Electrical And Electronic Engineering

To capture the dynamics of modern Cyber-Physical Systems, hybrid system models are introduced to combine their continuous dynamics with the discrete ones. Unfortunately, one important negative issue can affect hybrid system models: the so-called Zeno phenomenon, which results in an infinite number of discrete transitions in a finite amount of time occurring during the model’s simulation that leads to inconsistent results. In this context, the paper investigates the use of a recently proposed numerical algorithm, based on the Infinity Computer methodology, to handle the Zeno phenomenon and evaluate it with respect to standard numerical methods by considering the hybrid system models of two exemplary Cyber-Physical Systems: the Water tanks and the Thermostat.

Modelica is an innovative, equation-based, and acausal language that allows modeling complex physical systems, which are made of mechanical, electrical, and electrotechnical components, and evaluates their design through simulation techniques. Unfortunately, the increasing complexity and accuracy of such physical systems require new, more powerful, and flexible tools and techniques for evaluating important system properties and, in particular, the dependability ones such as reliability, safety, and maintainability. In this context, the paper describes some extensions of the Modelica language to support the modeling of system requirements and their relationships. Such extensions enable the requirement verification analysis through native constructs in the Modelica language. Furthermore, they allow exporting a Modelica-based system design as a Bayesian Network in order to analyze its dependability by employing a probabilistic approach. The proposal is exemplified through a case study ...

Remote manipulation (triggering and guiding) of lightning in atmospheric conditions of thunderstorms has been the subject of intense scientific research for decades. High power, ultrashort-pulse lasers are considered attractive in generating plasma channels in air that could serve as conductors/diverters for lightning. However, two fundamental obstacles, namely the limited length and lifetime of such plasma channels prevented their realization to this date. In this paper, we report decisive experimental results of our multi-element broken wire concept that extends the generated plasma channels to the required tens of meters range. We obtain 13-meter-long plasma wire, limited only by our current experimental setup, with plasma conditions that could be sufficient for the leader initiation. This advance, coupled with our demonstrated method of laser heating for long time sustenance of the plasma channel, is a major, significant step towards controlling lightning.

The Heat Loss Coefficient (HLC) characterizes the envelope efficiency of a building under in-use conditions, and it represents one of the main causes of the performance gap between the building design and its real operation. Accurate estimations of the HLC contribute to optimizing the energy consumption of a building. In this context, the application of black-box models in building energy analysis has been consolidated in recent years. The aim of this paper is to estimate the HLC of an existing building through the prediction of building thermal demands using a methodology based on Machine Learning (ML) models. Specifically, three different ML methods are applied to a public library in the northwest of Spain and compared; eXtreme Gradient Boosting (XGBoost), Support Vector Regression (SVR) and Multi-Layer Perceptron (MLP) neural network. Furthermore, the accuracy of the results is measured, on the one hand, using both CV(RMSE) and Normalized Mean Biased Error (NMBE), as advised by A...

This paper introduces a comprehensive approach based on computer vision for the automatic detection, identification and pose estimation of lamps in a building using the image and location data from low-cost sensors, allowing the incorporation into the building information modelling (BIM). The procedure is based on our previous work, but the algorithms are substantially improved by generalizing the detection to any light surface type, including polygonal and circular shapes, and refining the BIM integration. We validate the complete methodology with a case study at the Mining and Energy Engineering School and achieve reliable results, increasing the successful real-time processing detections while using low computational resources, leading to an accurate, cost-effective and advanced method. The suitability and the adequacy of the method are proved and concluded.

Stiffness sensing is an important issue in medical diagnostic, robotics surgery, safe handling, and safe grasping of objects in production lines. Detecting and obtaining the characteristics in dwelling lumps embedded in a soft tissue and safe removing and handling of detected lumps is needed in surgery. Also in industry, grasping and handling an object without damaging in a place where it is not possible to access a human operator is very important. In this paper, a method for object handling is presented. It is based on the use of an intelligent gripper to detect the object stiffness and then setting a programmable force for grasping the object to move it. The main components of this system includes sensors (sensors for measuring force and displacement), electrical (electrical and electronic circuits, tactile data processing and force control system), mechanical (gripper mechanism and driving system for the gripper) and the display unit. The system uses a rotary potentiometer for m...

