Controlled Environment
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2021 ◽  
Vol 11 (19) ◽  
pp. 8875
Jesus David Chaux ◽  
David Sanchez-Londono ◽  
Giacomo Barbieri

To ensure food security, agricultural production systems should innovate in the direction of increasing production while reducing utilized resources. Due to the higher level of automation with respect to traditional agricultural systems, Controlled Environment Agriculture (CEA) applications generally achieve better yields and quality crops at the expenses of higher energy consumption. In this context, Digital Twin (DT) may constitute a fundamental tool to reach the optimization of the productivity, intended as the ratio between production and resource consumption. For this reason, a DT Architecture for CEA systems is introduced within this work and applied to a case study for its validation. The proposed architecture is potentially able to optimize productivity since it utilizes simulation software that enables the optimization of: (i) Climate control strategies related to the control of the crop microclimate; (ii) treatments related to crop management. Due to the importance of food security in the worldwide landscape, the authors hope that this work may impulse the investigation of strategies for improving the productivity of CEA systems.

Niharika S K

Abstract: India is a country with a booming population and limited resources. 40 % of food grains are being wasted annually out of the world’s production due to factors like improper post-harvest management, lack of storage spaces, storage facilities, handling and distribution of food grains, etc. Thus an effective solution is required to bridge the gap between surplus production and hunger. The objective of our project is to develop methods for retaining the quality of food grains under a controlled environment for effective storage and distribution. Automation using sensors helps to prevent illegal racketing with data collection, monitor storage conditions like temperature and humidity levels, and eliminate man-to-man contact. When dispensed, the level and quantity of the grains can also be recorded. Thus, this machine is better than the existing manual methods of distribution as it acknowledges fair distribution and quality preservation. Keywords: Smart storage, proper distribution, sensors, post harvest losses, grain quality

2021 ◽  
Philipp A Schroeder ◽  
Enrico Collantoni ◽  
Johannes Lohmann ◽  
Martin V Butz ◽  
Christian Plewnia

Abstract Purpose: Attractive food elicits approaching behavior, which could be directly assessed in a combination of Virtual Reality (VR) with online motion-capture. Thus, VR enables the assessment of motivated approach and avoidance behavior towards food and non-food cues in controlled laboratory environments. Aim of this study was to test the specificity of a behavioral approach bias for high-calorie food in grasp movements compared to low-calorie food and neutral objects of different complexity, namely, simple balls and geometrically more complex tools. Methods: In a VR setting, healthy participants repeatedly grasped or pushed high-calorie food, low-calorie food, balls and office tools in randomized order with 30 item repetitions. All objects were rated for valence and arousal. Results: High-calorie food was less attractive and more arousing in subjective ratings than low-calorie food and neutral objects. Responses to high-calorie food were fastest only in grasp trials, but comparisons with low-calorie food and complex tools were inconclusive. Conclusion: A behavioral bias for food may be specific to high-calorie food objects, but more systematic variations of object fidelity are outstanding. The utility of VR in assessing approach behavior is confirmed in this study by exploring manual interactions in a controlled environment.

Perception ◽  
2021 ◽  
pp. 030100662110434
Sandhya Kumar ◽  
Surabhi Kumar

The human body has dedicated receptors for sensing temperature and touch, but not wetness. How then is wetness perceived? To test if wetness perception arises from the sensory integration of touch and temperature, and to quantify its measurement in humans, we designed a wetness perception monitor (WPM) which enabled variation of temperature at the fingertips of participants while measuring the pressure exerted on a test surface in the controlled environment of a moisture-free chamber. Thirty randomly selected adults (18+ years) were tested for their perception of dampness/wetness using the WPM. Our data suggest that humans perceive dampness and wetness at average temperatures of 22 ± 0.4°C and 18 ± 0.5°C, respectively, and these sensations are extinguished at temperatures below 16 ± 1°C. Measurements were obtained at an average tactile pressure of 1.5 ± 0.3 kPa. Young adults (18–35 years) sensed wetness at significantly higher temperatures than middle-aged adults (36–55 years) or mature adults (56+ years), who sensed wetness at similar temperatures. We found a surprising sex difference in wetness perception, with females sensing wetness at higher temperatures than males. When the data were screened for outliers, we found that participants whose readings were outside normal ranges, self-reported sensory deficits suggesting that wetness perception could potentially be used as a noninvasive biomarker.

2021 ◽  
pp. 000283122110463
Shira Alicia Korn Haderlein

As parents are increasingly given flexibility to enroll their children in a school of their choice, understanding parents’ preferences for school qualities is essential. Using a randomized survey experiment, this study adds to the existing literature by assessing parents’ preferences in a controlled environment, where they can be isolated from information asymmetries and constraints. Results suggest that achievement matters to parents but status matters more when evaluating quality and growth matters more when choosing between schools. Additionally, student demographics affect both parents’ perception of school quality and their likelihood of selecting into a school. This article has important implications for the theory and practice of accountability as it offers new insights on parents’ latent preferences for school qualities.

