Search results for: Multiple trauma
4565 Comparison of Statistical Methods for Estimating Missing Precipitation Data in the River Subbasin Lenguazaque, Colombia
Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza
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In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant
Procedia PDF Downloads 4684564 Comparison of Head Kinematics Resulting from Reconstructed Direct and Non-Direct Head-to-Glass Impacts in Ice Hockey
Authors: Ella Bowles, Alexandra Hughes, Clara Karton, T. Blaine Hoshizaki
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As a fast-paced and physical game, body contact is an inevitable component in professional men's ice hockey. Despite efforts and advancements in material engineering to create safer equipment, brain trauma continues to persist and burden hockey players. Head and body contact occur in many ways and vary in terms of impact characteristics including the inbound velocity, force, direction, location, and compliance of the surfaces, which in turn influence head dynamics and brain injury outcomes including concussions. It has been reported that glass and board impacts account for approximately 40% of diagnosed concussions. This type of impact often involves the body (i.e., shoulder) contacting the surface prior to head contact, which may influence the head’s dynamic response by interrupting the head’s initial trajectory. However, the effect of body-first contact during head impacts is not well understood. The purpose of this research is to compare the head’s kinematic response during direct and non-direct (body-first) head-to-glass impacts representative of ice hockey events. Analysis was performed under varying impact conditions of neck stiffness and impact velocity as they have been shown to influence the resulting head dynamics. Data was collected by video analysis of the 2016-17 NHL season and event reconstructions were performed using a Hybrid III headform, an unbiased neck with tension springs (uONSA), and a high-speed impactor. Direct and non-direct impacts were analyzed at three common velocities (3.0, 5.0, 7.0 m/s), and three neck stiffnesses representing low (25%), medium (75%), and high (100%) contraction. Reconstructions representing non-direct head-to-glass impacts used a shoulder bumper as the first point of contact followed by the head’s contact with the glass. The same method and equipment were used to replicate the direct head impacts, where the head made initial contact with the glass. The dynamic response of the head, specifically the peak resultant linear and rotational acceleration, was collected for each impact and compared between direct and non-direct contact under each condition. The results show that non-direct impacts created an initial head acceleration resulting from shoulder contact, preceding a secondary acceleration response from head contact with the glass. Compared to direct head impacts, non-direct impacts consistently resulted in lower linear and rotational acceleration of the head under all neck stiffness and velocity conditions with an average decrease of 32.56 g and 689.33 rad/s2. However, the linear acceleration produced from shoulder contact in non-direct impacts resulted in a higher response compared to direct impacts with low neck stiffness at 5 m/s (55.2g and 41.2g, respectively) and 7 m/s (76.1g and 73.4g, respectively), and medium neck stiffness at 5 m/s (55.4g and 43.9g, respectively ) and 7 m/s (94.4g and 69.5g, respectively. These findings show that non-direct impacts produce complex scenarios that are further influenced by interaction with neck stiffness and velocity. This research provides an understanding of the fundamentals of body-first impacts. With this basis, an understanding of the implications of body-first head-impacts to better distinguish trauma based on events, and adapt protocols, evaluations, technologies, and equipment accordingly.Keywords: body-first, concussion, direct, hockey, kinematics
Procedia PDF Downloads 44563 Interference among Lambsquarters and Oil Rapeseed Cultivars
Authors: Reza Siyami, Bahram Mirshekari
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Seed and oil yield of rapeseed is considerably affected by weeds interference including mustard (Sinapis arvensis L.), lambsquarters (Chenopodium album L.) and redroot pigweed (Amaranthus retroflexus L.) throughout the East Azerbaijan province in Iran. To formulate the relationship between four independent growth variables measured in our experiment with a dependent variable, multiple regression analysis was carried out for the weed leaves number per plant (X1), green cover percentage (X2), LAI (X3) and leaf area per plant (X4) as independent variables and rapeseed oil yield as a dependent variable. The multiple regression equation is shown as follows: Seed essential oil yield (kg/ha) = 0.156 + 0.0325 (X1) + 0.0489 (X2) + 0.0415 (X3) + 0.133 (X4). Furthermore, the stepwise regression analysis was also carried out for the data obtained to test the significance of the independent variables affecting the oil yield as a dependent variable. The resulted stepwise regression equation is shown as follows: Oil yield = 4.42 + 0.0841 (X2) + 0.0801 (X3); R2 = 81.5. The stepwise regression analysis verified that the green cover percentage and LAI of weed had a marked increasing effect on the oil yield of rapeseed.Keywords: green cover percentage, independent variable, interference, regression
Procedia PDF Downloads 4214562 Reinforcement Learning for Self Driving Racing Car Games
Authors: Adam Beaunoyer, Cory Beaunoyer, Mohammed Elmorsy, Hanan Saleh
