scholarly journals Driver Behavior Modeling: Developments and Future Directions

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Najah AbuAli ◽  
Hatem Abou-zeid
Keyword(s):  
Fog Computing ◽  
Driver Behavior ◽  
Behavior Modeling ◽  
Mobile Cloud ◽  
Context Aware ◽  
Design Development ◽  
Future Directions ◽  
Research Challenges ◽  
Recent Developments ◽  
Behavior Models

The advances in wireless communication schemes, mobile cloud and fog computing, and context-aware services boost a growing interest in the design, development, and deployment of driver behavior models for emerging applications. Despite the progressive advancements in various aspects of driver behavior modeling (DBM), only limited work can be found that reviews the growing body of literature, which only targets a subset of DBM processes. Thus a more general review of the diverse aspects of DBM, with an emphasis on the most recent developments, is needed. In this paper, we provide an overview of advances of in-vehicle and smartphone sensing capabilities and communication and recent applications and services of DBM and emphasize research challenges and key future directions.

scholarly journals Wearable technologies for active living and rehabilitation: Current research challenges and future opportunities

2019 ◽  
Vol 6 ◽  
pp. 205566831983960 ◽  
Author(s):  
Mary M Rodgers ◽  
Gad Alon ◽  
Vinay M Pai ◽  
Richard S Conroy
Keyword(s):  
Wearable Sensors ◽  
Active Living ◽  
Future Directions ◽  
Wearable Technologies ◽  
Future Developments ◽  
Research Challenges ◽  
Recent Developments

This paper presents some recent developments in the field of wearable sensors and systems that are relevant to rehabilitation and provides examples of systems with evidence supporting their effectiveness for rehabilitation. A discussion of current challenges and future developments for selected systems is followed by suggestions for future directions needed to advance towards wider deployment of wearable sensors and systems for rehabilitation.

scholarly journals Context-aware rule learning from smartphone data: survey, challenges and future directions

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Iqbal H. Sarker
Keyword(s):  
Intelligent Systems ◽  
Data Analytics ◽  
Rule Learning ◽  
Analytical Techniques ◽  
Context Aware ◽  
Learning Context ◽  
Future Directions ◽  
Intelligent Decision Making ◽  
Recent Developments ◽  
Data Survey

Abstract Smartphones are considered as one of the most essential and highly personal devices of individuals in our current world. Due to the popularity of context-aware technology and recent developments in smartphones, these devices can collect and process raw contextual data about users’ surrounding environment and their corresponding behavioral activities with their phones. Thus, smartphone data analytics and building data-driven context-aware systems have gained wide attention from both academia and industry in recent days. In order to build intelligent context-aware applications on smartphones, effectively learning a set of context-aware rules from smartphone data is the key. This requires advanced data analytical techniques with high precision and intelligent decision making strategies based on contexts. In comparison to traditional approaches, machine learning based techniques provide more effective and efficient results for smartphone data analytics and corresponding context-aware rule learning. Thus, this article first makes a survey on previous work in the area of contextual smartphone data analytics and then presents a discussion of challenges and future directions for effectively learning context-aware rules from smartphone data, in order to build rule-based automated and intelligent systems.

Green Synthesized Nanomaterials as Theranostic Platforms for Cancer Treatment: Principles, Challenges and the Road Ahead

2019 ◽  
Vol 26 (8) ◽  
pp. 1311-1327 ◽  
Author(s):  
Pala Rajasekharreddy ◽  
Chao Huang ◽  
Siddhardha Busi ◽  
Jobina Rajkumari ◽  
Ming-Hong Tai ◽  
...  
Keyword(s):  
Nanoparticle Synthesis ◽  
Research Field ◽  
Synthesis Methods ◽  
Synthetic Approach ◽  
Future Directions ◽  
The Road ◽  
New Methods ◽  
Recent Developments ◽  
Theranostic Applications ◽  
Insight Into

With the emergence of nanotechnology, new methods have been developed for engineering various nanoparticles for biomedical applications. Nanotheranostics is a burgeoning research field with tremendous prospects for the improvement of diagnosis and treatment of various cancers. However, the development of biocompatible and efficient drug/gene delivery theranostic systems still remains a challenge. Green synthetic approach of nanoparticles with low capital and operating expenses, reduced environmental pollution and better biocompatibility and stability is a latest and novel field, which is advantageous over chemical or physical nanoparticle synthesis methods. In this article, we summarize the recent research progresses related to green synthesized nanoparticles for cancer theranostic applications, and we also conclude with a look at the current challenges and insight into the future directions based on recent developments in these areas.

