Search results for: severity identification

Authors: Shin-Hyung Cho, Dong-Kyu Kim, Seung-Young Kho

Abstract:

Truck-involved crashes have higher crash severity than non-truck-involved crashes. There have been many studies about the frequency of crashes and the development of severity models, but those studies only analyzed the relationship between observed variables. To identify why more people are injured or killed when trucks are involved in the crash, we must examine to quantify the complex causal relationship between severity of the crash and risk factors by adopting the latent factors of crashes. The aim of this study was to develop a structural equation or model based on truck-involved and non-truck-involved crashes, including five latent variables, i.e. a crash factor, environmental factor, road factor, driver’s factor, and severity factor. To clarify the unique characteristics of truck-involved crashes compared to non-truck-involved crashes, a confirmatory analysis method was used. To develop the model, we extracted crash data from 10,083 crashes on Korean freeways from 2008 through 2014. The results showed that the most significant variable affecting the severity of a crash is the crash factor, which can be expressed by the location, cause, and type of the crash. For non-truck-involved crashes, the crash and environment factors increase severity of the crash; conversely, the road and driver factors tend to reduce severity of the crash. For truck-involved crashes, the driver factor has a significant effect on severity of the crash although its effect is slightly less than the crash factor. The multiple group analysis employed to analyze the differences between the heterogeneous groups of drivers.

Keywords: crash severity, structural structural equation modeling (SEM), truck-involved crashes, multiple group analysis, crash on freeway

Procedia PDF Downloads 357

Authors: Biniam Seifu Debelo, Bheema Lingaiah Thamineni, Hanumesh Kumar Dasari, Ahmed Ali Dawud

Abstract:

Background: One of the most frequent neurological conditions in newborns is neonatal seizures, which may indicate severe neurological dysfunction. They may be caused by a broad range of problems with the central nervous system during or after pregnancy, infections, brain injuries, and/or other health conditions. These seizures may have very subtle or very modest clinical indications because patterns like oscillatory (spike) trains begin with relatively low amplitude and gradually increase over time. This becomes very challenging and erroneous if clinical observation is the primary basis for identifying newborn seizures. Objectives: In this study, a diagnosis system using deep convolutional neural networks is proposed to determine and classify the severity level of neonatal seizures using multichannel neonatal EEG data. Methods: Clinical multichannel EEG datasets were compiled using datasets from publicly accessible online sources. Various preprocessing steps were taken, including converting 2D time series data to equivalent waveform pictures. The proposed models underwent training, and their performance was evaluated. Results: The proposed CNN was used to perform binary classification with an accuracy of 92.6%, F1-score of 92.7%, specificity of 92.8%, and precision of 92.6%. To detect newborn seizures, this model is utilized. Using the proposed CNN model, multiclassification was performed with accuracy rates of 88.6%, specificity rates of 92.18%, F1-score rates of 85.61%, and precision rates of 88.9%. A multiclassification model is used to classify the severity level of neonatal seizures. The results demonstrated that the suggested strategy can assist medical professionals in making accurate diagnoses close to healthcare institutions. Conclusion: The developed system was capable of detecting neonatal seizures and has the potential to be used as a decision-making tool in resource-limited areas with a scarcity of expert neurologists.

Keywords: CNN, multichannel EEG, neonatal seizure, severity identification

Procedia PDF Downloads 7

Authors: Ruhollah Heydari Sheikh Ahmad, Sara Alaie Khoraem

Abstract:

Introduction: Substance use disorder is conceptualized as a chronic relapsing condition where relapse is usually defined as the return to problematic substance use following treatment. An issue of great importance is the identification of the predictors of relapse and the development of treatments that may help prevent relapse. One of the strongest predictors of relapse is craving. The purpose of the present study was to study the effect of anxiety, anxiety sensitivity, and coping motives on craving. Materials and method: Participants (n=74) were male opiate users recruited from a semi-private clinic providing de-toxification and treatment services for substance users. Anxiety, anxiety sensitivity, coping motives and craving were assessed using relevant questionnaires. The addiction severity index was used to assess addiction severity. Results: All patients were methadone maintained and one year after detoxification, 36 patients (48.64%) relapsed. Stress and anxiety, anxiety sensitivity, addiction severity and coping motives predicted craving and relapse. Anxiety sensitivity specifically predicted early relapse. Conclusion: Substance use is a severe mental disorder, with high relapse rates. Substance users high in anxiety sensitivity are particularly prone to relapse during the first six months of treatment. Addiction severity and coping motives need to be taken into account when providing interventional services for substance users. Findings imply the significance of additional psychological attention to methadone maintained patients to prevent craving and relapse.

