Search results for: edge computing module

Authors: Der-Feng Guo

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Optoelectronic switches have attracted a considerable attention in the semiconductor research field due to their potential applications in optical computing systems and optoelectronic integrated circuits (OEICs). With high gains and high-speed operations, npn heterostructures can be used to produce promising optoelectronic switches. It is known that the bulk barrier and heterostructure-induced potential spike act important roles in the characteristics of the npn heterostructures. To investigate the effects of bulk barrier and potential spike heights on the optoelectronic switching of the npn heterostructures, GaAs/InGaP and AlGaAs/GaAs/InAlGaP npn heterostructural optoelectronic switches (HSOSs) have been fabricated in this work. It is seen that the illumination decreases the switching voltage Vs and increases the switching current Is, and thus the OFF state is under dark and ON state under illumination in the optical switching of the GaAs/InGaP HSOS characteristics. But in the AlGaAs/GaAs/InAlGaP HSOS characteristics, the Vs and Is present contrary trends, and the OFF state is under illumination and ON state under dark. The studied HSOSs show quite different switching variations with incident light, which are mainly attributed to the bulk barrier and potential spike heights affected by photogenerated carriers.

Keywords: bulk barrier, heterostructure, optoelectronic switch, potential spike

Procedia PDF Downloads 238

Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji

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The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.

Keywords: medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis

Procedia PDF Downloads 319

Authors: Helen Coronel, Will Brewer, Peggy Bergeron, Clarissa Hall, Victoria Casson

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Simulation-based training provides the nurse practitioner (NP) student with a safe and controlled environment in which they can practice a real-life scenario. This type of learning fosters critical thinking skills essential to practice. The expectation of this study was that students would have an increase in their competency and confidence after performing the simulation. Approximately 8.4% of Americans suffer from depression. The state of Alabama is ranked 47th out of 50 for access to mental health care. As a result of this significant shortage of mental health providers, primary care providers are frequently put in the position of screening for and treating mental health conditions, such as depression. Family nurse practitioners are often utilized as primary care providers, making their ability to assess, diagnose and treat these disorders a necessary skill. The expected outcome of this simulation is an increase in confidence, competency and the empowerment of the nurse practitioner student’s ability to assess, diagnose and treat a common mood disorder they may encounter in practice. The Kirkpatrick Module was applied for this study. A non-experimental design using descriptive statistical analysis was utilized. The simulation was based on a common psychiatric mood disorder frequently observed in primary care and mental health clinics. Students were asked to watch a voiceover power point presentation prior to their on-campus simulation. The presentation included training on the assessment, diagnosis, and treatment of a patient with depression. Prior to the simulation, the students completed a pre-test, then participated in the simulation, and completed a post-test when done. Apple iPads were utilized to access a simulated health record. Major findings of the study support an increase in students’ competency and confidence when assessing, diagnosing, and treating an adult patient with depression.

Keywords: advanced practice, nurse practitioner, simulation, primary care, depression

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Authors: Billy Moore, Izaiah Smith, Dominic Mckinney, Andrew Cisco, Mehdi Kabir

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Phase-change materials (PCMs) are considered one of the most promising substances to be engaged passively in thermal management and storage systems for spacecraft, where it is critical to diminish the overall mass of the onboard thermal storage system while minimizing temperature fluctuations upon drastic changes in the environmental temperature within the orbit stage. This makes the development of effective thermal management systems more challenging since there is no atmosphere in outer space to take advantage of natural and forced convective heat transfer. PCM can store or release a tremendous amount of thermal energy within a small volume in the form of latent heat of fusion in the phase-change processes of melting and solidification from solid to liquid or, conversely, during which temperature remains almost constant. However, the existing PCMs pose very low thermal conductivity, leading to an undesirable increase in total thermal resistance and, consequently, a slow thermal response time. This often turns into a system bottleneck from the thermal performance perspective. To address the above-mentioned drawback, the present study aims to design and develop various heat sinks featured by nano-structured graphitic foams (i.e., carbon foam), expanded graphite (EG), and open-cell copper foam (OCCF) infiltrated with a conventional paraffin wax PCM with a melting temperature of around 35 °C. This study focuses on the use of passive thermal management techniques to develop efficient heat sinks to maintain the electronics circuits’ and battery module’s temperature within the thermal safety limit for small spacecraft and satellites such as the Pumpkin and OPTIMUS battery modules designed for CubeSats with a cross-sectional area of approximately 4˝×4˝. Thermal response times for various heat sinks are assessed in a vacuum chamber to simulate space conditions.

