Search results for: medical tools
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7093

Search results for: medical tools

5203 Social Media as a Tool for Medication Adherence and Personal Health Management

Authors: Huang Wei-Chi, Li Wei, Yu Tien-Chieh

Abstract:

Medication adherence is crucial for treatment success. Adherence problem is common in patients with polypharmacy, especially in the geriatric population who are vulnerable to multiple chronic conditions but averagely less knowledgeable about diseases and medications. In order to help patients take medications appropriately and enhance the understanding of diseases or medications, a Line official account named e-Pharmacist was designed. The line is a popular freeware app with the highest penetration rate (95.7%) in Taiwan. The interface of e-Pharmacist is user-friendly for easy-to-read and convenient operating. Differ from other medication adherence apps, users just added e-Pharmacist as a LINE friend without installing any more apps and the drug lists were automatically downloaded from the personal electronic medical records with security permission. Over and above medication reminder, several additional capabilities were set up and engaged in the platform of e-Pharmacist including prescription refill reservation, laboratory examination consultation, medical appointment registration, and “Daily Health Log” where patients can record and track data of blood pressure/blood sugar and daily meals for self-health management as well as can share the important information to clinical professionals when seeking medical help. Additionally, a Line chatbot was utilized to provide tailored medicine information for the individual user. From July 2020 to March 2022, around 3000 patients added e-pharmacist as Line friends. Every day more than 1500 patients receive messages from e-pharmacist to notify them to take medicine. Thanks to the e-pharmacist alert system and Chatbot, the low-compliance patients (defined by Program on Adherence to Medication, PAM) significantly dropped from 36% to 6%, whereas the high-compliance patients dramatically increased from 13% to 77%. The user satisfaction is 98%. In brief, an e-pharmacist is not only a medication reminder but also a tailored personal assistant with value-added service for health management.

Keywords: e-pharmacist, self-health management, medication reminder, value-added service

Procedia PDF Downloads 148
5202 An Investigation into the Correlation between Music Preferences and Emotional Regulation in Military Cadets

Authors: Chiu-Pin Wei

Abstract:

This research aims to explore the impact of music preferences on the emotional well-being of military academy students, recognizing the potential long-term implications for their high-stress careers post-graduation. Given the significance of positive emotion regulation in military personnel, this study focuses on understanding the types of music preferred by military cadets and analyzing how these preferences correlate with their emotional states. The study employs a quantitative approach, utilizing the Music Category Scale and Mood Scale to collect data. Statistical tools, such as Statistical Product and Service Solutions (SPSS), are employed for inferential analysis, including t-tests for emotional responses to instrumental and vocal music, one-way variance analysis for different demographic factors (grades, genders, and music listening frequencies), and Pearson's correlation to examine the relationship between music preferences and moods of military students.

Keywords: music preference, emotional regulation, military academic students, SPASS

Procedia PDF Downloads 61
5201 An Alternative Approach for Assessing the Impact of Cutting Conditions on Surface Roughness Using Single Decision Tree

Authors: S. Ghorbani, N. I. Polushin

Abstract:

In this study, an approach to identify factors affecting on surface roughness in a machining process is presented. This study is based on 81 data about surface roughness over a wide range of cutting tools (conventional, cutting tool with holes, cutting tool with composite material), workpiece materials (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). A single decision tree (SDT) analysis was done to identify factors for predicting a model of surface roughness, and the CART algorithm was employed for building and evaluating regression tree. Results show that a single decision tree is better than traditional regression models with higher rate and forecast accuracy and strong value.

Keywords: cutting condition, surface roughness, decision tree, CART algorithm

Procedia PDF Downloads 368
5200 Basic Characteristics and Prospects of Synchronized Stir Welding

Authors: Shoji Matsumoto

Abstract:

Friction Stir Welding (FSW) has been widely used in the automotive, aerospace, and high-tech industries due to its superior mechanical properties after welding. However, when it becomes a matter to perform a high-quality joint using FSW, it is necessary to secure an advanced tilt angle (usually 1 to 5 degrees) using a dedicated FSW machine and to use a joint structure and a restraining jig that can withstand the tool pressure applied during the jointing process using a highly rigid processing machine. One issue that has become a challenge in this process is ‘productivity and versatility’. To solve this problem, we have conducted research and development of multi-functioning machines and robotics with FSW tools, which combine cutting/milling and FSW functions as one in recent years. However, the narrow process window makes it prone to welding defects and lacks repeatability, which makes a limitation for FSW its use in the fields where precisions required. Another reason why FSW machines are not widely used in the world is because of the matter of very high cost of ownership.