Keywords: anxiety sensitivity, coping motives, relapse, substance use craving

Procedia PDF Downloads 268

Authors: Niladri Sekhar Barma, Satish Dhandole

Abstract:

Damage identification in the context of safety, nowadays, has become a fundamental research interest area in the field of mechanical, civil, and aerospace engineering structures. The following research is aimed to identify damage in a mechanical beam structure and quantify the severity or extent of damage in terms of loss of stiffness, and obtain an updated analytical Finite Element (FE) model. An FE model is used for analysis, and the location of damage for single and multiple damage cases is identified numerically using the modal strain energy method and mode shape curvature method. Experimental data has been acquired with the help of an accelerometer. Fast Fourier Transform (FFT) algorithm is applied to the measured signal, and subsequently, post-processing is done in MEscopeVes software. The two sets of data, the numerical FE model and experimental results, are compared to locate the damage accurately. The extent of the damage is identified via modal frequencies using a mixed numerical-experimental technique. Mode shape comparison is performed by Modal Assurance Criteria (MAC). The analytical FE model is adjusted by the direct method of model updating. The same study has been extended to some real-life structures such as plate and GARTEUR structures.

Keywords: damage identification, damage quantification, damage detection using modal analysis, structural damage identification

Procedia PDF Downloads 89

Authors: Arefeh Lotfi, Mahdi Babaei, Ayda Mashhadizadeh, Samira Nikpour, Morteza Bagheri

Abstract:

The main objective of this study is to investigate the key factors in accidents’ severity at rail-road level crossings. The data required for this study is obtained from both accident and inventory database of Iran Railways during 2009-2015. The Ordered Probit model is developed using SPSS software to identify the significant factors in the accident severity at rail-road level crossings. The results show that 'train speed', 'vehicle type' and 'weather' are the most important factors affecting the severity of the accident. The results of these studies assist to allocate resources in the right place. This paper suggests mandating the regulations to reduce train speed at rail-road level crossings in bad weather conditions to improve the safety of rail-road level crossings.

Keywords: rail-road level crossing, ordered probit model, accidents’ severity, significant factors

Procedia PDF Downloads 127

Authors: Islem Kedidi, Rihab Bedoui Bensalem, Faysal Manssouri

Abstract:

In traditional models of insurance data, the number and size of claims are assumed to be independent. Relaxing the independence assumption, this article explores the Vine copula to model dependence structure between multivariate frequency and average severity of insurance claim. To illustrate this approach, we use the Wisconsin local government property insurance fund which offers several insurance protections for motor vehicles, property and contractor’s equipment claims. Results show that the C-vine copula can better characterize the multivariate dependence structure between frequency and severity. Furthermore, we find significant dependencies especially between frequency and average severity among different coverage types.

Keywords: dependency modeling, government insurance, insurance claims, vine copula

Procedia PDF Downloads 182

Authors: A. Alhusban, M. Alqawasmeh, F. Alfawares

Abstract:

Introduction: Diabetes is a chronic health problem and a major risk factor of stroke. A number of therapeutic modalities exist for diabetes management. It’s still unknown whether the different oral hypoglycemic agents would ameliorate the detrimental effect of diabetes on stroke severity. The objective of this work is to assess the effect of pretreatment with oral hypoglycemic agents, insulin and their combination on stroke severity at presentation. Patients and Methods: Patients admitted to the King Abdullah University Hospital (KAUH)-Jordan with ischemic stroke between January 2015 and December 2016 were evaluated and their comorbid diseases, treatment on admission and their neurologic severity was assessed using the National Institute of Health Stroke Scale (NIHSS) were documented. Stroke severity was compared for non-diabetic patients and diabetic patients treated with different antidiabetic agents. Results: Data from 324 patients with acute stroke was documented. The median age of participants was 69 years. Diabetes was documented in about 50% of the patients. Multinomial regression analysis identified diabetes treatment status as an independent predictor of neurological severity of stroke (p=0.032). Patients treated with oral hypoglycemic agents had a significantly lower NIHSS as compared to nondiabetic patients and insulin treated patients (p < 0.02). The positive effect of oral hypoglycemic agents was blunted by insulin co-treatment. Insulin did not alter the severity of stroke as compared to non-diabetics. Conclusion: Oral hypoglycemic agents may reduce the severity of neurologic deficit of ischemic stroke and may have neuroprotective effect.

