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The given system includes a vast dataset of India's states, but the previous system, only single state was selected. All the farmers will get a better knowledge of the crops to cultivate by using a pictorial depiction. Machine learning features give a detailed structure with the information and it gives the predictions. The main problems like knowing about the crop prediction, rotation techniques, utilization of water, need for fertilizer and safety will be taken care of. Due to varying climatic changes of the surrounding the need to have a proficient techniques are required for development of crops and to help the farmers in their knowledge of production and management features. The project gives the proper results for advanced farming techniques by choosing the land for farming, which can help the farmers to gain huge knowledge about this.

Visual information in large digital databases has been grown abundantly in the recent years and content based image retrieval (CBIR) attracts the interest of image processing oriented research people. The CBIR systems are vital performance due to the usage of features such as color, texture and shape of the query image. Searching a collection of images that have similarities with input images and without knowing the name of the image, makes a search system that applies the concept of content-based image retrieval (CBIR), is very necessary. The successful of the CBIR system creates the intension to apply it on many real world fields such as search engine, web and human disease analysis etc., This paper surveys a lot of applications based on the CBIR systems and this paper concentrates on the four types of applications which are belongs with medical field, remote sense imaging, forensic, security applications. The recent papers which are written showed that the applications which are reviewed with the explanation about technologies used to enhance the study of CBIR based applications and the methods which are adopted for CBIR in recent period. This paper is more useful for the people who want to continue their research in content based image retrieval.

Biomass is a renewable and sustainable green energy material. It is made up of lignin, cellulose, and hemicellulose with considerable amount of water, extractives, and inorganic chemical compounds. The use of biomass materials and other biogenic wastes for energy recovery represents an eco-friendly way. Biomass material selection is one of the most significant aspects for any energy conversion process, and it is a common outsourcing problem that includes material preparation, reactor performance, economic assessment, and calorific value of the products. Fuzzy systems can be quite useful in high-performance computing during the selection of biomass materials. In each engineering process, material selection is a crucial step since each material is having its own set of characteristics. This study presents the application of type-1 fuzzy set for the selection of suitable biomass material for yielding maximum bio-oil. This study focuses on seven locally available materials such as rice straw (M-1), sunflower shell (M-2), hardwood (M-3), wheat straw (M-4), sugarcane bagasse (M-5), corn cop (M-6), and palm shell (M-7). The study evaluated seven important properties of the materials such as lignin (P-1), cellulose (P-2), hemicellulose (P-3), volatile matter (P-4), fixed carbon (P-5), moisture content (P-6), and ash content (P-7). The findings demonstrated that sugarcane bagasse (M-5) is the best option for maximum bio-oil yield. Furthermore, the potential of nanoscale catalysts in improving the yield of bio-oil through real-time experiments was studied. The findings of this work add to our understanding of the application of fuzzy-based systems for energy applications.

In India, half the population depends on agriculture for a livelihood. Microbial diseases are a significant threat to food security, but their rapid identification remains difficult due to limited infrastructure. With AI, automatic detection of plant diseases from raw images is possible using deep learning and transfer learning. This paper aims to detect and classify Grapes and Mango leaf diseases, employing a dataset of 8,438 images of diseased and healthy leaves collected from the Plant Village dataset and acquired locally. The deep convolutional neural network (CNN) is trained to identify diseases or their absence. A pre-trained CNN architecture called AlexNet is modeled for automatic feature extraction and classification. The system is developed with MATLAB achieves an accuracy rate of the detection of 99% and 89% for Grape leaves and Mango leaves respectively. An app named "JIT CROPFIX" is developed to implement the same on an Android Smartphone.

The water and liquid repelling materials due to their low surface energy and specific nanometer and micrometer scale roughness have particular interest due to the great variety of potential applications ranging from self-cleaning surfaces to microfluidic devices. Natural plant-based polymer hydrophobic coatings have several engineering and biomedical applications. In this study, natural plants such as Aloe vera and Acalypha indica were used for preparation of polystyrene hydrophobic film by the dip-coating method. The effects of Aloe vera and Acalypha indica extract on the morphological, structural, optical and antibacterial properties of as-prepared polystyrene thin films were studied. FTIR spectra were carried out to ascertain the presence of functional groups in the prepared polymeric film. Contact angle measurement showed that the PS/ Aloe vera has higher anti-wetting property (CA = 112°) compared to PS/ Acalypha indica (CA = 104°), which could be confirmed by the surface morphology analysis. Furthermore, the effective antibacterial activity against Klebsiella pneumoniae and Staphylococcus aureus was compared by agar-well diffusion method. The observed result reports, PS with Aloe vera film exhibit higher hydrophobic with antibacterial activity compared to PS with Acalypha indica film. In addition, the PS/ Aloe vera coated cotton maintained their repellent properties against various liquids for 10 h, while PS/ Acalypha indica coated cotton exhibit anti-wetting property for 4 h. These findings open up new avenues for the preparation of hydrophobic film for various biomedical applications.

