All That Law! Cardozo Law Revue

Night of musical comedy with special guests.https://larc.cardozo.yu.edu/flyers-2017-2018/1072/thumbnail.jp

Classification of potatoes according to their cultivated field by SVM and KNN approaches using an electronic nose

In this article, we propose a homemade electronic nose to distinguish between two types of potatoes: the first type is traditionally treated with donkey and sheep manure, and the other type is treated with chicken manure. The proposed tool consists of a network of commercial metal oxide sensors, a data acquisition card, and a personal computer for data pre-processing and processing. Two methods were used, namely, support vector machines (SVM) and k-nearest neighbors (KNN) with 5-fold cross-validation and which achieved the same success rate of 97.5%. These results demonstrate that our concept, which is quick, simple, and inexpensive, can discriminate between potatoes based on the method of fertilization used in the field

Comparison between PI and PR Current Controllers of a Grid- Connected Photovoltaic System Under Load Variation

This paper presents a current control technique for a three-phase grid-connected DC /AC inverter which is used in photovoltaic systems. A Proportional-Resonant (PR) controller is used for replacing the conventional Proportional-Integral (PI) controller in this system. By comparison with the conventional PI control method, the PR control can introduce an infinite gain at the fundamental frequency and hence can achieve zero steady-state error. The proposed model is based on two control loops: the first control loop regulates DC link voltage and the second one is used to keep the injected current to the grid in phase with the voltage by means of a Phase Locked Loop (PLL) in order to achieve a unit power factor and to adjust the output power as required. In order to examine the effectiveness of the suggested control, a simulation using the Matlab/Simulink software has been done and it’s concluded from the simulation results that the presented control by using the PR controller can be able to maintain maximum active power and to keep always a unity power factor despite variation load

PEGASUS Centrifugal Particle Receiver CentRec300S - Optimization, Manufacturing and Test

The centrifugal particle receiver (CentRec®) developed by DLR for high-temperature solar applications, previously tested on sun in a 500 kWth prototype at the solar tower in Jülich was further developed and tested at slightly smaller scale of 300 kWth. The test with artificial sunlight provided more stationary and controllable boundary conditions. Outlet temperature of 681 °C was reached at an irradiating input power of 214 kW. The performance was determined with particle mass flow and temperature measurement systems. The data confirms the thermodynamic model for this receiver, indicating an extrapolated performance of 81% at nominal conditions

Initial Performance Outlook on the Sliding Particle Receiver (SlideRec)

The next generation of central receivers is expected to reach high outlet temperatures of 800 °C and above, maintain stable operation and react to a varying incoming flux magnitude caused by hourly and seasonal variations, endure high-temperature operation, and remain cost-effective. Particle-based central receivers are being considered due to their high-temperature durability and favorable thermal properties of particle materials such as bauxite particles. This paper describes a new particle-based central receiver concept and provides an initial exploration of its performance in comparison with the existing CentRec® technology. Discrete Element Method (DEM) simulations demonstrated that a stable falling and sliding particle film can be achieved inside the SlideRec. The residence time of particle flow within the SlideRec is estimated to be higher than a falling particle receiver and similar to that of an obstructed-flow receiver. The results of the thermal model (incorporating reflective, radiative, convective and conductive heat losses) indicate that the SlideRec demonstrates a higher thermal efficiency than the CentRec® under an incoming aperture flux of between 0.1 MW/m2 and 1.7 MW/m2. The concept therefore is promising and is recommended for further experimental exploration

An Electronic Nose for Reliable Measurement and Correct Classification of Beverages

This paper reports the design of an electronic nose (E-nose) prototype for reliable measurement and correct classification of beverages. The prototype was developed and fabricated in the laboratory using commercially available metal oxide gas sensors and a temperature sensor. The repeatability, reproducibility and discriminative ability of the developed E-nose prototype were tested on odors emanating from different beverages such as blackcurrant juice, mango juice and orange juice, respectively. Repeated measurements of three beverages showed very high correlation (r > 0.97) between the same beverages to verify the repeatability. The prototype also produced highly correlated patterns (r > 0.97) in the measurement of beverages using different sensor batches to verify its reproducibility. The E-nose prototype also possessed good discriminative ability whereby it was able to produce different patterns for different beverages, different milk heat treatments (ultra high temperature, pasteurization) and fresh and spoiled milks. The discriminative ability of the E-nose was evaluated using Principal Component Analysis and a Multi Layer Perception Neural Network, with both methods showing good classification results

Detection and Classification of Human Body Odor Using an Electronic Nose

An electronic nose (E-nose) has been designed and equipped with software that can detect and classify human armpit body odor. An array of metal oxide sensors was used for detecting volatile organic compounds. The measurement circuit employs a voltage divider resistor to measure the sensitivity of each sensor. This E-nose was controlled by in-house developed software through a portable USB data acquisition card with a principle component analysis (PCA) algorithm implemented for pattern recognition and classification. Because gas sensor sensitivity in the detection of armpit odor samples is affected by humidity, we propose a new method and algorithms combining hardware/software for the correction of the humidity noise. After the humidity correction, the E-nose showed the capability of detecting human body odor and distinguishing the body odors from two persons in a relative manner. The E-nose is still able to recognize people, even after application of deodorant. In conclusion, this is the first report of the application of an E-nose for armpit odor recognition

Sensor characterization for multisensor odor-discrimination system

In recent years, with the advent of new and cheaper sensors, the use of olfactory systems in homes, industries, and hospitals has a new start. Multisensor systems can improve the ability to distinguish between complex mixtures of volatile substances. To develop multisensor systems that are accurate and reliable, it is important to take into account the anomalies that may arise because of electronic instabilities, types of sensors, and air flow. In this approach, 32 metal oxide semiconductor sensors of 7 different types and operating at different temperatures have been used to develop a multisensor olfactory system. Each type of sensor has been characterized to select the most suitable temperature combinations. In addition, a prechamber has been designed to ensure a good air flow from the sample to the sensing area. The multisensor system has been tested with good results to perform multidimensional information detection of two fruits, based on obtaining sensor matrix data, extracting three features parameters from each sensor curve and using these parameters as the input to a pattern recognition system. (C) 2012 Elsevier B.V. All rights reserved.Cueto Belchí, AD.; Rothpfeffer, N.; Pelegrí Sebastiá, J.; Chilo, J.; García Rodríguez, D.; Sogorb Devesa, TC. (2013). Sensor characterization for multisensor odor-discrimination system. Sensors and Actuators A: Physical. 191:68-72. doi:10.1016/j.sna.2012.11.039S687219

A Wireless Electronic Nose System Using a Fe2O3 Gas Sensing Array and Least Squares Support Vector Regression

This paper describes the design and implementation of a wireless electronic nose (WEN) system which can online detect the combustible gases methane and hydrogen (CH4/H2) and estimate their concentrations, either singly or in mixtures. The system is composed of two wireless sensor nodes—a slave node and a master node. The former comprises a Fe2O3 gas sensing array for the combustible gas detection, a digital signal processor (DSP) system for real-time sampling and processing the sensor array data and a wireless transceiver unit (WTU) by which the detection results can be transmitted to the master node connected with a computer. A type of Fe2O3 gas sensor insensitive to humidity is developed for resistance to environmental influences. A threshold-based least square support vector regression (LS-SVR)estimator is implemented on a DSP for classification and concentration measurements. Experimental results confirm that LS-SVR produces higher accuracy compared with artificial neural networks (ANNs) and a faster convergence rate than the standard support vector regression (SVR). The designed WEN system effectively achieves gas mixture analysis in a real-time process