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The artificial bee colony (ABC) algorithm shows a relatively powerful exploration search capability but is constrained by the curse of dimensionality, especially on nonseparable functions, where its convergence speed slows dramatically. In this article, based on an analysis of the difference between updating mechanisms that include both all-variable and one-variable updating mechanisms, we find that when equipped with the former strategy, the algorithm rapidly converges to an optimal region, while with the latter strategy, it searches the solution space thoroughly. To utilize multivariable and one-variable updating mechanisms on nonseparable and separable functions, respectively, we embed an improved linkage identification strategy into the ABC by detecting the linkage between variables more effectively. Then, we propose three common strategies for ABC to improve its performance. First, a new approach that considers the historic experiences of the population is proposed to balance exploration and exploitation. Second, a new strategy for initializing scout bees is used to reduce the number of function evaluations. Finally, the individual with the worst performance is updated with a defined probability on multiple dimensions instead of one dimension, causing it to follow the population steps on nonseparable functions. This article is the first to propose all these concepts, which could be adopted for other ABC variants. The effectiveness of our algorithm is validated through basic, CEC2010, CEC2013, and CEC2014 functions and real-world problems.

Recently designed passenger vehicles with heightened features are entering the market every year. One of them is the power window which enables the fast movement of window-panes. Not opening of window-pane in an emergency is responsible for the death of passengers in some cases. Deaths of children, the disabled or older person have been reported due to carbon monoxide(CO) poisoning. Simultaneously, they were allowed to stay inside a static, locked car in the absence of other assisting occupants. Fatal injuries have also been reported repeatedly due to the sinking of the vehicle in a water body. In this paper, the design of an automatic opening mechanism is discussed for a car window during such crises. In this system, the temperature sensor, Carbon-monoxide sensor and water pressure sensor are placed inside a car cabin to monitor the temperature range, CO levels and water pressure continuously. In case of high internal temperatures or raised carbon monoxide in the cabin due to incomplete fuel combustion or excessive heat or vehicle rested under the Sun for long, or if the vehicle is subjected to pressure by flowing or static water, the sensors send signals to the motor controlling power window to slide it down. It also sends a warning message to the registered mobile phone of the vehicle owner.

Data Envelopment Analysis (DEA) is a linear programming methodology for measuring the efficiency of Decision Making Units (DMUs) to improve organizational performance in the private and public sectors. However, if a new DMU needs to be known its efficiency score, the DEA analysis would have to be re-conducted, especially nowadays, datasets from many fields have been growing rapidly in the real world, which will need a huge amount of computation. Following the previous studies, this paper aims to establish a linkage between the DEA method and machine learning (ML) algorithms, and proposes an alternative way that combines DEA with ML (ML-DEA) algorithms to measure and predict the DEA efficiency of DMUs. Four ML-DEA algorithms are discussed, namely DEA-CCR model combined with back-propagation neural network (BPNN-DEA), with genetic algorithm (GA) integrated with back-propagation neural network (GANN-DEA), with support vector machines (SVM-DEA), and with improved support vector machines (ISVM-DEA), respectively. To illustrate the applicability of above models, the performance of Chinese manufacturing listed companies in 2016 is measured, predicted and compared with the DEA efficiency scores obtained by the DEA-CCR model. The empirical results show that the average accuracy of the predicted efficiency of DMUs is about 94%, and the comprehensive performance order of four ML-DEA algorithms ranked from good to poor is GANN-DEA, BPNN-DEA, ISVM-DEA, and SVM-DEA.

Metamodels are simpler computer models that are designed to mimic the input-output behavior of discrete-event or other complex simulation models. They are models of models, thus the name (provided by Jack P. C. Kleijnen). This introductory tutorial will highlight uses of metamodels, commonly used metamodel types, the linkage between metamodel type and the set of simulation model runs used to fit the metamodel, and basic issues in building and validating metamodels. The tutorial ends with a brief summary of recent research in metamodel types and use, and the implications for future metamodeling applications.

