Search results for: clinical error
4843 A Monocular Measurement for 3D Objects Based on Distance Area Number and New Minimize Projection Error Optimization Algorithms
Authors: Feixiang Zhao, Shuangcheng Jia, Qian Li
Abstract:
High-precision measurement of the target’s position and size is one of the hotspots in the field of vision inspection. This paper proposes a three-dimensional object positioning and measurement method using a monocular camera and GPS, namely the Distance Area Number-New Minimize Projection Error (DAN-NMPE). Our algorithm contains two parts: DAN and NMPE; specifically, DAN is a picture sequence algorithm, NMPE is a relatively positive optimization algorithm, which greatly improves the measurement accuracy of the target’s position and size. Comprehensive experiments validate the effectiveness of our proposed method on a self-made traffic sign dataset. The results show that with the laser point cloud as the ground truth, the size and position errors of the traffic sign measured by this method are ± 5% and 0.48 ± 0.3m, respectively. In addition, we also compared it with the current mainstream method, which uses a monocular camera to locate and measure traffic signs. DAN-NMPE attains significant improvements compared to existing state-of-the-art methods, which improves the measurement accuracy of size and position by 50% and 15.8%, respectively.Keywords: monocular camera, GPS, positioning, measurement
Procedia PDF Downloads 1444842 Therapeutic Management of Toxocara canis Induced Hepatitis in Dogs
Authors: Milind D. Meshram
Abstract:
Ascarids are the most frequent worm parasite of dogs and cats. There are two species that commonly infect dogs: Toxocara canis and Toxascaris leonina. Adult roundworms live in the stomach and intestines and can grow to 7 inches (18 cm) long. A female may lay 200,000 eggs in a day. The eggs are protected by a hard shell. They are extremely hardy and can live for months or years in the soil. A dog aged about 6 years, from Satara was referred to Teaching Veterinary Clinical Complex (TVCC) with a complaint of abdominal pain, anorexia, loss of condition and dull body coat with mucous pale membrane. The clinical examination revealed Anaemia, palpation of abdomen revealed enlargement of liver, slimy feel of the intestine loop, diarrhea.Keywords: therapeutic management, Toxocara canis, induced hepatitis, dogs
Procedia PDF Downloads 5924841 Development of a Bi-National Thyroid Cancer Clinical Quality Registry
Authors: Liane J. Ioannou, Jonathan Serpell, Joanne Dean, Cino Bendinelli, Jenny Gough, Dean Lisewski, Julie Miller, Win Meyer-Rochow, Stan Sidhu, Duncan Topliss, David Walters, John Zalcberg, Susannah Ahern
Abstract:
Background: The occurrence of thyroid cancer is increasing throughout the developed world, including Australia and New Zealand, and since the 1990s has become the fastest increasing malignancy. Following the success of a number of institutional databases that monitor outcomes after thyroid surgery, the Australian and New Zealand Endocrine Surgeons (ANZES) agreed to auspice the development of a bi-national thyroid cancer registry. Objectives: To establish a bi-national population-based clinical quality registry with the aim of monitoring and improving the quality of care provided to patients diagnosed with thyroid cancer in Australia and New Zealand. Patients and Methods: The Australian and New Zealand Thyroid Cancer Registry (ANZTCR) captures clinical data for all patients, over the age of 18 years, diagnosed with thyroid cancer, confirmed by histopathology report, that have been diagnosed, assessed or treated at a contributing hospital. Data is collected by endocrine surgeons using a web-based interface, REDCap, primarily via direct data entry. Results: A multi-disciplinary Steering Committee was formed, and with operational support from Monash University the ANZTCR was established in early 2017. The pilot phase of the registry is currently operating in Victoria, New South Wales, Queensland, Western Australia and South Australia, with over 30 sites expected to come on board across Australia and New Zealand in 2018. A modified-Delphi process was undertaken to determine the key quality indicators to be reported by the registry, and a minimum dataset was developed comprising information regarding thyroid cancer diagnosis, pathology, surgery, and 30-day follow up. Conclusion: There are very few established thyroid cancer registries internationally, yet clinical quality registries have shown valuable outcomes and patient benefits in other cancers. The establishment of the ANZTCR provides the opportunity for Australia and New Zealand to further understand the current practice in the treatment of thyroid cancer and reasons for variation in outcomes. The engagement of endocrine surgeons in supporting this initiative is crucial. While the pilot registry has a focus on early clinical outcomes, it is anticipated that future collection of longer-term outcome data particularly for patients with the poor prognostic disease will add significant further value to the registry.Keywords: thyroid cancer, clinical registry, population health, quality improvement
Procedia PDF Downloads 1924840 Excellent Outcome with Early Diagnosis in an Infant with Wiskott-Aldrich Syndrome in a Tertiary Hospital in Oman
Authors: Surekha Tony, Roshan Mevada
Abstract:
Wiskott-Aldrich syndrome (WAS) is a primary immunodeficiency disease resulting in recurrent infections, eczema, and microthrombocytopenia. In its classical form, significant combined immune deficiency, autoimmune complications, and risk of hematological malignancy necessitate early correction, preferably before 2 years of age, with hematopoietic stem cell transplant (HSCT) or gene therapy. Clinical features and severity are varied, making the diagnosis difficult in milder cases. We report an Omani boy diagnosed in early infancy with WAS based on clinical presentation and confirmed by genetic diagnosis with cure by HSCT from an HLA-identical sibling donor.Keywords: genetic diagnosis, hematopoietic stem cell transplant, infant, Wiskott-Aldrich syndrome
