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The purpose of this paper is to design and validate an electronic nose (E-nose) prototype using commercially available metal oxide gas sensors (MOX). This prototype has a sensor array board that integrates eight different MOX gas sensors to handle multi-purpose applications. The number of sensors can be adapted to match different requirements and classification cases. The paper presents the validation of this E-nose prototype when used to identify three gas samples, namely, alcohol, butane and cigarette smoke. At the same time, it discusses the discriminative abilities of the prototype for the identification of alcohol, acetone and a mixture of them. In this respect, the selection of the appropriate type and number of gas sensors, as well as obtaining excellent discriminative abilities with a miniaturized design and minimal computation time, are all drivers for such implementation.

The suggested prototype contains two main parts: hardware (low-cost components) and software (Machine Learning). An interconnection printed circuit board, a Raspberry Pi and a sensor chamber with the sensor array board make up the first part. Eight sensors were put to the test to see how effective and feasible they were for the classification task at hand, and then the bare minimum of sensors was chosen. The second part consists of machine learning algorithms designed to ensure data acquisition and processing. These algorithms include feature extraction, dimensionality reduction and classification. To perform the classification task, two features taken from the sensors’ transient response were used.

Results reveal that the system presents high discriminative ability. The K-nearest neighbor (KNN) and support vector machine radial basis function based (SVM-RBF) classifiers both achieved 97.81% and 98.44% mean accuracy, respectively. These results were obtained after data dimensionality reduction using linear discriminant analysis, which is more effective in terms of discrimination power than principal component analysis. A repeated stratified K-cross validation was used to train and test five different machine learning classifiers. The classifiers were each tested on sets of data to determine their accuracy. The SVM-RBF model had high, stable and consistent accuracy over many repeats and different data splits. The total execution time for detection and identification is about 10 s.

Using information extracted from transient response of the sensors, the system proved to be able to accurately classify the gas types only in three out of the eight MQ-X gas sensors. The training and validation results of the SVM-RBF classifier show a good bias-variance trade-off. This proves that the two transient features are sufficiently efficient for this classification purpose. Moreover, all data processing tasks are performed by the Raspberry Pi, which shows real-time data processing with miniaturized architecture and low prices.

This paper aims to propose a one-layer Mamdani hierarchical fuzzy system (HFS) to navigate autonomously an omnidirectional mobile robot to a target with a desired angle in unstructured environment. To avoid collision with unknown obstacles, Mamdani limpid hierarchical fuzzy systems (LHFS) are developed based on infrared sensors information and providing the appropriate linear speed controls.

The one-layer Mamdani HFS scheme consists of three fuzzy logic units corresponding to each degree of freedom of the holonomic mobile robot. This structure makes it possible to navigate with an optimized number of rules. Mamdani LHFS for obstacle avoidance consists of a number of fuzzy logic units of low dimension connected in a hierarchical structure. Hence, Mamdani LHFS has the advantage of optimizing the number of fuzzy rules compared to a standard fuzzy controller. Based on sensors information inputs of the Mamdani LHFS, appropriate linear speed controls are generated to avoid collision with static obstacles.

Simulation results are performed with MATLAB software in interaction with the environment test tool “Robotino Sim.” Experiments have been done on an omnidirectional mobile robot “Robotino.” Simulation results show that the proposed approaches lead to satisfied performances in navigation between static obstacles to reach the target with a desired angle and have the advantage that the total number of fuzzy rules is greatly reduced. Experimental results prove the efficiency and the validity of the proposed approaches for the navigation problem and obstacle avoidance collisions.

By comparing simulation results of the proposed Mamdani HFS to another navigational controller, it was found that it provides better results in terms of path length in the same environment. Moreover, it has the advantage that the number of fuzzy rules is greatly reduced compared to a standard Mamdani fuzzy controller. The use of Mamdani LHFS in obstacle avoidance greatly reduces the number of involved fuzzy rules and overcomes the complexity of high dimensionality of the infrared sensors data information.

The purpose of this paper is to deal with the investigation of no-load operation of tubular linear permanent magnet synchronous machines (T-LPMSMs). It is aimed at the prediction of the phase flux linkages, the back-EMF and the cogging force using a position varying magnetic equivalent circuit (MEC).

This study is based on the elaboration and the resolution of the position varying MEC, and the utilization of its results for the prediction of the phase flux linkages, the back-EMF and the cogging force, considering a general topology of T-LPMSMs. Then, a case study is treated with a position varying MEC-based investigation of its no-load features. These are validated by a 2-D finite element analysis (FEA).

It has been found that the developed position varying MEC can be regarded as an accurate tool that requires a low CPU-time.

Beyond the FEA validation, this work should be extended to an experimental one. Moreover, the position varying MEC validity should be extended to load operation in order to enable the prediction of the force production capability.

The developed position varying MEC could be suitably used for the pre-design of T-LPMSMs. These are currently given an increasing attention in many applications, such as wave energy conversion and free-piston engines.

The paper proposes a position varying MEC for the prediction of the features of T-LPMSMs.

The purpose of this paper is to propose a generic platform for a robotic mobile system, seeking to obtain a support tool for under-graduation and graduation activities. Another objective was to gather knowledge in the mobile robotic area in order to provide practical solutions for industrial problems.

The proposed new integrated platform would serve as didactic material for many disciplines, shown to be an ideal platform to teach DC motor drives, stepper motor and motion-control systems. To reach this objective, the ability of the robot to plan its motion autonomously is of vital importance. The control of a mobile robot in dynamic and unstructured environments typically requires efficient processing of data/information to ensure precise navigation and many other applications. Path planning is also one common method of auto-navigation. After the computation of the shortest path, mobile robot can navigate safely and without occlusion.

