Drying is one of the oldest methods for food preservation that removes the water from fruit and makes it available for consumption throughout the year. Dried fruits can be produced by small- and ...large-scale processors, which makes them a very popular food among consumers and food manufacturers. The most frequent uses of drying technology include osmotic dehydration, vacuum drying, freeze-drying and different combinations of other drying technologies. However, drying may provoke undesirable changes with respect to physiochemical, sensory, nutritional and microbiological quality. Drying process energy efficiency and the quality of dried fruits are crucial factors in fruit drying. Recently, innovative technologies such as ultrasound, pulsed electric field and high pressure may be used as a pretreatment or in combination with traditional drying technologies for process intensification. This could result in quality improvements of dried fruits and enhanced efficiency and capacity of the production process, with a positive impact on environmental and economic benefits.
Infrared camera on a butterfly's wing Grujić, Dušan; Vasiljević, Darko; Pantelić, Dejan ...
Optics express,
2018-May-28, 2018-05-28, 20180528, Volume:
26, Issue:
11
Journal Article
Peer reviewed
Open access
Thermal cameras were constructed long ago, but working principles and complex technologies still limit their resolution, total number of pixels, and sensitivity. We address the problem of finding a ...new sensing mechanism surpassing existing limits of thermal radiation detection. Here we reveal the new mechanism on the butterfly wing, whose wing-scales act as pixels of an imaging array on a thermal detector. We observed that the tiniest features of a Morpho butterfly wing-scale match the mean free path of air molecules at atmospheric pressure - a condition when the radiation-induced heating produces an additional, thermophoretic force that deforms the wing-scales. The resulting deformation field was imaged holographically with mK temperature sensitivity and 200 Hz response speed. By imitating butterfly wing-scales, the effect can be further amplified through a suitable choice of material, working pressure, sensor design, and detection method. The technique is universally applicable to any nano-patterned, micro-scale system in other spectral ranges, such as UV and terahertz.
The authors provide an analysis of the nature of speech signal and processing, corresponding machine learning algorithms, and applied computational intelligence in order to give an insight into ...several fields, covering speech production and auditory perception, cognitive aspects of speech communication and language understanding, both speech recognition and text-to-speech synthesis in more detail, and consequently the main directions in development of spoken dialogue systems. The authors have demonstrated that through establishing a typical satellite communication system simulation platform, compared with the orthogonal signal tracking (OMP) and iterative sorting least squares (IORLS) algorithms, the proposed deep learning network algorithm has better performance in different conditions of SNR, CINR, and carrier frequency offset interference. By providing a variety of applications, from traditional signal processing areas such as speech, image, and medical signal processing to the applications for analysis of legal matters and civil engineering, we have shown that whatever our primary research area is, machine learning and signal processing techniques can significantly improve the performance of existing methods and enable emersion of novel approaches.
Agriculture is a growing field of research. In particular, crop prediction in agriculture is critical and is chiefly contingent upon soil and environment conditions, including rainfall, humidity, and ...temperature. In the past, farmers were able to decide on the crop to be cultivated, monitor its growth, and determine when it could be harvested. Today, however, rapid changes in environmental conditions have made it difficult for the farming community to continue to do so. Consequently, in recent years, machine learning techniques have taken over the task of prediction, and this work has used several of these to determine crop yield. To ensure that a given machine learning (ML) model works at a high level of precision, it is imperative to employ efficient feature selection methods to preprocess the raw data into an easily computable Machine Learning friendly dataset. To reduce redundancies and make the ML model more accurate, only data features that have a significant degree of relevance in determining the final output of the model must be employed. Thus, optimal feature selection arises to ensure that only the most relevant features are accepted as a part of the model. Conglomerating every single feature from raw data without checking for their role in the process of making the model will unnecessarily complicate our model. Furthermore, additional features which contribute little to the ML model will increase its time and space complexity and affect the accuracy of the model's output. The results depict that an ensemble technique offers better prediction accuracy than the existing classification technique.
This study aimed to determine the effects of osmotic dehydration on the kinetics of hot air drying of apricot halves under conditions that were similar to the industrial ones. The osmotic process was ...performed in a sucrose solution at 40 and 60 °C and concentrations of 50% and 65%. As expected increased temperatures and concentrations of the solution resulted in increased water loss, solid gain and shrinkage. The kinetics of osmotic dehydration were well described by the Peleg model. The effective diffusivity of water 5.50–7.387 × 10−9 m2/s and solute 8.315 × 10−10–1.113 × 10−9 m2/s was calculated for osmotic dehydration. Hot air drying was carried out at 40, 50, and 60 °C with air flow velocities of 1.0 m/s and 1.5 m/s. The drying time shortened with higher temperature and air velocity. The calculated effective diffusion of water was from 3.002 × 10−10 m2/s to 1.970 × 10−9 m2/s. The activation energy was sensitive to selected air temperatures, so greater air velocity resulted in greater activation energy: 46.379–51.514 kJ/mol, and with the osmotic pretreatment, it decreased to 35.216–46.469 kJ/mol. Osmotic dehydration reduced the effective diffusivity of water during the hot air drying process. It also resulted in smaller shrinkage of apricot halves in the hot air drying process.
