Search results for: rule based systems

Authors: Mohammad Reza Ebrahimi

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In new restructured power systems, swift fault detection is very important. The parallel transmission-lines are vastly used in this kind of power systems because of high amount of energy transferring. In this paper, a method based on the comparison of two schemes, i.e., i) maximum magnitude of travelling-wave (TW) energy ii) the instants of maximum energy occurrence at the circuits of parallel transmission-line is proposed. Using the travelling-wave of fault in order to faulted line identification this method has noticeable operation time. Moreover, the algorithm can cover for identification of faults as external or internal faults. For an internal fault, the exact location of the fault can be estimated confidently. A lot of simulations have been done with PSCAD/EMTDC to verify the performance of the proposed algorithm.

Keywords: travelling-wave, maximum energy, parallel transmission-line, fault location

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks

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Authors: Johannes Atug, Andreas Radke, Mitchell Tseng, Gunther Reinhart

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In modern supply chains, large numbers of SKU (Stock-Keeping-Unit) need to be timely managed, and any delays in noticing disruptions of items often limit the ability to defer the impact on customer order fulfillment. However, in supply chains of IoT-connected enterprises, the ERP (Enterprise-Resource-Planning), the MES (Manufacturing-Execution-System) and the SCADA (Supervisory-Control-and-Data-Acquisition) systems generate large amounts of data, which generally glean much earlier notice of deviations in the business process steps. That is, analyzing these streams of data with process mining techniques allows the monitoring of the supply chain business processes and thus identification of items that deviate from the standard order fulfillment process. In this paper, a framework to enable event-based SCM (Supply-Chain-Management) processes including an overview of core enabling technologies are presented, which is based on the RAMI (Reference-Architecture-Model for Industrie 4.0) architecture. The application of this framework in the industry is presented, and implications for SCM in industry 4.0 and further research are outlined.

Keywords: cyber-physical production systems, event-based monitoring, supply chain management, RAMI (Reference-Architecture-Model for Industrie 4.0)

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Authors: Boris M. Popović, Tatjana Jurić, Bojana Blagojević, Denis Uka, Ružica Ždero Pavlović

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Green solvents are environmentally friendly and greatly improve the sustainability of chemical processes. There is a growing interest in the green extraction of polyphenols from fruits. In this study, we consider three Natural Deep Eutectic Solvents (NADES) systems based on choline chloride as a hydrogen bond acceptor and malic acid, urea, and fructose as hydrogen bond donors. NADES systems were prepared by heating and stirring, ultrasound, and microwave (MW) methods. Sour cherry pomace was used as a natural source of polyphenols. Polyphenol extraction from cherry pomace was performed by ultrasound-assisted extraction and microwave-assisted extraction and compared with conventional heat and stirring method extraction. It was found that MW-assisted preparation of NADES was the fastest, requiring less than 30 s. Also, MW extraction of polyphenols was the most rapid, with less than 5 min necessary for the extract preparation. All three NADES systems were highly efficient for anthocyanin extraction, but the most efficient was the system with malic acid as a hydrogen bond donor (yield of anthocyanin content was enhanced by 62.33% after MW extraction with NADES compared with the conventional solvent).

Keywords: anthocyanins, green extraction, NADES, polyphenols

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Authors: C. J. Rossouw, T. I. van Niekerk

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The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

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Authors: M. L. Anitha, K. A. Radhakrishna Rao

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With the advent of modern computing technology, there is an increased demand for developing recognition systems that have the capability of verifying the identity of individuals. Recognition systems are required by several civilian and commercial applications for providing access to secured resources. Traditional recognition systems which are based on physical identities are not sufficiently reliable to satisfy the security requirements due to the use of several advances of forgery and identity impersonation methods. Recognizing individuals based on his/her unique physiological characteristics known as biometric traits is a reliable technique, since these traits are not transferable and they cannot be stolen or lost. Since the performance of biometric based recognition system depends on the particular trait that is utilized, the present work proposes a fusion approach which combines Inner knuckle print (IKP) trait of the middle, ring and index fingers with the geometrical features of hand. The hand image captured from a digital camera is preprocessed to find finger IKP as region of interest (ROI) and hand geometry features. Geometrical features are represented as the distances between different key points and IKP features are extracted by applying local binary pattern descriptor on the IKP ROI. The decision level AND fusion was adopted, which has shown improvement in performance of the combined scheme. The proposed approach is tested on the database collected at our institute. Proposed approach is of significance since both hand geometry and IKP features can be extracted from the palm region of the hand. The fusion of these features yields a false acceptance rate of 0.75%, false rejection rate of 0.86% for verification tests conducted, which is less when compared to the results obtained using individual traits. The results obtained confirm the usefulness of proposed approach and suitability of the selected features for developing biometric based recognition system based on features from palmar region of hand.