Carbon dots (CDs) are versatile nanomaterials with high biocompatibility and attractive optical properties. This research presents a microwave assisted rapid inexpensive method of CDs production using babul seed powder as a novel green source. Various parameters of synthesis were optimized and as obtained CDs were characterized by Transmission electronic microscopy (TEM), X-ray diffraction (XRD), UV–Visible, fluorescence, Fourier-transform infrared (FT-IR), Raman and X-ray photoelectron spectroscopic (XPS) techniques. CDs exhibited excellent water solubility and excitation dependent emission that is stable to pH, ionic strength and resistant to photo bleaching. Furthermore, the cytotoxicity of CDs tested on both normal (Human embryonic kidney HEK-293) and cancerous (Human breast adenocarcinoma MCF-7) cell lines disclosed their high biocompatibility. With these admirable properties, CDs were applied as multicolor cellular imaging agents. Furthermore the antioxidant activity of CDs was investigated by 2, 2-diphenyl-1-picrylhydrazyl (DPPH) assay.

Land use/Land cover (LULC) plays a vital role in planning and supervising the utilization of the natural resources based on the gradual increase in the human demands in the current ecosystem. This study mainly focuses on the usage of the geographic information system (GIS) and land usage to identify the changes in Ananthapuramu, which is located in the Ananthapur district of Andhra Pradesh (AP) state, South India. This paper mainly focuses on the classification and identification of the changes in LULC in the period of 1999–2019 based on a survey of India’s topographic map and temporal images gathered from the satellite. The experimental results indicate that over the specified period of study, the rate of increment and decrement in the built-up area, rate of underwater bodies, forest bodies that may demonstrate a significant impact on the environmental ecosystem.

In mobile ad hoc networks, nodes are connected and disconnected regularly; since every mobile node travels autonomously, those nodes are dispersed not uniformly. Connection damage has straight consequences on the network characteristics. For that motivation, various techniques are quick and efficient damage of connection identification using alert packet is difficult for that time to identify next connection in a mobile network. It increases end to end delay and reduces the network lifetime. The present effective connection alteration rate- (ECAR-) based communication scheme depends on the details of neighbouring nodes to survey the connection between the connection alteration rate and the hello time gap in terms of entire transmission rate. Nevertheless, the hello time gap tracking algorithm is constructed to increase transmission rate displaying a stable choice of connection alteration rate, still although node velocity alters. It reduces end to end delay and increases the network lifetime. The hello time gap tracking algorithm is constructed in the network, and it obtains effective connection among unstable mobile nodes. Experimental output indicates that the connection alteration rate in general enhances the hello time gap. It provides the effective connection changing rate for analyzing different metrics which are network lifetime. throughput, and detection efficiency that are improved in the proposed ECAR scheme.

With the advent of multimedia in education sector, there is a big paradigm shift in teaching and learning scenario. The revolutionary approach of technology-based and technology-enhanced learning mechanisms has taken the teaching and learning practices to a new horizon. Most of the higher education organizations have already adapted this shift keeping the rapid growth in the field education technology and they have even setup dedicated departments to support e-learning by means of various support systems, then whether its related to the hardware or software related support or it is related to the support provided for academic practices by means of various orientation and regular training sessions for the staff members. Various tools and techniques are available to assist teachers for varied level of studies, for the course as well their respective assessments. But deploying these tools and techniques are not always very comfortable with some level of customization and thus there are certain authoring tools which provide very easy to implement solutions to the teachers. Along with the Virtual Learning Environment (VLE), implementation of various online tools has equipped every community of learners with plenty of options to learn and implement to enhance the learning experience. These days, most of these VLEs are implemented on the cloud due to the constraint of storage at the organization level. And hence, various cloud-based authoring tools are developed to support the community of learners, which includes both educators as well as students. This paper highlights few of such implementations and their impact on the overall teaching and learning process. The paper finally recommends a framework, which can be implemented along with various cloud-based authoring solutions.

