Search results for: real output

Authors: Rihab Hamdi, Amel Hadri Hamida, Fatiha Khelili, Sakina Zerouali, Ouafae Bennis

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This paper features a comparative study performance of sliding mode controller (SMC) for closed-loop voltage control of direct current to direct current (DC-DC) three-cells buck converter connected in parallel, operating in continuous conduction mode (CCM), based on pulse-width modulation (PWM) with SMC based on hysteresis modulation (HM) where an adaptive feedforward technique is adopted. On one hand, for the PWM-based SM, the approach is to incorporate a fixed-frequency PWM scheme which is effectively a variant of SM control. On the other hand, for the HM-based SM, oncoming an adaptive feedforward control that makes the hysteresis band variable in the hysteresis modulator of the SM controller in the aim to restrict the switching frequency variation in the case of any change of the line input voltage or output load variation are introduced. The results obtained under load change, input change and reference change clearly demonstrates a similar dynamic response of both proposed techniques, their effectiveness is fast and smooth tracking of the desired output voltage. The PWM-based SM technique has greatly improved the dynamic behavior with a bit advantageous compared to the HM-based SM technique, as well as provide stability in any operating conditions. Simulation studies in MATLAB/Simulink environment have been performed to verify the concept.

Keywords: DC-DC converter, hysteresis modulation, parallel multi-cells converter, pulse-width modulation, robustness, sliding mode control

Procedia PDF Downloads 167

Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

Procedia PDF Downloads 228

Authors: Afef Dridi, Salah Mezlini

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Since experimental devices cannot calculate stress and deformation of complex structures. The Finite Element Method FEM has been widely used in several fields of research. One of these fields is orthodontics. The advantage of using such a method is the use of an accurate and non invasive method that allows us to have a sufficient data about the physiological reactions can happening in soft tissues. Most of researches done in this field were interested in the study of stresses and deformations induced by orthodontic apparatus in soft tissues (alveolar tissues). Only few studies were interested in the distribution of stress and strain in the orthodontic brackets. These studies, although they tried to be as close as possible to real conditions, their models did not reproduce the clinical cases. For this reason, the model generated by our research is the closest one to reality. In this study, a numerical model was developed to explore the stress and strain distribution under the application of real conditions. A comparison between different material properties was also done.

Keywords: visco-hyperelasticity, FEM, orthodontic treatment, inverse method

Procedia PDF Downloads 259

Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

Procedia PDF Downloads 87

Authors: A. B. M. Rezaul Islam, Ernur Karadogan

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Shape memory alloys (SMAs) are known for their shape memory effect and pseudoelasticity behavior. Their thermomechanical behaviors are modeled by numerous researchers using microscopic thermodynamic and macroscopic phenomenological point of view. Tanaka, Liang-Rogers and Ivshin-Pence models are some of the most popular SMA macroscopic phenomenological constitutive models. They describe SMA behavior in terms of stress, strain and temperature. These models involve material parameters and they have associated uncertainty present in them. At different operating temperatures, the uncertainty propagates to the output when the material is subjected to loading followed by unloading. The propagation of uncertainty while utilizing these models in real-life application can result in performance discrepancies or failure at extreme conditions. To resolve this, we used probabilistic approach to perform the sensitivity and uncertainty analysis of Tanaka, Liang-Rogers, and Ivshin-Pence models. Sobol and extended Fourier Amplitude Sensitivity Testing (eFAST) methods have been used to perform the sensitivity analysis for simulated isothermal loading/unloading at various operating temperatures. As per the results, it is evident that the models vary due to the change in operating temperature and loading condition. The average and stress-dependent sensitivity indices present the most significant parameters at several temperatures. This work highlights the sensitivity and uncertainty analysis results and shows comparison of them at different temperatures and loading conditions for all these models. The analysis presented will aid in designing engineering applications by eliminating the probability of model failure due to the uncertainty in the input parameters. Thus, it is recommended to have a proper understanding of sensitive parameters and the uncertainty propagation at several operating temperatures and loading conditions as per Tanaka, Liang-Rogers, and Ivshin-Pence model.

