Search results for: patent analytics

Authors: Hyun-Woo Cho

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Automatic process monitoring schemes are designed to give early warnings for unusual process events or abnormalities as soon as possible. For this end, various techniques have been developed and utilized in various industrial processes. It includes multivariate statistical methods, representation skills in reduced spaces, kernel-based nonlinear techniques, etc. This work presents a nonlinear empirical monitoring scheme for batch type production processes with incomplete process measurement data. While normal operation data are easy to get, unusual fault data occurs infrequently and thus are difficult to collect. In this work, noise filtering steps are added in order to enhance monitoring performance by eliminating irrelevant information of the data. The performance of the monitoring scheme was demonstrated using batch process data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: batch process, monitoring, measurement, kernel method

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Authors: Shahin Mirshekari, Mohammadreza Moradi, Hossein Jafari, Mehdi Jafari, Mohammad Ensaf

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This research employs Gaussian Process Regression (GPR) with an ensemble kernel, integrating Exponential Squared, Revised Matern, and Rational Quadratic kernels to analyze pharmaceutical sales data. Bayesian optimization was used to identify optimal kernel weights: 0.76 for Exponential Squared, 0.21 for Revised Matern, and 0.13 for Rational Quadratic. The ensemble kernel demonstrated superior performance in predictive accuracy, achieving an R² score near 1.0, and significantly lower values in MSE, MAE, and RMSE. These findings highlight the efficacy of ensemble kernels in GPR for predictive analytics in complex pharmaceutical sales datasets.

Keywords: Gaussian process regression, ensemble kernels, bayesian optimization, pharmaceutical sales analysis, time series forecasting, data analysis

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Authors: W. G. Kim, J. M. Chang, W. S. Kim

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Immunologically non-treated and acellularized porcine xenografts were implanted as an arterial graft in goats and comparatively analyzed for the explanted grafts with gross observation, as well as light microscopy and immunohistochemistry, following the predetermined periods. For immunologically non-treated xenografts, bilateral porcine carotid arteries were harvested, and after short-term freezing at -70°C, were implanted into goats. The preparation of acellularized xenograft vessels has been performed with Nacl-SDS solution and stored at the freezer until use. The goats were randomly assigned for three periods of observation (3, 6, and 12 months after implantation), four animals were observed at each of these times. Periodic ultrasonographic examinations were performed during observation period. Following the predetermined periods, the explanted grafts were analyzed. Among 12 animals, one goat died prematurely, and a total of 22 grafts were evaluated. Gross observations revealed non-thrombotic patent smooth lumens. Microscopic examinations of the explanted grafts showed satisfactory cellular reconstruction up to the 12-month observation period. The proportions of CD3 positive T lymphocytes among inflammatory cells infiltrations were very low. In conclusion, these findings, as a whole, suggest that porcine vessel xenografts can be clinically acceptably implanted in the goats as a form of small-diameter vascular graft, regardless of the acellularized xenograft or immunologically non-treated xenograft.

Keywords: xenograft, arterial graft, long-term survival animals, immunology

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Authors: Anna Fredriksson Häägg, Charlotte Weil, Niklas Rönnberg

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Map-based dashboards are used for data exploration every day. The present study used an insight-based methodology for evaluating a map-based dashboard that presents research findings of water management and ecosystem services in the Amazon. In addition to analyzing the insights gained from using the dashboard, the evaluation method was compared to standardized questionnaires and task-based evaluations. The result suggests that the dashboard enabled the participants to gain domain-relevant, complex insights regarding the topic presented. Furthermore, the insight-based analysis highlighted unexpected insights and hypotheses regarding causes and potential adaptation strategies for remediation. Although time- and resource-consuming, the insight-based methodology was shown to have the potential of thoroughly analyzing how end users can utilize map-based dashboards for data exploration and decision making. Finally, the insight-based methodology is argued to evaluate tools in scenarios more similar to real-life usage compared to task-based evaluation methods.

