Search results for: comprehensive CFD model

Authors: Felippe Clemente, Evaldo Henrique da Silva

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The need to adopt some type of industrial policy and innovation in Brazil is a recurring theme in the discussion of public interventions aimed at boosting economic growth. For many years, the country has adopted various policies to change its productive structure in order to increase the participation of sectors that would have the greatest potential to generate innovation and economic growth. Only in the 2000s, tax incentives as a policy to support industrial and technological innovation are being adopted in Brazil as a phenomenon associated with rates of productivity growth and economic development. In this context, in late 2004 and 2005, Brazil reformulated its institutional apparatus for innovation in order to approach the OECD conventions and the Frascati Manual. The Innovation Law (2004) and the 'Lei do Bem' (2005) reduced some institutional barriers to innovation, provided incentives for university-business cooperation, and modified access to tax incentives for innovation. Chapter III of the 'Lei do Bem' (no. 11,196/05) is currently the most comprehensive fiscal incentive to stimulate innovation. It complies with the requirements, which stipulates that the Union should encourage innovation in the company or industry by granting tax incentives. With its introduction, the bureaucratic procedure was simplified by not requiring pre-approval of projects or participation in bidding documents. However, preliminary analysis suggests that this instrument has not yet been able to stimulate the sector diversification of these investments in Brazil, since its benefits are mostly captured by sectors that already developed this activity, thus showing problems with moral hazard. It is necessary, then, to analyze the 'Lei do Bem' to know if there is indeed the need for some change, investigating what changes should be implanted in the Brazilian innovation policy. This work, therefore, shows itself as a first effort to analyze a current national problem, evaluating the effectiveness of the 'Lei do Bem' and suggesting public policies that help and direct the State to the elaboration of legislative laws capable of encouraging agents to follow what they describes. As a preliminary result, it is known that 130 firms used fiscal incentives for innovation in 2006, 320 in 2007 and 552 in 2008. Although this number is on the rise, it is still small, if it is considered that there are around 6 thousand firms that perform Research and Development (R&D) activities in Brazil. Moreover, another obstacle to the 'Lei do Bem' is the percentages of tax incentives provided to companies. These percentages reveal a significant sectoral correlation between R&D expenditures of large companies and R&D expenses of companies that accessed the 'Lei do Bem', reaching a correlation of 95.8% in 2008. With these results, it becomes relevant to investigate the law's ability to stimulate private investments in R&D.

Keywords: brazilian innovation system, moral hazard, R&D, Lei do Bem

Procedia PDF Downloads 339

Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

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Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

Procedia PDF Downloads 358

Authors: Zhi Zhu, Boquan Zhang, Tian Jing, Jingjing Li, Tao Wang

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Data assimilation is a model and data hybrid-driven method that dynamically fuses new observation data with a numerical model to iteratively approach the real system state. It is widely used in state prediction and parameter inference of continuous systems. Because of the discrete event system’s non-linearity and non-Gaussianity, traditional Kalman Filter based on linear and Gaussian assumptions cannot perform data assimilation for such systems, so particle filter has gradually become a technical approach for discrete event simulation data assimilation. Hence, we proposed a particle filter-based discrete event simulation data assimilation method and took the unmanned aerial vehicle (UAV) maintenance service system as a proof of concept to conduct simulation experiments. The experimental results showed that the filtered state data is closer to the real state of the system, which verifies the effectiveness of the proposed method. This research can provide a reference framework for the data assimilation process of other complex nonlinear systems, such as discrete-time and agent simulation.

Keywords: discrete event simulation, data assimilation, particle filter, model and data-driven

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Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

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Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: pollen recognition, logistic model tree, expectation-maximization, local binary pattern

Procedia PDF Downloads 184

Authors: Nasiru Aliyu, Glyn Atkinson, Nick Stannard

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With increasing demand for electric motors used in nearly all sectors of our day to day activities, which range from the motor that rotates the washing machine and dishwasher to the tens of thousands of motors used in domestic appliance. The number of applications for soft magnetic composites (SMC) material is growing significantly. This paper presents the development of a compact single sided concentrated winding axial flux PM motor using soft magnetic composite as core for reducing core losses and cost. The effects of changing the flux carrying component to pressed SMC parts are investigated based on a comprehensive understanding of the properties of the material. A 3-D finite-element analysis is performed for accurate parameter calculation. To validate the simulation, a new static test measurement was fully conducted on a prototype motor and agree with the theoretical calculations and old measured static test.