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2261
Lapo Miccinesi ◽  
Tommaso Consumi ◽  
Alessandra Beni ◽  
Massimiliano Pieraccini

Interferometric radars are widely used for static and dynamic monitoring of large structures such as bridges, culverts, wind turbine towers, chimneys, masonry towers, stay cables, buildings, and monuments. Most of these radars operate in Ku-band (17 GHz). Nevertheless, a higher operative frequency could allow the design of smaller, lighter, and faster equipment. In this paper, a fast MIMO-GBSAR (Multiple-Input Multiple-Output Ground-Based Synthetic Aperture Radar) operating in W-band (77 GHz) has been proposed. The radar can complete a scan in less than 8 s. Furthermore, as its overall dimension is smaller than 230 mm, it can be easily fixed to the head of a camera tripod, which makes its deployment in the field very easy, even by a single operator. The performance of this radar was tested in a controlled environment and in a realistic case study.

2021 ◽  
Oliver-Denzil Taylor ◽  
Amy Cunningham, ◽  
Robert Walker ◽  
Mihan McKenna ◽  
Kathryn Martin ◽  

Seismometers installed within the upper metre of the subsurface can experience significant variability in signal propagation and attenuation properties of observed arrivals due to meteorological events. For example, during rain events, both the time and frequency representations of observed seismic waveforms can be significantly altered, complicating potential automatic signal processing efforts. Historically, a lack of laboratory equipment to explicitly investigate the effects of active inundation on seismic wave properties in the near surface prevented recreation of the observed phenomena in a controlled environment. Presented herein is a new flow chamber designed specifically for near-surface seismic wave/fluid flow interaction phenomenology research, the ultrasonic near-surface inundation testing device and new vp-saturation and vs-saturation relationships due to the effects of matric suction on the soil fabric.

2021 ◽  
Ricardo Pinheiro ◽  
Sidney Lima ◽  
Danilo Souza ◽  
Sthéfano Silva ◽  
Petrônio Lopes ◽  

Abstract Background and Objective: Java vulnerabilities correspond to 91% of all exploits observed on the World Wide Web. Then, this present work aims to create an antivirus software with machine learning and artificial intelligence, master in Java malwares detection.. Methods: Within the proposed methodology, the suspect Jar sample is executed in order to infect, intentionally, Windows OS monitored in a controlled environment. In all, our antivirus monitors and ponders, statistically, 6,824 actions that the suspected Jar file can do when executed. Results: Our antivirus achieves an average performance of 91.58% in the distinction between benign and malwares Jar files. Different initial conditions, learning functions and architectures of our antivirus are investigated in order to maximize their accuracy.Conclusions: The limitations of commercial antiviruses can be supplied by intelligent antiviruses.Instead of blacklist-based models, our antivirus allows Jar malware detection in a preventive way and not in a reactive manner as Oracle's Java and traditional antivirus modus operandi.

2021 ◽  
Vol 4 (S2) ◽  
Anders Clausen ◽  
Krzysztof Arendt ◽  
Aslak Johansen ◽  
Fisayo Caleb Sangogboye ◽  
Mikkel Baun Kjærgaard ◽  

AbstractModel Predictive Control (MPC) can be used in the context of building automation to improve energy efficiency and occupant comfort.Ideally, the MPC algorithm should consider current- and planned usage of the controlled environment along with initial state and weather forecast to plan for optimal comfort and energy efficiency.This implies the need for an MPC application which 1) considers multiple objectives, 2) can draw on multiple data sources, and 3) provides an approach to effectively integrate against heterogeneous building automation systems to make the approach reusable across different installations.To this end, this paper presents a design and implementation of a framework for digital twins for buildings in which the controlled environments are represented as digital entities. In this framework, digital twins constitute parametrized models which are integrated into a generic control algorithm that uses data on weather forecasts, current- and planned occupancy as well as the current state of the controlled environment to perform MPC. This data is accessed through a generic data layer to enable uniform data access. This enables the framework to switch seamlessly between simulation and real-life applications and reduces the barrier towards reusing the application in a different control environment.We demonstrate an application of the digital twin framework on a case study at the University of Southern Denmark where a digital twin has been used to control heating and ventilation.From the case study, we observe that we can switch from rule-based control to model predictive control with no immediate adverse effects towards comfort or energy consumption. We also identify the potential for an increase in energy efficiency, as well as introduce the possibility of planning energy consumption against local electricity production or market conditions, while maintaining occupant comfort.

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