ESL learners’ vocabulary strategy use and learning perception
Vocabulary is an important aspect of second language acquisition. It plays a vital role in language learning. However, it has become the highest challenge that ESL learners faced in the process of language learning. This can be specifically focused on second language learning. In the need of high vocabulary in the second language, vocabulary learning strategies are suggested to be introduced among ESL learners. This enlightens of vocabulary learning strategies among ESL learners believed to have an improvement in vocabulary learning. This study employed a qualitative research design. It is conducted in need of identifying strategies used by learners. This study examined a number of strategies used by pupils from schools located in suburban areas. Besides, the interest of pupils towards vocabulary learning also examined in this study. Furthermore, this research was conducted to test whether there is any significant difference between male and female ESL learners in vocabulary learning perception. A set-off adopted version questionnaire was given to 100 samples which consist of 50 males and 50 females to gather the results of this study. The samples for this study were selected based on a random sampling method. The findings of the study showed that both male and female students have positive perceptions towards vocabulary learning and they preferred social strategy highly in their vocabulary learning.
Published by: Santhy Muthu, Parilah M. Shah
Author: Santhy Muthu
Paper ID: V5I6-1165
Paper Status: published
Published: December 3, 2019
“A study welfare facilities provided and employee satisfaction in Mahavitaran with special reference of Satara district”
Energy is an engine of economic growth and future growth will depend on availability and quality of energy. India is the world’s fifth-largest energy producer and seventh-largest energy consumer. Electricity is the ‘concurrent’ responsibility of the central and state governments. There is Dominance of public sector institutions in the power sector the private participation has been increasing after the adoption of new economic policy. Combination of natural monopoly and oligopolistic market structure. Electricity is a basic need for domestic, agriculture and industrial sector of any economy. hence study on welfare facilities provided and employee satisfaction is required which deeply affect on organization and policy implementation
Published by: Amit Anil Bartakke, Nirmohi Jadhav
Author: Amit Anil Bartakke
Paper ID: V5I6-1230
Paper Status: published
Published: December 3, 2019
Performance of fusion algorithm for active sonar detection in underwater acoustic reverberation environment
In the active SONAR system, the detection of a target is performed by Matched-Filter processing proceeded by a Constant False Alarm Rate (CFAR) thresholding method. CFAR alone is a not a competent method, to annihilate the invalid echoes. This method on sole does not attain the best pursuance under the reverberation scenario in the non-homogeneous condition of the acoustic environment. In this, the paper Fusion algorithm is recommended for active sonar application, where the CA-CFAR and Support Vector Machine (SVM) based classification method are together used to annihilate the invalid echoes and simultaneously improve the detection of valid echoes. In this paper, a comparison of linear and non-linear SVM with the CA-CFAR method is proposed for elevating the performance of detecting the valid echoes and annihilates the invalid echoes. The interpretation of the algorithm is accomplished using measured data.
Published by: Korla Jayanthi
Author: Korla Jayanthi
Paper ID: V5I6-1224
Paper Status: published
Published: December 2, 2019
Application of deep Neural Networks for object detection in satellite images
The rapid growth in satellite imagery has helped scientists understand the Earth better. The improved understanding of the Earth makes it possible for scientists to perform better in all activities that range from disaster management in the form of mobilizing resources to comprehend global warming by monitoring its effects. The major limitation of this achievement is the assumption that significant features in satellite images, like buildings, roads, trees, or water bodies, can be easily identified, either manually or semi-automatically, but always perfectly. In this paper to overcome this limitation, we use different convolutional neural networks with modifications such as proposed PSPNet, U-net architecture, Inverted pyramid and XGBoost algorithm for accurately detecting specified features in satellite images from Defense Science and Technology Laboratory (DSTL) database. Automation of feature detection in satellite images is not only useful in making smart and quick decisions, but also in bringing innovation in the application of computer vision methodologies to satellite imagery.
Published by: Akhilesh Kakade, Vikas C. Kakade
Author: Akhilesh Kakade
Paper ID: V5I6-1221
Paper Status: published
Published: December 2, 2019
Measuring employee motivation levels in an educational organisation
The study examined the motivation levels of employees of an educational institution. Employee motivation levels tend to have an influential impact on performance levels of the workforce as well as the success of the organization. The employees have ranked twenty factors of motivation on a constructed questionnaire and the results have further been interpreted in order to move beyond the usual ways of using pay as a motivating factor and suggesting better ways in order to keep the workforce motivated, keeping in mind the organizational policies of the institution.
Published by: Ananya Sood
Author: Ananya Sood
Paper ID: V5I6-1213
Paper Status: published
Published: December 2, 2019
Skin cancer detection using Digital Image Segmentation
The detection of skin cancer in the earlier stage is very important and critical. In recent days, skin cancer is seen as one of the most Hazardous forms of the Cancers found in Humans. Skin cancer is found in various types such as Melanoma, Basal and Squamous cell Carcinoma among which Melanoma is the most unpredictable. The detection of Melanoma cancer in an early stage can be helpful to cure it. Computer vision can play an important role in Medical Image Diagnosis and it has been proved by many existing systems. In this paper, we present a computer-aided method for the detection of Melanoma Skin Cancer using Image processing tools.
Published by: Dindi Dhanunjai, Kotur Guna Pragna
Author: Dindi Dhanunjai
Paper ID: V5I6-1168
Paper Status: published
Published: November 30, 2019