Keywords: SMC, compact development, axial field motor, 3DFA

Procedia PDF Downloads 333

Authors: Chia-Hao Chang, Geng-Gui Wang, Jee-Cheng Wu

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The prediction of a landslide is a difficult task because it requires a detailed study of past activities using a complete range of investigative methods to determine the changing condition. In this research, first step, LiDAR 1-meter by 1-meter resolution of digital elevation model (DEM) was used to generate six environmental factors of landslide. Then, back-propagation neural networks (BPNN) was adopted to identify scarp, landslide areas and non-landslide areas. The BPNN uses 6 environmental factors in input layer and 1 output layer. Moreover, 6 landslide areas are used as training areas and 4 landslide areas as test areas in the BPNN. The hidden layer is set to be 1 and 2; the hidden layer neurons are set to be 4, 5, 6, 7 and 8; the learning rates are set to be 0.01, 0.1 and 0.5. When using 1 hidden layer with 7 neurons and the learning rate sets to be 0.5, the result of Network training root mean square error is 0.001388. Finally, evaluation of BPNN classification accuracy by the confusion matrix shows that the overall accuracy can reach 94.4%, and the Kappa value is 0.7464.

Keywords: digital elevation model, DEM, environmental factors, back-propagation neural network, BPNN, LiDAR

Procedia PDF Downloads 147

Authors: Eisa Younes Alblooshi

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Counterterrorism strategies, to be effective and efficient, require a sound understanding of the dynamics, the interlinked organizational elements of the terrorist outfits being combated, with a view to having cognizance of their strong points to be guarded against, as well as the vulnerable zones that can be targeted for optimal results in a timely fashion by counterterrorism agencies. A unique model regarding the organizational imperatives was evolved in this research through likening the terrorist organizations with the traditional commercial ones, with a view to understanding in detail the dynamics of interconnectivity and dependencies, and the related compulsions facing the leaderships of such outfits that provide counterterrorism agencies with opportunities for forging better strategies. It involved assessing the evolving organizational dynamics and imperatives of different types of terrorist organizations, to enable the researcher to construct a prototype model that defines the progression and linkages of the related organizational elements of such organizations. It required detailed analysis of how the various elements are connected, with sequencing identified, as any outfit positions itself with respect to its external environment and internal dynamics. A case study focusing on a transnational radical religious state-sponsored terrorist organization was conducted to validate the research findings and to further strengthen the specific counterterrorism strategies. Six different variants of the business model of terrorist organizations were identified, categorized based on their outreach, mission, and status of any state sponsorship. The variants represent vast majority of the range of terrorist organizations acting locally or globally. The model shows the progression and dynamics of these organizations through various dimensions including mission, leadership, outreach, state sponsorship status, resulting in the organizational structure, state of autonomy, preference divergence in its fold, recruitment core, propagation avenues, down to their capacity to adapt, resulting critically in their own life cycles. A major advantage of the model is the utility of mapping terrorist organizations according to their fits to the sundry identified variants, allowing for flexibility and differences within, enabling the researchers and counterterrorism agencies to observe a neat blueprint of the organization’s footprint, along with highlighting the areas to be evaluated for focused target zone selection and timing of counterterrorism interventions. Special consideration is given to the dimension of financing, keeping in context the latest developments regarding cryptocurrencies, hawala, and global anti-money laundering initiatives. Specific counterterrorism strategies and intervention points have been identified for each of the respective model variants, with a view to efficient and effective deployment of resources.

