Search results for: clinical error

Authors: Nicola Colaninno, Eugenio Morello

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The urban environment affects local-to-global climate and, in turn, suffers global warming phenomena, with worrying impacts on human well-being, health, social and economic activities. Physic-morphological features of the built-up space affect urban air temperature, locally, causing the urban environment to be warmer compared to surrounding rural. This occurrence, typically known as the Urban Heat Island (UHI), is normally assessed by means of air temperature from fixed weather stations and/or traverse observations or based on remotely sensed Land Surface Temperatures (LST). The information provided by ground weather stations is key for assessing local air temperature. However, the spatial coverage is normally limited due to low density and uneven distribution of the stations. Although different interpolation techniques such as Inverse Distance Weighting (IDW), Ordinary Kriging (OK), or Multiple Linear Regression (MLR) are used to estimate air temperature from observed points, such an approach may not effectively reflect the real climatic conditions of an interpolated point. Quantifying local UHI for extensive areas based on weather stations’ observations only is not practicable. Alternatively, the use of thermal remote sensing has been widely investigated based on LST. Data from Landsat, ASTER, or MODIS have been extensively used. Indeed, LST has an indirect but significant influence on air temperatures. However, high-resolution near-surface air temperature (NSAT) is currently difficult to retrieve. Here we have experimented Geographically Weighted Regression (GWR) as an effective approach to enable NSAT estimation by accounting for spatial non-stationarity of the phenomenon. The model combines on-site measurements of air temperature, from fixed weather stations and satellite-derived LST. The approach is structured upon two main steps. First, a GWR model has been set to estimate NSAT at low resolution, by combining air temperature from discrete observations retrieved by weather stations (dependent variable) and the LST from satellite observations (predictor). At this step, MODIS data, from Terra satellite, at 1 kilometer of spatial resolution have been employed. Two time periods are considered according to satellite revisit period, i.e. 10:30 am and 9:30 pm. Afterward, the results have been downscaled at 30 meters of spatial resolution by setting a GWR model between the previously retrieved near-surface air temperature (dependent variable), the multispectral information as provided by the Landsat mission, in particular the albedo, and Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM), both at 30 meters. Albedo and DEM are now the predictors. The area under investigation is the Metropolitan City of Milan, which covers an area of approximately 1,575 km2 and encompasses a population of over 3 million inhabitants. Both models, low- (1 km) and high-resolution (30 meters), have been validated according to a cross-validation that relies on indicators such as R2, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). All the employed indicators give evidence of highly efficient models. In addition, an alternative network of weather stations, available for the City of Milano only, has been employed for testing the accuracy of the predicted temperatures, giving and RMSE of 0.6 and 0.7 for daytime and night-time, respectively.

Keywords: urban climate, urban heat island, geographically weighted regression, remote sensing

Procedia PDF Downloads 195

Authors: Ashika Govender

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This study seeks to determine whether Okun’s Law is valid for the South African economy, using time series data for the period 2004 to 2014. The data were accessed from the South African Reserve Bank and Stats SA. The stationarity of the variables was analysed by applying unit root tests via the Augmented Dickey-Fuller test (ADF), the Phillips-Perron (PP) test, and the Kwiatkowski–Phillips–Schmidt–Shin test (KPSS) test. The study used an ordinary least square (OLS) model in analysing the dynamic version of Okun’s law. The Error Correction Model (ECM) was used to analyse the short-run impact of GDP growth on unemployment, as well as the speed of adjustment. The results indicate a short run and long run relationship between unemployment rate and GDP growth rate in period 2004q1-2014q4, suggesting that Okun’s law is valid for the South African economy. With a 1 percent increase in GDP, unemployment can decrease by 0.13 percent, ceteris paribus. The research culminates in important policy recommendations, highlighting the relationship between unemployment and economic growth in the spirit of the National Development Plan.

