A Comprehensive Survey of Neural Architecture Search

2021 ◽  
Vol 54 (4) ◽  
pp. 1-34
Author(s):  
Pengzhen Ren ◽  
Yun Xiao ◽  
Xiaojun Chang ◽  
Po-yao Huang ◽  
Zhihui Li ◽  
...  
Keyword(s):  
Research Work ◽  
Search Space ◽  
Feature Representation ◽  
Future Research ◽  
Related Research ◽  
Neural Architecture ◽  
Comprehensive Survey ◽  
Future Research Directions ◽  
Intuitive Idea ◽  
New Perspective

Deep learning has made substantial breakthroughs in many fields due to its powerful automatic representation capabilities. It has been proven that neural architecture design is crucial to the feature representation of data and the final performance. However, the design of the neural architecture heavily relies on the researchers’ prior knowledge and experience. And due to the limitations of humans’ inherent knowledge, it is difficult for people to jump out of their original thinking paradigm and design an optimal model. Therefore, an intuitive idea would be to reduce human intervention as much as possible and let the algorithm automatically design the neural architecture. Neural Architecture Search ( NAS ) is just such a revolutionary algorithm, and the related research work is complicated and rich. Therefore, a comprehensive and systematic survey on the NAS is essential. Previously related surveys have begun to classify existing work mainly based on the key components of NAS: search space, search strategy, and evaluation strategy. While this classification method is more intuitive, it is difficult for readers to grasp the challenges and the landmark work involved. Therefore, in this survey, we provide a new perspective: beginning with an overview of the characteristics of the earliest NAS algorithms, summarizing the problems in these early NAS algorithms, and then providing solutions for subsequent related research work. In addition, we conduct a detailed and comprehensive analysis, comparison, and summary of these works. Finally, we provide some possible future research directions.

scholarly journals Carpooling in Connected and Autonomous Vehicles: Current Solutions and Future Directions

2022 ◽  
Author(s):  
Farkhanda Zafar ◽  
Hasan Ali Khattak ◽  
Moayad Aloqaily ◽  
Rasheed Hussain
Keyword(s):  
Business Model ◽  
Autonomous Vehicles ◽  
Research Work ◽  
Relevant Information ◽  
Security And Privacy ◽  
Future Research ◽  
Research Directions ◽  
Comprehensive Survey ◽  
One Stop ◽  
Future Research Directions

Owing to the advancements in communication and computation technologies, the dream of commercialized connected and autonomous cars is becoming a reality. However, among other challenges such as environmental pollution, cost, maintenance, security, and privacy, the ownership of vehicles (especially for Autonomous Vehicles (AV)) is the major obstacle in the realization of this technology at the commercial level. Furthermore, the business model of pay-as-you-go type services further attracts the consumer because there is no need for upfront investment. In this vein, the idea of car-sharing ( aka carpooling) is getting ground due to, at least in part, its simplicity, cost-effectiveness, and affordable choice of transportation. Carpooling systems are still in their infancy and face challenges such as scheduling, matching passengers interests, business model, security, privacy, and communication. To date, a plethora of research work has already been done covering different aspects of carpooling services (ranging from applications to communication and technologies); however, there is still a lack of a holistic, comprehensive survey that can be a one-stop-shop for the researchers in this area to, i) find all the relevant information, and ii) identify the future research directions. To fill these research challenges, this paper provides a comprehensive survey on carpooling in autonomous and connected vehicles and covers architecture, components, and solutions, including scheduling, matching, mobility, pricing models of carpooling. We also discuss the current challenges in carpooling and identify future research directions. This survey is aimed to spur further discussion among the research community for the effective realization of carpooling.

