-74813b3e17f460286df-17d7 20220523044841987 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 11 30 2019 8 4 Teaching Faculty Tihu College, Assam, India. Ms. Juri Das* Dr. R.D. Padmavathy Assistant Professor Department of Education, Tezpur Central University, India Emotional maturity indicates the state of mind where an individual can balance his/ her emotions and know how to handle the hard situation without feeling panic. The objectives of the study is to find out the relationship between emotional maturity and altruistic behaviour in relation to high school student’s gender, place of residence and type of school management. In the present study, the researchers adopted normative survey method with simple random sampling to select a sample of 160 high school students aged 14 –16 years in Sonitpur district of Assam. The researcher collected and analyzed the data statistically by using mean, standard deviation, and t-test. The findings of this study indicate that emotional maturity and altruistic behaviour has positive (relationship and there is a significant mean difference in emotional maturity among male and female students, rural and urban, and government and private school students. 11 30 2019 10065 10070 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9522.118419 https://www.ijrte.org/portfolio-item/D9522118419/ Faculty of Electrical and Electronics Engineering, Ho Chi Minh City University of Technology and Education, Vietnam. Son Ngoc Truong* Memristor crossbar array that has a lot of advantageous features such as non-volatile, high-density, and low-power, is potentially used for realizing artificial neural networks. One of the important factors affecting the performance of crossbar circuits is memristance variation. The variation of memristance causes the variation of synaptic weights resulting in the degradation of the performance of the neural networks. In this paper, the variation-tolerance of memristor synapse is improved by minimized the gradient of the synaptic weight function. To reduce the gradient of synaptic weight function, the memristance values of memristors must be close to the high resistance state. This can be achieved by selecting the value of bias resistance because memristance values of memristors in crossbar-based neural network are distributed around the bias resistance value. In the simulation result, we measure the recognition of crossbar circuit for recognizing the MNIST handwritten digits with the variation is in range of 0% to 10% and the value of bias resistance varies from 30KΩ to 80KΩ. For the bias resistance is as low as 30KΩ, the recognition rate of the crossbar circuit is as low as 17%, when the variation is 10%. When the bias resistance is 80KΩ, the recognition is 70%, when the variation is 10%. When the range of memristance is close to the high resistance state, the recognition rate is improved by 53% when the variation is 10%. 11 30 2019 12028 12031 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9532.118419 https://www.ijrte.org/portfolio-item/D9532118419/ Assitant Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.. B.Manjula Josephine* K.Ruth Ramya Assitant Professor, in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India Jashwanth Gottipati Student, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India Lokesh Nallani Student, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India Harshita Patel Assistant Professor, VIT, Vellore, TN, India Honey words (decoy passwords) are suggested to identify the attacks against hashed password databases. For every client account, the original password will be stored with numerous honey words to prevent any adversary. The honey words are choose deliberately, such that a cyber-attacker who bargains a file of hashed passwords might not be sure, whether it will be the honey word or real password for any account. Furthermore, entering with a honey word to login will trigger an alarm informing the administrator about a password file breach. In that expenditure about expanding those storage prerequisite by 24 times, the creators present a straightforward and successful answer for the identification for pass word file revelation occasions. In this study, we investigate the nectar expressions framework also highlight time permits powerless focuses. Moreover, we recommended an elective method, which chooses those nectar expressions from existing client information, a non-specific international ID list, word reference attack, What's more toward rearranging the characters. Four sets about honey words would include of the framework that resembles the true passwords, thereby accomplishing a greatly level honey words expressions era strategy. On measure those mankind's practices in connection to attempting with split the password, a tested engaged with by 820 people might have been made should focus those fitting expressions to those customary furthermore suggested routines. The outcomes indicate that under novel method, it is tougher to get any implication of true password when compared with conventional methodologies and mankind's practices in connection to attempting with split the password, a tested engaged with by 820 people might have been made should focus those fitting expressions to those customary furthermore suggested routines. The outcomes indicate that under novel method, it is tougher to get any implication of true password when compared with conventional methodologies and probability for picking true secret key may be 1/k, the place k = amount of honey words plus genuine password 11 30 2019 11278 11282 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9534.118419 https://www.ijrte.org/portfolio-item/D9534118419/ Control Equipment Engineering Division, BHEL, Bhopal, India. Manoj Kumar* Amit Ojha Electrical Engineering Department, MANIT, Bhopal, India. Permanent magnet synchronous motors (PMSM) are gaining popularity day by day and will rule in the next decade as these motors have several benefits over induction motor such more efficiency, low noise operation, reduced size, and maintenance free operation. These motors require a position sensor for its control, which makes it costlier, increase the size and low reliability. The development of fast microcontroller, IGBT devices, and high density permanent materials has opened the gate of industrial and commercial market for PM Synchronous Machine. The researchers from various corners of the world are working hard from more than two decades to evolve the sensorless control scheme for rotor flux estimation. A sensorless control schemes proposed till date works satisfactory, but, high performance is still a challenge. The paper presents a review of most popular robust SMO technique for position sensorless control of PM-Synchronous Motor with its benefits & drawbacks. 11 30 2019 10071 10077 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9537.118419 https://www.ijrte.org/portfolio-item/D9537118419/ Research Scholar,ECE, Koneru Lakshmaiah Education Foundation,Vaddeswaram,Guntur, India Darala Siva* Polaiah Bojja Professor, ECE, Koneru Lakshmaiah Education Foundation,Vaddeswaram,Guntur,India In this paper, we reflect on changing the detection environment for addressing the difficulty of detecting miniature area of Land Cover Land Use (LCLU) with a technique using Support Vector Machines (SVMs).We then become accustomed and sophisticatedly changing the Support Vector Machine for designing a supervised learning basis detection that enfolds the False Damage Assessment Index(FDAI). Primarily our proposed detection technique is controls easily the FDAI by simply adjusting two parameters() where it can be facilitate to control sensitivity of detection to the binary classifier and numerical supervised learning algorithm. The experimental results demonstrating about ours proposing detector noticeably improving the detection probability on many existing classifiers in both DAI and FDAI cases 11 30 2019 10957 10963 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9539.118419 https://www.ijrte.org/portfolio-item/D9539118419/