Keywords: constitutive models, FAST sensitivity analysis, sensitivity analysis, sobol, shape memory alloy, uncertainty analysis

Procedia PDF Downloads 144

Authors: Shanshan Zhu, Mohammad Nasim

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Financial fraud continues to be a major threat to financial institutions across the world, causing colossal money losses and undermining public trust. Fraud prevention techniques, based on hard rules, have become ineffective due to evolving patterns of fraud in recent times. Against such a background, the present study probes into distinct methodologies that exploit emergent AI-driven techniques to further strengthen fraud detection. We would like to compare the performance of generative adversarial networks and graph neural networks with other popular techniques, like gradient boosting, random forests, and neural networks. To this end, we would recommend integrating all these state-of-the-art models into one robust, flexible, and smart system for real-time anomaly and fraud detection. To overcome the challenge, we designed synthetic data and then conducted pattern recognition and unsupervised and supervised learning analyses on the transaction data to identify which activities were fishy. With the use of actual financial statistics, we compare the performance of our model in accuracy, speed, and adaptability versus conventional models. The results of this study illustrate a strong signal and need to integrate state-of-the-art, AI-driven fraud detection solutions into frameworks that are highly relevant to the financial domain. It alerts one to the great urgency that banks and related financial institutions must rapidly implement these most advanced technologies to continue to have a high level of security.

Keywords: AI-driven fraud detection, financial security, machine learning, anomaly detection, real-time fraud detection

Procedia PDF Downloads 42

Authors: Shorena Pharjiani

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The Present empirical paper investigates the relationship between FDI and economic growth by 10 selected industries in 10 Central and Eastern European countries from the period 1995 to 2012. Different estimation approaches were used to explore the connection between FDI and economic growth, for example OLS, RE, FE with and without time dummies. Obtained empirical results leads to some main consequences: First, the Central and East European countries (CEEC) attracted foreign direct investment, which raised the productivity of industries they entered in. It should be concluded that the linkage between FDI and output growth by industries is positive and significant enough to suggest that foreign firm’s participation enhanced the productivity of the industries they occupied. There had been an endogeneity problem in the regression and fixed effects estimation approach was used which partially corrected the regression analysis in order to make the results less biased. Second, it should be stressed that the results show that time has an important role in making FDI operational for enhancing output growth by industries via total factor productivity. Third, R&D positively affected economic growth and at the same time, it should take some time for research and development to influence economic growth. Fourth, the general trends masked crucial differences at the country level: over the last 20 years, the analysis of the tables and figures at the country level show that the main recipients of FDI of the 11 Central and Eastern European countries were Hungary, Poland and the Czech Republic. The main reason was that these countries had more open door policies for attracting the FDI. Fifth, according to the graphical analysis, while Hungary had the highest FDI inflow in this region, it was not reflected in the GDP growth as much as in other Central and Eastern European countries.

Keywords: central and East European countries (CEEC), economic growth, FDI, panel data

Procedia PDF Downloads 237

Authors: Dawoon Choi, Jian Li, Yunhyun Cho

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Axial Flux Permanent Magnet (AFPM) machines have been widely used in various applications due to their important merits, such as compact structure, high efficiency and high torque density. This paper presents one of the most important characteristics in the design process of the AFPM device, which is a recent issue. To design AFPM machine, the predicting electromagnetic forces between the permanent magnets and stator is important. Because of the magnitude of electromagnetic force affects many characteristics such as machine size, noise, vibration, and quality of output power. Theoretically, this force is canceled by the equilibrium of force when it is in the middle of the gap, but it is inevitable to deviate due to manufacturing problems in actual machine. Such as large scale wind generator, because of the huge attractive force between rotor and stator disks, this is more serious in getting large power applications such as large. This paper represents the characteristics of Double-Stator Inner –Rotor AFPM machines when it has rotor eccentricity. And, unbalanced air-gap and inclined air-gap condition which is caused by rotor offset and tilt in a double-stator single inner-rotor AFPM machine are each studied in electromagnetic and mechanical aspects. The output voltage and cogging torque under un-normal air-gap condition of AF machines are firstly calculated using a combined analytical and numerical methods, followed by a structure analysis to study the effect to mechanical stress, deformation and bending forces on bearings. Results and conclusions given in this paper are instructive for the successful development of AFPM machines.

Keywords: axial flux permanent magnet machine, inclined air gap, unbalanced air gap, rotor eccentricity

Procedia PDF Downloads 219

Authors: Shaikh Farhad Hossain, Liakot Ali

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Technology advances accelerate the quality and type of services provided for health care and especially for monitoring health conditions. Sensors have turned out to be more effective to detect diverse physiological signs and can be worn on the human body utilizing remote correspondence modules. An assortment of programming devices have been created to help in preparing a difference rundown of essential signs by examining and envisioning information produced by different sensors. In this proposition, we presented a Health signs and Activity acknowledgment monitoring system. Utilizing off-the-rack sensors, we executed a movement location system for identifying five sorts of action: falling, lying down, sitting, standing, and walking. The framework collects and analyzes sensory data in real-time, and provides different feedback to the users. In addition, it can generate alerts based on the detected events and store the data collected to a medical server.

