Miracle-dz/UniFAR-FTUs huggingface dataset:
The Face Mask Detection Technology for Image Analysis in the Covid-19 Surveillance System

Face mask recognition has been growing rapidly after corona insistent last years for its multiple uses in the areas of Law Enforcement Security purposes and other commercial uses Face appears spreading others to corona a novel approach to perform face new line detection and face mask recognition is proposed. The proposed system to classify face mask detection using COVID-19 precaution both in images and videos using convolution neural network. Extensive experimentation on the datasets and the performance evaluation of the proposed methods are exhibited. Further, we made a successful attempt to preserve inter and intra class variations of face mask detection using symbolic approach. We studied the different classifiers like Support Vector Machine and a Symbolic Classifier. The project is developed as a prototype to monitor temperature measurement and to detect mask for the people. The first method is performed using temperature sensor used to detect the present temperature of the body and automatically spray the sanitizer. In the second method, the work is designed to provide a safety system for the people in order to avoid COVID-19. We proposed continuous monitoring of the people conditions and store the people’s data in the server using the Deep learning concept. In order to investigate the performance the proposed method an extensive experimentation is conducted on 50 various Image dataset. We conducted experimentation under varying of training and testing percentage for 10 random trails. From the results we could observe that, the results obtained for symbolic approach is better than the conventional approach.
Artocarpus heterophyllus leaves extract improve facial skin in clay mask formulation

Artocarpus heterophyllus (A.heterophyllus) is one of plants that commonly used for skin care. This study aimed to formulate a clay mask preparation with the active ingredient A.heterophyllus 3% leaf extract and evaluating its activities in repairing facial moisture, smoothness, large pores, blemishes and wrinkles. The process of providing clay masks begins with the preparation of Artocarpus heterophyllus leaf etanol extracts with standardized quality, preparation of clay mask bases with guaranteed quality, mixing clay mask bases with extracts, testing the quality and stability and effectiveness of skin care tested. The extract of clay mask formulations were stable in storage, homogeneous, pH 5.6-6.3; drying time is 10-18 minutes, and does not irritate. Effectiveness testing was performed using a skin analyzer for 4 weeks of treatment in adult female volunteers. Test results after 4 weeks of treatment showed that the ethanol extract of A. heterophyllus leaves 3% was able to improve moisture (15.5%), smoothness (33.1%), pore size (60.1%), blemishes (50.2%) and facial wrinkles (61.5%). Statistically, significant effects were found in moisture and smoothnes of the facial skin (p < 0.05). This study concluded that ethanol extract of A. heterophyllus in concentration of 3% have benefit in refining facial skin.
Low Carbon Policy and Sustainable Development of Environment of the Indigenous Ceremonial Holiday in Taitung County, Taiwan

Low-carbon tourism is an emerging topic that the tourism industry and academia have paid attention to in recent years. In the past, many researchers have designed low-carbon tourism package itinerary from the point of view of practitioners, and rarely used the view of policy operation to guide self-service tourists how to engage in energy-saving and carbon reduction behaviour in tourism. The purpose of this study is to analyse the government departments in Taitung County, Taiwan as a case study on how to guide and promote the activities of participants in energy conservation and carbon reduction during ceremonial holiday. This study draws preliminary conclusions that the key to the success of low-carbon tourism lies in the specific implementation of government policies. In addition, the key to success is that people can abide by the law and government policies. There is also communication with indigenous tribes about low-carbon practices, and the use of mass media and school to promote this policy.
Neural networks and some practical applications in the field of artificial intelligence

Even since Antiquity, in ancient Greece 4th century BC, or in China, the 3rd century BC, but not only there, people have imagined and even created automatic mechanisms, mechanisms that somehow were trying to be shy replicas of real examples of intelligent life from nature, including replicas of Man’s creation, such as the first bronze man, but nonetheless, non-intelligent replicas. Subsequently, in the modern age, attempts have been made to simulate a human neural network, as well as the first steps towards artificially simulating the functioning of the human brain. We will present in this article concepts of neural networks and some practical applications in the field of artificial intelligence and their capabilities to simulate autonomous thinking through advanced programming and complex assimilation of large data sets, using the three major learning paradigms, namely: supervised learning, unsupervised learning, and reinforcement learning. All these new concepts, over the past 75 years, and the advances in information technology have led to the emergence and development of practical applications of artificial intelligence. In this way, the human dream of creation tends to live and fulfil itself, why not, even in the coming years.
Lip Reading using CNN Lip Deflection Classifier and GAN Two-Stage Lip Corrector