Keywords: unemployment, economic growth, Okun's law, South Africa

Procedia PDF Downloads 272

Authors: Abdelrahman Alghazali, Youssef Kassem, Hüseyin Çamur, Ozan Erenay

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Savonius is a drag type vertical axis wind turbine. Savonius wind turbines have a low cut-in speed and can operate at low wind speed. This makes it suitable for electricity or mechanical generation in low-power applications such as individual domestic installations. Therefore, the primary purpose of this work was to investigate the relationship between the type of Savonius rotor and the torque and mechanical power generated. And it was to illustrate how the type of rotor might play an important role in the prediction of mechanical power of wind turbine powered car. The main purpose of this paper is to predict and investigate the aerodynamic effects by means of velocity analysis on the performance of a wind turbine powered car by converting the wind energy into mechanical energy to overcome load that rotates the main shaft. The predicted results based on theoretical analysis were compared with experimental results obtained from literature. The percentage of error between the two was approximately around 20%. Prediction of the torque was done at a wind speed of 4 m/s, and an angular velocity of 130 RPM according to meteorological statistics in Northern Cyprus.

Keywords: mechanical power, torque, Savonius rotor, wind car

Procedia PDF Downloads 337

Authors: Li Wang, Dan Shu, Shiguang Pang, Lixiu Wang, Bing Xiang Yang, Qian Liu

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Background: Cancer is one of the most severe diseases in childhood; long-term treatment and its side effects significantly impact the patient's physical, psychological, social functioning and quality of life while also placing substantial physical and psychological burdens on caregivers and families. Family resilience is crucial for children with cancer, helping them cope better with the disease and supporting the family in facing challenges together. As a family-level variable, family resilience requires information from multiple family members. However, to our best knowledge, there is currently no research investigating family resilience from both the perspectives of pediatric cancer patients and their caregivers. Therefore, this study aims to investigate the family resilience and quality of life of pediatric cancer patients from a patient–caregiver dyadic perspective. Methods: A total of 149 dyads of patients diagnosed with pediatric cancer patients and their principal caregivers were recruited from oncology departments of 4 tertiary hospitals in Wuhan and Taiyuan, China. All participants completed questionnaires that identified their demographic and clinical characteristics as well as assessed their family resilience and quality of life for both the patients and their caregivers. K-means cluster analysis was used to identify different clusters of family resilience based on the reports from patients and caregivers. Multivariate logistic regression and linear regression are used to analyze the factors influencing family resilience and quality of life, as well as the relationship between the two. Results: Three clusters of family resilience were identified: a cluster of high family resilience (HR), a cluster of low family resilience (LR), and a cluster of discrepant family resilience (DR). Most (67.1%) families fell into the cluster with low resilience. Characteristics such as the types of caregivers perceived social support of the patient were different among the three clusters. Compared to the LR group, families where the mother is the caregiver and where the patient has high social support are more likely to be assigned to the HR. The quality of life for caregivers was consistently highest in the HR cluster and lowest in the LR cluster. The patient's quality of life is not related to family resilience. In the linear regression analysis of the patient's quality of life, patients who are the first-born have higher quality of life, while those living with their parents have lower quality of life. The participants' characteristics were not associated with the quality of life for caregivers. Conclusions: In most families, family resilience was low. Families with maternal caregivers and patients receiving high levels of social support are more inclined to be higher levels of family resilience. Family resilience was linked to the quality of life of caregivers of pediatric cancer patients. The clinical implications of this findings suggest that healthcare and social support organizations should prioritize and support the participation of mothers in caregiving responsibilities. Furthermore, they should assist families in accessing social support to enhance family resilience. This study also emphasizes the importance of promoting family resilience for enhancing family health and happiness, as well as improving the quality of life for caregivers.

Keywords: pediatric cancer, cluster analysis, family resilience, quality of life

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Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

Procedia PDF Downloads 196

Authors: Alebachew Halefom, Navsal Kumar, Arunava Poddar

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The purpose of this work is to specify the parameter values, the base flow index (BFI), and to rank the methods that should be used for base flow separation. Three different digital graphical approaches are chosen and used in this study for the purpose of comparison. The daily time series discharge data were collected from the site for a period of 30 years (1986 up to 2015) and were used to evaluate the algorithms. In order to separate the base flow and the surface runoff, daily recorded streamflow (m³/s) data were used to calibrate procedures and get parameter values for the basin. Additionally, the performance of the model was assessed by the use of the standard error (SE), the coefficient of determination (R²), and the flow duration curve (FDC) and baseflow indexes. The findings indicate that, in general, each strategy can be used worldwide to differentiate base flow; however, the Sliding Interval Method (SIM) performs significantly better than the other two techniques in this basin. The average base flow index was calculated to be 0.72 using the local minimum method, 0.76 using the fixed interval method, and 0.78 using the sliding interval method, respectively.