Keywords: ADL, SVM, TRIL , MEMS

Procedia PDF Downloads 398

Authors: Joanne F. Hayek

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This study explores the use of gamification to promote citizen e-participation in urban planning. The research departs from a case study: the ‘Shape Your City’ web app designed and programmed by the author and presented as part of the 2021 Dubai Design Week to engage citizens in the co-creation of the future of their city through a gamified experience. The paper documents the design and development methodology of the web app and concludes with the findings of its pilot release. The case study explores the use of mobile interactive mapping, real-time data visualization, augmented reality, and machine learning as tools to enable co-planning. The paper also details the user interface design strategies employed to integrate complex cross-sector e-planning systems and make them accessible to citizens.

Keywords: gamification, co-planning, citizen e-participation, mobile interactive mapping, real-time data visualization

Procedia PDF Downloads 141

Authors: R. Nagarani

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An intrinsic property of software in a real-world environment is its need to evolve, which is usually accompanied by the increase of software complexity and deterioration of software quality, making software maintenance a tough problem. Refactoring is regarded as an effective way to address this problem. Many refactoring approaches at the method and class level have been proposed. But the extent of research on software refactoring at the package level is less. This work presents a novel approach to refactor the package structures of object oriented software using genetic algorithm based community detection. It uses software networks to represent classes and their dependencies. It uses a constrained community detection algorithm to obtain the optimized community structures in software networks, which also correspond to the optimized package structures. It finally provides a list of classes as refactoring candidates by comparing the optimized package structures with the real package structures.

Keywords: community detection, complex network, genetic algorithm, package, refactoring

Procedia PDF Downloads 418

Authors: Udayan Patankar, Shashwati Bhagat, Vilas Nitneware, Ants Koel

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An ISM band power amplifier is a type of electronic amplifier used to convert a low-power radio-frequency signal into a larger signal of significant power, typically used for driving the antenna of a transmitter. Due to drastic changes in telecommunication generations may lead to the requirements of improvements. Rapid changes in communication lead to the wide implementation of WLAN technology for its excellent characteristics, such as high transmission speed, long communication distance, and high reliability. Many applications such as WLAN, Bluetooth, and ZigBee, etc. were evolved with 2.4GHz to 5 GHz ISM Band, in which the power amplifier (PA) is a key building block of RF transmitters. There are many manufacturing processes available to manufacture a power amplifier for desired power output, but the major problem they have faced is about the power it consumed for its proper working, as many of them are fabricated on the GaN HEMT, Bi COMS process. In this paper we present a CMOS Base two stage cascode design of power amplifier working on 2.4GHz ISM frequency band. To lower the costs and allow full integration of a complete System-on-Chip (SoC) we have chosen 0.13µm low power CMOS technology for design. While designing a power amplifier, it is a real task to achieve higher power efficiency with minimum resources. This design showcase the Multi biased Cascode methodology to implement a two-stage CMOS power amplifier using ADS and LTSpice simulating tool. Main source is maximum of 2.4V which is internally distributed into different biasing point VB driving and VB driven as required for distinct stages of two stage RF power amplifier. It shows maximum power added efficiency near about 70.195% whereas its Power added efficiency calculated at 1 dB compression point is 44.669 %. Biased MOSFET is used to reduce total dc current as this circuit is designed for different wireless applications comes under 2.4GHz ISM Band.

