Xiao Laisheng

Bio: Xiao Laisheng is an academic researcher from Guangdong Ocean University. The author has contributed to research in topics: The Internet & Semantic grid. The author has an hindex of 4, co-authored 6 publications receiving 105 citations.

Cloud Computing: A New Business Paradigm for E-learning

Abstract: At present, most of conventional education forms are becoming not being suitable for requirements of social progress and educational development and not being able to catch up with the changes of learning demand in time, thus computer networks have brought opportunities for it. However, in traditional web-based e-learning mode, system construction and maintenance are located in interior of educational institutions or enterprises, which results in a lot of problems existed, such as a lot of investment needed, but without capital gains to return, without development potential and staying power. Cloud computing that introduces efficient scale mechanism can let construction of e-learning system be entrusted to suppliers and provide a new mode for e-learning. In this paper, we introduced cloud computing to e-learning, built an e-learning cloud, and made an active research and exploration for it from the following aspects: its work mode, architecture, construction method, external interface with the business model, challenges and solutions etc. Our results suggest that the introduction of cloud computing into e-learning is feasible and it can greatly improve the efficiency of investment and the power of management, which can make e-learning system development into a virtuous circle and achieve a win-win situation for suppliers and customers.

Modern Logistics Monitoring Platform Based on the Internet of Things

Abstract: In this paper, a modern logistics monitoring platform based on the Internet of Things was studied and its system architecture and functions were particularly designed. The platform was designed based on the following technologies. In aspect of goods identification, a global unified electronic product code EPC was adopted and each goods was given a unique code that was according with international standards. Reading and writing EPC data was by taking use of RFID technology, which read data from electronic tags via a wireless non-contact method. In aspect of goods code management, new concepts of dynamic EPC and static EPC were proposed for goods in transport and movement. Through introduction of dynamic EPC and static EPC, data flow significantly was reduced, the management process was simplified and management efficiency was improved. In aspect of network transmission, both wired network and wireless network were taken for transmission task. Wired networks were available based on Internet and LAN. For mobile sites, wireless network GRPS was used for communication. In aspect of positioning goods, global positioning system GPS was used for location and tracking of goods. In aspect of platform function design, the system’s function requirements were analyzed and designed, and a series of its functions were proposed, such as real-time data acquisition, automatic alarm, remote control, data control and processing, historical information record and product quality safety tracing, market analysis and intelligent projections etc.. Modern logistics monitoring platform based on the Internet of Things, because of its advanced technologies, excellent performances and integrated functions, would play an important role in the development of modern logistics.

Remote Diagnosis and Control Expert System for Citrus Agricultural Diseases and Insect Pests Based on BP Neural Network and WebGIS

Abstract: In this paper, on the basis of full investigation and a lot of comparison with expert systems at home and abroad, introducing Web technology, WebGIS and BP neural network technology into expert system and taking full use of their respective advantages, we have designed and developed a remote diagnosis and control expert system for citrus agricultural diseases and insect pests based on WebGIS and BP neural network. We put emphases on the design of forward inference engine based on neural network and reverse inference engine based on rule system. In the whole expert system, neural network serves as a forward inference engine for the expert system. It accepts standardized raw data input of the diseases and insect pests and gives the diagnosis conclusion after reasoning process. Reverse reasoning is made by rule system, which is going to verify the diagnosis conclusions provided by neural network. In this way, the reasoning speed of entire system and correct diagnosis rate are greatly increased. At the same time, the rule system provides control methods for diseases and insect pests according to the diagnosis conclusions and also provides its geographical distribution information based on GIS. The experimental results show that the expert system has an accurate and reliable performance, so it has a good promotion prospects for applications.

Multi-polar Autonomous System Grid Resource Scheduling Model and Algorithm Based on Multi-agent and GA

Abstract: General sharing of information resources on the Internet has already be achieved through Internet technology. But the goal of grid is trying to achieve a comprehensive connectivity and sharing for all resources on the Internet, providing high-performance computing services for users. In this paper, grid resource scheduling was studied and according to the current research about it some innovation and improvement for it were made from the following aspects.

Living space evolution: a new crowd based computational approach

Abstract: Inspired by the life cycle and survival of the fittest and combined with the consideration of living space information, a new computational intelligence approach, namely, living space evolution (LSE), is presented. LSE has reflected two new ideas. One is living space evolution: under the guidance of living space information, the offspring of life concentrate and evolve continuously towards richer living spaces. The other is multiple offspring reproduction: simulating real life in nature, a life can reproduce multiple offspring within one generation. In this work, LSE dynamic model, its flow, and pseudocodes are described in detail. A digital simulation has shown the procedure of LSE living space evolution. Furthermore, two applications of using LSE are employed to demonstrate its effectiveness and applicability. One is to apply it to the optimization for continuous functions, and the other is to use it as an optimization tool for routing protocol in wireless sensor network that is a discrete problem in real world. Research has shown that LSE is effective for the optimization for the continuous functions and also applicable for the discrete problem in real world. In addition, LSE has a special ability to balance search process from exploration to exploitation gradually.