Keywords: diabetes, stroke, neuroprotection, oral hypoglycemic agents

Procedia PDF Downloads 140

Authors: Sharmila Rathee

Abstract:

Individuals with disability/ies often face negative attitudes, discrimination, exclusion, and inequality of treatment due to stigmatization and stigmatized treatment. While a significant number of studies in field of stigma suggest that group-identification has positive consequences for stigmatized individuals, ironically very miniscule empirical work in sight has attempted to investigate in-group identification as a coping measure against stigma, humiliation and related experiences among disability group. In view of death of empirical research on in-group identification among disability group, through present work, an attempt has been made to examine the experiences of stigma, humiliation, and in-group identification among disability group. Results of the study suggest that use of in-group identification as a coping strategy is not uniform across members of disability group and degree of in-group identification differs across different sub-groups of disability groups. Further, in-group identification among members of disability group depends on variables like degree and impact of disability, factors like onset of disability, nature, and visibility of disability, educational experiences and resources available to deal with disabling conditions.

Keywords: disability, stigma, in-group identification, social identity

Procedia PDF Downloads 294

Authors: Mohd Azraei Pangah Pa'at, Mohd Ruzlin Mohd Mokhtar, Norhidayu Rameli, Tashia Marie Anthony, Huzainie Shafi Abd Halim

Abstract:

Partial Discharge (PD) diagnostic mapping testing is one of the main diagnostic testing techniques that are widely used in the field or onsite testing for underground power cable in medium voltage level. The existence of PD activities is an early indication of insulation weakness hence early detection of PD activities can be determined and provides an initial prediction on the condition of the cable. To effectively manage the results of PD Mapping test, it is important to have acceptable criteria to facilitate prioritization of mitigation action. Tenaga Nasional Berhad (TNB) through Distribution Network (DN) division have developed PD severity model name Severity Index (SI) for offline PD mapping test since 2007 based on onsite test experience. However, this severity index recommendation action had never been revised since its establishment. At presence, PD measurements data have been extensively increased, hence the severity level indication and the effectiveness of the recommendation actions can be analyzed and verified again. Based on the new revision, the recommended action to be taken will be able to reflect the actual defect condition. Hence, will be accurately prioritizing preventive action plan and minimizing maintenance expenditure.

Keywords: partial discharge, severity index, diagnostic testing, medium voltage, power cable

Procedia PDF Downloads 159

Authors: Mustapha Aminu Bagiwa, Ainuddin Wahid Abdul Wahab, Mohd Yamani Idna Idris, Suleman Khan

Abstract:

Video source device identification has become a problem of concern in numerous domains especially in multimedia security and digital investigation. This is because videos are now used as evidence in legal proceedings. Source device identification aim at identifying the source of digital devices using the content they produced. However, due to affordable processing tools and the influx in digital content generating devices, source device identification is still a major problem within the digital forensic community. In this paper, we discuss source device identification for digital videos by identifying techniques that were proposed in the literature for model or specific device identification. This is aimed at identifying salient open challenges for future research.

Keywords: video forgery, source camcorder, device identification, forgery detection

Procedia PDF Downloads 606

Authors: Martin Goubej, Tomas Popule, Alois Krejci

Abstract:

This paper deals with experimental identification of mechanical systems with nonlinear friction characteristics. Dynamic LuGre friction model is adopted and a systematic approach to parameter identification of both linear and nonlinear subsystems is given. The identification procedure consists of three subsequent experiments which deal with the individual parts of plant dynamics. The proposed method is experimentally verified on an industrial-grade robotic manipulator. Model fidelity is compared with the results achieved with a static friction model.

Keywords: mechanical friction, LuGre model, friction identification, motion control

Procedia PDF Downloads 391

Authors: Fatemeh Keshavarz

Abstract:

Background: Rheumatoid arthritis (RA) is one of the most common autoimmune diseases, often leading to joint damage and physical disability. This study aimed to investigate the relationship of serum levels of interleukin 17 and anti-CCP factor with disease severity in RA patients. Materials and Methods: Fifty-four patients with RA confirmed by clinical and laboratory criteria were recruited. A 5 ml venous blood sample was taken from every patient, its serum was separated. Based on clinical data and severity of symptoms, patients were classified into three groups of those with mild, moderate, and severe symptoms. Serum levels of IL-17 and anti-CCP in all samples were measured using ELISA. Results: Analysis of IL-17 serum levels in different groups showed that its amount was higher in the group with mild clinical symptoms than in other groups. Comparison of IL-17 serum levels between mild and moderate disease severity groups showed a statistically significant relationship. There was also a positive linear relationship between anti-CCP and serum IL-17 levels in different groups of the disease, and serum IL-17 levels were inversely related to the duration of exposure to the disease. Conclusion: Higher IL-17 serum levels in patients with mild symptom severity confirm that this highly specific marker is involved in the pathogenesis of RA and may be effective in initiating patients’ clinical symptoms.

