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The purpose of this paper is to provide the historical background of genealogical records and analyze the value of Chinese genealogical research through the study of names and genealogical resources.

The paper examines the historical evolution and value of Chinese genealogical records, with the focus on researching the Islamic Chinese names used by the people living in Guilin. The highlight of this paper includes the analysis and evolution of the Islamic Chinese names commonly adopted by the local people in Guilin. It concludes with the recommendations on emphasizing and making the best use of genealogical records to enhance the research value of Chinese overseas studies.

The paper covers the history of Islam and describes how the religion was introduced into China, as well as Muslims' ethnicity and identity. It also places focus on the importance of building a research collection in Asian history and Chinese genealogy.

This research study has a strong subject focus on Chinese genealogy, Asian history, and Islamic Chinese surnames. It is a narrow field that few researchers have delved into.

The results of this study will assist students, researchers, and the general public in tracing the origin of their surnames and developing their interest in the social and historical value of Chinese local history and genealogies.

The study of Chinese surnames is, by itself, a particular field for researching the social and political implications of contemporary Chinese society during the time the family members lived.

Very little research has been done in the area of Chinese local history and genealogy. The paper would be of value to researchers such as historians, sociologists, ethnologists and archaeologists, as well as students and anyone interested in researching a surname origin, its history and evolution.

Semantic Web is an extension of the World Wide Web by tagging content with “meaning”. In general, question answering systems based on semantic Web face a number of difficult issues. This paper aims to design an experimental environment with custom rules and scalable data sets and evaluate the performance of a proposed optimized backward chaining ontology reasoning system. This study also compares the experimental results with other ontology reasoning systems to show the performance and scalability of this ontology reasoning system.

The authors proposed a semantic question answering system. This system has been built using ontological knowledge base including optimized backward chaining ontology reasoning system and custom rules. With custom rules, the proposed semantic question answering system will be able to answer questions that contain qualitative descriptors such as “groundbreaking” resesarch and “tenurable at university x”. Scalability has been one of the difficult issues faced by an optimized backward chaining ontology reasoning system and semantic question answering system. To evaluate the proposed ontology reasoning system, first, the authors design a number of innovative custom rule sets and corresponding query sets. The innovative custom rule sets and query sets will contribute to the future research on evaluating ontology reasoning systems as well. Then they design an experimental environment including ontologies and scalable data sets and metrics. Furthermore, they evaluate the performance of the proposed optimized backward chaining reasoning system on supporting custom rules. The evaluation results have been compared with other ontology reasoning systems as well.

The proposed innovative custom rules and query sets can be effectively employed for evaluating ontology reasoning systems. The evaluation results show that the scalability of the proposed backward chaining ontology reasoning system is better than in-memory reasoning systems. The proposed semantic question answering system can be integrated in sematic Web applications to solve scalability issues. For light weight applications, such as mobile applications, in-memory reasoning systems will be a better choice.

This paper fulfils an identified need for a study on evaluating an ontology reasoning system on supporting custom rules with and without external storage.

Today’s in-demand skills may not be needed tomorrow. As companies are adopting a new group of technologies, they are in huge need of information technology (IT) professionals who can fill various IT positions with a mixture of technical and problem-solving skills. This study aims to adopt a sematic analysis approach to explore how the US Information Systems (IS) programs meet the challenges of emerging IT topics.

This study considers the application of a hybrid semantic analysis approach to the analysis of IS higher education programs in the USA. It proposes a semantic analysis framework and a semantic analysis algorithm to analyze and evaluate the context of the IS programs. To be more specific, the study uses digital transformation as a case study to examine the readiness of the IS programs in the USA to meet the challenges of digital transformation. First, this study developed a knowledge pool of 15 principles and 98 keywords from an extensive literature review on digital transformation. Second, this study collects 4,093 IS courses from 315 IS programs in the USA and 493,216 scientific publication records from the Web of Science Core Collection.

Using the knowledge pool and two collected data sets, the semantic analysis algorithm was implemented to compute a semantic similarity score (DxScore) between an IS course’s context and digital transformation. To present the credibility of the research results of this paper, the state ranking using the similarity scores and the state employment ranking were compared. The research results can be used by IS educators in the future in the process of updating the IS curricula. Regarding IT professionals in the industry, the results can provide insights into the training of their current/future employees.

This study explores the status of the IS programs in the USA by proposing a semantic analysis framework, using digital transformation as a case study to illustrate the application of the proposed semantic analysis framework, and developing a knowledge pool, a corpus and a course information collection.

The Internet of Things (IoT) has attracted a lot of attention in both industrial and academic fields for recent years. Artificial intelligence (AI) has developed rapidly in recent years as well. AI naturally combines with the Internet of Things in various ways, enabling big data applications, machine learning algorithms, deep learning, knowledge discovery, neural networks and other technologies. The purpose of this paper is to provide state of the art in AI powered IoT and study smart public services in China.

This paper reviewed the articles published on AI powered IoT from 2009 to 2018. Case study as a research method has been chosen.

The AI powered IoT has been found in the areas of smart cities, healthcare, intelligent manufacturing and so on. First, this study summarizes recent research on AI powered IoT systematically; and second, this study identifies key research topics related to the field and real-world applications.

This research is of importance and significance to both industrial and academic fields researchers who need to understand the current and future development of intelligence in IoT. To the best of authors’ knowledge, this is the first study to review the literature on AI powered IoT from 2009 to 2018. This is also the first literature review on AI powered IoT with a case study of smart public service in China.

When integrating smart elements offered by emergent technologies, libraries are facing the challenges of technological renovation and maintaining their operation using emerging technology. Given the importance of smart library, new technologies are needed in building new libraries or renovation of existing libraries. The purpose of this paper is to propose a risk warning system for library construction or renovation in the aspect of risk management.

