Search results for: biomechanics and clinical applications

Authors: Mohammad Reza Zamanian

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The construction industry has always been recognized as one of the most dangerous available industries, and the statistics of accidents and injuries resulting from it say that the safety category needs more attention and the arrival of up-to-date technologies in this field. Building information modeling (BIM) is one of the relatively new and applicable technologies in Iran, that the necessity of using it is increasingly evident. The main purposes of this research are to evaluate the feasibility of using this technology in the safety sector of construction projects and to evaluate the effectiveness and operationality of its various applications in this sector. These applications were collected and categorized after reviewing past studies and researches then a questionnaire based on Delphi method criteria was presented to 30 experts who were thoroughly familiar with modeling software and safety guidelines. After receiving and exporting the answers to SPSS software, the validity and reliability of the questionnaire were assessed to evaluate the measuring tools. Fuzzy logic is a good way to analyze data because of its flexibility in dealing with ambiguity and uncertainty issues, and the implementation of the Delphi method in the fuzzy environment overcomes the uncertainties in decision making. Therefore, this method was used for data analysis, and the results indicate the usefulness and effectiveness of BIM in projects and improvement of safety status at different stages of construction. Finally, the applications and the sections discussed were ranked in order of priority for efficiency and effectiveness. Safety planning is considered as the most influential part of the safety of BIM among the four sectors discussed, and planning for the installation of protective fences and barriers to prevent falls and site layout planning with a safety approach based on a 3D model are the most important applications of BIM among the 18 applications to improve the safety of construction projects.

Keywords: building information modeling, safety of construction projects, Delphi method, fuzzy logic

Procedia PDF Downloads 164

Authors: Naridchaya Aberdour, Joanna Kao, Anne Miller, Timothy Shore, Richard Maher, Zhixin Liu

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Background: COVID-19 has and continues to be a strain on healthcare globally, with the number of patients requiring hospitalization exceeding the level of medical support available in many countries. As chest x-rays are the primary respiratory radiological investigation, the Radiological Assessment of Lung Edema (RALE) score was used to quantify the extent of pulmonary infection on baseline imaging. Assessment of RALE score's reproducibility and associations with clinical outcome parameters were then evaluated to determine implications for patient management and prognosis. Methods: A retrospective study was performed with the inclusion of patients testing positive for COVID-19 on nasopharyngeal swab within a single Local Health District in Sydney, Australia and baseline x-ray imaging acquired between January to June 2020. Two independent Radiologists viewed the studies and calculated the RALE scores. Clinical outcome parameters were collected and statistical analysis was performed to assess RALE score reproducibility and possible associations with clinical outcomes. Results: A total of 78 patients met inclusion criteria with the age range of 4 to 91 years old. RALE score concordance between the two independent Radiologists was excellent (interclass correlation coefficient = 0.93, 95% CI = 0.88-0.95, p<0.005). Binomial logistics regression identified a positive correlation with hospital admission (1.87 OR, 95% CI= 1.3-2.6, p<0.005), oxygen requirement (1.48 OR, 95% CI= 1.2-1.8, p<0.005) and invasive ventilation (1.2 OR, 95% CI= 1.0-1.3, p<0.005) for each 1-point increase in RALE score. For each one year increased in age, there was a negative correlation with recovery (0.05 OR, 95% CI= 0.92-1.0, p<0.01). RALE scores above three were positively associated with hospitalization (Youden Index 0.61, sensitivity 0.73, specificity 0.89) and above six were positively associated with ICU admission (Youden Index 0.67, sensitivity 0.91, specificity 0.78). Conclusion: The RALE score can be used as a surrogate to quantify the extent of COVID-19 infection and has an excellent inter-observer agreement. The RALE score could be used to prognosticate and identify patients at high risk of deterioration. Threshold values may also be applied to predict the likelihood of hospital and ICU admission.

Keywords: chest radiography, coronavirus, COVID-19, RALE score

Procedia PDF Downloads 176

Authors: M. Şimşek

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Additive manufacturing (AM) or generally known as three dimensional (3D) printing provides great opportunities for both civilian and military applications by which 3D has become the biggest nominee of breakthrough of 21th century. When properly used, it has a wide spectrum of applications that make production easier and more profitable. Considering the advantages of AM, every firm has an intention of catching up with this new trend. As well as reducing costs and thus increasing benefits, 3D printing provides opportunities for national armies by reducing maintenance and repair time and increasing operational readiness.

Keywords: additive manufacturing, operational cost, operational readiness, supply chain, three dimensional printing

Procedia PDF Downloads 391

Authors: Nishtha Madaan, Prateek Chaudhury, Nishant Kumar, Srikanta Bedathur

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In modern NLP applications, word embeddings are a crucial backbone that can be readily shared across a number of tasks. However, as the text distributions change and word semantics evolve over time, the downstream applications using the embeddings can suffer if the word representations do not conform to the data drift. Thus, maintaining word embeddings to be consistent with the underlying data distribution is a key problem. In this work, we tackle this problem and propose TransDrift, a transformer-based prediction model for word embeddings. Leveraging the flexibility of the transformer, our model accurately learns the dynamics of the embedding drift and predicts future embedding. In experiments, we compare with existing methods and show that our model makes significantly more accurate predictions of the word embedding than the baselines. Crucially, by applying the predicted embeddings as a backbone for downstream classification tasks, we show that our embeddings lead to superior performance compared to the previous methods.

Keywords: NLP applications, transformers, Word2vec, drift, word embeddings

Procedia PDF Downloads 85

Authors: Amal Machtalay

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In this survey, we aim to review the rapidly growing literature on numerical methods to solve different forms of mean field problems, namely mean field games (MFG), mean field controls (MFC), potential MFGs, and master equations, as well as their corresponding recent applications. Here, we distinguish two families of numerical methods: iterative methods based on mesh generation and those called mesh-free, normally related to neural networking and learning frameworks.