Lip reading is a task to infer the content of speech through the movement of the lips, which is a technology with wide application prospects. Thanks to the development of deep learning technology and the proposal of large-scale datasets, lip reading has made great progress. However, these large-scale datasets contain only small angle lip deflection which is different with the wild environment. Most networks based on these datasets take some simple methods to correct the lip deflection that led to performance degradation when in the wild. In this work, we proposed a very challenging dataset with large angle lip deflection and multiple speakers to simulate the wild environment, and we designed a lip deflection classifier based on Convolutional Neural Network and a two-stage corrector based on Generative Adversarial Network. We use these two models to correct the lip deflection and improve the recognition accuracy. Our proposed method achieves an absolute improvement of 18.3% and 7.4%, respectively, compared with no preprocessing and just face alignment, which shows that our proposed network is more suitable to correct the large angle lip deflection in the wild.
Educational animation: Environmentally friendly palm oil based products

The size of the palm oil industry in Indonesia raises concerns about environmental sustainability, but on the other hand, this industry is also needed by the community. It has led to the emergence of organizations or institutions that apply certification standards in the palm oil industry, one of which is the Roundtable on Sustainable Palm Oil (RSPO). This animation is created to introduce the RSPO and invite the audience to understand the products made from palm oil that care about the environment. The message delivered about RSPO-labeled products is that the products are more responsible for sustainable environmental issues. This animation production method goes through pre-production stages that focus on the core message, production in the form of visual asset design to the animation process, and post-production for artistic finishing touches. The final result is an educative animated film that is easy to understand and packaged with an attractive design.
Effect of flow velocity and pressure on carotid artery due to deposition of different shapes of plaque

Atherosclerosis is the disease progressed because of the deposition of stenosisat the interior walls of arteries which results in reducing the size and causing blockage in the carotid artery leading to brain attack or stroke. Twodimensional model of carotid artery is designed and analyzed by Computational Fluid Dynamics (CFD). Designing of general analytical model of artery followed by meshing of geometry, application of boundary conditions and analysis is done with ANSYS Fluent 16.2. The objective of this research is to analyze the consequence of flow velocity and pressure on the arteries having blockage to assess the diseases related to carotid artery. This paper provides analytical analysis of flow velocity and pressure on the artery due to deposition of different shapes of plaque. We consider plaque shape1, plaque shape2, cosine plaque and irregular plaque shapes. Hemodynamic variables like velocity and pressure differ with commute mostly in the shape of geometry. It’s found that velocity is maximal at the constraint as compared to pre- and post-stenotic areas which shows that the artery having more stenosis area has maximum pressure and velocity on the wall of the artery.
Bardeen black hole surrounded by perfect fluid dark matter

We derive an exact solution for a spherically symmetric Bardeen black hole surrounded by perfect fluid dark matter (PFDM). By treating the magnetic charge g and dark matter parameter as thermodynamic variables, we find that the first law of thermodynamics and the corresponding Smarr formula are satisfied. The thermodynamic stability of the black hole is also studied. The results show that there exists a critical radius where the heat capacity diverges, suggesting that the black hole is thermodynamically stable in the range . In addition, the critical radius increases with the magnetic charge g and decreases with the dark matter parameter . Applying the Newman-Janis algorithm, we generalize the spherically symmetric solution to the corresponding rotating black hole. With the metric at hand, the horizons and ergospheres are studied. It turns out that for a fixed dark matter parameter , in a certain range, with the increase of the rotation parameter a and magnetic charge g, the Cauchy horizon radius increases while the event horizon radius decreases. Finally, we investigate the energy extraction by the Penrose process in a rotating Bardeen black hole surrounded by PFDM.
Assessment of the models for predicting the responses of spherical objects in viscoelastic mediums and at viscoelastic interfaces

Spherical objects, such as bubbles and spheres, embedded in mediums and at viscoelastic interfaces are encountered in many applications, including the determination of material properties. This paper assesses the models for predicting the responses of spherical objects in viscoelastic mediums and at viscoelastic interfaces used in various applications. The models are presented very compactly, and evaluations are performed based on the analyses of the models for the spherical objects in viscoelastic mediums and at viscoelastic interfaces. First, the models for predicting the static displacements of spherical objects are presented and assessed. After that, the models for predicting the dynamic responses of spherical objects are presented and their dynamic behaviours are compared. Then, the models for the deformation of the medium around spherical objects and stress distribution are presented and evaluated. The models and evaluations presented in this study can be exploited in various applications, including biomedical applications.
Monocular Visual Odometry based on joint unsupervised learning of depth and optical flow with geometric constraints