Keywords: biometrics, hand geometry features, inner knuckle print, recognition

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Authors: Neda Navidi, Rene Jr. Landry

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Vehicle tracking and accident recognizing are considered by many industries like insurance and vehicle rental companies. The main goal of this paper is to detect the location of a car accident by combining different methods. The methods, which are considered in this paper, are Global Navigation Satellite Systems/Inertial Measurement Units (GNSS/IMU)-based navigation and vehicle accident detection algorithms. They are expressed by a set of raw measurements, which are obtained from a designed integrator black box using GNSS and inertial sensors. Another concern of this paper is the definition of accident detection algorithm based on its jerk to identify the position of that accident. In fact, the results convinced us that, even in GNSS blockage areas, the position of the accident could be detected by GNSS/INS integration with 50% improvement compared to GNSS stand alone.

Keywords: driver behavior monitoring, integration, IMU, GNSS, monitoring, tracking

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Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Amirhossein Eisapour, Mohammad Emamjome Kashan, Alan S. Fung

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This research addresses the pressing global challenges of clean energy and water supplies, emphasizing the need for sustainable solutions for the building sector. The research centers on integrating Reverse Osmosis (RO) systems with building energy systems, incorporating Solar Thermal Collectors (STC)/Photovoltaic Thermal (PVT), water-to-water heat pumps, and an Insulated Concrete Form (ICF) based building foundation wall thermal energy storage. The study explores an innovative configuration’s effectiveness in addressing water and heating demands through clean energy sources while addressing ICF-based thermal storage challenges, which could overheat in the cooling season. Analyzing four configurations—STC-ICF, STC-ICF-RO, PVT-ICF, and PVT-ICF-RO, the study conducts a sensitivity analysis on collector area (25% and 50% increase) and weather data (evaluating five Canadian cities, Winnipeg, Toronto, Edmonton, Halifax and Vancouver). Key outcomes highlight the benefits of integrated RO scenarios, showcasing reduced ICF wall temperature, diminished unwanted heat in the cooling season, reduced RO pump consumption and enhanced solar energy production. The STC-ICF-RO and PVT-ICF-RO systems achieved energy savings of 653 kWh and 131 kWh, respectively, in comparison to their non-integrated RO counterparts. Additionally, both systems successfully contributed to lowering the CO2 production level of the energy system. The calculated payback period of STC-ICF-RO (2 years) affirms the proposed systems’ economic viability. Compared to the base system, which does not benefit from the ICF and RO integration with the building energy system, the STC-ICF-RO and PVT-ICF-RO demonstrate a dramatic energy consumption reduction of 20% and 32%, respectively. The sensitivity analysis suggests potential system improvements under specific conditions, especially when implementing the introduced energy system in communities of buildings.

Keywords: insulated concrete form, thermal energy storage, reverse osmosis, building energy systems, solar thermal collector, photovoltaic thermal, heat pump

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Authors: Kanya L. Khatri, Ashfaque A. Memon, Rod J. Smith, Shamas Bilal

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The viability and sustainability of crop production is currently threatened by increasing water scarcity. Water scarcity problems can be addressed through improved water productivity and the options usually presumed in this context are efficient water use and conversion of surface irrigation to pressurized systems. By replacing furrow irrigation with drip or centre pivot systems, the water efficiency can be improved by up to 30 to 45%. However, the installation and application of pumps and pipes, and the associated fuels needed for these alternatives increase energy consumption and cause significant greenhouse gas emissions. Hence, a balance between the improvement in water use and the potential increase in energy consumption is required keeping in view adverse impact of increased carbon emissions on the environment. When surface water is used, pressurized systems increase energy consumption substantially, by between 65% to 75%, and produce greenhouse gas emissions around 1.75 times higher than that of gravity based irrigation. With gravity based surface irrigation methods the energy consumption is assumed to be negligible. This study has shown that a novel real-time infiltration model REIP has enabled implementation of real-time optimization and control of surface irrigation and surface irrigation with real-time optimization has potential to bring significant improvements in irrigation performance along with substantial water savings of 2.92 ML/ha which is almost equivalent to that given by pressurized systems. Thus real-time optimization and control offers a modern, environment friendly and water efficient system with close to zero increase in energy consumption and minimal greenhouse gas emissions.