Keywords: mean-field games, numerical schemes, partial differential equations, complex systems, machine learning

Procedia PDF Downloads 110

Authors: Shelley Y. Hawkins

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Introduction/Background: As technology has grown exponentially in healthcare, nurse educators must prepare Advanced Practice Registered Nurse (APRN) graduates with the knowledge and skills in information systems/technology to support and improve patient care and health care systems. APRN’s are expected to lead in caring for populations who lack accessibility and availability through the use of technology, specifically telehealth. The capacity to effectively and efficiently use technology in patient care delivery is clearly delineated in the American Association of Colleges of Nursing (AACN) Doctor of Nursing Practice (DNP) and Master of Science in Nursing (MSN) Essentials. However, APRN’s have minimal, or no, exposure to formalized telehealth education and lack necessary technical skills needed to incorporate telehealth into their patient care. APRN’s must successfully master the technology using telehealth/telemedicine, electronic health records, health information technology, and clinical decision support systems to advance health. Furthermore, APRN’s must be prepared to lead the coordination and collaboration with other healthcare providers in their use and application. Aim/Goal/Purpose: The purpose of this presentation is to establish and operationalize telehealth-focused educational partnerships between one University School of Nursing and two health care systems in order to enhance the preparation of APRN NP students for practice, teaching, and/or scholarly endeavors. Methods: The proposed project was initially presented by the project director to selected multidisciplinary stakeholders including leadership, home telehealth personnel, primary care providers, and decision support systems within two major health care systems to garner their support for acceptance and implementation. Concurrently, backing was obtained from key university-affiliated colleagues including the Director of Simulation and Innovative Learning Lab and Coordinator of the Health Care Informatics Program. Technology experts skilled in design and production in web applications and electronic modules were secured from two local based technology companies. Results: Two telehealth-focused APRN Program academic/practice partnerships have been established. Students have opportunities to engage in clinically based telehealth experiences focused on: (1) providing patient care while incorporating various technology with a specific emphasis on telehealth; (2) conducting research and/or evidence-based practice projects in order to further develop the scientific foundation regarding incorporation of telehealth with patient care; and (3) participating in the production of patient-level educational materials related to specific topical areas. Conclusions: Evidence-based APRN student telehealth clinical experiences will assist in preparing graduates who can effectively incorporate telehealth into their clinical practice. Greater access for diverse populations will be available as a result of the telehealth service model as well as better care and better outcomes at lower costs. Furthermore, APRN’s will provide the necessary leadership and coordination through interprofessional practice by transforming health care through new innovative care models using information systems and technology.

Keywords: academic/practice partnerships, advanced practice nursing, nursing education, telehealth

Procedia PDF Downloads 239

Authors: Juntip Kanjanasilp, Ratree Sawangjit, Kanokporn Meelap, Kwanchanok Kruthakool

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Depression is a common mental health disorder. Antidepressants are effective pharmacological treatments, but most patients have low medication adherence. This study aims to systematic review and meta-analysis what method increase the antidepressants adherence efficiently and improve clinical outcome. Systematic review of articles of randomized controlled trials obtained by a computerized literature search of The Cochrane, Library, Pubmed, Embase, PsycINFO, CINAHL, Education search, Web of Science and ThaiLIS (28 December 2017). Twenty-three studies were included and assessed the quality of research by ROB 2.0. The results reported that printing media improved in number of people who had medication adherence statistical significantly (p= 0.018), but education, phone call, and program utilization were no different (p=0.172, p=0.127, p=0.659). There was no significant difference in pharmacist’s group, health care team’s group and physician’s group (p=0.329, p=0.070, p=0.040). Times of intervention at 1 month and 6 months improved medication adherence significantly (p= 0.0001, p=0.013). There was significantly improved adherence in single intervention (p=0.027) but no different in multiple interventions (p=0.154). When we analyzed medication adherence with the mean score, no improved adherence was found, not relevant with who gives the intervention and times to intervention. However, the multiple interventions group was statistically significant improved medication adherence (p=0.040). Phone call and the physician’s group were statistically significant improved clinical outcomes in number of improved patients (0.025 and 0.020, respectively). But in the pharmacist’s group and physician’s group were not found difference in the mean score of clinical outcomes (p=0.993, p=0.120, respectively). Times to intervention and number of intervention were not significant difference than usual care. The overall intervention can increase antidepressant adherence, especially the printing media, and the appropriate timing of the intervention is at least 6 months. For effective treatment, the provider should have experience and expert in caring for patients with depressive disorders, such as a psychiatrist. Medical personnel should have knowledge in caring for these patients also.

Keywords: depression, medication adherence, clinical outcomes, systematic review, meta-analysis

Procedia PDF Downloads 132

Authors: Rosa L. Figueroa, Christopher A. Flores, Qing Zeng-Treitler

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A regular expression consists of sequence characters which allow describing a text path. Usually, in clinical research, regular expressions are manually created by programmers together with domain experts. Lately, there have been several efforts to investigate how to generate them automatically. This article presents a text classification algorithm based on regexes. The algorithm named REX was designed, and then, implemented as a simplified method to create regexes to classify Spanish text automatically. In order to classify ambiguous cases, such as, when multiple labels are assigned to a testing example, REX includes an information gain method Two sets of data were used to evaluate the algorithm’s effectiveness in clinical text classification tasks. The results indicate that the regular expression based classifier proposed in this work performs statically better regarding accuracy and F-measure than Support Vector Machine and Naïve Bayes for both datasets.