Inferring camera ego-motion from consecutive images is essential in visual odometry (VO). In this work, we present a jointly unsupervised learning system for monocular VO, consisting of single-view depth, two-view optical flow, and camera-motion estimation module. Our work mitigates the scale drift issue which can further result in a degraded performance in the long-sequence scene. We achieve this by incorporating standard epipolar geometry into the framework. Specifically, we extract correspondences over predicted optical flow and then recover ego-motion. Additionally, we obtain pseudo-ground-truth depth via triangulating 2D-2D pixel matches, which makes the depth scale is closely relevant to the pose. Experimentation on the KITTI driving dataset shows competitive performance compared to established methods.
Application of Artificial Intelligence Technology in Electronic Information Engineering

In the development process of artificial intelligence, electronic information engineering technology is indispensable. Electronic information engineering technology support is extremely important for the development of artificial application. This paper describes the related concepts of artificial intelligence and electronic information engineering, and researches and designs the application of artificial intelligence technology in the electronic information engineering platform. Through the analysis, we can see that the system is not There are fatal loopholes, the success rate of data transmission basically meets the demand of more than 80%, and the response time is within 3S, which can also meet the set requirements.
Optical behaviour of γ-black CsPbI3 phases formed by quenching from 80 °C and 325 °C

The orthorhombic γ-black phase of CsPbI3 is well-known to be unstable at room temperature and strategies are needed to counteract its transformation tendency. In this paper we compare γ-black CsPbI3 thin films (∼80 nm) formed via two different routes: a fast quenching of the cubic α-phase from 325 °C (HT-γ) or spontaneously cooling the layer from 80 °C (LT-γ). The successful application of the second procedure is allowed by the use of a mother solution containing Europium with an Eu/Pb ratio as small as 5%. This has been indeed used to form both LT-γ and HT-γ thin films. The phase transition during the heating and cooling pathways is followed in situ by spectroscopic ellipsometry and x-ray diffraction analyses. We demonstrate that both γ-black phases exhibit the same absorption features and critical points as depicted in very details by the dielectric functions. Minor differences can be found in the intensity of the absorption coefficient, assigned to an improved lattice quality in the layer that has experienced the high temperature path. On the other hand, α-black and δ-yellow phases show different critical points in the optical transitions. Besides providing benchmarking optical parameters to discriminates the different phases, we demonstrate that the LT-γ phase closely competes with the HT-γ counterpart during stress tests for stability, with the first one more suited for tandem monolithic architectures that require thermal treatments under 200 °C.
Evolution of Photobioreactors: A Review based on Microalgal Perspective

Energy is indispensable for bringing competence, resilience, and comfort for the ever-advancing human lifestyle. Therefore, to satisfy the growing energy requirement researchers are trying to delve in exploring sustainable and renewable energy sources that will contribute to the reduction of carbon footprint and ultimately help to check the issue of global warming caused by the increased emission of CO2, due to the excessive usage of non-renewable and exhaustive fossil fuels. Microalgae are having the potential which can be exploited to produce biofuels (substitute for fossil fuels) and other value-added compounds. Microalgae is a form of unicellular photoautotrophic microorganism which can attain higher rate of proliferation. Microalgae is having merits over other terrestrial crops and fossil fuels as they have higher productivity of oil per hectare of land. Various other advantages of microalgae include their tolerance in different types of environment because of their ubiquitous nature (in terms of pH, salinity, and temperature). Furthermore, they can be cultivated in nonarable land and wastewater which will resolve the food-fuel duel and problem of freshwater usage, therefore leading towards environmental sustainability. The main factors governing the growth and cultivation of microalgae are light, CO2/air, nutrients, process parameters (pH, temperature, growth medium etc) and most importantly the type of system used for cultivation. The systems usually employed for the cultivation of microalgae are open system (open ponds, raceway ponds, scrubbers), closed system also commonly known as photobioreactors (flat plate and tubular photobioreactors) and hybrid system in which separation of biomass growth and lipid accumulation is achieved in two stages. All the systems have some merits and demerits but photobioreactors are widely accepted and used because they are having an upper hand over open system because of the optimised control of the growth conditions, contamination evasion and efficient productivity of microalgal biomass. This review will provide an insight to different parameters which govern the growth of microalgae and various types of photobioreactors with their advantages and disadvantages. This study will help in the optimized selection of the photobioreactors for a particular species of microalgae because despite the continuous and intensive research going on the cultivation systems it is a challenge for the researchers to achieve a suitable and economically viable system.
Reduction of the unbalance excited vibrations during the resonance passage of a rotor