Keywords: RFIC, PAE, RF CMOS, impedance matching

Procedia PDF Downloads 224

Authors: Jasim Uddin, Rod Smith, Malcolm Gillies

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Surface irrigation is the most popular irrigation method all over the world. However, two issues: low efficiency and huge labour involvement concern irrigators due to scarcity in recent years. To address these issues, a smart automated furrow is conceptualised that can be operated using digital devices like smartphone, iPad or computer and a preliminary evaluation was conducted in this study. The smart automated system is the integration of commercially available software and hardware. It includes real-time surface irrigation optimisation software (SISCO) and Rubicon Water’s surface irrigation automation hardware and software. The automated system consists of automatic water delivery system with 300 mm flexible pipes attached to both sides of a remotely controlled valve to operate the irrigation. A water level sensor to obtain the real-time inflow rate from the measured head in the channel, advance sensors to measure the advance time to particular points of an irrigated field, a solar-powered telemetry system including a base station to communicate all the field sensors with the main server. On the basis of field data, the software (SISCO) is optimised the ongoing irrigation and determine the optimum cut-off for particular irrigation and send this information to the control valve to stop the irrigation in a particular (cut-off) time. The preliminary evaluation shows that the automated surface irrigation worked reasonably well without manual intervention. The evaluation of farmers managed irrigation events show the potentials to save a significant amount of water and labour. A substantial amount of economic and social benefits are expected in rural industries by adopting this system. The future outcome of this work would be a fully tested commercial adaptive real-time furrow irrigation system able to compete with the pressurised alternative of centre pivot or lateral move machines on capital cost, water and labour savings but without the massive energy costs.

Keywords: furrow irrigation, smart automation, infiltration, SISCO, real-time irrigation, adoptive control

Procedia PDF Downloads 452

Authors: T. Bouchabchoub, A. Bendahmane, A. Haouriqui, N. Attou

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This paper presents simulation results of Forex predicting model equations in order to give approximately a prevision of interest rates. First, Hall-Taylor (HT) equations have been used with Taylor rule (TR) to adapt them to European and American Forex Markets. Indeed, initial Taylor Rule equation is conceived for all Forex transactions in every States: It includes only one equation and six parameters. Here, the model has been used with Hall-Taylor equations, initially including twelve equations which have been reduced to only three equations. Analysis has been developed on the following base macroeconomic variables: Real change rate, investment wages, anticipated inflation, realized inflation, real production, interest rates, gap production and potential production. This model has been used to specifically study the impact of an inflation shock on macroeconomic director interest rates.

Keywords: interest rate, Forex, Taylor rule, production, European Central Bank (ECB), Federal Reserve System (FED).

Procedia PDF Downloads 527

Authors: Alex B. Cusick

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The objective of this study is to improve upon the current ²³⁸PuO₂ fuel technology for space and defense applications. Modern RTGs (radioisotope thermoelectric generators) utilize the heat generated from the radioactive decay of ²³⁸Pu to create heat and electricity for long term and remote missions. Application of RTG technology is limited by the scarcity and expense of producing the isotope, as well as the power output which is limited to only a few hundred watts. The scarcity and expense make the efficient use of ²³⁸Pu absolutely necessary. By utilizing the decay of ²³⁸Pu, not only to produce heat directly but to also indirectly induce fission in ²³⁹Pu (which is already present within currently used fuel), it is possible to see large increases in temperature which allows for a more efficient conversion to electricity and a higher power-to-weight ratio. This concept can reduce the quantity of ²³⁸Pu necessary for these missions, potentially saving millions on investment, while yielding higher power output. Current work investigating radioisotope power systems have focused on improving efficiency of the thermoelectric components and replacing systems which produce heat by virtue of natural decay with fission reactors. The technical feasibility of utilizing (α,n) reactions to induce fission within current radioisotopic fuels has not been investigated in any appreciable detail, and our study aims to thoroughly investigate the performance of many such designs, develop those with highest capabilities, and facilitate experimental testing of these designs. In order to determine the specific design parameters that maximize power output and the efficient use of ²³⁸Pu for future RTG units, MCNP6 simulations have been used to characterize the effects of modifying fuel composition, geometry, and porosity, as well as introducing neutron moderating, reflecting, and shielding materials to the system. Although this project is currently in the preliminary stages, the final deliverables will include sophisticated designs and simulation models that define all characteristics of multiple novel RTG fuels, detailed enough to allow immediate fabrication and testing. Preliminary work has consisted of developing a benchmark model to accurately represent the ²³⁸PuO₂ pellets currently in use by NASA; this model utilizes the alpha transport capabilities of MCNP6 and agrees well with experimental data. In addition, several models have been developed by varying specific parameters to investigate their effect on (α,n) and (n,fi ssion) reaction rates. Current practices in fuel processing are to exchange out the small portion of naturally occurring ¹⁸O and ¹⁷O to limit (α,n) reactions and avoid unnecessary neutron production. However, we have shown that enriching the oxide in ¹⁸O introduces a sufficient (α,n) reaction rate to support significant fission rates. For example, subcritical fission rates above 10⁸ f/cm³-s are easily achievable in cylindrical ²³⁸PuO₂ fuel pellets with a ¹⁸O enrichment of 100%, given an increase in size and a ⁹Be clad. Many viable designs exist and our intent is to discuss current results and future endeavors on this project.