Keywords: heat sink, porous foams, phase-change material (PCM), spacecraft thermal management

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Authors: Phuoc Si Nguyen

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Infinite impulse response (IIR) filters can be designed from an analogue low pass prototype by using frequency transformation in the s-domain and bilinear z-transformation with pre-warping frequency; this method is known as frequency transformation from the s-domain to the z-domain. This paper will introduce a new method to transform an IIR digital filter to another type of IIR digital filter (low pass, high pass, band pass, band stop or narrow band) using a technique based on inverse bilinear z-transformation and inverse matrices. First, a matrix equation is derived from inverse bilinear z-transformation and Pascal’s triangle. This Low Pass Digital to Digital Filter Pascal Matrix Equation is used to transform a low pass digital filter to other digital filter types. From this equation and the inverse matrix, a Digital to Digital Filter Pascal Matrix Equation can be derived that is able to transform any IIR digital filter. This paper will also introduce some specific matrices to replace the inverse matrix, which is difficult to determine due to the larger size of the matrix in the current method. This will make computing and hand calculation easier when transforming from one IIR digital filter to another in the digital domain.

Keywords: bilinear z-transformation, frequency transformation, inverse bilinear z-transformation, IIR digital filters

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Authors: Sonja Gögele, Petra Kletzenbauer

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International strategies are ranked as one of the core activities in the development plans of Austrian universities. This has led to numerous promising activities in terms of internationalization (i.e. development of international degree programmes, increased staff, and student mobility, and blended international projects). The latest innovative approach are so called Blended Intensive Programmes (BIP), which combine jointly delivered teaching and learning elements of at least three participating ERASMUS universities in a virtual and short-term mobility setup. Students who participate in BIP can maintain their study plans at their home institution and include BIP as a parallel activity. This paper presents the experiences of this programme on the topic of sustainable computing hosted by the University of Applied Sciences FH JOANNEUM. By means of an online survey and face-to-face interviews with all stakeholders (20 students, 8 professors), the empirical study addresses the challenges of hosting an international blended learning programme (i.e. virtual phase and on-site intensive phase) and discusses the impact of such activities in terms of innovative pedagogy (i.e. virtual collaboration, research-based learning).

Keywords: internationalization, collaborative learning, blended intensive programme, pedagogy

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Authors: Concepcion Gonzalez-Concepcion, Maria Candelaria Gil-Fariña, Celina Pestano-Gabino

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We analyze six relevant economic and financial variables for the period 2000M1-2015M3 in the context of the Spanish economy: a financial index (IBEX35), a commodity (Crude Oil Price in euros), a foreign exchange index (EUR/USD), a bond (Spanish 10-Year Bond), the Spanish National Debt and the Consumer Price Index. The goal of this paper is to analyze the main relations between them by computing the Wavelet Power Spectrum and the Cross Wavelet Coherency associated with Morlet wavelets. By using a special toolbox in MATLAB, we focus our interest on the period variable. We decompose the time-frequency effects and improve the interpretation of the results by non-expert users in the theory of wavelets. The empirical evidence shows certain instability periods and reveals various changes and breaks in the causality relationships for sample data. These variables were individually analyzed with Daubechies Wavelets to visualize high-frequency variance, seasonality, and trend. The results are included in Proceeding 20th International Academic Conference, 2015, International Institute of Social and Economic Sciences (IISES), Madrid.

Keywords: economic and financial variables, Spain, time-frequency domain, wavelet coherency

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Authors: Abdulrahman S. Alqahtani

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The revolution of computing and networks could revolutionise terrorism in the same way that it has brought about changes in other aspects of life. The modern technological era has faced countries with a new set of security challenges. There are many states and potential adversaries who have the potential and capacity in cyberspace, which makes them able to carry out cyber-attacks in the future. Some of them are currently conducting surveillance, gathering and analysis of technical information, and mapping of networks and nodes and infrastructure of opponents, which may be exploited in future conflicts. This poster presents the results of the quantitative study (survey) to test the validity of the proposed theoretical framework for the cyber terrorist threats. This theoretical framework will help to in-depth understand these new digital terrorist threats. It may also be a practical guide for managers and technicians in critical infrastructure, to understand and assess the threats they face. It might also be the foundation for building a national strategy to counter cyberterrorism. In the beginning, it provides basic information about the data. To purify the data, reliability and exploratory factor analysis, as well as confirmatory factor analysis (CFA) were performed. Then, Structural Equation Modelling (SEM) was utilised to test the final model of the theory and to assess the overall goodness-of-fit between the proposed model and the collected data set.

