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To make the single‐antenna attitude method more useful as a back‐up or fault diagnostic system than was targeted originally.

The enhancement incorporates information from the GPS satellite constellation and aircraft dynamic model. The visibility of GPS satellites affects the accuracy of the aircraft's volocity that is the main source of single‐antenna attitude. In addition, to use the aircraft dynamic model is natural because single‐antenna attitude is for exclusive use of aircraft. These are considered and implemented as a covariance matrix or process model of Kalman filters. The enhanced performances are verified by an aircraft nonlinear simulation.

The proposed method estimates more accurate volocity and unpiased single‐antenna attitude by using satellite constellation information and the aircraft dynamics. Moreover, the implemented system has a structure that combines other navigation sensors easily.

It would be more desirable to perform further researches; sensor integration, stability against wind disturbance, and aircraft model uncertainty, etc.

A useful attitude sensor for a back‐up attitude system at low cost on manned aircraft or a main attitude system on unmanned aircraft that are sensitive to the mass or size of payload.

This paper has been the first to promote the potential of single‐antenna attitude and with only information that can be easily obtained.

The purpose of this paper is to provide an overview of podcasting and webcasting, and to examine student preferences between the different delivery richness of communication media.

Background information regarding podcasting and webcasting is discussed. A conceptual model, based on media richness theory, is developed to explain student's perceptions. For the testing of the model, a survey metric is introduced, and a research methodology is explained. Finally, a conclusion and research limitations are discussed.

The conceptual model of the motivations to use podcasting was adopted from media richness theory. It was proposed that six factors are related to future media use; immediacy of feedback, personal focus, transmission of cues, functionality, usability, and ease of use. The methodology relied heavily on logistic regression analysis for testing the various hypotheses. The authors collected data for hypothesis testing. The results of the study were inconclusive. This may be due to the lack of user experience with podcasting.

Some instructors have even adopted such techniques as their primary means (within the classroom or outside classroom) of communicating to students. However, the selection of appropriate communication media requires an understanding of the students' perceptions, preferences and receptiveness of these new technologies.

The findings from this exploratory research will be valuable for podcasting users.

This study is the first kind of empirical research in this area. With this study, the authors examined the perceived value of podcasting.

The purpose of this paper is to examine the status of current mobile TV phone usage and discuss the issues for strategic implications for the communications and mobile TV industry.

Real tracking data, collected from server's logs during 2006 and 2007 from South Korean satellite DMB providers, were analyzed according to users' age group, peak viewing time of programs, location usage and program duration. Further analysis with the previous literature led to inferences about strategic implications.

The analysis revealed the current mobile TV usage patterns: widespread user age group, peak viewing time, high indoor usage and longer viewing time. These results shaped strategic implications, furthering and enhancing a personalized media experience.

The data set, collected from the subscription‐based satellite DMB usage in South Korea, is well recognized as being a technological frontier. Further cultural comparison research work on mobile TV usage is required to validate the strategic implications for a wider cross cultural adoption.

This research benefits the strategic planning of the mobile communications and entertainment content industries in decision‐making regarding the improvement of hands‐on experience for mobile TV users.

The findings, based on the mobile TV real tracking data, collected in South Korea for over two years contrast to that of other countries, which only begin to experience the roll‐out of a full commercial service. Consequently, the data presented here highlights an important role in understanding and shaping of the mobile TV phone market for other parts of the world.

To investigate relationships between teamwork, trust and teacher team commitment.

Research has confirmed the value‐added effects of organizational commitment in terms of job performance, organizational effectiveness, and employee retention. This study focused on teacher teams as the unit of analysis, and posited associations between teamwork, viewed as team skills, trust and teacher team commitment. Data were derived from responses of elementary school teachers to an instrument including established measures of teamwork component skills, affective‐ and cognition‐based trust, and team commitment.

Teamwork was found to be a significant predictor of teacher team commitment. Respondents showing higher levels of teamwork skills perceived higher levels of team commitment. Results, while not entirely confirmatory, suggested the importance of trust in the commitment equation.

This research was limited by the study sample of elementary schools. Future research should test initially confirmed associations in different school contexts with substantially dissimilar teacher demographics, and include consideration of dispositional antecedents that may impact teacher perceptions.