Keywords: pressurised irrigation, carbon emissions, real-time, environmentally-friendly, REIP

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Authors: Aniketh Ravukutam, Rajath Rao M., Pradyumna S. A.

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In the past few decades there has been great advancement in use of aerodynamics in cars. Now its use has been evident from commercial cars to race cars for achieving higher speeds, stability and efficiency. This paper focusses on studying the effects of aerodynamics in Formula Student car. These cars weigh around 200kgs with an average speed of 60kmph. With increasing competition every year, developing a competitive car is a herculean task. The race track comprises mostly of tight corners and little or no straights thus testing the car’s cornering capabilities. Higher cornering speeds can be achieved by increasing traction at the tires. Studying the aerodynamics helps in achieving higher traction without much addition in overall weight of car. The main focus is to develop an aerodynamic package involving front wing, under tray and body to obtain an optimum value of down force. The initial process involves the detail study of geometrical constraints mentioned in the rule book and calculating the limiting value of drag as per the engine specifications. The successive steps involve conduction of various iterations in ANSYS for selection of airfoils, deciding the number of elements, designing the nose for low drag, channelizing the flow under the body and obtain an optimum value of down force within the limits defined in the initial process. The final step involves design of model using these results in Virtual environment called OptimumLap® for detailed study of performance with and without the presence of aerodynamics. The CFD analysis results showed an overall down force of 377.44N with a drag of 164.08N. The corresponding parameters of the last model were applied in OptimumLap® and an improvement of 3.5 seconds in lap times was observed.

Keywords: aerodynamics, formula student, traction, front wing, undertray, body, rule book, drag, down force, virtual environment, computational fluid dynamics (CFD)

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Authors: Javad Khazaei, Rick Blum

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Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: consensus tracking, distributed control, model-free control, sparse identification of dynamical systems

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Authors: P. Nafisi Poor, P. Javid

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Over the past few years, the idea of adaptive buildings and specifically, adaptive building energy management systems (ABEMS) has become popular. Well-performed management in terms of energy is to create a balance between energy consumption and user comfort; therefore, in new energy management models, efficient energy consumption is not the sole factor and the user's comfortability is also considered in the calculations. One of the main ways of measuring this factor is by analyzing user feedback on the conditions to understand whether they are satisfied with conditions or not. This paper provides a comprehensive review of recent approaches towards energy management systems based on users' feedbacks and subsequently performs a comparison between them premised upon their efficiency and accuracy to understand which approaches were more accurate and which ones resulted in a more efficient way of minimizing energy consumption while maintaining users' comfortability. It was concluded that the highest accuracy rate among the presented works was 95% accuracy in determining satisfaction and up to 51.08% energy savings can be achieved without disturbing user’s comfort. Considering the growing interest in designing and developing adaptive buildings, these studies can support diverse inquiries about this subject and can be used as a resource to support studies and researches towards efficient energy consumption while maintaining the comfortability of users.

Keywords: adaptive buildings, energy efficiency, intelligent buildings, user comfortability

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.

Keywords: deep learning, generative, knowledge, response generation, retrieval

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Authors: Mateusz Paszko, Miroslaw Wendeker, Adam Majczak

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High temperature waste energy offers a number of management options. The most common energy recuperation systems, that are actually used to utilize energy from the high temperature sources are steam turbines working in a high pressure and temperature closed cycles. Due to the high costs of production of energy recuperation systems, especially rotary turbine discs equipped with blades, currently used solutions are limited in use with waste energy sources of temperature below 100 °C. This study presents the results of simulating the flow of the water vapor in various configurations of flow ducts in a reaction steam turbine based on Hero’s steam turbine. The simulation was performed using a numerical model and the ANSYS Fluent software. Simulation computations were conducted with use of the water vapor as an internal agent powering the turbine, which is fully safe for an environment in case of a device failure. The conclusions resulting from the conducted numerical computations should allow for optimization of the flow ducts geometries, in order to achieve the greatest possible efficiency of the turbine. It is expected that the obtained results should be useful for further works related to the development of the final version of a low drag steam turbine dedicated for low cost energy recuperation systems.