Keywords: information gain, regular expressions, smith-waterman algorithm, text classification

Procedia PDF Downloads 314

Authors: Meera Tandan, Mohan Timilsina, Martin Cormican, Akke Vellinga

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Background: In general practice, many infections are treated empirically without microbiological confirmation. Understanding susceptibility of antimicrobials during empirical prescribing can be helpful to reduce inappropriate prescribing. This study aims to apply a prediction model using a decision tree approach to predict the antimicrobial resistance (AMR) of urinary tract infections (UTI) based on non-clinical features of patients over 65 years. Decision tree models are a novel idea to predict the outcome of AMR at an initial stage. Method: Data was extracted from the database of the microbiological laboratory of the University Hospitals Galway on all antimicrobial susceptibility testing (AST) of urine specimens from patients over the age of 65 from January 2011 to December 2014. The primary endpoint was resistance to common antimicrobials (Nitrofurantoin, trimethoprim, ciprofloxacin, co-amoxiclav and amoxicillin) used to treat UTI. A classification and regression tree (CART) model was generated with the outcome ‘resistant infection’. The importance of each predictor (the number of previous samples, age, gender, location (nursing home, hospital, community) and causative agent) on antimicrobial resistance was estimated. Sensitivity, specificity, negative predictive (NPV) and positive predictive (PPV) values were used to evaluate the performance of the model. Seventy-five percent (75%) of the data were used as a training set and validation of the model was performed with the remaining 25% of the dataset. Results: A total of 9805 UTI patients over 65 years had their urine sample submitted for AST at least once over the four years. E.coli, Klebsiella, Proteus species were the most commonly identified pathogens among the UTI patients without catheter whereas Sertia, Staphylococcus aureus; Enterobacter was common with the catheter. The validated CART model shows slight differences in the sensitivity, specificity, PPV and NPV in between the models with and without the causative organisms. The sensitivity, specificity, PPV and NPV for the model with non-clinical predictors was between 74% and 88% depending on the antimicrobial. Conclusion: The CART models developed using non-clinical predictors have good performance when predicting antimicrobial resistance. These models predict which antimicrobial may be the most appropriate based on non-clinical factors. Other CART models, prospective data collection and validation and an increasing number of non-clinical factors will improve model performance. The presented model provides an alternative approach to decision making on antimicrobial prescribing for UTIs in older patients.

Keywords: antimicrobial resistance, urinary tract infection, prediction, decision tree

Procedia PDF Downloads 251

Authors: Moshe Wasserblat, Jonathan Mamou, Oren Pereg

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Natural Language Processing (NLP) has made a major leap in the last few years, in practical integration into medical solutions; for example, extracting clinical concepts from medical texts such as medical condition, medication, treatment, and symptoms. However, training and deploying those models in real environments still demands a large amount of annotated data and NLP/Machine Learning (ML) expertise, which makes this process costly and time-consuming. We present a practical and efficient method for clinical concept extraction that does not require costly labeled data nor ML expertise. The method includes three steps: Step 1- the user injects a large in-domain text corpus (e.g., PubMed). Then, the system builds a contextual model containing vector representations of concepts in the corpus, in an unsupervised manner (e.g., Phrase2Vec). Step 2- the user provides a seed set of terms representing a specific medical concept (e.g., for the concept of the symptoms, the user may provide: ‘dry mouth,’ ‘itchy skin,’ and ‘blurred vision’). Then, the system matches the seed set against the contextual model and extracts the most semantically similar terms (e.g., additional symptoms). The result is a complete set of terms related to the medical concept. Step 3 –in production, there is a need to extract medical concepts from the unseen medical text. The system extracts key-phrases from the new text, then matches them against the complete set of terms from step 2, and the most semantically similar will be annotated with the same medical concept category. As an example, the seed symptom concepts would result in the following annotation: “The patient complaints on fatigue [symptom], dry skin [symptom], and Weight loss [symptom], which can be an early sign for Diabetes.” Our evaluations show promising results for extracting concepts from medical corpora. The method allows medical analysts to easily and efficiently build taxonomies (in step 2) representing their domain-specific concepts, and automatically annotate a large number of texts (in step 3) for classification/summarization of medical reports.

Keywords: clinical concepts, concept expansion, medical records annotation, medical records summarization

Procedia PDF Downloads 130

Authors: Lancer Scott

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Purpose: High quality clinical disaster medicine requires providers working collaboratively to care for multiple patients in chaotic environments; however, many providers lack adequate training. To address this deficit, we created a competency-based, 5-hour Emergency Preparedness Training (EPT) curriculum using didactics, small-group discussion, and kinetic learning. The goal was to evaluate the effect of a short course on improving provider knowledge, confidence and skills in disaster scenarios. Methods: Diverse groups of medical university students, health care professionals, and community members were enrolled between 2011 and 2014. The course consisted of didactic lectures, small group exercises, and two live, multi-patient mass casualty incident (MCI) scenarios. The outcome measures were based on core competencies and performance objectives developed by a curriculum task force and assessed via trained facilitator observation, pre- and post-testing, and a course evaluation. Results: 708 participants completed were trained between November 2011 and August 2014, including 49.9% physicians, 31.9% medical students, 7.2% nurses, and 11% various other healthcare professions. 100% of participants completed the pre-test and 71.9% completed the post-test, with average correct answers increasing from 39% to 60%. Following didactics, trainees met 73% and 96% of performance objectives for the two small group exercises and 68.5% and 61.1% of performance objectives for the two MCI scenarios. Average trainee self-assessment of both overall knowledge and skill with clinical disasters improved from 33/100 to 74/100 (overall knowledge) and 33/100 to 77/100 (overall skill). The course assessment was completed by 34.3% participants, of whom 91.5% highly recommended the course. Conclusion: A relatively short, intensive EPT course can improve the ability of a diverse group of disaster care providers to respond effectively to mass casualty scenarios.

Keywords: clinical disaster medicine, training, hospital preparedness, surge capacity, education, curriculum, research, performance, training, student, physicians, nurses, health care providers, health care