Procedia PDF Downloads 184839 External Sector and Its Impact on Economic Growth of Pakistan (1990-2010)
Authors: Rizwan Fazal
Abstract:
This study investigates the behavior of external sector of Pakistan economy and its impact on economic growth, using quarterly data for the period 1990:01-2010:04. External sector indices used in this study are financial integration, net foreign assets and trade integration. Augmented Ducky fuller confirms that all variables of external sector are non-stationary at level, but at first difference it becomes stationary. The co-integration test suggests one co-integrating variables in the study. The analysis is based on Vector Auto Regression model followed by Vector Error Correction Model. The empirical findings show that financial integration play important role in increasing economic growth in Pakistan economy while trade integration has negative effect on economic growth of Pakistan in the long run. However, the short run confirms that output lag accounts for error correction. The estimated CUSUM and CUSUMQ stability test provide information that the period of the study equation remains stable.Keywords: financial integration, trade integration, net foreign assets, gross domestic product
Procedia PDF Downloads 2724838 Machine Learning Assisted Prediction of Sintered Density of Binary W(MO) Alloys
Authors: Hexiong Liu
Abstract:
Powder metallurgy is the optimal method for the consolidation and preparation of W(Mo) alloys, which exhibit excellent application prospects at high temperatures. The properties of W(Mo) alloys are closely related to the sintered density. However, controlling the sintered density and porosity of these alloys is still challenging. In the past, the regulation methods mainly focused on time-consuming and costly trial-and-error experiments. In this study, the sintering data for more than a dozen W(Mo) alloys constituted a small-scale dataset, including both solid and liquid phases of sintering. Furthermore, simple descriptors were used to predict the sintered density of W(Mo) alloys based on the descriptor selection strategy and machine learning method (ML), where the ML algorithm included the least absolute shrinkage and selection operator (Lasso) regression, k-nearest neighbor (k-NN), random forest (RF), and multi-layer perceptron (MLP). The results showed that the interpretable descriptors extracted by our proposed selection strategy and the MLP neural network achieved a high prediction accuracy (R>0.950). By further predicting the sintered density of W(Mo) alloys using different sintering processes, the error between the predicted and experimental values was less than 0.063, confirming the application potential of the model.Keywords: sintered density, machine learning, interpretable descriptors, W(Mo) alloy
Procedia PDF Downloads 824837 Artificial Neural Network and Satellite Derived Chlorophyll Indices for Estimation of Wheat Chlorophyll Content under Rainfed Condition
Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman
Abstract:
Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat
Procedia PDF Downloads 1464836 Mechanical Performance of Sandwich Square Honeycomb Structure from Sugar Palm Fibre
Authors: Z. Ansari, M. R. M. Rejab, D. Bachtiar, J. P. Siregar
Abstract:
This study focus on the compression and tensile properties of new and recycle square honeycombs structure from sugar palm fibre (SPF) and polylactic acid (PLA) composite. The end data will determine the failure strength and energy absorption for both new and recycle composite. The control SPF specimens were fabricated from short fibre co-mingled with PLA by using a bra-blender set at 180°C and 50 rpm consecutively. The mixture of 30% fibre and 70% PLA were later on the hot press at 180°C into sheets with thickness 3mm consecutively before being assembled into a sandwich honeycomb structure. An INSTRON tensile machine and Abaqus 6.13 software were used for mechanical test and finite element simulation. The percentage of error from the simulation and experiment data was 9.20% and 9.17% for both new and recycled product. The small error of percentages was acceptable due to the nature of the simulation model to be assumed as a perfect model with no imperfect geometries. The energy absorption value from new to recycled product decrease from 312.86kJ to 282.10kJ. With this small decrements, it is still possible to implement a recycle SPF/PLA composite into everyday usages such as a car's interior or a small size furniture.Keywords: failure modes, numerical modelling, polylactic acid, sugar palm fibres
Procedia PDF Downloads 2944835 Scenario-Based Learning Using Virtual Optometrist Applications
Authors: J. S. M. Yang, G. E. T. Chua
Abstract:
Diploma in Optometry (OPT) course is a three-year program offered by Ngee Ann Polytechnic (NP) to train students to provide primary eye care. Students are equipped with foundational conceptual knowledge and practical skills in the first three semesters before clinical modules in fourth to six semesters. In the clinical modules, students typically have difficulties in integrating the acquired knowledge and skills from the past semesters to perform general eye examinations on public patients at NP Optometry Centre (NPOC). To help the students overcome the challenge, a web-based game Virtual Optometrist (VO) was developed to help students apply their skills and knowledge through scenario-based learning. It consisted of two interfaces, Optical Practice Counter (OPC) and Optometric Consultation Room (OCR), to provide two simulated settings for authentic learning experiences. In OPC, students would recommend and provide appropriate frame and lens selection based on virtual patient’s case history. In OCR, students would diagnose and manage virtual patients with common ocular conditions. Simulated scenarios provided real-world clinical situations that required contextual application of integrated knowledge from relevant modules. The stages in OPC and OCR are of increasing complexity to align