MetaLearning with Graph Neural Networks

2021 ◽  
Vol 23 (2) ◽  
pp. 13-22
Author(s):  
Debmalya Mandal ◽  
Sourav Medya ◽  
Brian Uzzi ◽  
Charu Aggarwal
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Future Research ◽  
Open Problems ◽  
Research Directions ◽  
Graph Problems ◽  
Meta Learning ◽  
Comprehensive Survey ◽  
Future Research Directions ◽  
Graph Neural Networks

Graph Neural Networks (GNNs), a generalization of deep neural networks on graph data have been widely used in various domains, ranging from drug discovery to recommender systems. However, GNNs on such applications are limited when there are few available samples. Meta-learning has been an important framework to address the lack of samples in machine learning, and in recent years, researchers have started to apply meta-learning to GNNs. In this work, we provide a comprehensive survey of different metalearning approaches involving GNNs on various graph problems showing the power of using these two approaches together. We categorize the literature based on proposed architectures, shared representations, and applications. Finally, we discuss several exciting future research directions and open problems.

Business-IT Alignment Literature Review

2018 ◽  
Vol 31 (3) ◽  
pp. 34-53 ◽  
Author(s):  
Yu Jia ◽  
Nianxin Wang ◽  
Shilun Ge
Keyword(s):  
Citation Analysis ◽  
Knowledge Flows ◽  
Intellectual Structure ◽  
Future Research ◽  
Research Directions ◽  
It Alignment ◽  
Research Themes ◽  
Future Research Directions ◽  
Business It Alignment ◽  
New Perspective

The purpose of this article is to portray the knowledge evolution paths of business-IT alignment (BITA) research and identify a set of important papers in the development of BITA, and elucidate the intellectual structure of this field. This study collected 309 papers published during the period 1983-2015 from the Web of Science (WOS) database. Using a variety of bibliometric and visualization analytic techniques such as citation analysis, co-citation analysis and main path analysis, this article (1) delineates the significant knowledge flows of BITA research and identifies 15 important papers in this field; (2) graphically maps the influential countries, institutions, and journals of BITA research; (3) identifies four major research themes: BITA model, measurement, antecedents, and dynamics, and visualizing the relationships among them. Based on these findings, recommendations for the future research directions have suggested. This article provides IT practitioners, executives, and scholars with a new perspective to get a better understanding of BITA.

Extending Workflows for Knowledge Flow Automation

2012 ◽  
pp. 199-211
Author(s):  
Surendra Sarnikar ◽  
J. Leon Zhao
Keyword(s):  
Business Processes ◽  
Knowledge Flow ◽  
Future Research ◽  
Transfer Of Knowledge ◽  
Research Directions ◽  
Workflow Technology ◽  
Workflow Systems ◽  
Future Research Directions ◽  
New Perspective ◽  
Seamless Transfer

Effective execution of business processes also requires the provisioning of relevant knowledge to workers in various business contexts. Knowledge flow automation aims to enable seamless transfer of knowledge by supporting the capture and sharing of organizational knowledge related to business processes. Given the strong correlation between the flow of work and the flow of knowledge, workflow systems are a natural platform for supporting knowledge flow. However, existing workflow technology does not yet provide the needed mechanisms suitable for supporting knowledge flow. This chapter presents an overview of different types of workflow-based knowledge management systems that provide knowledge workers with the required knowledge while supporting the flow of work. In addition, a new perspective is presented on extending workflows to support knowledge transfer processes by introducing the concept of “knowledge workflows” and outline future research directions in this area.

State of the Art and Key Design Challenges of Telesurgical Robotics

2019 ◽  
pp. 1100-1111
Author(s):  
Sajid Nisar ◽  
Osman Hasan
Keyword(s):  
State Of The Art ◽  
Robotic Systems ◽  
Future Research ◽  
Research Directions ◽  
Remote Locations ◽  
Comprehensive Survey ◽  
Future Research Directions ◽  
Surgical System ◽  
Surgical Operations ◽  
Design Challenges

Telesurgical robotic systems allow surgeons to perform surgical operations from remote locations with enhanced comfort and dexterity. Introduction of robotic technology has revolutionized operation theaters but its multidisciplinary nature and high associated costs pose significant challenges. This chapter provides a comprehensive survey of the current progress in the field of surgical robotics with a detailed discussion on various state-of-the-art telesurgical robotic systems. The key design approaches and challenges are identified, and their solutions are recommended. A set of parameters that can be used to assess usefulness of a telesurgical robot are discussed. Finally, guidelines for selection of a suitable surgical system and the future research directions are described.