Keywords: radioisotope thermoelectric generators (RTG), Pu-238, subcritical reactors, (alpha, n) reactions

Procedia PDF Downloads 171

Authors: Biruhi Tesfaye, Avinash M. Potdar

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The laboratory test process to determine the California bearing ratio (CBR) of black cotton soils is not only overpriced but also time-consuming as well. Hence advanced prediction of CBR plays a significant role as it is applicable In pavement design. The prediction of CBR of treated soil was executed by Artificial Neural Networks (ANNs) which is a Computational tool based on the properties of the biological neural system. To observe CBR values, combined eggshell and waste glass was added to soil as 4, 8, 12, and 16 % of the weights of the soil samples. Accordingly, the laboratory related tests were conducted to get the required best model. The maximum CBR value found at 5.8 at 8 % of eggshell waste glass powder addition. The model was developed using CBR as an output layer variable. CBR was considered as a function of the joint effect of liquid limit, plastic limit, and plastic index, optimum moisture content and maximum dry density. The best model that has been found was ANN with 5, 6 and 1 neurons in the input, hidden and output layer correspondingly. The performance of selected ANN has been 0.99996, 4.44E-05, 0.00353 and 0.0067 which are correlation coefficient (R), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE) respectively. The research presented or summarized above throws light on future scope on stabilization with waste glass combined with different percentages of eggshell that leads to the economical design of CBR acceptable to pavement sub-base or base, as desired.

Keywords: CBR, artificial neural network, liquid limit, plastic limit, maximum dry density, OMC

Procedia PDF Downloads 191

Authors: Ann D. Christy, Beenish Saba

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The Microbial fuel Cell (MFC) is a successful integrated technology for power production and wastewater treatment. MFCs are recognized for their dual function, but research in this field is still ongoing to increase efficiency and power output. One such effort is successful integration of phototrophic and autotrophic microorganisms to create bacterio-algal MFCs for sustainable electricity production along with wastewater treatment and algal biomass production. An MFC is typically configured with an anaerobic anodic chamber containing exoelectrogenic microorganisms separated by a cation exchange membrane from an adjacent aerobic cathodic chamber. The two electrodes are connected by an external circuit. This conventional MFC can be converted into a phototrophic MFC by introducing photosynthetic microorganisms into the cathode chamber. This study examines adding a third desalination chamber to a two-chamber bacterio-algal MFC. Successful results have been observed from these three-chamber MFCs demonstrating wastewater treatment in the anodic chamber, phototrophic algal growth in the cathodic chamber, and desalination in the middle chamber. The present article will summarize successful results of the bacterio-algal fuel cells and offer insights about the mechanisms involved. Tables summarizing the input substrate along with optimized operational conditions and output performance in terms of power production and efficiencies of water and wastewater treatment will be presented. The negative impacts and challenges will be discussed, along with possible future research directions. Results suggest that the three chamber bacterio-algal desalination cell has potential as a feasible technology for power production, wastewater treatment and desalination, but it needs further investigation under optimized conditions.

Keywords: bacterio-algal MFC, three chamber, microbial fuel cell, wastewater treatment and desalination

Procedia PDF Downloads 362

Authors: Josef Slapal

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Digital images are approximations of real ones and, therefore, to be able to study them, we need the digital plane Z2 to be equipped with a convenient structure that behaves analogously to the Euclidean topology on the real plane. In particular, it is required that such a structure allows for a digital analogue of the Jordan curve theorem. We introduce certain adjacency graphs on the digital plane and prove digital Jordan curves for them thus showing that the graphs provide convenient structures on Z2 for the study and processing of digital images. Further convenient structures including the wellknown Khalimsky and Marcus-Wyse adjacency graphs may be obtained as quotients of the graphs introduced. Since digital Jordan curves represent borders of objects in digital images, the adjacency graphs discussed may be used as background structures on the digital plane for solving the problems of digital image processing that are closely related to borders like border detection, contour filling, pattern recognition, thinning, etc.