Keywords: IL-17, anti-CCP, rheumatoid arthritis, autoimmune

Procedia PDF Downloads 116

Authors: A. Brouri, F. Giri, A. Mkhida, A. Elkarkri, M. L. Chhibat

Abstract:

Standard Hammerstein-Wiener models consist of a linear subsystem sandwiched by two memoryless nonlinearities. Presently, the linear subsystem is allowed to be parametric or not, continuous- or discrete-time. The input and output nonlinearities are polynomial and may be noninvertible. A two-stage identification method is developed such the parameters of all nonlinear elements are estimated first using the Kozen-Landau polynomial decomposition algorithm. The obtained estimates are then based upon in the identification of the linear subsystem, making use of suitable pre-ad post-compensators.

Keywords: nonlinear system identification, Hammerstein-Wiener systems, frequency identification, polynomial decomposition

Procedia PDF Downloads 485

Authors: Sun Shi, Sun Cheng

Abstract:

The pedestrian corridor is the most crowded area in the public space. The crowded severity has been focused on the field of evacuation strategies of the entrance in large public spaces. The aim of this paper is to analyze the walking efficiency in different spaces of pedestrian corridor with the variation of spatial parameters. The congestion condition caused by the variation of walking efficiency is modeled as well. This study established the space model of the walking corridor by setting the width, slope, turning form and turning angle of the pedestrian corridor. The pedestrian preference of walking mode varied with the difference of the crowded severity, walking speed, field of vision, sight direction and the expected destination, which is influenced by the characters of physical space form. Swarm software is applied to build Agent model. According to the output of the Agent model, the relationship between the pedestrian corridor width, ground slope, turning forms, turning angle and the walking efficiency, crowded severity is acquired. The results of the simulation can be applied to pedestrian corridor design in order to reduce the crowded severity and the potential safety risks caused by crowded people.

Keywords: crowded severity, multi-agent, pedestrian preference, urban space design

Procedia PDF Downloads 193

Authors: Meryem Saban Guler, Saniye Bilici

Abstract:

Malnutrition is a problem that significantly affects patients with cancer throughout the course of their illness, and it may be present from the moment of diagnosis until the end of treatment. We searched electronic databases using key terms such as ‘malnutrition in cancer patients’ or ‘nutritional status in cancer’ or ‘nutritional screening tools’ etc. Decline in nutritional status and continuing weight loss are associated with an increase in number and severity of complications, impaired quality of life and decreased survival rate. Nutrition is an important factor in the treatment and progression of cancer. Cancer patients are particularly susceptible to nutritional depletion due to the combined effects of the malignant disease and its treatment. With increasing incidence of cancer, identification and management of nutritional deficiencies are needed. Early identification of malnutrition, is substantial to minimize or prevent undesirable outcomes throughout clinical course. In determining the nutritional status; food consumption status, anthropometric methods, laboratory tests, clinical symptoms, psychosocial data are used. First-line strategies must include routine screening and identification of inpatients or outpatients at nutritional risk with the use of a simple and standardized screening tool. There is agreement among international nutrition organizations and accredited health care organizations that routine nutritional screening should be a standard procedure for every patient admitted to a hospital. There are f management of all cancer patients therefore routine nutritional screening with validated tools can identify cancer patients at risk.

Keywords: cancer, malnutrition, nutrition, nutritional screening

Procedia PDF Downloads 182

Authors: Mohammad Hossein Harirchian, Siavash Babaie, Nika keshtkaran, Sama Bitarafan

Abstract:

Background: Fatigue is a common complaint of multiple sclerosis (MS) patients, adversely affecting their quality of life. There is a lot of evidence showing that Carnitine deficiency is linked to fatigue development and severity in some conditions. This study aimed to compare the levels of Free L-Carnitine (FLC) between MS patients and healthy people and evaluate its association with the severity of fatigue. Methods: This case-control study included 30 patients with relapsing-remitting MS (RRMS) in 2 sex-matched equal-number groups according to the presence or absence of fatigue and 30 sex-matched healthy people in the control group. In addition, between two patient groups, we compared Serum level of FLC between the patient and healthy group. Fatigue was scored using two valid questionnaires of fatigue Severity Scale (FSS) and Modified Fatigue Impact Scale (MFIS). In addition, association between Serum level of FLC and fatigue severity was evaluated in MS patients. Results: There was no significant difference in serum levels of FLC between MS patients and healthy people. The patients with fatigue had a significantly lower FLC (mg/dl) value than patients without fatigue (22.53 ± 15.84 vs. 75.36 ± 51.98, P < 0.001). The mean value of FSS and MFIS in patients with fatigue were 48.80±8.55 and 62.87 ± 13.63, respectively, which was nearly two-fold higher than group without fatigue (P < 0.001). There was a negative correlation between the serum level of FLC and fatigue severity scales (Spearman rank correlation= 0.76, P < 0.001). Conclusion: We showed healthy people and MS patients were not different in levels of FLC. In addition, patients with lower serum levels of FLC might experience more severe fatigue. Therefore, this could clarify that supplementation with L-Carnitine might be considered as a complementary treatment for MS-related fatigue.

Keywords: fatigue, multiple sclerosis, L-carnitine, modified fatigue impact scale

Procedia PDF Downloads 119

Authors: A: Asmawi, L. S. Affendey, N. I. Udzir, R. Mahmod

Abstract:

The topic of enhancing security in XML databases is important as it includes protecting sensitive data and providing a secure environment to users. In order to improve security and provide dynamic access control for XML databases, we presented XLog file to calculate user trust values by recording users’ bad transaction, errors and query severities. Severity-aware trust-based access control for XML databases manages the access policy depending on users' trust values and prevents unauthorized processes, malicious transactions and insider threats. Privileges are automatically modified and adjusted over time depending on user behaviour and query severity. Logging in database is an important process and is used for recovery and security purposes. In this paper, the Xlog file is presented as a dynamic and temporary log file for XML databases to enhance the level of security.

Keywords: XML database, trust-based access control, severity-aware, trust values, log file

Procedia PDF Downloads 281

Authors: Ghirmay Teklemicheal, Samsom Mehari, Sara Tesfay

Abstract:

Objectives: A total of 1074 suspected chikungunya cases were reported in Tesseney Province, Gash Barka region, Eritrea, during an outbreak. This study was aimed to assess the possible association of chikungunya severity among ABO blood groups and other potential determinants. Methods: A sex-matched and age-matched case-control study was conducted during the outbreak. For each case, one control subject had been selected from the mild Chikungunya cases. Along the same line of argument, a second control subject had also been designated through which neighborhood of cases were analyzed, scrutinized, and appeared to the scheme of comparison. Time is always the most sacrosanct element in pursuance of any study. According to the temporal calculation, this study was pursued from October 15, 2018, to November 15, 2018. Coming to the methodological dependability, calculating odds ratios (ORs) and conditional (fixed-effect) logistic regression methods were being applied. As a consequence of this, the data was analyzed and construed on the basis of the aforementioned methodological systems. Results: In this outbreak, 137 severe suspected chikungunya cases and 137 mild chikungunya suspected patients, and 137 controls free of chikungunya from the neighborhood of cases were analyzed. Non-O individuals compared to those with O blood group indicated as significant with a p-value of 0.002. Separate blood group comparison among A and O blood groups reflected as significant with a p-value of 0.002. However, there was no significant difference in the severity of chikungunya among B, AB, and O blood groups with a p-value of 0.113 and 0.708, respectively, and a strong association of chikungunya severity was found with hypertension and diabetes (p-value of < 0.0001); whereas, there was no association between chikungunya severity and asthma with a p-value of 0.695 and also no association with pregnancy (p-value =0.881), ventilator (p-value =0.181), air conditioner (p-value = 0.247), and didn’t use latrine and pit latrine (p-value = 0.318), among individuals using septic and pit latrine (p-value = 0.567) and also among individuals using flush and pit latrine (p-value = 0.194). Conclusions: Non- O blood groups were found to be at risk more than their counterpart O blood group individuals with severe form of chikungunya disease. By the same token, individuals with chronic disease were more prone to severe forms of the disease in comparison with individuals without chronic disease. Prioritization is recommended for patients with chronic diseases and non-O blood group since they are found to be susceptible to severe chikungunya disease. Identification of human cell surface receptor(s) for CHIKV is quite necessary for further understanding of its pathophysiology in humans. Therefore, molecular and functional studies will necessarily be helpful in disclosing the association of blood group antigens and CHIKV infections.