Keywords: energy recuperation, CFD analysis, waste energy, steam turbine

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Authors: Abdulatif Abdulsalam, Mohamed Shaban

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This paper introduces interfacing and replication of electronic tools based on the MATLAB/ SIMULINK mock-up package. Mock-up components contain dc-dc converters, power issue rectifiers, motivation machines, dc gear, synchronous gear, and more entire systems. Power issue rectifier model includes solid state device models. The tools are the clear-cut structure and mock-up of complex energetic systems connecting with power electronic machines.

Keywords: power electronics, machine, MATLAB, simulink

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Authors: Lu Anne A. Godinez, May Claudine I. Gador, Preacious G. Gumolon, Louiechi Von R. Mendoza, Neil Bryan N. Moninio

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Gender equality and women empowerment is the third of eight Millennium Development Goals. Understanding corruption’s linkages to gender equality issues and how it impacts women’s empowerment is part of the broader process of advancing women’s rights and understanding the gender dimensions of democratic governance. Taking a long view of political (corruption index) and the social (women empowerment) dimension — a view from 2015 to 2030, a context based forecast was conducted to forecast the ASEAN corruption index in the next 15 years, answering the question: “Does women political involvement decrease corruption rate index of ASEAN countries in the next 15 years?” The study have established that there will be an increase women political involvement in the ASEAN countries in the next 15 years that will cause a drop on corruption rate index. There will be a significant decline on corruption rate index in 2030. This change entails reform not only in the political aspect of progress, but to the social aspect as well. Finally, the political aspect is increasing at a constant rate however a double or triple increase of the social aspect is seen to be the key solution for corruption.

Keywords: women, women political involvement, corruption, gender equity index, economic participation, educational attainment, political empowerment, control of corruption, regulatory quality, rule of law, voice and accountability government effectiveness, political stability and corruption perception index

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Authors: Chukwuka E. V., Rowling J. K., Rushdie Salman

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The field of electronic engineering encompasses the study and application of electrical systems, circuits, and devices. Engineers in this discipline design, analyze and optimize electronic components to develop innovative solutions for various industries. This abstract provides a brief overview of the diverse areas within electronic engineering, including analog and digital electronics, signal processing, communication systems, and embedded systems. It highlights the importance of staying abreast of advancements in technology and fostering interdisciplinary collaboration to address contemporary challenges in this rapidly evolving field.

Keywords: smart home engineering, energy efficiency, user-centric design, security frameworks

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Authors: Arellano Karina, Diego Avila-Pesántez, Leticia Vaca-Cárdenas, Alberto Arellano, Carmen Mantilla

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Nowadays, security threats in Voice over IP (VoIP) systems are an essential and latent concern for people in charge of security in a corporate network, because, every day, new Denial-of-Service (DoS) attacks are developed. These affect the business continuity of an organization, regarding confidentiality, availability, and integrity of services, causing frequent losses of both information and money. The purpose of this study is to establish the necessary measures to mitigate DoS threats, which affect the availability of VoIP systems, based on the Session Initiation Protocol (SIP). A Security Model called MS-DoS-SIP is proposed, which is based on two approaches. The first one analyzes the recommendations of international security standards. The second approach takes into account weaknesses and threats. The implementation of this model in a VoIP simulated system allowed to minimize the present vulnerabilities in 92% and increase the availability time of the VoIP service into an organization.

Keywords: Denial-of-Service SIP attacks, MS-DoS-SIP, security model, VoIP-SIP vulnerabilities

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Authors: Mohamed Belhorma, Aboubakar S. Bouchikhi, Belkacem Bounab

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This paper addresses modeling a Double A-Arm suspension, a three-dimensional nonlinear model has been developed using the multibody systems formalism. Dynamical study of the different components responses was done, particularly for the wheel assembly. To validate those results, the system was constructed and simulated by RecurDyn, a professional multibody dynamics simulation software. The model has been used as the Objectif function in an optimization algorithm for ride quality improvement.

