Survey Paper on Resume Building Applications

Nowadays getting a good job is a vigorous and vast competition and many fail in the first step i.e., Resume shortlisting due to either imperfect data in the resume or imperfect/wrong resume format. Recruiter hardly takes 10-15 seconds to judge you upon your resume. In this survey paper, we point out a comparative study on different methods used for resume building and which technology is used to build them. Some of the methods use Android applications, some use Desktop applications. This paper makes a detailed analysis and talks about the merits and demerits of various Resume building methods. Keywords: Android applications, Desktop applications, Recruiter, Vigorous, Vast.

A Systematic Review on Data Scarcity Problem in Deep Learning: Solution and Applications

Recent advancements in deep learning architecture have increased its utility in real-life applications. Deep learning models require a large amount of data to train the model. In many application domains, there is a limited set of data available for training neural networks as collecting new data is either not feasible or requires more resources such as in marketing, computer vision, and medical science. These models require a large amount of data to avoid the problem of overfitting. One of the data space solutions to the problem of limited data is data augmentation. The purpose of this study focuses on various data augmentation techniques that can be used to further improve the accuracy of a neural network. This saves the cost and time consumption required to collect new data for the training of deep neural networks by augmenting available data. This also regularizes the model and improves its capability of generalization. The need for large datasets in different fields such as computer vision, natural language processing, security and healthcare is also covered in this survey paper. The goal of this paper is to provide a comprehensive survey of recent advancements in data augmentation techniques and their application in various domains.

Recommended System

In this study searched for the survey paper on recommendation system. Recommendation system sorts through massive amounts of data to identify interest of users and makes the information search easier. For that purpose many methods have been used. Collaborative Filtering (CF) is a method of making automatic predictions about the interests of customers by collecting information from number of other customers, for that purpose many collaborative base algorithms are used. Web Recommendation(WR) help the website visitors for easy navigation of web pages, quickly reaching their destination and to obtain relevant information. Content based filtering method(CBF) filtering is done based on customer’s interested items. In content-based filtering technique, the web pages are recommended for a user very quickly from ancient database. In that database different content of items are added that the user has used in the ancient times and/or user’s personal information and preferences.

Fuel Flowrate Control for Aeroengine and Fuel Thermal Management for Airborne System of Aircraft—An Overview

Fuel flowrate control system and fuel thermal management are very important for aeroengine and the overall aircraft, and it has been researched for several decades. This survey paper makes a comprehensive and systematic overview on the exiting fuel flowrate regulation methods, thermal load of fuel metering units, fuel-based thermal management, and the fuel tank’s thermal management topology network with drain and recirculation. This paper firstly reviews the mechanism, technical advantages, and technical challenges of the fuel metering unit with flowrate control valve and constant pressure difference valve compensator, flowrate control valve and variable displacement pump-based pressure difference compensator, and motor-based flowrate regulation. Then, the technical characteristics of above fuel flowrate control methods related to thermal management are discussed and compared. Meanwhile, the behaviors of recirculated fuel flow within single tank system and dual tank system are explored. Thirdly, the paper discusses the future directions of fuel flowrate control and thermal management. The survey is significant to the fuel flowrate control and fuel thermal management of the aircraft.

A Survey on Internet of Vehicle (IoV): A pplications & Comparison of VANETs, IoV and SDN-IoV

The swift evolution of communication network technologies brings the smart connected objects into existence. The objects or things are connected and able to communicate with each other through Internet of Things (IoT). Internet of Vehicle (IoV) are the subset of the IoT technologies that has been implemented to the vehicle. IoV is the evolution of traditional Vehicular Adhoc Networks (VANETs) bringing new technologies to the smart connected vehicles. IoV network communication is purposedly to serve a real time data exchanged on roads between the vehicles and roads, vehicles and vehicles, vehicle and sensors, and vehicles and everything through different network technologies. There are significant differences between IoV, SDN-IoV and VANETs in term of network architecture, features, and applications that available. IoV and IoV-SDN is using different network framework giving different flexibility and scalability. In term of features and applications, IoV and IoV-SDN are having more wider and broad wireless connection technology in contrast with VANETs. In this survey paper, the survey will focus on the introduction to SDN, and differences of application and features in IoV, SDN-IoV and VANETs.

Thin Distance-Regular Graphs with Classical Parameters $(D,q,q, \frac{q^{t}-1}{q-1}-1)$ with $t> D$ are the Grassmann Graphs

In the survey paper by Van Dam, Koolen and Tanaka (2016), they asked to classify the thin $Q$-polynomial distance-regular graphs. In this paper, we show that a thin distance-regular graph with the same intersection numbers as a Grassmann graph $J_q(n, D)~ (n \geqslant 2D)$ is the Grassmann graph if $D$ is large enough.

A Literature Review of the Detection and Categorization of various Arecanut Diseases using Image Processing and Machine Learning Approaches

Background/Purpose: Every scholarly research project starts with a survey of the literature, which acts as a springboard for new ideas. The purpose of this literature review is to become familiar with the study domain and to assess the work's credibility. It also improves with the subject's integration and summary. This article briefly discusses the detection of disease and classification to achieve the objectives of the study. Objective: The main objective of this literature survey is to explore the different techniques applied to identify and classify the various diseases on arecanut. This paper also recommends the methodology and techniques that can be used to achieve the objectives of the study. Design/Methodology/Approach: Multiple data sources, such as journals, conference proceedings, books, and research papers published in reputable journals, were used to compile the essential literature on the chosen topic and collect information from the arecanuts research centre and many farmers in the south Canara and Udupi districts, before narrowing down the literature that is relevant to the research work. The shortlisted literature was carefully assessed by reading each paper and taking notes as appropriate. The information gathered is then examined to identify the potential gap in the study. Findings/Result: Based on the analysis of the papers reviewed, discussion with farmers and research center officers, it is observed that, not much work is carried out in the field of disease identification and classification on arecanut using machine learning techniques. This survey paper recommends techniques and the methodology that can be applied to identify and classify the diseases in arecanut and to classify them in to healthy and unhealthy. Research limitations/implications: The literature review mentioned in this paper are detection and classification of different diseases in arecanut. Originality/Value: This paper focuses on various online research journals, conference papers, technical books, and web articles. Paper Type: Literature review paper on techniques and methods used to achieve the objectives.

Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on Communication Efficiency and Trustworthiness

A survey paper.

A Meeting Point of Probability, Graphs, and Algorithms: The Lovász Local Lemma and Related Results—A Survey

A classic and fundamental result, known as the Lovász Local Lemma, is a gem in the probabilistic method of combinatorics. At a high level, its core message can be described by the claim that weakly dependent events behave similarly to independent ones. A fascinating feature of this result is that even though it is a purely probabilistic statement, it provides a valuable and versatile tool for proving completely deterministic theorems. The Lovász Local Lemma has found many applications; despite being originally published in 1973, it still attracts active novel research. In this survey paper, we review various forms of the Lemma, as well as some related results and applications.