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Traditional multivariable grey prediction models define the background-value coefficients of the dependent and independent variables uniformly, ignoring the differences between their physical properties, which in turn affects the stability and reliability of the model performance.

A novel multivariable grey prediction model is constructed with different background-value coefficients of the dependent and independent variables, and a one-to-one correspondence between the variables and the background-value coefficients to improve the smoothing effect of the background-value coefficients on the sequences. Furthermore, the fractional order accumulating operator is introduced to the new model weaken the randomness of the raw sequence. The particle swarm optimization (PSO) algorithm is used to optimize the background-value coefficients and the order of the model to improve model performance.

The new model structure has good variability and compatibility, which can achieve compatibility with current mainstream grey prediction models. The performance of the new model is compared and analyzed with three typical cases, and the results show that the new model outperforms the other two similar grey prediction models.

This study has positive implications for enriching the method system of multivariable grey prediction model.

The cotton fabrics were surface modified for water repellent finishing with silicon sol, which was prepared with the tetraethoxysilane(TEOS) and solvent ethanol, catalyzer HCl, water and modified with additives, such as Methyltriethoxysilane(MTEOS), Octyltriethoxysilane(OTEOS) and Hexadec-ltrimethoxysilane(HTEOS). As a result, acceptable water repellence could only be achieved via the addition of longer chain length additives such as OTEOS, HTEOS, while the use of additives containing a shorter alkyl chain length such as MTES led to insufficient water repellence. The factors which influence contact angles were examined. Excellent water repellent properties could be achieved on the cotton fabrics treated with the silica sols by twice dip and pad and cured at 160°. The silica sol preparation preference conditions were with TEOS: H₂O: EtOH=1: 5: 8 (mol) by stirring for 6 hours at 65°C which was added with HTEOS. The water repellence contact angle was able to be reached around 140° and the hydrostatic pressure was 46cm.

The motion vector estimation algorithm is very widely used in many image process applications, such as the image stabilization and object tracking algorithms. The conventional searching algorithm, based on the block matching manipulation, is used to estimate the motion vectors in conventional image processing algorithms. During the block matching manipulation, the violent motion will result in greater amount of computation. However, too large amount of calculation will reduce the effectiveness of the motion vector estimation algorithm. This paper aims to present a novel searching method to estimate the motion vectors effectively.

This paper presents a novel searching method to estimate the motion vectors for high-resolution image sequences. The searching strategy of this algorithm includes three steps: the larger area searching, the adaptive directional searching and the small area searching.

The achievement of this paper is to develop a motion vector searching strategy to improve the computation efficiency. Compared with the conventional motion vector searching algorithms, the novel motion vector searching algorithm can reduce the motion matching manipulation effectively by 50 per cent.

This paper presents a novel searching strategy to estimate the motion vectors effectively. From the experimental results, the novel motion vector searching algorithm can reduce the motion matching manipulation effectively, compared with the conventional motion vector searching algorithms.

Surface roughness has a serious impact on the fatigue strength, wear resistance and life of mechanical products. Realizing the evolution of surface quality through theoretical modeling takes a lot of effort. To predict the surface roughness of milling processing, this paper aims to construct a neural network based on deep learning and data augmentation.

This study proposes a method consisting of three steps. Firstly, the machine tool multisource data acquisition platform is established, which combines sensor monitoring with machine tool communication to collect processing signals. Secondly, the feature parameters are extracted to reduce the interference and improve the model generalization ability. Thirdly, for different expectations, the parameters of the deep belief network (DBN) model are optimized by the tent-SSA algorithm to achieve more accurate roughness classification and regression prediction.

The adaptive synthetic sampling (ADASYN) algorithm can improve the classification prediction accuracy of DBN from 80.67% to 94.23%. After the DBN parameters were optimized by Tent-SSA, the roughness prediction accuracy was significantly improved. For the classification model, the prediction accuracy is improved by 5.77% based on ADASYN optimization. For regression models, different objective functions can be set according to production requirements, such as root-mean-square error (RMSE) or MaxAE, and the error is reduced by more than 40% compared to the original model.

A roughness prediction model based on multiple monitoring signals is proposed, which reduces the dependence on the acquisition of environmental variables and enhances the model's applicability. Furthermore, with the ADASYN algorithm, the Tent-SSA intelligent optimization algorithm is introduced to optimize the hyperparameters of the DBN model and improve the optimization performance.

The purpose of this study is to investigate the effects of load and rotation speed on dry sliding of silicon nitride, including a series of tribological behaviors (friction coefficient, wear rate, temperature rise, etc.) and wear mechanism. Through the analysis of the above characteristics, the influence law of load and speed on them and the internal relationship between them are determined, and then the best comprehensive performance parameters of silicon nitride full-ceramic spherical plain bearings in dry sliding are predicted, which can provide guidance for the operation condition of silicon nitride full-ceramic spherical plain bearings in dry sliding.

The experimental study of different loads and rotation speeds under dry friction conditions was carried out by the using ball-disk sliding test method.

With the increase of load, the friction coefficient of silicon nitride friction pair and the wear rate of silicon nitride ball decrease continuously. With the increase of rotation speed, the friction coefficient of silicon nitride friction pair first increases and then decreases, and the wear of silicon nitride ball first increases and then decreases. With the increase of load and rotation speed, the wear mechanism eventually changes to adhesive wear.