This article presents an active ball joint mechanism (ABENICS) enhanced by interactions of spherical gears. The gear-based joint drives three rotational degrees of freedom (RDoF) without slippage. The capabilities were inspired by the unique interactions between two different innovative gears [the cross spherical gear (CS-gear) and monopole gear (MP-gear)] and the superimposition of those interactions by the CS-gear's quadrature spherical tooth structure. One MP-gear constrains two of the three RDoF of the CS-gear. The driving module which drives the MP-gear converts this “constraint” into a “drive” and drives the CS-gear with two RDoF. The CS-gear orthogonally superimposes the interactions caused by two MP-gears to achieve three RDoF driving forces. The principle was revealed by analyzing an equivalent linkage modeled on the mechanism of ABENICS. The linkage also led to the kinematics and torque equations. The theory and physical characteristics of ABENICS were verified in comprehensive and continuous positioning experiments on manufactured prototypes. The flexibility of the actuator placement was also verified in different configurations of the driving modules. The active ball joint, ABENICS can transmit high torque and reliable positioning in three RDoF without an orientation sensor, which applies to robot joints and orientation control mechanisms.

This paper examines the effects of HSR development on airport technical efficiency and the labor productivity at airports. Existing literature mainly focuses on the impacts of HSR on passenger traffic. In addition to passengers, HSR development may influence airports' other outputs such as cargo and flight movements together with various inputs. These inputs and outputs collectively determine airports' technical efficiency. With access to a dataset consisting of 46 Chinese airports and 16 Japanese airports from 2007 to 2015, the paper firstly adopts both the standard two-stage Data Envelopment Analysis (DEA) and double bootstrap methods to evaluate the impacts of HSR development on airports’ technical efficiency. We then evaluate the effects of HSR on airport labor productivity which is measured by both work-load units per employee and aircraft movements per employee. Our main findings indicate that HSR development relates to a decline in airport efficiency. Airports located in cities that have better connectivity or accessibility in the HSR network suffer more efficiency loss than the others. It is also observed that the locational advantage of HSR stations relative to airports is negatively associated with airport efficiency. By contrast, good intermodal linkage between the airport and its nearest HSR station is positively correlated with airport efficiency. Furthermore, the study reports different results between China and Japan with respect to the effects of HSR on labor productivity.

A systematic review of studies providing evidence of the linkage between human factors (HF) in the design and management of operations to production quality performance was conducted. 71 peer reviewed research papers were found to provide evidence of the HF-Quality relationship. These studies identified 178 design factors relating to quality. These included 1) Product Design (54), 2) Production Process Design (75), and 3) Workstation Design aspects (49). In addition 26 Individual quality risk factors were identified. Of the studies identified, about half studied the effects on the human finding associations with the operator workload and fatigue indicators and quality performance. These intermediary variables may provide insight into the mechanism by which HF flaws in the design of production lead to quality deficits in running manufacturing. These results provide useful information for operations managers and production system design teams to secure higher quality performance in their systems by applying human factors.

A huge amount of sensitive personal data is being collected by various online health monitoring applications. Although the data is anonymous, the personal trajectories (e.g., the chronological access records of small cells) could become the anchor of linkage attacks to re-identify the users. Focusing on trajectory privacy in online health monitoring, we propose the User Trajectory Model (UTM), a generic trajectory re-identification risk predicting model to reveal the underlying relationship between trajectory uniqueness and aggregated data (e.g., number of individuals covered by each small cell), and using the parameter combination of aggregated data to further mathematically derive the statistical characteristics of uniqueness (i.e., the expectation and the variance). Eventually, exhaustive simulations validate the effectiveness of the UTM in privacy risk evaluation, confirm our theoretical deductions and present counter-intuitive insights.