Procedia PDF Downloads 190

Authors: Yaşar Önal, Aydın Akın

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This study was conducted Ismailoglu grape type (Vitis vinifera L.) and its vine which was aged 15 was grown on its own root in a vegetation period of 2013 in Nevşehir province in Turkey. In this research, it was investigated whether the applications of Control (C), 1/3 cluster tip reduction (1/3 CTR), shoot tip reduction (STR), 1/3 CTR + STR, TKI-HUMAS (TKI-HM) (Soil) (S), TKI-HM (Foliar) (F), TKI-HM (S + F), 1/3 CTR + TKI-HM (S), 1/3 CTR + TKI-HM (F), 1/3 CTR + TKI-HM (S+F), STR + TKI-HM (S), STR + TKI-HM (F), STR + TKI-HM (S + F), 1/3 CTR + STR+TKI-HM (S), 1/3 CTR + STR + TKI-HM (F), 1/3 CTR + STR + TKI-HM (S + F) on yield and yield components of Ismailoglu grape type. The results were obtained as the highest fresh grape yield (16.15 kg/vine) with TKI-HM (S), as the highest cluster weight (652.39 g) with 1/3 CTR + STR, as the highest 100 berry weight (419.07 g) with 1/3 CTR + STR + TKI-HM (F), as the highest maturity index (44.06) with 1/3 CTR, as the highest must yield (810.00 ml) with STR + TKI-HM (F), as the highest intensity of L* color (42.04) with TKI-HM (S + F), as the highest intensity of a* color (2.60) with 1/3 CTR + TKI-HM (S), as the highest intensity of b* color (7.16) with 1/3 CTR + TKI-HM (S) applications. To increase the fresh grape yield of Ismailoglu grape type can be recommended TKI-HM (S) application.

Keywords: 1/3 cluster tip reduction, shoot tip reduction, TKI-Humas application, yield and yield components

Procedia PDF Downloads 395

Authors: G. K. S. Prakash, Rao K. Srinivasa

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MEMS plays an important role in wide range of applications like biological, automobiles, military and communication engineering. This paper mainly investigates on capacitive shunt RF MEMS switch with low actuation voltage and low insertion losses. To trim the pull-in voltage, a step structure has introduced to trim air gap between the beam and the dielectric layer with that pull in voltage is trim to 2.9 V. The switching time of the proposed switch is 39.1μs, and capacitance ratio is 67. To get more isolation, we have used aluminum nitride as dielectric material instead of silicon nitride (Si₃N₄) and silicon dioxide (SiO₂) because aluminum nitride has high dielectric constant (εᵣ = 9.5) increases the OFF capacitance and eventually increases the isolation of the switch. The results show that the switch is ON state involves return loss (S₁₁) less than -25 dB up to 40 GHz and insertion loss (S₂₁) is more than -1 dB up to 35 GHz. In OFF state switch shows maximum isolation (S₂₁) of -38 dB occurs at a frequency of 25-27 GHz for K band applications.

Keywords: RF MEMS, actuation voltage, isolation loss, switches

Procedia PDF Downloads 360

Authors: Mequanent Wale Mekonen, Edoardo Otranto, Angela Alibrandi

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Diabetic kidney disease is one of the main microvascular complications caused by diabetes. Several clinical and biochemical variables are reported to be associated with diabetic kidney disease in people with type 2 diabetes. However, their interrelations could distort the effect estimation of these variables for the disease's progression. The objective of the study is to determine how the biochemical and clinical variables in people with type 2 diabetes are interrelated with each other and their effects on kidney disease progression through advanced statistical methods. First, principal component analysis was used to explore how the biochemical and clinical variables intercorrelate with each other, which helped us reduce a set of correlated biochemical variables to a smaller number of uncorrelated variables. Then, ordered logit regression models (cumulative, stage, and adjacent) were employed to assess the effect of biochemical and clinical variables on the order-level response variable (progression of kidney function) by considering the proportionality assumption for more robust effect estimation. This retrospective cross-sectional study retrieved data from a type 2 diabetic cohort in a polyclinic hospital at the University of Messina, Italy. The principal component analysis yielded three uncorrelated components. These are principal component 1, with negative loading of glycosylated haemoglobin, glycemia, and creatinine; principal component 2, with negative loading of total cholesterol and low-density lipoprotein; and principal component 3, with negative loading of high-density lipoprotein and a positive load of triglycerides. The ordered logit models (cumulative, stage, and adjacent) showed that the first component (glycosylated haemoglobin, glycemia, and creatinine) had a significant effect on the progression of kidney disease. For instance, the cumulative odds model indicated that the first principal component (linear combination of glycosylated haemoglobin, glycemia, and creatinine) had a strong and significant effect on the progression of kidney disease, with an effect or odds ratio of 0.423 (P value = 0.000). However, this effect was inconsistent across levels of kidney disease because the first principal component did not meet the proportionality assumption. To address the proportionality problem and provide robust effect estimates, alternative ordered logit models, such as the partial cumulative odds model, the partial adjacent category model, and the partial continuation ratio model, were used. These models suggested that clinical variables such as age, sex, body mass index, medication (metformin), and biochemical variables such as glycosylated haemoglobin, glycemia, and creatinine have a significant effect on the progression of kidney disease.

Keywords: diabetic kidney disease, ordered logit model, principal component analysis, type 2 diabetes

Procedia PDF Downloads 36

Authors: Shalinawati Ramli, Khairani Omar, Nurul Azmawati Mohamed, Zarini Ismail, Nur Syahrina Rahim, Nurul Hayati Chamhuri

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Medical doctors’ work to prevent, diagnose, treat diseases, disorders, and injuries as well as prescribing medication. Many people are attracted to this profession because it gives them the opportunity to help others. Doctors’ improve quality of life by providing advice, healing physical ailments and performing complex surgeries. Medicine is a profession in which dedication to the wellbeing of others is of paramount importance. Balancing the requirements of work and personal life can be a struggle as the demand of work as a doctors’ is great. Perception and expectation of medical students regarding the lifestyle of doctors’ is important to ensure that they had made the right career choice. Thus, the aim of this study is to assess the perception of pre-clinical students regarding doctors’ lifestyle. This study is a cross-sectional study involving all third-year pre-clinical medical students at University Sains Islam Malaysia. A total of 81 students participated in this study. Participants were given a set of questionnaire consisting of demographic data, open-ended questions on their perception on doctors’ lifestyle of working environment, salary expectation and family life. Thematic analysis were used to analyse the data. The participants comprised 69% female and their age range was between 20-21 years old. Majority of them were from middle-income families. Majority of the students perceived that the doctors’ lifestyle would be busy (72%). Approximately 30% of them expected that the time schedule will be unpredictable, 21% mentioned that sacrifice is required and 16% perceived it as a tiring job. Other themes emerged were ‘requiring high commitment’ (6%), challenging (7%) and risky (4%). With regards to salary expectation, 48% expected reasonable salary, 33% high salary and 12% described it as 'not worth compared to the workload'. Majority of them perceived that their family life will be restricted (62%) and time management is important (33%). Only 15% mentioned that family members have to sacrifice and spousal understanding is important (7%). About 10% of them perceived that their family will not be affected by their profession. Majority of the medical students perceived a busy doctors’ lifestyle, reasonable salary and restricted family life. However, there was a significant proportion of them who required counselling for better preparation of their future lifestyle.

