation of a probability distribution from scarce observations. Proposed forecast quantum computing algorithm is simulated based on traditional computer architecture and combinatorial optimization of Ising model parameters for the Ronald Reagan Washington National Airport dataset with 1-day lead-time on learning sample (1975-2010 yr). Analysis of the forecast accuracy (ratio of successful predictions to total number of predictions) on the validation sample (2011-2014 yr) shows that Ising model with three qubits has 100 % accuracy, which is quite significant as compared to other methods. However, number of identified heat waves is small (only one out of nineteen in this case). Other models with 2, 4, and 5 qubits have 20 %, 3.8 %, and 3.8 % accuracy respectively. Presented three-qubit forecast model is applied for prediction of heat waves at other five locations: Aurel Vlaicu, Romania – accuracy is 28.6 %; Bratislava, Slovakia – accuracy is 21.7 %; Brussels, Belgium – accuracy is 33.3 %; Sofia, Bulgaria – accuracy is 50 %; Akhisar, Turkey – accuracy is 21.4 %. These predictions are not ideal, but not zeros. They can be used independently or together with other predictions generated by different method(s). The loss of human life, as well as environmental, economic, and material damage, from extreme air temperatures could be reduced if some of heat waves are predicted. Even a small success rate implies a large socio-economic benefit.

Keywords: heat wave, D-wave, forecast, Ising model, quantum computing

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Authors: Pedro A. Marques, Francisco Monteiro, Alessandra Zumbo, Alessia Simonini, Miguel A. Mendez

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Cryogenic fuels such as Liquid Hydrogen (LH₂) must be transported and stored at extremely low temperatures. Without expensive active cooling solutions, preventing fuel boil-off over time is impossible. Hence, one must resort to venting systems at the cost of significant energy and fuel mass loss. These losses increase significantly in propellant tanks installed on vehicles, as the presence of external accelerations induces sloshing. Sloshing increases heat and mass transfer rates and leads to significant pressure oscillations, which might further trigger propellant venting. To make LH₂ economically viable, it is essential to minimize these factors by using advanced control techniques. However, these require accurate modelling and a full understanding of the tank's thermodynamics. The present research aims to implement a simple thermodynamic model capable of predicting the state of a cryogenic fuel tank under different operating conditions (i.e., filling, pressurization, fuel extraction, long-term storage, and sloshing). Since this model relies on a set of closure parameters to drive the system's transient response, it must be calibrated using experimental or numerical data. This work focuses on the former approach, wherein the model is calibrated through an experimental campaign carried out on a reduced-scale model of a cryogenic tank. The thermodynamic model of the system is composed of three control volumes: the ullage, the liquid, and the insulating walls. Under this lumped formulation, the governing equations are derived from energy and mass balances in each region, with mass-averaged properties assigned to each of them. The gas-liquid interface is treated as an infinitesimally thin region across which both phases can exchange mass and heat. This results in a coupled system of ordinary differential equations, which must be closed with heat and mass transfer coefficients between each control volume. These parameters are linked to the system evolution via empirical relations derived from different operating regimes of the tank. The derivation of these relations is carried out using an inverse method to find the optimal relations that allow the model to reproduce the available data. This approach extends classic system identification methods beyond linear dynamical systems via a nonlinear optimization step. Thanks to the data-driven assimilation of the closure problem, the resulting model accurately predicts the evolution of the tank's thermodynamics at a negligible computational cost. The lumped model can thus be easily integrated with other submodels to perform complete system simulations in real time. Moreover, by setting the model in a dimensionless form, a scaling analysis allowed us to relate the tested configurations to a representative full-size tank for naval applications. It was thus possible to compare the relative importance of different transport phenomena between the laboratory model and the full-size prototype among the different operating regimes.