Keywords: cyberterrorism, critical infrastructure, , national security, theoretical framework, terrorism

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Authors: Adedapo Jepson Olumide, Kurowska Ewa, K. Schoeneich, Ikpokonte A. Enoch

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In this paper, subsurface temperature measured from continuous temperature logs were used to determine the geothermal gradient of NigerDelta sedimentary basin. The measured temperatures were corrected to the true subsurface temperatures by applying the American Association of Petroleum Resources (AAPG) correction factor, borehole temperature correction factor with La Max’s correction factor and Zeta Utilities borehole correction factor. Geothermal gradient in this basin ranges from 1.20C to 7.560C/100m. Six geothermal anomalies centres were observed at depth in the southern parts of the Abakaliki anticlinorium around Onitsha, Ihiala, Umuaha area and named A1 to A6 while two more centre appeared at depth of 3500m and 4000m named A7 and A8 respectively. Anomaly A1 describes the southern end of the Abakaliki anticlinorium and extends southwards, anomaly A2 to A5 were found associated with a NW-SE structural alignment of the Calabar hinge line with structures describing the edge of the Niger Delta basin with the basement block of the Oban massif. Anomaly A6 locates in the south-eastern part of the basin offshore while A7 and A8 are located in the south western part of the basin offshore. At the average exploratory depth of 3500m, the geothermal gradient values for these anomalies A1, A2, A3, A4, A5, A6, A7, and A8 are 6.50C/100m, 1.750C/100m, 7.50C/100m, 1.250C/100m, 6.50C/100m, 5.50C/100m, 60C/100m, and 2.250C/100m respectively. Anomaly A8 area may yield higher thermal value at greater depth than 3500m. These results show that anomalies areas of A1, A3, A5, A6 and A7 are potentially prospective and explorable for geothermal energy using abandoned oil wells in the study area. Anomalies A1, A3.A5, A6 occur at areas where drilled boreholes were not exploitable for oil and gas but for the remaining areas where wells are so exploitable there appears no geothermal anomaly. Geothermal energy is environmentally friendly, clean and reversible.

Keywords: temperature logs, geothermal gradient anomalies, alternative energy, Niger delta basin

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Authors: Rakan Hassan M. Alzahrani, Ziyad Alzahrani, Bader Bashrahil, Abdulrahman Elyasi, Abdullah a Ghaddaf, Rayan Alzahrani, Mohammed Alkathlan, Nawaf Alghamdi, Dakheelallah Almutairi

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Background: Corticosteroid irrigations, which regularly involve the off-label use of budesonide mixed with normal saline in high volume Sino-nasal irrigations, have been more commonly used in the management of post-operative chronic rhinosinusitis (CRS). Objective: This article attempted to measure the efficacy of post-operative budesonide nasal irrigation compared to normal saline-alone nasal irrigation in the management of chronic rhinosinusitis (CRS) through a systematic review and meta-analysis of randomized controlled trials (RCTs). Methods: The databases PubMed, Embase, and Cochrane Central Register of Controlled Trials were searched by two independent authors. Only RCTs comparing budesonide irrigation to normal saline alone irrigation for CRS with or without polyposis after functional endoscopic sinus surgery (FESS) were eligible. A random effect analysis model of the reported CRS-related quality of life (QOL) measures and the objective endoscopic assessment scales of the disease was done. Results: Only 6 RCTs met the eligibility criteria, with a total number of participants of 356. Compared to normal saline irrigation, budesonide nasal irrigation showed statically significant improvements in both the CRS-related quality of life (QOL) and the endoscopic findings (MD= -4.22 confidence interval [CI]: -5.63, -2.82 [P < 0.00001]), (SMD= -0.50 confidence interval [CI]: -0.93, -0.06 [P < 0.03]) respectively. Conclusion: Both intervention arms showed improvements in CRS-related QOL and endoscopic findings in post-FESS chronic rhinosinusitis with or without polyposis. However, budesonide irrigation seems to have a slight edge over conventional normal saline irrigation with no reported serious side effects, including hypothalamic-pituitary-adrenal (HPA) axis suppression.

