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Maintaining optimal tyre pressure enhances the performance of a vehicle in many ways. Tyre pressure monitoring system (TPMS) provides a safety feature that shows an alert when the car's tyre pressure drops below the recommended levels. In this paper, the TPMS is built through training of the KNN algorithm based on wheel hub vibrations. An inexpensive system was developed by interfacing the ADXL335 accelerometer with Arduino for collecting real-time data. In order to process the raw data suitable conditioning was undertaken. The initial judgment of wkNNheel hub vibrations was carried out statistically. The features reflecting the relevant statistical judgment of tyre pressure conditions were selected and training of the KNN algorithm was initiated. Perfectly filled, partially filled and unhealthy tyre conditions were considered while acquiring the wheel hub vibrations and classification was achieved.

Solar-based thermal energy storage (TES) systems, often integrated with solar collectors like parabolic troughs and flat plate collectors, play a crucial role in sustainable energy solutions. This article explores the use of hybrid nanofluids as a working fluid in thermal storage units, focusing on their potential to increase system efficiency. The review highlights the popularity of hybrid nanofluids, composed of oil and nanoparticles, as effective heat transfer fluids in solar energy-based thermal energy storage and heat transmission systems. Key findings highlight the superior heat transfer capabilities of multi-walled carbon nanotubes (MWCNT) and alumina nanoparticles when dispersed in various base fluids. Additionally, PCMs such as erythritol and nitrate salt emerge as optimal choices for efficiently storing thermal energy. The stored energy becomes invaluable during non-sunlight hours, offering a continuous and reliable energy supply. This study highlights the potential of hybrid nanoparticles as heat transfer fluids for solar-based thermal energy storage systems, opening the path for progress in sustainable and efficient energy use. Future directions may include further optimization of hybrid nanofluids, the incorporation of improved PCMs, and novel techniques to improve the overall efficiency of solar energy storage systems.

The rural population of India suffers from various medical ailments and due to the lack of medical facilities and practitioners, enough support is not available. Medical help might come late and the problem might have been aggravated. With the increasing awareness about artificial intelligence (AI), it is possible to solve these problems using technology. The research aims at detecting an early stage of the skin disease 'eczema', when the affected part of the human body is captured through a smart phone and approximate symptoms are provided by the medical practitioner. It uses artificial intelligence algorithms like convolutional neural networks and support vector machines algorithm for classifying the images, and back propagation algorithm for training a model based on the symptoms. Around 50 clinical photographs of eczema acquired from KEM Hospital, Mumbai to train the classifier and then different images of eczema were tested with an accuracy of greater than 85%.

Here we report a highly sensitive real-time PCR (qPCR) assay to detect Paramyrothecium roridumfrom pure culture and infected samples of cotton plants. A specific set of primer pair pMyro F/R is designed to target the 185 bp ITS region of rDNA of Paramyrothecium roridumspecies and validated using qPCR. The fluorescence signals were detected above the baseline threshold from samples containing Paramyrothecium roridumDNA, whereas other samples did not produce any fluorescence or produced fluorescence which did not reach detection threshold values. A single dissociation peak of increased fluorescence was obtained for the specific primers at 92.2 °C melting temperature. The limit of detection using SYBR Green dye in this assay was up to 0.1 pg per µL of DNA from pure culture of P. roridum. The assay is accurate, sensitive, less laborious and time saving for detection of P. roridumin infected tissues of cotton.

Due to high cost of fossil fuels and uncertainty regarding future cost and availability, use of sun drying of various agriculture products, vegetables, fruits, fish, milk products, food products, etc. is being practiced largely since ancient times for preservation of agriculture products. Despite many disadvantages of natural drying, almost 80% of farmers are using open sun drying method for drying their crops. Open sun drying, in which the product is spread on ground in open, is the simplest and cheapest method of drying. But there are considerable losses associated with it. So, the advanced method of drying i.e., solar drying can also be used for drying the products and improve the quality. In this paper, comprehensive study of solar drying of various products is presented.

•The COP of refrigeration system is improved by achieving sub-cooling of the refrigerant using phase change material.•Heat stored in phase change material is supplied to thermoelectric generator's hot end, and electric power is generated from the waste heat of refrigerant.•The net-work input is reduced as compared to a conventional system using a thermoelectric generator.•Around 7% improvement in the COP of refrigeration system is achieved.