Keywords: terrorism, counterterrorism, model, strategy

Procedia PDF Downloads 159

Authors: Justin-Herve Noubissi, Jean Claude Kamgang, Eric Ramat, Januarius Asongu, Christophe Cambier

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The goal of our study is to analyse the impact of climatic factors in malaria transmission taking into account migration between Douala and Yaoundé, two cities of Cameroon country. We show how variations of climatic factors such as temperature and relative humidity affect the malaria spread. We propose a meta-population model of the dynamic transmission of malaria that evolves in space and time and that takes into account temperature and relative humidity and the migration between Douala and Yaoundé. We also integrate the variation of environmental factors as events also called mathematical impulsion that can disrupt the model evolution at any time. Our modelling has been done using the Discrete EVents System Specification (DEVS) formalism. Our implementation has been done on Virtual Laboratory Environment (VLE) that uses DEVS formalism and abstract simulators for coupling models by integrating the concept of DEVS.

Keywords: compartmental models, DEVS, discrete events, meta-population model, VLE

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Authors: Moses Emetere, Marvel Akinyemi, S. E. Sanni

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At the moment, AERONET or AMMA database shows a large volume of data loss. With only about 47% data set available to the scientist, it is evident that accurate nowcast or forecast cannot be guaranteed. The calibration constants of most radiosonde or weather stations are not compatible with the atmospheric conditions of the West African climate. A dispersion model was developed to incorporate salient mathematical representations like a Unified number. The Unified number was derived to describe the turbulence of the aerosols transport in the frictional layer of the lower atmosphere. Fourteen years data set from Multi-angle Imaging SpectroRadiometer (MISR) was tested using the dispersion model. A yearly estimation of the atmospheric constants over Ouagadougou using the model was obtained with about 87.5% accuracy. It further revealed that the average atmospheric constant for Ouagadougou-Niger is a_1 = 0.626, a_2 = 0.7999 and the tuning constants is n_1 = 0.09835 and n_2 = 0.266. Also, the yearly atmospheric constants affirmed the lower atmosphere of Ouagadougou is very dynamic. Hence, it is recommended that radiosonde and weather station manufacturers should constantly review the atmospheric constant over a geographical location to enable about eighty percent data retrieval.

Keywords: aerosols retention, aerosols loading, statistics, analytical technique

Procedia PDF Downloads 319

Authors: Reza Heidari, Maryam Amiri

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In a technological world, many countries have a tendency to fortifying their companies and technological infrastructures. Also, one of the most important requirements for developing technology is innovation, and then, all companies are struggling to consider innovation as a basic principle. Since, the expansion of a product need to combine different technologies, therefore, different innovative projects would be run in the firms as a base of technology development. In such an environment, enterprise resource planning (ERP) has special significance in order to develop and strengthen of innovations. In this article, an economic-probabilistic analysis was provided to perform an implementation project of ERP in the technological innovation (TI) based firms. The used model in this article assesses simultaneously both risk and economic analysis in view of the probability of each event that is jointly between economical approach and risk investigation approach. To provide an economic-probabilistic analysis of risk of the project, activities and milestones in the cash flow were extracted. Also, probability of occurrence of each of them was assessed. Since, Resources planning in an innovative firm is the object of this project. Therefore, we extracted various risks that are in relation with innovative project and then they were evaluated in the form of cash flow. This model, by considering risks affecting the project and the probability of each of them and assign them to the project's cash flow categories, presents an adjusted cash flow based on Net Present Value (NPV) and with probabilistic simulation approach. Indeed, this model presented economic analysis of the project based on risks-adjusted. Then, it measures NPV of the project, by concerning that these risks which have the most effect on technological innovation projects, and in the following measures probability associated with the NPV for each category. As a result of application of presented model in the information and communication technology (ICT) industry, provided an appropriate analysis of feasibility of the project from the point of view of cash flow based on risk impact on the project. Obtained results can be given to decision makers until they can practically have a systematically analysis of the possibility of the project with an economic approach and as moderated.

