Search results for: automated

Authors: Rimon Rafiah

Abstract:

This paper will present a combination of two seemingly unrelated models, which are the one for estimating economic development impacts as a result of transportation investment and the other for increasing CAV penetration in order to reduce congestion. Measuring economic development impacts resulting from transportation investments is becoming more recognized around the world. Examples include the UK’s Wider Economic Benefits (WEB) model, Economic Impact Assessments in the USA, various input-output models, and additional models around the world. The economic impact model is based on WEB and is based on the following premise: investments in transportation will reduce the cost of personal travel, enabling firms to be more competitive, creating additional throughput (the same road allows more people to travel), and reducing the cost of travel of workers to a new workplace. This reduction in travel costs was estimated in out-of-pocket terms in a given localized area and was then translated into additional employment based on regional labor supply elasticity. This additional employment was conservatively assumed to be at minimum wage levels, translated into GDP terms, and from there into direct taxation (i.e., an increase in tax taken by the government). The CAV model is based on economic principles such as CAV usage, supply, and demand. Usage of CAVs can increase capacity using a variety of means – increased automation (known as Level I thru Level IV) and also by increased penetration and usage, which has been predicted to go up to 50% by 2030 according to several forecasts, with possible full conversion by 2045-2050. Several countries have passed policies and/or legislation on sales of gasoline-powered vehicles (none) starting in 2030 and later. Supply was measured via increased capacity on given infrastructure as a function of both CAV penetration and implemented technologies. The CAV model, as implemented in the USA, has shown significant savings in travel time and also in vehicle operating costs, which can be translated into economic development impacts in terms of job creation, GDP growth and salaries as well. The models have policy implications as well and can be adapted for use in Japan as well.

Keywords: CAV, economic development, WEB, transport economics

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Authors: Debasis Sarkar, Jatan Talati

Abstract:

This paper is an attempt to develop an Integrated Mass Rapid Transit System (MRTS) for a smart city project in Western India. Integrated transportation is one of the enablers of smart transportation for providing a seamless intercity as well as regional level transportation experience. The success of a smart city project at the city level for transportation is providing proper integration to different mass rapid transit modes by way of integrating information, physical, network of routes fares, etc. The methodology adopted for this study was primary data research through questionnaire survey. The respondents of the questionnaire survey have responded on the issues about their perceptions on the ways and means to improve public transport services in urban cities. The respondents were also required to identify the factors and attributes which might motivate more people to shift towards the public mode. Also, the respondents were questioned about the factors which they feel might restrain the integration of various modes of MRTS. Furthermore, this study also focuses on developing a utility equation for respondents with the help of multiple linear regression analysis and its probability to shift to public transport for certain factors listed in the questionnaire. It has been observed that for shifting to public transport, the most important factors that need to be considered were travel time saving and comfort rating. Also, an Integrated MRTS can be obtained by combining metro rail with BRTS, metro rail with monorail, monorail with BRTS and metro rail with Indian railways. Providing a common smart card to transport users for accessing all the different available modes would be a pragmatic solution towards integration of the available modes of MRTS.

Keywords: mass rapid transit systems, smart city, metro rail, bus rapid transit system, multiple linear regression, smart card, automated fare collection system

Procedia PDF Downloads 238

Authors: A. Barratt, M. H. Granat, S. Buttress, B. Roy

Abstract:

Introduction: Physiotherapy is an essential part of the treatment of patients with shoulder problems. The focus of treatment is usually centred on addressing specific physiotherapy goals, ultimately resulting in the improvement in pain and function. This study investigates if computerised physiotherapy using gamification principles are as effective as standard physiotherapy. Methods: Physiotherapy exergames were created using a combination of commercially available hardware, the Microsoft Kinect, and bespoke software. The exergames used were validated by mapping physiotherapy goals of physiotherapy which included; strength, range of movement, control, speed, and activation of the kinetic chain. A multicenter, randomised prospective controlled trial investigated the use of exergames on patients with Shoulder Impingement Syndrome who had undergone Arthroscopic Subacromial Decompression surgery. The intervention group was provided with the automated sensor-based technology, allowing them to perform exergames and track their rehabilitation progress. The control group was treated with standard physiotherapy protocols. Outcomes from different domains were used to compare the groups. An important metric was the assessment of shoulder range of movement pre- and post-operatively. The range of movement data included abduction, forward flexion and external rotation which were measured by the software, pre-operatively, 6 weeks and 12 weeks post-operatively. Results: Both groups show significant improvement from pre-operative to 12 weeks in elevation in forward flexion and abduction planes. Results for abduction showed an improvement for the interventional group (p < 0.015) as well as the test group (p < 0.003). Forward flexion improvement was interventional group (p < 0.0201) with the control group (p < 0.004). There was however no significant difference between the groups at 12 weeks for abduction (p < 0.118067) , forward flexion (p < 0.189755) or external rotation (p < 0.346967). Conclusion: Exergames may be used as an alternative to standard physiotherapy regimes; however, further analysis is required focusing on patient engagement.