The proposed Internet of Things (IoT)-based system consists of sensors that automatically monitor the status of materials, equipment and construction activities in real time. AI techniques including case-based reasoning and fuzzy sets are applied.

The proposed system can easily track material flow and visualize construction processes. The experiment shows that the proposed system can effectively detect, monitor and manage risks in construction projects including library construction.

Compared with existing risk warning systems, the proposed IoT-based system requires less data for making dynamic predictions. The proposed system can be applied to new builds and renovation of libraries.

The purpose of this paper is to propose a rational and complete design scheme of seam type of outdoor clothing, so as to improve the seam efficiency and appearance of outdoor clothing, as well as to provide an optimal seam base for the subsequent pressure adhesive process.

Four types of common outdoor fabrics and four seam types were selected. Seam strength and thickness were measured. Seam efficiency and seam thickness strain were calculated to evaluate seam quality. Multiple linear regression analysis was adopted to analyze the influence of seam type essential factors on seam strength.

Among the component factors of seam type, based on two stitches, seam strength was significantly affected by stitch distance, followed by fabric layer on the seam side. The increase of stitch and the interaction among fabrics can effectively improve the seam efficiency. The methods are as follows: the increase of stitches, stitch distance shortening, the increase of fabric layers, etc. The change of seam type had no significant influence on seam thickness strain. A seam-type design scheme of outdoor clothing with good mechanical and appearance properties was designed by choosing the seam types FX₁, FX₂ and FX₄.

This paper designed a practical scheme of seam-type design of outdoor clothing, which has been applied in the industrial production process. It is important for guiding the improvement of seam quality and the production efficiency of outdoor clothing.

The purpose of this paper is to reveal the unique thermal property of Mongolian clothing from the current western clothing and explain their environmental adaptation to the climate of Mongolian plateau in China.

Thermal insulation and the temperature rating (TR) of eight Mongolian robe ensembles and two western clothing ensembles were investigated by manikin testing and wearing trials, respectively. The clothing area factor (f_cl) of these Mongolian clothing was measured by photographic method and estimated equation from ISO 15831. Finally, the TR prediction model for Mongolian clothing was built and compared with current models for western clothing in ISO 7730 and for Tibetan clothing in previous article.

The results demonstrated that the total thermal insulation of Mongolian robe ensembles was much bigger than that of western clothing ensembles and ranged from 1.81clo to 3.11clo during the whole year. The f_cl of the Mongolian clothing should be determined by photographic method because the differences between these two methods were much bigger from 0.6 to 13.9 percent; the TR prediction model for Mongolian robe ensembles is TR=25.57−7.13Icl, which revealed that the environmental adaptation of Mongolian clothing was much better than that of western clothing and similar to that of Tibetan clothing.

The research findings give a detailed information about the thermal property of China Mongolian clothing, and explain the environmental adaptation of Mongolian clothing to the cold and changing climate.

Understanding costumer requirements is a precondition for clothing design and manufacturing. A good shapewear designer should know women’s preferences for their buttock shapes before making patterns. The purpose of this paper is to figure out factors affecting the beauty of women’s buttock shapes and the effect of ethnic background to buttock shapes preference.

The approach utilized both 3D virtual models and 3D printed models to detect women’s preference for their buttock shapes. As a first stage, a two-step K-means cluster method was used to classify female buttock shapes into ten groups and these ten kinds of buttock shapes were output as 3D virtual models and printed out as 3D plastic models. In a subsequent stage, 51 Caucasians, 35 African-Americans and 49 Asians were selected to rank the models separately based on their preference and choose the factors which they thought could influence the beauty of buttock shapes. Kendall’s W coefficient was tested to help assessing the ranking results. Finally, a sample girdle was designed based on the buttock shape preferences of Asian females as an example, and was tested by a model.

Results showed some correlation between ethnicity and buttock shape preference. Both methods of presentation of the shapes were equally preferred by participants. Caucasian women preferred a full, round buttock shape, which was coordinated to other parts of the body. The attractive buttock shape as judged by Asian women was curvy, not drooping and not too big. African-American women choose buttock shapes that were very full with high buttock bumps as beautiful. A sample girdle was made based on the preferences of Asian females and it proved to perform well in creating the desired shape during the trial test.

Current research in the literature about women’s buttock beauty is based on plastic surgeons’ experiences. This study provides a novel method to analyze female’s preference for their buttock shapes; a method that can also be used for other body parts. The results can also be used as an indicator for underwear designers to improve shapewear pattern designs and for consumers to evaluate the shaping ability of shapewear.

The purpose of this paper is to investigate the influence of key parameters on the bond strength and failure modes of laminated structures made of different aluminum alloys (i.e. Al 2024 and Al 7075) via the ultrasonic consolidation (UC) process.

The UC is used to fabricate laminated structures with various parameters. The push-pin tests were performed on the specimens of different materials and parameters, and the force and displacement were recorded during the tests. The peak punch force was used to represent the bond quality of the laminated structure, and the curves of force versus displacement were used to study the failure modes of the structures.

It is found that the lower normal force, the larger vibration amplitude and the lower travel speed can result in stronger bonding. Three different failure modes are observed in the tests, due to the different relations between the toughness of interface and raw materials. The process parameters have influence on the interface toughness of a laminated structure, which further leads to different failure modes.

The overall mechanical properties of a laminated structure highly depend on the bond quality between laminated layers. The push-pin test can easily and effectively evaluate the bond quality of the laminated structure. This paper not only focuses on the bond strength evaluation, but also analyzes the different failure modes of laminated structures made of different aluminum alloys, which can give an opportunity to optimize the parameters for different materials.