Keywords: destratification, hydrogen, modeling, pressure-drop, pressurization, sloshing, thermodynamics

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Authors: Rebin Mzhda Mohammed, Hoshmand Ali Hama Agha

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Excess skin, often consequential to substantial weight loss or the aging process, introduces physical discomfort, obstructs daily activities, and undermines an individual's self-esteem. As these challenges become increasingly prevalent, the need to explore viable solutions grows in significance. Extra skin removal surgery, colloquially known as body contouring surgery, has emerged as a compelling intervention to ameliorate the physical and psychological burdens of excess skin. This study undertakes a comprehensive review to illuminate the intricacies of extra skin removal surgery, encompassing its diverse procedures, associated risks, benefits, and psychological implications on patients. The methodological approach adopted involves a systematic and exhaustive review of pertinent scholarly literature sourced from reputable databases, including PubMed, Google Scholar, and specialized cosmetic surgery journals. Articles are meticulously curated based on their relevance, credibility, and recency. Subsequently, data from these sources are synthesized and categorized, facilitating a comprehensive understanding of the subject matter. Qualitative analysis serves to unravel the nuanced psychological effects, while quantitative data, where available, are harnessed to underpin the study's conclusions. In terms of major findings, the research underscores the manifold advantages of extra skin removal surgery. Patients experience a notable improvement in physical comfort, amplified mobility, enhanced self-confidence, and a newfound ability to don clothing comfortably. Nonetheless, the benefits are juxtaposed with potential risks, encompassing infection, scarring, hematoma, delayed healing, and the challenge of achieving symmetry. A salient discovery is the profound psychological impact of the surgery, as patients consistently report elevated body image satisfaction, heightened self-esteem, and a substantial enhancement in overall quality of life. In summation, this research accentuates the pivotal role of extra skin removal surgery in ameliorating the intricate interplay of physical and psychological difficulties posed by excess skin. By elucidating the diverse procedures, associated risks, and psychological outcomes, the study contributes to a comprehensive and informed comprehension of the surgery's multifaceted effects. Therefore, individuals contemplating this transformative surgical option are equipped with comprehensive insights, ultimately fostering informed decision-making, guided by the expertise of medical professionals.

Keywords: extra skin removal surgery, body contouring, abdominoplasty, brachioplasty, thigh lift, body lift, benefits, risks, psychological effects

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Authors: Erhan Berk

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The purpose of this study is to examine the efficiency and productivity of the health care sector in Turkey based on four years of health care cross-sectional data. Efficiency measures are calculated by a nonparametric approach known as Data Envelopment Analysis (DEA). Productivity is measured by the Malmquist index. The research shows how DEA-based Malmquist productivity index can be operated to appraise the technology and productivity changes resulted in the Turkish hospitals which are located all across the country.

Keywords: data envelopment analysis, efficiency, health care, Malmquist Index

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Authors: Manar Y. Abd El-Aziz, Alyaa E. Morgham, Amira A. El-Fallal, Heba Tolla E. Abo El Naga

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Sport wears almost preferred with knitted fabrics, specially interlock construction. But, there is a need for higher comfortability and functional properties for fabrics to be more fitted to this application. This study compared cotton and polyester microfibers and blended them to improve the functional activity of interlock in sport wear by mercerized and non-mercerized. also, fabric dyeing and dyeability are affected by mercerization. Many functional properties, such as UV protection as well as antimicrobial activity. The changes in different mechanical as well as physical properties were investigated. The washing fastness properties of the dyed fabrics are also given. The changes in moisture regain, loss in weight, and burst and burst elongation for all mercerized fabrics have been studied.

Keywords: interlock, mercirization, dyeability, function properties, moisture management

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Authors: Syed Towseef Ahmad, Fatima Amin, Pritha Acharya, Anil K. Gupta, Pervez Ahmad

