1,721,030 research outputs found
A Detailed Study on Algorithms for Predictive Maintenance in Smart Manufacturing: Chip Form Classification Using Edge Machine Learning
No full textIndustrial and technological evolution has led to the identification of different techniques and strategies that can best adapt to the needs of Manufacturing Industry 4.0. As industrial production has become more automated, the need for more efficient maintenance strategies has increased. Today, among the possible, several applications demonstrate how the Predictive Maintenance (PdM) strategy is the best performing. In fact, PdM makes it possible to predict an impending failure with high accuracy in order to intervene before failure occurs. This work focuses on the application of PdM technique in order to predict the type of chips produced by a lathe through a machine learning algorithm. Moreover, being our application a delay-sensitive one, to drastically decrease the time delay in prediction, our solution proposes the combination of PdM with the Edge Computing paradigm. To simulate this paradigm, the chosen machine learning models were deployed on STM microcontrollers obtaining both high accuracy (98%) and an inference time in the order of milliseconds
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
LED junction temperature prediction using machine learning techniques
No full textLight Emitting Diodes (LEDs) are the longest lasting source of artificial illumination whose duration can exceed 50.000 continuous working hours. Nevertheless, they show a gradual reduction of the luminous flux due to the increase of the device temperature. In this work, a Machine Learning algorithm will be introduced and discussed, able to predict the junction temperature value of a LED in real-time while connected in the end-user circuit, taking into account current and voltage flowing in the device and, further, the actual model and aging of the LED. The algorithm was implemented on a microcontroller, showing the feasibility of performing edge machine learning on tiny yet powerful devices
Cmos rf transmitters with on-chip antenna for passive RFID and iot nodes
No full textThe performances of two RF transmitters, monolithically integrated with their antennas on a single CMOS microchip fabricated in a standard 0.35 μm process, are presented. The usage of these architectures in the Internet of Things (IoT) paradigm is envisioned, as part of a custom conceived data transmission system. The implemented circuits use two different directly on–off keying (OOK) modulated oscillator topologies whose outputs are employed to feed two loop antennas. The powering of both transmitters is duty-cycled for reducing the average power consumption to a few tenths of a microwatt, allowing the usage as low-power transmitters for IoT nodes. The integrated loop antennas radiate sufficient power for a few meters’ communication range. The OOK transmitted signal can be easily detected using a commercial receiver
Valutazione dell’antibiotico-resistenza di patogeni respiratori dei suini isolati in Italia nel 2009
No full textElectronic sensors for intraoral force monitoring: State-of-the-art and comparison
No full textThe aim of this work is to provide a comprehensive view on sensors technology for intraoral forces monitoring. State-of-the-art electronic sensors, exploitable for the application of measuring intraoral human forces are compared in this work. Furthermore, a possible configuration for data acquisition from multiple sensors, using Wheatstone bridges to detect the resistance variation and the force output of miniature strain gauges, is also provided
Mobile synchronization recovery for ultrasonic indoor positioning
Full text linkThe growing interest for indoor position-based applications and services, as well as ubiquitous computing and location aware information, have led to increasing efforts toward the development of positioning techniques. Many applications require accurate positioning or tracking of people and assets inside buildings, and some market sectors are waiting for such technologies for starting a fast growth. Ultrasonic systems have already been shown to possess the desired positioning accuracy and refresh rate. However, they still require accurate synchronization between ultrasound emitters and receivers to work properly. Usually, synchronization is carried out through radio frequency (RF) signals, adding system complexity and raising the cost. In this work, this limit is overcome by introducing a novel self-synchronizing indoor positioning technique. Ultrasonic signals travel from emitters placed at fixed reference positions to any number of mobile devices (MD). The travelled distance is computed from the time of flight (TOF), which requires in turn synchronism between emitter and receiver. It is shown that this synchronism can be indirectly estimated from the time difference of arrival (TDOA) of the ultrasonic signals. The obtained positioning information is private, in the sense that the positioning infrastructure is not aware of the number or identity of the MDs that use it. Computer simulations and experimental results obtained in a typical office room are provided
Reconfigurable UHF RFID tag with sensing capabilities
No full textThe pervasiveness of RFID in application fields commonly prerogative of other technologies is related to the addition of sensor and computational capabilities to the systems. This paper presents a smart RFID tag based on a custom designed microchip, able to transmit wirelessly the information coming from a series of integrated sensors and complying with part of the RFID UHF EPC-Gen2 standard, developed implementing the state machine on a Field Programmable Gate Array (FPGA) board. The solution provided aims to demonstrate the feasibility to create augmented RFID tags useful in several applications such as a safer and more manageable food supply chain of perishable comestibles, or biomedical sensor data transmitters. The solution conceived, thanks to the possible miniaturization of the FPGA IC, is a practical solution to obtain compact, small size and low cost devices for short range applications. The FPGA-based implementation ensures a low-cost alternative to dedicated ASIC design for achieving high-end features such as bi-directional communication, anti-collision and on-board computational power
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