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This research aims to create a reinforcement learning agent capable of racing in challenging simulated environments with a low collision count. We present a reinforcement learning agent that can navigate challenging tracks using both a Deep Q-Network (DQN) and a Soft Actor-Critic (SAC) method. A challenging track includes curves, jumps, and varying road widths throughout. Using open-source code on Github, the environment used in this research is based on the 1995 racing game WipeOut. The proposed reinforcement learning agent can navigate challenging tracks rapidly while maintaining low racing completion time and collision count. The results show that the SAC model outperforms the DQN model by a large margin. We also propose an alternative multiple-car model that can navigate the track without colliding with other vehicles on the track. The SAC model is the basis for the multiple-car model, where it can complete the laps quicker than the single-car model but has a higher collision rate with the track wall.Keywords: reinforcement learning, soft actor-critic, deep q-network, self-driving cars, artificial intelligence, gaming
Procedia PDF Downloads 494561 DeepLig: A de-novo Computational Drug Design Approach to Generate Multi-Targeted Drugs
Authors: Anika Chebrolu
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Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.Keywords: drug design, multitargeticity, de-novo, reinforcement learning
Procedia PDF Downloads 994560 Indoor Fingerprint Localization Using 5G NR Multi-SSB Beam Features with GAN-Based Interpolation
Authors: LiRen Kang, LingXia Li, KaiKai Liu, Yue Jin, ZengShan Tian
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With the widespread adoption of 5G technology in the Internet of Things (IoT), indoor localization methods based on 5G signals have gradually become a research hotspot. However, traditional methods often perform poorly in multipath interference and signal attenuation environments. To address these challenges, this paper proposes an innovative fingerprint localization method that utilizes the multiple synchronization signal block (SSB) beam features of 5G signals combined with generative adversarial networks (GANs) for interpolation. Our method incorporates a ray tracing model as an auxiliary, integrating signal propagation models to enhance the interpolation process. We precisely extract the multiple SSB beam features from 5G signals; in the localization stage, deep learning neural networks (DNN) are used for localization. Field tests show that localization errors of less than 1.5 meters can be achieved within about 200 square meters of indoor environment. Our method represents a 56.7% improvement compared to traditional methods that use received signal strength (RSS) as a single feature.Keywords: 5G NR, fingerprint localization, generative adversarial networks, Internet of Things, indoor localization systems
Procedia PDF Downloads 74559 Short-Term Physiological Evaluation of Augmented Reality System for Thanatophobia Psychotherapy
Authors: Kais Siala, Mohamed Kharrat, Mohamed Abid
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Exposure therapies encourage patients to gradually begin facing their painful memories of the trauma in order to reduce fear and anxiety. In this context, virtual reality techniques are widely used for treatment of different kinds of phobia. The particular case of fear of death phobia (thanataphobia) is addressed in this paper. For this purpose, we propose to make a simulation of Near Death Experience (NDE) using augmented reality techniques. We propose in particular to simulate the Out-of-Body experience (OBE) which is the first step of a Near-Death-Experience (NDE). In this paper, we present technical aspects of this simulation as well as short-term impact in terms of physiological measures. The non-linear Poincéré plot is used to describe the difference in Heart Rate Variability between In-Body and Out-Of-Body conditions.Keywords: Out-of-Body simulation, physiological measure, augmented reality, phobia psychotherapy, HRV, Poincaré plot
Procedia PDF Downloads 3084558 Graph Based Traffic Analysis and Delay Prediction Using a Custom Built Dataset
Authors: Gabriele Borg, Alexei Debono, Charlie Abela
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There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale. Furthermore, a series of traffic prediction graph neural network models are conducted to compare MalTra to large-scale traffic datasets.Keywords: graph neural networks, traffic management, big data, mobile data patterns
Procedia PDF Downloads 1334557 Paper-Like and Battery Free Sensor Patches for Wound Monitoring
Authors: Xiaodi Su, Xin Ting Zheng, Laura Sutarlie, Nur Asinah binte Mohamed Salleh, Yong Yu
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Wound healing is a dynamic process with multiple phases. Rapid profiling and quantitative characterization of inflammation and infection remain challenging. We have developed paper-like battery-free multiplexed sensors for holistic wound assessment via quantitative detection of multiple inflammation and infection markers. In one of the designs, the sensor patch consists of a wax-printed paper panel with five colorimetric sensor channels arranged in a pattern resembling a five-petaled flower (denoted as a ‘Petal’ sensor). The five sensors are for temperature, pH, trimethylamine, uric acid, and moisture. The sensor patch is sandwiched between a top transparent silicone layer and a bottom adhesive wound contact layer. In the second design, a palm-like-shaped paper strip is fabricated by a paper-cutter printer (denoted as ‘Palm’ sensor). This sensor strip carries five sensor regions connected by a stem sampling entrance that enables rapid colorimetric detection of multiple bacteria metabolites (aldehyde, lactate, moisture, trimethylamine, tryptophan) from wound exudate. For both the “\’ Petal’ and ‘Palm’ sensors, color images can be captured by a mobile phone. According to the color changes, one can quantify the concentration of the biomarkers and then determine wound healing status and identify/quantify bacterial species in infected wounds. The ‘Petal’ and ‘Palm’ sensors are validated with in-situ animal and ex-situ skin wound models, respectively. These sensors have the potential for integration with wound dressing to allow early warning of adverse events without frequent removal of the plasters. Such in-situ and early detection of non-healing condition can trigger immediate clinical intervention to facilitate wound care management.Keywords: wound infection, colorimetric sensor, paper fluidic sensor, wound care