Keywords: Budesonide, chronic rhinosinusitis, corticosteroids, nasal irrigation, normal saline

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Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

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A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: Emmanuel Ifeanyi Ugwu

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Calcium Sulphide which is one of Chalcogenide group of thin films has been analyzed in this work using a theoretical approach in which a scalar wave was propagated through the material thin film medium deposited on a glass substrate with the assumption that the dielectric medium has homogenous reference dielectric constant term, and a perturbed dielectric function, representing the deposited thin film medium on the surface of the glass substrate as represented in this work. These were substituted into a defined scalar wave equation that was solved first of all by transforming it into Volterra equation of second type and solved using the method of separation of variable on scalar wave and subsequently, Green’s function technique was introduced to obtain a model equation of wave propagating through the thin film that was invariably used in computing the propagated field, for different input wavelengths representing UV, Visible and Near-infrared regions of field considering the influence of the dielectric constants of the thin film on the propagating field. The results obtained were used in turn to compute the band gaps, solid state and optical properties of the thin film.

Keywords: scalar wave, dielectric constant, calcium sulphide, solid state, optical properties

Procedia PDF Downloads 118

Authors: Shawna Staud, Mary Kaye Scaramucci

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Objective: Rubber cup polishing has been a traditional method of preventative therapy in dental hygiene treatment. Newer methods such as air polishing have changed the way dental hygiene care is provided, yet this technique has not been embraced by students in the program nor by practitioners in the workforce. Students entering the workforce tend to follow office protocol and are limited in confidence to introduce technologies learned in the curriculum. This project was designed to help students gain confidence in newer skills and encourage private practice settings to adopt newer technologies for patient care. Our program recently introduced air polishing earlier in the program before the rubber cup technique to determine if students would embrace the technology to become leading-edge professionals when they enter the marketplace. Methods: The class of 2022 was taught the traditional method of polishing in the first-year curriculum and air polishing in the second-year curriculum. The class of 2023 will be taught the air polishing method in the first-year curriculum and the traditional method of polishing in the second-year curriculum. Pre- and post-graduation survey data will be collected from both cohorts. Descriptive statistics and pre and post-paired t-tests with alpha set at .05 to compare pre and post-survey results will be used to assess data. Results: This study is currently in progress, with a completion date of October 2023. The class of 2022 completed the pre-graduation survey in the spring of 2022. The post-gradation survey will be sent out in October 2022. The class of 2023 cohort will be surveyed in the spring of 2023 and October 2023. Conclusion: Our hypothesis is students who are taught air polishing first will be more inclined to adopt that skill in private practice, thereby embracing newer technology and improving oral health care.

Keywords: luggage handling system at world’s largest pilgrimage center

Procedia PDF Downloads 103

Authors: Violeta Damjanovic-Behrendt

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This paper presents an approach for optimal cyber security decisions to protect instances of a federated Internet of Things (IoT) platform in the cloud. The presented solution implements the repeated Stackelberg Security Game (SSG) and a model called Stochastic Human behaviour model with AttRactiveness and Probability weighting (SHARP). SHARP employs the Subjective Utility Quantal Response (SUQR) for formulating a subjective utility function, which is based on the evaluations of alternative solutions during decision-making. We augment the repeated SSG (including SHARP and SUQR) with a reinforced learning algorithm called Naïve Q-Learning. Naïve Q-Learning belongs to the category of active and model-free Machine Learning (ML) techniques in which the agent (either the defender or the attacker) attempts to find an optimal security solution. In this way, we combine GT and ML algorithms for discovering optimal cyber security policies. The proposed security optimization components will be validated in a collaborative cloud platform that is based on the Industrial Internet Reference Architecture (IIRA) and its recently published security model.

Keywords: security, internet of things, cloud computing, stackelberg game, machine learning, naive q-learning

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Authors: Arman Ameen, Mathias Cehlin

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The use of Building Energy Simulation (BES) software has increased in the last two decades, parallel to the development of increased computing power and easy to use software applications. This type of software is primarily used to simulate the energy use and the indoor environment for a building. The rapid development of these types of software has raised their level of user-friendliness, better parameter input options and the increased possibility of analysis, both for a single building component or an entire building. This, in turn, has led to many researchers utilizing BES software in their research in various degrees. The aim of this paper is to carry out a literature review concerning the use of the BES software IDA Indoor Climate and Energy (IDA ICE) in the scientific community. The focus of this paper will be specifically the use of the software for whole building energy simulation, number and types of articles and publications dates, the area of application, types of parameters used, the location of the studied building, type of building, type of analysis and solution methodology. Another aspect that is examined, which is of great interest, is the method of validations regarding the simulation results. The results show that there is an upgoing trend in the use of IDA ICE and that researchers use the software in their research in various degrees depending on case and aim of their research. The satisfactory level of validation of the simulations carried out in these articles varies depending on the type of article and type of analysis.