Many rotor dynamic systems are faced with large oscillation amplitudes while passing through the resonance. The coupled differential equations for the position of the center of the shaft and the rotation angle describe the dynamic behaviour of the rotordynamic system. With an appropriate external excitation the amplitude of the oscillations can be reduced. An unbalance excited oscillator is used to study the effects of a modulated angular velocity, where the angular velocity is prescribed as linear increasing with a superimposed harmonic function. The resulting excitation force is expressed as a series of Bessel functions of the first kind. In order to achieve small amplitudes near the resonance frequency of the system, special conditions for the ratio of the modulation frequency and the angular acceleration and the argument of the Bessel function of the first kind with integer order zero are derived. These requirements are first developed for a linear oscillator with an excitation force. Due to the analogy of the solution of the equation of motion these solutions are then applied directly to an unbalance excited oscillator. The results show smaller displacement amplitudes compared to the case with only linear increasing angular velocity. For the resulting motion the required torque is computed.
Study of the impact of fire-extinguishing foaming agents on agricultural crops

In order to study the qualitative and quantitative effects on living organisms, the toxic effect of foaming agents was assessed. As an object, the use of seeds of sowing oats (Avena sativa) is proposed. It has been established that the development and growth of the root system of the bioindicator directly depends on the degree of soil toxicity. The greatest negative impact on the test object was produced by a nonionic foaming agent at a concentration of 10 mg/l.
A Study on Key LPWAN Technologies

In the ever-changing world of technology, various communication technologies have penetrated people’s daily lives, which has greatly improved people’s work efficiency and quality of life. By means of the Internet and various LAN technologies, users can remotely control their smart home appliances. In addition, the commercial use of 5G networks has contributed to the integration of communication technologies with people’s work and life. Meanwhile, each communication technology has its own advantages and disadvantages. For wireless network technologies, distance and power consumption are always contradictory. LPWAN (Low-Power Wide-Area Network) is a wireless network technology designed to allow long-range communication with low power consumption. Therefore, this paper studied key LPWAN technologies with a focus on the LoRa technology.
Social Distancing Analyzer Using Computer Vision and Deep Learning

In the fight against the coronavirus, social distancing has proven to be an effective measure to hamper the spread of the disease. The system presented is for analyzing social distancing by calculating the distance between people in order to slow down the spread of the virus. This system utilizes input from video frames to figure out the distance between individuals to alleviate the effect of this pandemic. This is done by evaluating a video feed obtained by a surveillance camera. The video is calibrated into bird’s view and fed as an input to the YOLOv3 model which is an already trained object detection model. The YOLOv3 model is trained using the Common Object in Context (COCO). The proposed system was corroborated on a pre-filmed video. The results and outcomes obtained by the system show that evaluation of the distance between multiple individuals and determining if rules are violated or not. If the distance is less than the minimum threshold value, the individuals are represented by a red bounding box, if not then it is represented by a green bounding box. This system can be further developed to detect social distancing in real-time applications.
Improved Parametrization of Li+, Na+, K+, and Mg2+ Ions for All-Atom Molecular Dynamics Simulations of Nucleic Acid Systems

Atomic-scale modeling of compacted nucleic acids has the ability to reveal the inner workings of spectacular biomolecular machines, yet the outcome of such modeling efforts sensitively depends on the accuracy of the underlying computational models. Our molecular dynamics simulations of an array of 64 parallel duplex DNA revealed considerable artifacts of cation–DNA phosphate interactions in CHARMM and AMBER parameter sets: both the DNA arrangement and the pressure inside the DNA arrays were found to be in considerable disagreement with experiment. To improve the models, we fine-tuned van der Waals interaction parameters for specific ion pairs to reproduce experimental osmotic pressure of binary electrolyte solutions of biologically relevant ions. Repeating the DNA array simulations using our parameters produced results consistent with experiment. Our improved parametrization can be directly applied to molecular dynamics simulations of various charged biomolecular systems, including nucleic acids, proteins.
Sdgan: Improve Speech Enhancement Quality by Information Filter

The speech denoising model based on adversarial generative network has achieved better results than the traditional machine learning model. In this paper, for the short cut connection in the generator, we discuss its influence on the information transfer between encoder and decoder, and propose SDGAN at target. SDGAN sets linear and convolution filters in the short cut connection which adaptively learn the optimal information processing. The information filter still enables the generator to solve the gradient vanishing problem, and it can also avoid information redundancy and improve expression ability. In addition, SDGAN replaces the L1 regularization term in loss function with the L2 regularization term, which not only makes the output speech of the generator closer to the clean speech, but also avoids sparsity. In the experiments, SDGAN significantly performs better than other traditional GAN in five performance metrics (such as PESQ), and the effect of convolution filter is better than that of linear filter.