Procedia PDF Downloads 814556 A Simulation Study on the Applicability of Overbooking Strategies in Inland Container Transport
Authors: S. Fazi, B. Behdani
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The inland transportation of maritime containers entails the use of different modalities whose capacity is typically booked in advance. Containers may miss their scheduled departure time at a terminal for several reasons, such as delays, change of transport modes, multiple bookings pending. In those cases, it may be difficult for transport service providers to find last minute containers to fill the vacant capacity. Similarly to other industries, overbooking could potentially limit these drawbacks at the cost of a lower service level in case of actual excess of capacity in overbooked rides. However, the presence of multiple modalities may provide the required flexibility in rescheduling and limit the dissatisfaction of the shippers in case of containers in overbooking. This flexibility is known with the term 'synchromodality'. In this paper, we evaluate via discrete event simulation the application of overbooking. Results show that in certain conditions overbooking can significantly increase profit and utilization of high-capacity means of transport, such as barges and trains. On the other hand, in case of high penalty costs and limited no-show, overbooking may lead to an excessive use of expensive trucks.Keywords: discrete event simulation, flexibility, inland shipping, multimodality, overbooking
Procedia PDF Downloads 1354555 Improved Super-Resolution Using Deep Denoising Convolutional Neural Network
Authors: Pawan Kumar Mishra, Ganesh Singh Bisht
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Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.Keywords: resolution, deep-learning, neural network, de-blurring
Procedia PDF Downloads 5184554 One-Class Classification Approach Using Fukunaga-Koontz Transform and Selective Multiple Kernel Learning
Authors: Abdullah Bal
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This paper presents a one-class classification (OCC) technique based on Fukunaga-Koontz Transform (FKT) for binary classification problems. The FKT is originally a powerful tool to feature selection and ordering for two-class problems. To utilize the standard FKT for data domain description problem (i.e., one-class classification), in this paper, a set of non-class samples which exist outside of positive class (target class) describing boundary formed with limited training data has been constructed synthetically. The tunnel-like decision boundary around upper and lower border of target class samples has been designed using statistical properties of feature vectors belonging to the training data. To capture higher order of statistics of data and increase discrimination ability, the proposed method, termed one-class FKT (OC-FKT), has been extended to its nonlinear version via kernel machines and referred as OC-KFKT for short. Multiple kernel learning (MKL) is a favorable family of machine learning such that tries to find an optimal combination of a set of sub-kernels to achieve a better result. However, the discriminative ability of some of the base kernels may be low and the OC-KFKT designed by this type of kernels leads to unsatisfactory classification performance. To address this problem, the quality of sub-kernels should be evaluated, and the weak kernels must be discarded before the final decision making process. MKL/OC-FKT and selective MKL/OC-FKT frameworks have been designed stimulated by ensemble learning (EL) to weight and then select the sub-classifiers using the discriminability and diversities measured by eigenvalue ratios. The eigenvalue ratios have been assessed based on their regions on the FKT subspaces. The comparative experiments, performed on various low and high dimensional data, against state-of-the-art algorithms confirm the effectiveness of our techniques, especially in case of small sample size (SSS) conditions.Keywords: ensemble methods, fukunaga-koontz transform, kernel-based methods, multiple kernel learning, one-class classification
Procedia PDF Downloads 244553 Hyper-Immunoglobulin E (Hyper-Ige) Syndrome In Skin Of Color: A Retrospective Single-Centre Observational Study
Authors: Rohit Kothari, Muneer Mohamed, Vivekanandh K., Sunmeet Sandhu, Preema Sinha, Anuj Bhatnagar