School leaders concerned with teacher commitment and related implications for teacher retention should consider strategies to strengthen performance‐enhancing teamwork and support satisfying teaming processes.

This study provides an initial understanding of teacher teamwork and affects on commitment in the context of teams viewed as building blocks of organization in locally‐managed schools.

The purpose of this paper is to make an overview of 474 publications and 512 patents of FTL from 1987 to 2020 in order to provide a conclusive and comprehensive analysis for researchers in this field, as well as a preliminary knowledge of FTL for interested researchers.

Firstly, the FTL algorithms are classified and its functions are introduced in detail. Secondly, the structures of the publications are analyzed in terms of the fundamental information and the publication of the most productive countries/regions, institutions and authors. After that, co-citation networks of institutions, authors and papers illustrated by VOS Viewer are given to show the relationship among those and the most influential of them is further analyzed. Then, the characteristics of the patent are analyzed based on the basic information and classification of the patent and the most productive inventors. In order to obtain research hotspots and trends in this field, the time-line review and citation burst detection of keywords carried out by Cite Space are made to be visual. Finally, based on the above analysis, it draws some other important conclusions and the development trend of this field.

The research on FTL algorithm is still the top priority in the future, and how to improve the performance of SSD in the era of big data is one of the research hotspots.

This paper makes a comprehensive analysis of FTL with the method of bibliometrics, and it is valuable for researchers can quickly grasp the hotspots in this area.

This article draws the structural characteristics of the publications in this field and summarizes the research hotspots and trends in this field in recent years, aiming to inspire new ideas for researchers.

The purpose of this paper is to develop a similarity evaluation method between virtual and actual clothing.

The paper analyzes the subjective and objective evaluation results of virtual and actual clothing.

In this paper, significant factors affecting the evaluation of similarity between actual and virtual clothing have been found.

Evaluation experiment was performed only for a skirt. However, the method can be easily applied for other types of garments.

The evaluation of similarity between actual and virtual garment will be facilitated.

The garment design process can be facilitated by simulating garments in virtual space.

There has not been any quantitative evaluation method for the similarity of virtual and actual garment.

The purpose of this study is to solve the cold start problem caused by the lack of evaluation information about the products.

A recommendation system has been developed by using the image data of the clothing products, assuming that the user considers the visual characteristics importantly when purchasing fashion products. In order to evaluate the performance of the model developed in this study, it was compared with Random, Itempop, Matrix Factorization and Generalized Matrix Factorization models.

The newly developed model was able to cope with the cold start problem better than other models.

A hybrid recommendation system has been developed that combines the existing recommendation system with deep learning to effectively recommend fashion products considering the user's taste.

This is the first research to improve the performance of fashion recommendation system using the deep learning model trained by the images of fashion products.

The purpose of this paper is to illustrate the generation of basic garment pattern using three‐dimensional body measurement data.

A pre‐defined garment model is deformed using free‐form deformation method and the model is flattened to generate flat patterns.

The paper finds that individual basic garment patterns are automatically generated and verified to be well fit on human subjects.

The current approach is to focus on the generation of basic bodice patterns; however, other patterns can also be generated by this method by preparing more garment models.

This method can reduce the time required to design basic patterns as well as enhance their fitness.

The automatic generation of individually fitted garment pattern is one of the most important steps in future garment production process.

The generation of individually fit basic garment pattern is one of the most important steps in the garment‐manufacturing process. This paper seeks to present a new methodology to generate basic patterns of various sizes and styles using three‐dimensional geometric modeling method.

The geometry of a garment is divided into fit zone and fashion zone. The geometry of fit zone is prepared from 3D body scan data and can be resized parametrically. The fashion zone is modeled using various parameters characterizing the aesthetic appearance of garments. Finally, the 3D garment model is projected into corresponding flat panels considering the physical properties of the base material as well as the producibility of the garment.

The main findings were geometric modeling and flat pattern generation method for various garments.

Parametrically deformable garment models enable the design of garments with various size and silhouette so that designers can obtain flat patterns of complex garments before actually making them. Also the number and direction of darts can be determined automatically considering the physical property of fabric.