Keywords: doctors lifestyle, pre-clinical students, perception, understanding

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Authors: Barbora Haltofová

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In recent years, citizens have become an important source of geographic information and, therefore, geo-crowdsourcing, often known as volunteered geographic information, has provided an interesting alternative to traditional mapping practices which are becoming expensive, resource-intensive and unable to capture the dynamic nature of urban environments. In order to address a gap in research literature, this paper deals with a survey conducted to assess the current state of geo-crowdsourcing, a recent phenomenon popular with people who collect geographic information using their smartphones. This article points out that there is an increasing body of knowledge of geo-crowdsourcing mobile applications in the Visegrad countries marked by the ubiquitous Internet connection and the current massive proliferation of smartphones. This article shows how geo-crowdsourcing can be used as a complement, or in some cases a replacement, to traditionally generated sources of spatial data and information in public management. It discusses the new spaces of citizen participation constructed by these geo-crowdsourcing practices.

Keywords: citizen participation, e-Government, geo-crowdsourcing, participatory mapping, mobile applications

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Authors: Ajay Kumar, Neha Gupta

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This work presents the sensitivity assessment of Gallium Nitride (GaN) material-based FinFET by dielectric modulation in the nanocavity gap for label-free biosensing applications. The significant deflection is observed in the electrical characteristics such as drain current (ID), transconductance (gm), surface potential, energy band profile, electric field, sub-threshold slope (SS), and threshold voltage (Vth) in the presence of biomolecules owing to GaN material. Further, the device sensitivity is evaluated to identify the effectiveness of the proposed biosensor and its capability to detect the biomolecules with high precision or accuracy. Higher sensitivity is observed for Gelatin (k=12) in terms of on-current (SION), threshold voltage (SVth), and switching ratio (SSR) by 104.88%, 82.12%, and 119.73%, respectively. This work is performed using a powerful tool 3D Sentaurus TCAD using a well-calibrated structure. All the results pave the way for GaN-FinFET as a viable candidate for label-free dielectric modulated biosensor applications.

Keywords: biosensor, biomolecules, FinFET, sensitivity

Procedia PDF Downloads 199

Authors: Ratun Rahman, Rafid Islam, Akin Ahmed, Kamrul Hasan, Hasan Mahmud

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Malware is becoming more prevalent, and several threat categories have risen dramatically in recent years. This paper provides a bird's-eye view of the world of malware analysis. The efficiency of five different machine learning methods (Naive Bayes, K-Nearest Neighbor, Decision Tree, Random Forest, and TensorFlow Decision Forest) combined with features picked from the retrieval of Android permissions to categorize applications as harmful or benign is investigated in this study. The test set consists of 1,168 samples (among these android applications, 602 are malware and 566 are benign applications), each consisting of 948 features (permissions). Using the permission-based dataset, the machine learning algorithms then produce accuracy rates above 80%, except the Naive Bayes Algorithm with 65% accuracy. Of the considered algorithms TensorFlow Decision Forest performed the best with an accuracy of 90%.

Keywords: android malware detection, machine learning, malware, malware analysis

Procedia PDF Downloads 163

Authors: Kumar Gular, Viswanathan S., Mastour Saeed Alshahrani, Ravi Shankar Reddy, Jaya Shanker Tedla, Snehil Dixit, Ajay Prasad Gautam, Venkata Nagaraj Kakaraparthi, Devika Rani Sangadala

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Background: Despite trunk control’s significant contribution to improving various functional activity components, the independent effect of trunk performance on quality of life is yet to be estimated in stroke survivors. Ascertaining the correlation between trunk control and self-reported quality of life while evaluating the effect of demographic and clinical characteristics on their relationship will guide concerned healthcare professionals in designing ideal rehabilitation protocols during the late sub-acute stroke stage of recovery. The aims of the present research were to (1) investigate the associations of trunk performance with self-rated quality of life and (2) evaluate if age, body mass index (BMI), and clinical characteristics mediate the relationship between trunk motor performance and perceived quality of life in the sub-acute stroke population. Methods: Trunk motor functions and quality of life among the late sub-acute stroke population aged 57.53 ± 6.42 years were evaluated through the trunk Impairment Scale (TIS) and Stroke specific quality of life (SSQOL) questionnaire, respectively. Pearson correlation coefficients and mediation analysis were performed to elucidate the relationship of trunk motor function with quality of life and determine the mediation impact of demographic and clinical characteristics on their association, respectively. Results: The current study observed significant correlations between trunk motor functions (TIS) and quality of life (SSQOL) with r=0.68 (p<0.001). Age, BMI, and type of stroke were detected as potential mediating factors in the association between trunk performance and quality of life. Conclusion: Validated associations between trunk motor functions and perceived quality of life among the late sub-acute stroke population emphasize the importance of comprehensive evaluation of trunk control. Rehabilitation specialists should focus on appropriate strategies to enhance trunk performance anticipating the potential effects of age, BMI, and type of stroke to improve health-related quality of life in stroke survivors.