Keywords: synchronized, stir, welding, friction, traveling speed, synchronized stir welding, friction stir welding

Procedia PDF Downloads 38
5199 Ecological Networks: From Structural Analysis to Synchronization

Authors: N. F. F. Ebecken, G. C. Pereira

Abstract:

Ecological systems are exposed and are influenced by various natural and anthropogenic disturbances. They produce various effects and states seeking response symmetry to a state of global phase coherence or stability and balance of their food webs. This research project addresses the development of a computational methodology for modeling plankton food webs. The use of algorithms to establish connections, the generation of representative fuzzy multigraphs and application of technical analysis of complex networks provide a set of tools for defining, analyzing and evaluating community structure of coastal aquatic ecosystems, beyond the estimate of possible external impacts to the networks. Thus, this study aims to develop computational systems and data models to assess how these ecological networks are structurally and functionally organized, to analyze the types and degree of compartmentalization and synchronization between oscillatory and interconnected elements network and the influence of disturbances on the overall pattern of rhythmicity of the system.

Keywords: ecological networks, plankton food webs, fuzzy multigraphs, dynamic of networks

Procedia PDF Downloads 295
5198 Evaluating the Effectiveness of Electronic Response Systems in Technology-Oriented Classes

Authors: Ahmad Salman

Abstract:

Electronic Response Systems such as Kahoot, Poll Everywhere, and Google Classroom are gaining a lot of popularity when surveying audiences in events, meetings, and classroom. The reason is mainly because of the ease of use and the convenience these tools bring since they provide mobile applications with a simple user interface. In this paper, we present a case study on the effectiveness of using Electronic Response Systems on student participation and learning experience in a classroom. We use a polling application for class exercises in two different technology-oriented classes. We evaluate the effectiveness of the usage of the polling applications through statistical analysis of the students performance in these two classes and compare them to the performances of students who took the same classes without using the polling application for class participation. Our results show an increase in the performances of the students who used the Electronic Response System when compared to those who did not by an average of 11%.

Keywords: Interactive Learning, Classroom Technology, Electronic Response Systems, Polling Applications, Learning Evaluation

Procedia PDF Downloads 123
5197 Green Aviation System: The Way Forward for Better Environment

Authors: Ramana Reddy, Vijay Kothari

Abstract:

Aircraft provide a fast, reliable mode of transport with no comparable alternative for long distance travel. Throughout the years, technology improvements have been made to aircraft and engines to make them more fuel efficient. Air traffic continues to grow around the world and needs more aircrafts to accommodate such rapid growth. This has direct consequences on two of the most important environmental factors i.e. emissions and noise. Aviation contributes about 2% of global greenhouse gas emissions. Aviation emits a number of pollutants that alter the chemical composition of the atmosphere, changing its radiative balance and hence influencing the climate. In order to reduce or if possible eliminate potential harm to the environment and also make air travel efficient and economical, an environmentally beneficial concept called “Green Aviation System” is required. This is a structured frame work with elements like innovative technologies/tools in engineering design, manufacturing, airport and fleet operations.

Keywords: air traffic, environment, emissions, noise, green aviation system

Procedia PDF Downloads 448
5196 The Digital Desert in Global Business: Digital Analytics as an Oasis of Hope for Sub-Saharan Africa

Authors: David Amoah Oduro

Abstract:

In the ever-evolving terrain of international business, a profound revolution is underway, guided by the swift integration and advancement of disruptive technologies like digital analytics. In today's international business landscape, where competition is fierce, and decisions are data-driven, the essence of this paper lies in offering a tangible roadmap for practitioners. It is a guide that bridges the chasm between theory and actionable insights, helping businesses, investors, and entrepreneurs navigate the complexities of international expansion into sub-Saharan Africa. This practitioner paper distils essential insights, methodologies, and actionable recommendations for businesses seeking to leverage digital analytics in their pursuit of market entry and expansion across the African continent. What sets this paper apart is its unwavering focus on a region ripe with potential: sub-Saharan Africa. The adoption and adaptation of digital analytics are not mere luxuries but essential strategic tools for evaluating countries and entering markets within this dynamic region. With the spotlight firmly fixed on sub-Saharan Africa, the aim is to provide a compelling resource to guide practitioners in their quest to unearth the vast opportunities hidden within sub-Saharan Africa's digital desert. The paper illuminates the pivotal role of digital analytics in providing a data-driven foundation for market entry decisions. It highlights the ability to uncover market trends, consumer behavior, and competitive landscapes. By understanding Africa's incredible diversity, the paper underscores the importance of tailoring market entry strategies to account for unique cultural, economic, and regulatory factors. For practitioners, this paper offers a set of actionable recommendations, including the creation of cross-functional teams, the integration of local expertise, and the cultivation of long-term partnerships to ensure sustainable market entry success. It advocates for a commitment to continuous learning and flexibility in adapting strategies as the African market evolves. This paper represents an invaluable resource for businesses, investors, and entrepreneurs who are keen on unlocking the potential of digital analytics for informed market entry in Africa. It serves as a guiding light, equipping practitioners with the essential tools and insights needed to thrive in this dynamic and diverse continent. With these key insights, methodologies, and recommendations, this paper is a roadmap to prosperous and sustainable market entry in Africa. It is vital for anyone looking to harness the transformational potential of digital analytics to create prosperous and sustainable ventures in a region brimming with promise. In the ever-advancing digital age, this practitioner paper becomes a lodestar, guiding businesses and visionaries toward success amidst the unique challenges and rewards of sub-Saharan Africa's international business landscape.

Keywords: global analytics, digital analytics, sub-Saharan Africa, data analytics

Procedia PDF Downloads 66
5195 Community Engagement of Motorcycle Taxi Drivers in Bangkok, Thailand

Authors: Wanchak Noichan, Phakchira Noichan, Nuntiya Noichun

Abstract:

The objectives of this research were 1) to study the level of community engagement, 2) to compare community engagement level of motorcycle taxi drivers in Bangkok, Thailand, classified by personal factors. The sample population of this study was 400 motorcycle taxi drivers in Bangkok, Thailand, using the unknown size method of W. G. Cochran's population. The sample was chosen by probability-based randomization. A study using quantitative methods (quantitative research) use the research tools as a questionnaire. The statistics used in the research were the mean, standard deviation, t-test, and F-Test (One-Way ANOVA). The study found that (1) the sample groups have a high level of community engagement (x̄=3.65, S.D.=0.735). (2) The sample groups with different ages, education, status, and income have different levels of community commitment with statistical significance at the level of 0.05.

Keywords: community engagement, motorcycle taxi drivers, Bangkok, Thailand

Procedia PDF Downloads 118
5194 Single Cell Rna Sequencing Operating from Benchside to Bedside: An Interesting Entry into Translational Genomics

Authors: Leo Nnamdi Ozurumba-Dwight

Abstract:

Single-cell genomic analytical systems have proved to be a platform to isolate bulk cells into selected single cells for genomic, proteomic, and related metabolomic studies. This is enabling systematic investigations of the level of heterogeneity in a diverse and wide pool of cell populations. Single cell technologies, embracing techniques such as high parameter flow cytometry, single-cell sequencing, and high-resolution images are playing vital roles in these investigations on messenger ribonucleic acid (mRNA) molecules and related gene expressions in tracking the nature and course of disease conditions. This entails targeted molecular investigations on unit cells that help us understand cell behavoiur and expressions, which can be examined for their health implications on the health state of patients. One of the vital good sides of single-cell RNA sequencing (scRNA seq) is its probing capacity to detect deranged or abnormal cell populations present within homogenously perceived pooled cells, which would have evaded cursory screening on the pooled cell populations of biological samples obtained as part of diagnostic procedures. Despite conduction of just single-cell transcriptome analysis, scRNAseq now permits comparison of the transcriptome of the individual cells, which can be evaluated for gene expressional patterns that depict areas of heterogeneity with pharmaceutical drug discovery and clinical treatment applications. It is vital to strictly work through the tools of investigations from wet lab to bioinformatics and computational tooled analyses. In the precise steps for scRNAseq, it is critical to do thorough and effective isolation of viable single cells from the tissues of interest using dependable techniques (such as FACS) before proceeding to lysis, as this enhances the appropriate picking of quality mRNA molecules for subsequent sequencing (such as by the use of Polymerase Chain Reaction machine). Interestingly, scRNAseq can be deployed to analyze various types of biological samples such as embryos, nervous systems, tumour cells, stem cells, lymphocytes, and haematopoietic cells. In haematopoietic cells, it can be used to stratify acute myeloid leukemia patterns in patients, sorting them out into cohorts that enable re-modeling of treatment regimens based on stratified presentations. In immunotherapy, it can furnish specialist clinician-immunologist with tools to re-model treatment for each patient, an attribute of precision medicine. Finally, the good predictive attribute of scRNAseq can help reduce the cost of treatment for patients, thus attracting more patients who would have otherwise been discouraged from seeking quality clinical consultation help due to perceived high cost. This is a positive paradigm shift for patients’ attitudes primed towards seeking treatment.