Duality beyondPersons and Groups

2020 ◽  
pp. 391-413
Author(s):  
Sophie Mützel ◽  
Ronald Breiger
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Data ◽  
Future Directions ◽  
Affiliation Networks ◽  
The Social ◽  
Recent Developments ◽  
Principle Of Duality ◽  
Seminal Article

This chapter focuses on the general principle of duality, which was originally introduced by Simmel as the intersection of social circles. In a seminal article, Breiger formalized Simmel’s idea, showing how two-mode types of network data can be transformed into one-mode networks. This formal translation proved to be fundamental for social network analysis, which no longer needed data on who interacted with whom but could work with other types of data. In turn, it also proved fundamental for the analysis of how the social is structured in general, as many relations are dual (e.g. persons and groups, authors and articles, organizations and practices), and are thus susceptible to an analysis according to duality principles. The chapter locates the concept of duality within past and present sociology. It also discusses the use of duality in the analysis of culture as well as in affiliation networks. It closes with recent developments and future directions.

scholarly journals The Past, Present and Future of Cannabis sativa Tissue Culture

Plants ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 185
Author(s):  
Adrian S. Monthony ◽  
Serena R. Page ◽  
Mohsen Hesami ◽  
Andrew Maxwell P. Jones
Keyword(s):  
Tissue Culture ◽  
Disease Virus ◽  
Cannabis Sativa ◽  
Clonal Plants ◽  
Future Directions ◽  
The Past ◽  
Recent Developments ◽  
History Of ◽  
Drug Type

The recent legalization of Cannabis sativa L. in many regions has revealed a need for effective propagation and biotechnologies for the species. Micropropagation affords researchers and producers methods to rapidly propagate insect-/disease-/virus-free clonal plants and store germplasm and forms the basis for other biotechnologies. Despite this need, research in the area is limited due to the long history of prohibitions and restrictions. Existing literature has multiple limitations: many publications use hemp as a proxy for drug-type Cannabis when it is well established that there is significant genotype specificity; studies using drug-type cultivars are predominantly optimized using a single cultivar; most protocols have not been replicated by independent groups, and some attempts demonstrate a lack of reproducibility across genotypes. Due to culture decline and other problems, the multiplication phase of micropropagation (Stage 2) has not been fully developed in many reports. This review will provide a brief background on the history and botany of Cannabis as well as a comprehensive and critical summary of Cannabis tissue culture. Special attention will be paid to current challenges faced by researchers, the limitations of existing Cannabis micropropagation studies, and recent developments and future directions of Cannabis tissue culture technologies.

scholarly journals Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions

2021 ◽  
Vol 11 (4) ◽  
pp. 1627
Author(s):  
Yanbin Li ◽  
Gang Lei ◽  
Gerd Bramerdorfer ◽  
Sheng Peng ◽  
Xiaodong Sun ◽  
...  
Keyword(s):  
Machine Learning ◽  
Design Optimization ◽  
Optimization Methods ◽  
Machine Learning Algorithms ◽  
Cloud Services ◽  
Robust Design Optimization ◽  
Support Vector ◽  
Future Directions ◽  
Electromagnetic Devices ◽  
Recent Developments

This paper reviews the recent developments of design optimization methods for electromagnetic devices, with a focus on machine learning methods. First, the recent advances in multi-objective, multidisciplinary, multilevel, topology, fuzzy, and robust design optimization of electromagnetic devices are overviewed. Second, a review is presented to the performance prediction and design optimization of electromagnetic devices based on the machine learning algorithms, including artificial neural network, support vector machine, extreme learning machine, random forest, and deep learning. Last, to meet modern requirements of high manufacturing/production quality and lifetime reliability, several promising topics, including the application of cloud services and digital twin, are discussed as future directions for design optimization of electromagnetic devices.

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