Because of the low timeliness and inefficiency of bearing experiments, this work adopts a simple ball-disk model to comprehensively explore the influence rules of different conditions, which provides a theoretical basis for the subsequent practical application of silicon nitride full-ceramic spherical plain bearings.

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.

This paper seeks to discuss the genealogical sources for Chinese immigrants as well as the settlement of Chinese in the USA and the historical evolution of Chinese names, their origins, arrangement and development. It aims to cover the origins of various classes of Chinese surnames, followed by the content description of a traditional genealogical book for jiapu.

The paper researches the various ways that a Chinese person can find out about their ancestry.

The paper reveals the roles of libraries, including serving the needs of patrons interested in genealogical research, preserving and interpreting information through oral and family history projects and collaborating with other libraries through interlibrary loan, document delivery, library consortia, collection management and international resource‐sharing.

The study provides information on where and how to locate the genealogical resources for researching the genealogy of a Chinese family.

The paper analyzes the value of genealogical research as a documentary source for population history, life expectancy in a clan, marriages and family connections, as well as lineage organizations and inter‐lineage relations.

This paper aims to reveal the interdisciplinarity of information science (IS) from the perspective of the evolution of theory application.

Select eight representative IS journals as data sources, extract the theories mentioned in the full texts of the research papers and then measure annual interdisciplinarity of IS by conducting theory co-occurrence network analysis, diversity measure and evolution analysis.

As a young and vibrant discipline, IS has been continuously absorbing and internalizing external theoretical knowledge and thus formed a high degree of interdisciplinarity. With the continuous application of some kernel theories, the interdisciplinarity of IS appears to be decreasing and gradually converging into a few neighboring disciplines. Influenced by big data and artificial intelligence, the research paradigm of IS is shifting from a theory centered one to a technology centered one.

This study helps to understand the evolution of the interdisciplinarity of IS in the past 21 years. The main limitation is that the data were collected from eight journals indexed by the Social Sciences Citation Index and a small amount of theories might have been omitted.

This study identifies the kernel theories in IS research, measures the interdisciplinarity of IS based on the evolution of the co-occurrence network of theory source disciplines and reveals the paradigm shift being happening in IS.

The purpose of this paper is agile attitude control design with the novel three-dimensional (3D) magnetically suspended wheel (MSW) that is the preferred type for agile maneuvering compared to conventional control moment gyro due to frictionless, low vibration and long lifetime. This system does not require a separate steering law for pyramid arrangement to derive tilt angles. It is also conducting an agile maneuver with high accuracy despite the high-frequency disturbances.

In this paper, a disturbance observer-based attitude stabilization method is proposed for an agile satellite with a pyramid cluster of the novel 3D magnetically suspended wheel actuator. This strategy includes a disturbance observer and a linear quadratic regulator controller. The rotor shaft deflection of MSW is actively controlled to reduce vibration and producing gyro torque. The deflection angle of the pyramid cluster MSWs considered as control parameters. The closed-loop stability is proved by using the Lyapunov strategy. The efficiency and performance of the offered method verified by numerical simulation via MATLAB/SIMULINK software.

According to simulation results, the disturbance observer-based control controller stabilized the system with high accuracy and optimal tilt angles without any extra steering law equation. Hence, the system speed is increased, and the system error is minimized without separate steering law.

The magnetically suspended wheel is a new kind of inertia actuator for attitude control that has several benefits such as frictionless, high-speed rotor, clean environment and low vibration compared to the traditional wheel. It has complex nonlinear dynamics that cause have complicated controller design. The proposed strategy stabilizes the system and conducting an agile maneuver with high precision despite the high-frequency disturbances. It is applicable for some missions requiring high accuracies, like Earth observation and the solar observation mission that require a very accurate pointing control and a long lifetime.

This paper is the initial paper to design a pyramid array for magnetically suspended wheels. Compared to other research, this method doesn’t need a separate steering law of the MSWs cluster and presented optimal tilt angles with less computational. Also, it designs a disturbance observer-based controller for this system that proposed high accuracy and agile stabilization.

The purpose of this study is to restore the spatial distribution of overseas remittance businesses in Shantou during the 1940s. It explores various socioeconomic factors that influenced the concentration of local remittance business investment in real estate. By reconstructing the spatial distribution of remittance business activities in Shantou, this study hopes to lay a foundation for further analysis of the business strategies of Chaoshan merchants.

This research draws on information from the published Swatow Guide, archival sources and cadastral maps to identify the location of remittance enterprises and the native place and overseas networks of property owners.

This study reveals that the spatial distribution of the remittance enterprises was determined by the native place origins of local property owners, and that the inflow of overseas Chinese capital contributed to real estate development in Shantou.

Despite the limited access to Chinese official archives, this paper manages to identify several building blocks and neighbors in Shantou for spatial analysis.

This study is the first attempt to use the geographical information system (GIS) method in Chinese urban history research and hopes to establish a larger historical database of Shantou as a sample for comparison.

This investigation advances the spatial study of urban history and overseas Chinese remittances in the maritime society of South China.