Keywords: sub-acute stroke, quality of life, functional independence, trunk control

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Authors: Micheal O. Alabi

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Additive manufacturing (AM) is the official industry standard term (ASTM F2792) for all applications of the technology which is also known as 3D printing technology. It is defined as the process of joining materials to make objects from 3D model data, and it is usually layer upon layer, as opposed to subtractive manufacturing methodologies. This technology has gained significant interest within the academic, research institute and industry because of its ability to create complex geometries with customizable material properties. Despite the late adoption of the technology, additive manufacturing has been active in South Africa for past 21 years and it is predicted that additive manufacturing technology will play a significant and game-changing role in the fourth industrial revolution and in particular it promises to play an ever-growing role in efforts to re-industrialize the economy of South Africa. At the end of 2006, there are approximately ninety 3D printers in South Africa and in 2015 it was estimated that there are 3500 additive manufacturing systems and 3D printers in circulation in South Africa. A reasonable number of these additive manufacturing machines are in the high end of the market, in science councils and higher education institutions and this shows that the future of additive manufacturing in South Africa is very brighter compared to other African countries. This paper reviews the past and current industrial applications of additive manufacturing in South Africa from the academic research and industry perspective and what are the benefits of this technology to manufacturing companies and industrial sectors in the country.

Keywords: additive manufacturing, 3D printing technology, industrial applications, manufacturing

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Authors: Adila Shaukat, Hussam Al Soub, Muna Al Maslamani, Abdullatif Al Khal

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Background: The aim of this study was to assess clinical presentation and antimicrobial susceptibility of Streptococcus (S.) anginosus group infections in Hamad General Hospital, a tertiary care hospital in the state of Qatar, which is a multinational community. The S. anginosus group is a subgroup of viridans streptococci that consist of 3 different species: S. anginosus, S. constellatus, and S. intermedius. Although a part of the human bacteria flora, they have potential to cause suppurative infections. Method: We studied a total of 101 patients with S. anginosus group infections from January 2006 until March 2012 by reviewing medical records and identification of organisms by VITEK 2 and MALDI-TOF. Results: The most common sites of infection were skin and soft tissue, intra-abdominal, and bacteremia (28.7%, 24.8%, and 22.7%, respectively). Abscess formation was seen in approximately 30% of patients. Streptococcus constellatus was the most common isolated species (40%) followed by S. anginosus(30%) and S. intermedius(7%). In 23% of specimens, the species was unidentified. The most common type of specimen for organism isolation was blood followed by pus and tissue (50%, 22%, and 8%, respectively). Streptococcus constellatus was more frequently associated with abdominal and skin and soft tissue infections than the other 2 species, whereas S. anginosus was isolated more frequently from blood. All isolates were susceptible to penicillin, ceftriaxone, and vancomycin. Susceptibility to erythromycin and clindamycin was also good, reaching 91% and 95%, respectively. Forty percent of patients needed surgical drainage along with antibiotic therapy. Conclusions: Identification of S. anginosus group to species level is helpful in clinical practice because different species exhibit different pathogenic potentials.

Keywords: abscess, bacterial infection, bacteremia, Streptococcus anginosus

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Authors: Tanimola Kazeem Abiodun

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In Nigeria, both formal education and distance learning opportunities are used in teacher training. Practical courses aim to improve the skills of teacher candidates in a school environment. Teacher candidates attend kindergarten classes under the supervision of a teacher. In this context, the guiding skills of teachers gain importance in terms of shaping candidates’ perceptions about teaching profession. In this study, the teachers’ perceptions related to the guiding skills within the practical courses were determined. Also, the perceptions and applications related to guiding skills were compared. A Likert scale questionnaire and an open-ended question were used to determine perceptions and applications. 120 questionnaires were taken into consideration and analyses of data were performed by using percentage distribution and QSR Nvivo 8 program. In this study, statements related to teachers’ perceptions about the guiding skills were asked and it is determined that almost all the teachers agreed about the importance of these statements. On the other hand, how these guidance skills are applied by teachers is also queried with an open-ended question. Finally, thoughts and applications related to guidance skills were compared to each other. Based on this comparison, it is seen that there are some differences between the thoughts and applications especially related with time management, planning, feedbacks, curriculum, workload, rules and guidance. It can be said that some guidance skills cannot be controlled only by teachers. For example, candidates’ motivation, attention, population and educational environment are also determinative factors for effective guidance. In summary, it is necessary to have prior conditions for teachers to apply these idealized guidance skills for training more successful candidates to pre-school education era. At this point, organization of practical courses by the faculties gains importance and in this context it is crucial for faculties to revise their applications based on more detailed researches.

Keywords: teacher training, guiding skills, education, practical courses

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Authors: Jack Nash, Chris Simpson, Holly Hurn, Ronel Terblanche, Alan Mistlin

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There is an increasing incidence of mild traumatic brain injury (mTBI) cases throughout sport and with this, a growing interest from governing bodies to ensure these are managed appropriately and player welfare is prioritised. The Berlin consensus statement on concussion in sport recommends a multidisciplinary approach when managing those patients who do not have full resolution of mTBI symptoms. There are as of yet no standardised guideline to follow in the treatment of complex cases mTBI in athletes. The aim of this project was to analyse the outcomes, both clinical and vocational, of all patients admitted to the mild Traumatic Brain Injury (mTBI) service at the UK’s Defence Military Rehabilitation Centre Headley Court between 1st June 2008 and 1st February 2017, as a result of a sport induced injury, and evaluate potential predictive indicators of outcome. Patients were identified from a database maintained by the mTBI service. Clinical and occupational outcomes were ascertained from medical and occupational employment records, recorded prospectively, at time of discharge from the mTBI service. Outcomes were graded based on the vocational independence scale (VIS) and clinical documentation at discharge. Predictive indicators including referral time, age at time of injury, previous mental health diagnosis and a financial claim in place at time of entry to service were assessed using logistic regression. 45 Patients were treated for sport-related mTBI during this time frame. Clinically 96% of patients had full resolution of their mTBI symptoms after input from the mTBI service. 51% of patients returned to work at their previous vocational level, 4% had ongoing mTBI symptoms, 22% had ongoing physical rehabilitation needs, 11% required mental health input and 11% required further vestibular rehabilitation. Neither age, time to referral, pre-existing mental health condition nor compensation seeking had a significant impact on either vocational or clinical outcome in this population. The vast majority of patients reviewed in the mTBI clinic had persistent symptoms which could not be managed in primary care. A consultant-led, multidisciplinary approach to the diagnosis and management of mTBI has resulted in excellent clinical outcomes in these complex cases. High levels of symptom resolution suggest that this referral and treatment pathway is successful and is a model which could be replicated in other organisations with consultant led input. Further understanding of both predictive and individual factors would allow clinicians to focus treatments on those who are most likely to develop long-term complications following mTBI. A consultant-led, multidisciplinary service ensures a large number of patients will have complete resolution of mTBI symptoms after sport-related mTBI. Further research is now required to ascertain the key predictive indicators of outcome following sport-related mTBI.