Keywords: visual analytics, dashboard, insight-based evaluation, geographic visualization

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Authors: Aitor Barbero-López, Soumaya Chibily, Gerhard Scheepers, Thomas Grahn, Martti Venäläinen, Antti Haapala

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Wood decay is addressed continuously within the wood industry through use and development of wood preservatives. The increasing awareness on the negative effects of many chemicals towards the environment is causing political restrictions in their use and creating more urgent need for research on green alternatives. This paper discusses some of the possible natural extracts for wood preserving applications and compares the analytical methods available for testing their behavior and efficiency against decay fungi. The results indicate that natural extracts have interesting chemical constituents that delay fungal growth but vary in efficiency depending on the chemical concentration and substrate used. Results also suggest that presence and redistribution of preservatives in wood during exposure trials can be assessed by spectral imaging methods although standardized methods are not available. This study concludes that, in addition to the many standard methods available, there is a need to develop new faster methods for screening potential preservative formulation while maintaining the comparability and relevance of results.

Keywords: analytics, methods, preservatives, wood decay

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Authors: Taweechai Nuntawisuttiwong, Natasha Dejdumrong

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Geometric modeling plays an important role in the constructions and manufacturing of curve, surface and solid modeling. Their algorithms are critically important not only in the automobile, ship and aircraft manufacturing business, but are also absolutely necessary in a wide variety of modern applications, e.g., robotics, optimization, computer vision, data analytics and visualization. The calculation and display of geometric objects can be accomplished by these six techniques: Polynomial basis, Recursive, Iterative, Coefficient matrix, Polar form approach and Pyramidal algorithms. In this research, the coefficient matrix (simply called monomial form approach) will be used to model polynomial rectangular patches, i.e., Said-Ball, Wang-Ball, DP, Dejdumrong and NB1 surfaces. Some examples of the monomial forms for these surface modeling are illustrated in many aspects, e.g., construction, derivatives, model transformation, degree elevation and degress reduction.

Keywords: monomial forms, rectangular surfaces, CAGD curves, monomial matrix applications

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Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

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Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: support vector mechanism (SVM), machine learning (ML), support vector machines (SVM), department of transportation (DFT)

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Authors: The Danh Phan

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House price forecasting is a main topic in the real estate market research. Effective house price prediction models could not only allow home buyers and real estate agents to make better data-driven decisions but may also be beneficial for the property policymaking process. This study investigates the housing market by using machine learning techniques to analyze real historical house sale transactions in Australia. It seeks useful models which could be deployed as an application for house buyers and sellers. Data analytics show a high discrepancy between the house price in the most expensive suburbs and the most affordable suburbs in the city of Melbourne. In addition, experiments demonstrate that the combination of Stepwise and Support Vector Machine (SVM), based on the Mean Squared Error (MSE) measurement, consistently outperforms other models in terms of prediction accuracy.

Keywords: house price prediction, regression trees, neural network, support vector machine, stepwise

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Authors: Ashiff Khan, A. Seetharaman, Abhijit Dasgupta

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The new era of big data (BD) is influencing chemical industries tremendously, providing several opportunities to reshape the way they operate and help them shift towards intelligent manufacturing. Given the availability of free software and the large amount of real-time data generated and stored in process plants, chemical industries are still in the early stages of big data adoption. The industry is just starting to realize the importance of the large amount of data it owns to make the right decisions and support its strategies. This article explores the importance of professional competencies and data science that influence BD in chemical industries to help it move towards intelligent manufacturing fast and reliable. This article utilizes a literature review and identifies potential applications in the chemical industry to move from conventional methods to a data-driven approach. The scope of this document is limited to the adoption of BD in chemical industries and the variables identified in this article. To achieve this objective, government, academia, and industry must work together to overcome all present and future challenges.

Keywords: chemical engineering, big data analytics, industrial revolution, professional competence, data science

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Authors: Jalil Qoulizadeh, Hasan Sadeghi

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Brain waves are electrical wave patterns that are produced in the human brain. Knowing these waves and activating them can have a positive effect on brain function and ultimately create an ideal life. The brain has the ability to produce waves from 0.1 to above 65 Hz. (The Beta One device produces exactly these waves) This is because it is said that the waves produced by the Beta One device exactly match the waves produced by the brain. The function and method of this device is based on the magnetic stimulation of the brain. The technology used in the design and producƟon of this device works in a way to strengthen and improve the frequencies of brain waves with a pre-defined algorithm according to the type of requested function, so that the person can access the expected functions in life activities. to perform better. The effect of this field on neurons and their stimulation: In order to evaluate the effect of this field created by the device, on the neurons, the main tests are by conducting electroencephalography before and after stimulation and comparing these two baselines by qEEG or quantitative electroencephalography method using paired t-test in 39 subjects. It confirms the significant effect of this field on the change of electrical activity recorded after 30 minutes of stimulation in all subjects. The Beta One device is able to induce the appropriate pattern of the expected functions in a soft and effective way to the brain in a healthy and effective way (exactly in accordance with the harmony of brain waves), the process of brain activities first to a normal state and then to a powerful one. Production of inexpensive neuroscience equipment (compared to existing rTMS equipment) Magnetic brain stimulation for clinics - homes - factories and companies - professional sports clubs.

