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Online encyclopedia has facilitated users to easily access interesting knowledge and find solutions for daily problems. However, for the staff in specific domains, especially in secret-related domains, a domain-micropedia is still necessary for work.

In this paper, the authors propose an approach to extract entities from DBpedia and construct the SDPedia in space debris mitigation domain. First, the authors select the root categories about space debris mitigation domain by manual methods. Subsequently, the authors propose Distance of Electrical Resistance, Pages Common Words and AVDP algorithms to implement the extraction. The authors also achieve the data visualization by generating swf files and embedding them into web pages.

In the experiments, the precision, recall and F1-measure are used to evaluate the proposed algorithms. The authors set a series of thresholds to pursue the highest F1-measure. The experimental data indicate that the AVDP algorithm gets the highest F1-measure and is statistically effective for the entities extraction from DBpedia.

The authors propose an approach of deriving linked data from DBpedia and construct their own SDPedia, which has been applied in the space debris mitigation domain currently. Compared with DBpedia, the authors also add the linked data visualization. Moreover, the methodology can be used in many other domains in the future.

The paper aims to explore the effect of problem-based learning (PBL) embedding degree and education level on individual perception, as well as the moderating effect of nationality.

The paper first conceptualizes PBL embedding degree which means the extent of applying PBL. It takes an empirical study on an international MBA class in one of the first-class universities in China. An investigation is taken with the designed “PBL-based Cognitive Perception Scale” and an Ordered Probit Model is constructed.

The findings of this study are as follows: PBL embedding degree has a significant effect on the cognitive perception of student, which varies in different dimensions; the educational level of international student positively affects the cognitive perception toward PBL; and nationality may moderate the relationship between the PBL embedding degree and individual perception.

The paper replenishes the investigation and application of Bloom’s Taxonomy of Learning. By conceptualizing PBL embedding degree, the paper extends the research perspectives of PBL and proposes a subjective method on the evaluation of PBL. The paper also may provide a guidance for PBL curriculum design with sustainable development of education.

The integration and retrieval of the vast data have attracted sufficient attention, thus the W3C workgroup releases R2RML to standardize the transformation from relational data to semantic-aware data. However, it only provides a data transform mechanism to resource description framework (RDF). The generation of mapping alignments still needs manual work or other algorithms. Therefore, the purpose of this paper is to propose a domain-oriented automatic mapping method and an application of the R2RML standard.

In this paper, materials science is focussed to show an example of domain-oriented mapping. source field concept and M3B2 (Metal Materials Mapping Background Base) knowledge bases are established to support the auto-recommending algorithm. As for the generation of RDF files, the idea is to generate the triples and the links, respectively. The links of the triples follow the object-subject relationship, and the links of the object properties can be achieved by the range individuals and the trail path.

Consequently based on the previous work, the authors proposed Engine for Metal Materials Mapping Background Base (EM3B2), a semantic integration engine for materials science. EM3B2 not only offers friendly graphical interfaces, but also provides auto-recommending mapping based on materials knowledge to enable users to avoid vast manually work. The experimental result indicates that EM3B2 supplies accurate mapping. Moreover, the running time of E3MB2 is also competitive as classical methods.

This paper proposed EM3B2 semantic integration engine, which contributes to the relational database-to-RDF mapping by the application of W3C R2RML standard and the domain-oriented mapping.

To implement a risk-based regulatory approach, this paper aims to make an assessment on customers' money laundering risk and conducts some applications.

During the transition of a regulatory approach from “rule-based” to “risk-based”, this paper considers that the area of a customer, types of business and the industries to which the customer belongs are the main indicators to judge money laundering risk of a customer. Based on the statistical analysis of 221 typical money laundering cases, first-class index weights are given by using the entropy weight method and then by combining with the membership function, this paper determines a customer’s money laundering risk levels. On the basis of the entropy weight method, this paper uses the C5.0 algorithm to construct a decision tree model and then carries out application research on customer money laundering risk assessment to verify the effectiveness of the entropy weight method and the decision tree model.

This empirical research found the weights of three key money laundering indicators: customer areas, business types and corresponding industries.

Asserting that current money laundering risk assessments of customers are marginal at best, this paper contends from the perspective of practice, and applies the entropy weight method and the decision tree model for money laundering risk assessment of customers.

