Short-term traffic forecasting is becoming more important in intelligent transportation systems. The k-nearest neighbours (kNN) method is widely used for short-term traffic forecasting. However, the self-adjustment of kNN parameters has been a problem due to dynamic traffic characteristics. This paper proposes a fully automatic dynamic procedure kNN (DP-kNN) that makes the kNN parameters self-adjustable and robust without predefined models or training for the parameters. A real-world dataset with more than one year traffic records is used to conduct experiments. The results show that DP-kNN can perform better than manually adjusted kNN and other benchmarking methods in terms of accuracy on average. This study also discusses the difference between holiday and workday traffic prediction as well as the usage of neighbour distance measurement.

ABSTRACT

Health data integration enables a collaborative utilization of data across different systems. It not only provides a comprehensive view of a patient’s health but can also potentially cope with challenges faced by the current healthcare system. In this literature review, we investigated the existing work on heterogeneous health data integration as well as the methods of utilizing the integrated health data. Our search was narrowed down to 32 articles for analysis. The integration approaches in the reviewed articles were classified into three classifications, and the utilization approaches were classified into five classifications. The topic of health data integration is still under debate and problems are far from being resolved. This review suggests the need for a more efficient way to invoke the various services for aggregating health data, as well as a more effective way to integrate the aggregated health data for supporting collaborative utilization. We have found that the combination of Web Application Programming Interface and Semantic Web technologies has the potential to cope with the challenges based on our analysis of the review result.

This paper proposes an epistemological model based on cybernetic principles and activity theory to interpret two levels of problems that are intertwined in our social-economic system, namely the liveability and sustainability problems. In the first part of the paper, important principles and concepts from related fields of cybernetics and activity theory are introduced for later construction of a model. In the second part, a model is constructed based on the introduced concepts. To validate the proposed model, the current economic crisis is studied in the third part. An important contribution of the proposed model is a theoretical understanding of the two levels problems, and how to construct macro social-economical policies to avoid similar crisis in the future.

Abstract-Intelligent transportation systems (ITS) are becoming more and more effective, benefiting from big data. Despite this, missing data is a problem that prevents many prediction algorithms in ITS from working effectively. Much work has been done to impute those missing data. Among different imputation methods, k-nearest neighbours (kNN) has shown excellent accuracy and efficiency. However, the general kNN is designed for matrix instead of time series so it lacks the usage of time series characteristics such as windows and weights that are gap-sensitive. This work introduces gap-sensitive windowed kNN (GSW-kNN) imputation for time series. The results show that GSW-kNN is 34% more accurate than benchmarking methods, and it is still robust even if the missing ratio increases to 90%.

No abstract

This paper will approach the nature of system development based on dialectical thinking. To conduct this approach, the paper is divided into three parts. In the first part, the concept "contradiction' is introduced in the context of dialectical thinking. In the second part, "systems development' is discussed in terms of contradiction in the Activity Theory. And in the last part, "information systems development' is presented as an example to demonstrate how information systems are developed in the light of this dialectical approach. © 1998 John Wiley & Sons, Ltd.

Abstract-eHealth is an emerging area that boosts up with advancement in Information and Communication Technology (ICT). Due to variety of eHealth solutions developed by different IT firms with no unified standards, interoperability issue has raised. In this paper, a case study in Blekinge County healthcare organizations has been conducted for understanding the contexts of eHealth interoperability issues. Then a peer-to-peer (P2P) model based on JXTA platform is implemented to solve the identified eHealth interoperability problems. According to the test result of the prototype, the suggested syntactic level interoperability among healthcare organizations has been achieved.