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This paper aims to introduce constructed CeO2/TiO2 core/shell nanoparticle as sensitive substance organic compounds.

The CeO₂ nanoparticles were synthesized by hydrothermal treatment. Then CeO₂/TiO₂ core/shell was fabricated by sol–gel method preparation of TiO₂ in the presence of ceria nanoparticles and applied as the sensitive material to make a sensor.

Formation of the nanoparticles was confirmed by X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), field emission scanning electron microscopy (FESEM) and high resolution transmission electron microscopy (HRTEM). The synthesized sensor exhibited not only good sensitivity to volatile organic compounds at room temperature but also logarithm of sensitivity versus concentrations was linear.

The sensor shows acceptable sensitivity to volatile organic compound at room temperature.

Experimental data revealed satisfactory reproducibility and short response and recovery times.

A radical mechanism for gas sensor reaction in two pathways was considered and activation energies were calculated by density functional theory (DFT) method to describe different sensitivities of tested volatile gases. The experimental results were consistent with the calculations.

Buildings use approximately 40% of global energy and are responsible for almost a third of the worldwide greenhouse gas emissions. They also utilise about 60% of the world’s electricity. In the last decade, stringent building regulations have led to significant improvements in the quality of the thermal characteristics of many building envelopes. However, similar considerations have not been paid to the number and activities of occupants in a building, which play an increasingly important role in energy consumption, optimisation processes, and indoor air quality. More than 50% of the energy consumption could be saved in Demand Controlled Ventilation (DCV) if accurate information about the number of occupants is readily available (Mysen et al., 2005). But due to privacy concerns, designing a precise occupancy sensing/counting system is a highly challenging task. While several studies count the number of occupants in rooms/zones for the optimisation of energy consumption, insufficient information is available on the comparison, analysis and pros and cons of these occupancy estimation techniques. This paper provides a review of occupancy measurement techniques and also discusses research trends and challenges. Additionally, a novel privacy preserved occupancy monitoring solution is also proposed in this paper. Security analyses of the proposed scheme reveal that the new occupancy monitoring system is privacy preserved compared to other traditional schemes.

The purpose of this paper is to present issues related to the design of a modern lighting system based on LED technology. The developed system provides lighting with a high colour rendering index (up to 98); it also has many innovative functions, which make its implementation bring significant energy savings and increase the comfort of work.

In contrast to typical solutions, the dynamic synthesis of white light from six component colours was used in the presented project. This process is controlled by a microcontroller, and there is a colour temperature sensor in the feedback loop. The communication between smart luminaires and sensor modules is provided by means of a ZigBee wireless network.

The correctness of the proposed methodology has been proved by measurements and laboratory tests.

The process of improving the lighting system is continued and significant changes in the spectrum of used sensors are expected.

The proposed system based on mixing light from six components is an innovative solution that besides undoubted advantages entails a more elaborate electronic circuitry. However, good characteristics of the obtained light, as well as the possibility of compensating for changes in colour temperature of natural light and reducing the impact of aging of LEDs, in the authors’ opinion, make the proposed solution find its place on the market.

The proposed solution is original, both in terms of the light mixing technique and advanced functionality offered by the system.

The purpose of the paper is to present an approach to detect and isolate the sensor failures, using a bank of extended Kalman filters (EKF) using an innovative initialization of covariance matrix using system dynamics.

The EKF is developed for nonlinear flight dynamic estimation of a spacecraft and the effects of the sensor failures using a bank of Kalman filters is investigated. The approach is to develop a fast convergence Kalman filter algorithm based on covariance matrix computation for rapid sensor fault detection. The proposed nonlinear filter has been tested and compared with the classical Kalman filter schemes via simulations performed on the model of a space vehicle; this simulation activity has shown the benefits of the novel approach.

In the simulations, the rotational dynamics of a spacecraft dynamic model are considered, and the sensor failures are detected and isolated.

A novel fast convergence Kalman filter for detection and isolation of faulty sensors applied to the three‐axis spacecraft attitude control problem is examined and an effective approach to isolate the faulty sensor measurements is proposed. Advantages of using innovative initialization of covariance matrix are presented in the paper. The proposed scheme enhances the improvement in estimation accuracy. The proposed method takes advantage of both the fast convergence capability and the robustness of numerical stability. Quaternion‐based initialization of the covariance matrix is not considered in this paper.

A new fast converging Kalman filter for sensor fault detection and isolation by innovative initialization of covariance matrix applied to a nonlinear spacecraft dynamic model is examined and an effective approach to isolate the measurements from failed sensors is proposed. An EKF is developed for the nonlinear dynamic estimation of an orbiting spacecraft. The proposed methodology detects and decides if and where a sensor fault has occurred, isolates the faulty sensor, and outputs the corresponding healthy sensor measurement.

The CIM framework pursues the integration of components in a manufacturing enterprise by means of computer systems. This, however, may be obstructed due to heterogeneity in the field: programmable controllers, robots, sensors and actuators, etc. in communications: different kinds of networks and/or field buses; and in the programming tools for all these devices. Thus a solution is needed to integrate heterogeneous software/hardware components in a well‐defined and flexible fashion. This paper seeks to address these issues.

