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This paper aims to show the current situation and additional requirements for the aircraft automation systems based on the lessons learned from the two 737 MAX crashes.

In this study, the Swiss cheese model was used to find the real root causes of the 737 MAX accidents. Then, the results have been compared with the actions taken by the manufacturers and authorities. Based on the comparison, the necessary improvements to prevent such accidents are defined. Regarding the faulty sensor that forms the accidents, a synthetic sensor was developed using an aerodynamic model.

It has been proven that the safety-critical automation systems should not be designed by relying on a single set of sensor data. Automation levels should be defined in a standard way. Depending on the defined automation level, the system must be designed as either fail-safe or fail-operational system. When designing backup systems, it should be decided by looking at not only whether it has power but also the accuracy of the incoming signals.

Aviation certification requirements related to automation systems need to be revised and improved. With this context, it was revealed that the certification processes for automation systems should be re-evaluated and updated by aviation authorities, especially Federal Aviation Administration and European Union Aviation Safety Agency.

Task sharing between automation system and pilot based on the classification of automation levels and determining certification requirements accordingly has been brought to the agenda. A synthetic Angle of Attack sensor was developed by using an aerodynamic model for fault detection and diagnosis.

Most recent developments in the Internet of Things (IoT) technologies can boost the efficacy of business process management (BPM) to improve process performance. The purpose of this paper is to describe a method for redesigning bank branch (BB) protection systems contributing to make BBs “smarter.”

Based upon a multiple case study approach, the paper deployed a four-step business process reengineering design from an information system development perspective. To overcome limitations of information scarcity required for modeling activities, a multimethod approach to data gathering and results validation was adopted. The approach was based on a comprehensive literature review and an in-depth qualitative survey involving a sample of six security managers of primary Italian banking groups.

The intelligent protection system resulting from the application of the methodology to the Italian BB sector was able to improve the security management process. Lead time and actors’ workload were reduced; running costs decreased; quality of information improved as well as the overall effectiveness of the protection system against criminal attacks.

The specific IoT technologies proposed are new. Additionally, to date, their application to BB security management has not been analyzed in the BPM literature. The value resides in the highly applicable results of the methodology to the BB network of a banking group both inside and outside of Italy.

This paper aims to experimentally study the external flow characteristic of an isolated two-dimensional synthetic jet actuator undergoing diaphragm resonance.

The resonance frequency of the diaphragm (40 Hz) depends on the excitation mechanism in the actuator, whereas it is independent of cavity geometry, excitation waveform and excitation voltage. The velocity response of the synthetic jet is influenced by excitation voltage rather than excitation waveform. Thus, this investigation selected four different voltages (5, 10, 15 and 20 V) under the same sine waveform as experiment parameters.

The velocity field along the downstream direction is classified into five regions, which can be obtained by hot-wire measurement. The first region refers to an area in which flow moves from within the cavity to the exit of orifice through the oscillation of the diaphragm, but prior to the formation of the vortex of a synthetic jet. In this region, two characteristic frequencies exist at 20 and 40 Hz in the flow field. The second region refers to the area in which the vortices of a synthetic jet fully develop following their initial formation. In this region, the characteristic frequencies at 20 and 40 Hz still occur in the flow field. The third region refers to the area in which both fully developed vortices continue traveling downstream. It is difficult to obtain the characteristic frequency in this flow field, because the mean center velocities (ū) decay downstream and are proportional to (x/w)^−1/2 for the four excitation voltages. The fourth region reveals variations in both vortices as they merge into a single vortex. The mean center velocities (ū) are approximately proportional to (x/w)⁰ in this region for the four excitation voltages. A fifth region deals with variations in the vortex of a synthetic jet after both vortices merge into one, in which the mean center velocities (ū) are approximately proportional to (x/w)⁻¹ in this region for the four excitation voltages (x/w is the dimensionless streamwise distance).

Although the flow characteristics of synthetic jets had reported for flow control in some literatures, variations of flow structure for synthetic jets are still not studied under the excitation of diaphragm resonance. This paper showed some novel results that our velocity response results obtained by hot-wire measurement along the downstream direction compared with flow visualization resulted in the classification of five regions under the excitation of diaphragm resonance. In the future, it makes valuable contributions for experimental findings to provide researchers with further development of flow control.