Keywords: stimulation, brain, waves, betaOne

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Authors: Bashar Tarawneh, Yasser Hakam

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Rapid Impact Compaction (RIC) is a modern dynamic compaction device mainly used to compact sandy soils, where silt and clay contents are low. The device uses the piling hammer technology to increase the bearing capacity of soils through controlled impacts. The RIC device uses "controlled impact compaction" of the ground using a 9-ton hammer dropped from the height between 0.3 m to 1.2 m onto a 1.5 m diameter steel patent foot. The delivered energy is about 26,487 to 105,948 Joules per drop. To evaluate the performance of this technique, three project sites in the United Arab Emirates were improved using RIC. In those sites, a loose to very loose fine to medium sand was encountered at a depth ranging from 1.0m to 4.0m below the ground level. To evaluate the performance of the RIC, Cone Penetration Tests (CPT) were carried out before and after improvement. Also, load tests were carried out post-RIC work to assess the settlements and bearing capacity. The soil was improved to a depth of about 5.0m below the ground level depending on the CPT friction ratio (the ratio between sleeve friction and tip resistance). CPT tip resistance was significantly increased post ground improvement work. Load tests showed enhancement in the soil bearing capacity and reduction in the potential settlements. This study demonstrates the successful application of the RIC for middle-deep improvement and compaction of the ground. Foundation design criteria were achieved in all site post-RIC work.

Keywords: compaction, RIC, ground improvement, CPT

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Authors: Oualid Walid Ben Ali

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Big Data has become one of the buzzwords today. The recent explosion of digital data has led the organization, either private or public, to a new era towards a more efficient decision making. At some point, business decided to use that concept in order to learn what make their clients tick with phrases like ‘sales funnel’ analysis, ‘actionable insights’, and ‘positive business impact’. So, it stands to reason that Big Data was viewed through green (read: money) colored lenses. Somewhere along the line, however someone realized that collecting and processing data doesn’t have to be for business purpose only, but also could be used for other purposes to assist law enforcement or to improve policing or in road safety. This paper presents briefly, how Big Data have been used in the fields of policing order to improve the decision making process in the daily operation of the police. As example, we present a big-data driven system which is sued to accurately dispatch the patrol cars in a geographic environment. The system is also used to allocate, in real-time, the nearest patrol car to the location of an incident. This system has been implemented and applied in the Emirate of Abu Dhabi in the UAE.

Keywords: big data, big data analytics, patrol car allocation, dispatching, GIS, intelligent, Abu Dhabi, police, UAE

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Authors: Ahlem Abid, Farah Jemili

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Intrusion detection has been the subject of numerous studies in industry and academia, but cyber security analysts always want greater precision and global threat analysis to secure their systems in cyberspace. To improve intrusion detection system, the visualisation of the security events in form of graphs and diagrams is important to improve the accuracy of alerts. In this paper, we propose an approach of an IDS based on cloud computing, big data technique and using a machine learning graph algorithm which can detect in real time different attacks as early as possible. We use the MAWILab intrusion detection dataset . We choose Microsoft Azure as a unified cloud environment to load our dataset on. We implement the k2 algorithm which is a graphical machine learning algorithm to classify attacks. Our system showed a good performance due to the graphical machine learning algorithm and spark structured streaming engine.

Keywords: Apache Spark Streaming, Graph, Intrusion detection, k2 algorithm, Machine Learning, MAWILab, Microsoft Azure Cloud

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Authors: João Pedro Albino, Ana Cláudia Pires Ferreira de Lima

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Humanity has undergone a transformation from the physical to the virtual world, generating an enormous amount of data on the world wide web, known as big data. Many facts that occur in the physical world or in the digital world are proven through records made on the internet, such as digital photographs, posts on social media, contract acceptances by digital platforms, email, banking, and messaging applications, among others. These data recorded on the internet have been used as evidence in judicial proceedings. The identification of internet users is essential for the security of legal relationships. This research was carried out on scientific articles and materials from courses and lectures, with an analysis of Brazilian legislation and some judicial decisions on the request of static data from logs and Internet Protocols (IPs) from application and connection providers. In this article, we will address the determination of authorship of data processing on the internet by obtaining the IP address and the appropriate judicial procedure for this purpose under Brazilian law.