Keywords: baseflow index, digital graphical methods, streamflow, Emba Madre Watershed

Procedia PDF Downloads 79

Authors: Naman Singla, Ajay Pal Singh Chauhan

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As the demand for providing high bit rate and high bandwidth is increasing at a rapid rate so there is a need to see in this problem and finds a technology that provides high bit rate and also high bandwidth. One possible solution is by use of optical fiber. Optical fiber technology provides high bandwidth in THz. But the disadvantage of optical fiber is of high cost and not used everywhere because it is not possible to reach all the locations on the earth. Also high maintenance required for usage of optical fiber. It puts a lot of cost. Another technology which is almost similar to optical fiber is Free Space Optics (FSO) technology. FSO is the line of sight technology where modulated optical beam whether infrared or visible is used to transfer information from one point to another through the atmosphere which works as a channel. This paper concentrates on analyzing the performance of FSO in terms of bit error rate (BER) and quality factor (Q) using different modulation techniques like non return to zero on off keying (NRZ-OOK), differential phase shift keying (DPSK) and differential quadrature phase shift keying (DQPSK) using OptiSystem software. The findings of this paper show that FSO system based on DQPSK modulation technique performs better.

Keywords: attenuation, bit rate, free space optics, link length

Procedia PDF Downloads 347

Authors: Mojtaba Farzaneh, Majid Baghaei Nejad

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This article proposes a new Flexible Capacitive Tactile Sensors based on paper sheets. This method combines the parameters of sensor's material and dielectric, and forms a new model of flexible capacitive sensors. The present article tries to present a practical explanation of this method's application and advantages. With the use of this new method, it is possible to make a more flexibility and accurate sensor in comparison with the current models. To assess the performance of this model, the common capacitive sensor is simulated and the proposed model of this article and one of the existing models are assessed. The results of this article indicate that the proposed model of this article can enhance the speed and accuracy of tactile sensor and has less error in comparison with the current models. Based on the results of this study, it can be claimed that in comparison with the current models, the proposed model of this article is capable of representing more flexibility and more accurate output parameters for touching the sensor, especially in abnormal situations and uneven surfaces, and increases accuracy and practicality.

Keywords: capacitive sensor, paper sheets, flexible, tactile, uneven

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Authors: Neerja Meena, Paresh Sukhani

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Dandy walker malformation is a generalised disorder of mesenchymal development that affect both the cerebellum and overlying meninges. Classically dandy-walker malformation consists of a triad of- 1:vermian and hemispheric cerebellar hypoplasia 2:cystic dilatation of 4th ventricle 3: enlarged posterior fossa with the upward migration of tentorium(lambdoid- torcular inversion). Clinical presentation: four months old female child with hydrocephalus and neurological symptoms. Generally- early death is common in classic dandy walker malformation. However, if it is relatively mild and uncomplicated by other CNS anomalies, intelligence can be normal and neurologic deficits minimal. Usually, VP shunting is the treatment of choice for this hydrocephalus. Conclusion: MRI is the modality of choice to diagnose posterior fossa malformation. However, it can be ruled out through using during the antenatal check as the prognosis of this malformation is not good; it's better to diagnose it inutero.