Keywords: immunotherapy, transcriptome, re-modeling, mRNA, scRNA-seq

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5193 Design On Demand (DoD): Spiral Model of The Lifecycle of Products in The Personal 3D-Printed Products' Market

Authors: Zuk Nechemia Turbovich

Abstract:

This paper introduces DoD, a contextual spiral model that describes the lifecycle of products intended for manufacturing using Personal 3D Printers (P3DP). The study is based on a review of the desktop P3DPs market that shows that the combination of digital connectivity, coupled with the potential ownership of P3DP by home users, is radically changing the form of the product lifecycle, comparatively to familiar lifecycle paradigms. The paper presents the change in the design process, considering the characterization of product types in the P3DP market and the possibility of having a direct dialogue between end-user and product designers. The model, as an updated paradigm, provides a strategic perspective on product design and tools for success, understanding that design is subject to rapid and continuous improvement and that products are subject to repair, update, and customization. The paper will include a review of real cases.

Keywords: lifecycle, mass-customization, personal 3d-printing, user involvement

Procedia PDF Downloads 175
5192 Integrating ICT- Based Applications for Sustainable Tourism Development in Algeria

Authors: Boutkhil Guemide, Chellali Benachaiba

Abstract:

Information and Communication Technology (ICT) has an inevitable impact on different industries and their performances. The tourism industry as the largest and fastest growing industry in the world cannot be excluded from this technology and its huge impacts. ICT provides information about tourist attractions in the different destinations before travelling and may improve tourists’ satisfaction. Although Algeria has great tourism potentials, it still needs to be performed well in promoting its attractions to international tourists via ICT tools yet. This research explores the impact of ICT on foreign tourists’ satisfaction of the tourism industry and uses Algerian tourist agencies as a case study, and proposes a model for the impact of ICT on sustainable tourism. Finally, it is concluded that e-ticketing, e-reservation, online payment, multilingual and updated information websites are essential needs for planning strategies in the field of e-tourism. Also, it is recommended that the tourism authorities should develop e-tourism infrastructures in order to keep up with the competitiveness of this field to enable the country to benefit from the global benefits of the tourism industry.

Keywords: Information and Communications Technology (ICT), tourism, tourists’ satisfaction, sustainable tourism

Procedia PDF Downloads 527
5191 Power of Sales and Marketing in Electronics Engineering with E-commerce: Connecting the Circuits

Authors: Muhammad Awais Kiani, Maryam Kiani

Abstract:

In today's digital age, the field of electronics engineering is experiencing unprecedented growth and innovation. To keep pace with this rapidly evolving industry, effective sales and marketing strategies are crucial, especially when combined with the power of e-commerce. This study explores the significance of integrating sales and marketing techniques with e-commerce platforms in the context of electronics engineering. It highlights the benefits, challenges, and best practices in leveraging e-commerce for sales and marketing in this industry. By embracing e-commerce, electronics engineering companies can reach a wider customer base, enhance brand visibility, and personalize customer experiences. Furthermore, this abstract delves into the importance of utilizing digital marketing tools such as search engine optimization (SEO), social media marketing, and content creation to optimize online sales. Therefore, this research aims to provide insights and recommendations for electronics engineering professionals to effectively navigate the dynamic landscape of sales and marketing in conjunction with e-commerce.