Keywords: IP address, digital forensics, big data, data analytics, information and communication technology

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Authors: Gehan Hussein, Hams Ahmad, Baher Matta, Yasmeen Mansi, Mohamad Fawzi

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Background: Congenital heart disease (CHD) is a common problem worldwide with variable incidence in different countries. The exact etiology is unknown, suggested to be multifactorial. We aimed to study the incidence of various CHD in a neonatal intensive care unit (NICU) in a tertiary care hospital in Egypt and the possible associations with variable risk factors. Methods: Prospective study was conducted over a period of one year (2013 /2014) at NICU KasrAlAini School of Medicine, Cairo University. Questionnaire about possible maternal and/or paternal risk factors for CHD, clinical examination, bedside echocardiography were done. Cases were classified into groups: group 1 without CHD and group 2 with CHD. Results: from 723 neonates admitted to NICU, 180 cases were proved to have CHD, 58 % of them were males. patent ductus arteriosus(PDA) was the most common CHD (70%), followed by an atrial septal defect (ASD8%), while Fallot tetralogy and single ventricle were the least common (0.45 %) for each. CHD was found in 30 % of consanguineous parents Maternal age ≥ 35 years at the time of conception was associated with increased incidence of PDA (p= 0.45 %). Maternal diabetes and insulin intake were significantly associated with cases of CHD (p=0.02 &0.001 respectively), maternal hypertension and hypothyroidism were both associated with VSD, but the difference did not reach statistical significance (P=0.36 &0.44respectively). Maternal passive smoking was significantly associated with PDA (p=0.03). Conclusion: The most frequent CHD in the studied population was PDA, followed by ASD. Maternal conditions as diabetes was associated with VSD occurrence.

Keywords: NICU, risk factors, congenital heart disease, echocardiography

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Authors: Francesco Coraci, Abdul-Hadi G. Abulrub

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Digital technology is transforming the landscape of the industrial sector at a precedential level by connecting people, processes, and machines in real-time. It represents the means for a new pathway to achieve innovative, dynamic competitive advantages, deliver unique customers’ values, and sustain critical relationships. Thus, success in a constantly changing environment is governed by the ability of an organization to revolutionize their business models, deliver innovative solutions, and capture values from big data analytics and insights. Businesses need to re-strategize operations and develop extra capabilities to cope with the necessity for additional flexibility and agility. The traditional “command and control” leadership style is structurally and operationally incompatible with the digital era. In this paper, the authors discuss how transformational leaders can act as a glue in the social, organizational context, which is crucial to enable the workforce and develop a psychological attachment to the digital vision.

Keywords: internet of things, strategy, change leadership, dynamic competitive advantage, digital transformation

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Authors: Hoyeon Park, Yunhwan Keon, Kyoung-Jae Kim

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Location Based Social Network services (LBSNs) is a new term that combines location based service and social network service (SNS). Unlike traditional SNS, LBSNs emphasizes empirical elements in the user's actual physical location. Point-of-Interest (POI) is the most important factor to implement LBSNs recommendation system. POI information is the most popular spot in the area. In this study, we would like to recommend POI to users in a specific area through recommendation system using collaborative filtering. The process is as follows: first, we will use different data sets based on Seoul and New York to find interesting results on human behavior. Secondly, based on the location-based activity information obtained from the personalized LBSNs, we have devised a new rating that defines the user's preference for the area. Finally, we have developed an automated rating algorithm from massive raw data using distributed systems to reduce advertising costs of LBSNs.

Keywords: location-based social network services, point-of-interest, recommender systems, business analytics

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Authors: Sepinoud Hamedi

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Over the past few decades, companies have appeared developing concerns in connection to the natural affect of their fabricating exercises. Green supply chain administration has been considered by the producers as a attainable choice to decrease the natural affect of operations whereas at the same time moving forward their operational execution. Contemporaneously the coming of digitalization and globalization within the supply chain space has driven to a developing acknowledgment of the importance of data preparing methodologies, such as enormous information analytics and fake insights innovations, in improving and optimizing supply chain execution. Also, supply chain collaboration in part intervenes the relationship between manufactured innovation and supply chain execution Ponders appear that the use of BDA-AI advances includes a significant impact on natural handle integration and green supply chain collaboration conjointly underlines that both natural handle integration and green supply chain collaboration have a critical affect on natural execution. Correspondingly savvy supply chain contributes to green execution through overseeing green connections and setting up green operations.