Keywords: building simulation, IDA ICE, literature review, validation

Procedia PDF Downloads 135

Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: A. Šapkauskienė, A. Mačerinskienė, R. Andrulienė, R. Bruzgė, S. Masteika, K. Driaunys

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The COVID-19 pandemic has affected not only world markets and economies but also the daily lives of customers and their payment habits. The pandemic has accelerated the digital transformation, so the role of technology will become even more important post-COVID. Although the popularity of cryptocurrencies has reached unprecedented heights, there are still obstacles, such as a lack of consumer experience and distrust of these technologies, so exploring the role of cryptocurrency and blockchain in the context of international travel becomes extremely important. Research on tourists’ intentions to use cryptocurrencies for payment purposes is limited due to the small number of research studies. To fill this research gap, an exploratory study based on the analysis of survey data was conducted. The purpose of the research is to explore how the behavior of tourists has changed making their financial transactions when paying for the tourism services in order to determine the intention to pay in cryptocurrencies. Behavioral intention can be examined as a dependent variable that is useful for the study of the acceptance of blockchain as cutting-edge technology. Therefore, this study examines the intention of travelers to use cryptocurrencies in electronic payments for tourism services. Several studies have shown that the intention to accept payments in a cryptocurrency is affected by the perceived usefulness of these payments and the perceived ease of use. The findings deepen our understanding of the readiness of service users to apply for blockchain-based payment in the tourism sector. The tourism industry has to focus not only on the technology but on consumers who can use cryptocurrencies, creating new possibilities and increasing business competitiveness. Based on research results, suggestions are made to guide future research on the use of cryptocurrencies by tourists in the tourism industry. Therefore, in line with the rapid expansion of virtual currency users, market capitalization, and payment in cryptographic currencies, it is necessary to explore the possibilities of implementing a blockchain-based system aiming to promote the use of services in the tourism sector as the most affected by the pandemic.

Keywords: behavioral intention, blockchain-based payment, cryptocurrency, tourism

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Authors: Hossam Ali-Hassan, Michael Bliemel

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This poster reflects upon our experiences using INNOV8, IBM’s Business Process Management (BPM) simulation game, in online MBA and undergraduate MIS classes over a period of 2 years. The game is designed to gives both business and information technology players a better understanding of how effective BPM impacts an entire business ecosystem. The game includes three different scenarios: Smarter Traffic, which is used to evaluate existing traffic patterns and re-route traffic based on incoming metrics; Smarter Customer Service where players develop more efficient ways to respond to customers in a call centre environment; and Smarter Supply Chains where players balance supply and demand and reduce environmental impact in a traditional supply chain model. We use the game as an experiential learning tool, where students have to act as managers making real time changes to business processes to meet changing business demands and environments. The students learn how information technology (IT) and information systems (IS) can be used to intelligently solve different problems and how computer simulations can be used to test different scenarios or models based on business decisions without having to actually make the potentially costly and/or disruptive changes to business processes. Moreover, when students play the three different scenarios, they quickly see how practical process improvements can help meet profitability, customer satisfaction and environmental goals while addressing real problems faced by municipalities and businesses today. After spending approximately two hours in the game, students reflect on their experience from it to apply several BPM principles that were presented in their textbook through the use of a structured set of assignment questions. For each final scenario students submit a screenshot of their solution followed by one paragraph explaining what criteria you were trying to optimize, and why they picked their input variables. In this poster we outline the course and the module’s learning objectives where we used the game to place this into context. We illustrate key features of the INNOV8 Simulation Game, and describe how we used them to reinforce theoretical concepts. The poster will also illustrate examples from the simulation, assignment, and learning outcomes.