Keywords: shoulder, physiotherapy, exergames, gamification

Procedia PDF Downloads 151

Authors: Mahmoud B. Rokaya

Abstract:

The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

Procedia PDF Downloads 151

Authors: Junaid Mahmood Alam

Abstract:

Revalidating and harmonizing clinical chemistry analytical principles and optimizing methods through quality control programs and assessments is the preeminent means to attain optimal outcome within the clinical laboratory services. Present study reports revalidation of our existing IFCC regularized analytical methods, particularly hepatic and thyroid function tests, by optimization of precision analyses and processing through external and internal quality assessments and regression determination. Parametric components of hepatic (Bilirubin ALT, γGT, ALP), cardiac (LDH, AST, Trop I) and thyroid/pituitary (T3, T4, TSH, FT3, FT4) function tests were used to validate analytical techniques on automated chemistry and immunological analyzers namely Hitachi 912, Cobas 6000 e601, Cobas c501, Cobas e411 with UV kinetic, colorimetric dry chemistry principles and Electro-Chemiluminescence immunoassay (ECLi) techniques. Process of validation and revalidation was completed with evaluating and assessing the precision analyzed Preci-control data of various instruments plotting against each other with regression analyses R2. Results showed that: Revalidation and optimization of respective parameters that were accredited through CAP, CLSI and NEQAPP assessments depicted 99.0% to 99.8% optimization, in addition to the methodology and instruments used for analyses. Regression R2 analysis of BilT was 0.996, whereas that of ALT, ALP, γGT, LDH, AST, Trop I, T3, T4, TSH, FT3, and FT4 exhibited R2 0.998, 0.997, 0.993, 0.967, 0.970, 0.980, 0.976, 0.996, 0.997, 0.997, and R2 0.990, respectively. This confirmed marked harmonization of analytical methods and instrumentations thus revalidating optimized precision standardization as per IFCC recommended guidelines. It is concluded that practices of revalidating and harmonizing the existing or any new services should be followed by all clinical laboratories, especially those associated with tertiary care hospital. This is will ensure deliverance of standardized, proficiency tested, optimized services for prompt and better patient care that will guarantee maximum patients’ confidence.

Keywords: revalidation, standardized, IFCC, CAP, harmonized

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Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

Abstract:

Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

Procedia PDF Downloads 295

Authors: Fatma Koksal Cakirlar, Murat Gunaydin, Nevri̇ye Gonullu, Nuri Kiraz

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During the last few decades, the increasing prevalence of methicillin resistant-CoNS isolates has become a common problem worldwide. Macrolide-lincosamide-streptogramin B (MLSB) antibiotics are effectively used for the treatment of CoNS infections. However, resistance to MLSB antibiotics is prevalent among staphylococci. The aim of this study is to determine species distribution and the incidence of inducible clindamycin resistance in CoNS isolates caused nosocomial bacteremia in our hospital. Between January 2014 and October 2015, a total of 484 coagulase-negative CoNS isolates were isolated from blood samples of patients with true bacteremia who were hospitalized in intensive care units and in other departments of Istanbul University Cerrahpasa Medical Hospital. Blood cultures were analyzed with the BACTEC 9120 system (Becton Dickinson, USA). The identification and antimicrobial resistance of isolates were determined by Phoenix automated system (BD Diagnostic Systems, Sparks, MD). Inducible clindamycin resistance was detected using D-test. The species distribution was as follows: Staphylococcus epidermidis 211 (43%), S. hominis 154 (32%), S. haemolyticus 69 (14%), S. capitis 28 (6%), S. saprophyticus 11 (2%), S. warnerii 7 (1%), S. schleiferi 5 (1%) and S. lugdunensis 1 (0.2%). Resistance to methicillin was detected in 74.6% of CoNS isolates. Methicillin resistance was highest in S.hemoliticus isolates (89%). Resistance rates of CoNS strains to the antibacterial agents, respectively, were as follows: ampicillin 77%, gentamicin 20%, erythromycin 71%, clindamycin 22%, trimethoprim-sulfamethoxazole 45%, ciprofloxacin 52%, tetracycline 34%, rifampicin 20%, daptomycin 0.2% and linezolid 0.2%. None of the strains were resistant to vancomycin and teicoplanin. Fifteen (3%) CoNS isolates were D-test positive, inducible MLSB resistance type (iMLSB-phenotype), 94 (19%) were constitutively resistant (cMLSB -phenotype), and 237 (46,76%) isolates were found D-test negative, indicating truly clindamycin-susceptible MS phenotype (M-phenotype resistance). The incidence of iMLSB-phenotypes was higher in S. epidermidis isolates (4,7%) compared to other CoNS isolates.

Keywords: bacteremia, inducible MLSB resistance phenotype, methicillin-resistant, staphylococci

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Authors: Tim Giesen, Raphael Adamietz, Pablo Mayer, Philipp Stiefel, Patrick Alle, Dirk Schlenker

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The competitiveness and success of new electrical energy storages such as battery cells are significantly dependent on a short time-to-market. Producers who decide to supply new battery cells to the market need to be easily adaptable in manufacturing with respect to the early customers’ needs in terms of cell size, materials, delivery time and quantity. In the initial state, the required output rates do not yet allow the producers to have a fully automated manufacturing line nor to supply handmade battery cells. Yet there was no solution for manufacturing battery cells in low to medium volumes in a reproducible way. Thus, in terms of cell format and output quantity, a concept for the flexible assembly of battery cells was developed by the Fraunhofer-Institute for Manufacturing Engineering and Automation. Based on clustered processes, the modular system platform can be modified, enlarged or retrofitted in a short time frame according to the ordered product. The paper shows the analysis of the production steps from a conventional battery cell assembly line. Process solutions were found by using I/O-analysis, functional structures, and morphological boxes. The identified elementary functions were subsequently clustered by functional coherences for automation solutions and thus the single process cluster was generated. The result presented in this paper enables to manufacture different cell products on the same production system using seven process clusters. The paper shows the solution for a batch-wise flexible battery cell production using advanced process control. Further, the performed tests and benefits by using the process clusters as cyber-physical systems for an integrated production and value chain are discussed. The solution lowers the hurdles for SMEs to launch innovative cell products on the global market.