Purpose The purpose of this paper is to develop a model based on the total interpretive structural modeling (TISM) approach for analysis of factors of additive manufacturing (AM) and industry 4.0 (I4.0) integration. Design/methodology/approach AM integration with I4.0 is attributed due to various reasons such as developing complex shapes with good quality, real-time data analysis, augmented reality and decentralized production. To enable the integration of AM and I4.0, a structural model is to be developed. TISM technique is used as a solution methodology. TISM approach supports establishing a contextual relationship-based structural model to recognize the influential factors. Cross-impact matrix multiplication applied to classification (MICMAC) analysis has been used to validate the TISM model and to explore the driving and dependence power of each factor. Findings The derived structural model indicated the dominant factors to be focused on. Dominant factors include sensor integration (F9), resolution (F12), small build volumes (F19), internet of things and lead time (F14). MICMAC analysis showed the number of driving, dependent, linkage and autonomous factors as 3, 2, 12 and 3, respectively. Research limitations/implications In the present study, 20 factors are considered. In the future, additional factors could be considered based on advancements in I4.0 technologies. Practical implications The study has practical relevance as it had been conducted based on inputs from industry practitioners. The industry decision-makers and practitioners may use the developed TISM model to understand the inter-relationship among the factors to take appropriate measures before adoption. Originality/value The study on developing a structural model for analysis of factors influencing AM and I4.0 is the original contribution of the authors.

This research investigates the heterogeneous dynamic impacts of rural-urban migration and industrial agglomeration on the environmental degradation across regional development levels of Chinese provinces. An aggregated data set of 31 provinces, along with three provincial-scale panels, are used from 2005 through 2018. The long-run parameter estimates are obtained employing dynamic common correlated effects mean group technique (DCCEMGT), while the heterogeneous Granger non-causality Dumitrescu-Hurlin test is employed for causal directions. The core results are as follows. Firstly, a unidirectional positive linkage is revealed from industrial agglomeration and rural-urban migration to energy utilization. These linkages showed heterogeneity across the development levels—the most substantial impacts are discovered in highly developed regions (eastern provinces), while the least substantial are found in low developed regions (western provinces). Secondly, the combined impacts of linear and non-linear parameters of both industrial agglomeration and rural-urban migration confirmed environmental Kuznets curves (EKCs) in models with the tertiary sector. However, in the model with the secondary sector, only EKC based on rural-urban migration is verified. Finally, rural-urban migration mitigated the environmental degradation more substantially in the model with tertiary sector-based industrial agglomeration. It suggests that rural to urban migration contributes less to the environmental emissions through the economy's service sector.

This paper investigates the forward and inverse kinematics in screw coordinates for a planar slider-crank linkage. According to the definition of a screw, both the angular velocity of a rigid body and the linear velocity of a point on it are expressed in screw components. Through numerical integration on the velocity solution, we get the displacement. Through numerical differential interpolation of velocity, we gain the acceleration of any joint. Traditionally, position and angular parameters are usually the only variables for establishing the displacement equations of a mechanism. For a series mechanism, the forward kinematics can be expressed explicitly in the variable of position parameters while the inverse kinematics will have to resort to numerical algorithms because of the multiplicity of solution. For a parallel mechanism, the inverse kinematics can be expressed explicitly in the variable of position parameters of the end effector while the forward kinematics will have to resort to numerical algorithms because of the nonlinearity of system. Therefore this will surely lead to second order numerical differential interpolation for the calculation of accelerations. The most prominent merit of this kinematic algorithm is that we only need the first order numerical differential interpolation for computing the acceleration. To calculate the displacement, we also only need the first order numerical integral of the velocity. This benefit stems from the screw the coordinates of which are velocity components. The example of planar four-bar and five-bar slider-crank linkages validate this algorithm. It is especially suited to developing numerical algorithms for forward and inverse velocity, displacement and acceleration of a linkage.

Law enforcement and security agencies around the globe have integrated geospatial analysis into their intelligence workflow to profile serial offenders, track suspects, and direct crime reduction/p...

In order to study the effect of the central linkage on the mesomorphic behaviour of aromatic ring liquid crystals we have synthesized two homologues groups, group A includes compounds 1a-d and grou...