Keywords: double A-Arm suspension, multibody systems, ride quality optimization, dynamic simulation

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Authors: A. Rong, P. B. Luh, R. Lahdelma

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High penetration of intermittent renewable energy sources (RES) such as solar power and wind power into the energy system has caused temporal and spatial imbalance between electric power supply and demand for some countries and regions. This brings about the critical need for coordinating power production and power exchange for different regions. As compared with the power-only systems, the combined heat and power (CHP) systems can provide additional flexibility of utilizing RES by exploiting the interdependence of power and heat production in the CHP plant. In the CHP system, power production can be influenced by adjusting heat production level and electric power can be used to satisfy heat demand by electric boiler or heat pump in conjunction with heat storage, which is much cheaper than electric storage. This paper addresses multi-site CHP systems without considering RES, which lay foundation for handling penetration of RES. The problem under study is the unit commitment (UC) of the transmission-constrained multi-site CHP systems. We solve the problem by combining linear relaxation of ON/OFF states and sequential dynamic programming (DP) techniques, where relaxed states are used to reduce the dimension of the UC problem and DP for improving the solution quality. Numerical results for daily scheduling with realistic models and data show that DP-based algorithm is from a few to a few hundred times faster than CPLEX (standard commercial optimization software) with good solution accuracy (less than 1% relative gap from the optimal solution on the average).

Keywords: dynamic programming, multi-site combined heat and power system, relaxed states, transmission-constrained generation unit commitment

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Authors: Hadeel Al Obaidy, Amani Al Heela

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The main purpose of this paper is to examine the concept of semantic web and the role that ontology and semantic annotation plays in the development of semantic web services. The paper focuses on semantic web infrastructure illustrating how ontology and annotation work to provide the learning capabilities for building content semantically. To improve productivity and quality of software, the paper applies approaches, notations and techniques offered by software engineering. It proposes a conceptual model to develop semantic web services for the infrastructure of web information retrieval system of digital libraries. The developed system uses ontology and annotation to build a knowledge based system to define and link the meaning of a web content to retrieve information for users’ queries. The results are more relevant through keywords and ontology rule expansion that will be more accurate to satisfy the requested information. The level of results accuracy would be enhanced since the query semantically analyzed work with the conceptual architecture of the proposed system.

Keywords: semantic web services, software engineering, semantic library, knowledge representation, ontology

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Authors: Ehsan Daryadel, Hamid Shakeri

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Good governance is considered as one of the necessary prerequisites for promotion of sustainable development programs in countries. Theoretical model of good governance is going to form the best methods for administration and management of subject country. The importance of maintaining the balance between the needs of present and future generation through sustainable development caused a change in method of management and providing service for citizens that is addressed as the most efficient and effective way of administration of countries. This method is based on democratic and equal-seeking sustainable development which is trying to affect all actors in this area and also be accountable to all citizens’ needs. Meanwhile, it should be noted that good governance is a prerequisite for sustainable development. In fact, good governance means impact of all actors on administration and management of the country for fulfilling public services, general needs of citizens and establishing a balance and harmony between needs of present and future generation. In the present study, efforts have been made to present concepts, definitions, purposes and indices of good governance with a descriptive-analytical method.

Keywords: accountability, efficiency and effectiveness, good governance, rule of law, transparency

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Authors: Anette Hay, Zama Simamane

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Capacity-building and integration of practical activities is one of the key SDGs of the 2030 Agenda for Sustainable Development. This paper will focus on SDG# 17 – “the means of implementation” - and the role of systems thinking in practice (STiP) in supporting both competence and SDG implementation capability in teacher education curricula at North-West University, South Africa. The “Environmental Management for Sustainability” module (EDTM 312), which is compulsory for all students enrolled in the education program at North-West University, will be used as a case study. There is a need for higher education to implement and practically integrate SDG goals into their curricula, and one way to achieve this is through the development of competencies. Education for Sustainable Development (ESD) has the potential to offer approaches that can be useful in the development of capacity-building activities to foster sustainability. The methodological approach adopted is based on a participatory paradigm followed by two cycles and reflection. This paper focuses on systems thinking in practice demonstrating how students apply and reflect on competencies to situations and how praxis captures the actual experiences. The results of this research indicated how to re-orientate the EDTM 312 curriculum to include an environmental justice focus. This research shares practical knowledge of systems thinking as a sustainability competency.

Keywords: education for sustainable development, environmental justice competencies, sustainable development goals, systems thinking in practice

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Authors: I. D. Arroyo

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This article seeks to integrate different concepts from contemporary software engineering with an agile development approach. We seek to clarify some definitions and uses, we make a difference between the Systems Development Life Cycle (SDLC) and the methodologies, we differentiate the types of frameworks such as methodological, philosophical and behavioral, standards and documentation. We define relationships based on the documentation of the development process through formal and ad hoc models, and we define the usefulness of using DevOps and Agile Modeling as integrative methodologies of principles and best practices.