Keywords: automation, battery production, carrier, advanced process control, cyber-physical system

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Authors: Deniz Guven, Wil Ward, Jinming Duan, Li Bai

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Over the past two decades or so, Optical Coherence Tomography (OCT) has been used to diagnose retina and optic nerve diseases. The retinal nerve fibre layer, for example, is a powerful diagnostic marker for detecting and staging glaucoma. With the advances in optical imaging hardware, the adoption of OCT is now commonplace in clinics. More and more OCT images are being generated, and for these OCT images to have clinical applicability, accurate automated OCT image segmentation software is needed. Oct image segmentation is still an active research area, as OCT images are inherently noisy, with the multiplicative speckling noise. Simple edge detection algorithms are unsuitable for detecting retinal layer boundaries in OCT images. Intensity fluctuation, motion artefact, and the presence of blood vessels also decrease further OCT image quality. In this paper, we introduce a new method for segmenting three-dimensional (3D) OCT images. This involves the use of a Kalman filter, which is commonly used in computer vision for object tracking. The Kalman filter is applied to the 3D OCT image volume to track the retinal layer boundaries through the slices within the volume and thus segmenting the 3D image. Specifically, after some pre-processing of the OCT images, points on the retinal layer boundaries in the first image are identified, and curve fitting is applied to them such that the layer boundaries can be represented by the coefficients of the curve equations. These coefficients then form the state space for the Kalman Filter. The filter then produces an optimal estimate of the current state of the system by updating its previous state using the measurements available in the form of a feedback control loop. The results show that the algorithm can be used to segment the retinal layers in OCT images. One of the limitations of the current algorithm is that the curve representation of the retinal layer boundary does not work well when the layer boundary is split into two, e.g., at the optic nerve, the layer boundary split into two. This maybe resolved by using a different approach to representing the boundaries, such as b-splines or level sets. The use of a Kalman filter shows promise to developing accurate and effective 3D OCT segmentation methods.

Keywords: optical coherence tomography, image segmentation, Kalman filter, object tracking

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Authors: Antoifi Abdoulhalik, Ashraf Ahmed

Abstract:

The ever growing threat of saltwater intrusion has prompted the need to further advance the understanding of underlying processes related to SWI for effective water resource management. While research efforts have mainly been focused on steady state analysis, studies on the transience of saltwater intrusion mechanism remain very scarce and studies considering transient SWI in heterogeneous medium are, as per our knowledge, simply inexistent. This study provides for the first time a quantitative analysis of the effect of both inland and coastal water level changes on the transition zone under transient conditions in layered coastal aquifer. In all, two sets of four experiments were completed, including a homogeneous case, and four layered cases: case LH and case HL presented were two bi-layered scenarios where a low K layer was set at the top and the bottom, respectively; case HLH and case LHL presented two stratified aquifers with High K–Low K–High K and Low K–High K– Low K pattern, respectively. Experimental automated image analysis technique was used here to quantify the main SWI parameters under high spatial and temporal resolution. The findings of this study provide an invaluable insight on the underlying processes responsible of transition zone dynamics in coastal aquifers. The results show that in all the investigated cases, the width of the transition zone remains almost unchanged throughout the saltwater intrusion process regardless of where the boundary change occurs. However, the results demonstrate that the width of the transition zone considerably increases during the retreat, with largest amplitude observed in cases LH and LHL, where a low K was set at the top of the system. In all the scenarios, the amplitude of widening was slightly smaller when the retreat was prompted by instantaneous drop of the saltwater level than when caused by inland freshwater rise, despite equivalent absolute head change magnitude. The magnitude of head change significantly caused larger widening during the saltwater wedge retreat, while having no impact during the intrusion phase.

Keywords: freshwater-saltwater transition-zone dynamics, heterogeneous coastal aquifers, laboratory experiments, transience seawater intrusion

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Authors: Ioannis Iglezakis, Theodoros D. Trokanas, Panagiota Kiortsi

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This paper aims to explore major legal issues arising from the collection and processing of Health Big Data in the light of the new European secondary legislation for the protection of personal data of natural persons, placing emphasis on the General Data Protection Regulation 679/2016. Whether Big Health Data can be characterised as ‘personal data’ or not is really the crux of the matter. The legal ambiguity is compounded by the fact that, even though the processing of Big Health Data is premised on the de-identification of the data subject, the possibility of a combination of Big Health Data with other data circulating freely on the web or from other data files cannot be excluded. Another key point is that the application of some provisions of GPDR to Big Health Data may both absolve the data controller of his legal obligations and deprive the data subject of his rights (e.g., the right to be informed), ultimately undermining the fundamental right to the protection of personal data of natural persons. Moreover, data subject’s rights (e.g., the right not to be subject to a decision based solely on automated processing) are heavily impacted by the use of AI, algorithms, and technologies that reclaim health data for further use, resulting in sometimes ambiguous results that have a substantial impact on individuals. On the other hand, as the COVID-19 pandemic has revealed, Big Data analytics can offer crucial sources of information. In this respect, this paper identifies and systematises the legal provisions concerned, offering interpretative solutions that tackle dangers concerning data subject’s rights while embracing the opportunities that Big Health Data has to offer. In addition, particular attention is attached to the scope of ‘consent’ as a legal basis in the collection and processing of Big Health Data, as the application of data analytics in Big Health Data signals the construction of new data and subject’s profiles. Finally, the paper addresses the knotty problem of role assignment (i.e., distinguishing between controller and processor/joint controllers and joint processors) in an era of extensive Big Health data sharing. The findings are the fruit of a current research project conducted by a three-member research team at the Faculty of Law of the Aristotle University of Thessaloniki and funded by the Greek Ministry of Education and Religious Affairs.

