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Hot spots are formed when energetic microstructures are shocked, and they play a critical role in shock sensitivity. It is important to know both the time-dependent size and temperature of the hot spots, in order to generate a kinetic model to describe reaction growth in plastic-bonded explosives (PBX). Here we use a recently developed technique where PBX is fabricated in the form of a thin wafer, embedded within a transparent polymer binder, and shocked with a laser-launched flyer plate that produces pressures of about 30 GPa range. In this method, every crystal of the cyclotetramethylene-tetranitramine (HMX)-based PBX can be observed during the shock. Hot spots can be seen via their thermal emission, which is detected with both a 32-channel optical pyrometer, which gives spatial-average temperatures and emissivities, and an eight-frame nanosecond camera that images hot spots directly with 2 um resolution. Using hyperspectral imaging, we acquire four pairs of time-resolved images using red and blue filters. With simultaneous two-color imaging we can watch temperature and emissivity change with time. [ABSTRACT FROM AUTHOR]

The survival of life on Earth may depend on access to fresh water. Solar distillation has been discovered as a low-cost distillation solution to address the lack of potable water. The treatment of brackish or saltwater using solar distillation and a solar collector may be a straightforward and affordable method. According to earlier studies, coating the basin liner with nanoparticles enhances the efficiency of solar collecting devices. By using nanoparticles, typically metal oxides, this cutting-edge technology boosts the effectiveness of solar stills. Under the conditions of Coimbatore, Tamil Nadu, experimental work was carried out using a basin liner coated with graphene nanoparticles dissolved in black paint on the only single-slope, single-basin solar still (SS-SS). The temperature of the solar still basin is raised by employing nanoparticles dissolved in black paint. According to the study's conclusions, using black paint with nanoparticles dissolved in it at different water levels of 2 cm, 3 cm and 4 cm results in a 40% boost in productivity and a 12.18% improvement in thermal efficiency. Two different kinds of solar stills, with and without nano-coating were made to show the difference in production. This study aims to compare and analyze the improved performance of a single solar basin still using nano-coating, which significantly boosts evaporation speed and efficiency. [ABSTRACT FROM AUTHOR]

Many advances in science are now commonplace in our lives, with many of these applications being interconnected. Due to the tight schedule, certain parents tend to keep their children in parked cars while adopting IOT technology in the protection department. The purpose of this survey is to provide notifications or alerts to parents who are using the most important items that everyone has cell phone. The safety pad and keychain alarm device are two important features of the design. In this article, we recommend a straightforward and reasonably priced capacitive sensor for use in the front seat to assist parents in finding their kids. The intended system to determine the existence of a driver inside a vehicle includes a vehicle ignition monitor. A temperature gauge for the interior of the car is also included. A GSM modem will alert the driver if a child is discovered left in the front seat and it is discovered that the car has been switched off. The capacitive sensor, the measuring technique used, and the warning system that was designed and tested all worked as expected. [ABSTRACT FROM AUTHOR]

Voice pathology can be successfully identified using computer-aided voice pathology categorization approaches. The goal of this research is to develop a tool using deep learning technique to diagnose voice pathological conditions including age and gender aspects. Here, a dataset of vocal pathology is used to train a Convolutional Neural Network (CNN) which is a pre-trained model to improve classification accuracy. The proposed work exhibits a high level of instantaneous, automatic diagnostic and therapeutic alternatives to achieve classification accuracy. Usually, recordings from people of all ages are used to develop algorithms that can recognize speech abnormalities automatically. However, this approach might not be sufficient due to the acoustic changes in the voice brought on by aging naturally. Additionally, it can be more challenging to identify pathological voice since the quality of older voices changes in ways that are comparable to those linked to vocal problems. Research developing methods that automatically account for speaker age to make it easier to identify speech anomalies is therefore of interest. The current study introduces an age/gender based automated classification utilizing both healthy and pathological voice. [ABSTRACT FROM AUTHOR]

In today's technological era, every home, industry, and commercial place has numerous electrical appliances to perform all tasks quickly and with ease. It also mandates every home to have a three-phase electrical supply and leads to a growing increase in energy demand. The traditional and new equipment have been modernized by making them very smart and energy efficient to manage the continuously growing energy demand. In the previous decades, power saving was done during the monitoring of the load alone, which was not very effective. The main objective of this paper is to continuously monitor the power consumption of the load and also to save energy in an efficient way using the Internet of Things (IOT). In a three-phase supply, whenever there is a phase shift, phase angle changes and so it has to be corrected. This system helps to correct the phaseangle automatically during the reverse condition. The IoT devices will be used to share voltage and current values on the website. Power management is also carried out to ensure proper power consumption. The monitoring relay is the main component of the system, and it checks the phase sequence, overvoltage, and undervoltage. A multifunction monitoring relay based on a microcontroller integrates the voltage and current values to calculate the supply's phase angle. The Proteus software was used for the website updates. [ABSTRACT FROM AUTHOR]