Keywords: Dandy Walker, Mri, Earlydaignosis, Treatment

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Authors: Junior Akunzi

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In the matter of patient treatment planning quality assurance in 3D conformational therapy (3D-CRT) and volumetric arc therapy (VMAT or RapidArc), the independent monitor unit verification calculation (MUVC) is an indispensable part of the process. Concerning 3D-CRT treatment planning, the MUVC can be performed manually applying the standard ESTRO formalism. However, due to the complex shape and the amount of beams in advanced treatment planning technic such as RapidArc, the manual independent MUVC is inadequate. Therefore, commercially available software such as RadCalc can be used to perform the MUVC in complex treatment planning been. Indeed, RadCalc (version 6.3 LifeLine Inc.) uses a simplified Clarkson algorithm to compute the dose contribution for individual RapidArc fields to the isocenter. The purpose of this project is the validation of RadCalc in 3D-CRT and RapidArc for treatment planning dosimetry quality assurance at Antoine Lacassagne center (Nice, France). Firstly, the interfaces between RadCalc and our treatment planning systems (TPS) Isogray (version 4.2) and Eclipse (version13.6) were checked for data transfer accuracy. Secondly, we created test plans in both Isogray and Eclipse featuring open fields, wedges fields, and irregular MLC fields. These test plans were transferred from TPSs according to the radiotherapy protocol of DICOM RT to RadCalc and the linac via Mosaiq (version 2.5). Measurements were performed in water phantom using a PTW cylindrical semiflex ionisation chamber (0.3 cm³, 31010) and compared with the TPSs and RadCalc calculation. Finally, 30 3D-CRT plans and 40 RapidArc plans created with patients CT scan were recalculated using the CT scan of a solid PMMA water equivalent phantom for 3D-CRT and the Octavius II phantom (PTW) CT scan for RapidArc. Next, we measure the doses delivered into these phantoms for each plan with a 0.3 cm³ PTW 31010 cylindrical semiflex ionisation chamber (3D-CRT) and 0.015 cm³ PTW PinPoint ionisation chamber (Rapidarc). For our test plans, good agreements were found between calculation (RadCalc and TPSs) and measurement (mean: 1.3%; standard deviation: ± 0.8%). Regarding the patient plans, the measured doses were compared to the calculation in RadCalc and in our TPSs. Moreover, RadCalc calculations were compared to Isogray and Eclispse ones. Agreements better than (2.8%; ± 1.2%) were found between RadCalc and TPSs. As for the comparison between calculation and measurement the agreement for all of our plans was better than (2.3%; ± 1.1%). The independent MU verification calculation software RadCal has been validated for clinical use and for both 3D-CRT and RapidArc techniques. The perspective of this project includes the validation of RadCal for the Tomotherapy machine installed at centre Antoine Lacassagne.

Keywords: 3D conformational radiotherapy, intensity modulated radiotherapy, monitor unit calculation, dosimetry quality assurance

Procedia PDF Downloads 216

Authors: Khaja Moiduddin, Tamer Khalaf, Muthuramalingam Thangaraj

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Due to the variety of benefits over traditional cutting techniques, the usage of laser cutting technology has risen substantially in recent years. Hot wire machining can cut the leather in the required shape by controlling the wire by generating thermal energy. In the present study, an attempt has been made to investigate the effects of performance measures in the hot wire machining process on cutting leather specimens. Carbonization and material removal rates were considered as quality indicators. Burning leather during machining might cause carbon particles, reducing product quality. Minimizing the effect of carbon particles is crucial for assuring operator and environmental safety, health, and product quality. Hot wire machining can efficiently cut the specimens by controlling the current through it. Taguchi- DEAR-based optimization was also performed in the process, which resulted in a required Carbonization and material removal rate. Using the DEAR approach, the optimal parameters of the present study were found with 3.7% prediction error accuracy.

Keywords: cabronization, leather, MRR, current

Procedia PDF Downloads 64

Authors: Jui-Chen Huang

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This research used artificial intelligence method to explore elderly’s opinions on the reuse of telecare, its effect on their service quality, satisfaction and the relationship between customer perceived value and intention to reuse. This study conducted a questionnaire survey on the elderly. A total of 124 valid copies of a questionnaire were obtained. It adopted Backpropagation Network (BPN) to propose an effective and feasible analysis method, which is different from the traditional method. Two third of the total samples (82 samples) were taken as the training data, and the one third of the samples (42 samples) were taken as the testing data. The training and testing data RMSE (root mean square error) are 0.022 and 0.009 in the BPN, respectively. As shown, the errors are acceptable. On the other hand, the training and testing data RMSE are 0.100 and 0.099 in the regression model, respectively. In addition, the results showed the service quality has the greatest effects on the intention to reuse, followed by the satisfaction, and perceived value. This result of the Backpropagation Network method is better than the regression analysis. This result can be used as a reference for future research.