Keywords: big health data, data subject rights, GDPR, pandemic

Procedia PDF Downloads 100

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Bartosz Kedra, Robert Malkowski

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This paper provides description and presentation of laboratory test unit built basing on 150 kVA power frequency converter and Simulink RealTime platform. Assumptions, based on criteria which load and generator types may be simulated using discussed device, are presented, as well as control algorithm structure. As laboratory setup contains transformer with thyristor controlled tap changer, a wider scope of setup capabilities is presented. Information about used communication interface, data maintenance, and storage solution as well as used Simulink real-time features is presented. List and description of all measurements are provided. Potential of laboratory setup modifications is evaluated. For purposes of Rapid Control Prototyping, a dedicated environment was used Simulink RealTime. Therefore, load model Functional Unit Controller is based on a PC computer with I/O cards and Simulink RealTime software. Simulink RealTime was used to create real-time applications directly from Simulink models. In the next step, applications were loaded on a target computer connected to physical devices that provided opportunity to perform Hardware in the Loop (HIL) tests, as well as the mentioned Rapid Control Prototyping process. With Simulink RealTime, Simulink models were extended with I/O cards driver blocks that made automatic generation of real-time applications and performing interactive or automated runs on a dedicated target computer equipped with a real-time kernel, multicore CPU, and I/O cards possible. Results of performed laboratory tests are presented. Different load configurations are described and experimental results are presented. This includes simulation of under frequency load shedding, frequency and voltage dependent characteristics of groups of load units, time characteristics of group of different load units in a chosen area and arbitrary active and reactive power regulation basing on defined schedule.

Keywords: MATLAB, power converter, Simulink Real-Time, thyristor-controlled tap changer

Procedia PDF Downloads 292

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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Authors: Leszek Szpakowski, Daniel Celiński, Sławomir Pilip, Grzegorz Michalak

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The aim of the study was to analyse the usefulness of the 'E-rescuer' pilot project planned to be implemented in a chosen area of Eastern Poland in the cases of suspected sudden cardiac arrests in the extra-urban areas. Inventing an application allowing to dispatch simultaneously both Medical Emergency Teams and the E-rescuer to the place of the accident is the crucial assumption of the mentioned pilot project. The E-rescuer is defined to be the trained person able to take effective basic life support and to use automated external defibrillator. Having logged in using a smartphone, the E-rescuer's readiness is reported online to provide cardiopulmonary resuscitation exactly at the given location. Due to the accurately defined location of the E-rescuer, his arrival time is possible to be precisely fixed, and the substantive support through the displayed algorithms is capable of being provided as well. Having analysed the medical records in the years 2015-2016, cardiopulmonary resuscitation was considered to be effective when an early indication of circulation was provided, and the patient was taken to hospital. In the mentioned term, there were 2.291 cases of a sudden cardiac arrest. Cardiopulmonary resuscitation was taken in 621 patients in total including 205 people in the urban area and 416 in the extra-urban areas. The effectiveness of cardiopulmonary resuscitation in the extra-urban areas was much lower (33,8%) than in the urban (50,7%). The average ambulance arrival time was respectively longer in the extra-urban areas, and it was 12,3 minutes while in the urban area 3,3 minutes. There was no significant difference in the average age of studied patients - 62,5 and 64,8 years old. However, the average ambulance arrival time was 7,6 minutes for effective resuscitations and 10,5 minutes for ineffective ones. Hence, the ambulance arrival time is a crucial factor influencing on the effectiveness of cardiopulmonary resuscitation, especially in the extra-urban areas where it is much longer than in the urban. The key role of trained E-rescuers being nearby taking basic life support before the ambulance arrival can effectively support Emergency Medical Services System in Poland.

Keywords: basic life support, bystander, effectiveness, resuscitation

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Authors: Antoifi Abdoulhalik, Ashraf Ahmed

Abstract:

Saltwater intrusion (SWI) in coastal aquifers has become a growing threat for many countries around the world. While various control measures have been suggested to mitigate SWI, the construction of subsurface physical barriers remains one of the most effective solutions for this problem. In this work, we used laboratory experiments and numerical simulations to investigate the effectiveness of subsurface dams in heterogeneous layered coastal aquifer with different layering patterns. Four different cases were investigated, including a homogeneous (case H), and three heterogeneous cases in which a low permeability (K) layer was set in the top part of the system (case LH), in the middle part of the system (case HLH) and the bottom part of the system (case HL). Automated image analysis technique was implemented to quantify the main SWI parameters under high spatial and temporal resolution. The method also provides transient salt concentration maps, allowing for the first time clear visualization of the spillage of saline water over the dam (advancing wedge condition) as well as the flushing of residual saline water from the freshwater area (receding wedge condition). The SEAWAT code was adopted for the numerical simulations. The results show that the presence of an overlying layer of low permeability enhanced the ability of the dam to retain the saline water. In such conditions, the rate of saline water spillage and inland extension may considerably be reduced. Conversely, the presence of an underlying low K layer led to a faster increase of saltwater volume on the seaward side of the wall, therefore considerably facilitating the spillage. The results showed that a complete removal of the residual saline water eventually occurred in all the investigated scenarios, with a rate of removal strongly affected by the hydraulic conductivity of the lower part of the aquifer. The data showed that the addition of the underlying low K layer in case HL caused the complete flushing to be almost twice longer than in the homogeneous scenario.