In this work, it was selected to focus on the development of multi-element organometallic precursors in the Si/C/Zr system. In addition, various polymer structures have been considered to anticipate the shape controls of these precursors and to modify the chemical composition of the final ceramics. Furthermore, the laser pyrolysis spray process was selected to integrate the micro phase sequence powders to gain access to the microstructure of the final compound material. In order to evaluate the compatibility of the original precursors with this formulation process, this work will take up the spray pyrolysis tests. [ABSTRACT FROM AUTHOR]

Organic food, a rapidly developing market in India, appears to be extremely adaptable in urban areas. In semi-urban and rural locations, the same is quite new. Cultural compatibility is a major factor in the market adoption of new products. In the dimensions of Individualism, uncertainty avoidance, Power distance, and Masculinity, nearly 18 indices have been developed. To assess the instruments' reliability, a reliability test, a KMO test, and a factor analysis were performed to find the components with the highest loading, which were then utilized to create a path model. AGFI, GFI, RMSEA, and CMIN are all within permissible limits. AVE and Composite reliability are also identified to validate the model. It interpret that the dimensions of power distance, uncertainty avoidance, individualism and masculinity has shown the significant relationship with the cultural compatibility on the adoption of organic food product in the Virudhunagar District. [ABSTRACT FROM AUTHOR]

There has been an alarmingly high mortality rate because of cardiovascular diseases since the past few years and some innovative research has been done by scientists and research scholars all over the world to make the pre-emptive detection of these diseases efficient, cheap and accessible to the public. In this paper, we have studied the research and experimentation that has been done on detection and classification of Cardiovascular diseases using Phonocardiogram signals. There are many problems that come with the cheap and democratized process of heart monitoring using Phonocardiogram signals, like environment noise, lung sounds etc. sever a innovative classification and transformation methods that solved these problems and yielded promising results were found in literature. This paper aims at providing a detailed view on such techniques and optimal classification models which yield comparable results and are computationally cheaper. [ABSTRACT FROM AUTHOR]

Parkinson's disease is a neurodegenerative disorder which degrades the quality of life of the affected. Caused due to the reduction in dopamine production in the body, PD causes speech impairments, gait problems, tremors, fatigue, depression in the patients. Speech impairments include monotonous speech, hoarse or rough voice, slurring, while gait problems include short steps, hypokinesia, and instability in posture amongst others. Even with the advancements in medicine, there is no cure for PD nor a systematic procedure to detect it. Parkinson's disease is diagnosed by trained neurologists using extensive and invasive tests which are time consuming and expensive. Therefore, extensive research is being undertaken in developing and training machine learning models to aid the PD detection process so that PD can be detected as early as possible in patients ensuring quality treatment and better quality of life. Several modalities are used as training and testing data for the machine learning models including voice signals, gait signals, hand writing and MRI images. In this paper, literature review has been conducted on research undertaken in PD detection focusing on two biomarkers - speech and gait. Gait and Speech abnormalities are amongst the early manifestations of Parkinson's disease, therefore early detection of PD can be aided by using features extracted from these signals. Furthermore, they are non-intrusive and painless methods, thus making the feature extraction and diagnostic process painless and less complex. [ABSTRACT FROM AUTHOR]

Alzheimer's disease is a very serious neurological disorder. It not only causes dimensioning brain tissues but leads to a memory loss which is almost incurable after a certain stage. Due to this, a huge tally in the number of AD patients and scarcity of proper diagnostic tools, detection and classification is considered to be a challenging area of study. For years, the medical industry has always transpired systematic research and study, proposing alternative methods to detect the presence of Alzheimer's Disease. This provides an opportunity to investigate and learn about this specific neural disease using digital image processing. To understand further, the use of quantitative models based on a widely used specialized softwares, which helps determine the characteristics of iris and landmarking attributed patterns to diagnose the existence of Alzhiemers have been discussed. Here, we also explore various image processing techniques, some of them using a wide range of data bases of brain MRI scans in order to eliminate differences in interindividual brain anatomy. A large amount of research work continues to be in progress for detection and classification of this disease based on brain changes that occur with time. In this paper, we have discussed various detection techniques to identify brain degeneration at an early stage and classification based on various feature extractions and segmentation techniques including landmark based, iridology, fast detection, support vector, transfer learning etc. We have also put forward and compared these several detection and classification mechanisms to understand and analyse in order to opt for a better method that can be helpful so as to achieve desired results with even higher accuracy in the foreseeable future. [ABSTRACT FROM AUTHOR]