Keywords: green supply chain, artificial intelligence, manufacturers, technology, environmental

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Authors: Paulina Solórzano Salgado, Luis Rodrigo Valencia Pérez, Alberto de Jesús Pastrana Palma

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In this research, it is presented a digital maturity framework, which contributes to the development of small and medium-sized enterprises (SMEs) in the commercial sector. This proposal is based on three important concepts: Marketing activities in the enterprise, information and communication technologies ICT, as well as Innovation. Prior to the development of this framework, was formulated a quantitative assessment tool through a literature review, and was validated with a method used by experts, and which determines the relationship of digital marketing and innovation activities in companies. The instrument was applied to 64 Mexican companies from the Made in Mexico database, which allowed both descriptive results and correlation results. These contributed to the development of the methodology, and confirming that the management of digital marketing has a positive relation with innovation activities of companies. Also, that analytics in digital marketing is a source for its development. In this paper, the management stages and activities are presented to be developed by companies in order to generate knowledge, which will allow them to reach its digital maturity.

Keywords: digital marketing, digital maturity, innovation, SMEs

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Authors: Keshavamurthy Ganapathy Bhat, Manvinderpal Singh Marwaha

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Background: Coronary artery Disease (CAD) is a common cause of morbidity, mortality and reason for unfitness amongst aircrew. Coronary angioplasty and stenting are the standard of care for CAD. Antiplatelet drugs like Aspirin and Clopidogrel(Dual Antiplatelet therapy) are routinely prescribed post-stenting which are permitted for flying. However, in the recent past, Ticagrelor is being used in place of Clopidogrel as per ACC AHA and ESC guidelines. However Ticagrelor is not permitted for flying. Case Presentation: A 55-year-old pilot suffered Anterior Wall Myocardial Infarction. Angiography showed blockages in Left Anterior Descending Artery(LAD) and Right coronary artery (RCA). He underwent primary angioplasty and stenting LAD and subsequent stenting to RCA. Recovery was uneventful. One year later he was asymptomatic with normal Left ventricular function and no reversible perfusion defect on stress MPI. He had patent stents and coronaries on check angiogram. However, he was not allowed to fly since he was on Ticagrelor. He had to be switched over to Clopidogrel from Ticagrelor one year after stenting to permit him for flying. Similarly, switching had to be done in a 45-year-old pilot. Ticagrelor has been proven to be more effective than clopidogrel and as safe as Clopidogrel in preventing stent thrombosis. If Clopidogrel is being permitted, there is no need to restrict Ticagrelor. Hence "Policy" needs to be changed. Conclusions: Dual Antiplatelet therapy is the standard of care post coronary stenting which has been proved safe and effective. Policy needs to be changed to permit flying with Ticagrelor which is more effective than Clopidogrel and equally safe.

Keywords: antiplatelet drugs, coronary artery disease, stenting, ticagrelor

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Authors: Inas S. Khayal, Weiping Zhou, Jonathan Skinner

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Healthcare delivery systems around the world are in crisis. The need to improve health outcomes while decreasing healthcare costs have led to an imminent call to action to transform the healthcare delivery system. While Bioinformatics and Biomedical Engineering have primarily focused on biological level data and biomedical technology, there is clear evidence of the importance of the delivery of care on patient outcomes. Classic singular decomposition approaches from reductionist science are not capable of explaining complex systems. Approaches and methods from systems science and systems engineering are utilized to structure healthcare delivery system data. Specifically, systems architecture is used to develop a multi-scale and multi-dimensional characterization of the healthcare delivery system, defined here as the Healthcare Delivery System Knowledge Base. This paper is the first to contribute a new method of structuring and visualizing a multi-dimensional and multi-scale healthcare delivery system using systems architecture in order to better understand healthcare delivery.