Keywords: heterogeneous coastal aquifers, laboratory experiments, physical barriers, seawater intrusion control

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Authors: Nicky Wilson, Graeme Ralph

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Legacy aerostructure assembly is defined by large components, low build rates, and manual assembly methods. With an increasing demand for commercial aircraft and emerging markets such as the eVTOL (electric vertical take-off and landing) market, current methods of manufacturing are not capable of efficiently hitting these higher-rate demands. This project will look at how legacy manufacturing processes can be rate enabled by taking a holistic view of data usage, focusing on how data can be collected to enable fully integrated digital factories and supply chains. The study will focus on how data is flowed both up and down the supply chain to create a digital thread specific to each part and assembly while enabling machine learning through real-time, closed-loop feedback systems. The study will also develop a bespoke architecture to enable connectivity both within the factory and the wider PLM (product lifecycle management) system, moving away from traditional point-to-point systems used to connect IO devices to a hub and spoke architecture that will exploit report-by-exception principles. This paper outlines the key issues facing legacy aircraft manufacturers, focusing on what future manufacturing will look like from adopting Industry 4 principles. The research also defines the data architecture of a PLM system to enable the transfer and control of a digital thread within the supply chain and proposes a standardised communications protocol to enable a scalable solution to connect IO devices within a production environment. This research comes at a critical time for aerospace manufacturers, who are seeing a shift towards the integration of digital technologies within legacy production environments, while also seeing build rates continue to grow. It is vital that manufacturing processes become more efficient in order to meet these demands while also securing future work for many manufacturers.

Keywords: Industry 4, digital transformation, IoT, PLM, automated assembly, connected factories

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Authors: Nardjes Hamini, Mohamed Bachir Yagoubi

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Precision agriculture has revolutionized farming by enabling farmers to monitor their crops remotely in real-time. By utilizing technologies such as sensors, farmers can detect the state of growth, hydration levels, and nutritional status and even identify diseases affecting their crops. With this information, farmers can make informed decisions regarding irrigation, fertilization, and pesticide application. Automated agricultural tasks, such as plowing, seeding, planting, and harvesting, are carried out by autonomous robots and have helped reduce costs and increase production. Despite the advantages of precision agriculture, its high cost makes it inaccessible to small and medium-sized farms. To address this issue, this paper presents an open-source guidance system for an autonomous planter robot. The system is composed of a Raspberry Pi-type nanocomputer equipped with Wi-Fi, a GPS module, a gyroscope, and a power supply module. The accompanying application allows users to enter and calibrate maps with at least four coordinates, enabling the localized contour of the parcel to be captured. The application comprises several modules, such as the mission entry module, which traces the planting trajectory and points, and the action plan entry module, which creates an ordered list of pre-established tasks such as loading, following the plan, returning to the garage, and entering sleep mode. A remote control module enables users to control the robot manually, visualize its location on the map, and use a real-time camera. Wi-Fi coverage is provided by an outdoor access point, covering a 2km circle. This open-source system offers a low-cost alternative for small and medium-sized farms, enabling them to benefit from the advantages of precision agriculture.

Keywords: autonomous robot, guidance system, low-cost, medium farms, open-source system, planter robot, precision agriculture, real-time monitoring, remote control, small farms

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Authors: Subrata Sarkar

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The aerospace industry is experiencing a profound product development transformation driven by the powerful integration of digitalization and 3D printing technologies. This paper delves into the significant impact of this convergence on aerospace innovation, specifically focusing on developing jet pumps for fuel systems. This case study is a compelling example of the immense potential of these technologies. In response to the industry's increasing demand for lighter, more efficient, and customized components, the combined capabilities of digitalization and 3D printing are reshaping how we envision, design, and manufacture critical aircraft parts, offering a distinct paradigm in aerospace engineering. Consider the development of a jet pump for a fuel system, a task that presents unique and complex challenges. Despite its seemingly simple design, the jet pump's development is hindered by many demanding operating conditions. The qualification process for these pumps involves many analyses and tests, leading to substantial delays and increased costs in fuel system development. However, by harnessing the power of automated simulations and integrating legacy design, manufacturing, and test data through digitalization, we can optimize the jet pump's design and performance, thereby revolutionizing product development. Furthermore, 3D printing's ability to create intricate structures using various materials, from lightweight polymers to high-strength alloys, holds the promise of highly efficient and durable jet pumps. The combined impact of digitalization and 3D printing extends beyond design, as it also reduces material waste and advances sustainability goals, aligning with the industry's increasing commitment to environmental responsibility. In conclusion, the convergence of digitalization and 3D printing is not just a technological advancement but a gateway to a new era in aerospace product development, particularly in the design of jet pumps. This revolution promises to redefine how we create aerospace components, making them safer, more efficient, and environmentally responsible. As we stand at the forefront of this technological revolution, aerospace companies must embrace these technologies as a choice and a strategic imperative for those striving to lead in innovation and sustainability in the 21st century.

Keywords: jet pump, digitalization, 3D printing, aircraft fuel system.

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Authors: Muhammad Dawood Idrees, Maria Hafeez, Arsalan Ansari

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Toll tax collection is the earliest method of tax collection and revenue generation. This revenue is utilized for the development of roads networks, maintenance, and connecting to roads and highways across the country. Pakistan is one of the biggest countries, covers a wide area of land, roads networks, and motorways are important source of connecting cities. Every day millions of people use motorways, and they have to stop at toll plazas to pay toll tax as majority of toll plazas are manually collecting toll tax. The purpose of this study is to calculate the waiting time of vehicles at Karachi Hyderabad (M-9) motorway. As Karachi is the biggest city of Pakistan and hundreds of thousands of people use this route to approach other cities. Currently, toll tax collection is manual system which is a major cause for long time waiting at toll plaza. This study calculates the waiting time of vehicles, fuel consumed in waiting time, manpower employed at toll plaza as all process is manual, and it also leads to mental and physical fatigue of driver. All wastages of sources are also calculated, and a most feasible automatic toll tax collection system is proposed which is not only beneficial to reduce waiting time but also beneficial in reduction of fuel, reduction of manpower employed, and reduction in physical and mental fatigue. A cost comparison in terms of wastages is also shown between manual and automatic toll tax collection system (E-Z Pass). Results of this study reveal that, if automatic tool collection system is implemented at Karachi to Hyderabad motorway (M-9), there will be a significance reduction in waiting time of vehicles, which leads to reduction of fuel consumption, environmental pollution, mental and physical fatigue of driver. All these reductions are also calculated in terms of money (Pakistani rupees) and it is obtained that millions of rupees can be saved by using automatic tool collection system which will lead to improve the economy of country.