Keywords: brain injury, concussion, neurology, rehabilitation, sports injury

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Authors: Syakirin O. Yong, Nasrudin A. Rahim, Bilal M. Eid, Buray Tankut

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The aim of this paper is to develop an ultra-fast gate driver for Silicon Carbide (SiC) based switching device applications such as AC/DC DC/AC converters. Wide bandgap semiconductors such as SiC switches are growing rapidly nowadays due to their numerous capabilities such as faster switching, higher power density and higher voltage level. Wide band-gap switches can work properly on high frequencies such 50-250 kHz which is very useful for many power electronic applications such as solar inverters. Increasing the frequency minimizes the output filter size and system complexity however, this causes huge spike between MOSFET’s drain and source leg which leads to the failure of MOSFET if the voltage rating is exceeded. This paper investigates and concludes the optimum design for a gate drive board for SiC MOSFET switches without causing spikes and noises.

Keywords: PV system, lithium-ion, charger, constant current, constant voltage, renewable energy

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Authors: Yassine Bouzouita, Oumaima Belghith, Cyrine Zitoun, Charles Bonneau

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Performance measurement framework (PMF) is an essential tool in any organization to assess the performance of its processes. It guides businesses to stay on track with their objectives and benchmark themselves from the market. With the growing trend of the digital transformation of business processes, led by innovations in artificial intelligence (AI) & Big Data applications, developing a mature system capable of capturing the impact of digital solutions across different industries became a necessity. Based on the conducted research, no such system has been developed in academia nor the industry. In this context, this paper covers a variety of methodologies on performance measurement, overviews the major AI and big data applications in the banking sector, and covers an exhaustive list of relevant metrics. Consequently, this paper is of interest to both researchers and practitioners. From an academic perspective, it offers a comparative analysis of the reviewed performance measurement frameworks. From an industry perspective, it offers exhaustive research, from market leaders, of the major applications of AI and Big Data technologies, across the different departments of an organization. Moreover, it suggests a standardized classification model with a well-defined structure of intelligent digital solutions. The aforementioned classification is mapped to a centralized library that contains an indexed collection of potential metrics for each application. This library is arranged in a manner that facilitates the rapid search and retrieval of relevant metrics. This proposed framework is meant to guide professionals in identifying the most appropriate AI and big data applications that should be adopted. Furthermore, it will help them meet their business objectives through understanding the potential impact of such solutions on the entire organization.

Keywords: AI and Big Data applications, impact assessment, metrics, performance measurement

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Authors: Madhavi-Priya Singh, Liam Lowe, Farouk Arnaout, Ludmilla Pillay, Giordan Perez, Luke Mischker, Steve Costa

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An Emergency Department consultant identified the failure of medical students to complete the task of clerking a patient in its entirety. As six medical students on our first clinical placement, we recognised our own failure and endeavoured to examine why this failure was consistent among all medical students that had been given this task, despite our best motivations as adult learner. Our aim is to understand and investigate the elements which impeded our ability to learn and perform as medical students in the clinical environment, with reference to the prescribed task. We also aim to generate a discussion around the delivery of medical education with potential solutions to these barriers. Six medical students gathered together to have a comprehensive reflective discussion to identify possible factors leading to the failure of the task. First, we thoroughly analysed the delivery of the instructions with reference to the literature to identify potential flaws. We then examined personal, social, ethical, and cultural factors which may have impacted our ability to complete the task in its entirety. Through collation of our shared experiences, with support from discussion in the field of medical education and ethics, we identified two major areas that impacted our ability to complete the set task. First, we experienced an ethical conflict where we believed the inconvenience and potential harm inflicted on patients did not justify the positive impact the patient interaction would have on our medical learning. Second, we identified a lack of confidence stemming from multiple factors, including the conflict between preclinical and clinical learning, perceptions of perfectionism in the culture of medicine, and the influence of upward social comparison. After discussions, we found that the various factors we identified exacerbated the fears and doubts we already had about our own abilities and that of the medical education system. This doubt led us to avoid completing certain aspects of the tasks that were prescribed and further reinforced our vulnerability and perceived incompetence. Exploration of philosophical theories identified the importance of the role of doubt in education. We propose the need for further discussion around incorporating both pedagogic and andragogic teaching styles in clinical medical education and the acceptance of doubt as a driver of our learning. Doubt will continue to permeate our thoughts and actions no matter what. The moral or psychological distress that arises from this is the key motivating factor for our avoidance of tasks. If we accept this doubt and education embraces this doubt, it will no longer linger in the shadows as a negative and restrictive emotion but fuel a brighter dialogue and positive learning experience, ultimately assisting us in achieving our full potential.

Keywords: medical education, clinical education, andragogy, pedagogy

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Authors: Danica Vidotto

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Digital technology is continuing to disrupt and challenge local conventions of teaching and education. As mobile devices continue to make their way into contemporary classrooms, educators need new pedagogies incorporating information communication technology to help reform the learning environment. In physical education, however, this can seem controversial as physical inactivity is often related to an excess of screen-time. This qualitative research project is an investigation on how physical educators use mobile device applications (apps) in their pedagogy and to what end. A comprehensive literature review is included to examine and engage current academic research of new pedagogies and technology, and their relevance to physical activity. Data were collected through five semi-structured interviews resulting in three overarching themes; i) changing pedagogies in physical education; ii) the perceived benefits and experienced challenges of using apps; and iii) apps, physical activity, and physical education. This study concludes with a discussion of the findings engaging the literature, discussing the implications of findings, and recommendations for future research.