Using an IoT analytics platform service, we simulated real-time pipeline monitoring and pinpointed the exact site of pipeline damage in this research. This research uses pressure pulses to monitor pipelines, using vibration in pipes. This work similarly uses the notion of a temporal delay between the arrival of pulses at sensor sites. The Thing Speak internet of things (IoT) analytics platform interfaces with a wireless communication device built with an Arduino and a Wi-Fi module. An experiment rig that employed a wireless connection device called for five channels of data collection on the platform. All tracks were refreshed every two minutes, and every 15 seconds signal data were recorded. The wireless communication device's data was instantly visualized using Thing Speak. The data was analyzed and processed online as soon as it was received. Data were processed on a second test rig developed with an onboard data logger. The recorded pulse propagation velocity was 355 m/s. Between 4.243 and 4.246 m, the 50 measurements yielded event location estimations. Compared to the measured event location of 4.23 m, this had a dispersion of only 3 mm, It was found that the wireless communication device performed as well as the data logger when used for real-time monitoring of pipelines, according to the trial findings. [ABSTRACT FROM AUTHOR]

This is the best case scenario since no energy is lost due to reflection from the antenna. Figure 3 displays the VSWR value for the proposed antenna under stimulation from ports 1 and 2.Novel Decision Tree is related to a loan dataset which contains 346 records. A methodology for loan default prediction in the financial/banking sector comparing Decision Tree and Logistic There has been discussion about and research on regression. For each group, 17 people were chosen as the sample size. Evaluation and documentation of the classifier's accuracy and precision. The Logistic Regression produces 81% in predicting the loan default prediction on the dataset used whereas the Decision Tree predicts the same at the rate of 96%. The significant value is (p < 0.029). Hence Novel Decision Tree surpasses Logistic Regression Compared to Logistic Regression, Accuracy and precision are both improved upon by the novel decision tree. [ABSTRACT FROM AUTHOR]

Video Captioning is a process that generates the sentences for the visual information in a video. It is an essential process for video retrieval and analysis. Unlike the still images, the frames in video are temporally connected. It is very important to consider the visual, temporal and grammatical information while generating captions for a video. This is done through encoder-decoder architecture model. In encoder module, the ResNet-152 is used as a feature extractor to obtain the features from video frames. Then, in the decoder module, LSTM and GRU were employed to make the sentence generation. The architecture is trained and tested over the benchmark dataset Microsoft Video Description Corpus (MSVD) and performance is evaluated using BLEU, METEOR and CIDEr. [ABSTRACT FROM AUTHOR]

A new method is described to study how microstructures within a plastic-bonded explosive (PBX) interact with shock waves to produce hot spots, and to identify the critical hot spots that grow into a deflagration. A unique feature of this method is that it allows us to see every crystal in the PBX during the shock. We used an HMX-based PBX fabricated into a wafer about one crystal thick so there are no crystals hidden from view. The wafer is embedded in a transparent polymer in a traveling wave geometry, and a microscope with a laser flyer launcher and a nanosecond camera is used to watch hot spots appear and grow so we can determine which microstructural elements favor or disfavor hot spots. [ABSTRACT FROM AUTHOR]

A vital concept of handling data nowadays is the use of big data. As the size of the data exponentially increases, the regular database management system experiences a number of constraints and restrictions to deal with the large volume of data. The complexity of the system increases in storing, retrieving and processing these data. Search engines suffers to performs their operations in spite of the presence of huge volume of data. Documents of different size are hyperlinked in various levels and forms web resources in the Internet. The size and number of documents increases and the web becomes overwhelmed with dense volume of documents. In this point, the concept of document clustering arises and plays important role in addressing this situation. This technique groups the documents with relevancy and forms clusters of documents. The size of the clusters would be manageable and hence this helps in handling the big data as reduced size clusters with reduced overheads. For the purpose of clustering and handling document, we use the MapReduce paradigm. This model processes the documents in an enormously parallel way. This could be achieved in two steps using two functions the Map function and Reduce function respectively. The Map function applied on the documents with key and value pairs and produces intermediate values. The Reduce function used in this work accepts the intermediate key value pairs and produces reduced number of data items. Hence the relevant documents are grouped with reduced size and clusters are formed. Document clusters are easily handled than processing the big data directly. The results are compared for serial execution and MapReduce execution. The comparison shows that MapReduce performs document clustering with reduced computation complexity for documents with large number of terms. [ABSTRACT FROM AUTHOR]