The experimentation has been performed in Central Indian climatic conditions to investigate the performance of the novel heat‐pipe‐assisted thermal storage system with parabolic trough solar collector and nanofluid. The present thermal energy storage system is nanofluid (Al2O3/soybean oil) based and the eutectic mixture of KNO3and NaNO3(nitrate salt) in the molar ratio of 40:60 has been used as phase change material to store the heat energy. The system is based on the natural circulation of heat transfer fluid (thermo‐syphon) and the receiver to arrest the solar radiation is parabolic trough solar collector using an evacuated tube. The major and novel incorporation in this system is the heat pipe insertion in the storage unit of the system, which provides better heat transfer, and hence the improved storage capacity is achieved. The final remark of this study has been done with the comparison of the present system with the existing and similar kinds of thermal energy storage systems. For the same charging cycle time and same climatic conditions, the compared value of specific heat storage capacity is 67% higher as compared to the average value of other considered systems. The heat pipe is more useful in the thermal storage system to store and transfer energy. The parabolic trough solar collector is best suitable for the solar‐based thermal storage system. The thermal storage can operate on solar energy and temperatures above 220 °C.

AbstractA wide array of supernumerary and accessory musculature of forearm has been described in the anatomical, surgical and radiological literature. In majority of the cases, these accessory muscles are asymptomatic but in some cases, these accessory muscles produce clinical symptoms. They may be present as a palpable soft swelling or as a fibro-osseous mass near carpal tunnel with symptoms of neurovascular compression. In symptomatic cases, recognition and careful evaluation of accessory muscle with electromyographic examination may aid in diagnosis and in finalizing the treatment. We report a rare case of accessory muscle bellies arising from Flexor Digitorum Superficialis (FDS) muscle on right and left sides. During routine dissections of the forearm performed by preclinical students in the department of anatomy, we observed an accessory muscle belly arising from the tendon of index finger of flexor digitorum superficialis muscle on the right and left sides of a cadaver. The accessory muscle belly has taken its origin at the junction of upper two third and lower one third of forearm and traversed in the carpal tunnel and merged with the tendon of FDS to the index finger in the hand at the level of origin of first lumbrical.Although many anatomical variations of FDS muscle were reported in the past, we describe a rare case, first of its kind, which to our knowledge has not been mentioned in the literature till date.

AbstractHypertension is a silent but known risk factor for cardiovascular diseases and is estimated to contribute 4.5 percent of current global disease burden in developed countries and many developing countries. A family history of cardiovascular disease has been shown to be a risk factor for the subsequent development of the disease in children. Hence, the present study was conducted keeping in mind the objective to measure the anthropometric parameters of young healthy adults and its association with presence or absence of parental history of hypertension. A cross-sectional study was conducted on 18-25 years collegegoing 200 adolescents of both sexes. Half of the students were selected having parental history of hypertension and half were selected without any history of parental hypertension. A pretested questionnaire was used along with anthropometric measurements to know obesity or overweight. Among the 200 participants, 63 percent were male with average age 20.12 years (SD ±2.01). 32 percent had Body Mass Index more than 25, their prevalence being 35.5 percent in male and 26.3 percent in female compared to that in offspring of normotensive parents which was 10 percent for both genders, 12.5 percent for male and 5.6 percent for female. Out of the 100 participants of the study group, 56 have their Waist Hip Ratio above the standard defined cut-off for their respective sex. There is a definite need of monitoring the children’s of parental history of hypertension with other non communicable diseases like diabetes & obesity to prevent the occurrence of disease in future.

Total productive maintenance (TPM) is a people-intensive, preventive maintenance system for maximizing equipment effectiveness in the enterprise. The concept of TPM was originally suggested by Nakajima (1988) who proposed overall equipment effectiveness (OEE) as a metric for evaluating the progress of TPM, which is interpreted as the multiplication of availability, performance and quality. This paper aims to study and investigate the implementation of a TPM to improve the OEE in manufacturing enterprises. In today’s industrial scenario huge losses occur in the manufacturing shop floor. These losses are due to operators, maintenance personal, process, tooling problems and non-availability of components in time etc. The quality related waste are of significant importance as they matter the company in terms of time, material and the hard earned reputation of the company. There are also other invisible losses like operating the machines below the rated speed, start up loss, break down of the machines and bottle necks in process. Zero oriented concepts such as zero tolerance for losses, defects, break down and zero accidents are becoming a pre-requisite in the manufacturing and assembly industry. In this situation, a TPM is the answer to resolve the above said problems which helps in benefitting the growth prospects of any organization.

