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Identification of topic changes within a user search session is a key issue in content analysis of search engine user queries. Recently, various studies have focused on new topic identification/session identification of search engine transaction logs, and several problems regarding the estimation of topic shifts and continuations were observed in these studies. This study aims to analyze the reasons for the problems that were encountered as a result of applying automatic new topic identification.

Measures, such as cleaning the data of common words and analyzing the errors of automatic new topic identification, are applied to eliminate the problems in estimating topic shifts and continuations.

The findings show that the resulting errors of automatic new topic identification have a pattern, and further research is required to improve the performance of automatic new topic identification.

Improving the performance of automatic new topic identification would be valuable to search engine designers, so that they can develop new clustering and query recommendation algorithms, as well as custom‐tailored graphical user interfaces for search engine users.

Automatic identification is a fast growing business, but because its methods and applications are so diverse its importance is frequently not appreciated. Jack Hollingum of IFS Publications looks at this essential ingredient in the accelerating trend towards automation in industry and commerce.

The purpose of this paper is to provide algorithms of the automatic landmark extraction software program that are applicable for any torso shape.

In this study, Automatic Landmark Identification (AULID), an automatic landmark extraction software program, was developed to extract consistent landmark locations from any torso shape. A methodology of geometrical characteristics of the body surfaces around each landmark was used for the algorithms and implemented with C++. The accuracy of the AULID was tested on various torso shapes. The verification methodology consisted of mean difference (MD), mean absolute differences (MAD), and one‐way analysis of variance. Duncan test for multiple comparisons was used to evaluate the significant differences of MAD values among different torso groups. The MAD values were compared to the anthropometric survey allowable errors.

The algorithms of AULID provided both accuracy and consistency of identifying landmarks on any body torso types.

Most 3D body scanning systems often show landmark location errors when dealing with nonstandard body shapes. None of automatic landmark extraction software program provides consistency of identifying landmarks in various body shapes. However, algorithms of AULID, an automatic landmark extraction software program, in this study are only consistent definitions for identifying landmarks in any torso shape.

This work analyzes a pharmaceutical supply chain (PSC) in terms of supply chain visibility (SCV). The current good distribution practice (GDP) guideline demands increased visibility from firms. The purpose of this paper is to propose a solution for SCV enhancements based on automatic identification (Auto-ID) technologies.

The authors qualitatively analyze data from ten case studies of actors in a PSC. A review of Auto-ID technologies supports the derivation of solutions to enhance SCV.

This work shows that the functionalities of Auto-ID technologies offered by current practical monitoring solutions and challenges created by the GDP guideline necessitate further SCV enhancements. To enhance SCV, the authors propose three solutions: securPharm with passive radio frequency identification tags, transport containers with sensor nodes, and an SCV dashboard.

This study is limited to a PSC in Germany and is therefore not intended to be exhaustive. Thus, the results serve as a foundation for further analyses.

This study provides an overview of the functionality of Auto-ID technologies. In juxtaposition with the influence of the GDP guideline, the use of our Auto-ID-based solutions can help to enhance SCV.

This work analyzes a PSC in Germany, with consideration given to the influence of current legislation. Based on a multiple-case-study design, the authors derive three Auto-ID-based solutions for enhancing SCV.

Intelligent vehicle‐highway systems (IVHS) combine computing, sensors and telecom‐munications to deliver a more effective road/vehicle system for freight and passenger vehicles. Many of these technologies involve surveillance of the location and behaviour of identified vehicles and/or people, and the collation of such data for further use. These and other aspects of IVHS technologies raise concerns among the community, and have delayed the adoption of some systems. Outlines IVHS systems, and considers strategies for their introduction. The ownership and use of data collected in the course of IVHS operations is shown to present opportunities relating to revenue‐collection and law‐enforcement, on the one hand, and public acceptability problems, on the other. There are growing links with large‐scale data transmission facilities such as the US National Information Initiative (NII) and the equivalent massive interactive data networks developing elsewhere. Major errors in the implementation of early elements of IVHS may make it extremely difficult to deploy further elements. Argues that adoption of a number of principles could safeguard the potential benefits at an acceptable social cost.

The technology for optical identification and automatic sorting of products marked with fluorescent materials in trace concentrations is described. A small number of such materials in binary combinations allows marking of a large number of products. The concept has been applied to sort custom‐made domestic plastic products of different types in a fast‐moving mixed stream. The performance of the optical sensor, developed on the basis of identifying fluorescence signatures of some selected markers in these products, has been tested in an industrial singulation and sorting system. Commercially viable sorting rate and purity of “sort” have been demonstrated. The concept is applicable to other industry sectors.

This paper aims to outline the results of a study of the potential use of sensor technology such as radio frequency identification (RFID) and/or ZigBee technology in providing real-time tracking and tracing of patients and equipment in hospitals. The government of Saudi Arabia has given high priority to providing the best practice in patients’ care. However, the growing requirement of the healthcare industry to obtain real-time information and data from various applications that can improve the performance and accuracy of management systems has not been addressed seriously in Saudi Arabia.

ZigBee and RFID are both emerging technologies and have become important topics in recent years. RFID technology is a non-contact identification technology that does not require direct eyesight to the target object. It is cheap and reliable, but its coverage zone is limited. ZigBee is another communication technology, which has a larger coverage and can also be used as an automatic identification technology with the benefits of lower power consumption.

This paper proposes a smart hospital management system that can be used to detect, locate and monitor patients and track assets and equipment using modern sensor technologies in a real-time environment for e-health systems in Saudi Arabia.

A novel management information system/knowledge management system framework based on sensor technologies for supporting and speeding up development of healthcare systems.

The purpose of this paper is to evaluate the performance of table type radio frequency identification (RFID) reader and verify the effect of the use of a parasitic element on the table type RFID reader to increase the communication performance and improve the automatic identification of books in the library.

In this study, the authors observe the magnetic field at each point on the reader by using a small probe antenna and evaluate the reading performance of table type RFID reader at each point on the reader by using a RFID tag. Furthermore, to increase the communication performance, they add a parasitic element on the table type RFID reader and evaluate its usefulness.

The power distribution on the table type RFID reader and the communication performance of the table type REID reader were clearly shown. From the experiments of the magnetic field observation, when the coil surface of a tag is put in the parallel with the antenna plane of the reader, the tag can obtain electric power from the reader most effectively. Furthermore, by using a loop coil between the reader and the tag as a parasitic element, the points where communication is enabled with tag increased as the number of turns of coil increased.

In this research work, the author clearly showed the table type RFID reader’s performance by experiment. Moreover, to increase the communication performance, the author proposed to add a parasitic element to the table type RFID leader.

More sophisticated customer demand chains and electronic business pose new challenges to supply chain management. Delivery sizes decrease as a result of more deliveries directly to the point of use. Customers are demanding products and deliveries customised to their specific needs. Also, the information concerning small, customised deliveries has to be shared in volatile supply networks. This article analyses the opportunities of wireless product identification technology in transforming supply chain management. A new concept of item level supply chain management and enabling steps to achieve the benefits are proposed. Innovative companies already use wireless product identification with great benefits in specific functional areas, e.g. manufacturing and warehousing. However, the biggest potential is in supply chain wide solutions, i.e. item level supply chain management.