This paper proposes a metalanguage, called H, and a set of tools that serve for designing, implementing, deploying, and debugging distributed heterogeneous software on the shopfloor. The metalanguange includes fault‐tolerance and real‐time mechanisms, among other features.

The use of a framework that can integrate different software and hardware components enables the engineer to take advantage of the best features of each existing technology. The use of object‐oriented techniques, concurrent and distributed programming, and the isolation of heterogeneous parts, have also important benefits in the reusability and optimality of the solutions.

The use of a metalanguage like H, that separates the parts of the application that depend on particular (heterogeneous) components from the parts that are portable, has, as a main implication, important improvements in the development time, effort, and cost of CIM projects.

H is the first metalanguage coping with heterogeneity through the complete development cycle of software for manufacturing applications. It also provides a formal and well‐defined framework for future extensions.

The purpose of this paper is to present a framework for cultivating virtual communities of practice in distributed environments. The framework is based on the integration of knowledge artifacts and wearable technologies.

The proposed knowledge artifact is based on the correlation between conceptual and computational tools for the representation of different kinds of knowledge.

In this way, it is possible to make deeper the collaboration between knowledge seekers and contributors within the community, given that seekers and contributors share, at least in part, design choices at the knowledge modeling level.

A practical application of the framework has been described, to show its originality with respect to traditional knowledge management systems. In particular, it has been demonstrated how lurking phenomenon inside communities of practice can be significantly reduced. To this aim, opportune indexes have been defined from existing ones in literature.

Many manufacturing sites require precision assembly. Particularly, similar to cell phones, assembly at the sub-mm scale is not easy, even for humans. In addition, the system should assemble each part with adequate force and avoid breaking the circuits with excessive force. The purpose of this study is to assemble high precision components with relatively reasonable vision devices compared to previous studies.

This paper presents a vision-force guided precise assembly system using a force sensor and two charge coupled device (CCD) cameras without an expensive 3-dimensional (3D) sensor or computer-aided design model. The system accurately estimates 6 degrees-of-freedom (DOF) poses from a 2D image in real time and assembles parts with the proper force.

In this experiment, three connectors are assembled on a printed circuit board. This system obtains high accuracy under 1 mm and 1 degree error, which shows that this system is effective.

This is a new method for sub-mm assembly using only two CCD cameras and one force sensor.

Identify how value is created through a product-service system (PSS). Recognize the different types of PSS and their characteristics at an economic and environmental level. Design a business model for a PSS that allows to generate economic and environmental value in a sustainable way.

On October 15th of 2014, Javier Ramirez, Chief Executive Officer of Famoc Depanel, was in his office in Bogotá, Colombia, thinking about a decision he had to take. Either Famoc Depanel continued in the traditional office furniture market generating new lower-cost products, and continued facing the informal competition or the company risked accepting a new business that the National Tax and Customs Direction of Colombia (DIAN, the acronym according to its name in Spanish) had proposed and give its business a complete turnaround. Either way, he would keep his commitment to innovation and environmental care.

This case is appropriate for use in sustainability and entrepreneurship courses with contents about business models based on PSS. This case can be used at undergraduate and graduate levels. It is recommended that students have prior knowledge about business models and the Canvas Business Model methodology.

Teaching Notes are available for educators only.

CSS 11: Strategy.

The purpose of this paper is to review the use of technologies for measuring space occupancy to guide the selection of appropriate tools for workplace post-occupancy evaluation (POE) studies. The authors focus on how actual space occupancy was measured in previous studies and the pros and cons of the different technologies and tools. This paper also addresses research gaps and directions for future research.

The space occupancy measures/tools are categorized based on the three types of technologies: environmental/ambient sensors, wearable sensors/smartphones and computer vision. A total of 50 studies are reviewed to identify the capabilities and limitations of these measurements.

Based on review results, the authors propose that although sensor technology can be a useful addition to the measures/tools list, a comprehensive review of the research goal, the occupants' behavior, and the environmental settings' characteristics should be conducted beforehand. Selecting appropriate technology is critical for collecting the proper behavioral data type, with a lower level of surveillance and increased validity.

This paper urges critical thinking about existing occupancy measures/tools across various fields, to inform the adoption and creation of new building occupancy measures. The knowledge of emerging sensor technology allows researchers to better study the temporal patterns of occupant behavior over extended periods and in a wide range of settings.

This paper aims to investigate the efficacy of teeth flux sensors in detecting, locating and assessing the severity of short-circuit faults in the stator windings of induction machines.

The experimental study involves inducing short-circuit winding turn variations on the induction machine’s stator and continuously measuring the RMS values across teeth flux sensors. Two crucial steps are taken for machine diagnosis: measurements under load operating conditions for fault detection and measurements under no-load conditions to determine fault location and severity.

The experimental results demonstrate that the proposed approach using teeth flux sensors is reliable and effective in detecting, locating and evaluating the severity of stator winding faults.

While this study focuses on short-circuit faults, future research could explore other fault types and alternative sensor configurations to enhance the comprehensiveness of fault diagnosis.

The methodology outlined in this paper holds the potential to significantly reduce maintenance time and costs for induction machines, leading to substantial savings for companies.

This research contributes to the field by presenting an innovative approach that uses teeth flux sensors for a comprehensive fault diagnosis in induction machines. The originality lies in the effectiveness of this approach in providing reliable fault detection, location and severity evaluation.