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Glaciers being the sentinels of climate change, are the most visible evidence of global warming. Given the unavailability of observed field-based data, this study has focussed on the use of geospatial techniques to obtain information about the glaciers of Pir-Panjal (PPJ) and the Great Himalayan Regions of Jhelum Basin (GHR). These glaciers need to be monitored in line with the variations in climatic conditions because they significantly contribute to various sectors in the region. The main aim of this study is to map the glaciers in the two adjacent regions (PPJ and GHR) in the north-western Himalayas with different topographies and compare the changes in various glacial attributes during two different time periods (1990-2020). During the last three decades, both PPJ as well as GHR regions have observed deglaciation of around 36 and 26 percent, respectively. The mean elevation of GHR glaciers has increased from 4312 to 4390 masl, while the same for PPJ glaciers has increased from 4085 to 4124 masl during the observation period. Using accumulation area ratio (AAR) method, mean mass balance of -34.52 and -37.6 cm.w.e was recorded for the glaciers of GHR and PPJ, respectively. The difference in areal and mass loss of glaciers in these regions may be due to (i) the smaller size of PPJ glaciers which are all smaller than 1 km² and are thus more responsive to climate change (ii) Higher mean elevation of GHR glaciers (iii) local variations in climatic variables in these glaciated regions. Time series analysis of climate variables indicates that both the mean maximum and minimum temperatures of Qazigund station (Tmax= 19.2, Tmin= 6.4) are comparatively higher than the Pahalgam station (Tmax= 18.8, Tmin= 3.2). Except for precipitation in Qazigund (Slope= - 0.3 mm a⁻¹), each climatic parameter has shown an increasing trend during these three decades, and with the slope of 0.04 and 0.03°c a⁻¹, the positive trend in Tmin (pahalgam) and Tmax (qazigund) are observed to be statistically significant (p≤0.05).

Keywords: glaciers, climate change, Pir-Panjal, greater Himalayas, mass balance

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Authors: Pablo Martinez, Emad Mohamed, Osama Mohsen, Yasser Mohamed

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Highway and bridge agencies, such as the Ministry of Transportation in Ontario, use the Bridge Condition Index (BCI) which is defined as the weighted condition of all bridge elements to determine the rehabilitation priorities for its bridges. Therefore, accurate forecasting of BCI is essential for bridge rehabilitation budgeting planning. The large amount of data available in regard to bridge conditions for several years dictate utilizing traditional mathematical models as infeasible analysis methods. This research study focuses on investigating different classification models that are developed to predict the bridge condition index in the province of Ontario, Canada based on the publicly available data for 2800 bridges over a period of more than 10 years. The data preparation is a key factor to develop acceptable classification models even with the simplest one, the k-NN model. All the models were tested, compared and statistically validated via cross validation and t-test. A simple k-NN model showed reasonable results (within 0.5% relative error) when predicting the bridge condition in an incoming year.

Keywords: asset management, bridge condition index, data mining, forecasting, infrastructure, knowledge discovery in databases, maintenance, predictive models

Procedia PDF Downloads 195

Authors: Rima T. Alfaraj, Murtadha J. Al Tammar, Khaqan Khan, Khalid M. Alruwaili

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OBJECTIVE/SCOPE (25-75): Caliper logging data provides critical information about wellbore shape and deformations, such as stress-induced borehole breakouts or washouts. Multiarm mechanical caliper logs are often run using wireline, which can be time-consuming, costly, and/or challenging to run in certain formations. To minimize rig time and improve operational safety, it is valuable to develop analytical solutions that can estimate caliper logs using available Logging-While-Drilling (LWD) data without the need to run wireline caliper logs. As a first step, the objective of this paper is to perform statistical analysis using an extensive datasetto identify important physical parameters that should be considered in developing such analytical solutions. METHODS, PROCEDURES, PROCESS (75-100): Caliper logs and LWD data of eleven wells, with a total of more than 80,000 data points, were obtained and imported into a data analytics software for analysis. Several parameters were selected to test the relationship of the parameters with the measured maximum and minimum caliper logs. These parameters includegamma ray, porosity, shear, and compressional sonic velocities, bulk densities, and azimuthal density. The data of the eleven wells were first visualized and cleaned.Using the analytics software, several analyses were then preformed, including the computation of Pearson’s correlation coefficients to show the statistical relationship between the selected parameters and the caliper logs. RESULTS, OBSERVATIONS, CONCLUSIONS (100-200): The results of this statistical analysis showed that some parameters show good correlation to the caliper log data. For instance, the bulk density and azimuthal directional densities showedPearson’s correlation coefficients in the range of 0.39 and 0.57, which wererelatively high when comparedto the correlation coefficients of caliper data with other parameters. Other parameters such as porosity exhibited extremely low correlation coefficients to the caliper data. Various crossplots and visualizations of the data were also demonstrated to gain further insights from the field data. NOVEL/ADDITIVE INFORMATION (25-75): This study offers a unique and novel look into the relative importance and correlation between different LWD measurements and wireline caliper logs via an extensive dataset. The results pave the way for a more informed development of new analytical solutions for estimating the size and shape of the wellbore in real-time while drilling using LWD data.