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Introduction: Hyper-IgE syndrome is a rare primary immunodeficiency syndrome characterised by triad of severe atopic dermatitis, recurrent pulmonary infections, and recurrent staphylococcal skin infections. The diagnosis requires a high degree of suspicion, typical clinical features, and not mere rise in serum-IgE levels, which may be seen in multiple conditions. Genetic studies are not always possible in a resource poor setting. This study highlights various presentations of Hyper-IgE syndrome in skin of color children. Case-series: Our study had six children of Hyper-IgE syndrome aged twomonths to tenyears. All had onset in first ten months of life except one with a late-onset at two years. All had recurrent eczematoid rash, which responded poorly to conventional treatment, secondary infection, multiple episodes of hospitalisation for pulmonary infection, and raised serum IgE levels. One case had occasional vesicles, bullae, and crusted plaques over both the extremities. Genetic study was possible in only one of them who was found to have pathogenic homozygous deletions of exon-15 to 18 in DOCK8 gene following which he underwent bone marrow transplant (BMT), however, succumbed to lower respiratory tract infection two months after BMT and rest of them received multiple courses of antibiotics, oral/ topical steroids, and cyclosporine intermittently with variable response. Discussion: Our study highlights various characteristics, presentation, and management of this rare syndrome in children. Knowledge of these manifestations in skin of color will facilitate early identification and contribute to optimal care of the patients as representative data on the same is limited in literature.Keywords: absolute eosinophil count, atopic dermatitis, eczematous rash, hyper-immunoglobulin E syndrome, pulmonary infection, serum IgE, skin of color
Procedia PDF Downloads 1394552 The Sr-Nd Isotope Data of the Platreef Rocks from the Northern Limb of the Bushveld Igneous Complex: Evidence of Contrasting Magma Composition and Origin
Authors: Tshipeng Mwenze, Charles Okujeni, Abdi Siad, Russel Bailie, Dirk Frei, Marcelene Voigt, Petrus Le Roux
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The Platreef is a platinum group element (PGE) deposit in the northern limb of the Bushveld Igneous Complex (BIC) which was emplaced as a series of mafic and ultramafic sills between the Main Zone (MZ) and the country rocks. The PGE mineralisation in the Platreef is hosted in different rock types, and its distribution and style vary with depth and along strike. This study contributes towards understanding the processes involved in the genesis of the Platreef. Twenty-four Platreef (2 harzburgites, 4 olivine pyroxenites, 17 feldspathic pyroxenites and 1 gabbronorite) and few MZ (1 gabbronorite and 1 leucogabbronorite) quarter core samples were collected from four drill cores (e.g., TN754, TN200, SS339, and OY482) and analysed for whole-rock Sr-Nd isotope data. The results show positive ɛNd values (+3.53 to +7.51) for harzburgites suggesting their parental magmas derived from the depleted Mantle. The remaining Platreef rocks have negative ɛNd values (-2.91 to -22.88) and show significant variations in Sr-Nd isotopic compositions. The first group of Platreef samples has relatively high isotopic compositions (ɛNd= -2.91 to -5.68; ⁸⁷Sr/⁸⁶Sri= 0.709177 - 0.711998). The second group of Platreef samples has Sr ratios (⁸⁷Sr/⁸⁶Sri= 0.709816-0.712106) overlapping with samples of the first group but slightly lower ɛNd values (-7.44 to -8.39). Lastly, the third group of Platreef samples has low ɛNd values (-10.82 to -14.32) and low Sr ratios (⁸⁷Sr/⁸⁶Sri= 0.707545-0.710042) than those from samples of the two Platreef groups mentioned above. There is, however, a Platreef sample with ɛNd value (-5.26) in range with the Platreef samples of the first group, but its Sr ratio (0.707281) is the lowest even when compared to samples of the third Platreef group. There are also five other Platreef samples which have either anomalous ɛNd or Sr ratios which make it difficult to assess their isotopic compositions relative to other samples. These isotopic variations for the Platreef samples indicate both multiple sources and multiple magma chambers where varying crustal contamination styles have operated during the evolution of these magmas prior their emplacements into the Platreef setting as sills. Furthermore, the MZ rocks have different Sr-Nd isotopic compositions (For OY482 gabbronorite [ɛNd= +0.65; ⁸⁷Sr/⁸⁶Sri= 0.711746]; for TN754 leucogabbronorite [ɛNd= -7.44; ⁸⁷Sr/⁸⁶Sri= 0.709322]) which do not only indicate different MZ magma chambers, but also different magmas from those of the Platreef. Although the Platreef is still considered a single stratigraphic unit in the northern limb of the BIC, its genesis involved multiple magmatic processes which evolved independently from each other.Keywords: crustal contamination styles, magma chambers, magma sources, multiple sills emplacement
Procedia PDF Downloads 1674551 Heroin Withdrawal, Prison and Multiple Temporalities
Authors: Ian Walmsley
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The aim of this paper is to explore the influence of time and temporality on the experience of coming off heroin in prison. The presentation draws on qualitative data collected during a small-scale pilot study of the role of self-care in the process of coming off drugs in prison. Time and temporality emerged as a key theme in the interview transcripts. Drug dependent prisoners experience of time in prison has not been recognized in the research literature. Instead, the literature on prison time typically views prisoners as a homogenous group or tends to focus on the influence of aging and gender on prison time. Furthermore, there is a tendency in the literature on prison drug treatment and recovery to conceptualize drug dependent prisoners as passive recipients of prison healthcare, rather than active agents. In building on these gaps, this paper argues that drug dependent prisoners experience multiple temporalities which involve an interaction between the body-times of the drug dependent prisoner and the economy of time in prison. One consequence of this interaction is the feeling that they are doing, at this point in their prison sentence, double prison time. The second part of the argument is that time and temporality were a means through which they governed their withdrawing bodies. In addition, this paper will comment on the challenges of prison research in England.Keywords: heroin withdrawal, time and temporality, prison, body