The emissions from transportation and industrial sectors have an impact on human health. It is the most significant factor in the deterioration of air quality. By decreasing hazardous emissions from diesel engines, biofuel is a viable option for improving human health and environmental quality. The goal of this study is to examine the exhibition and emanations of diesel joined with linseed and neem seed oil as biodiesels all the while. Five distinct ternary mixes were delivered and tried in a solitary chamber four stroke water-cooled diesel motor. The presentation of the motor worked with TB5 (5% LME + 5% NME + 90% diesel) and TB10 (10% LME + 10% NME + 80% diesel) is ideal contrasted with crude biodiesel and its mixes. The variation in SFC from neat diesel to blends is very minimal at higher loads. The CO emissions are lower in ternary blends compared to diesel. However, the emission of NOx is high. [ABSTRACT FROM AUTHOR]

Anaerobic fermentation is a highly promising technology for converting biomass waste into methane, which may directly be used as an energy source. The objective of this research was to investigate production rate of biogas from camel dung, chicken dropping and vegetable waste. Attempts have been made in this study to optimize various parameters in order to determine the most favorable conditions for maximum biogas production from three different types of wastes such as camel dung (CAD), chicken droppings (CHD) and vegetable waste (VW). The amount of biogas produced from the wastes is compared as: VW >CHD>CAD. The results showed that biogas produced from VW is 720 ml in 32 days as compared to CHD and CAD which are 600 ml in 36 days and 80 ml in 40 days respectively. The effect of the pH and temperature on the amount of biogas produced was also studied. The experiments were conducted in temperatures ranging from 36 °C to 44 °C. [ABSTRACT FROM AUTHOR]

In this paper it is proved that Subdivision of a Bistar graph B (m, n) and Subdivision of a Coconut tree S(CT(m,n)) admits mean square cordial labeling. [ABSTRACT FROM AUTHOR]

CaxBa1-xNb2O6 (CBN) ceramics with tetragonal tungsten bronze (TTB) structures are very attractive from academic and technological fronts due to their outstanding ferroelectric properties. Hence, CBN ceramics were prepared by high temperature solid state reaction technique in this work. The phase formation, microstructure and dielectric properties of the prepared samples were investigated by X-ray diffraction, scanning electron microscope and impedance analyzer, respectively. The X-ray analysis confirms the partially filled tetragonal tungsten bronze (TTB) structure. The scanning electron micrographs provide information related to the morphology and grain size distribution of the samples. The dielectric and ferroelectric properties of CaxBa1-xNb2O6 (x= 0, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4) ceramics were also measured, and they have been found to be strongly processing-dependent. The frequency dependence of the dielectric constant (e) of the samples have been discussed. Detailed analysis of the structural and dielectric properties suggests that these samples have undergone a phase transition well above the room temperature. DC resistivity studies on the samples are marked by a response of positive temperature coefficient of resistivity (PTCR) in all the compositions. [ABSTRACT FROM AUTHOR]

Multiferroic BiFeO3 has been synthesized through hydrothermal route under different reaction conditions. From the basic characterization such as of X-Ray diffraction analysis (XRD), the synthesized Nps were found to having rhombohedral structure with R3c space group. Photodegradation studies of toxic dye phenol red have been investigated under visible light irradiation. Vibrating sample magnetometer (VSM) analysis has been carried out to identify the magnetic properties and recycle ability photocatalysts. [ABSTRACT FROM AUTHOR]

A co-precipitation method has been adopted to synthesis Bi1-xGdxFeO3 (x = 0.00 and 0.15) nanoparticles. XRD studies confirms the phase formation and the crystallite size measured by using Debye-Scherrer relation reveals particle sizes of 72 and 36 nm for Bi1-xGdxFeO3 (x = 0.00) and Bi1-xGdxFeO3 (x=0.15) respectively. A distinct anomaly peak has been observed around 390°C in Bi1-xGdxFeO3 (x = 0.00) and 273°C in Bi1-xGdxFeO3 (x=0.15) from the temperature dependent dielectric studies attributed to the antiferromagnetic to paramagnetic phase transition. Bi1-xGdxFeO3 (x=0.15) shows better leakage current characteristics due to partial substitution of stable rare-earth Gd3+ ions for volatile Bi3+ ions leading to the reduction in oxygen vacancies. Further, Bi1-xGdxFeO3 (x = 0.00) shows lower remnant polarization value and a antiferromagnetic behavior. Whereas, Bi1-xGdxFeO3 (x=0.15) shows higher remnant polarization value and a weak ferromagnetic behavior. [ABSTRACT FROM AUTHOR]

Multiferroic BiFeO3 (BFO) nanoparticles (Nps) were synthesized using hydrothermal method. From the X-Ray diffraction analysis (XRD), the synthesized Nps were found to having rhombohedral structure with R3c space group confirmed by Rietveld analysis. Fourier transform infrared spectroscopy (FTIR) analysis was carried out to identify the chemical bonds present in the BFO Nps. Photocatalytic properties of synthesized Nps were studied for the degradation of Methylene Blue (MB) dye under visible light of 150W. [ABSTRACT FROM AUTHOR]