Keywords: toll tax collection, waiting time, wastages, driver fatigue

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Authors: Recep Kesli, Gulsah Asik, Cengiz Demir, Onur Turkyilmaz

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Objective: Stenotrophomonas maltophilia (S. maltophilia) has recently emerged as an important nosocomial microorganism. Treatment of invasive infections caused by this organism is problematic because this microorganism is usually resistant to a wide range of commonly used antimicrobials. We aimed to evaluate clinical isolates of S. maltophilia in respect to sampling sites and antimicrobial resistant. Method: During a two years period (October 2013 and September 2015) eighteen samples collected from the intensive care unit (ICU) patients hospitalized in Afyon Kocatepe University, ANS Practice and Research Hospital. Identification of the bacteria was determined by conventional methods and automated identification system-VITEK 2 (bio-Mérieux, Marcy l’toile, France). Antibacterial resistance tests were performed by Kirby Bauer disc (Oxoid, England) diffusion method following the recommendations of CLSI. Results: Eighteen S. maltophilia strains were identified as the causative agents of different infections. The main type of infection was lower respiratory tract infection (83,4 %); three patients (16,6 %) had bloodstream infection. While, none of the 18 S. maltophilia strains were found to be resistant against to trimethoprim sulfametaxasole (TMP-SXT) and levofloxacine, eight strains 66.6 % were found to be resistant against ceftazidim. Conclusion: The isolation of S.maltophilia starains resistant to TMP-SXT is vital. In order to prevent or minimize infections due to S. maltophilia such precuations should be utilized: Avoidance of inappropriate antibiotic use, prolonged implementation of foreign devices, reinforcement of hand hygiene practices and the application of appropriate infection control practices. Microbiology laboratories also may play important roles in controlling S. maltophilia infections by monitoring the prevalence, continuously, the provision of local antibiotic resistance paterns data and the performance of synergistic studies also may help to guide appropirate antimicrobial therapy choices.

Keywords: Stenotrophomonas maltophilia, trimethoprim-sulfamethoxazole, antimicrobial resistance, Stenotrophomonas spp.

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Authors: Maria A. Castillo H., Andrés R. Leandro C.

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During the last decades, agricultural productivity in Latin America has increased with precision agriculture and more efficient agricultural technologies. The use of automated systems, satellite images, geographic information systems, and tools for data analysis, and artificial intelligence have contributed to making more effective strategic decisions. Twenty years ago, the state of Mérida, located in the Venezuelan Andes, reported the largest area covered by greenhouses in the country, where certified seeds of potatoes, vegetables, ornamentals, and flowers were produced for export and consumption in the central region of the country. In recent years, it is estimated that production under greenhouses has changed, and the area covered has decreased due to different factors, but there are few historical statistical data in sufficient quantity and quality to support this estimate or to be used for analysis and decision making. The objective of this study is to compare data collected about geoposition, use, and covered areas of the greenhouses in 2007 to data available in 2021, as support for the analysis of the current situation of horticultural production in the main municipalities of the state of Mérida. The document presents the development of the work in the diagnosis and integration of geographic coordinates in GIS and data analysis phases. As a result, an evaluation of the process is made, a dashboard is presented with the most relevant data along with the geographical coordinates integrated into GIS, and an analysis of the obtained information is made. Finally, some recommendations for actions are added, and works that expand the information obtained and its geographical traceability over time are proposed. This study contributes to granting greater certainty in the supporting data for the evaluation of social, environmental, and economic sustainability indicators and to make better decisions according to the sustainable development goals in the area under review. At the same time, the methodology provides improvements to the agricultural data collection process that can be extended to other study areas and crops.

Keywords: greenhouses, geographic information system, protected agriculture, data analysis, Venezuela

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Authors: Larissa Bolliger, Junoš Lukan, Mitja Lustrek, Dirk De Bacquer, Els Clays

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Introduction and Aim: Chronic workplace stress and its health-related consequences like mental and cardiovascular diseases have been widely investigated. This project focuses on the sources and context of psychosocial daily workplace stress in a real-world setting. The main objective is to analyze and model real-time relationships between (1) psychosocial stress experiences within the natural work environment, (2) micro-level work activities and events, and (3) physiological signals and behaviors in office workers. Methods: An Ecological Momentary Assessment (EMA) protocol has been developed, partly building on machine learning techniques. Empatica® wristbands will be used for real-life detection of stress from physiological signals; micro-level activities and events at work will be based on smartphone registrations, further processed according to an automated computer algorithm. A field study including 100 office-based workers with high-level problem-solving tasks like managers and researchers will be implemented in Slovenia and Belgium (50 in each country). Data mining and state-of-the-art statistical methods – mainly multilevel statistical modelling for repeated data – will be used. Expected Results and Impact: The project findings will provide novel contributions to the field of occupational health research. While traditional assessments provide information about global perceived state of chronic stress exposure, the EMA approach is expected to bring new insights about daily fluctuating work stress experiences, especially micro-level events and activities at work that induce acute physiological stress responses. The project is therefore likely to generate further evidence on relevant stressors in a real-time working environment and hence make it possible to advise on workplace procedures and policies for reducing stress.