The purpose of this paper is to propose an optimization method by combining artificial immune algorithm and finite element analysis to find the optimal exciting electrode of a piezoceramic plate type ultrasonic motor vibrator.

The artificial immune algorithm is selected as optimizer for its merit of fast convergence to global optimal solution. The finite element analysis is used to calculate the motion trajectory of contact point. The objective function is the work that the vibrator does to rotor. The design variables are the boundaries of exciting electrode on piezoceramic plate vibrator surface.

The calculated results and the experimental results show that using this method, both the position and the size of optimal exciting electrode of this ultrasonic motor can be quickly and accurately determined.

In order to successfully design an ultrasonic motor, both the position and the size of the exciting electrode must be investigated, so as to change more electric energy into mechanical energy. In this paper, an optimization method by combining artificial immune algorithm and finite element analysis is proposed for the exciting location optimization of a piezoceramic plate type ultrasonic motor to obtain large power output.

The purpose of this study is to build a consensus model of social network group decision-making (SNGDM) based on improved PageRank algorithm. By objectively and fairly measuring the evaluation ability of participants in the decision-making process, the authors can improve the fairness and authenticity of the weight solution of decision-makers (DM) in the decision-making process. This ensures the reliability of the final group consensus results.

This study mainly includes six parts: preference expression, calculation of DM's weight, preference aggregation, consensus measurement, opinion adjustment and alternative selection. First, Pythagorean fuzzy expression is introduced to express the preference of DMs, which expands the scope of preference expression of DMs. Second, based on the social network structure among DMs, the process of “mutual judgment” among DMs is increased to measure the evaluation ability of DMs. On this basis, the PageRank algorithm is improved to calculate the weight of DMs. This makes the process of reaching consensus more objective and fair. Third, in order to minimize the evaluation difference between groups and individuals, a preference aggregation model based on plant growth simulation algorithm (PGSA) is proposed to aggregate group preferences. Fourth, the consensus index of DMs is calculated from three levels to judge whether the consensus degree reaches the preset value. Fifth, considering the interaction of DMs in the social network, the evaluation value to achieve the required consensus degree is adjusted according to the DeGroot model to obtain the overall consensus. Finally, taking the group preference as the reference, the ranking of alternatives is determined by using the Pythagorean fuzzy score function.

This paper proposes a consensus model of SNGDM based on improved PageRank algorithm to aggregate expert preference information. A numerical case of product evaluation is introduced, and the feasibility and effectiveness of the model are explained through sensitivity analysis and comparative analysis. The results show that this method can solve the problem of reaching consensus in SNGDM.

Different DMs may have different judgment criteria for the same decision-making problem, and the angle and depth of considering the problem will also be different. By increasing the process of mutual evaluation of DMs, the evaluation ability of each DM is judged only from the decision-making problem itself. In this way, the evaluation opinions recognized by most DMs will form the mainstream of opinions, and the influence of corresponding DMs will increase. Therefore, in order to improve the fairness and reliability of the consensus process, this study measures the real evaluation ability of DMs by increasing the “mutual judgment” process. On this basis, the defect of equal treatment of PageRank algorithm in calculating the weight of DMs is improved. This ensures the authenticity and objectivity of the weight of DMs. That is to improve the effectiveness of the whole evaluation mechanism. This method considers both the influence of DMs in the social network and their own evaluation level. The weight of DMs is calculated from two aspects: sociality and professionalism. It provides a new method and perspective for the calculation of DM’s weight in SNGDM.

How to model blind image deblurring that arises when a camera undergoes ego-motion while observing a static and close scene. In particular, this paper aims to detail how the blurry image can be restored under a sequence of the linear model of the point spread function (PSF) that are derived from the 6-degree of freedom (DOF) camera’s accurate path during the long exposure time.

There are two existing techniques, namely, an estimation of the PSF and a blind image deconvolution. Based on online and short-period inertial measurement unit (IMU) self-calibration, this motion path has discretized a sequence of the uniform speed of 3-DOF rectilinear motion, which unites with a 3-DOF rotational motion to form a discrete 6-DOF camera’s path. These PSFs are evaluated through the discrete path, then combine with a blurry image to restoration through deconvolution.

This paper describes to build a hardware attachment, which is composed of a consumer camera, an inexpensive IMU and a 3-DOF motion mechanism to the best of the knowledge, together with experimental results demonstrating its overall effectiveness.