Procedia PDF Downloads 2784550 Effectiveness of Using Multiple Non-pharmacological Interventions to Prevent Delirium in the Hospitalized Elderly
Authors: Yi Shan Cheng, Ya Hui Yeh, Hsiao Wen Hsu
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Delirium is an acute state of confusion, which is mainly the result of the interaction of many factors, including: age>65 years, comorbidity, cognitive function and visual/auditory impairment, dehydration, pain, sleep disorder, pipeline retention, general anesthesia and major surgery… etc. Researches show the prevalence of delirium in hospitalized elderly patients over 50%. If it doesn't improve in time, may cause cognitive decline or impairment, not only prolong the length of hospital stay but also increase mortality. Some studies have shown that multiple nonpharmacological interventions are the most effective and common strategies, which are reorientation, early mobility, promoting sleep and nutritional support (including water intake), could improve or prevent delirium in the hospitalized elderly. In Taiwan, only one research to compare the delirium incidence of the older patients who have received orthopedic surgery between multi-nonpharmacological interventions and general routine care. Therefore, the purpose of this study is to address the prevention or improvement of delirium incidence density in medical hospitalized elderly, provide clinical nurses as a reference for clinical implementation, and develop follow-up related research. This study is a quasi-experimental design using purposive sampling. Samples are from two wards: the geriatric ward and the general medicine ward at a medical center in central Taiwan. The sample size estimated at least 100, and then the data will be collected through a self-administered structured questionnaire, including: demographic and professional evaluation items. Case recruiting from 5/13/2023. The research results will be analyzed by SPSS for Windows 22.0 software, including descriptive statistics and inferential statistics: logistic regression、Generalized Estimating Equation(GEE)、multivariate analysis of variance(MANOVA).Keywords: multiple nonpharmacological interventions, hospitalized elderly, delirium incidence, delirium
Procedia PDF Downloads 794549 Non-parametric Linear Technique for Measuring the Efficiency of Winter Road Maintenance in the Arctic Area
Authors: Mahshid Hatamzad, Geanette Polanco
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Improving the performance of Winter Road Maintenance (WRM) can increase the traffic safety and reduce the cost as well as environmental impacts. This study evaluates the efficiency of WRM technique, named salting, in the Arctic area by using Data Envelopment Analysis (DEA), which is a non-parametric linear method to measure the efficiencies of decision-making units (DMUs) based on handling multiple inputs and multiple outputs at the same time that their associated weights are not known. Here, roads are considered as DMUs for which the efficiency must be determined. The three input variables considered are traffic flow, road area and WRM cost. In addition, the two output variables included are level of safety in the roads and environment impacts resulted from WRM, which is also considered as an uncontrollable factor in the second scenario. The results show the performance of DMUs from the most efficient WRM to the inefficient/least efficient one and this information provides decision makers with technical support and the required suggested improvements for inefficient WRM, in order to achieve a cost-effective WRM and a safe road transportation during wintertime in the Arctic areas.Keywords: environmental impacts, DEA, risk and safety, WRM
Procedia PDF Downloads 1204548 A Rare Case of Acquired Benign Tracheoesophageal Fistula: Case Report and Literature Review
Authors: Sarah Bouayyad, Ajay Nigam, Meera Beena
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Acquired benign tracheoesophageal fistula is a rare medical condition that usually results from trauma, foreign bodies, or granulomatous infections. This is an unusual presentation of a male patient with a history of laryngectomy who had had over a period of several years inappropriately and vigorously used valve cleaning brushes to clean tracheal secretions, which had led to the formation of a tracheoesophageal fistula. Due to the patient’s obsessive habit, we couldn’t manage him using conventional surgical methods. Instead, we opted for the placement of a salivary bypass tube, which yielded good results and recovery. To the best of our knowledge, no other case of similar etiology has been published. We would like to highlight the importance of appropriate patient selection and education prior to performing a tracheoesophageal puncture to avoid developing life-threatening complications as demonstrated in our case report.Keywords: tracheoesophageal fistula, speech valve, endoscopic insertion of salivary bypass tube, head and neck malignancies
Procedia PDF Downloads 1264547 The Importance of Functioning and Disability Status Follow-Up in People with Multiple Sclerosis
Authors: Sanela Slavkovic, Congor Nad, Spela Golubovic