Keywords: cash flow categorization, economic evaluation, probabilistic, risk assessment, technological innovation

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Authors: Ruchika Goyal, Ashwani Kumar, Sandeep Jain

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The experimental data for anticancer potential of curcumin nanoparticles was calculated by means of eclectic data. The optimal descriptors were examined using Monte Carlo method based CORAL SEA software. The statistical quality of the model is following: n = 14, R² = 0.6809, Q² = 0.5943, s = 0.175, MAE = 0.114, F = 26 (sub-training set), n =5, R²= 0.9529, Q² = 0.7982, s = 0.086, MAE = 0.068, F = 61, Av Rm² = 0.7601, ∆R²m = 0.0840, k = 0.9856 and kk = 1.0146 (test set) and n = 5, R² = 0.6075 (validation set). This data can be used to build predictive QSAR models for anticancer activity.

Keywords: anticancer potential, curcumin, model, nanoparticles, optimal descriptors, QSAR

Procedia PDF Downloads 323

Authors: Halim Djerroud, Arab Ali Cherif

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We assume that conscious functions are implemented automatically. In other words that consciousness as well as the non-consciousness aspect of human thought, planning, and perception, are produced by biologically adaptive algorithms. We propose that the mechanisms of consciousness can be produced using similar adaptive algorithms to those executed by the mechanism. In this paper, we propose a computational model of consciousness, the ”Global Abstraction Workspace” which is an internal environmental modelling perceived as a multi-agent system. This system is able to evolve and generate new data and processes as well as actions in the environment.

Keywords: artificial consciousness, cognitive architecture, global abstraction workspace, multi-agent system

Procedia PDF Downloads 342

Authors: Majid Etaati, Hamid Majedi

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Relational planning approach proposed by Patsy Healey goes beyond the physical proximity and emphasizes social proximity. This approach stresses the importance of nodes and flows between nodes. Current plans in European cities have incrementally incorporated this approach, but urban plans in Iran have still stayed very detailed and rigid. In response to the weak evaluation results of the comprehensive planning approach in Qazvin, the local authorities applied the City Development Strategy (CDS) to cope with new urban challenges. The paper begins with an explanation of relational planning and suggests that Healey gives urban planners about spatial strategies and then it surveys relational factors in CDS of Qazvin. This study analyzes the extent which CDS of Qazvin have highlighted nodes, flows, and dynamics. In the end, the study concludes that there is a relational understanding of urban dynamics in the plan, but it is weak.

Keywords: relational, dynamics, city development strategy, urban planning, Qazvin

Procedia PDF Downloads 141

Authors: Yinglisong, Jingge Chen, Jingxuan Chen, Yan Wang, Hui Huang, Jing Zhnag, Qianqian Zhang, Zhenzhen Zhang, Ji Zhang

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Purpose: The study aims to establish a nomogram prediction model for postpartum hemorrhage (PPH) in vaginal delivery. Patients and Methods: Clinical data were retrospectively collected from vaginal delivery patients admitted to a hospital in Zhengzhou, China, from June 1, 2022 - October 31, 2022. Univariate and multivariate logistic regression were used to filter out independent risk factors. A nomogram model was established for PPH in vaginal delivery based on the risk factors coefficient. Bootstrapping was used for internal validation. To assess discrimination and calibration, receiver operator characteristics (ROC) and calibration curves were generated in the derivation and validation groups. Results: A total of 1340 cases of vaginal delivery were enrolled, with 81 (6.04%) having PPH. Logistic regression indicated that history of uterine surgery, induction of labor, duration of first labor, neonatal weight, WBC value (during the first stage of labor), and cervical lacerations were all independent risk factors of hemorrhage (P <0.05). The area-under-curve (AUC) of ROC curves of the derivation group and the validation group were 0.817 and 0.821, respectively, indicating good discrimination. Two calibration curves showed that nomogram prediction and practical results were highly consistent (P = 0.105, P = 0.113). Conclusion: The developed individualized risk prediction nomogram model can assist midwives in recognizing and diagnosing high-risk groups of PPH and initiating early warning to reduce PPH incidence.