Keywords: ecological momentary assessment, real-time, stress, work

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Authors: S. Sreeja, Radhakrishnan R. Nair, Noble Gracious, Sreeja S. Nair, M. Radhakrishna Pillai

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Background: Tacrolimus is a potent immunosuppressant clinically used for the long term treatment of antirejection of transplanted organs in liver and kidney transplant recipients though dose optimization is poorly managed. However, So far no study has been carried out on the South Indian kidney transplant patients. The objective of this study is to evaluate the potential influence of a functional polymorphism in CYP3A5*3 gene on tacrolimus physiological availability/dose ratio in South Indian renal transplant patients. Materials and Methods: Twenty five renal transplant recipients receiving tacrolimus were enrolled in this study. Their body weight, drug dosage, and therapeutic concentration of Tacrolimus were observed. All patients were on standard immunosuppressive regime of Tacrolimus-Mycophenolate mofetil along with steroids on a starting dose of Tac 0.1 mg/kg/day. CYP3A5 genotyping was performed by PCR followed with RFLP. Conformation of RFLP analysis and variation in the nucleotide sequence of CYP3A5*3 gene were determined by direct sequencing using a validated automated generic analyzer. Results: A significant association was found between tacrolimus per dose/kg/d and CYP3A5 gene (A6986G) polymorphism in the study population. The CYP3A5 *1/*1, *1/*3 and *3/*3 genotypes were detected in 5 (20 %), 5 (20 %) and 15 (60 %) of the 25 graft recipients, respectively. CYP3A5*3 genotypes were found to be a good predictor of tacrolimus Concentration/Dose ratio in kidney transplant recipients. Significantly higher L/D was observed among non-expressors 9.483 ng/mL(4.5- 14.1) as compared with the expressors 5.154 ng/mL (4.42-6.5 ) of CYP3A5. Acute rejection episodes were significantly higher for CYP3A5*1 homozygotes compared to patients with CYP3A5*1/*3 and CYP3A5*3/*3 genotypes (40 % versus 20 % and 13 %, respectively ). The dose normalized TAC concentration (ng/ml/mg/kg) was significantly lower in patients having CYP3A5*1/*3 polymorphism. Conclusion: This is the first study to extensively determine the effect of CYP3A5*3 genetic polymorphism on tacrolimus pharmacokinetics in South Indian renal transplant recipients and also shows that majority of our patients carry mutant allele A6986G in CYP3A5*3 gene. Identification of CYP3A5 polymorphism prior to transplantation could contribute to evaluate the appropriate initial dosage of tacrolimus for each patient.

Keywords: kidney transplant patients, CYP3A5 genotype, tacrolimus, RFLP

Procedia PDF Downloads 273

Authors: F. Murilo T. Luna, Vanessa F. Oliveira, Alysson Rocha, Expedito J. S. Parente, Andre V. Bueno, Matheus C. M. Farias, Celio L. Cavalcante Jr.

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Aviation jetfuel used in aircraft gas-turbine engines is customarily obtained from the kerosene distillation fraction of petroleum (150-275°C). Mineral jetfuel consists of a hydrocarbon mixture containing paraffins, naphthenes and aromatics, with low olefins content. In order to ensure their safety, several stringent requirements must be met by jetfuels, such as: high energy density, low risk of explosion, physicochemical stability and low pour point. In this context, aviation fuels eventually obtained from biofeedstocks (which have been coined as ‘biojetfuel’), must be used as ‘drop in’, since adaptations in aircraft engines are not desirable, to avoid problems with their operation reliability. Thus, potential aviation biofuels must present the same composition and physicochemical properties of conventional jetfuel. Among the potential feedtstocks for aviation biofuel, the babaçu oil, extracted from a palm tree extensively found in some regions of Brazil, contains expressive quantities of short chain saturated fatty acids and may be an interesting choice for biojetfuel production. In this study, biojetfuel was synthesized through homogeneous transesterification of babaçu oil using methanol and its properties were compared with petroleum-based jetfuel through measurements of oxidative stability, physicochemical properties and low temperature properties. The transesterification reactions were carried out using methanol and after decantation/wash procedures, the methyl esters were purified by molecular distillation under high vacuum at different temperatures. The results indicate significant improvement in oxidative stability and pour point of the products when compared to the fresh oil. After optimization of operational conditions, potential biojetfuel samples were obtained, consisting mainly of C8 esters, showing low pour point and high oxidative stability. Jet engine tests are being conducted in an automated test bed equipped with pollutant emissions analysers to study the operational performance of the biojetfuel that was obtained and compare with a mineral commercial jetfuel.

Keywords: biojetfuel, babaçu oil, oxidative stability, engine tests

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Authors: Rachel Goh, Alexander McNab, Brent Alsop, David O'Hare

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In a busy airport, the decision whether to take passengers aside and search their luggage for dangerous items can have important consequences. If an officer fails to search and stop a bag containing a dangerous object, a life-threatening incident might occur. But stopping a bag unnecessarily means that the officer might lose time searching the bag and face an angry passenger. Passengers’ bags, however, are often cluttered with personal belongings of varying shapes and sizes. It can be difficult to determine what is dangerous or not, especially if the decisions must be made quickly in cases of busy flight schedules. Additionally, the decision to search bags is often made with input from the surrounding officers on duty. This scenario raises several questions: 1) Past findings suggest that humans are more reliant on an automated aid when under time pressure in a visual search task, but does this translate to human-human reliance? 2) Are humans more likely to agree with another person if the person is assumed to be an expert or a novice in these ambiguous situations? In the present study, forty-one participants performed a simulated luggage-screening task. They were partnered with an advisor of two different statuses (expert vs. novice), but of equal accuracy (90% correct). Participants made two choices each trial: their first choice with no advisor input, and their second choice after advisor input. The second choice was made within either 2 seconds or 8 seconds; failure to do so resulted in a long time-out period. Under the 2-second time pressure, participants were more likely to disagree with their own first choice and agree with the expert advisor, regardless of whether the expert was right or wrong, but especially when the expert suggested that the bag was safe. The findings indicate a tendency for people to assume less responsibility for their decisions and defer to their partner, especially when a quick decision is required. This over-reliance on others’ opinions might have negative consequences in real life, particularly when relying on fallible human judgments. More awareness is needed regarding how a stressful environment may influence reliance on other’s opinions, and how better techniques are needed to make the best decisions under high stress and time pressure.