A Survey of Recent Approaches Integrating Blogs in School Education

2021 ◽  
pp. 229-245
Author(s):  
Stavros Tsetsos ◽  
Jim Prentzas
Keyword(s):  
Secondary Education ◽  
Web 2.0 ◽  
Research Work ◽  
School Education ◽  
Future Research ◽  
Research Directions ◽  
Web 2.0 Tools ◽  
Primary And Secondary Education ◽  
Future Research Directions ◽  
Enhanced Learning

Web 2.0 tools are frequently integrated in education. The main goal of this integration is to provide enhanced learning experiences to students. Among other Web 2.0 tools, blogs are often used. Many approaches have been presented that successfully exploited blogs in all levels of education. An aspect of interest is to outline main directions of the corresponding research work that will provide insight to researchers, teachers, students, developers, and policymakers. This chapter provides a brief survey of approaches integrating blogs in primary and secondary education. Initially, main concepts regarding blogs as Web 2.0 tools and educational blogs are briefly discussed. Then, 16 approaches concerning the use of blogs in primary and secondary education are surveyed. The results derived from these approaches are analyzed. The analysis shows that the results are positive, and blogs turn out to be useful tools for school education. It is likely that more such approaches will be presented in the future. The chapter also outlines future research directions.

scholarly journals Deep Learning for Generic Object Detection: A Survey

2019 ◽  
Vol 128 (2) ◽  
pp. 261-318 ◽  
Author(s):  
Li Liu ◽  
Wanli Ouyang ◽  
Xiaogang Wang ◽  
Paul Fieguth ◽  
Jie Chen ◽  
...  
Keyword(s):  
Deep Learning ◽  
Object Detection ◽  
Rapid Evolution ◽  
Feature Representation ◽  
Future Research ◽  
Context Modeling ◽  
Feature Representations ◽  
Learning Techniques ◽  
Comprehensive Survey ◽  
Object Feature

Abstract Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined categories in natural images. Deep learning techniques have emerged as a powerful strategy for learning feature representations directly from data and have led to remarkable breakthroughs in the field of generic object detection. Given this period of rapid evolution, the goal of this paper is to provide a comprehensive survey of the recent achievements in this field brought about by deep learning techniques. More than 300 research contributions are included in this survey, covering many aspects of generic object detection: detection frameworks, object feature representation, object proposal generation, context modeling, training strategies, and evaluation metrics. We finish the survey by identifying promising directions for future research.

scholarly journals Authentication Protocols for Internet of Things: A Comprehensive Survey

2017 ◽  
Vol 2017 ◽  
pp. 1-41 ◽  
Author(s):  
Mohamed Amine Ferrag ◽  
Leandros A. Maglaras ◽  
Helge Janicke ◽  
Jianmin Jiang ◽  
Lei Shu
Keyword(s):  
Internet Of Things ◽  
Future Research ◽  
Communication Overhead ◽  
Authentication Protocols ◽  
Internet Of Vehicles ◽  
Current Survey ◽  
Comprehensive Survey ◽  
Future Research Directions ◽  
Target Environment ◽  
Verification Techniques

In this paper, a comprehensive survey of authentication protocols for Internet of Things (IoT) is presented. Specifically more than forty authentication protocols developed for or applied in the context of the IoT are selected and examined in detail. These protocols are categorized based on the target environment: (1) Machine to Machine Communications (M2M), (2) Internet of Vehicles (IoV), (3) Internet of Energy (IoE), and (4) Internet of Sensors (IoS). Threat models, countermeasures, and formal security verification techniques used in authentication protocols for the IoT are presented. In addition a taxonomy and comparison of authentication protocols that are developed for the IoT in terms of network model, specific security goals, main processes, computation complexity, and communication overhead are provided. Based on the current survey, open issues are identified and future research directions are proposed.

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