Keywords: vaginal delivery, postpartum hemorrhage, risk factor, nomogram

Procedia PDF Downloads 81

Authors: Javier Donoso-Bravo, Camila Cortés-Zambrano

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In this paper, we analyze socioterritorial inequalities in the region of Valparaiso (Chile) using secondary data to account for these inequalities drawing on economic, social, educational, and environmental dimensions regarding the thirty-six municipalities of the region. We looked over a wide-ranging set of secondary data from public sources regarding economic activities, poverty, employment, income, years of education, post-secondary education access, green areas, access to potable water, and others. We found sharp socioterritorial inequalities especially based on the economic performance in each territory. Analysis show, on the one hand, the existence of a dual and unorganized development model in some territories with a strong economic activity -especially in the areas of finance, real estate, mining, and vineyards- but, at the same time, with poor social indicators. On the other hand, most of the territories show a dispersed model with very little dynamic economic activities and very poor social development. Finally, we discuss how socioterritorial inequalities in the region of Valparaiso reflect the level of globalization of the economic activities carried on in every territory.

Keywords: socioterritorial inequalities, development model, Chile, secondary data, Region of Valparaiso

Procedia PDF Downloads 104

Authors: Julio Macedo

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Several methodologies are now available to conceive the improvements of a process so that it becomes competitive as for example total quality, process reengineering, six sigma, define measure analysis improvement control method. These improvements are of different nature and can be external to the process represented by an optimization model or a discrete simulation model. In addition, the process stakeholders are several and have different desired performances for the process. Hence, the methodologies above do not have a tool to aid in the conception of the required improvements. In order to fill this void we suggest the use of intelligent reference models. A reference model is a set of qualitative differential equations and an objective function that minimizes the gap between the current and the desired performance indexes of the process. The reference models are intelligent so when they receive the current state of the problematic process and the desired performance indexes they generate the required improvements for the problematic process. The reference models are fuzzy cognitive maps added with an objective function and trained using the improvements implemented by the high performance firms. Experiments done in a set of students show the reference models allow them to conceive more improvements than students that do not use these models.

Keywords: continuous improvement, fuzzy cognitive maps, process competitiveness, qualitative simulation, system dynamics

Procedia PDF Downloads 90

Authors: P. Valdez, M. Pelissero, A. Haim, F. Muiño, F. Galia, R. Tula

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As a result of the studies performed on the wave energy resource worldwide, a research project was set up to harvest wave energy for its conversion into electrical energy. Within this framework, a theoretical model of the electromechanical energy harvesting system, developed with MATLAB’s Simulink software, will be provided. This tool recreates the site conditions where the device will be installed and offers valuable information about the amount of energy that can be harnessed. This research provides a deeper understanding of the utilization of wave energy in order to improve the efficiency of a 1:1 scale prototype of the device.

Keywords: electromechanical device, modeling, renewable energy, sea wave energy, simulation

Procedia PDF Downloads 491

Authors: Sameh Abaza, Mohamed Ibrahim, Tarek Mahmoud

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Due to the development in the digital image processing, its wide use in many applications such as medical, security, and others, the need for more accurate techniques that are reliable, fast and robust is vehemently demanded. In the field of security, in particular, speed is of the essence. In this paper, a pattern recognition technique that is based on the use of Hidden Markov Model (HMM), K-means and the Sobel operator method is developed. The proposed technique is proved to be fast with respect to some other techniques that are investigated for comparison. Moreover, it shows its capability of recognizing the normal face (center part) as well as face boundary.

Keywords: HMM, K-Means, Sobel, accuracy, face recognition

Procedia PDF Downloads 336

Authors: Reham Al-Zahrani, Noura Aleisa

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The proliferation of Radio Frequency Identification (RFID) technology has raised concerns about system security, particularly regarding tag impersonation attacks. Regarding RFID systems, an appropriate authentication protocol must resist active and passive attacks. A tag impersonation occurs when an adversary's tag is used to fool an authenticating reader into believing it is a legitimate tag. This paper analyzed the security of the efficient, secure, and practical ultra-lightweight RFID Authentication Scheme (ESRAS). Then, the paper presents a comprehensive analysis of the Efficient, Secure, and Practical Ultra-Lightweight RFID Authentication Scheme (ESRAS) in the context of radio frequency identification (RFID) systems that employed the Scyther tool to examine the protocol's security against a tag impersonation attack.