The present experiment and analytical study was carried out for suitability analysis of novel hybrid system of nano-enhanced Phase change material (PCM) for thermal energy storage applications. In this study, an experimental setup of a hybrid thermal energy storage system was fabricated. Parabolic dish solar collector was used as receiver of solar energy so as to store heat via PCM. And experimentation was conducted with selected nano enhanced PCM after comparing the heat storage capacity of various available nano-enhance PCMs from past literature. Further, the detailed comparison was carried out between pure paraffin wax and it's composite with CuO-MWCNT on the basis of their attributes like thermal conductivity, heat capacity, and useful temperature range. Results showed that nano-enhanced PCM exhibited 6.125% higher thermal conductivity than that of pure paraffin wax. It was also observed from the experimentation that time taken by nano-enhanced PCM for complete transformation from solid to liquid phase was 66.6% lower than the time taken by pure paraffin wax. This study also unveils that the hybrid system exhibited wide range of useful temperature band that is from 60 °C–180 °C which confirms its suitability for efficient space heating applications.

Non-stationarity of electroencephalogram (EEG) signals greatly affect classifier performance in brain-computer interface (BCI). To overcome this problem we propose an adaptive classifier model known as extended multi-class pooled mean linear discriminant analysis (EMPMLDA). Here, we update the average class pair co-variance matrix along with pooled mean values. Evaluation of classifiers are done on visual evoked cortical potential data-sets. We demonstrate that EMPMLDA can significantly outperform other static classifiers such as MLDA and adaptive classifiers (MPMLDA). Furthermore an optimal update coefficient can be achieved using different datasets.

Computerized lip reading, or speech reading, is concerned with the difficult task of converting a video signal of a speaking person to written text. It has several applications like teaching deaf and dumb to speak and communicate effectively with the other people, its crime fighting potential and invariance to acoustic environment. We convert the video of the subject speaking vowels into images and then images are further selected manually for processing. However, several factors like fast speech, bad pronunciation, and poor illumination, movement of face, moustaches and beards make lip reading difficult. Contour tracking methods and Template matching are used for the extraction of lips from the face. K Nearest Neighbor algorithm is then used to classify the 'speaking' images and the 'silent' images. The sequence of images is then transformed into segments of utterances. Feature vector is calculated on each frame for all the segments and is stored in the database with properly labeled class. Character recognition is performed using modified KNN algorithm which assigns more weight to nearer neighbors. This paper reports the recognition of vowels using KNN algorithms

Computerized Face Detection, is concerned with the difficult task of converting a video signal of a person to written text. It has several applications like face recognition, simultaneous multiple face processing, biometrics, security, video surveillance, human computer interface, image database management, digital cameras use face detection for autofocus, selecting regions of interest in photo slideshows that use a pan-and-scale and The Present Paper deals with energy conservation using face detection. Automating the process to a computer requires the use of various image processing techniques. There are various methods that can be used for Face Detection such as Contour tracking methods, Template matching, Controlled background, Model based, Motion based and color based. Basically, the video of the subject are converted into images are further selected manually for processing. However, several factors like poor illumination, movement of face, viewpoint-dependent Physical appearance, Acquisition geometry, Imaging conditions, Compression artifacts makes Face detection difficult. This paper reports an algorithm for conservation of energy using face detection for various devices. The present paper suggests Energy Conservation can be done by Detecting the Face and reducing the brightness of complete image and then adjusting the brightness of the particular area of an image where the face is located using histogram equalization.

Many of the micaceous soils of the IndoGangetic alluvial plain of northwestern India are sodic and have clayenriched textural B horizons. These soils sometimes lack identifiable clay skins. In order to determine the genesis of the textural B horizons of these soils, both with and without identifiable clay skins, one Natrustalf Sakit soil and one Aeric Halaquept Rahamabad soil were selected for study.