The Internet of Things--A survey of topics and trends

Abstract: The Internet of Things is a paradigm where everyday objects can be equipped with identifying, sensing, networking and processing capabilities that will allow them to communicate with one another and with other devices and services over the Internet to accomplish some objective. Ultimately, IoT devices will be ubiquitous, context-aware and will enable ambient intelligence. This article reports on the current state of research on the Internet of Things by examining the literature, identifying current trends, describing challenges that threaten IoT diffusion, presenting open research questions and future directions and compiling a comprehensive reference list to assist researchers.

A Complex View of Industry 4.0

Abstract: This article is focused on the importance and influence of Industry 4.0 and consequently the Internet-connected technologies for the creation of value added for organizations and society. The contribution of the article is mainly conceptual. With the development of the Internet, the Internet of things that is central to the new industrial revolution has led to “Industry 4.0.” The aim of this article is to synthesize the known theory and practices of Industry 4.0, and to investigate the changes that will result from Industry 4.0 and with the development of the Internet of things.

Cloud computing and education

Abstract: This paper surveys the state of the art on the use and research of cloud computing in education following a systematic methodology. After a comprehensive search of the scientific literature, 112 works were selected for the review. The survey identifies and analyzes the advantages and risks that the use of cloud computing may have for the main stakeholders in education, which can be useful to identify the scenarios in which the use of cloud computing in an educational context may have significant advantages. Furthermore, the survey categorizes and discusses the main technical and domain-specific research challenges, thus facilitating researchers the task of finding relevant issues, in which they can focus their efforts. We review 112 scientific works on cloud computing in education up to 2012.The survey takes into account the main educational stakeholders.Advantages and risks of cloud in education are categorized and exemplified.We identify and discuss promising technical and domain-specific research issues.

Developing online learning resources: Big data, social networks, and cloud computing to support pervasive knowledge

Abstract: Utilizing online learning resources (OLR) from multi channels in learning activities promise extended benefits from traditional based learning-centred to a collaborative based learning-centred that emphasises pervasive learning anywhere and anytime. While compiling big data, cloud computing, and semantic web into OLR offer a broader spectrum of pervasive knowledge acquisition to enrich users' experience in learning. In conventional learning practices, a student is perceived as a recipient of information and knowledge. However, nowadays students are empowered to involve in learning processes that play an active role in creating, extracting, and improving OLR collaborative learning platform and knowledge sharing as well as distributing. Researchers have employed contents analysis for reviewing literatures in peer-reviewed journals and interviews with the teachers who utilize OLR. In fact, researchers propose pervasive knowledge can address the need of integrating technologies like cloud computing, big data, Web 2.0, and Semantic Web. Pervasive knowledge redefines value added, variety, volume, and velocity of OLR, which is flexible in terms of resources adoption, knowledge acquisition, and technological implementation.

An intelligent model for logistics management based on geofencing algorithms and RFID technology

Abstract: The proposed model manages travels and cargos, without user interaction.We developed a hardware that obtains context information using RFID technology.The model uses context information and geofencing algorithms to perform decisions.The model sends notifications, speeding decision-making up, and reducing costs. The cargo transport represents the largest share of logistics costs in most companies. Consequently, companies are investing in tracking and tracing systems aiming to improve services, reduce costs and ensure the safety in cargo transportation. To play a part in this area, we propose in this article SafeTrack, a model for logistics management based on geofencing algorithms and radio-frequency technology. In this approach, the focus is on dealing with delivery management. The main scientific contribution of SafeTrack is automatic delivery management. Besides dealing with deliveries without user interaction, we provide a mechanism to detect inconsistencies at real-time. Furthermore, the model monitors detours in planned routes and deals with alarms notifications using mobile devices. To provide that features, we employed Geofence concept with two solutions that enable to detect, in real-time, the occurrence of detours in planned routes. We also created a component, named SafeDuino, to control loads delivery and pickups. The decision on the occurrence of inconsistencies during the logistics flow is performed through the fusion of context information, obtained from SafeDuino and a mobile device, using radio-frequency technology. We built a complete and functional prototype, which was evaluated in a controlled environment, testing several conditions. The test scenario was executed twenty times, showing that the proposed model is capable to identify all inconsistencies along the travels. We concluded that SafeTrack improves logistics operation, optimizing decision-making, avoiding losses during the logistics flow, and also allowing companies to remain competitive in the market.