Keywords: RFID, impersonation attack, authentication, ultra-lightweight protocols

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Mojtaba Ghodsi, Hamidreza Ziaifar, Morteza Mohammadzaheri, Payam Soltani

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This article presents an analytical model to estimate the harvested power from a Magnetostrictive cantilevered beam with tip excitation. Furthermore, the effects of internal and external damping on harvested power are investigated. The magnetostrictive material in this harvester is Galfenol. In comparison to other popular smart materials like Terfenol-D, Galfenol has higher strength and machinability. In this article, first, a mechanical model of the Euler-Bernoulli beam is employed to calculate the deflection of the harvester. Then, the magneto-mechanical equation of Galfenol is combined with Faraday's law to calculate the generated voltage of the Magnetostrictive cantilevered beam harvester. Finally, the beam model is incorporated in the aforementioned combination. The results show that a 30×8.5×1 mm Galfenol cantilever beam harvester with 80 turn pickup coil can generate up to 3.7 mV and 9 mW. Furthermore, sensitivity analysis made by Response Surface Method (RSM) shows that the harvested power is only sensitive to the internal damping coefficient.

Keywords: internal damping coefficient, external damping coefficient, euler-bernoulli, energy harvester, galfenol, magnetostrictive, response surface method

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Authors: Polvasut Mahaiamsiri, Piraphong Foosiri

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The purpose of this research is to explore the model of factors affecting decision making to select successor in family business of Thailand. A Structural Equation Model (SEM) was created from relevant theories and researches. Consequently, examine and analyse, the causal relation factors of Succession Plan, Recruitment Process and Strategic Planning, whether they have direct or indirect effects on Decision Making to Select Successor in family business. Units of analysis are selected from the family business, totalling 300 sampling. Population sampling is current owners or CEO from the percentage of six district areas in Thailand with multi-stage sampling. A set of questionnaires is used to collect data. An analysis of structural equation modelling (SEM) technique using AMOS 21 program is conducted to test the hypotheses and confirmatory factor analysis is performed and shows that these variables can be tested. The finding of this study revealed that these factors are separate constructs that combine to determine decision making to select successors.

Keywords: succession plan, family business, recruitment process, strategic planning, decision making to select successor

Procedia PDF Downloads 212

Authors: Zhi Hao Chow, Cian Mulligan, Jack Walsh, Antonio Garzon Vico, Dimitar Krastev

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Drug development is resource-intensive, time-consuming, and increasingly expensive with each developmental stage. The success rates of drug development are also relatively low, and the resources committed are wasted with each failed candidate. As such, a reliable method of predicting the success of drug development is in demand. The hypothesis was that some examples of failed drug candidates are pushed through developmental pipelines based on false confidence and may possess common linguistic features identifiable through sentiment analysis. Here, the concept of using text analysis to discover such features in research publications and investor reports as predictors of success was explored. R studios were used to perform text mining and lexicon-based sentiment analysis to identify affective phrases and determine their frequency in each document, then using SPSS to determine the relationship between our defined variables and the accuracy of predicting outcomes. A total of 161 publications were collected and categorised into 4 groups: (i) Cancer treatment, (ii) Neurodegenerative disease treatment, (iii) Vaccines, and (iv) Others (containing all other drugs that do not fit into the 3 categories). Text analysis was then performed on each document using 2 separate datasets (BING and AFINN) in R within the category of drugs to determine the frequency of positive or negative phrases in each document. A relative positivity and negativity value were then calculated by dividing the frequency of phrases with the word count of each document. Regression analysis was then performed with SPSS statistical software on each dataset (values from using BING or AFINN dataset during text analysis) using a random selection of 61 documents to construct a model. The remaining documents were then used to determine the predictive power of the models. Model constructed from BING predicts the outcome of drug performance in clinical trials with an overall percentage of 65.3%. AFINN model had a lower accuracy at predicting outcomes compared to the BING model at 62.5% but was not effective at predicting the failure of drugs in clinical trials. Overall, the study did not show significant efficacy of the model at predicting outcomes of drugs in development. Many improvements may need to be made to later iterations of the model to sufficiently increase the accuracy.