to expected students’ clinical competency as they progress to more senior semesters. This prevented gameplay fatigue as VO was used over the semesters to achieve different learning outcomes. Numerous feedback opportunities were provided to students based on their decisions to allow individualized learning to take place. The game-based learning element in VO was achieved through the scoreboard and leader board to enhance students' motivation to perform. Scores were based on the speed and accuracy of students’ responses to the questions posed in the simulated scenarios, preparing the students to perform accurately and effectively under time pressure in a realistic optometric environment. Learning analytics was generated in VO’s backend office based on students’ responses, offering real-time data on distinctive and observable learners’ behavior to monitor students’ engagement and learning progress. The backend office allowed versatility to add, edit, and delete scenarios for different intended learning outcomes. Likert Scale was used to measure students’ learning experience with VO for OPT Year 2 and 3 students. The survey results highlighted the learning benefits of implementing VO in the different modules, such as enhancing recall and reinforcement of clinical knowledge for contextual application to develop higher-order thinking skills, increasing efficiency in clinical decision-making, facilitating learning through immediate feedback and second attempts, providing exposure to common and significant ocular conditions, and training effective communication skills. The results showed that VO has been useful in reinforcing optometry students’ learning and supporting the development of higher-order thinking, increasing efficiency in clinical decision-making, and allowing students to learn from their mistakes with immediate feedback and second attempts. VO also exposed the students to diverse ocular conditions through simulated real-world clinical scenarios, which may otherwise not be encountered in NPOC, and promoted effective communication skills.Keywords: authentic learning, game-based learning, scenario-based learning, simulated clinical scenarios
Procedia PDF Downloads 1174834 Analysis of Business Intelligence Tools in Healthcare
Authors: Avishkar Gawade, Omkar Bansode, Ketan Bhambure, Bhargav Deore
Abstract:
In recent year wide range of business intelligence technology have been applied to different area in order to support decision making process BI enables extraction of knowledge from data store. BI tools usually used in public health field for financial and administrative purposes.BI uses a dashboard in presentation stage to deliver information to information to end users.In this paper,we intend to analyze some open source BI tools on the market and their applicability in the clinical sphere taking into consideration the general characteristics of the clinical environment.A pervasive BI platform was developed using a real case in order to prove the tool viability.Analysis of various BI Tools in done with the help of several parameters such as data security,data integration,data quality reporting and anlaytics,performance,scalability and cost effectivesness.Keywords: CDSS, EHR, business intelliegence, tools
Procedia PDF Downloads 1374833 Performance Evaluation of MIMO-OFDM Communication Systems
Authors: M. I. Youssef, A. E. Emam, M. Abd Elghany
Abstract:
This paper evaluates the bit error rate (BER) performance of MIMO-OFDM communication system. MIMO system uses multiple transmitting and receiving antennas with different coding techniques to either enhance the transmission diversity or spatial multiplexing gain. Utilizing alamouti algorithm were the same information transmitted over multiple antennas at different time intervals and then collected again at the receivers to minimize the probability of error, combat fading and thus improve the received signal to noise ratio. While utilizing V-BLAST algorithm, the transmitted signals are divided into different transmitting channels and transferred over the channel to be received by different receiving antennas to increase the transmitted data rate and achieve higher throughput. The paper provides a study of different diversity gain coding schemes and spatial multiplexing coding for MIMO systems. A comparison of various channels' estimation and equalization techniques are given. The simulation is implemented using MATLAB, and the results had shown the performance of transmission models under different channel environments.Keywords: MIMO communication, BER, space codes, channels, alamouti, V-BLAST
Procedia PDF Downloads 1754832 Imputing Missing Data in Electronic Health Records: A Comparison of Linear and Non-Linear Imputation Models
Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand
Abstract:
Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias
Procedia PDF Downloads 854831 Platform Virtual for Joint Amplitude Measurement Based in MEMS
Authors: Mauro Callejas-Cuervo, Andrea C. Alarcon-Aldana, Andres F. Ruiz-Olaya, Juan C. Alvarez
Abstract:
Motion capture (MC) is the construction of a precise and accurate digital representation of a real motion. Systems have been used in the last years in a wide range of applications, from films special effects and animation, interactive entertainment, medicine, to high competitive sport where a maximum performance and low injury risk during training and competition is seeking. This paper presents an inertial and magnetic sensor based technological platform, intended for particular amplitude monitoring and telerehabilitation processes considering an efficient cost/technical considerations compromise. Our platform particularities offer high social impact possibilities by making telerehabilitation accessible to large population sectors in marginal socio-economic sector, especially in underdeveloped countries that in opposition to developed countries specialist are scarce, and high technology is not available or inexistent. This platform integrates high-resolution low-cost inertial and magnetic sensors