ترابع زا هلاقم نیا هب عاجرا يارب دییامن هدافتسا لیذ : Please cite this article using: M.S. Mohamadzadeh Moghadam, M. Modabberifar, B. Mirzakhani, Design of a new actuator for actuating a linear hydraulic valve and its optimization with genetic algorithm, Iranian Journal of Manufacturing Engineering, Vol. 3, No. 3, pp. 1-9, 2016 (in Persian) یحارط هکرحم يا دیدج تهج کیرحت کی هنومن ریش یکیلوردیه یطخ یتعنص و هنیهب يزاس نآ اب متیروگلا کیتنژ

We consider a discrete-time dynamical system generated by a nonlinear operator (with four real parameters [Formula: see text]) of ocean ecosystem. We find conditions on the parameters under which the operator is reduced to a [Formula: see text]-Volterra quadratic stochastic operator mapping two-dimensional simplex to itself. We show that if [Formula: see text], then (under some conditions on [Formula: see text]) this [Formula: see text]-Volterra operator may have up to three or a countable set of fixed points; if [Formula: see text], then the operator has up to three fixed points. Depending on the parameters, the fixed points may be attracting, repelling or saddle points. The limit behaviors of trajectories of the dynamical system are studied. It is shown that independently on values of parameters and on initial (starting) point, all trajectories converge. Thus, the operator (dynamical system) is regular. We give some biological interpretations of our results.

One of the most important tasks of System Operator (SO) is to manage congestion as it threatens system security and may cause rise in electricity price resulting in market inefficiency. In corrective action congestion management schemes, it is crucial for SO to select the most sensitive generators to re-schedule their real and reactive powers and the loads to curtail in extreme congestion management. This paper proposed the selection of most sensitive generators and loads to re-schedule their generation and load curtailment based on the improved line flow sensitivity indices to manage congestion. The impact of slack bus on power flow sensitivity factors has been determined to encourage fair competition in the electricity markets. Effect of bilateral and multilateral transactions, and impact of multi-line congestion on congestion cost has also been studied. The generators’ reactive power bid has been modeled by a continuous differentiable tangent hyperbolic function. The proposed con...

Information and Communication Technologies, to a long extent, have a major influence on our social life, economy as well as on worldwide security. Holistically, computer networks embrace the Information Technology. Although the world is never free from people having malicious intents i.e. cyber criminals, network intruders etc. To counter this, Intrusion Detection System (IDS) plays a very significant role in identifying the network intrusions by performing various data analysis tasks. In order to develop robust IDS with accuracy in intrusion detection, various papers have been published over the years using different classification techniques of Data Mining (DM) and Machine Learning (ML) based hybrid approach. The present paper is an in-depth analysis of two focal aspects of Network Intrusion Detection System that includes various pre-processing methods in the form of dimensionality reduction and an assortment of classification techniques. This paper also includes comparative algor...

For a happy and healthy life, a happy married life is very much essential. But nowadays, divorce cases are increasing rapidly day by day. According to a study, the divorce rate worldwide was 4.08% per 1000 married people in May 2022. For this reason, there is a need for effective prediction of divorce rate which helps the marriage counselor or therapist to understand how serious a case is. For this research purpose, a dataset was collected from UCI repository and contains some data based on the questions asked to the couple and the answers they gave. First, the dataset was cleaned using different ranking methods such as Information Gain, One R, Gain Ratio and ReliefF. Using these ranking methods, the most important fields that really affect the divorce are selected. Then, different classification algorithms such as Logistic Regression, Naïve Bayes, SGD, Decision Tree, Random Forest and Multilayer Perceptron were used and compared to find the accuracy. These algorithms are used first...