Keywords: experiential learning, business process management, BPM, INNOV8, simulation, game

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Authors: Dar-Bin Shieh, Gwo-Bin Lee, Chen-Ming Chang, Chen Sheng Yeh, Chih-Chia Huang, Tsung-Ju Li

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Mitochondrial defects have a significant impact in many human diseases and aging associated phenotypes. The pathogenic mitochondrial DNA (mtDNA) mutations are diverse and usually present as heteroplasmic. mtDNA 4977bps deletion is one of the common mtDNA defects, and the ratio of mutated versus normal copy is significantly associated with clinical symptoms thus their quantitative detection has become an important unmet needs for advanced disease diagnosis and therapeutic guidelines. This study revealed a Micro-electro-mechanical-system (MEMS) enabled automatic microfluidic chip that only required minimal sample. The system integrated multiple laboratory operation steps into a Lab-on-a-Chip for high-sensitive and prompt measurement. The entire process including magnetic nanoparticle based mtDNA extraction in chip, mutation selective photonic DNA cleavage, and nanoparticle accelerated photonic quantitative polymerase chain reaction (qPCR). All subsystems were packed inside a miniature three-dimensional micro structured system and operated in an automatic manner. Integration of magnetic beads with microfluidic transportation could promptly extract and enrich the specific mtDNA. The near infrared responsive magnetic nanoparticles enabled micro-PCR to be operated by pulse-width-modulation controlled laser pulsing to amplify the desired mtDNA while quantified by fluorescence intensity captured by a complementary metal oxide system array detector. The proportions of pathogenic mtDNA in total DNA were thus obtained. Micro capillary electrophoresis module was used to analyze the amplicone products. In conclusion, this study demonstrated a new magnetophotonic based qPCR MEMS system that successfully detects and quantify specific disease related DNA mutations thus provides a promising future for rapid diagnosis of mitochondria diseases.

Keywords: mitochondrial DNA, micro-electro-mechanical-system, magnetophotonics, PCR

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Authors: Asowata Osamede, Christo Pienaar, Johan Bekker

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Mismatch in electrical energy (power) or outage from commercial providers, in general, does not promote development to the public and private sector, these basically limit the development of industries. The necessity for a well-structured photovoltaic (PV) system is of importance for an efficient and cost-effective monitoring system. The major renewable energy potential on earth is provided from solar radiation and solar photovoltaics (PV) are considered a promising technological solution to support the global transformation to a low-carbon economy and reduction on the dependence on fossil fuels. Solar arrays which consist of various PV module should be operated at the maximum power point in order to reduce the overall cost of the system. So power regulation and conditioning circuits should be incorporated in the set-up of a PV system. Power regulation circuits used in PV systems include maximum power point trackers, DC-DC converters and solar chargers. Inappropriate choice of power conditioning device in a basic off-grid PV system can attribute to power loss, hence the need for a right choice of power conditioning device to be coupled with the system of the essence. This paper presents the design and implementation of a power conditioning devices in order to improve the overall yield from the availability of solar energy and the system’s total efficiency. The power conditioning devices taken into consideration in the project includes the Buck and Boost DC-DC converters as well as solar chargers with MPPT. A logging interface circuit (LIC) is designed and employed into the system. The LIC is designed on a printed circuit board. It basically has DC current signalling sensors, specifically the LTS 6-NP. The LIC is consequently required to program the voltages in the system (these include the PV voltage and the power conditioning device voltage). The voltage is structured in such a way that it can be accommodated by the data logger. Preliminary results which include availability of power as well as power loss in the system and efficiency will be presented and this would be used to draw the final conclusion.

Keywords: tilt and orientation angles, solar chargers, PV panels, storage devices, direct solar radiation

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Authors: Marlone D. Severo

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A pre- and post-test quasi-experimental design was used to test the intervention of Trachtenberg Speed Math on the mathematical competency of sixty (60) matched-paired students with a poor performing grade in Mathematics from one of the biggest public national high school at the South of Metro Manila. Both control and experimental group were administered with the Attitude Towards Mathematics Inventory (ATMI) before the pretest were given and both group showed high dislike for Mathematics. Pretest showed a 53 percent accuracy for the control group and 51 percent for the experimental group using a 15-item long multiplication test without any aid of a computing device. The experimental group were taught how to use the Trachtenberg number-keys and techniques in multiplication between October 2014 to March 2015. Post-test showed an improvement in the experimental group with 96 percent accuracy for the control group and a dismal 57 percent for the control group in long-multiplication. Post-test ATMI were administered. The control group showed a great dislike towards Mathematics, while the experimental group showed a positive attitude towards the subject.