with adequate user interfaces and communication protocols to perform a web or other communication networks available diagnosis service. The amplitude information is generated by sensors then transferred to a computing device with adequate interfaces to make it accessible to inexperienced personnel, providing a high social value. Amplitude measurements of the platform virtual system presented a good fit to its respective reference system. Analyzing the robotic arm results (estimation error RMSE 1=2.12° and estimation error RMSE 2=2.28°), it can be observed that during arm motion in any sense, the estimation error is negligible; in fact, error appears only during sense inversion what can easily be explained by the nature of inertial sensors and its relation to acceleration. Inertial sensors present a time constant delay which acts as a first order filter attenuating signals at large acceleration values as is the case for a change of sense in motion. It can be seen a damped response of platform virtual in other images where error analysis show that at maximum amplitude an underestimation of amplitude is present whereas at minimum amplitude estimations an overestimation of amplitude is observed. This work presents and describes the platform virtual as a motion capture system suitable for telerehabilitation with the cost - quality and precision - accessibility relations optimized. These particular characteristics achieved by efficiently using the state of the art of accessible generic technology in sensors and hardware, and adequate software for capture, transmission analysis and visualization, provides the capacity to offer good telerehabilitation services, reaching large more or less marginal populations where technologies and specialists are not available but accessible with basic communication networks.Keywords: inertial sensors, joint amplitude measurement, MEMS, telerehabilitation
Procedia PDF Downloads 2594830 Nursing and Allied Health Perception of Desirable Junior Doctor Attributes for Effective Collaboration and Teamwork
Authors: Maneka Marianne Britto, Hansraj Riteesh Bookun
Abstract:
The ability of a junior doctor to deliver complex multi-disciplinary care to patients in a paradigm of respect and collaboration requires a multitude of interpersonal skills and competencies. A short survey was used to explore the perspective of allied health staff on the desirable attributes of a junior doctor which are conducive to good teamwork. 23 allied health professionals (14 nurses, 4 physiotherapists, 2 dietitians, 1 occupational therapist, 1 speech therapist and 1 audiologist) responded to this 17-item survey. There were 17 females. The mean age of the respondents was 34.9 ± 10.1 years. The salient findings of our survey are that 95% of our respondents rated friendliness and non-clinical small talk with average importance or greater. 45% of them viewed these 2 items as very important or absolutely essential. A single respondent viewed these 2 items with little importance. The other criteria which were rated with high levels of importance were the acknowledgment of allied health suggestions and good ward organizational skills. Training these collaborative skills is challenging, and an enhanced understanding of interprofessional perspectives will help a junior doctor to achieve better clinical outcomes. It is hoped that this paper will further stimulate discussion in this area and will encourage junior doctors to engage in non-clinical conversations with allied health staff in the spirit of promoting effective teamwork.Keywords: allied health, collaboration, doctor, medicine, surgery
Procedia PDF Downloads 1304829 Investigation of User Position Accuracy for Stand-Alone and Hybrid Modes of the Indian Navigation with Indian Constellation Satellite System
Authors: Naveen Kumar Perumalla, Devadas Kuna, Mohammed Akhter Ali
Abstract:
Satellite Navigation System such as the United States Global Positioning System (GPS) plays a significant role in determining the user position. Similar to that of GPS, Indian Regional Navigation Satellite System (IRNSS) is a Satellite Navigation System indigenously developed by Indian Space Research Organization (ISRO), India, to meet the country’s navigation applications. This system is also known as Navigation with Indian Constellation (NavIC). The NavIC system’s main objective, is to offer Positioning, Navigation and Timing (PNT) services to users in its two service areas i.e., covering the Indian landmass and the Indian Ocean. Six NavIC satellites are already deployed in the space and their receivers are in the performance evaluation stage. Four NavIC dual frequency receivers are installed in the ‘Advanced GNSS Research Laboratory’ (AGRL) in the Department of Electronics and Communication Engineering, University College of Engineering, Osmania University, India. The NavIC receivers can be operated in two positioning modes: Stand-alone IRNSS and Hybrid (IRNSS+GPS) modes. In this paper, analysis of various parameters such as Dilution of Precision (DoP), three Dimension (3D) Root Mean Square (RMS) Position Error and Horizontal Position Error with respect to Visibility of Satellites is being carried out using the real-time IRNSS data, obtained by operating the receiver in both positioning modes. Two typical days (6th July 2017 and 7th July 2017) are considered for Hyderabad (Latitude-17°24'28.07’N, Longitude-78°31'4.26’E) station are analyzed. It is found that with respect to the considered parameters, the Hybrid mode operation of NavIC receiver is giving better results than that of the standalone positioning mode. This work finds application in development of NavIC receivers for civilian navigation applications.Keywords: DoP, GPS, IRNSS, GNSS, position error, satellite visibility
Procedia PDF Downloads 2134828 Uncloaking Priceless Pieces of Evidence: Psychotherapy with an Older New Zealand Man; Contributions to Understanding Hidden Historical Phenomena and the Trans-Generation Transmission of Silent and Un-Witnessed Trauma
Authors: Joanne M. Emmens
Abstract:
This paper makes use of the case notes of a single psychoanalytically informed psychotherapy of a now 72-year-old man over a four-year period to explore the potential of qualitative data to be incorporated into a research methodology that can contribute theory and knowledge to the wider professional community involved in mental health care. The clinical material arising out of any psychoanalysis provides a potentially rich source of clinical data that could contribute valuably to our historical understanding of both individual and societal traumata. As psychoanalysis is primarily an investigation, it is argued that clinical case material is a rich source of qualitative data which has relevance for sociological and historical understandings and that it can potentially aluminate important ‘gaps’ and collective blind spots that manifest unconsciously and are a contributing factor in the transmission of trauma, silently across generations. By attending to this case material the hope is to illustrate the value of using a psychoanalytic centred methodology. It is argued that the study of individual defences and the manner in which they come into consciousness, allows an insight into group defences and the unconscious forces that contribute to the silencing or un-noticing of important sources (or originators) of mental suffering.Keywords: dream furniture (Bion) and psychotic functioning, reverie, screen memories, selected fact
Procedia PDF Downloads 1994827 Generalized Extreme Value Regression with Binary Dependent Variable: An Application for Predicting Meteorological Drought Probabilities
Authors: Retius Chifurira
Abstract:
Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe.Keywords: generalized extreme value distribution, general linear model, mean annual rainfall, meteorological drought probabilities
Procedia PDF Downloads 2004826 Study of Effect of Gear Tooth Accuracy on Transmission Mount Vibration
Authors: Kalyan Deepak Kolla, Ketan Paua, Rajkumar Bhagate
Abstract:
Transmission dynamics occupy major role in customer perception of the product in both senses of touch and quality of sound. The quantity and quality of sound perceived is more concerned with the whine noise of the gears engaged. Whine noise is tonal in nature and tonal noises cause fatigue and irritation to customers, which in turn affect the quality of the product. Transmission error is the usual suspect for whine noise, which can be caused due to misalignments, tolerances, manufacturing variabilities. In-cabin noise is also more sensitive to the gear design. As the details of the gear tooth design and manufacturing are in microns, anything out of the tolerance zone, either in design or manufacturing, will cause a whine noise. This will also cause high variation in stress and deformation due to change in the load and leads to the fatigue failure of the gears. Hence gear design and development take priority in the transmission development process. This paper aims to study such variability by considering five pairs of helical spur gears and their effect on the transmission error, contact pattern and vibration level on the transmission.Keywords: gears, whine noise, manufacturing variability, mount vibration variability
Procedia PDF Downloads 1504825 Nitrous Oxide Wastage: Putting Strategies “In the Pipeline” to Reduce Carbon Emissions from Nitrous Oxide
Authors: F. Gallop, C. Ward, M. Zaky, M. Vaghela, R. Sabaratnam
Abstract:
Nitrous oxide (N₂O) has been used in anaesthesia for over 150 years owing to advantageous physical and pharmacological properties. However, with a global warming potential of 310, we have an urgent responsibility to reduce its usage and emission. Anecdotal evidence in our hospital trust suggests minimal N₂O usage, yet our theatres receive a staggering supply. This warranted further investigation. We used a data collection tool to prospectively capture quantitative and qualitative data regarding N₂O cases during one week: this recorded demographics, N₂O indications, clinical management, and total N₂O consumption in litres. In addition, N₂O usage in dental sedation suites and paediatric theatres was separately quantified. Pipeline supply data was acquired from British Oxygen Company accounts. We captured 490 cases. 4% (n=19) used N₂O, 63% (n=12) of these in dental theatres. Common N₂0 indications were induction speed (37%) and rapidly increasing anaesthesia depth (32%). In adult cases, N₂O was always used intraoperatively rather than solely at induction. 74% (n=14) of anaesthetists reported environmental concern over using N₂O. The week’s total N₂O usage was 8109 litres, amounting to 421,668 litres annually. However, the annual N₂O pipeline supply is 2,997,000 litres; an enormous 1.8 million Kg of CO₂. Our results supportively demonstrate that the N₂O pipeline supply greatly exceeds its clinical use. Acknowledging clinical areas not audited, the discrepancy between supply and usage suggests approximately 2.5 million litres of yearly wastage. We consequently recommend terminating the N₂O pipeline supply in minimally used areas, eliminating 1.5 million Kg of CO₂ emissions. High usage clinical areas could consider portable N₂O cylinders as an alternative. In Sweden, N₂O destruction technology is routinely used to minimise CO₂ emissions. Our results support National Health System investment in similar infrastructure.Keywords: anaesthesia, environment, medical gases, nitrous oxide, sustainability
Procedia PDF Downloads 1384824 English 2A Students’ Oral Presentation Errors: Basis for English Policy Revision
Authors: Marylene N. Tizon
Abstract:
English instructors pay attention on errors committed by students as errors show whether they know or master their oral skills and what difficulties they may have in the process of learning the English language. This descriptive quantitative study aimed at identifying and categorizing the oral presentation errors of the purposively chosen 118 English 2A students enrolled during the first semester of school year 2013 – 2014. The analysis of the data for this study was undertaken using the errors committed by the students in their presentation. Marking and classifying of errors were made by first classifying them into linguistic grammatical errors then all errors were categorized further into Surface Structure Errors Taxonomy with the use of Frequency and Percentage distribution. From the analysis of the data, the researcher found out: Errors in tenses of the verbs (71 or 16%) and in addition 167 or 37% were most frequently uttered by the students. And Question and negation mistakes (12 or 3%) and misordering errors (28 or 7%) were least frequently enunciated by the students. Thus, the respondents in this study most frequently enunciated errors in tenses and in addition while they uttered least frequently the errors in question, negation, and misordering.Keywords: grammatical error, oral presentation error, surface structure errors taxonomy, descriptive quantitative design, Philippines, Asia
Procedia PDF Downloads 3924823 Clinical Audit of Selected Nephrology Nursing Procedures Performed in Nephrology Unit of AIIMS with a View to Develop Nephrology Nursing Procedure Protocol
Authors: Mamta Thakur, Dr. Shashi Mawar, Ms. Levis Murry, Dr. D.k.sharma
Abstract:
Aim: The aim of this study is to develop nephrology nursing procedure protocol after clinical audit of current nephrology nursing practices. Materials and methods: This descriptive observational study was conducted on 40 nurses who were working in Nephrology Department of AIIMS, New Delhi to observe their current practices to assess the existing gaps in the practice. The nurses were enrolled through total enumerative sampling. Sociodemographic profile of nurses and clinical profile for site of procedure was collected. Observation checklist was formed on the basis of standard nursing practices, which included 7 dimensions for hemodialysis procedure and 3 dimensions for procedure of assisting renal biopsy. Based on the gaps identified, nephrology nursing procedure protocol will be developed. Nurses were observed during two shifts, and each nurse was observed once. Scoring of items were done in each dimension, and for acceptable practices, nurses have to score ≥80% in each dimension. Results: Data was analyzed using descriptive statistics. Majority of nurses (73.7%) in nephrology ward and (80.9%) in hemodialysis unit have not undergone any special training in nephrology. Most of nurses (80.9%) followed the acceptable nursing practices for procedure of connection for hemodialysis. None of nurses followed the acceptable level (≥80%) of nursing practices for the procedure of predialysis assessment, the procedure for site preparation, during dialysis assessment and post dialysis assessment. None (100%) showed the acceptable level of nursing practices for all the dimensions of assisting renal biopsy procedure. Nephrology nursing procedure protocol was developed by researcher following a rigorous process, and this will reduce the gaps in the nursing practice. Conclusion: Clinical audit found that there were gaps in the existing nursing practices compared to the standardised nursing practices for procedure of hemodialysis and assisting renal biopsy, and these gaps have been addressed by the development of the protocol.Keywords: nursing practice, nephrology nursing procedure, nursing protocol, renal biopsy, hemodialysis
Procedia PDF Downloads 1024822 Comparative Study of Accuracy of Land Cover/Land Use Mapping Using Medium Resolution Satellite Imagery: A Case Study
Authors: M. C. Paliwal, A. K. Jain, S. K. Katiyar
Abstract:
Classification of satellite imagery is very important for the assessment of its accuracy. In order to determine the accuracy of the classified image, usually the assumed-true data are derived from ground truth data using Global Positioning System. The data collected from satellite imagery and ground truth data is then compared to find out the accuracy of data and error matrices are prepared. Overall and individual accuracies are calculated using different methods. The study illustrates advanced classification and accuracy assessment of land use/land cover mapping using satellite imagery. IRS-1C-LISS IV data were used for classification of satellite imagery. The satellite image was classified using the software in fourteen classes namely water bodies, agricultural fields, forest land, urban settlement, barren land and unclassified area etc. Classification of satellite imagery and calculation of accuracy was done by using ERDAS-Imagine software to find out the best method. This study is based on the data collected for Bhopal city boundaries of Madhya Pradesh State of India.Keywords: resolution, accuracy assessment, land use mapping, satellite imagery, ground truth data, error matrices
Procedia PDF Downloads 5074821 Creation of a Clinical Tool for Diagnosis and Treatment of Skin Disease in HIV Positive Patients in Malawi
Authors: Alice Huffman, Joseph Hartland, Sam Gibbs
Abstract:
Dermatology is often a neglected specialty in low-resource settings, despite the high morbidity associated with skin disease. This becomes even more significant when associated with HIV infection, as dermatological conditions are more common and aggressive in HIV positive patients. African countries have the highest HIV infection rates and skin conditions are frequently misdiagnosed and mismanaged, because of a lack of dermatological training and educational material. The frequent lack of diagnostic tests in the African setting renders basic clinical skills all the more vital. This project aimed to improve diagnosis and treatment of skin disease in the HIV population in a district hospital in Malawi. A basic dermatological clinical tool was developed and produced in collaboration with local staff and based on available literature and data collected from clinics. The aim was to improve diagnostic accuracy and provide guidance for the treatment of skin disease in HIV positive patients. A literature search within Embase, Medline and Google scholar was performed and supplemented through data obtained from attending 5 Antiretroviral