Artificial fruit ripening is hazardous to mankind. In the recent past, artificial fruit ripening is increasing gradually due to its commercial benefits. To discriminate the type of fruit ripening involved at the vendors’ side, there is a great demand for on-sight ethylene detection in a nondestructive manner. Therefore, this study aims to deal with a comparison of various laboratory and portable methods developed so far with high-performance metrics to identify the ethylene detection at fruit ripening site.

This paper focuses on various types of technologies proposed up to date in ethylene detection, fabrication methods and signal conditioning circuits for ethylene detection in parts per million and parts per billion levels. The authors have already developed an infrared (IR) sensor to detect ethylene and also developed a lab-based setup belonging to the electrochemical sensing methods to detect ethylene for the fruit ripening application.

The authors have developed an electrochemical sensor based on multi-walled carbon nanotubes whose performance is relatively higher than the sensors that were previously reported in terms of material, sensitivity and selectivity. For identifying the best sensing technology for optimization of ethylene detection for fruit ripening discrimination process, authors have developed an IR-based ethylene sensor and also semiconducting metal-oxide ethylene sensor which are all compared with literature-based comparable parameters. This review paper mainly focuses on the potential possibilities for developing portable ethylene sensing devices for investigation applications.

The authors have elaborately discussed the new chemical and physical methods of ethylene detection and quantification from their own developed methods and also the key findings of the methods proposed by fellow researchers working on this field. The authors would like to declare that the extensive analysis carried out in this technical survey could be used for developing a cost-effective and high-performance portable ethylene sensing device for fruit ripening and discrimination applications.

Many types of sensing from satellites and aircraft are giving the offshore oil and gas industry increasingly comprehensive information.

Describes the Amocut advanced monitoring system developed in the UK and Italy for the automatic monitoring of pH value, concentration, tramp oil, particulates (by abrasion), corrosivity and microbial activity of metalworking fluids.

SYNOPSIS. A new type of cutting fluid is essential to achieving utilisation of the full potential of Automated Machining (AM). Coolant capabilities frequently determine the scope of multi‐tool machining applications. Identifying operational needs and overcoming AM system constraints has provided a unique opportunity to develop a new synthetic cutting fluid technology. A vision for the future is where the expansion of synthetic lubricant technology will continue to contribute significant benefits to an ever‐widening area of manufacturing industry's lubricant requirements.

The purpose of the study is to highlight the potential of the sensor based smartphone in assessing the covid-19 cases. Coronavirus disease 2019 (COVID-19) is a noxious pandemic affecting the respiratory system of the human and leading to the severe acute respiratory syndrome, sometimes causing death. COVID-19 is a highly transmittable disease that spreads from an infected person to others. In this regard, a smart device is required to monitor the COVID-19 infected patients by which widespread pandemic can be reduced.

In this paper, an electrochemical sensor-enabled smartphone has been developed to assess the COVID-19 infected patients. The data-enabled smartphone uses the Internet of Things (IoT) to share the details with the other devices. The electrochemical sensor enables the smartphone to evaluate the ribonucleic acid (RNA) of COVID-19 without the nucleic acid and feeds the data into the data server by using a smartphone.

The obtained result identifies the infected person by using the portable electrochemical sensor-enabled smartphone, and the data is feed into the data server using the IoT. Whenever an infected person moves outside the restricted zone, the data server gives information to the concerned department.

The developed electrochemical sensor-enabled smartphone gives an accuracy of 81% in assessing the COVID-19 cases. Thus, through the developed approach, a COVID-19 infected person can be identified and the spread can be minimized.

Synthetic aperture radar exploits the receiving signals in the antenna for detecting the moving targets and estimates the motion parameters of the moving objects. The limitation of the existing methods is regarding the poor power density such that those received signals are essentially to be transformed to the background ratio. To overcome this issue, fractional Fourier transform (FrFT) is employed in the moving target detection (MTD) process. The paper aims to discuss this issue.

The proposed MTD method uses the fuzzy decisive approach for detecting the moving target in the search space. The received signal and the FrFT of the received signal are subjected to the calculation of correlation using the ambiguity function. Based on the correlation, the location of the target is identified in the search space and is fed to the fuzzy decisive module, which detects the target location using the fuzzy linguistic rules.

The simulation is performed, and the analysis is carried out based on the metrics, like detection time, missed target rate, and MSE. From the analysis, it can be shown that the proposed Fuzzy-based MTD process detected the object in 5.0237 secs with a minimum missed target rate of 0.1210 and MSE of 23377.48.

The proposed Fuzzy-MTD is the application of the fuzzy rules for locating the moving target in search space based on the peak energy of the original received signal and FrFT of the original received signal.