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The human visual cortex processes visual stimuli hierarchically. Early visual areas (V1, V2) of the ventral visual stream feed crude visual features (like orientation and edges) into later visual areas (V4, lateral occipital (Lat Occ), inferior temporal (IT)) that then encode complex visual features (like object form). Previous studies have reported a difference in fMRI responses between natural and urban landscapes in certain parts of the brain. Here we asked if this distinction in the representation of complex natural and man-made visual stimuli extends to the ventral visual stream and if state-of-the-art convolutional neural networks (CNN) provide a map to this categorical distinction. To assess this, we used an open source fMRI data set of V1-4 and LatOcc BOLD responses to 1750 passively viewed natural and man-made grayscale images. The same images were fed into the pre-trained CORnet-S, a CNN designed to model hierarchical human visual processing layer-wise. To identify differences in representations within and between the human visual cortex and the CNN, we computed representational dissimilarity matrices. The BOLD response to the manmade and natural images shows correlation differences for the two categories, which increase across V4 and LatOcc. Such differences were also observed in the model CORnet-S for the layers V4 and IT. Our results suggest that the human visual cortex processes natural and manmade images differently starting from V4 and that this representational difference is modeled in CORnet-S. In both, categorical representation is progressively established in the later processing stages. This might indicate that the brain has perhaps developed two-distinct systems for their representations which can be directed through evolution. Further analysis may elucidate the contributory role of evolution towards this paradigm.

The production of ammonia is facilitated by the nitrogen reduction reaction (NRR), where the inert di-nitrogen molecule is converted to ammonia. Along with being a major carrier of hydrogen, ammonia holds authority in the fertilizer realm. Therefore, it is inevitable to develop a viable and eco-friendly method of production that is cost-effective and resource-efficient. The primary challenge of nitrogen reduction is the cleavage of the particularly stable nitrogen bond. The most popular Haber-Bosch process for ammonia production, although efficient, is highly energy-intensive, and the need for maintaining exceptionally high temperature and pressure conditions is an environmental concern. As an alternative, the direct conversion of nitrogen has been carried out by photocatalysis and electrocatalysis. However, this strategy falls short of achieving superior conversion efficiencies. Consequently, it is conceivable that a fitting catalyst can be the solution for the difficulties associated with NRR. Over the years, several attempts have been made at formulating the best catalyst, including chromium oxynitride nanoparticles, niobium dioxide, various metal (Ru, Al, Rh, Ga) clusters, single-atom catalysts supported on different surfaces, and double atom catalysts. Recently, perovskites have emerged into the spotlight as excellent catalysts for NRR. In this chapter, we discuss the challenges faced by researchers to formulate righteous catalysts for the sustainable reduction of nitrogen by studying each of these types with a few examples. We also review the recent advancements in the experimental domain of NRR using different electrochemical cells.

In this study, truxene, along with its nitrogen- and sulphur-substituted counterparts were investigated for their properties. The important characteristic properties of a potential conducting material such as HOMO-LUMO gap, electron affinity, ionization potential, and density of states were calculated and compared for analysis. Furthermore, Fukui function and dual descriptor analyses were also carried out, to identify the reactive sites in each of the molecules, as well as understand the effect of substituted heteroatoms. It was seen that the di-substituted candidates were convincingly better fitting for optoelectronic applications.

This paper describes a model-based method for estimating the speed of an induction motor drive that does not have a speed sensor. Because of its less complicated implementation technique, the model-based approach is extensively employed. Vector Controlled Induction with No Sensors To get good dynamic performance, motor control is used. Studies on inverter switching techniques led to the creation of a bus clamped space vector modulation scheme, which has a direct impact on the performance of induction motor drives, particularly in sensorless applications. The modulation technique reduces motor current distortions, pulsation in torque, inverter losses and harmonics in the inverter thus, improvising the performance of the drive. Simulation analysis is performed on MATLAB platform and the results obtained prove the efficacy of Model based speed estimator and Bus Clamped Modulation analogy.