clinics. From the literature, conditions were selected for inclusion in the resource if they were described as specific, more prevalent, or extensive in the HIV population or have more adverse outcomes if they develop in HIV patients. Resource-appropriate treatment options were decided using Malawian Ministry of Health guidelines and textbooks specific to African dermatology. After the collection of data and discussion with local clinical and pharmacy staff a list of 15 skin conditions was included and a booklet created using the simple layout of a picture, a diagnostic description of the disease and treatment options. Clinical photographs were collected from local clinics (with full consent of the patient) or from the book ‘Common Skin Diseases in Africa’ (permission granted if fully acknowledged and used in a not-for-profit capacity). This tool was evaluated by the local staff, alongside an educational teaching session on skin disease. This project aimed to reduce uncertainty in diagnosis and provide guidance for appropriate treatment in HIV patients by gathering information into one practical and manageable resource. To further this project, we hope to review the effectiveness of the tool in practice.Keywords: dermatology, HIV, Malawi, skin disease
Procedia PDF Downloads 2034820 A New Cytoprotective Drug on the Basis of Cytisine: Phase I Clinical Trial Results
Authors: B. Yermekbayeva, A. Gulyayaev, T. Nurgozhin, C. Bektur
Abstract:
Cytisine aminophosphonate under the name "Cytafat" was approved for clinical trials in Republic of Kazakhstan as a putative liver protecting drug for the treatment of acute toxic hepatitis. A method of conducting the clinical trial is a double blind study. Total number of patients -71, aged from 16 to 56 years. Research on healthy volunteers determined the maximal tolerable doze of "Cytafat" as 200 mg/kg. Side effects when administered at high dozes (100-200 mg/kg) are tachycardia and increase of arterial blood pressure. The drug is tested in the treatment of 28 patients with a syndrome of hepatocellular failure (a poisoning with substitutes of alcohol, rat poison, or medical products). "Cytafat" was intravenously administered at a dose of 10 mg/kg in 200 ml of 5 % glucose solution once daily. The number of administrations: 1-3. In the comparison group, 23 patients were treated intravenously once a day with “Essenciale H” at a dose of 10 ml. 20 patients received a placebo (10 ml of glucose intravenously). In all cases of toxic hepatopathology the significant positive clinical effect of the testing drug distinguishable from placebo and surpassing the alternative was observed. Within a day after administration a sharp reduction of cytolitic syndrome parameters (ALT, AST, alkaline phosphatase, thymol turbidity test, GGT) was registered, a reduction of the severity of cholestatic syndrome (bilirubin decreased) was recorded, significantly decreased indices of lipid peroxidation. The following day, in all cases the positive dynamics was determined with ultrasound study (reduction of diffuse changes and events of reactive pancreatitis), hepatomegaly disappeared. Normalization of all parameters occurred in 2-3 times faster, than when using the drug "Essenciale H" and placebo. Average term of elimination of toxic hepatopathy when using the drug "Cytafat" -2,8 days, "Essenciale H" -7,2 days, and placebo -10,6 days. The new drug "Cytafat" has expressed cytoprotective properties.Keywords: cytisine, cytoprotection, hepatopathy, hepatoprotection
Procedia PDF Downloads 3674819 Machine Learning Approach for Automating Electronic Component Error Classification and Detection
Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski
Abstract:
The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.Keywords: augmented reality, machine learning, object recognition, virtual laboratories
Procedia PDF Downloads 1344818 Optimization of Assay Parameters of L-Glutaminase from Bacillus cereus MTCC1305 Using Artificial Neural Network
Authors: P. Singh, R. M. Banik
Abstract:
Artificial neural network (ANN) was employed to optimize assay parameters viz., time, temperature, pH of reaction mixture, enzyme volume and substrate concentration of L-glutaminase from Bacillus cereus MTCC 1305. ANN model showed high value of coefficient of determination (0.9999), low value of root mean square error (0.6697) and low value of absolute average deviation. A multilayer perceptron neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model and its topology was obtained as 5-3-1 after applying Levenberg Marquardt (LM) training algorithm. The predicted activity of L-glutaminase was obtained as 633.7349 U/l by considering optimum assay parameters, viz., pH of reaction mixture (7.5), reaction time (20 minutes), incubation temperature (35˚C), substrate concentration (40mM), and enzyme volume (0.5ml). The predicted data was verified by running experiment at simulated optimum assay condition and activity was obtained as 634.00 U/l. The application of ANN model for optimization of assay conditions improved the activity of L-glutaminase by 1.499 fold.Keywords: Bacillus cereus, L-glutaminase, assay parameters, artificial neural network
Procedia PDF Downloads 4294817 The Role of Maladaptive Personality Traits in Obesity Treatment – Quantitative Study
Authors: Judita Konečná, Dagmar Halo, Martin Matoulek
Abstract:
Background: Personality pathology does not have to be a contraindication nor an obstacle in obesity treatment, or eventually, surgical treatment. Detection of specific maladaptive personality traits can help us understand the manner of behavior leading to obesity as well as to address the treatment better. Objective: Using The Personality Inventory for DSM-5 (PID-5) in combination with clinical interviews with the goal of gaining a psychological evaluation to set the treatment procedure. Data was collected from more than 400 patients to detect differences in constellations of maladaptive personality traits based on BMI, DM2 and gender. Conclusions: Besides the fact that a psychological evaluation can help address the treatment better, analyses showed that it is also useful to detect specific groups of patients. Implications for clinical practice are discussed, as well as recommendations for group education programs based on quantitative research.Keywords: bariatric surgery, obesity, personality traits, PID-5, treatment