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Background: The diagnosis of multiple sclerosis (MS) is a major life challenge and has repercussions on all aspects of the daily functioning of those attained by it – personal activities, social participation, and quality of life. Regular follow-up of only the neurological status is not informative enough so that it could provide data on the sort of support and rehabilitation that is required. Objective: The aim of this study was to establish the current level of functioning of persons attained by MS and the factors that influence it. Methods: The study was conducted in Serbia, on a sample of 108 persons with relapse-remitting form of MS, aged 20 to 53 (mean 39.86 years; SD 8.20 years). All participants were fully ambulatory. Methods applied in the study include Expanded Disability Status Scale-EDSS and World Health Organization Disability Assessment Schedule, WHODAS 2.0 (36-item version, self-administered). Results: Participants were found to experience the most problems in the domains of Participation, Mobility, Life activities and Cognition. The least difficulties were found in the domain of Self-care. Symptom duration was the only control variable with a significant partial contribution to the prediction of the WHODAS scale score (β=0.30, p < 0.05). The total EDSS score correlated with the total WHODAS 2.0 score (r=0.34, p=0.00). Statistically significant differences in the domain of EDSS 0-5.5 were found within categories (0-1.5; 2-3.5; 4-5.5). The more pronounced a participant’s EDSS score was, although not indicative of large changes in the neurological status, the more apparent the changes in the functional domain, i.e. in all areas covered by WHODAS 2.0. Pyramidal (β=0.34, p < 0.05) and Bowel and bladder (β=0.24, p < 0.05) functional systems were found to have a significant partial contribution to the prediction of the WHODAS score. Conclusion: Measuring functioning and disability is important in the follow-up of persons suffering from MS in order to plan rehabilitation and define areas in which additional support is needed.Keywords: disability, functionality, multiple sclerosis, rehabilitation
Procedia PDF Downloads 1224546 High-Frequency Cryptocurrency Portfolio Management Using Multi-Agent System Based on Federated Reinforcement Learning
Authors: Sirapop Nuannimnoi, Hojjat Baghban, Ching-Yao Huang
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Over the past decade, with the fast development of blockchain technology since the birth of Bitcoin, there has been a massive increase in the usage of Cryptocurrencies. Cryptocurrencies are not seen as an investment opportunity due to the market’s erratic behavior and high price volatility. With the recent success of deep reinforcement learning (DRL), portfolio management can be modeled and automated. In this paper, we propose a novel DRL-based multi-agent system to automatically make proper trading decisions on multiple cryptocurrencies and gain profits in the highly volatile cryptocurrency market. We also extend this multi-agent system with horizontal federated transfer learning for better adapting to the inclusion of new cryptocurrencies in our portfolio; therefore, we can, through the concept of diversification, maximize our profits and minimize the trading risks. Experimental results through multiple simulation scenarios reveal that this proposed algorithmic trading system can offer three promising key advantages over other systems, including maximized profits, minimized risks, and adaptability.Keywords: cryptocurrency portfolio management, algorithmic trading, federated learning, multi-agent reinforcement learning
Procedia PDF Downloads 1194545 Glucose Monitoring System Using Machine Learning Algorithms
Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe
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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning
Procedia PDF Downloads 2064544 Managing Incomplete PSA Observations in Prostate Cancer Data: Key Strategies and Best Practices for Handling Loss to Follow-Up and Missing Data
Authors: Madiha Liaqat, Rehan Ahmed Khan, Shahid Kamal
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Multiple imputation with delta adjustment is a versatile and transparent technique for addressing univariate missing data in the presence of various missing mechanisms. This approach allows for the exploration of sensitivity to the missing-at-random (MAR) assumption. In this review, we outline the delta-adjustment procedure and illustrate its application for assessing the sensitivity to deviations from the MAR assumption. By examining diverse missingness scenarios and conducting sensitivity analyses, we gain valuable insights into the implications of missing data on our analyses, enhancing the reliability of our study's conclusions. In our study, we focused on assessing logPSA, a continuous biomarker in incomplete prostate cancer data, to examine the robustness of conclusions against plausible departures from the MAR assumption. We introduced several approaches for conducting sensitivity analyses, illustrating their application within the pattern mixture model (PMM) under the delta adjustment framework. This proposed approach effectively handles missing data, particularly loss to follow-up.Keywords: loss to follow-up, incomplete response, multiple imputation, sensitivity analysis, prostate cancer
Procedia PDF Downloads 904543 Performance Evaluation of MIMO-OFDM Communication Systems
Authors: M. I. Youssef, A. E. Emam, M. Abd Elghany
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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 1754542 Evaluating Factors Influencing Information Quality in Large Firms
Authors: B. E. Narkhede, S. K. Mahajan, B. T. Patil, R. D. Raut