Keywords: artificial intelligence, backpropagation network (BPN), elderly, reuse, telecare

Procedia PDF Downloads 212

Authors: Fathi Kallel, Saida Khachira, Mohamed Ben Slima, Ahmed Ben Hamida

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Speckle noise is a main characteristic of cardiac ultrasound images, it corresponding to grainy appearance that degrades the image quality. For this reason, the ultrasound images are difficult to use automatically in clinical use, then treatments are required for this type of images. Then a filtering procedure of these images is necessary to eliminate the speckle noise and to improve the quality of ultrasound images which will be then segmented to extract the necessary forms that exist. In this paper, we present the importance of the pre-treatment step for segmentation. This work is applied to cardiac ultrasound images. In a first step, a comparative study of speckle filtering method will be presented and then we use a segmentation algorithm to locate and extract cardiac structures.

Keywords: medical image processing, ultrasound images, Speckle noise, image enhancement, speckle filtering, segmentation, snakes

Procedia PDF Downloads 530

Authors: J. F. Pollo Gaspary, F. Peron Gaspary, E. M. Simão, R. Concatto Beltrame, G. Orengo de Oliveira, M. S. Ristow Ferreira, J.C. Mairesse Siluk, I. F. Minello, F. dos Santos de Oliveira

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Background: Although palliative care policies and services have been developed, research in this area continues to lag. An integrated model of palliative care is suggested, which includes complementary and alternative services aimed at improving the well-being of patients and their families. The palliative aquatics care multi-device (AuBento) uses several electromagnetic techniques to decrease pain and promote well-being through relaxation and interaction among patients, specialists, and family members. Aim: The scope of this paper is to present a preliminary design study of a device capable of exploring the various existing theories on the biomedical application of magnetic fields. This will be achieved by standardizing clinical data collection with sensory integration, and adding new therapeutic options to develop an advanced palliative aquatics care, innovating in symptom and pain management. Methods: The research methodology was based on the Work Package Methodology for the development of projects, separating the activities into seven different Work Packages. The theoretical basis was carried out through an integrative literature review according to the specific objectives of each Work Package and provided a broad analysis, which, together with the multiplicity of proposals and the interdisciplinarity of the research team involved, generated consistent and understandable complex concepts in the biomedical application of magnetic fields for palliative care. Results: Aubento ambience was idealized with restricted electromagnetic exposure (avoiding data collection bias) and sensory integration (allowing relaxation associated with hydrotherapy, music therapy, and chromotherapy or like floating tank). This device has a multipurpose configuration enabling classic or exploratory options on the use of the biomedical application of magnetic fields at the researcher's discretion. Conclusions: Several patients in diverse therapeutic contexts may benefit from the use of magnetic fields or fluids, thus validating the stimuli to clinical research in this area. A device in controlled and multipurpose environments may contribute to standardizing research and exploring new theories. Future research may demonstrate the possible benefits of the aquatics care multi-device AuBento to improve the well-being and symptom control in palliative care patients and their families.

Keywords: advanced palliative aquatics care, magnetic field therapy, medical device, research design

Procedia PDF Downloads 128

Authors: Mehrnaz Mostafavi

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Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

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Authors: Elysia Barker, Jian Guo Zhou, Ling Qian, Steve Decent

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A method of modelling topography used in the simulation of riverbeds is proposed in this paper, which removes the need for datapoints and measurements of physical terrain. While complex scans of the contours of a surface can be achieved with other methods, this requires specialised tools, which the proposed method overcomes by using fractional Brownian motion (FBM) as a basis to estimate the real surface within a 15% margin of error while attempting to optimise algorithmic efficiency. This removes the need for complex, expensive equipment and reduces resources spent modelling bed topography. This method also accounts for the change in topography over time due to erosion, sediment transport, and other external factors which could affect the topography of the ground by updating its parameters and generating a new bed. The lattice Boltzmann method (LBM) is used to simulate both stationary and steady flow cases in a side-by-side comparison over the generated bed topography using the proposed method and a test case taken from an external source. The method, if successful, will be incorporated into the current LBM program used in the testing phase, which will allow an automatic generation of topography for the given situation in future research, removing the need for bed data to be specified.

