Study of PVDF/ (Co-ZnFe2O4 and Cu-ZnFe2O4) nanocomposite for the piezo-phototronics applications

Polyvinylidene fluoride (PVDF) polymer is considered as a promising piezoelectric material whose optical properties need to be improved. Zinc ferrite is an excellent photoelectric material, in the present work it was doped separately by both cobalt and copper. Co-ZnFe2O4 and Cu-ZnFe2O4 nanoparticles were synthesized and characterized to be used as PVDF fillers, aiming to improve its optical properties. The optical properties as well as, the piezoelectric response of the prepared PVDF/ (Co-ZnFe2O4 and Cu-ZnFe2O4) nanocomposites were investigated. A remarkable improvement in the PVDF relative permittivity, optical conductivity, refractive index, non-linear susceptibility, and a great reduction in the band gap energy value is obtained by adding Co-ZnFe2O4 nanoparticles to it. However, Cu-ZnFe2O4 nanoparticles have limited improvement of the PVDF optical properties compared to the Co-ZnFe2O4 nanoparticles. The piezoelectric response of the PVDF polymer is clearly increased by the addition of both Co-ZnFe2O4 and Cu-ZnFe2O4 nanoparticles.

Multimodal Biometric Person Authentication Using Face, Ear and Periocular Region Based on Convolution Neural Networks

Biometrics is an active area of research because of the increase in need for accurate person identification in numerous applications ranging from entertainment to security. Unimodal and multimodal are the well-known biometric methods. Unimodal biometrics uses one biometric modality of a person for person identification. The performance of an unimodal biometric system is degraded due to certain limitations such as: intra-class variations and nonuniversality. The person identification using more than one biometric modality of a person is multimodal biometrics. This method of identification has gained more interest due to resistance on spoof attacks and more recognition rate. Conventional methods of feature extraction have difficulty in engineering features that are liable to more variations such as illumination, pose and age variations. Feature extraction using convolution neural network (CNN) can overcome these difficulties because large dataset with robust variations can be used for training, where CNN can learn these variations. In this paper, we propose multimodal biometrics at feature level horizontal fusion using face, ear and periocular region biometric modalities and apply deep learning CNN for feature representation and also we propose face, ear and periocular region dataset that are robust to intra-class variations. The evaluation of the system is made by using proposed database. Accuracy, Precision, Recall and [Formula: see text] score are calculated to evaluate the performance of the system and had shown remarkable improvement over existing biometric system.

A Novel MPPT Design for a Partially Shaded PV System Using Spotted Hyena Optimization Algorithm

Partial shading is a common problem in photovoltaic (PV) systems, known for its difficulty. Numerous attempts have been conducted to mitigate this problem. Some of these efforts deploy metaheuristic optimization with a view to tracking the multiple-peak P–V curve in a partial shading PV system. Hence, this paper proposes a novel metaheuristic algorithm to track the maximum power point of PV systems using the Spotted Hyena Optimization (SHO) algorithm. When evaluated, the SHO algorithm proved to be very fast, robust, and accurate in standard conditions, Partial Shading Conditions (PSCs), and irradiance variations. Also, the results reveal a remarkable improvement in the performance when we compare the SHO algorithm with the Grey Wolf Optimization (GWO) algorithm and the Perturb and Observe (P&O) algorithm.

Ayurvedic Management on Vicharchika- A case study

Vicharchika is often correlated to eczema based on the clinical presentation. Eczema is a form of dermatitis. As per Ayurvedic texts Vicharchika is characterized by symptoms namely kandu (itching), srava (discharge), pidaka (vesicles) and shyava vrana (discolouration). No satisfactory treatment is available in contemporary medical practice except antihistamines and topical steroids. A 55 years old female patient approached to OPD with chief complains of discharge, edema, erythematous skin lesion and intense itching at right ankle region. Line of treatment plan was Raktamokshana as shodhana upkarma and Shaman aushadhi according to dosh dushya samurchana. Remarkable improvement was observed within span of 30 days of commencement of treatment.

Flexible open-shop problem for minimizing weighted total completion time

In this article, scheduling flexible open shops with identical machines in each station is studied. A new mathematical model is offered to describe the overall performance of the system. Since the problem enjoys an NP-hard complexity structure, we used two distinct metaheuristic methods to achieve acceptable solutions for minimizing weighted total completion time as the objective function. The first method is customary memetic algorithm (MA). The second one, MPA, is a modified version of memetic algorithm in which the new permutating operation is replaced with the mutation. Furthermore, some predefined feasible solutions were imposed in the initial population of both MA and MPA. According to the results, the latter action caused a remarkable improvement in the performance of algorithms.

Research on Model Compression for Embedded Platform through Quantization and Pruning

So far, artificial intelligence has gone through decades of development. Although artificial intelligence technology is not yet mature, it has already been applied in many walks of life. With the explosion of IoT technology in 2019, artificial intelligence has ushered in a new climax. It can be said that the development of IoT technology has led to the development of artificial intelligence once again. But the traditional deep learning model is very complex and redundant. The hardware environment of IoT can not afford the time and resources cost by the model which runs on the GPU originally, so model compression without decreasing accuracy rate so much is applicable in this situation. In this paper, we experimented with using two tricks for model compression: Pruning and Quantization. By utilizing these methods, we got a remarkable improvement in model simplification while retaining a relatively close accuracy.

Impact of Radio Occultation Data on the Prediction of Typhoon Haishen (2020) with WRFDA Hybrid Assimilation

FORMOSAT-7/COSMIC-2 (FS7/C2) satellite was successfully launched in June 2019. The satellite provides about 5000 radio occultation (RO) soundings daily over the tropical and partial subtropical regions. Such plentiful RO soundings with high accuracy and vertical resolution could be used to improve model initial analysis for typhoon prediction. In this study, assimilation experiments with and without the RO data were conducted with the WRFDA hybrid system for the prediction of Typhoon Haishen (2020). The experimental results show a remarkable improvement in typhoon track prediction with RO data assimilation, especially when using a nonlocal refractivity operator. Results in cycling DA and forecast are analyzed and verified for the RO data impact. Diagnostics of potential vorticity (PV) tendency budget helps explain the typhoon translation induced by different physical processes in the budget. The typhoon translation is essentially dominated by horizontal PV advection, but the track deviation can increase due to the vertical PV advection with opposite effects in the absence of RO data. Sensitivity experiments for different model initial times, physics schemes, and RO observation amounts show positive RO data impacts on typhoon prediction, mainly contributed from FS7. Complementary, an improved forecast of Typhoon Hagupit (2020) is also illustrated for the RO data impact.

The Political Economy of China's Dramatically Improved Coal Safety Record

China's coal safety has improved dramatically since 2003. This article will present the official data and conclude that it is almost impossible that the figures conceal a situation where there has not been remarkable improvement. Structural factors including China's level of economic development, changes in the labour market and the economic health of the industry have played an important role, but state commitment and policies have been central at least to the speed and magnitude of the improvement.