The developed platform is an integrated system for intelligent software middleware to coordinate many activities in the field of electric drives, robotics, autonomous systems and artificial intelligence.

As a result of the study, this paper contributed to research in the industrial development, principally in the fields of industrial robotics and also in different application purposes such as entertainment, personal use, welfare, education, rehabilitation, etc.

Covering a fiber-reinforced concrete column (fiber reinforced plastic (FRP)) improves the performance of the column primarily. The purpose of this paper is to investigate the behavior of small FRP concrete columns that are subject to axial pressure loading, in order to study the effect of many parameters on the effectiveness of FRP couplings on circular and square concrete columns.

These parameters include the shape of the browser (circular and square), whole core and cavity, square radius of square columns, concrete strength (low strength, normal and high), type of FRP (carbon and glass) and number of FRP (1–3) layers. The effective fibrillation failure strain was investigated and the effect of effective lateral occlusion pressure.

The results of the test showed that the FRP-coated columns improved significantly the final conditions of both the circular and square samples compared to the unrestricted columns; however, improvement of square samples was not as prominent as improvement in circular samples. The results indicated that many parameters significantly affected the behavior of FRP-confined columns. A new model for predicting compressive force and the corresponding strain of FRP is presented. A good relationship is obtained between the proposed equations and the current experimental results.

The average hoop strain in FRP wraps at rupture in FRP-confined concrete specimens can be much lower than that given by tensile coupon tests, meaning the theoretical assumption that the FRP-confined concrete cylinder ruptures when the FRP material tensile strength attained at its maximum is not suitable. Based on this observation, the effective peak strength and corresponding strain formula for FRP concrete confined columns must be based on the effective hoop rupture strain composite materials.

The purpose of this paper is to propose improvement of the generation capability of a claw pole alternator with DC excitation in the stator (CPAES) using analytical investigation based on a dedicated reluctant model.

The paper analyzes the effects of geometry and material transformations of the magnetic circuit on the generation capability of the CPAES as well as the reduction of claw‐claw leakage flux by inserting permanent magnets in between adjacent claws.

The generation capability could be improved considering the proposed geometry and material changes of the magnetic circuit of the CPAES. The inclusion of permanent magnets in between adjacent claws offers an increase of the alternator generation due to the reduction of the claw‐claw leakage flux.

The research should be extended by building a new prototype of the CPAES in order to compare analytical results and experimental ones.

A new concept with no brush‐ring for excitation and an improvement of the generation capability of the alternator make the CPAES an interesting candidate especially in large‐scale production applications such as the automotive industry.

The paper proposes a new alternator topology called claw pole alternator with DC excitation in the stator (CPAES) and an analytical approach to improve the generation capability of such a concept, which represents a crucial challenge in electric generation systems especially in automotive applications.

People in prison are at a higher risk of preventable mortality from infectious disease such as human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS), hepatitis B (HBV), hepatitis C (HCV) and tuberculosis (TB) than those in the community. The extent of infectious disease-related mortality within the prison setting remains unclear. The purpose of this paper was to collate available information on infectious disease-related mortality, including the number of deaths and calculate the person-time death rate.

The authors searched databases between 1 January 2000 and 18 November 2020 for studies reporting HIV, HBV, HCV, TB and/or HIV/TB-related deaths among people in prison.

The authors identified 78 publications drawn from seven Joint United Nations Programme on HIV/AIDS’ regions encompassing 33 countries and reporting on 6,568 deaths in prison over a 20-year period. HIV/AIDS (n = 3,305) was associated with the highest number of deaths, followed by TB (n = 2,892), HCV (n = 189), HIV/TB (n = 173) and HBV (n = 9). Due to the limitations of the available published data, it was not possible to meta-analyse or in any other way synthesise the available evidence.

To inform targeted efforts to reduce mortality, there is a need for more, better quality data to understand infectious disease-related mortality in custodial settings. Increased investment in the prevention and management of infectious diseases in custodial settings, and in documenting infectious disease-related deaths in prison, is warranted and will yield public health benefits.

To the authors’ best knowledge, this is the first scoping review focussed on deaths due to these infections among people in prison internationally. The gaps identified form recommendations to improve the future collection and reporting of prison mortality data.

This work proposes a method to improve the estimation performance at standstill and low speed operations of an adaptive fuzzy logic speed‐sensorless field‐oriented control of an induction motor.

First, the speed estimation algorithm presented in Tursini et al., which it has been designed to consider constant speed operation, is modified in an attempt to reduce the estimation error. Second, the speed regulation by fuzzy logic controller (FLC) with fuzzy adapted gains (FAG) is proposed for speed regulation. The main features of the proposed algorithm are investigated and compared with those of the algorithm of (Tursini) considering different dynamic operating conditions.

Simulation results clearly show the performance of the proposed algorithm.

The proposed scheme is recommended for applications requiring robust speed control and field‐orientation even in the presence of some key parameter deviations.

The purpose of this paper is to deal with a new dispatching and optimization of reactive power sources in power systems.

The methodology is first based on an optimal movement of existing reactive sources as a first phase, then an optimal investment in a second phase and finally a combination of the two previous phases as the third one. The methodology showed also the advantage of a two‐levels procedure, considering an initial minimal compensation before minimizing the active losses. The solution of the global non‐linear problem is performed using the projected and augmented Lagrange method associated with the reduced gradient and the DFP methods.

In waiting for new investment programs which are planned for limited periods, the study presents an alternative of optimizing the reactive power compensation by a movement of the power sources or some of them, satisfying all system constraints and minimizing also the active power losses.

The planners and operators are able to decide what cases are to be considered for reactive power dispatch; the proposed program gives a proposal solution to almost all changes that can occur to the power system (incident, contingency, load variation, development).