Keywords: digital plane, adjacency graph, Jordan curve, quotient adjacency

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Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

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A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

Procedia PDF Downloads 156

Authors: Hong Zhang

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The main purpose of this study is to show that machine translation (MT) post-editing (PE) training can help our Chinese students learn Spanish as a second language. Our hypothesis is that they might make better use of it by learning PE skills specific for foreign language learning. We have developed PE training materials based on the data collected in a previous study. Training material included the special error types of the output of MT and the error types that our Chinese students studying Spanish could not detect in the experiment last year. This year we performed a pilot study in order to evaluate the PE training materials effectiveness and to what extent PE training helps Chinese students who study the Spanish language. We used screen recording to record these moments and made note of every action done by the students. Participants were speakers of Chinese with intermediate knowledge of Spanish. They were divided into two groups: Group A performed PE training and Group B did not. We prepared a Chinese text for both groups, and participants translated it by themselves (human translation), and then used Google Translate to translate the text and asked them to post-edit the raw MT output. Comparing the results of PE test, Group A could identify and correct the errors faster than Group B students, Group A did especially better in omission, word order, part of speech, terminology, mistranslation, official names, and formal register. From the results of this study, we can see that PE training can help Chinese students learn Spanish as a second language. In the future, we could focus on the students’ struggles during their Spanish studies and complete the PE training materials to teach Chinese students learning Spanish with machine translation.

Keywords: machine translation, post-editing, post-editing training, Chinese, Spanish, foreign language learning

Procedia PDF Downloads 144

Authors: Mohammadreza Aghasadeghi, Mojtaba Hamidi-Fard, Seyed Amir Sadeghi, Ashkan Noorbakhsh

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Introduction: HIV is known as one of the most important pathogens and mortality in all human societies, but unfortunately, no definitive cure has been found for it. Due to its weakened immune system, this virus causes a variety of primary and secondary opportunistic infections. Cytomegalovirus (CMV) is one of the most relevant opportunistic viruses seen in HIV-positive people that cause various infections in HIV-positive people. This virus causes various infections in HIV-positive people, such as retinal infection (CMVR), gastrointestinal infections, diarrhea, severe weight loss, and cerebrospinal fluid problems. These various infections make it important to evaluate the prevalence of CMV in HIV-positive people to diagnose it quickly and in a timely manner. This infection in HIV-positive people reduces life expectancy and causes serious harm to patients. However, a simple test in HIV-positive people can prevent the virus from progressing. Material and Methods: In this study, we collected 200 blood samples (including 147 men and 53 women) from HIV-positive individuals and examined the frequency of CMV-DNA in these cases by real-time PCR method. In the next step, the data was analyzed by SPSS software, and then we obtained the relationship between age, sex, and the frequency of CMV in HIV-positive individuals. Results: The total frequency of CMV DNA was about 59%, which is a relatively high prevalence due to the age range of the subjects. The frequency in men was 61.2% and 52.8% in women. This frequency was also higher in males than females. We also observed more frequency in two age groups of 16 to 30 years and 31 to 45 years. Discussion: Due to the high prevalence of CMV in HIV-positive individuals and causing serious problems in this group of people, this study was shown that both the patients and the community should pay more attention to this issue. Ministry of Health, as a stakeholder organization, can make CMV DNA testing mandatory as soon as a person is HIV positive.

Keywords: CMV, HIV, AIDS, real-time PCR, SPSS

Procedia PDF Downloads 213

Authors: E. T. El Shenawy, O. N. A. Esmail, Adel A. Elbaset, Hesham F. A. Hamed

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Generation of the electrical energy based on photovoltaic (PV) technology has been increased over the world due to either the continuous reduction in the traditional energy sources in addition to the pollution problems related to their usage, or the clean nature and safe usage of the PV technology. Also, PV systems can generate clean electricity in the site of use without any transmission, which can be considered cost effective than other generation systems. The performance of the PV system is highly affected by the amount of solar radiation incident on it. Completely or partially shaded PV systems can affect its output. The PV system can be shaded by trees, buildings, dust, incorrect system configuration, or other obstacles. The present paper studies the effect of the partial shading on the performance of a thin film PV module under climatic conditions of Cairo, Egypt. This effect was measured and evaluated according to practical measurement of the characteristic curves such as current-voltage and power-voltage for two identical PV modules (with and without shading) placed at the same time on one mechanical structure for comparison. The measurements have been carried out for the following shading patterns; half cell (bottom, middle, and top of the PV module); complete cell; and two adjacent cells. The results showed that partially shading the PV module changes the shapes of the I-V and P-V curves and produces more than one maximum power point, that can disturb the traditional maximum power point trackers. Also, the output power from the module decreased according to the incomplete solar radiation reaching the PV module due to shadow patterns. The power loss due shading was 7%, 22%, and 41% for shading of half-cell, one cell, and two adjacent cells of the PV module, respectively.