Keywords: electronics engineering, marketing, sales, E-commerce

Procedia PDF Downloads 71
5190 Urban Growth Prediction Using Artificial Neural Networks in Athens, Greece

Authors: Dimitrios Triantakonstantis, Demetris Stathakis

Abstract:

Urban areas have been expanded throughout the globe. Monitoring and modeling urban growth have become a necessity for a sustainable urban planning and decision making. Urban prediction models are important tools for analyzing the causes and consequences of urban land use dynamics. The objective of this research paper is to analyze and model the urban change, which has been occurred from 1990 to 2000 using CORINE land cover maps. The model was developed using drivers of urban changes (such as road distance, slope, etc.) under an Artificial Neural Network modeling approach. Validation was achieved using a prediction map for 2006 which was compared with a real map of Urban Atlas of 2006. The accuracy produced a Kappa index of agreement of 0,639 and a value of Cramer's V of 0,648. These encouraging results indicate the importance of the developed urban growth prediction model which using a set of available common biophysical drivers could serve as a management tool for the assessment of urban change.

Keywords: artificial neural networks, CORINE, urban atlas, urban growth prediction

Procedia PDF Downloads 522
5189 Impact of Network Workload between Virtualization Solutions on a Testbed Environment for Cybersecurity Learning

Authors: Kevin Fernagut, Olivier Flauzac, Erick M. G. Robledo, Florent Nolot

Abstract:

The adoption of modern lightweight virtualization often comes with new threats and network vulnerabilities. This paper seeks to assess this with a different approach studying the behavior of a testbed built with tools such as Kernel-Based Virtual Machine (KVM), Linux Containers (LXC) and Docker, by performing stress tests within a platform where students experiment simultaneously with cyber-attacks, and thus observe the impact on the campus network and also find the best solution for cyber-security learning. Interesting outcomes can be found in the literature comparing these technologies. It is, however, difficult to find results of the effects on the global network where experiments are carried out. Our work shows that other physical hosts and the faculty network were impacted while performing these trials. The problems found are discussed, as well as security solutions and the adoption of new network policies.

Keywords: containerization, containers, cybersecurity, cyberattacks, isolation, performance, virtualization, virtual machines

Procedia PDF Downloads 141
5188 A Survey of Digital Health Companies: Opportunities and Business Model Challenges

Authors: Iris Xiaohong Quan

Abstract:

The global digital health market reached 175 billion U.S. dollars in 2019, and is expected to grow at about 25% CAGR to over 650 billion USD by 2025. Different terms such as digital health, e-health, mHealth, telehealth have been used in the field, which can sometimes cause confusion. The term digital health was originally introduced to refer specifically to the use of interactive media, tools, platforms, applications, and solutions that are connected to the Internet to address health concerns of providers as well as consumers. While mHealth emphasizes the use of mobile phones in healthcare, telehealth means using technology to remotely deliver clinical health services to patients. According to FDA, “the broad scope of digital health includes categories such as mobile health (mHealth), health information technology (IT), wearable devices, telehealth and telemedicine, and personalized medicine.” Some researchers believe that digital health is nothing else but the cultural transformation healthcare has been going through in the 21st century because of digital health technologies that provide data to both patients and medical professionals. As digital health is burgeoning, but research in the area is still inadequate, our paper aims to clear the definition confusion and provide an overall picture of digital health companies. We further investigate how business models are designed and differentiated in the emerging digital health sector. Both quantitative and qualitative methods are adopted in the research. For the quantitative analysis, our research data came from two databases Crunchbase and CBInsights, which are well-recognized information sources for researchers, entrepreneurs, managers, and investors. We searched a few keywords in the Crunchbase database based on companies’ self-description: digital health, e-health, and telehealth. A search of “digital health” returned 941 unique results, “e-health” returned 167 companies, while “telehealth” 427. We also searched the CBInsights database for similar information. After merging and removing duplicate ones and cleaning up the database, we came up with a list of 1464 companies as digital health companies. A qualitative method will be used to complement the quantitative analysis. We will do an in-depth case analysis of three successful unicorn digital health companies to understand how business models evolve and discuss the challenges faced in this sector. Our research returned some interesting findings. For instance, we found that 86% of the digital health startups were founded in the recent decade since 2010. 75% of the digital health companies have less than 50 employees, and almost 50% with less than 10 employees. This shows that digital health companies are relatively young and small in scale. On the business model analysis, while traditional healthcare businesses emphasize the so-called “3P”—patient, physicians, and payer, digital health companies extend to “5p” by adding patents, which is the result of technology requirements (such as the development of artificial intelligence models), and platform, which is an effective value creation approach to bring the stakeholders together. Our case analysis will detail the 5p framework and contribute to the extant knowledge on business models in the healthcare industry.