Keywords: LWD measurements, caliper log, correlations, analysis

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Authors: Arka Roy, Chandra Prakash Dubey

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Inverse problem generally used for recovering hidden information from outside available data. Vertical component of gravity field we will be going to use for underneath density structure calculation. Ill-posing nature is main obstacle for any inverse problem. Linear regularization using Tikhonov formulation are used for appropriate choice of SVD and GSVD components. For real time data handle, signal to noise ratios should have to be less for reliable solution. In our study, 2D and 3D synthetic model with rectangular grid are used for gravity field calculation and its corresponding inversion for density reconstruction. Fine grid also we have considered to hold any irregular structure. Keeping in mind of algebraic ambiguity factor number of observation point should be more than that of number of data point. Picard plot is represented here for choosing appropriate or main controlling Eigenvalues for a regularized solution. Another important study is depth resolution plot (DRP). DRP are generally used for studying how the inversion is influenced by regularizing or discretizing. Our further study involves real time gravity data inversion of Vredeforte Dome South Africa. We apply our method to this data. The results include density structure is in good agreement with known formation in that region, which puts an additional support of our method.

Keywords: depth resolution plot, gravity inversion, Picard plot, SVD, Tikhonov formulation

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Authors: Vishnu Pratap Singh Kirar, Madhuri Saxena

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Advancement in sequence data generation technologies is churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. With so much data available, the use of machine learning methods and tools to make novel inferences has become obvious. Machine learning methods have been successfully applied to a lot of disciplines, including computational biology and bioinformatics. Researchers in computational biology are interested to develop novel machine learning frameworks to classify the huge amounts of biological data. In this proposal, it plan to employ novel machine learning approaches to aid the understanding of how apparently innocuous mutations (in intergenic DNA and at synonymous sites) cause diseases. We are also interested in discovering novel functional sites in the genome and mutations in which can affect a phenotype of interest.

Keywords: genome wide association studies (GWAS), next generation sequencing (NGS), deep learning, omics

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Authors: Benukar Biswas, S. Banerjee, P. K. Bandhyopadhyaya, S. K. Patra, S. Sarkar