In this study, the optical design of a solar parabolic dish concentrator is
presented. The parabolic dish concentrator consists from 11 curvilinear
trapezoidal reflective petals made of polymethyl ...methacrylate with special
reflective coating. The dish diameter is equal to 3.8 m and the theoretical
focal point distance is 2.26 m. Numerical simulations are made with the
commercial software TracePro from Lambda Research, USA, and the final optimum
position between absorber and reflector was calculated to 2.075 m; lower than
focus distance. This paper presents results for the optimum position and the
optimum diameter of the receiver. The decision for selecting these parameters
is based on the calculation of the total flux over the flat and corrugated
pipe receiver surface; in its central region and in the peripheral region.
The simulation results could be useful reference for designing and optimizing
of solar parabolic dish concentrators as for as for CFD analysis, heat
transfer and fluid flow analysis in corrugated spiral heat absorbers.
Agriculture is one of the most important activities that produces crop and food that is crucial for the sustenance of a human being. In the present day, agricultural products and crops are not only ...used for local demand, but globalization has allowed us to export produce to other countries and import from other countries. India is an agricultural nation and depends a lot on its agricultural activities. Prediction of crop production and yield is a necessary activity that allows farmers to estimate storage, optimize resources, increase efficiency and decrease costs. However, farmers usually predict crops based on the region, soil, weather conditions and the crop itself based on experience and estimates which may not be very accurate especially with the constantly changing and unpredictable climactic conditions of the present day. To solve this problem, we aim to predict the production and yield of various crops such as rice, sorghum, cotton, sugarcane and rabi using Machine Learning (ML) models. We train these models with the weather, soil and crop data to predict future crop production and yields of these crops. We have compiled a dataset of attributes that impact crop production and yield from specific states in India and performed a comprehensive study of the performance of various ML Regression Models in predicting crop production and yield. The results indicated that the Extra Trees Regressor achieved the highest performance among the models examined. It attained a R-Squared score of 0.9615 and showed lowest Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) of 21.06 and 33.99. Following closely behind are the Random Forest Regressor and LGBM Regressor, achieving R-Squared scores of 0.9437 and 0.9398 respectively. Moreover, additional analysis revealed that tree-based models, showing a R-Squared score of 0.9353, demonstrate better performance compared to linear and neighbors-based models, which achieved R-Squared scores of 0.8568 and 0.9002 respectively.
Design and manufacturing of customized implants is a field that has been rapidly developing in recent years. This paper presents an originally developed method for designing a 3D model of customized ...anatomically adjusted implants. The method is based upon a CT scan of a bone fracture. A CT scan is used to generate a 3D bone model and a fracture model. Using these scans, an indicated location for placing the implant is recognized and the design of a 3D model of customized implants is made. With this method it is possible to design volumetric implants used for replacing a part of the bone or a plate type for fixation of a bone part. The sides of the implants, this one lying on the bone, are fully aligned with the anatomical shape of the bone surface which neighbors the fracture. The given model is designed for implants production utilizing any method, and it is ideal for 3D printing of implants.
•Conducted an analysis of fault tolerant LCDMA-based interconnect candidates.•Described structures for LCDMA–DLC, LCDMA–TMR and LCDMA–TSV schemes.•Inserted additional evaluations of both FPGA and ...ASIC implementations.•Discussed the benefits of using LCDMA–DLC architecture.•Concerned application of the LCDMA–DLC interconnection architecture.
High computing capabilities and limited number of input/output pins of modern integrated circuits require an efficient and reliable interconnection architecture. The proposed communication scheme allows a large number of IP cores to send data over a single wire using logic code division multiple access (LCDMA) technique. Reliability is increased by using hardware redundancy, and three LCDMA-based fault tolerant designs are proposed: (a) duplication with logic comparison (DLC), (b) conventional triple modular redundancy (TMR), and (c) triple modular redundancy with sign voter (TSV). With aim to detect a received bit from chip sequence, LCDMA–DLC and LCDMA–TSV designs compare absolute values of the sums, while LCDMA–TMR compares only sign bits of the sums generated at the outputs of decoders. All proposed designs are implemented in FPGA and ASIC technologies. MATLAB simulation results show that increasing the length of spreading codes affects to an increase in reliability. A comparative analysis of the proposed fault tolerant designs in terms of hardware complexity, latency, power consumption and error detecting and correcting capability is conducted. It is shown that LCDMA–DLC design has lower hardware overhead and power consumption, with satisfactory better bit error rate (BER) performance, in comparison to LCDMA–TMR and LCDMA–TSV approach.
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