Keywords: digital health, business models, entrepreneurship opportunities, healthcare

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5187 Τhe Importance of Previous Examination Results, in Futural Differential Diagnostic Procedures and Especially in the Era of Covid-19

Authors: Angelis P. Barlampas

Abstract:

Purpose or Learning Objective It is well known that previous examinations play a major role in futural diagnosis, thus avoiding unnecessary new exams that cost in time and money both for the patient and the health system. A case is presented in which past patient’s results, in combination with the least needed new tests, give an easy final diagnosis. Methods or Background A middle aged man visited the emergency department complaining of hard controlled, persisting fever for the last few days. Laboratory tests showed an elevated number of white blood cells with neutrophil shift and abnormal CRP. The patient was admitted to hospital a month ago for continuing lungs symptomatology after a recent covid-19 infection. Results or Findings Computed tomography scanning showed a solid mass with spiculating margins in right lower lobe. After intravenous iodine contrast administration, there was mildly peripheral enhancement and eccentric non enhancing area. A pneumonic cancer was suspected. Comparison with the patient’s latest computed tomography revealed no mass in the area of interest but only signs of recent post covid-19 lung parenchyma abnormalities. Any new mass that appears in a month’s time span can not be a cancer but a benign lesion. It was obvious that an abscess was the most suitable explanation. The patient was admitted to hospital, and antibiotic therapy was given, with very good results. After a few days, the patient was afebrile and in good condition. Conclusion In this case , a PET scan or a biopsy was avoided, thanks to the patient’s medical history and the availability of previous examinations. It is worthy encouraging the patients to keep their medical records and organizing more efficiently the health system with the current technology of archiving the medical examinations, too.

Keywords: covid-19, chest ct, cancer, abscess, fever

Procedia PDF Downloads 54
5186 Inhibitions in Implementing Green Supply Chain Management at Hospitals

Authors: M. Aruna, Uma Gunasilan

Abstract:

Hospitals play an ample role in securing the health of a country. Nevertheless, they also have an unhealthy side. Ecological issues strengthen ill-health throughout the domain which subsequently puts pressure on hospital supply chains. Medical waste indeed is hazardous for environment and subsequently for human. The hospital waste management is of immense prominence due to its infectious and hazardous nature that can source many effects on human health and the environment. Government regulations and public cognizance regarding hospital waste issues have imposed hospital units to admit these strategies. The innovative technologies and instruments have been developed to handle hospital wastes. Green supply chain management practices are common in the United States. In India, Green Supply Chain management (GSCM) has just started to be recognized and practiced. GSCM are green, integrated and ecologically optimized. In Green supply chain management environmental sustainability is found to be an important driver. Eleven barriers are identified in this work. Interpretive Structural Modeling (ISM) technique is used for ranking the obstructions.

Keywords: green supply chain management (GSCM), hospital waste management (HWM), interpretive structural modeling (ISM), medical waste (MW)

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5185 Human Capital Mobility of a Skilled Workforce: A Need for a Future of Europe

Authors: Tiron-Tudor Adriana, Farcas Teodora Viorica, Ciolomic Ioana Andreea

Abstract:

The issue of human capital mobility inside Europe is still an open one. Even though there were created some tools in order to better move from one country to another to work and study the number of the people doing this is very low because of various factors presented in this paper. The "rethinking educational" agenda of the European Commission has open the floor for new projects which can create steps towards a European language for skills and competences, qualifications. One of these projects is the Partnership for Exchange of experience in Student on-the-job Training. As part of this project, we are interested to see the situation of the human capital inside EU and the elements that were created until now to support this mobility. Also, the main objective of the project is to make a comparison between the four countries involved in PEST project (Romania, Hungary, Finland, and Estonia), at the education and internship level. The results are helpful for the follow of the project, for identifying where changes can be done and need to be done.