Keywords: data analysis, drug development, sentiment analysis, text-mining

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Authors: Rima Abu Jaber Bransi, Rawya Jarjoura Burbara

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This study deals with two pioneering approaches in teaching Arabic as a mother tongue: first, computerization of literary and functional texts in the mother tongue; second, the pioneering model in teaching writing skills by computerization. The significance of the study lies in its treatment of a serious problem that is faced in the era of technology, which is the widening gap between the pupils and their mother tongue. The innovation in the study is that it introduces modern methods and tools and a pioneering instructional model that turns the process of mother tongue teaching into an effective, meaningful, interesting and motivating experience. In view of the Arabic language diglossia, standard Arabic and spoken Arabic, which constitutes a serious problem to the pupil in understanding unused words, and in order to bridge the gap between the pupils and their mother tongue, we resorted to computerized techniques; we took texts from the pre-Islamic period (Jahiliyya), starting with the Mu'allaqa of Imru' al-Qais and other selected functional texts and computerized them for teaching in an interesting way that saves time and effort, develops high thinking strategies, expands the literary good taste among the pupils, and gives the text added values that neither the book, the blackboard, the teacher nor the worksheets provide. On the other hand, we have developed a pioneering computerized model that aims to develop the pupil's ability to think, to provide his imagination with the elements of growth, invention and connection, and motivate him to be creative, and raise level of his scores and scholastic achievements. The model consists of four basic stages in teaching according to the following order: 1. The Preparatory stage, 2. The reading comprehension stage, 3. The writing stage, 4. The evaluation stage. Our lecture will introduce a detailed description of the model with illustrations and samples from the units that we built through highlighting some aspects of the uniqueness and innovation that are specific to this model and the different integrated tools and techniques that we developed. One of the most significant conclusions of this research is that teaching languages through the employment of new computerized strategies is very likely to get the Arabic speaking pupils out of the circle of passive reception into active and serious action and interaction. The study also emphasizes the argument that the computerized model of teaching can change the role of the pupil's mind from being a store of knowledge for a short time into a partner in producing knowledge and storing it in a coherent way that prevents its forgetfulness and keeping it in memory for a long period of time. Consequently, the learners also turn into partners in evaluation by expressing their views, giving their notes and observations, and application of the method of peer-teaching and learning.

Keywords: classical poetry, computerization, diglossia, writing skill

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Authors: Seyed Mohammadbagher Jafari, Izmeera Shiham, Masoud Arianfar

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The increased usage of Social media for different uses in turn makes it important to develop an understanding of users and their attitudes toward these sites, and moreover, the uses of such sites in a broader perspective such as broadcasting. This quantitative study addressed the problem of factors influencing the adoption of social media as a medium of public service broadcasting in the Republic of Maldives. These powerful and increasingly usable tools, accompanied by large public social media datasets, are bringing in a golden age of social science by empowering researchers to measure social behavior on a scale never before possible. This was conducted by exploring social responses on the use of social media. Research model was developed based on the previous models such as TAM, DOI and Trust combined model. It evaluates the influence of perceived ease of use, perceived usefulness, trust, complexity, compatibility and relative advantage influence on the adoption of social Media. The model was tested on a sample of 365 Maldivian people using survey method via questionnaire. The result showed that perceived usefulness, trust, relative advantage and complexity would highly influence the adoption of social media.