Modern digitalized era of our 21st century needs automation in each and every sector. In India forming is called the vertebrae of the country because most part of India depend upon agriculture so automation in agriculture will surely help in lifting up lift the country’s economy and irrigation is the most basic requirement of the agriculture. The exercise of proper method of irrigation system is very reasonable and proficient this method will reduce the human interference with the irrigation and provide the proper water management. To achieving the automation in the fields with irrigation we require various hardware and software components such as GSM for wireless communication, sensors to check the status of the soil and Arduino etc. The arranged framework is working with programmed activity, which considers detected information alongside the climate conjecture boundaries like precipitation, air temperature, stickiness, and UV for the not-so-distant future. The total framework has been created and conveyed on a pilot scale, where the sensor hub information is remotely gathered over the cloud utilizing webservices and an online data perception and choice emotionally supportive network gives the continuous data bits of knowledge dependent on the investigation of sensors information and climate estimate information [1]-[2]. This paper targets fostering the GSM based mechanized water system framework which give satisfactory water needed by crop by checking the dampness of soil and environment condition to forestall the wastage of water asset. It will likewise enjoy numerous benefits for ranchers.

Controller Area Network(CAN) which is specially designed for Automotive connectivity has a major drawback in the security of data transmission, where the data can be easily hacked. By hacking the data can be read, altered or even false data can be injected which will lead to a huge risk for the vehicle itself and the driver/passengers in the vehicle. To prevent this combining two algorithms in cryptography (AES and RSA) encryption to the messages in the CAN bus is provided. The data sent from the ECU will be encrypted using the AES algorithm, the key used by the AES will also be encrypted using the RSA algorithm. Decryption will be done by a reverse process where first the key of AES will be decrypted and then the data will be decrypted. By providing encryption and decryption the data can be transferred securely. This project also provides authentication which is achieved by sending acknowledgment signals. By providing encryption and authentication the Replay attack and Injection of forged frames can be avoided. Here the time taken for encryption, authentication, and decryption for different samples of the text of different sizes are also calculated. Results shows that proposed algorithm is more suitable for e-vehicle with better CAN protocol security.

In this era of digitalization, the new technology is being designed and developed which helps the day-to-day livelihood of common man. The technological assistance has improved the efficiency with which the common man completes his/her assigned task in every aspect. Several systems/modules have been developed to assist the visually impaired people to use public transport system. The objective of the paper is to provide a system which is easy to implement and require low cost and common equipment using wireless communication system. This proposed system is useful not only for the blind person but also for the people who have recently shifted to the city and has no idea about the public transport system. This system will result in easy and convenient public transport system for the citizen of the city. The proposed system can be improvised by using machine learning techniques and algorithms to estimate the vacant seats in the bus before bus reaches the bus stop and many more features can be implemented., {"references":["Xiaojian Feng, Jiuling Zhang, Jinhong Chen, Guoqing Wang, Liuye Zhang, Runze Li (2018), \"Design of Intelligent Bus Positioning Based on Internet of Things for Smart Campus\", IEEE Access, Volume 6, pp. 60005-60015","Mr. Anilkumar J Kadam, Mr. Virendra Patil, Mr. Kapish Kaith, Ms. Dhanashree Patil, Ms. Sham (2018), \"Developing a Smart Bus for Smart City using IOT Technology\", Second International Conference on Electronics, Communication and Aerospace Technology (ICECA), Coimbatore, India","Mr. Pranab Das, Mr. Vijay Prasad (2015), \"Voice Recognition System: Speech-To-Text\", Journal of Applied and Fundamental Sciences, Volume 1, Issue 2, pp. 191-195","Swapnil Gholap, Govind Ekshinge, Parag Naik, Prof. S D Chavan (December 2015), \"Navigation of Blind People Using Passenger Bus Alert System\", International Journal of Scientific and Research Publications, Volume 5, Issue 12, pp. 189-194","Vidya Bhoge, SY Chinchulikar, \"Review on GPS Navigation System for Blind People\", International Journal of Engineering Sciences & Research Technology, Volume 5, Issue 6, pp. 570-574"]}