Keywords: attitude towards mathematics, mathematical competency, number-keys, trachtenberg speed math

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Authors: Pejman Hosseinioun, Abolghasem Ghasempour, Elham Gholami, Hamed Sarbazi

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Considering the development in global semiconductor technology, it is anticipated that gadgets such as diodes and resonant transistor tunnels (RTD/RTT), Single electron transistors (SET) and quantum cellular automata (QCA) will substitute CMOS (Complementary Metallic Oxide Semiconductor) gadgets in many applications. Unfortunately, these new technologies cannot disembark the common Boolean logic efficiently and are only appropriate for liminal logic. Therefor there is no doubt that with the development of these new gadgets it is necessary to find new MacDraw technologies which are compatible with them. Resonant transistor tunnels (RTD/RTT) and circuit MacDraw with enhanced computing abilities are candida for accumulating Nano criterion in the future. Quantum cellular automata (QCA) are also advent Nano technological gadgets for electrical circuits. Advantages of these gadgets such as higher speed, smaller dimensions, and lower consumption loss are of great consideration. QCA are basic gadgets in manufacturing gates, fuses and memories. Regarding the complex Nano criterion physical entity, circuit designers can focus on logical and constructional design to decrease complication in MacDraw. Moreover Single electron technology (SET) is another noteworthy gadget considered in Nano technology. This article is a survey in future of Nano technology in digital MacDraw.

Keywords: nano technology, resonant transistor tunnels, quantum cellular automata, semiconductor

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Authors: Ankur Bansal, Shashank Bishnoi

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Degradation of Sewage pipes, sewage pumping station and Sewage treatment plants(STP) is of major concern due to difficulty in their maintenance and the high cost of replacement. Most of these systems undergo degradation due to Biogenic sulphuric acid (BSA) attack. Since most of Waste water treatment system are underground, detection of this deterioration remains hidden. This paper presents a literature review, outlining the mechanism of this attack focusing on critical parameters of BSA attack, along with available models and software to predict the deterioration due to this attack. This paper critically examines the various steps and equation in various Models of BSA degradation, detail on assumptions and working of different softwares are also highlighted in this paper. The paper also focuses on the service life design technique available through various codes and method to integrate the servile life design with BSA degradation on concrete. In the end, various methods enhancing the resistance of concrete against Biogenic sulphuric acid attack are highlighted. It may be concluded that the effective modelling for degradation phenomena may bring positive economical and environmental impacts. With current computing capabilities integrated degradation models combining the various durability aspects can bring positive change for sustainable society.

Keywords: concrete degradation, modelling, service life, sulphuric acid attack

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Authors: Kwang Chun, John Kemeny

Abstract:

Light detection and ranging (LiDAR) has been a prevalent remote-sensing technology applied in the geological fields due to its high precision and ease of use. One of the major applications is to use the detailed geometrical information of underground structures as a basis for the generation of a three-dimensional numerical model that can be used in a geotechnical stability analysis such as FEM or DEM. To date, however, straightforward techniques in reconstructing the numerical model from the scanned data of the underground structures have not been well established or tested. In this paper, we propose a comprehensive approach integrating all the various processes, from LiDAR scanning to finite element numerical analysis. The study focuses on converting LiDAR 3D point clouds of geologic structures containing complex surface geometries into a finite element model. This methodology has been applied to Kartchner Caverns in Arizona, where detailed underground and surface point clouds can be used for the analysis of underground stability. Numerical simulations were performed using the finite element code Abaqus and presented by 3D computing visualization solution, ParaView. The results are useful in studying the stability of all types of underground excavations including underground mining and tunneling.

Keywords: finite element analysis, LiDAR, remote-sensing, scientific visualization, underground stability

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Authors: Daidai Shen, Jean Claude Thill, Wenjia Zhang

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This study explores the dynamics of synergy and complementarity within city networks, specifically focusing on the headquarters-subsidiary relations of firms. We begin by defining these two types of networks and establishing their pivotal roles in shaping city network structures. Utilizing the mesoscale analytic approach of weighted stochastic block modeling, we discern relational patterns between city pairs and determine connection strengths through statistical inference. Furthermore, we introduce a community detection approach to uncover the underlying structure of these networks using advanced statistical methods. Our analysis, based on comprehensive network data up to 2017, reveals the coexistence of both complementarity and synergy networks within China’s technology-intensive manufacturing cities. Notably, firms in technology hardware and office & computing machinery predominantly contribute to the complementarity city networks. In contrast, a distinct synergy city network, underpinned by the cities of Suzhou and Dongguan, emerges amidst the expansive complementarity structures in technology hardware and equipment. These findings provide new insights into the relational dynamics and structural configurations of city networks in the context of technology-intensive manufacturing, highlighting the nuanced interplay between synergy and complementarity.