Procedia PDF Downloads 2284816 The Impact of Centralisation on Radical Prostatectomy Outcomes: Our Outcomes
Authors: Jemini Vyas, Oluwatobi Adeyoe, Jenny Branagan, Chandran Tanabalan, John Beatty, Aakash Pai
Abstract:
Introduction: The development of robotic surgery has accelerated centralisation to tertiary centres, where robotic radical prostatectomy (RP) is offered. The purpose of concentrating treatment in high volume specialist centres is to improve the quality of care and patient outcomes. The aim of this study was to assess the impact on clinical outcomes of centralisation for locally diagnosed patients undergoing RP. Methods: Clinical outcomes for 169 consecutive laparoscopic & open RP pre-centralisation were retrospectively compared with 50 consecutive robotic RP conducted over a similar period post-centralisation. Preoperative risk stratification and time to surgery were collected. Perioperative outcomes, including length of stay (LOS) and complications, were collated. Post-operative outcomes, including erectile dysfunction (ED), biochemical recurrence (BCR), and urinary continence, were assessed. Results: Preoperative risk stratification showed no difference between the two groups. The median time from diagnosis to treatment was similar between the two groups (pre-centralisation, 121 days, post-centralisation, 117 days). The mean length of stay (pre-centralisation, 2.1 days, post-centralisation, 1.6 days) showed no significant difference (p=0.073). Proportion of overall complications (pre-centralisation, 11.4%, post-centralisation, 8.7%) and complications, above Clavien-Dindo 2, were similar between the two groups (pre-centralisation1.2%, post-centralisation 2.2%). Post operative functional parameters, including continence and ED, were comparable. Five-year BCR free rate was 78% for the pre-centralisation group and 79% for the post centralisation group. Conclusion: For our cohort of patients, clinical outcomes have remained static during centralisation. It is imperative that centralisation is accompanied by increased capacity, streamlining of pathways, and training to ensure that improved quality of care is achieved. Our institution has newly acquired a robot, and prospectively studying this data may support the reversal of centralisation for RP surgery.Keywords: prostate, cancer, prostatectomy, clinical
Procedia PDF Downloads 944815 Design of Parity-Preserving Reversible Logic Signed Array Multipliers
Authors: Mojtaba Valinataj
Abstract:
Reversible logic as a new favorable design domain can be used for various fields especially creating quantum computers because of its speed and intangible power consumption. However, its susceptibility to a variety of environmental effects may lead to yield the incorrect results. In this paper, because of the importance of multiplication operation in various computing systems, some novel reversible logic array multipliers are proposed with error detection capability by incorporating the parity-preserving gates. The new designs are presented for two main parts of array multipliers, partial product generation and multi-operand addition, by exploiting the new arrangements of existing gates, which results in two signed parity-preserving array multipliers. The experimental results reveal that the best proposed 4×4 multiplier in this paper reaches 12%, 24%, and 26% enhancements in the number of constant inputs, number of required gates, and quantum cost, respectively, compared to previous design. Moreover, the best proposed design is generalized for n×n multipliers with general formulations to estimate the main reversible logic criteria as the functions of the multiplier size.Keywords: array multipliers, Baugh-Wooley method, error detection, parity-preserving gates, quantum computers, reversible logic
Procedia PDF Downloads 2594814 The Use of Phototherapy with Unusual Case Studies in Counselling
Authors: Briar Schulz
Abstract:
The use of phototherapy within the counselling room offers significant advantages in extending far beyond typical "talk therapy" avenues. The benefits of using this approach are numerous and include: efficiency in recalling pertinent information in addition to utilizing a visual lens that often captures opulent detail that can be eluded in traditional dialogue. The goal of this presentation is to provide conference attendees with an opportunity to understand the therapeutic benefits and creative possibilities of incorporating photography into the clinical counselling process. This includes practical strategies for using in specific case studies, where studies of phototherapy have previously been limited. Ethical considerations and limitations to the process will also be addressed. Attendees will observe the benefits of using phototherapy with six longitudinal case studies including: a 30 year old female, with anorexia nervosa; a 22 year old self-harming individual with obsessive compulsive disorder; a 24 year old client with developmental delays, and bipolar disorder; a 14 year old client with Autism; and two clients with rare medical conditions struggling with depression and anxiety, one 21 years old and the other 16 years old. Aspects of each case will be linked to various theoretical modalities to highlight the efficiency and benefits of phototherapy in drawing important clinical conclusions. Furthermore, the use of phototherapy within these clinical areas remains a relatively unexplored area of the literature, and possibilities for future research will be highlighted. Finally, conference attendees will have the opportunity to try various phototherapy strategies within the interactive portion of this presentation. .Keywords: Atypical, Case studies, Phototherapy, Photovoice
Procedia PDF Downloads 149