Keywords: applications (apps), mobile devices, new pedagogies, physical education

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Authors: Eashwar V. Somasundaram, Raoul R. Wadhwa, Jacob G. Scott

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The use of radiomics in measuring geometric properties of tumor images such as size, surface area, and volume has been invaluable in assessing cancer diagnosis, treatment, and prognosis. In addition to analyzing geometric properties, radiomics would benefit from measuring topological properties using persistent homology. Intuitively, features uncovered by persistent homology may correlate to tumor structural features. One example is necrotic cavities (corresponding to 2D topological features), which are markers of very aggressive tumors. We develop a data pipeline in R that clusters tumors images based on persistent homology is used to identify meaningful clinical distinctions between tumors and possibly new relationships not captured by established clinical categorizations. A preliminary analysis was performed on 16 Magnetic Resonance Imaging (MRI) breast tissue segments downloaded from the 'Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis' (I-SPY TRIAL or ISPY1) collection in The Cancer Imaging Archive. Each segment represents a patient’s breast tumor prior to treatment. The ISPY1 dataset also provided the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status data. A persistent homology matrix up to 2-dimensional features was calculated for each of the MRI segmentation. Wasserstein distances were then calculated between all pairwise tumor image persistent homology matrices to create a distance matrix for each feature dimension. Since Wasserstein distances were calculated for 0, 1, and 2-dimensional features, three hierarchal clusters were constructed. The adjusted Rand Index was used to see how well the clusters corresponded to the ER/PR/HER2 status of the tumors. Triple-negative cancers (negative status for all three receptors) significantly clustered together in the 2-dimensional features dendrogram (Adjusted Rand Index of .35, p = .031). It is known that having a triple-negative breast tumor is associated with aggressive tumor growth and poor prognosis when compared to non-triple negative breast tumors. The aggressive tumor growth associated with triple-negative tumors may have a unique structure in an MRI segmentation, which persistent homology is able to identify. This preliminary analysis shows promising results in the use of persistent homology on tumor imaging to assess the severity of breast tumors. The next step is to apply this pipeline to other tumor segment images from The Cancer Imaging Archive at different sites such as the lung, kidney, and brain. In addition, whether other clinical parameters, such as overall survival, tumor stage, and tumor genotype data are captured well in persistent homology clusters will be assessed. If analyzing tumor MRI segments using persistent homology consistently identifies clinical relationships, this could enable clinicians to use persistent homology data as a noninvasive way to inform clinical decision making in oncology.

Keywords: cancer biology, oncology, persistent homology, radiomics, topological data analysis, tumor imaging

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Authors: Omneya M. Helmy, Mona T. Kashef

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Aminoglycosides are used in treating a wide range of infections caused by both Gram-negative and Gram positive bacteria. The presence of 16S rRNA methyl transferases (16S-RMTase) is among the newly discovered resistance mechanisms that confer high resistance to clinically useful aminoglycosides. Cephalosporins are the most commonly used antimicrobials in Egypt; therefore, this study was conducted to determine the isolation frequency of 16S rRNA methyl transferases among third generation cephalosporin-resistant clinical isolates in Egypt. One hundred and twenty three cephalosporin resistant Gram-negative clinical isolates were screened for aminoglycoside resistance by the Kirby Bauer disk diffusion method and tested for possible production of 16S-RMTase. PCR testing and sequencing were used to confirm the presence of 16S-RMTase and the associated antimicrobial resistance determinants, as well as the genetic region surrounding the armA gene. Out of 123 isolates, 66 (53.66%) were resistant to at least one aminoglycoside antibiotic. Only one Escherichia coli isolate (E9ECMO) which was totally resistant to all tested aminoglycosides, was confirmed to have the armA gene in association with blaTEM-1, blaCTX-M-15, blaCTX-M-14 and aac(6)-Ib genes. The armA gene was found to be carried on a large A/C plasmid. Genetic mapping of the armA surrounding region revealed, for the first time, the association of armA with aac(6)-Ib on the same transposon. In Conclusion, the isolation frequency of 16S-RMTase was low among the tested cephalosporin-resistant clinical samples. However, a novel composite transposon has been detected conferring high-level aminoglycosides resistance.

Keywords: aminoglcosides, armA gene, β lactmases, 16S rRNA methyl transferases

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Authors: Mona T. Kashef, Omneya M. Helmy

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Multidrug resistant (MDR) bacteria have become a significant public health threat. The prevalence rates, of Gram negative MDR bacteria, are in continuous increase. However, few data are available about these resistant strains. Since, third generation cephalosporins are one of the most commonly used antimicrobials, we set out to investigate the prevalence, different mechanisms and clonal relatedness of multidrug resistance among third generation resistant Gram negative clinical isolates. A total of 114 Gram negative clinical isolates, previously characterized as being resistant to at least one of 3rd generation cephalosporins, were included in this study. Each isolate was tested, using Kirby Bauer disk diffusion method, against its assigned categories of antimicrobials. The role of efflux pump in resistance development was tested by the efflux pump inhibitor-based microplate assay using chloropromazine as an inhibitor. Detecting different aminoglycosides, β-lactams and quinolones resistance genes was done using polymerase chain reaction. The genetic diversity of MDR isolates was investigated using Random Amplification of Polymorphic DNA technique. MDR phenotype was detected in 101 isolates (89%). Efflux pump mediated resistance was detected in 49/101 isolates. Aminoglycosides resistance genes; armA and aac(6)-Ib were detected in one and 53 isolates, respectively. The aac(6)-Ib-cr allele, that also confers resistance to floroquinolones, was detected in 28/53 isolates. β-lactam resistance genes; blaTEM, blaSHV, blaCTX-M group 1 and group 9 were detected in 52, 29, 61 and 35 isolates, respectively. Quinolone resistance genes; qnrA, qnrB and qnrS were detectable in 2, 14, 8 isolates respectively, while qepA was not detectable at all. High diversity was observed among tested MDR isolates. MDR is common among 3rd generation cephalosporins resistant Gram negative bacteria, in Egypt. In most cases, resistance was caused by different mechanisms. Therefore, new treatment strategies should be implemented.

Keywords: gram negative, multidrug resistance, RAPD typing, resistance genes

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