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Information quality is a major performance measure for an Enterprise Resource Planning (ERP) system of any firm. This study identifies various critical success factors of information quality. The effect of various critical success factors like project management, reengineering efforts and interdepartmental communications on information quality is analyzed using a multiple regression model. Here quantitative data are collected from respondents from various firms through structured questionnaire for assessment of the information quality, project management, reengineering efforts and interdepartmental communications. The validity and reliability of the data are ensured using techniques like factor analysis, computing of Cronbach’s alpha. This study gives relative importance of each of the critical success factors. The findings suggest that among the various factors influencing information quality careful reengineering efforts are the most influencing factor. This paper gives clear insight to managers and practitioners regarding the relative importance of critical success factors influencing information quality so that they can formulate a strategy at the beginning of ERP system implementation.Keywords: Enterprise Resource Planning (ERP), information systems (IS), multiple regression, information quality
Procedia PDF Downloads 3344541 Impact of Forgiveness Therapy on Quality of Life of Parents of Children with Intellectual Disability
Authors: Prajakta Bhadgaonkar
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Forgiveness is taught since birth in Indian tradition. However, delivering a disabled child is a trauma for the parents. They keep on blaming themselves for the fault, which they are not responsible. Hence, due to lack of forgiving oneself the quality of life of both parent and child gets affected. In forgiveness, person tries to relieve oneself from the feeling of hatred towards oneself or other person. Forgiveness helps move ahead in the life. Hence, one can handle problem more efficiently resulting into better quality of life. In this study, the 30 parents of children with intellectual disability were contacted to find out quality of life. They were administered standardized measure of quality of life (QOL). The children were between 6 to 8 years of age. Out of these 30 parents, 12 parents (7 females and 5 males) were given forgiveness therapy for three months span. After every one month, the QOL scale was administered. At the end of three months, the significant difference was observed in quality of life of parents of children with intellectual disability. Genderwise there was no significant difference between male and female on quality of life.Keywords: children with intellectual disability, forgiveness, parents, quality of life
Procedia PDF Downloads 3314540 Evaluating Contextually Targeted Advertising with Attention Measurement
Authors: John Hawkins, Graham Burton
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Contextual targeting is a common strategy for advertising that places marketing messages in media locations that are expected to be aligned with the target audience. There are multiple major challenges to contextual targeting: the ideal categorisation scheme needs to be known, as well as the most appropriate subsections of that scheme for a given campaign or creative. In addition, the campaign reach is typically limited when targeting becomes narrow, so a balance must be struck between requirements. Finally, refinement of the process is limited by the use of evaluation methods that are either rapid but non-specific (click through rates), or reliable but slow and costly (conversions or brand recall studies). In this study we evaluate the use of attention measurement as a technique for understanding the performance of targeting on the basis of specific contextual topics. We perform the analysis using a large scale dataset of impressions categorised using the iAB V2.0 taxonomy. We evaluate multiple levels of the categorisation hierarchy, using categories at different positions within an initial creative specific ranking. The results illustrate that measuring attention time is an affective signal for the performance of a specific creative within a specific context. Performance is sustained across a ranking of categories from one period to another.Keywords: contextual targeting, digital advertising, attention measurement, marketing performance
Procedia PDF Downloads 1054539 Sport-Related Hand and Wrist Injuries Treatment
Authors: Sergei Kosarev
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Wrong treatment tactics for hand and wrist sport-related injuries can lead to the inability to play sports in the future. It is especially important for professional athletes. The members of the Russian Olympic Team are treated in our hospital -Federal Clinical Research Center (Moscow). For their treatment, we use minimally invasive methods such as wrist arthroscopy and also orthobiologics procedures. In 2022 we had cases with scaphoid fracture and TFCC injuries. In all the cases, we were using the arthroscopy technic for treatment. The scaphoid fracture was fixed by K-wires with free bone grafting. For TFCC injures we used transossal sutures. Rehabilitation started the next day after surgery. Rehabilitation included hand therapy and physiotherapy. All athletes returned to the sport after 8-12 weeks after surgery. One of them had pain in the wrist after 12 weeks after surgery, not more than 4 point VAS. Pain syndrome was blocked after 2 PRP injections in the ulnar side of the wrist.Keywords: sport trauma, wrist arthroscopy, wrist pain, scaphoid fracture
Procedia PDF Downloads 1004538 Data and Spatial Analysis for Economy and Education of 28 E.U. Member-States for 2014
Authors: Alexiou Dimitra, Fragkaki Maria
