scholarly journals A Recommendation System for Cloud Services Selection Based on Intelligent Agents

2018 ◽  
Vol 11 (9) ◽  
pp. 1-6
Author(s):  
Abid Mahmood ◽  
Umar Shoaib ◽  
M. Shahzad Sarfraz ◽  
◽  
◽  
...  
Keyword(s):  
Intelligent Agents ◽  
Recommendation System ◽  
Cloud Services

scholarly journals E-Learning Recommendation System for Big Data Based on Cloud Computing

2021 ◽  
Vol 16 (21) ◽  
pp. 177
Author(s):  
Mounia Rahhali ◽  
Lahcen Oughdir ◽  
Youssef Jedidi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Academic Success ◽  
Recommendation System ◽  
Learning Experience ◽  
Research Work ◽  
Cloud Services ◽  
Data Sets ◽  
E Learning ◽  
Processing Optimization

In educational institutions, E-learning has been known as a successful technology for enhancing performance, concentration, and thus providing higher academic success. Nevertheless, the conventional system for executing research work and selecting courses is a time-consuming and unexciting practice, that not only directly impacts the students ’ academic achievement but also impacts the learning experience of students. In addition to that, there is an enormous number of various kinds of data in the E-Learning domain both structured and unstructured, and the academic establishments attempt to manage and understand big complicated data sets. To fix this problem, this paper proposes a model of an E-learning recommendation system that will suggest and encourage the learner in choosing the courses according to their needs. This system used big data tools such as Hadoop and Spark to enhance data collection, storage, analysis, processing, optimization, and visualization, furthermore based on cloud computing infrastructure and especially Google cloud services.

Digital Twin-Based Control Approach for Industrial Cloud Robotics

2019 ◽  
Author(s):  
Lan Li ◽  
Wenjun Xu ◽  
Zhihao Liu ◽  
Bitao Yao ◽  
Zude Zhou ◽  
...  
Keyword(s):  
Intelligent Agents ◽  
Effective Means ◽  
Physical World ◽  
Cloud Services ◽  
Industrial Robots ◽  
Control Approach ◽  
Digital Twin ◽  
Digital World ◽  
Cloud Robotics ◽  
Industrial Cloud

Abstract Industrial robots can be mechanical intelligent agents by integrating programs, intelligent algorithms and facilitating intelligent manufacturing models from cyber world into physical entities. After introducing the concept of cloud, their storage, computing, knowledge sharing and evolution capabilities are further strengthened. Digital twin is an effective means to achieve the fusion of physics and information. Therefore, it is feasible to introduce the digital twin to the industrial cloud robotics (ICR), in order to facilitate the control optimization of robots’ running state. The traditional manufacturing task-oriented service composition is limited to execution in the cloud, and it is separated from the underlying robot equipment control, which greatly reduces the real-time performance and accuracy of the underlying service response, such as Robotic Control as a Cloud Service (RCaaCS). Therefore, this paper proposes a digital twin-based control approach for ICR. At the manufacturing cell level, robots’ control instruction service modeling is conducted, and then the control service in the digital world is mapped to the robot action control in the physical world through the concept of digital twin. The accumulated operational data in the physical world can be fed back to the digital world as a reference for simulation and control strategy adjustment, finally achieving the integration of cloud services and robot control. A case study based on workpiece disassembly is presented to verify the availability and effectiveness of the proposed control approach.

Controlled Intelligent Agents' Security Model for Multi-Tenant Cloud Computing Infrastructures

2017 ◽  
Vol 9 (1) ◽  
pp. 1-13
Author(s):  
Howard Hamilton ◽  
Hadi Alasti
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Intelligent Agents ◽  
Cloud Service ◽  
Cloud Services ◽  
Service Users ◽  
Security Model ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Service Models

Data security in the cloud continues to be a huge concern. The adoption of cloud services continues to increase with more businesses transitioning from on premise technology infrastructures to outsourcing cloud-based infrastructures. As the cloud becomes more popular, users are increasingly demanding control over critical security elements of the data and technology assets that are in the cloud. In addition, there are still cries for greater data and security in the cloud. The goal of this paper is to provide cloud service users with greater control over data security in the cloud while at the same time optimizing overall security in the multi-tenant cloud computing environment. This paper introduces cloud-based intelligent agents that are configurable by the users and are expected to give greater compliance for data security in any of the cloud service models.

Time-Slot Based Intelligent Music Recommender in Indian Music

2017 ◽  
pp. 319-351
Author(s):  
Sudipta Chakrabarty ◽  
Samarjit Roy ◽  
Debashis De
Keyword(s):  
Mobile Phones ◽  
Recommendation System ◽  
Time Slot ◽  
Age Groups ◽  
Cloud Services ◽  
Music Listening ◽  
Music Recommendation ◽  
Human Behaviors ◽  
Mobile Music ◽  
Playing Time

Music listening is one of the most common thing of human behaviors. Normally mobile music is downloaded to mobile phones and played by mobile phones. Today millennial people use mobile music in about all the age groups. Music recommendation system enhances personalized music classifications that create a profile with the service and build up a music library based on the choice preferences using mobile cloud services. Music recommendation through cloud is therefore an emerging field, and this can be done using various parameters like song genre similarity, human behavior, human mood, song rhythmic patterns, seasons etc. In this article an intelligent music recommender system that identifies the raga name of one particular song music and then mapping with the raga time database and classify the songs according to their playing time and create time slot based personalized music libraries.

Controlled Intelligent Agents' Security Model for Multi-Tenant Cloud Computing Infrastructures

2018 ◽  
pp. 471-484
Author(s):  
Howard Hamilton ◽  
Hadi Alasti
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Intelligent Agents ◽  
Cloud Service ◽  
Cloud Services ◽  
Service Users ◽  
Security Model ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Service Models

Data security in the cloud continues to be a huge concern. The adoption of cloud services continues to increase with more businesses transitioning from on premise technology infrastructures to outsourcing cloud-based infrastructures. As the cloud becomes more popular, users are increasingly demanding control over critical security elements of the data and technology assets that are in the cloud. In addition, there are still cries for greater data and security in the cloud. The goal of this paper is to provide cloud service users with greater control over data security in the cloud while at the same time optimizing overall security in the multi-tenant cloud computing environment. This paper introduces cloud-based intelligent agents that are configurable by the users and are expected to give greater compliance for data security in any of the cloud service models.

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