Keywords: I-V measurements, PV module characteristics, PV module power loss, PV module shading

Procedia PDF Downloads 137

Authors: Siti Rafeah Md Rafei, Karen Wang Yanping, Park Mi Kyoung

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Tissue samples are precious supply for molecular studies or disease identification diagnosed using molecular assays, namely real-time PCR (qPCR). It is critical to establish the most favorable nucleic acid extraction that gives the PCR-amplifiable genomic DNA. Furthermore, automated nucleic acid extraction is an appealing alternative to labor-intensive manual methods. Operational complexity, defined as the number of steps required to obtain an extracted sample, is one of the criteria in the comparison. Here we are comparing the One BioMed’s automated X8 platform with the commercially available manual-operated kits from QIAGEN Mini Kit and Roche. We extracted DNA from rat fresh-frozen tissue (from different type of organs) in the matrices. After tissue pre-treatment, it is added to the One BioMed’s X8 pre-filled cartridge, and the QIAGEN QIAmp column respectively. We found that the results after subjecting the eluates to the Real Time PCR using BIORAD CFX are comparable.

Keywords: DNA extraction, frozen tissue, PCR, qPCR, rat

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Authors: Vaishali D. Khairnar

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The main aim is to provide lower-latency and highly reliable communication facilities for vehicles in the automobile industry; vehicle-to-everything (V2X) communication basically intends to increase expressway road security and its effectiveness. The Ultra-Reliable Low-Latency Communications (URLLC) algorithm and cellular networks are applied in combination with Mobile Broadband (MBB). This is particularly used in express way safety-based driving applications. Expressway vehicle drivers (humans) will communicate in V2X systems using the sixth-generation (6G) communication systems which have very high-speed mobility features. As a result, we need to determine how to ensure reliable and consistent wireless communication links and improve the quality to increase channel gain, which is becoming a challenge that needs to be addressed. To overcome this challenge, we proposed a unique multi-user scheduling algorithm for ultra-massive multiple-input multiple-output (MIMO) systems using 6G. In wideband wireless network access in case of high traffic and also in medium traffic conditions, moreover offering quality-of-service (QoS) to distinct service groups with synchronized contemporaneous traffic on the highway like the Mumbai-Pune expressway becomes a critical problem. Opportunist MAC (OMAC) is a way of proposing communication across a wireless communication link that can change in space and time and might overcome the above-mentioned challenge. Therefore, a multi-user scheduling algorithm is proposed for MIMO systems using a cross-layered MAC protocol to achieve URLLC and high reliability in V2X communication.

Keywords: ultra-reliable low latency communications, vehicle-to-everything communication, multiple-input multiple-output systems, multi-user scheduling algorithm

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Authors: Jiří. J. Urbánek, Hana Malachová, Josef Krahulec, Jitka Johanidisová

Abstract:

The paper deals with crisis situations investigation and modelling within the organizations of critical infrastructure. Every crisis situation has an origin in the emergency event occurrence in the organizations of energetic critical infrastructure especially. Here, the emergency events can be both the expected events, then crisis scenarios can be pre-prepared by pertinent organizational crisis management authorities towards their coping or the unexpected event (Black Swan effect) – without pre-prepared scenario, but it needs operational coping of crisis situations as well. The forms, characteristics, behaviour and utilization of crisis scenarios have various qualities, depending on real critical infrastructure organization prevention and training processes. An aim is always better organizational security and continuity obtainment. This paper objective is to find and investigate critical/ crisis zones and functions in critical situations models of critical infrastructure organization. The DYVELOP (Dynamic Vector Logistics of Processes) method is able to identify problematic critical zones and functions, displaying critical interfaces among actors of crisis situations on the DYVELOP maps named Blazons. Firstly, for realization of this ability is necessary to derive and create identification algorithm of critical interfaces. The locations of critical interfaces are the flags of crisis situation in real organization of critical infrastructure. Conclusive, the model of critical interface will be displayed at real organization of Czech energetic crisis infrastructure subject in Black Out peril environment. The Blazons need live power Point presentation for better comprehension of this paper mission.

Keywords: algorithm, crisis, DYVELOP, infrastructure

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Authors: Deon de Jager, Yahya Zweiri, Dimitrios Makris

Abstract:

The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.