Keywords: bed topography, FBM, LBM, shallow water, simulations

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Authors: U. Sabura Banu, S. K. Lakshmanaprabu

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The improvement of meta-heuristic algorithm encourages control engineer to design an optimal controller for industrial process. Most real-world industrial processes are non-linear multivariable process with high interaction. Even in sub-process unit, thousands of loops are available mostly interacting in nature. Optimal controller design for such process are still challenging task. Closed loop controller design by multiloop PID involves a tedious procedure by performing interaction study and then PID auto-tuning the loop with higher interaction. Finally, detuning the controller to accommodate the effects of the other process variables. Fractional order PID controllers are replacing integer order PID controllers recently. Design of Multiloop Fractional Order (MFO) PID controller is still more complicated. Cuckoo algorithm, a swarm intelligence technique is used to optimally tune the MFO PID controller with easiness minimizing Integral Time Absolute Error. The closed loop performance is tested under servo, regulatory and servo-regulatory conditions.

Keywords: Cuckoo algorithm, mutliloop fractional order PID controller, two Interacting conical tank process

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Authors: Ehsan Ahmed Yahia

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Introduction: The nursing role in nutrition screening and assessing hospitalized patients is important. Malnutrition is a common and costly problem, particularly among hospitalized patients, and can have an adverse effect on the healing process. The study's goal is to assess the prevalence of malnutrition among adult hospitalized orthopedic patients and to detect the barriers to the nutrition screening process. Aim of the study: This study aimed to (a) assess the prevalence of malnutrition in hospitalized orthopedic patients and (b) evaluate the relationship between malnutrition and selected clinical outcomes. Material and Methods: This prospective field study was conducted for three months between 03/2022 and 06/2022 in the selected orthopedic departments in a teaching hospital affiliated withCairo University, Egypt. with a total number of one hundred twenty (120) patients. Patients' assessment included checking for malnutrition using the Nutritional Risk Screening Questionnaire. Patients at risk for malnourishment were defined as NRS score ≥ 3. Clinical outcomes under consideration included 1) length of hospitalization, 2) mobilization after surgery and conservative treatment, and 3) rate of adverse events. Results: This study found that malnutrition is a significant problem among patients hospitalized in an orthopedic ward. The prevalence of malnutrition was the highest in patients with lumbar spine and pelvis fractures, followed by the proximal femur and proximal humerus fractures. Patients at risk for malnutrition had significantly prolonged hospitalization, delayed postoperative mobilization, and increased incidence of adverse events.27.8% of the study sample were at risk for malnutrition. The highest prevalence of malnourishment was found in Septic Surgery with 32%, followed by Traumatology with 19.6% and Arthroplasty with 15.3%. A higher prevalence of malnutrition was detected among patients with typical fractures, such as lumbar spine and pelvis (46.7%), proximal femur (34.4%), and proximal humeral (23.7%) fractures. Additionally, patients at risk for malnutrition showed prolonged hospitalization (14.7 ± 11.1 vs. 21.2 ± 11.7 days), delayed postoperative mobilization (2.3 ± 2.9 vs. 4.1 ± 4.9 days), and delayed to mobilize after conservative treatment (1.1 ± 2.7 vs. 1.8 ± 1.9 days). A significant statistical correlation of NRS with individual parameters (Spearman's rank correlation, p < 0.05) was observed. The rate of adverse incidents in patients at risk for malnutrition was significantly higher than that of patients with a regular nutritional status (37.2% vs. 21.1%, p < 0.001). Conclusions: Our results indicate that the prevalence of malnutrition in surgical patients is significant. The nutritional status of patients with typical fractures is especially at risk. Prolonged hospitalization, delayed postoperative mobilization, and delayed mobilization after conservative treatment is significantly associated with malnutrition. In addition, the incidence of adverse events in patients at risk for malnutrition is significantly higher.

Keywords: malnutrition, nutritional risk screening, surgery, nursing, orthopedic nurse

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Authors: Longqing Li

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The paper addresses the inefficiency of the classical model in measuring the Value-at-Risk (VaR) using a normal distribution or a Student’s t distribution. Specifically, the paper focuses on the one day ahead Value-at-Risk (VaR) of major stock market’s daily returns in US, UK, China and Hong Kong in the most recent ten years under 95% confidence level. To improve the predictable power and search for the best performing model, the paper proposes using two leading alternatives, Extreme Value Theory (EVT) and a family of GARCH models, and compares the relative performance. The main contribution could be summarized in two aspects. First, the paper extends the GARCH family model by incorporating EGARCH and TGARCH to shed light on the difference between each in estimating one day ahead Value-at-Risk (VaR). Second, to account for the non-normality in the distribution of financial markets, the paper applies Generalized Error Distribution (GED), instead of the normal distribution, to govern the innovation term. A dynamic back-testing procedure is employed to assess the performance of each model, a family of GARCH and the conditional EVT. The conclusion is that Exponential GARCH yields the best estimate in out-of-sample one day ahead Value-at-Risk (VaR) forecasting. Moreover, the discrepancy of performance between the GARCH and the conditional EVT is indistinguishable.