Keywords: Chikungunya, Chikungunya virus, disease outbreaks, case-control studies, Eritrea

Procedia PDF Downloads 134

Authors: Yogendra K. Karna, Lauren T. Bennett

Abstract:

Fire-tolerant eucalypt forests are one of the major forest ecosystems of south-eastern Australia and thought to be highly resistant to frequent high severity wildfires. However, the impact of different severity wildfires on the canopy structure of fire-tolerant forest type is under-studied, and there are significant knowledge gaps in relation to the assessment of tree and stand level canopy structural dynamics and recovery after fire. Assessment of canopy structure is a complex task involving accurate measurements of the horizontal and vertical arrangement of the canopy in space and time. This study examined the utility of multitemporal, small-footprint lidar data to describe the changes in the horizontal and vertical canopy structure of fire-tolerant eucalypt forests seven years after wildfire of different severities from the tree to stand level. Extensive ground measurements were carried out in four severity classes to describe and validate canopy cover and height metrics as they change after wildfire. Several metrics such as crown height and width, crown base height and clumpiness of crown were assessed at tree and stand level using several individual tree top detection and measurement algorithm. Persistent effects of high severity fire 8 years after both on tree crowns and stand canopy were observed. High severity fire increased the crown depth but decreased the crown projective cover leading to more open canopy.

Keywords: canopy gaps, canopy structure, crown architecture, crown projective cover, multi-temporal lidar, wildfire severity

Procedia PDF Downloads 153

Authors: Sivanandan Balakrishnan, Sara Moridpour, Richard Tay

Abstract:

Heavy vehicles make a significant contribution to many developed economies, including Australia, because they are a major means of transporting goods within these countries. With the increase in road freight, there will be an increase in the heavy vehicle traffic proportion, and consequently, an increase in the possibility of collisions involving heavy vehicles. Crashes involving heavy vehicles are a major road safety concern because of the higher likelihood of fatal and serious injury, especially to any small vehicle occupant involved. The primary objective of this research is to identify the factors influencing injury severity to occupants in vehicle collisions involving heavy vehicle at T- intersection using a binary logit model in Victoria, Australia. Our results show that the factors influencing injury severity include occupants' gender, age and restraint use. Also, vehicles' type, movement, point-of-impact and damage, time-of-day, day-of-week and season, higher percentage of trucks in traffic volume, hit pedestrians, number of occupants involved and type of collisions are associated with severe injury.

Keywords: binary logit model, heavy vehicle, injury severity, T-intersections

Procedia PDF Downloads 367

Authors: Carlos Alberto Riveros, Edwin Fabián García, Javier Enrique Rivero

Abstract:

The measured data obtained from sensors in continuous monitoring of civil structures are mainly used for modal identification and damage detection. Therefore when modal identification analysis is carried out the quality in the identification of the modes will highly influence the damage detection results. It is also widely recognized that the usefulness of the measured data used for modal identification and damage detection is significantly influenced by the number and locations of sensors. The objective of this study is the numerical implementation of two widely known optimum sensor placement methods in beam-like structures

Keywords: optimum sensor placement, structural damage detection, modal identification, beam-like structures.

Procedia PDF Downloads 412

Authors: Jinan Fiaidhi, Sabah Mohammed

Abstract:

Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

Procedia PDF Downloads 86

Authors: Mathias Marquardt, Peter Dünow, Sandra Baßler

Abstract:

The paper describes the use of subspace based identification methods for auto tuning of a state space control system. The plant is an unstable but self balancing transport robot. Because of the unstable character of the process it has to be identified from closed loop input-output data. Based on the identified model a state space controller combined with an observer is calculated. The subspace identification algorithm and the controller design procedure is combined to a auto tuning method. The capability of the approach was verified in a simulation experiments under different process conditions.