Keywords: health informatics, systems thinking, systems architecture, healthcare delivery system, data analytics

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Authors: Pedro Rubio

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Antonio Romero y Andía, was one of the most active and interesting figures in 19th century Spanish music. He was not only an exceptional clarinetist, he was also a publisher, a brilliant oboist, a music critic, and he revitalized Madrid’s musical scene by promoting orchestras and a national opera. In 1849, Romero was appointed Professor of Clarinet at the Conservatory of Madrid. Shortly after, Romero introduced to Spain the Boehm-System clarinet recently appeared in France. However, when initial interest in that system waned, he conceived his own system in 1853. The clarinet was manufactured in Paris by Lefêvre, who registered its first patent in 1862. In 1867 a second version was patented, and a year earlier, in 1866, the Romero clarinet was adopted as an official instrument for teaching the clarinet at the Conservatory of Madrid. The Romero-System clarinet mechanism has incorporated numerous additional devices and several extra keys, its skillful combination in a single instrument represents not only one of the pinnacles in the manufacture of musical instruments of the 19th century, but also an authentic synthesis of knowledge and practice in an era in which woodwind instruments were shaped as we know them today. Through the description and analysis of the data related to the aforementioned historical period, this lecture will try to show a crucial time in the history of all woodwind instruments, a period of technological effervescence in which the Romero-System clarinet emerged. The different stages of conception of the clarinet will be described, as well as its manufacturing and marketing process. Romero played with his clarinet system over twenty-five years. The research has identified the repertoire associated with this instrument whose conclusions will be presented in its case in the Congress.

Keywords: Antonio Romero, clarinet, keywork, 19th century

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Authors: Adeolu O. Dairo

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Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: geospatial, geo-analytics, self-organizing map, customer-centric

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Authors: Merey M. Sarsengeldin, Alexandr S. Kolokhmatov, Galiya Seidaliyeva, Alexandr Ozerov, Sanim T. Imatayeva

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This series of interdisciplinary studies is an attempt to investigate and develop a scalable model of fair socioeconomic relations on the base of blockchain using positive psychology techniques and Machine Learning algorithms for data analytics. In this particular study, we use hyperinteraction approach and intuition to investigate their influence on 'wisdom of crowds' via created mobile application which was created for the purpose of this research. Along with the public blockchain and private Decentralized Autonomous Organization (DAO) which were elaborated by us on the base of Ethereum blockchain, a model of fair financial relations of members of DAO was developed. We developed a smart contract, so-called, Fair Price Protocol and use it for implementation of model. The data obtained from mobile application was analyzed by ML algorithms. A model was tested on football matches.

Keywords: blockchain, Naïve Bayes algorithm, hyperinteraction, intuition, wisdom of crowd, decentralized autonomous organization

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Authors: Peijen Pamela Chuang, Tzu-Hua Wang

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To address the notion of educational equity, undergo the global pandemic, a digital learning system was cross-disciplinarily designed by a 15-year-experienced teaching practitioner. A study was performed on students through the use of this pioneering e-learning system, in which Taiwanese students with different learning styles and special needs have a foreign language- English as the target subject. 121 students are particularly selected from an N= 580 sample spread across 20 inclusive and special education schools throughout districts of Taiwan. To bring off equity, the participants are selected from a mix of different socioeconomic statuses. Grouped data, such as classroom observation, individual learning preference, prerequisite knowledge, learning interest, and learning performance of the population, is carefully documented for further analyzation. The paper focuses on documenting the awareness and needs of this pedagogical methodology revolution, data analysis of UX (User Experience), also examination and system assessment of this system. At the time of the pilot run, this newly-developed e-learning system had successfully applied for and received a national patent in Taiwan. This independent research hoped to expand the awareness of the importance of individual differences in SDG4 (Substantial Development Goals 4) as a part of the ripple effect, and serve as a comparison for future scholars in the pedagogical research with an interdisciplinary approach.

Keywords: e-learning, educational equity, foreign language acquisition, inclusive education, individual differences, interdisciplinary innovation, learning preferences, SDG4

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Authors: Maria Tsompanoglou, Dimitris Armenis

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Vessel behavior in different operational and weather conditions constitutes the main area of interest for the ship operator. Ship speed and fuel consumption are the most decisive parameters in this respect, as their correlation provides information about the economic and environmental efficiency of the vessel, becoming the basis of decision making in terms of maintenance and trading. In the analysis of vessel operational profile for the evaluation of fuel consumption and the equivalent CO2 emissions footprint, the indications of Speed Through Water are widely used. The seasonal and regional variations in seawater characteristics, which are available nowadays, can provide the basis for accurate estimation of the errors in Speed Through Water indications at any time. Accuracy in the speed value on a route basis can enable operator identify the ship fuel and propulsion efficiency and proceed with improvements. This paper discusses case studies, where the actual vessel speed was corrected by a post-processing algorithm. The effects of the vessel correction to standard Key Performance Indicators, as well as operational findings not identified earlier, are also discussed.