Keywords: Value-at-Risk, Extreme Value Theory, conditional EVT, backtesting

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Authors: M. A. Sohaly, M. A. Elfouly

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Parkinson's disease (PD) is a heterogeneous movement disorder that often appears in the elderly. PD is induced by a loss of dopamine secretion. Some drugs increase the secretion of dopamine. In this paper, we will simply study the stability of PD models as a nonlinear delay differential equation. After a period of taking drugs, these act as positive feedback and increase the tremors of patients, and then, the differential equation has positive coefficients and the system is unstable under these conditions. We will present a set of suggested modifications to make the system more compatible with the biodynamic system. When giving a set of numerical examples, this research paper is concerned with the mathematical analysis, and no clinical data have been used.

Keywords: Parkinson's disease, stability, simulation, two delay differential equation

Procedia PDF Downloads 130

Authors: Mohammad Y. Abualhoul, Edgar Talavera Munoz, Fawzi Nashashibi

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The new emerging Visible Light Communication (VLC) technology has been subjected to intensive investigation, evaluation, and lately, deployed in the context of convoy-based applications for Intelligent Transportations Systems (ITS). The technology limitations were defined and supported by different solutions proposals to enhance the crucial alignment and mobility limitations. In this paper, we propose the incorporation of VLC technology and Lane-Centering (LC) technique to assure the VLC-connectivity by keeping the autonomous vehicle aligned to the lane center using vision-based lane detection in a convoy-based formation. Such combination can ensure the optical communication connectivity with a lateral error less than 30 cm. As soon as the road lanes are detectable, the evaluated system showed stable behavior independently from the inter-vehicle distances and without the need for any exchanged information of the remote vehicles. The evaluation of the proposed system is verified using VLC prototype and an empirical result of LC running application over 60 km in Madrid M40 highway.

Keywords: visible light communication, lane-centerin, platooning, intelligent transportation systems, road safety applications

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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

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Authors: Nayera E. Hassan, Sahar A. El-Masry, Rokia El-Banna, Mohamed S. El Hussieny

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There are several different modalities for treatment of obesity. Common intervention methods for obesity include low-calorie diet, exercise. Also acupuncture has shown good therapeutic results in the treatment of obesity. A recent clinical observation showed that laser acupuncture could reduce body weight and body mass index in obese persons. So, the aim of this research is focused on body composition changes as related to type of intervention, before and after intentional weight loss in overweight and obesity. 76 subjects were included in the study analysis. The present study recommended that every obese female must do lipid profile and fasting blood sugar analysis before weight-loss intervention to take the decision of which method should be used.

Keywords: obesity, weight-loss, body composition, modalities

Procedia PDF Downloads 488

Authors: Ninlawat Phuangchoke, Waraporn Viyanon, Setta Sasananan

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The most important process of the water treatment plant process is the coagulation using alum and poly aluminum chloride (PACL), and the value of usage per day is a hundred thousand baht. Therefore, determining the dosage of alum and PACL are the most important factors to be prescribed. Water production is economical and valuable. This research applies an artificial neural network (ANN), which uses the Levenberg–Marquardt algorithm to create a mathematical model (Soft Jar Test) for prediction chemical dose used to coagulation such as alum and PACL, which input data consists of turbidity, pH, alkalinity, conductivity, and, oxygen consumption (OC) of Bangkhen water treatment plant (BKWTP) Metropolitan Waterworks Authority. The data collected from 1 January 2019 to 31 December 2019 cover changing seasons of Thailand. The input data of ANN is divided into three groups training set, test set, and validation set, which the best model performance with a coefficient of determination and mean absolute error of alum are 0.73, 3.18, and PACL is 0.59, 3.21 respectively.

