Comparitive study on self cleaning property of Activated charcoal supported Bi2O3−ZnO with other coupled semiconductor oxide nanocomposites
The development of active semiconductor oxide nanomaterials creates a vital role in catalytic effective materials. Here we compare the self-cleaning property of Activated charcoal supported Bi2O3 – ZnO (AC−BZ) nanocomposites with other Photocatalytic nanocomposites of CdWO4 −ZnO and Pr6O11 − Zn. This study has been evaluated using contact angle measurement and our results give some new vision on the performance of coupled semiconductor oxide nanomaterials on an environmental basis.
Published by: G. Ida, D. Easwaramoorthy
Author: G. Ida
Paper ID: V6I4-1224
Paper Status: published
Published: July 19, 2020
Don’t Sleep – Drowsiness Detection Tool
An important application for machine vision and image processing can be the driver's recovery program because of its high importance. In recent years a number of research works have been reported in the literature in this field. In this paper, in contrast to the conventional tone detection methods, which are based on eye regions alone, we have used facial expressions to detect drowsiness. There are many challenges that involve pull detection systems. Some of the important issues are: changes in stiffness due to lighting conditions, the presence of glasses and beards on a person's face. For this project, I propose and implement an infrared light-based hardware system and can be used to solve these problems. In the proposed method, following the acquisition step of the face, the most important face elements and considered to be the most effective, are extracted and tracked in the video sequence frames. The system is monitored and performed locally. Every year more and more people lose their lives because of fatal road accidents worldwide and hot driving is one of the leading causes of road accidents and deaths. Exhaustion and poor sleep in the most common driving sources are the cause of major accidents. However, the first signs of fatigue may appear before the emergence of a crisis and therefore, the diagnosis of driver fatigue and its identification is a topic of further research. Most traditional methods of getting sleep are based on behavioral behavior while some are less confusing and may distract motorists, while others require expensive sensors. So, in this paper, a light weight, driver-specific death detection system was developed and implemented in the Android app. The program records videos and recognizes the face of the driver in all sectors using image printing techniques. The system can detect facial expressions, including the Eye Aspect Ratio (EAR) to detect driver drowsiness based on a changing threshold. Machine learning algorithms were employed to test the performance of the proposed method.
Published by: Anjaneya Turai
Author: Anjaneya Turai
Paper ID: V6I4-1205
Paper Status: published
Published: July 19, 2020
Review paper on connecting the dots using drones
From the past few years, drones have been a trending topic surrounding technology. There are many applications leading to the advancement of the drones such as aerial photography as well as videography, shipping and delivery, geographic mapping, disaster management, precision agriculture, search and rescue operations, weather forecast, wildlife monitoring, law enforcement, and many more. In a country like India, drones will play a vital role in dealing with problems from the front. A Drone with the latest technology onboard will be able to change the downgraded frame of India. Like a drone with a medical kit will give higher efficiency in reachability, remote farming will be smoothly operated using a drone, from a military point view it will be helpful in guarding the hilly posts over LOC, etc. Thus if the future technology implemented as soon as possible in India it will provide huge latency.
Published by: Shritish Shete, Siddhi Dave
Author: Shritish Shete
Paper ID: V6I4-1194
Paper Status: published
Published: July 19, 2020
Parameter extraction for audio signal
Speech is a signal which consisting of various complex information, like the information contain in a signal which to be communicate, language, speaker, region, emotions etc. Speech Processing is one of the important parts of signal processing and finds applications in Audio mining, Human computer interfaces, Assistive technologies, Telecommunication, Security etc. For the speaker identification and emotion analysis Gender Identification is a pre requites. By analyzing the features of different voice signals of male & female it can be determined that which parameters are creating a difference in between the male voice & female voice. For this a comparison between the different parameters present in a voice signal like energy, mean, median and standard deviation is done. It observed that in the graph of mean and standard deviation one can differentiate between a male voice and female as the statistical results are shown. In this paper an input voice signal taken as .wav file and added some noise or unwanted signal; the unwanted noise signals are removed from the original signal by reducing the intensities of high frequencies by averaging and Gaussian window for the smoothing and conv function to removing the pseudo numbers that added as a noise to the original signal
Published by: Neha Sohani Mohanty
Author: Neha Sohani Mohanty
Paper ID: V6I4-1222
Paper Status: published
Published: July 18, 2020
Law of ten generations gap in Heredity
Heredity is the transfer of physical or behaviour characters genetically from one generation to another through genetic material.During the transfer of the genetic material only half of them from both the parents will be transfered to the offspring. The question here is, how many generation genes that was transferred from our forefathers exist in our genetic material,If present how much it will be and what all ways genes from the forefathers can be moved.For finding a suitable answer and explanation to this I put forwarding some new ideas in relate to this
Published by: Ajil Benny
Author: Ajil Benny
Paper ID: V6I4-1232
Paper Status: published
Published: July 17, 2020
Clinico haematological profile in beta Thalassemia trait
Introduction with Objectives: - The most common causes of microcytic hypochromic anemia in India are β Thalassemia & Iron deficiency anemia (IDA). β- Thalassemia is one of the most common single gene disorder in India with an overall prevalence of 3-4 %. Effective screening of β Thalassemia trait (βTT), decrease its incidence. Hb electrophoresis, serum iron profile & RBC indices are used to differentiate βTT from IDA .HbA2, red cell indices are observed as effective screening tests in βTT. Our main objective is to study the hemoglobin electrophoresis & RBC indices in β-Thalassemia Trait & to differentiate from IDA. Methodology: - A retrospective study of 50 patients (OP & IP) admitted in our KMC & hospital, Manipal was done. Study period was 1year (Aug 2015-Sep 2016). HbA2 level is studied by capillary zone electrophoresis method. Hb & red cell indices (MCV, MCH, RDW) were calculated. From red cell indices formulas –Mentzer (MI-cut off-13), Srivastava (SI-3.3), Shine & Lal(S&L-595), England & Frazer (E&F-1.39) were derived & serum iron profiles (Fe 2+, TIBC, Ferritin) was done to distinguish βTT from IDA. Vitamin B12 & folate assay was done . Sensitivity, specificity & Youden index were also calculated . Results:-All 50 pts were diagnosed as β-Thalassemia Trait (HbA2≥3.5 .Hb≤8gms/dl, MCV<60fL, MCH5x106/mm3, RDW>16%).Mean age group is 50yrs, M>F.3/50 cases (6%) shows ↑ HbF along with ↑HbA2.2/50 (4%) has ↑HbS .1 case shows IDA features with βTT. 49/50 (98%) cases of βTT showed-≤ cut off values of all index (MI,SI, S&LI ,E&FI). Serum iron profile was normal in 24/50 (48%), ↑ serum ferritin in 5/50 (10%).↑ vitamin B12 & folate levels seen in 9/50(18%).1 case showed ↓iron profile & ↑index. The MI is the most sensitive (>90%) & specific (>83%). Conclusion:-βTT & IDA are the M.C. causes of microcytic anemia. Hemogram parameters and RBC indices have significant role in βTT. HbA2, MCV & MI are the most sensitive tool to detect βTT.
Published by: Dr. Muthu Venkat T.
Author: Dr. Muthu Venkat T.
Paper ID: V6I4-1193
Paper Status: published
Published: July 15, 2020