Keywords: cognitive robotics, semantic memory, episodic memory, maximum entropy principle, particle swarm optimization

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Authors: M. Brandt, A. Peniak, J. Makarovič, P. Rafajdus

Abstract:

This paper deals with a novel approach of power transformers diagnostics. This approach identifies the exact location and the range of a fault in the transformer and helps to reduce operation costs related to handling of the faulty transformer, its disassembly and repair. The advantage of the approach is a possibility to simulate healthy transformer and also all faults, which can occur in transformer during its operation without its disassembling, which is very expensive in practice. The approach is based on creating frequency dependent impedance of the transformer by sweep frequency response analysis measurements and by 3D FE parametrical modeling of the fault in the transformer. The parameters of the 3D FE model are the position and the range of the axial short circuit. Then, by comparing the frequency dependent impedances of the parametrical models with the measured ones, the location and the range of the fault is identified. The approach was tested on a real transformer and showed high coincidence between the real fault and the simulated one.

Keywords: transformer, parametrical model of transformer, fault, sweep frequency response analysis, finite element method

Procedia PDF Downloads 483

Authors: Yifan Gao

Abstract:

Owing to the high breakdown field, high saturation drift velocity, 2DEG with high density and mobility and so on, AlGaN/GaN HEMTs have been widely used in high-frequency and high-power applications. To acquire a higher power often means higher breakdown voltage and higher drain current. Surface leakage current is usually the key issue affecting the breakdown voltage and power performance. In this work, we have performed in-situ N₂/NH₃ pretreatment before the passivation to suppress the surface leakage and achieve device performance enhancement. The AlGaN/GaN HEMT used in this work was grown on a 3-in. SiC substrate, whose epitaxial structure consists of a 3.5-nm GaN cap layer, a 25-nm Al₀.₂₅GaN barrier layer, a 1-nm AlN layer, a 400-nm i-GaN layer and a buffer layer. In order to analyze the mechanism for the N-based pretreatment, the details are measured by XPS analysis. It is found that the intensity of Ga-O bonds is decreasing and the intensity of Ga-N bonds is increasing, which means with the supplement of N, the dangling bonds on the surface are indeed reduced with the forming of Ga-N bonds, reducing the surface states. The surface states have a great influence on the leakage current, and improved surface states represent a better off-state of the device. After the N-based pretreatment, the breakdown voltage of the device with Lₛ𝒹=6 μm increased from 93V to 170V, which increased by 82.8%. Moreover, for HEMTs with Lₛ𝒹 of 6-μm, we can obtain a peak output power (Pout) of 12.79W/mm, power added efficiency (PAE) of 49.84% and a linear gain of 20.2 dB at 60V under 3.6GHz. Comparing the result with the reference 6-μm device, Pout is increased by 16.5%. Meanwhile, PAE and the linear gain also have a slight increase. The experimental results indicate that using N₂/NH₃ pretreatment before passivation is an attractive approach to achieving power performance enhancement.

Keywords: AlGaN/GaN HEMT, N-based pretreatment, output power, passivation

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Authors: Aniket Tiwari, Ameya London

Abstract:

Web-based student attendance management system is required to assist the faculty and the lecturer for the time-consuming process. For this purpose, GSM/GPRS (Global System for Mobile Communication/General Packet Radio Service) based student’s attendance management system using RFID (Radio Frequency Identification) is a much convenient method to take the attendance. Student is provided with the RFID tags. When student comes near to the reader, it will sense the respective student and update attendance. The whole process is controlled using the microcontroller. The main advantage of this system is that it reduced the complexity comparison to student attendance system using RF technology. This system requires only one microcontroller for the operation, it is real time process. This paper reviews some of these monitoring systems and proposes a GPRS based student attendance system. The system can be easily accessed by the lecturers via the web and most importantly, the reports can be generated in real-time processing, thus, provides valuable information about the students’ commitments in attending the classes.

Keywords: RFID reader, RFID tags, student, attendance

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Authors: Yingxu Wang, Jianhua Lu, Jun Peng, Jiawei Zhang

Abstract:

The fundamental demand in contemporary intelligent science towards Autonomous AI (AI*) is the creation of unprecedented formal means of Intelligent Mathematics (IM). It is discovered that natural intelligence is inductively created rather than exhaustively trained. Therefore, IM is a family of algebraic and denotational mathematics encompassing Inference Algebra, Real-Time Process Algebra, Concept Algebra, Semantic Algebra, Visual Frame Algebra, etc., developed in our labs. IM plays indispensable roles in training-free AI* theories and systems beyond traditional empirical data-driven technologies. A set of applications of IM-driven AI* systems will be demonstrated in contemporary intelligence science, AI*, and cognitive computers.

Keywords: intelligence mathematics, foundations of intelligent science, autonomous AI, cognitive computers, inference algebra, real-time process algebra, concept algebra, semantic algebra, applications

Procedia PDF Downloads 61