Keywords: data analytics, MATLAB, vessel performance monitoring, speed through water

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Authors: Mohammed Saeed Jawad

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Metaverse involves the convergence of three major technologies trends of AI, VR, and AR. Together these three technologies can provide an entirely new channel for delivering healthcare with great potential to lower costs and improve patient outcomes on a larger scale. Telepresence is the technology that allows people to be together even if they are physically apart. Medical doctors can be symbolic as interactive avatars developed to have smart conversations and medical recommendations for patients at the different stages of the treatment. Medical digital assets such as Medical IoT for real-time remote healthcare monitoring as well as the symbolic doctors’ avatars as well as the hospital and clinical physical constructions and layout can be immersed in extended realities 3D metaverse environments where doctors, nurses, and patients can interact and socialized with the related digital assets that facilitate the data analytics of the sensed and collected personal medical data with visualized interaction of the digital twin of the patient’s body as well as the medical doctors' smart conversation and consultation or even in a guided remote-surgery operation.

Keywords: personal healthcare, metaverse, telemedicine, telepresence, avatar, medical consultation, remote-surgery

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Authors: Alina Hamid Bari

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Intellectual Property (IP) policies of a country have a huge impact on the pharmaceutical industry as this industry is all about patents. Developed countries have used IP protection to boost their economy; developing countries are concerned about access to medicine for poor people. U.S. company, Pfizer had a monopoly for 14 years for Lipitor and it all came to end when Pfizer decided to operate in India. This research will focus at the effects of Indian IP policies on USA by comparing Pfizer & Ranbaxy with regards to Trade Related Aspects of Intellectual Property Rights. For this research inductive approach has been used. Main source of material is Annual reports, theory based on academic books and articles along with rulings of court, policy statements and decisions, websites and newspaper articles. SWOT analysis is done for both Pfizer & Ranbaxy. The main comparison was done by doing ratio analysis and analyses of annual reports for the year 2011-2012 for Pfizer and Ranbaxy to see the impact on their profitability. This research concludes that Indian intellectual laws do affect the profitability of the U.S. pharmaceutical industry which can in turn have an impact on the US economy. These days India is only granting patents on products which it feels are deserving of it. So the U.S. companies operating in India have to defend their invention to get a patent. Thus, to operate in India and maintain monopoly in market, US firms have to come up with different strategies.

Keywords: atorvastatin, India, intellectual property, lipitor, Pfizer, pharmaceutical industry, Ranbaxy, TRIPs, U.S.

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Authors: M. B. Ricardo De Oliveira, A. Borghi-Silva, L. Di Thommazo, D. Braatz

Abstract:

Prototypes can be understood as representations of a product concept. Furthermore, prototyping consists in an important stage in product development and results in better team communication, decision making, testing and problem solving through feedback. Although there are several methods of prototyping suggested by recent studies for designers to choose from, some methods present different advantages, such as cost and time reduction, performance and fidelity, which should be taken in account during a product development project. In this multidisciplinary study, involving areas of physiotherapy, engineering and computer science (hardware and software), we compared four developed prototypes of an ergometric step: a virtual prototype, a 3D printed prototype, a bricolage prototype and a prototype manufactured by a third-party company. These prototypes were evaluated in a comparative-qualitative approach for their contribution to the concept’s maturation of the product, the different prototyping methods used and the advantages and disadvantages of each one based on the product’s design specifications (performance, safety, materials, cost, maintenance, usability, ergonomics and portability). Our results indicated that despite prototypes show overall advantages, all of them have limitations, thus being crucial to have different methods of testing and interacting with the product. Additionally, virtual and 3D printed prototypes were essential at early stages of the project due to their low-cost and high-fidelity representation of the product, while the prototype manufactured by a third-party company and bricolage prototype introduced functional tests in real scenarios, allowing more detailed evaluations. This study also resulted in a patent for an ergometric step.

Keywords: Product Design, Product Development, Prototypes, Step

Procedia PDF Downloads 90

Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

Abstract:

The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph

Procedia PDF Downloads 149