Keywords: advisors, decision-making, time pressure, trust

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Authors: R. Hellmuth

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The orientation of flexibility and adaptability with regard to factory planning is at machine and process level. Factory buildings are not the focus of current research. Factory planning has the task of designing products, plants, processes, organization, areas and the construction of a factory. The adaptability of a factory can be divided into three types: spatial, organizational and technical adaptability. Spatial adaptability indicates the ability to expand and reduce the size of a factory. Here, the area-related breathing capacity plays the essential role. It mainly concerns the factory site, the plant layout and the production layout. The organizational ability to change enables the change and adaptation of organizational structures and processes. This includes structural and process organization as well as logistical processes and principles. New and reconfigurable operating resources, processes and factory buildings are referred to as technical adaptability. These three types of adaptability can be regarded independently of each other as undirected potentials of different characteristics. If there is a need for change, the types of changeability in the change process are combined to form a directed, complementary variable that makes change possible. When planning adaptability, importance must be attached to a balance between the types of adaptability. The vision of the intelligent factory building and the 'Internet of Things' presupposes the comprehensive digitalization of the spatial and technical environment. Through connectivity, the factory building must be empowered to support a company's value creation process by providing media such as light, electricity, heat, refrigeration, etc. In the future, communication with the surrounding factory building will take place on a digital or automated basis. In the area of industry 4.0, the function of the building envelope belongs to secondary or even tertiary processes, but these processes must also be included in the communication cycle. An integrative view of a continuous communication of primary, secondary and tertiary processes is currently not yet available and is being developed with the aid of methods in this research work. A comparison of the digital twin from the point of view of production and the factory building will be developed. Subsequently, a tool will be elaborated to classify digital twins from the perspective of data, degree of visualization, and the trades. Thus a contribution is made to better integrate the secondary and tertiary processes in a factory into the added value.

Keywords: adaptability, digital factory twin, factory planning, industry 4.0

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Authors: Kyra Kannen, Sonja D. Roelen, Sebastian Schnieder, Jarek Krajewski, Steffen Holsteg, André Karger, Johanna Askeridis, Celina Slawik, Philip Mildner, Jens Piesk, Ruslan David, Holger Kürten, Benjamin Oster, Robert Malzan, Mike Ludemann

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Virtual Reality (VR) is increasingly recognized for its potential in transforming mental disorder treatment, offering advantages such as cost-effectiveness, time efficiency, accessibility, reduced stigma, and scalability. While the application of VR in the context of anxiety disorders has been extensively evaluated and demonstrated to be effective, the utilization of VR as a therapeutic treatment for depression remains under-investigated. Our goal is to pioneer immersive VR therapy modules for treating major depression, alongside a web-based system for home use. We develop a modular digital therapy platform grounded in psychodynamic therapy interventions which addresses stress reduction, exploration of social situations and relationship support, social skill training, avoidance behavior analysis, and psychoeducation. In addition, an automated depression monitoring system, based on acoustic voice analysis, is implemented in the form of a speech-based diary to track the affective state of the user and depression severity. The use of immersive VR facilitates patient immersion into complex and realistic interpersonal interactions with high emotional engagement, which may contribute to positive treatment acceptance and satisfaction. In a proof-of-concept study, 45 depressed patients were assigned to VR or web-platform modules, evaluating user experience, usability and additional metrics including depression severity, mindfulness, interpersonal problems, and treatment satisfaction. The findings provide valuable insights into the effectiveness and user-friendliness of VR and web modules for depression therapy and contribute to the refinement of more tailored digital interventions to improve mental health.

Keywords: virtual reality therapy, digital health, depression, psychotherapy

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Authors: Menna Brown, Tania Domun

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Digital health interventions are effective across a wide array of health conditions spanning physical health, lifestyle behaviour change, and mental health and wellbeing; furthermore, they are rapidly increasing in volume within both the academic literature and society as commercial apps continue to proliferate the digital health market. However, adherence and engagement to digital health interventions remains problematic. Technology-based personalised and tailored reminder strategies can support engagement to digital health interventions. Interventions which support individuals’ mental health and wellbeing are of critical importance in the wake if the COVID-19 pandemic. Student and young person’s mental health has been negatively affected and digital resources continue to offer cost effective means to address wellbeing at a population level. Develop a databank of digital co-produced tailored messages to support engagement to a range of digital health interventions including those focused on mental health and wellbeing, and lifestyle behaviour change. Qualitative research design. Participants discussed their views of health and wellbeing, engagement and adherence to digital health interventions focused around a 12-week wellbeing intervention via a series of focus group discussions. They worked together to co-create content following a participatory design approach. Three focus group discussions were facilitated with (n=15) undergraduate students at one Welsh university to provide an empirically derived, co-produced, databank of (n=145) tailored messages. Messages were explored and categorised thematically, and the following ten themes emerged: Autonomy, Recognition, Guidance, Community, Acceptance, Responsibility, Encouragement, Compassion, Impact and Ease. The findings provide empirically derived, co-produced tailored messages. These have been made available for use, via ‘ACTivate your wellbeing’ a digital, automated, 12-week health and wellbeing intervention programme, based on acceptance and commitment therapy (ACT). The purpose of which is to support future research to evaluate the impact of thematically categorised tailored messages on engagement and adherence to digital health interventions.

Keywords: digital health, engagement, wellbeing, participatory design, positive psychology, co-production

Procedia PDF Downloads 91