Keywords: ECVET, human capital mobility, partnership exchange, students on the job mobility, vocational education and training

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5184 A Global Perspective on Urban Environmental Problems in Developing Countries: The Case of Turkey

Authors: Nükhet Konuk, N. Gamze Turan, Yüksel Ardalı

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Cities play a vital role in the social fabric of countries and in national and regional economic growth worldwide; however, the environmental effects of such growth need to be assessed and managed better. The critical and most immediate problems faced by cities of developing countries are the health impacts of urban pollution that derive from inadequate water, sanitation, drainage and solid waste services, poor urban and industrial waste management, and air pollution. As globalization continues, earth's natural processes transform local problems into international issues. The aim of this study is to provide a broad overview of the pollution from urban wastes and emissions in Turkey which is a developing country. It is aimed to underline the significance of reorganizing the institutional tools in a worldwide perspective in order to generate coherent solutions to urban problems, and to enhance urban quality.

Keywords: environmental pollution, developing countries, environmental degradation, urban environmental problems

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5183 Experimental Chip/Tool Temperature FEM Model Calibration by Infrared Thermography: A Case Study

Authors: Riccardo Angiuli, Michele Giannuzzi, Rodolfo Franchi, Gabriele Papadia

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Temperature knowledge in machining is fundamental to improve the numerical and FEM models used for the study of some critical process aspects, such as the behavior of the worked material and tool. The extreme conditions in which they operate make it impossible to use traditional measuring instruments; infrared thermography can be used as a valid measuring instrument for temperature measurement during metal cutting. In the study, a large experimental program on superduplex steel (ASTM A995 gr. 5A) cutting was carried out, the relevant cutting temperatures were measured by infrared thermography when certain cutting parameters changed, from traditional values to extreme ones. The values identified were used to calibrate a FEM model for the prediction of residual life of the tools. During the study, the problems related to the detection of cutting temperatures by infrared thermography were analyzed, and a dedicated procedure was developed that could be used during similar processing.

Keywords: machining, infrared thermography, FEM, temperature measurement

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5182 Proof of Concept of Video Laryngoscopy Intubation: Potential Utility in the Pre-Hospital Environment by Emergency Medical Technicians

Authors: A. Al Hajeri, M. E. Minton, B. Haskins, F. H. Cummins

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The pre-hospital endotracheal intubation is fraught with difficulties; one solution offered has been video laryngoscopy (VL) which permits better visualization of the glottis than the standard method of direct laryngoscopy (DL). This method has resulted in a higher first attempt success rate and fewer failed intubations. However, VL has mainly been evaluated by experienced providers (experienced anesthetists), and as such the utility of this device for those whom infrequently intubate has not been thoroughly assessed. We sought to evaluate this equipment to determine whether in the hands of novice providers this equipment could prove an effective airway management adjunct. DL and two VL methods (C-Mac with distal screen/C-Mac with attached screen) were evaluated by simulating practice on a Laerdal airway management trainer manikin. Twenty Emergency Medical Technicians (basics) were recruited as novice practitioners. This group was used to eliminate bias, as these clinicians had no pre-hospital experience of intubation (although they did have basic airway skills). The following areas were assessed: Time taken to intubate, number of attempts required to successfully intubate, ease of use of equipment VL (attached screen) took on average longer for novice clinicians to successfully intubate and had a lower success rate and reported higher rating of difficulty compared to DL. However, VL (with distal screen) and DL were comparable on intubation times, success rate, gastric inflation rate and rating of difficulty by the user. This study highlights the routine use of VL by inexperienced clinicians would be of no added benefit over DL. Further studies are required to determine whether Emergency Medical Technicians (Paramedics) would benefit from this airway adjunct, and ascertain whether after initial mastery of VL (with a distal screen), lower intubation times and difficulty rating may be achievable.

Keywords: direct laryngoscopy, endotracheal intubation, pre-hospital, video laryngoscopy

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5181 Effect of Post Hardening on PVD Coated Tools

Authors: Manjinder Bajwa, Mahipal Singh, Ashish Tulli

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In the research, the effect of varying cutting parameters, design parameters and heat treatment processes were studied on the cutting performance (Tool life) of a PVD coated tool. Thus, in a quest for these phenomenon comparison, a single coated tool and a multicoated tool were analyzed after suitable heat treatment process. TNMG shaped insert with single coating of TiCN and multi-coating of TiAlN/TiN were developed on tungsten carbide substrate. These coated inserts were then successfully annealed and normalized for a temperature of 350°C for 30 minutes and their cutting performance was evaluated as per the flank wear obtained after turning of mild steel. The results showed that heat treatment had a suitable impact on the tool life of the coated insert and also led to increase in the micro-hardness of the tool coatings and decrease in the wear rate.