Automatic image registration of the satellite images aids in the field of the computer-aided research. In the recent years, image registration is useful in the environment monitoring and the agriculture purpose. In this work, the automatic image registration model has been developed through the novel hybrid optimization algorithm. This work mainly concentrates in image registration of the hyperspectral images arriving from the satellite. The proposed automatic image registration model uses the input image and the reference image for the registration purpose. From both the images, the E-SIFT features are extracted and given to the point matching algorithm for the keypoint detection. Then, the similarity transformation model gets the keypoints and makes the input images to the original position. Here, the weighted average model is developed for the image fusion, and the weight score for the image fusion is selected optimally through the proposed salp swarm-crow search algorithm (SS-CSA). For the experimentation, the proposed scheme uses the standard database having the hyperspectral satellite images. The simulation results reveal that the proposed image registration scheme with the SS-CSA algorithm has progressed better than the existing techniques with 0.711788 and 0.993602 for the RMSE and NCC, respectively.

Presently, lung infection is severe to humans that leads to death if left untreated, and Tracking down a disease on the dot is a way we get out of a hock. Recurrently, the eleventh-hour tracking of bugs or incertitude in prognosis margins to voluminously hefty blow-offs. Deep learning branches out a scheme to cut and run of it. Deep learning models work on medical images to detect the type of lung disease. The fashioning of a gadget aids the medical technicians to put a finger on the type and also sub-type of the syndrome without chaos by postulating the prototype as input to it, to enforce the primitive and definite therapy. Grail is to define a common system that categorizes all possible lung diseases like cancer, TB, Pneumonia, and COVID from CT or CXR images.

The current methods of energy monitoring and metering in India are extremely labor-intensive and prone to human errors. The system the authors propose will incorporate an automatic energy reading meter system (AERM) which will aid in the collection of data accurately and efficiently. Additionally, power companies find it hard to withstand the power requirement of a consumer because of a surge in industries, buildings, and population. The usage of electrical appliances has drastically increased over time. As per as energy balance maintains between the energy demand and supply for the power companies are bearing in mind an energy supervision technique. Therefore, there is adoption for load scheduling or load shifting to reduce the electricity bill. So consequently, the authors look into various optimization algorithms for load-shifting.

The purpose of our project is to enable storage and file transfer for the users, making it possible with the use of single USB connected mouse with the help of an integrated chip. This Integrated Chip(IC) is (GL850G) that acts as a splitter. This splitter splits the USB connector to connect the receiver and a storage medium, so that the users can make use of this mouse as storage device also. So the user can transfer the files or data to another unknown computer via this mouse with an inbuilt storage facility instead of using an additional storage device. File transfers are made easier between two unknown computers., {"references":["Working of a computer mouse (https://www.explainthatstuff.co m/computermouse.html) (https://www.tutorialspoint.com/e rasable-programmable-read-onlymemory-eprom)","Optical mouse working (https://computer.howstuffworks. com/question631.htm)","Wireless mouse working (https://computer.howstuffworks. com/mouse6.htm)","USB Working (https://www.electroschematics.c om/usb-how-things-work/)","Pen drive working (https://electroviees.wordpress.c om/2013/05/03/3/)","Memory types (https://semiengineering.com/wh ats-really-happening-insidememory/)","EPROM","GL850G Working (https://datasheet.lcsc.com/szlcs c/Genesys-Logic-GL850GOHY37_C127278.pdf)","Bluetooth working(https://computer.howstuffw orks.com/mouse7.htm)","Share mouse (https://www.sharemouse.com/)","Sherin Mohammed Sali Shajideen, V H Preetha. Hand Gestures-Virtual Mouse for Human Computer Interaction. International Conference on Smart Systems and Inventive Technology (ICSSIT).2018.","Mohamed Nasor; K K Mujeeb Rahman; Maryam Mohamed Zubair; Haya Ansari; Farida Mohamed Eyecontrolled mouse cursor for physically disabled individual. Advances in Science and Engineering Technology International Conferences (ASET).2018.","Yui Tanaka, Takayuki Fujimoto. sMouse: A Development of the Analog Operability of Computer Mouse.7th International Congress on Advanced Applied Informatics (IIAIAAI).2018."]}

Advancement from Verilog for the design and development of digital ICs is the innovation in QCA (Quantum Cellular Automata) Design which represents ideal cell automation using Quantum dots. QCA Design uses a transistor less computation technology which can produce high-density Nanoscale transistor. The main area of concentration in this paper is to simulate design and comparison of digital circuits using QCA Designer and Verilog Code, more specifically multiplexers and demultiplexers. The simulation results of these two digital circuits using QCA Designer and Verilog code are shown separately along with a performance comparison table. It was observed that they seem to be the same. But., while we consider other parameters like time, space, speed and sensitivity., we truly get to know that QCA design is more reliable when compared to Verilog Code Design. QCAD is a free computer-aided design software application for 2-Dimensional design and drafting. Multiplexers are used in telephone networking, computer memory, and transmission from the computer system of a satellite and in many more fields. Demultiplexers are used in Communication Systems, ALU (Arithmetic Logic Unit) and many other fields.