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The objective of the paper is the study of geographic, economic and educational variables and their contribution to determine the position of each member-state among the EU-28 countries based on the values of seven variables as given by Eurostat. The Data Analysis methods of Multiple Factorial Correspondence Analysis (MFCA) Principal Component Analysis and Factor Analysis have been used. The cross tabulation tables of data consist of the values of seven variables for the 28 countries for 2014. The data are manipulated using the CHIC Analysis V 1.1 software package. The results of this program using MFCA and Ascending Hierarchical Classification are given in arithmetic and graphical form. For comparison reasons with the same data the Factor procedure of Statistical package IBM SPSS 20 has been used. The numerical and graphical results presented with tables and graphs, demonstrate the agreement between the two methods. The most important result is the study of the relation between the 28 countries and the position of each country in groups or clouds, which are formed according to the values of the corresponding variables.Keywords: Multiple Factorial Correspondence Analysis, Principal Component Analysis, Factor Analysis, E.U.-28 countries, Statistical package IBM SPSS 20, CHIC Analysis V 1.1 Software, Eurostat.eu Statistics
Procedia PDF Downloads 5134537 School Accidents in Educational Establishment in Tunisia: A Five Years Retrospective Survey in the Governorate of Mahdia
Authors: Lamia Bouzgarrou, Amira Omrane, Leila Mrabet, Taoufik Khalfallah
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Background and aims: School accidents are one of the leading causes of morbidity and mortality among pupils and students. Indeed, they may induce an elevated number of lost school days, heavy emotional and physical disabilities, and financial costs on the victims and their families. This study aims to evaluate the annual incidence of school accidents in the central Tunisian governorate of Mahdia and to identify the epidemiological profile of victims and risk factors of these accidents. Methods: A retrospective study was conducted over the period of 5 school years, focusing on school accidents that occurred in public educational institutions (primary, basic, secondary and university) in the governorate of Mahdia (area = 2 966 km² and number of inhabitants in 2014 = 410 812). All accidents declared near the only official insurance of this type of injuries (MASU: Mutual School and University Accidents), and initially taken in charge at the University Hospital of Mahdia were included. Data was collected from the MASU reporting forms and the medical records of emergency and other specialized hospital departments. Results: With 3248 identified victims, the annual incidence of school accidents was equal to 0.69 per 100 pupils and students per year. The average age of victims was 14.51 ± 0.059 years and the sex ratio was 1.58. Pupils aged between 12 and 15 years, were concerned by 46.7% of the identified accidents. The practice of sports was the most relevant circumstances of these accidents (76.2 %). In 56.58 % of cases, falls were the leading mechanism. Bruises and fractures were the most frequent lesions (32.43 % and 30.51 %). Serious school accidents were noted in 28% of cases with hospitalization in 2.27 % of them. The average lost school days, was 12.23±1.73 days. Accidents occurring during sports or leisure activities were significantly more serious (p= 0.021). Furthermore, the frequency of hospitalization was significantly higher among boys (2.81% vs. 1.43%; p= 0.035), students ≤11 years (p= 0.008), and following crush trauma (p= 0.000). In addition, the surgical interventions were statistically more frequent among male victims (p=0.00), accidents occurring during physical education sessions (p=0.000); those associated to falls (p=0.000) and to crushes mechanisms (p=0.002), and injuries affecting lower limbs (p=0.000). Following this Multi-varied analysis concluded that the severity of school accident is correlated to the activity practiced during the trauma and the geographical location of the school. Conclusion: Children and adolescents are one of the most vulnerable groups against incidents with the risk of permanent disability, mainly related to the perturbation of the growth process and physiological limitations. Our five-year study, objectified a real elevate incidence of school accident among children and adolescents, with a considerable rate of severe injuries. In any community, the promotion of adolescents and children’s health is an important indicator of the public health level. Thus, it’s important to develop a multidisciplinary prevention strategy of school accident, based on safety and security rules and adapted to the specificity of our context.Keywords: children and adolescents, children health, injuries and disability, school accident
Procedia PDF Downloads 1184536 Umbilical Epidermal Inclusion Cysts, a Rare Cause of Umbilical Mass: A Case Report and Review of Literature
Authors: Christine Li, Amanda Robertson
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Epidermal inclusion cysts occur when epidermal cells are implanted in the dermis following trauma, or surgery. They are a rare cause of an umbilical mass, with very few cases previously reported following abdominal surgery. These lesions can present with a range of symptoms, including palpable mass, pain, redness, or discharge. This paper reports a case of an umbilical epidermal inclusion cyst in a 52-year-old female presenting with a six-week history of a painful, red umbilical lump on a background of two previous diagnostic laparoscopies. Abdominal computed tomography (CT) scans revealed non-specific soft tissue thickening in the umbilical region. This was successfully treated with complete excision of the lesion. Umbilical lumps are a common presentation but can represent a diagnostic challenge. The differential diagnosis should include an epidermal inclusion cyst, particularly in a patient who has had previous abdominal surgery, including laparoscopic surgery.Keywords: epidermal inclusion cyst, laparoscopy, umbilical mass, umbilicus
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