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Jute can be sown as relay crop in between the lines of 15-20 days old green gram for additional pulse yield without reducing the yield of jute. The main problem of this system is water use efficiency (WUE). The increase in water productivity and reduction in production cost were reported in the zero-tilled crop. The hydrogel can hold water up to 400 times of its weight and can release 95 % of the retained water. The present field study was carried out during 2015-16 at BCKV (tropical sub-humid, 1560 mm annual rainfall, 22058/ N, 88051/ E, 9.75 m AMSL, sandy loam soil, aeric Haplaquept, pH 6.75, organic carbon 5.4 g kg-1, available N 85 kg ha-1, P2O5 15.3 kg ha-1 and K2O 40 kg ha-1) with four levels of irrigation regimes: no irrigation - RF, cumulative pan evaporation 250mm (CPE250), CPE125 and CPE83 and three levels of hydrogel: no hydrogel (H0), 2.5 kg ha-1 (H2.5) and 5 kg ha-1 (H5). Throughout the crop growing period a linear positive relationship remained between Leaf Area Index (LAI) and evapotranspiration rate. The strength of the relationship between ETa and LAI started increasing and reached its peak at 7 WAS (R2=0.78) when green gram was at its maturity, and both the crops covered the nearly entire base area. This relation starts weakening from 13 WAS due to jute leaf shading. A linear relationship between system yield and ET was also obtained in the present study. The variation in system yield might be predicted 75% with ET alone. Effective rainfall was reduced with increasing irrigation frequency due to enhanced water supply in contrast to hydrogel application due to the difference in water storage capacity. Irrigation contributed a major source of variability of ET. Higher irrigation frequency resulted in higher ET loss ranging from 574 mm in RF to 764 mm in CPE83. Hydrogel application also increased water storage on a sustained basis and supplied to crops resulting higher ET from 639 mm in H0 to 671mm in H5. WUE ranged between 0.4 kg m-3 (RF) to 0.63 kg m-3 (CPE83 H5). WUE increased with increased application of irrigation water from 0.42 kg m-3 in RF to 0.57 kg m-3 in CPE 83. Hydrogel application significantly improves the WUE from 0.45 kg m-3 in H0 to 0.50 in H2.5 and 0.54 in H5. Under relatively dry root zone (RF), both evaporation and transpiration remain at suboptimal level resulting in lower ET as well as lower system yield. Green gram – jute relay system can be water use efficient with 38% higher yield with application of hydrogel @ 2.5 kg ha-1 under deficit irrigation regime of CPE 125 over rainfed system without application of the gel. Application of gel conditioner improved water storage, checked excess water loss from the system, and mitigated ET demand of the relay system for a longer time. Hence, irrigation frequency was reduced from five times at CPE 83 to only three times in CPE 125.

Keywords: zero tillage, deficit irrigation, hydrogel, relay system

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Authors: Raja Lahiani

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This study is concerned with scrutinising translations into English and French of references to locations in the desert of pre-Islamic Arabia. These references are used in the Source Text (ST) within a poetic image. Reference is made to the names of three different mountains in Arabia, namely Qatan, Sitar, and Yadhbul. As these mountains are referred to in the context of the poet’s description of the density and expansion of the clouds, it is crucial to know that while Sitar and Yadhbul are close to each other, Qatan is far away from them. This distance was functional for the poet to describe the expansion of the clouds. This reflects the spacious place (desert) he handled, and the fact that it was possible for him to physically see what he described. The purpose of this image is for the poet to communicate the vastness of the space he managed to see as he was in a moment of contemplation. Thus, knowledge of this characteristic about the setting is capital for the receiver to understand the communicative function of the verse. A corpus of eighteen translations is gathered. These vary between verse and prose renderings. The methodology adopted in this research work is comparative. Comparison is conducted at both the synchronic and diachronic levels; every translation shall be compared to the ST and then to previous translations. The comparative work will prove at the end that the translators who target historical facts do not necessarily succeed in preserving the image of the ST. It also proves that the more recent the translation is, the deeper the translator’s awareness is the link between imagery, setting, and point of view. Since the late eighteenth century and until nowadays, pre-Islamic poetry has been translated into Western languages. Translators differ as to motives, sources, priorities and intellectual backgrounds. A translator's skopoi undoubtedly affect the way s/he handles aspects of the ST. When it comes to culture-specific aspects and details related to setting, the problem is even more complex. Setting is a very important factor that reveals a great deal of the culture of pre-Islamic Arabia as this is remote in place, historical framework and literary tradition from its translators. History is present in pre-Islamic poetry, which justifies the important literature that has been written to extract information and data from it. These are imbedded not only by signalling given facts, events, and meditations but also by means of references to specific locations and landmarks that used to exist at the time. Spatial setting is an integral part of a literary text as it places it within its historical context. The importance of the translator’s awareness of spatial anthropological data before indulging in the process of translation is tested. This is also crucial in measuring the effect of setting loss and setting gain in translation. The findings of this research would ultimately evaluate the extent to which a comparative methodology is reliable in investigating the role of spatial setting awareness in translation.