First, the paper proposes that a high-precision 6-DOF motion platform periodically adjusts the speed of a three-axis rotational motion and a three-axis rectilinear motion in a short time to compensate the bias of the gyroscope and the accelerometer. Second, this paper establishes a model of 6-DOF motion and emphasizes on rotational motion, translational motion and scene depth motion. Third, this paper addresses a novel model of the discrete path that the motion during long exposure time is discretized at a uniform speed, then to estimate a sequence of PSFs.

This paper aims to develop a novel trajectory optimization algorithm which is capable of producing high accuracy optimal solution with superior computational efficiency for the hypersonic entry problem.

A two-stage trajectory optimization framework is constructed by combining a convex-optimization-based algorithm and the pseudospectral-nonlinear programming (NLP) method. With a warm-start strategy, the initial-guess-sensitive issue of the general NLP method is significantly alleviated, and an accurate optimal solution can be obtained rapidly. Specifically, a successive convexification algorithm is developed, and it serves as an initial trajectory generator in the first stage. This algorithm is initial-guess-insensitive and efficient. However, approximation error would be brought by the convexification procedure as the hypersonic entry problem is highly nonlinear. Then, the classic pseudospectral-NLP solver is adopted in the second stage to obtain an accurate solution. Provided with high-quality initial guesses, the NLP solver would converge efficiently.

Numerical experiments show that the overall computation time of the two-stage algorithm is much less than that of the single pseudospectral-NLP algorithm; meanwhile, the solution accuracy is satisfactory.

Due to its high computational efficiency and solution accuracy, the algorithm developed in this paper provides an option for rapid trajectory designing, and it has the potential to evolve into an online algorithm.

The paper provides a novel strategy for rapid hypersonic entry trajectory optimization applications.

Mumbai needs to be transformed into a world-class city as stated in the 2005–2025 development plan of Municipal Corporation. For this initiative, hospital management information system (HMIS) has to be implemented across 400+ health facilities in the city.

A case study methodology was adopted to study HMIS implementation. Wave 1 of Phase 1 implementation of HMIS is carried out as a pilot project at Film City’s Hospital, Mumbai, which “go-live” on 21st June 2018. The work for hardware and software implementation was awarded to HardSystems and Solutions Limited and SoftSolutions India Private Limited, respectively, through e-tender.

Provision of inadequate quantity of hardware, slowness of network or system, non-satisfactory training after observation confirmation and sign-off process, lack of data entry operators, mismatch in numbering systems in blood bank and many other challenges concerned with the specific departments had become a major impediment in the efforts to maximize number of patients registered into HMIS.

Even after providing many clinical and managerial benefits, being the first cloud-based centrally located HMIS in any of the hospitals in the city, it imposes a major challenge for the management in terms of resistance of employees toward technology and need for the adoption of theoretical models for implementing change for the overall organizational development.

To the best of the authors’ knowledge, no other teaching case study is conducted to study the HMIS implementation in large-scale public health-care services. This is a dummy case study for teaching exercises. The identity of the stakeholders, organizations and events has been masked to maintain confidentiality.

The present study aims to investigate the inverse-thermocapillary effect in an evaporating thin liquid film of self-rewetting fluid, which is a dilute aqueous solution (DAS) of long-chain alcohol.

A long-wave evolution model modified for self-rewetting fluids is used to study the inverse thermocapillary characteristics of an evaporating thin liquid film. The flow attributed to the inverse thermocapillary action is manifested through the streamline plots and the evaporative heat transfer characteristics are quantified and analyzed.

The thermocapillary flow induced by the negative surface tension gradient drives the liquid from a low-surface-tension (high temperature) region to a high-surface-tension (low temperature) region, retarding the liquid circulation and the evaporation strength. The positive surface tension gradients of self-rewetting fluids induce inverse-thermocapillary flow. The results of different working fluids, namely, water, heptanol and DAS of heptanol, are examined and compared. The thermocapillary characteristic of a working fluid is significantly affected by the sign of the surface tension gradient and the inverse effect is profound at a high excess temperature. The inverse thermocapillary effect significantly enhances evaporation rates.

The current investigation on the inverse thermocapillary effect in a self-rewetting evaporating thin film liquid has not been attempted previously. This study provides insights on the hydrodynamic and thermal characteristics of thermocapillary evaporation of self-rewetting liquid, which give rise to significant thermal enhancement of the microscale phase-change heat transfer devices.