Keywords: city system, complementarity, synergy network, higher-order network

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Authors: A. Mohamed Mydeen, Pallapa Venkataram

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The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.

Keywords: knowledge representation, pervasive computing, agent technology, ECA rules

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Authors: Leonardo A. Ambrosio, Carlos. H. Silva Santos, Ivan E. L. Rodrigues, Ayumi K. de Campos, Leandro A. Machado

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In this work, we propose an algorithm developed under Python language for the modeling of ordinary scalar Bessel beams and their discrete superpositions and subsequent calculation of optical forces exerted over dielectric spherical particles. The mathematical formalism, based on the generalized Lorenz-Mie theory, is implemented in Python for its large number of free mathematical (as SciPy and NumPy), data visualization (Matplotlib and PyJamas) and multiprocessing libraries. We also propose an approach, provided by a synchronized Software as Service (SaaS) in cloud computing, to develop a user interface embedded on a mobile application, thus providing users with the necessary means to easily introduce desired unknowns and parameters and see the graphical outcomes of the simulations right at their mobile devices. Initially proposed as a free Android-based application, such an App enables data post-processing in cloud-based architectures and visualization of results, figures and numerical tables.

Keywords: Bessel Beams and Frozen Waves, Generalized Lorenz-Mie Theory, Numerical Methods, optical forces

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Authors: Apirak Sombat, Teerapol Saleewong, Poom Kumam, Parin Chaipunya, Wiyada Kumam, Anantachai Padcharoen, Yeol Je Cho, Thana Sutthibutpong

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This research is aimed to study a two-step iteration process defined over a finite family of σ-asymptotically quasi-nonexpansive nonself-mappings. The strong convergence is guaranteed under the framework of Banach spaces with some additional structural properties including strict and uniform convexity, reflexivity, and smoothness assumptions. With similar projection technique for nonself-mapping in Hilbert spaces, we hereby use the generalized projection to construct a point within the corresponding domain. Moreover, we have to introduce the use of duality mapping and its inverse to overcome the unavailability of duality representation that is exploit by Hilbert space theorists. We then apply our results for σ-asymptotically quasi-nonexpansive nonself-mappings to solve for ideal efficiency of vector optimization problems composed of finitely many objective functions. We also showed that the obtained solution from our process is the closest to the origin. Moreover, we also give an illustrative numerical example to support our results.

Keywords: asymptotically quasi-nonexpansive nonself-mapping, strong convergence, fixed point, uniformly convex and uniformly smooth Banach space

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Authors: Leila Baghaarabani, Parvin Razzaghi, Mennatolla Magdy Mostafa, Ahmad Albaqsami, Al Warith Al Rushaidi, Masoud Al Rawahi

Abstract:

Predicting the interaction between drugs and their molecular targets is pivotal for advancing drug development processes. Due to the time and cost limitations, computational approaches have emerged as an effective approach to drug-target interaction (DTI) prediction. Most of the introduced computational based approaches utilize the drug molecule and protein sequence as input. This study does not only utilize these inputs, it also introduces a protein representation developed using a masked protein language model. In this representation, for every individual amino acid residue within the protein sequence, there exists a corresponding probability distribution that indicates the likelihood of each amino acid being present at that particular position. Then, the similarity between each pair of amino-acids is computed to create similarity matrix. To encode the knowledge of the similarity matrix, Bi-Level Routing Attention (BiFormer) is utilized, which combines aspects of transformer-based models with protein sequence analysis and represents a significant advancement in the field of drug-protein interaction prediction. BiFormer has the ability to pinpoint the most effective regions of the protein sequence that are responsible for facilitating interactions between the protein and drugs, thereby enhancing the understanding of these critical interactions. Thus, it appears promising in its ability to capture the local structural relationship of the proteins by enhancing the understanding of how it contributes to drug protein interactions, thereby facilitating more accurate predictions. To evaluate the proposed method, it was tested on two widely recognized datasets: Davis and KIBA. A comprehensive series of experiments was conducted to illustrate its effectiveness in comparison to cuttingedge techniques.

Keywords: BiFormer, transformer, protein language processing, self-attention mechanism, binding affinity, drug target interaction, similarity matrix, protein masked representation, protein language model

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