Keywords: historical context, translation, comparative literature, spatial setting

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Authors: Rahul Jain, Jagdish Chander, Anish Gupta

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Introduction: Laparoscopic common bile duct exploration (LCBDE) allows cholecystectomy and the removal of common bile duct (CBD) stones to be performed during the same sitting, thereby decreasing hospital stay. CBD exploration through choledochotomy can be closed primarily with an absorbable suture material, but can lead to biliary leakage postoperatively. In this study we tried to find a solution to further lower the incidence of bile leakage by using fibrin glue to reinforce the sutures put on choledochotomy suture line. It has haemostatic and sealing action, through strengthening the last step of the physiological coagulation and biostimulation, which favours the formation of new tissue matrix. Methodology: This study was conducted at a tertiary care teaching hospital in New Delhi, India, from 2011 to 2013. 20 patients with CBD stones documented on MRCP with CBD diameter of 9 mm or more were included in this study. Patients were randomized into two groups namely Group A in which choledochotomy was closed with polyglactin 4-0 suture and suture line reinforced with fibrin glue, and Group ‘B’ in which choledochotomy was closed with polyglactin 4-0 suture alone. Both the groups were evaluated and compared on clinical parameters such as operative time, drain content, drain output, no. of days drain was required, blood loss & transfusion requirements, length of postoperative hospital stay and conversion to open surgery. Results: The operative time for Group A ranged from 60 to 210 min (mean 131.50 min) and Group B 65 to 300 min (mean 140 minutes). The blood loss in group A ranged from 10 to 120 ml (mean 51.50 ml), in group B it ranged from 10 to 200 ml (mean 53.50 ml). In Group A, there was no case of bile leak but there was bile leak in 2 cases in Group B, minimum 0 and maximum 900 ml with a mean of 97 ml and p value of 0.147 with no statistically significant difference in bile leak in test and control groups. The minimum and maximum serous drainage in Group A was nil & 80 ml (mean 11 ml) and in Group B was nil & 270 ml (mean 72.50 ml). The p value came as 0.028 which is statistically significant. Thus serous leakage in Group A was significantly less than in Group B. The drains in Group A were removed from 2 to 4 days (mean: 3 days) while in Group B from 2 to 9 days (mean: 3.9 days). The patients in Group A stayed in hospital post operatively from 3 to 8 days (mean: 5.30) while in Group B it ranged from 3 to 10 days with a mean of 5 days. Conclusion: Fibrin glue application on CBD decreases bile leakage but in statistically insignificant manner. Fibrin glue application on CBD can significantly decrease post operative serous drainage after LCBDE. Fibrin glue application on CBD is safe and easy technique without any significant adverse effects and can help less experienced surgeons performing LCBDE.

Keywords: bile leak, fibrin glue, LCBDE, serous leak

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Authors: Ghoname Abdullah, Hidekazu Nishimura

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Dust accumulation on the photovoltaic module's surface results in appreciable loss and negatively affects the generated power. Hence, in this paper, the design of a photovoltaic array cleaning system is presented. The cleaning system utilizes one drive motor, two guide rails, and four sweepers during the cleaning process. The cleaning system was experimentally implemented for one month to investigate its efficiency on PV array energy output. The energy capture over a month for PV array cleaned using the proposed cleaning system is compared with that of the energy capture using soiled PV array. The results show a 15% increase in energy generation from PV array with cleaning. From the results, investigating the optimal scheduling of the PV array cleaning could be an interesting research topic.

Keywords: cleaning system, dust accumulation, PV array, PV module, soiling

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory

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Authors: Supatchalee Sirichokworrakit

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Fishbone of Nile tilapia (Tilapia nilotica), waste from the frozen Nile tilapia fillet factory, is one of calcium sources. In order to increase fish bone powder value, this study aimed to investigate the effect of tilapia bone flour (TBF) addition (5, 10, 15% by flour weight) on cooking quality, texture and sensory attributes of noodles. The results indicated that tensile strength, color value (a*) and water absorption of noodles significantly decreased (p≤0.05) as the levels of TBF increased from 0-15%. While cooking loss, cooking time and color values (L* and b*) of noodles significantly increased (p≤0.05). Sensory evaluation indicated that noodles with 5% TBF received the highest overall acceptability score.

Keywords: tilapia bone flour, noodles, cooking quality, calcium

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Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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