Keywords: adoption, broadcasting, maldives, social media

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Authors: Alaa El-Din Rezk

Abstract:

For organic xenobiotics, sorption to Aldrich humic acid is a key process controlling their mobility, bioavailability, toxicity and fate in the soil. Hydrophobic organic compounds possessing either acid or basic groups can be partially ionized (deprotonated or protonated) within the range of natural soil pH. For neutral and ionogenicxenobiotics including (neutral, acids and bases) sorption coefficients normalized to organic carbon content, Koc, have measured at different pH values. To this end, the batch equilibrium technique has been used, employing SPME combined with GC-MSD as an analytical tool. For most ionogenic compounds, sorption has been affected by both pH and pKa and can be explained through Henderson-Hasselbalch equation. The results demonstrate that when assessing the environmental fate of ionogenic compounds, their pKa and speciation under natural conditions should be taken into account. A new model has developed to predict the relationship between log Koc and pH with full statistical evaluation against other existing predictive models. Neutral solutes have displayed a good fit with the classical model using log Kow as log Koc predictor, whereas acidic and basic compounds have displayed a good fit with the LSER approach and the new proposed model. Measurement limitations of the Batch technique and SPME-GC-MSD have been found with ionic compounds.

Keywords: humic acid, log Koc, pH, pKa, SPME-GCMSD

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Authors: Mimoun Melliti

Abstract:

This research paper investigates the promises, challenges, and perspectives associated with teaching STEM subjects in English within Tunisian higher education institutions. The study explores the potential benefits of English-medium instruction in Science, Technology, Engineering, and Mathematics (henceforth STEM) education, with a special focus on enhanced global competitiveness, improved English language proficiency, and increased access to international resources and collaborations. Additionally, it examines the various challenges faced by educators and students, such as language shift/barriers, curriculum adaptation, faculty training, and student support. Through a comprehensive analysis of promises and challenges, this paper aims to provide insights and recommendations for effectively implementing English medium instruction (henceforth EMI) of STEM in Tunisian higher education institutions. The paper concludes with a recommended action plan for the proper introduction of EMI of STEM in Tunisia.

Keywords: EMI;, STEM education, EFL, language reforms

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Authors: Theo Ndereyimana, Yann Dufresne, Micael Boulet, Stephane Moreau

Abstract:

The DEM (Discrete Element Method) is used a lot in the industry to simulate large-scale flows of particles; for instance, in a fluidized bed, it allows to predict of the trajectory of every particle. One of the main limits of the DEM is the computational time. The CGM (Coarse-Graining Method) has been developed to tackle this issue. The goal is to increase the size of the particle and, by this means, decrease the number of particles. The method leads to a reduction of the collision frequency due to the reduction of the number of particles. Multiple characteristics of the particle movement and the fluid flow - when there is a coupling between DEM and CFD (Computational Fluid Dynamics). The main characteristic that is impacted is the energy dissipation of the system, to regain the dissipation, an ADM (Additional Dissipative Mechanism) can be added to the model. The objective of this current work is to observe the influence of the choice of the ADM and the factor of coarse-graining on the numerical results. These results will be compared with experimental results of a fluidized bed and with a numerical model of the same fluidized bed without using the CGM. The numerical model is one of a 3D cylindrical fluidized bed with 9.6M Geldart B-type particles in a bubbling regime.

Keywords: additive dissipative mechanism, coarse-graining, discrete element method, fluidized bed

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Authors: Ananya Mitra Pramanik, Anjali Agrawal

Abstract:

This paper traces the waste produced by the textile industry and evaluates the need for this waste to be reused or repurposed. From ancient times the textile industry has been a prominent part of all the economies of the world. It is famous for traditional as well as mill made fabrics. However the beauty and utility radiated by the textiles are juxtaposed by the piling amount of waste that the whole life cycle of a textile production and disposal entails. Waste happens in stages in a textile life cycle. It can be broadly categorised as pre-consumer and post-consumer waste. This research suggests suitable processes and techniques for channelizing post-industrial waste. It explores the scope of textile waste as a raw material for innovation and design. It discusses the role of designers in using waste to create useful and appealing designs. The paper examines the need of designers to create novel ideas to reuse textiles. This paper is based on secondary research. Most of the information used is taken from books and journals. The DEFRA report 2009 is also consulted for comprehensive data on textile waste percentage.

Keywords: designers, repurposing, textiles, waste

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Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

Abstract:

Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

Procedia PDF Downloads 219