Keywords: PVD coatings, flank wear, micro-hardness, annealing, normalizing

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5180 Modern Machine Learning Conniptions for Automatic Speech Recognition

Authors: S. Jagadeesh Kumar

Abstract:

This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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5179 Seismic Retrofit of Rectangular Columns Using Fiber Reinforced Polymers

Authors: E. L. Elghazy, A. M. Sanad, M. G. Ghoneim

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Over the past two decades research has shown that fiber reinforced polymers can be efficiently, economically and safely used for strengthening and rehabilitation of reinforced concrete (RC) structures. Designing FRP confined concrete columns requires reliable analytical tools that predict the level of performance and ductility enhancement. A numerical procedure is developed aiming at determining the type and thickness of FRP jacket needed to achieve a certain level of ductility enhancement. The procedure starts with defining the stress strain curve, which is used to obtain moment curvature relationship then displacement ductility ratio of reinforced concrete cross-sections subjected to bending moment and axial force. Three sets of published experimental tests were used to validate the numerical procedure. Comparisons between predicted results obtained by using the proposed procedure and actual results of experimental tests proved the reliability of the proposed procedure.

Keywords: columns, confinement, ductility, FRP, numerical

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5178 Breast Cancer Prediction Using Score-Level Fusion of Machine Learning and Deep Learning Models

Authors: Sam Khozama, Ali M. Mayya

Abstract:

Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

Procedia PDF Downloads 153
5177 A Generic Metamodel for Dependability Analysis

Authors: Moomen Chaari, Wolfgang Ecker, Thomas Kruse, Bogdan-Andrei Tabacaru

Abstract:

In our daily life, we frequently interact with complex systems which facilitate our mobility, enhance our access to information, and sometimes help us recover from illnesses or diseases. The reliance on these systems is motivated by the established evaluation and assessment procedures which are performed during the different phases of the design and manufacturing flow. Such procedures are aimed to qualify the system’s delivered services with respect to their availability, reliability, safety, and other properties generally referred to as dependability attributes. In this paper, we propose a metamodel based generic characterization of dependability concepts and describe an automation methodology to customize this characterization to different standards and contexts. When integrated in concrete design and verification environments, the proposed methodology promotes the reuse of already available dependability assessment tools and reduces the costs and the efforts required to create consistent and efficient artefacts for fault injection or error simulation.

Keywords: dependability analysis, model-driven development, metamodeling, code generation

Procedia PDF Downloads 484
5176 PRISM: An Analytical Tool for Forest Plan Development

Authors: Dung Nguyen, Yu Wei, Eric Henderson

Abstract:

Analytical tools have been used for decades to assist in the development of forest plans. In 2016, a new decision support system, PRISM, was jointly developed by United States Forest Service (USFS) Northern Region and Colorado State University to support the forest planning process. Prism has a friendly user interface with functionality for database management, model development, data visualization, and sensitivity analysis. The software is tailored for USFS planning, but it is flexible enough to support planning efforts by other forestland owners and managers. Here, the core capability of PRISM and its applications in developing plans for several United States national forests are presented. The strengths of PRISM are also discussed to show its potential of being a preferable tool for managers and experts in the domain of forest management and planning.

Keywords: decision support, forest management, forest plan, graphical user interface, software

Procedia PDF Downloads 106
5175 Glucose Monitoring System Using Machine Learning Algorithms

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

Abstract:

The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

Procedia PDF Downloads 193
5174 Student and Group Activity Level Assessment in the ELARS Recommender System

Authors: Martina Holenko Dlab, Natasa Hoic-Bozic

Abstract:

This paper presents an original approach to student and group activity level assessment that relies on certainty factors theory. Activity level is used to represent quantity and continuity of student’s contributions in individual and collaborative e‑learning activities (e‑tivities) and is calculated to assist teachers in assessing quantitative aspects of student's achievements. Calculated activity levels are also used to raise awareness and provide recommendations during the learning process. The proposed approach was implemented within the educational recommender system ELARS and validated using data obtained from e‑tivity realized during a blended learning course. The results showed that the proposed approach can be used to estimate activity level in the context of e-tivities realized using Web 2.0 tools as well as to facilitate the assessment of quantitative aspect of students’ participation in e‑tivities.

Keywords: assessment, ELARS, e-learning, recommender systems, student model

Procedia PDF Downloads 257