Keywords: soft jar test, jar test, water treatment plant process, artificial neural network

Procedia PDF Downloads 166

Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

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Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

Procedia PDF Downloads 339

Authors: Nancy Wilson

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In utero, fetal drug exposure is prevalent amongst birthing facilities. Assessment tools for neonatal abstinence syndrome (NAS) are often cumbersome and ill-fitting, harboring immense subjectivity. This paradox often leads the clinical assessor to be hypervigilant when assessing the newborn for subtle symptoms of NAS, often mistaken for normal newborn behaviors. As a quality improvement initiative, this project led to a more adaptable NAS tool termed eat, sleep, console (ESC). This function-based NAS assessment scores the infant based on the ability to accomplish three basic newborn necessities- to sleep, to eat, and to be consoled. Literature supports that ESC methodology improves patient and family outcomes while providing more cost-effective care.

Keywords: neonatal abstinence syndrome, neonatal opioid withdrawal, maternal substance abuse, pregnancy, and addiction, Finnegan neonatal abstinence syndrome tool, eat, sleep, console

Procedia PDF Downloads 153

Authors: Hamed Afrasiab, Saeed Khodaygan

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Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.

Keywords: process capability, machining error, dimensional and geometrical tolerances, uncertainty analysis

Procedia PDF Downloads 307

Authors: Mary Rose Eunice S. Gundayao, Manolo M. Fernandez

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Metachromatic leukodystrophy (MLD) is a rare lysosomal storage disorder with an autosomal recessive inheritance pattern. Lysosomal storage disorders are often severe, follow a progressively neurodegenerative path, and may result in multi-organ failure, potentially leading to death within 5 to 6 years in cases of early-onset forms. There are limited data regarding cases of MLD in Filipino children. This is the case of a 2-year-old Filipino girl who presented with progressive neurological deterioration and was diagnosed with metachromatic leukodystrophy by molecular genetic testing. This case report aims to present this patient’s clinical history, neurological findings, diagnosis and novel genetic mutations causing MLD. A concise review of updated literature on MLD will be discussed.

Keywords: metachromatic leukodystrophy, ARSA gene, peripheral neuropathy, case report, demyelinating disease

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Authors: Alessio Mastrorillo, Giuseppe Silvi, Francesco Scagliola

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In this work, we introduce an Ambisonics decoder with an implementation of the C-format, also called Super Stereo. This format is an alternative to conventional stereo and binaural decoding. Unlike those, this format conveys audio information from the horizontal plane and works with stereo speakers and headphones. The two C-format channels can also return a reconstructed planar B-format. This work provides an open-source implementation for this format. We implement an all-pass filter for signal quadrature, as required by the decoding equations. This filter works with six Biquads in a cascade configuration, with values for control frequency and quality factor discovered experimentally. The phase response of the filter delivers a small error in the 20-14.000Hz range. The decoder has been tested with audio sources up to 192kHz sample rate, returning pristine sound quality and detailed stereo image. It has been included in the Envelop for Live suite and is available as an open-source repository. This decoder has applications in Virtual Reality and 360° audio productions, music composition, and online streaming.

Keywords: ambisonics, UHJ, quadrature filter, virtual reality, Gerzon, decoder, stereo, binaural, biquad

Procedia PDF Downloads 91

Authors: Meesun Sun, Yongmin Kim

Abstract:

Estimating maintenance cost is crucial in defense management because it affects military budgets and availability of equipment. When it comes to estimating maintenance cost of the deployed equipment, time series forecasting can be applied with the actual historical cost data. It is more difficult issue to estimate maintenance cost of new equipment for which the actual costs are not provided. In this underlying context, this study proposes an analytical method for maintenance cost estimating relationships (CERs) development of helicopters using linear programming. The CERs can be applied to a new helicopter because they use non-cost independent variables such as the number of engines, the empty weight and so on. In the Republic of Korea, the maintenance cost of new equipment has been usually estimated by reflecting maintenance cost to unit price ratio of the legacy equipment. This study confirms that the CERs perform well for the 10 types of airmobile helicopters in terms of mean absolute percentage error by applying leave-one-out cross-validation. The suggested method is very useful to estimate the maintenance cost of new equipment and can help in the affordability assessment of acquisition program portfolios for total life cycle systems management.

Keywords: affordability analysis, cost estimating relationship, helicopter, linear programming, maintenance cost

Procedia PDF Downloads 139