Keywords: methodologies, modeling languages, agile modeling, UML

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Authors: I Made Ginarsa, Agung Budi Muljono, I Made Ari Nrartha

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Transient voltage response appears in power system operation when an additional loading is forced to load bus of power systems. In this research, improvement of transient voltage response is done by using power system stabilizer-static var compensator (PSS-SVC) based on adaptive neuro-fuzzy inference system (ANFIS)-algorithm. The main function of the PSS is to add damping component to damp rotor oscillation through automatic voltage regulator (AVR) and excitation system. Learning process of the ANFIS is done by using off-line method where data learning that is used to train the ANFIS model are obtained by simulating the PSS-SVC conventional. The ANFIS model uses 7 Gaussian membership functions at two inputs and 49 rules at an output. Then, the ANFIS-PSS and ANFIS-SVC models are applied to power systems. Simulation result shows that the response of transient voltage is improved with settling time at the time of 4.25 s.

Keywords: improvement, transient voltage, PSS-SVC, ANFIS, settling time

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Authors: Jawid Ahmad Baktash, Mursal Dawodi, Tomokazu Nagata

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With the rapid growth of Cloud Computing, Formal Methods became a good choice for the refinement of message specification and verification for Dynamic Routing in Cloud Computing. Cloud-based Dynamic Routing is becoming increasingly popular. We propose feedback in Formal Methods for Dynamic Routing and Cloud Computing; the model and topologies show how to send messages from index zero to all others formally. The responsibility of proper verification becomes crucial with Dynamic Routing in the cloud. Formal Methods can play an essential role in the routing and development of Networks, and the testing of distributed systems. Event-B is a formal technique that consists of describing the problem rigorously and introduces solutions or details in the refinement steps. Event-B is a variant of B, designed for developing distributed systems and message passing of the dynamic routing. In Event-B and formal methods, the events consist of guarded actions occurring spontaneously rather than being invoked.

Keywords: cloud, dynamic routing, formal method, Pro-B, event-B

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Authors: Rodrigo Arnaldo Scarpel

Abstract:

Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

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Authors: Settana M. Abdulh, Naila A. Sadalla, Yaseen H. Taha, Howaida Elshoush

Abstract:

Side channel attacks are based on side channel information, which is information that is leaked from encryption systems. This includes timing information, power consumption as well as electromagnetic or even sound leaking which can exploited by an attacker. Implementing side channel attacks are possible if and only if an attacker has access to a cryptosystem. In this case, the attacker can exploit bad implementation in software or hardware which is not controlled by encryption implementer. Thus, he/she will represent a real threat to the security system. Several countermeasures have been proposed to eliminate side channel information vulnerability.Cache timing attack is a special type of side channel attack. Here, timing information is collected and analyzed by an attacker to guess sensitive information such as encryption key or plaintext. This paper reviews the technique applied in this attack and surveys the countermeasures against it, evaluating the feasibility and usability of each. Based on this evaluation, finally we pose several recommendations about using these countermeasures.

Keywords: AES algorithm, side channel attack, cache timing attack, cache timing countermeasure

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Authors: Yoshiaki Shikata, Nobutane Hanayama

Abstract:

We present a prioritized, limited multi-server processor sharing (PS) system where each server has various capacities, and N (≥2) priority classes are allowed in each PS server. In each prioritized, limited server, different service ratio is assigned to each class request, and the number of requests to be processed is limited to less than a certain number. Routing strategies of such prioritized, limited multi-server PS systems that take into account the capacity of each server are also presented, and a performance evaluation procedure for these strategies is discussed. Practical performance measures of these strategies, such as loss probability, mean waiting time, and mean sojourn time, are evaluated via simulation. In the PS server, at the arrival (or departure) of a request, the extension (shortening) of the remaining sojourn time of each request receiving service can be calculated by using the number of requests of each class and the priority ratio. Utilising a simulation program which executes these events and calculations, the performance of the proposed prioritized, limited multi-server PS rule can be analyzed. From the evaluation results, most suitable routing strategy for the loss or waiting system is clarified.

Keywords: processor sharing, multi-server, various capacity, N-priority classes, routing strategy, loss probability, mean sojourn time, mean waiting time, simulation

Procedia PDF Downloads 332