Keywords: auto tuning, balanced robot, closed loop identification, subspace identification

Procedia PDF Downloads 352

Authors: Jaworski Mariusz, Owczarek Krzysztof, Adamus Mirosława

Abstract:

Binge eating disorder (BED) is one of the three main eating disorders, beside anorexia and bulimia nervosa. BED is characterized by a loss of control over the quantity of food consumed and the lack of the compensatory behaviors, such as induced vomiting or purging. Studies highlight that certain personality traits may contribute to the severity of symptoms in the ED. The aim of this study is to analyze the relationship between psychological variables (Impulsivity and Urgency) and Nutritional restrictions in BED. The study included two groups. The first group consisted of 35 women with BED aged 18 to 28. The control group - 35 women without ED aged 18 to 28. ED-1 questionnaire was used in a study to assess the severity of impulsivity, urgency and nutritional restrictions. The obtained data were standardized. Statistical analyzes were performed using SPSS 21 software. The severity of impulsivity was higher in patients with BED than the control group. The relation between impulsivity and nutritional restrictions in BED was observed, only taking into consideration the relationship of these variables with the level of urgency. However, if the severity of urgency in this relationship is skipped, the relationship between impulsivity and nutritional restrictions will not occur. Impulsivity has a negative relationship with the level of urgency. This study suggests the need to analyze the interaction between impulsivity and urgency, and their relationship with dietary behavior in BED, especially nutritional restrictions. Analysis of single isolated features may give erroneous results.

Keywords: binge eating disorder, impulsivity, nutritional restrictions, urgency

Procedia PDF Downloads 448

Authors: Moustafa Ibrahim Moustafa

Abstract:

The purpose of this study was to determine the immediate and long term effects of a multimodal program, with the addition of cervical sagittal curve restoration and forward head correction, on severity of dizziness, disability, frequency of dizziness, and severity of cervical pain. 72 patients with cervicogenic dizziness, definite hypolordotic cervical spine, and forward head posture were randomized to experimental or a control group. Both groups received the multimodal program, additionally, the study group received the Denneroll cervical traction. All outcome measures were measured at three intervals. The general linear model indicated a significant group × time effects in favor of experimental group on measures of anterior head translation (F=329.4 P < .0005), cervical lordosis (F=293.7 P < .0005), severity of dizziness (F=262.1 P < .0005), disability (F=248.9 P < .0005), frequency of dizziness (F=53.9 P < .0005), and severity of cervical pain (F=350.1 P < .0005). The addition of Dennroll cervical traction to a multimodal program can positively affect dizziness management outcomes.

Keywords: randomized controlled trial, traction, dizziness, cervical

Procedia PDF Downloads 287

Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung

Abstract:

In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.

Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining

Procedia PDF Downloads 408

Authors: M. J. Falade

Abstract:

Field experiment was conducted to compare the efficacy of hot water extracts of three plants (Ricinus communis, Jatropha gossypifolia and Datura stramonium) with benomyl in the control of cowpea anthracnose disease. Three concentrations of the extracts (65, 50 and 30%) were used in the study. Result from the experiment shows that all the extracts at the tested concentration reduced the incidence and severity of the disease. D. stramonium at 65% concentration compares favourably with that of benomyl fungicide in reducing incidence and severity of infection. At 65% concentration of D. stramonium, incidence of the disease was 22% on pooled mean basis, and this was not significantly different from that of benomyl (21%). Similarly, the percentage of normal seeds recorded at this same concentration of the extract was 85% and was not significantly different from that of benomyl (86%). In terms of disease severity trace infections were observed on the cowpea plants at this concentration of the extract and that of benomyl. However, at lower concentrations of all the extracts, significant variations were observed on incidence of disease and percentage of normal seeds such that values obtained from use of benomyl were higher than those obtained from the use of the extracts. The study, therefore, shows that extracts of these indigenous plants can be used as a substitute for the benomyl fungicide in the management of anthracnose disease.

Keywords: benomyl, C. lindemuthianum, disease incidence, disease severity

Procedia PDF Downloads 261

Authors: D. Madhushanka, Y. Liu, H. C. Fernando

Abstract:

Fires are one of the foremost factors of land surface disturbance in diverse ecosystems, causing soil erosion and land-cover changes and atmospheric effects affecting people's lives and properties. Generally, the severity of the fire is calculated as the Normalized Burn Ratio (NBR) index. This is performed manually by comparing two images obtained afterward. Then by using the bitemporal difference of the preprocessed satellite images, the dNBR is calculated. The burnt area is then classified as either unburnt (dNBR<0.1) or burnt (dNBR>= 0.1). Furthermore, Wildfire Severity Assessment (WSA) classifies burnt areas and unburnt areas using classification levels proposed by USGS and comprises seven classes. This procedure generates a burn severity report for the area chosen by the user manually. This study is carried out with the objective of producing an automated tool for the above-mentioned process, namely the World Wildfire Severity Assessment Tool (WWSAT). It is implemented in Google Earth Engine (GEE), which is a free cloud-computing platform for satellite data processing, with several data catalogs at different resolutions (notably Landsat, Sentinel-2, and MODIS) and planetary-scale analysis capabilities. Sentinel-2 MSI is chosen to obtain regular processes related to burnt area severity mapping using a medium spatial resolution sensor (15m). This tool uses machine learning classification techniques to identify burnt areas using NBR and to classify their severity over the user-selected extent and period automatically. Cloud coverage is one of the biggest concerns when fire severity mapping is performed. In WWSAT based on GEE, we present a fully automatic workflow to aggregate cloud-free Sentinel-2 images for both pre-fire and post-fire image compositing. The parallel processing capabilities and preloaded geospatial datasets of GEE facilitated the production of this tool. This tool consists of a Graphical User Interface (GUI) to make it user-friendly. The advantage of this tool is the ability to obtain burn area severity over a large extent and more extended temporal periods. Two case studies were carried out to demonstrate the performance of this tool. The Blue Mountain national park forest affected by the Australian fire season between 2019 and 2020 is used to describe the workflow of the WWSAT. This site detected more than 7809 km2, using Sentinel-2 data, giving an error below 6.5% when compared with the area detected on the field. Furthermore, 86.77% of the detected area was recognized as fully burnt out, of which high severity (17.29%), moderate-high severity (19.63%), moderate-low severity (22.35%), and low severity (27.51%). The Arapaho and Roosevelt National Forest Park, California, the USA, which is affected by the Cameron peak fire in 2020, is chosen for the second case study. It was found that around 983 km2 had burned out, of which high severity (2.73%), moderate-high severity (1.57%), moderate-low severity (1.18%), and low severity (5.45%). These spots also can be detected through the visual inspection made possible by cloud-free images generated by WWSAT. This tool is cost-effective in calculating the burnt area since satellite images are free and the cost of field surveys is avoided.

Keywords: burnt area, burnt severity, fires, google earth engine (GEE), sentinel-2

Procedia PDF Downloads 206

Authors: A. Mansouri, F. Krim

Abstract:

This paper presents two techniques for DC motor parameters identification. We propose a numerical method using the adaptive extensive recursive least squares (AERLS) algorithm for real time parameters estimation. This algorithm, based on minimization of quadratic criterion, is realized in simulation for parameters identification of DC motor autoregressive moving average with extra inputs (ARMAX). As advanced technique, we use genetic algorithms (GA) identification with biased estimation for high dynamic performance speed regulation. DC motors are extensively used in variable speed drives, for robot and solar panel trajectory control. GA effectiveness is derived through comparison of the two approaches.

Keywords: ARMAX model, DC motor, AERLS, GA, optimization, parameter identification, PID speed regulation

Procedia PDF Downloads 358

Authors: Shahan Waheed, Muhammad Waqas, Asher Feroz

Abstract:

Objectives: To determine the utility of base deficit in traumatic brain injury in assessing the severity and to correlate with the conventional computed tomography scales in grading the severity of head injury. Methodology: Observational cross-sectional study conducted in a tertiary care facility from 1st January 2010 to 31st December 2012. All patients with isolated traumatic brain injury presenting within 24 hours of the injury to the emergency department were included in the study. Initial Glasgow Coma Scale and base deficit values were taken at presentation, the patients were followed during their hospital stay and CT scan brain findings were recorded and graded as per the Rotterdam scale, the findings were cross-checked by a radiologist, Glasgow Outcome Scale was taken on last follow up. Outcomes were dichotomized into favorable and unfavorable outcomes. Continuous variables with normal and non-normal distributions are reported as mean ± SD. Categorical variables are presented as frequencies and percentages. Relationship of the base deficit with GCS, GOS, CT scan brain and length of stay was calculated using Spearman`s correlation. Results: 154 patients were enrolled in the study. Mean age of the patients were 30 years and 137 were males. The severity of brain injuries as per the GCS was 34 moderate and 109 severe respectively. 34 percent of the total has an unfavorable outcome with a mean of 18±14. The correlation was significant at the 0.01 level with GCS on presentation and the base deficit 0.004. The correlation was not significant between the Rotterdam CT scan brain findings, length of stay and the base deficit. Conclusion: The base deficit was found to be a good predictor of severity of brain injury. There was no association of the severity of injuries on the CT scan brain as per the Rotterdam scale and the base deficit. Further studies with large sample size are needed to further evaluate the associations.

Keywords: base deficit, traumatic brain injury, Rotterdam, GCS

Procedia PDF Downloads 419