Purpose This study aims to explore the linkage between fluctuations in the global crude oil price and equity market in fast emerging economies of India and China. Design/methodology/approach The present research uses wavelet decomposition and maximal overlap discrete wavelet transform (MODWT), which decompose the time series into various frequencies of short, medium and long-term nature. The paper further uses continuous and cross wavelet transform to analyze the variance among the variables and wavelet coherence analysis and wavelet-based Granger causality analysis to examine the direction of causality between the variables. Findings The continuous wavelet transform indicates strong variance in WTIR (return series of West Texas Instrument crude oil price) in short, medium and long run at various time periods. The variance in CNX Nifty is observed in the short and medium run at various time periods. The Chinese stock index, i.e. SCIR, experiences very little variance in short run and significant variance in the long and medium run. The causality between the changes in crude oil price and CNX Nifty is insignificant and there exists a bi-directional causality between global crude oil price fluctuations and the Chinese equity market. Originality/value To the best of the authors’ knowledge, very limited work has been done where the researchers have analyzed the linkage between the equity market and crude oil price fluctuations under the framework of discrete wavelet transform, which overlooks the bottleneck of non-stationarity nature of the time series. To bridge this gap, the present research uses wavelet decomposition and MODWT, which decompose the time series into various frequencies of short, medium and long-term nature.

Linking user profiles belonging to the same people across multiple social networks underlines a wide range of applications, such as cross-platform prediction, cross-platform recommendation, and advertisement. Most of existing approaches focus on pairwise user profile linkage between two platforms, which can not effectively piece up information from three or more social platforms. Different from the previous work, we investigate scalable user profile linkage across multiple social platforms by proposing an effective and efficient model called EEUPL, which can detect duplicate profiles within one platform that belong to same person and is implemented with Apache Spark for distributed execution. The model contains two key components: 1) To link cross-platform user profiles effectively, we propose an average-link strategy based clustering method. 2) To extend the model EEUPL to large-scale datasets, an Apache Spark based approach is developed. Extensive experiments are conducted on two real-world datasets, and the results demonstrate the superiority of the model EEUPL compared with the state-of-art methods.

In this work, the design, modeling, dimensional synthesis, and experimental characterization of a dexterous robotic hand based on the Stewart-Gough parallel manipulator are presented. The mechanism consists of three parallel linkage fingers with six prismatic actuators that control manipulation. An additional actuator maintains stable grasping forces. A computational model to predict the hand's workspace is then utilized to determine the optimal design parameters that maximize the workspace size and manipulability. A physical prototype based on the optimized parameters is built and experimentally characterized to assess its performance (Figure 1).

In the crowdsourcing task allocation scheme, there is an emerging and realistic co-opetition phenomenon. To availably solve the crowdsourcing task allocation problem with co-opetition, this paper designs a two-stage co-opetition model by constructing novel three-way decision (TWD), including a competition-optimization model and a negotiation-cooperation model. Unlike the other studies, the two-stage co-opetition model with TWD can not only protect the profits of the task candidates, but also optimize the overall benefits. Specifically speaking, in the competition-optimization model, we construct an optimization model based on the data envelopment analysis (DEA) method in advance, which maximizes the personal benefit. By integrating information system and the loss function matrix, we consider the linkage of evaluation information and risk information and then improve the original TWD to make an initial allocation. In the negotiation-cooperation model, considering that the relationship among the candidates may influence the task performance, the fuzzy measure is introduced to describe a broader partnership. Meanwhile, we also design two different schemes to coordinate and optimize the best task allocations based on the initial allocation. In order to choose the best scheme, the selection strategy between schemes is further investigated under the guidance of the utility and the loss. Finally, we give an example of a medical supply chain crowdsourcing problem to illustrate and verify our proposed approach.

The integral shrouded blisk provides better performance with minimum weight, but its semi-open structure presents problems for its production. Manufacturing processes of these components require a removal of about 70%-90% of material from their blanks. Multi-axis electrical discharge machining (EDM) is commonly used for these processes, but its poor efficiency cannot meet the requirements of mass production. Strong flushing assisted high-current discharge is able to improve the machining efficiency. In this paper, this method was applied to manufacture the integral shrouded blisk. An electrode design method was proposed. Taking the largest revolving entity inside the flow channel as the base geometry, this laminated arc-shaped hollow electrode meets the requirements such as high pressure flushing, tool wear compensation, and easy to be made. A 4-axis linkage machining tool path with planetary motion was proposed. Taking an integral guide vane ring as an example, it has been experimentally verified that the time consumption for each channel using this method was reduced to a half of the ordinary EDM method, while the finished surface quality remains same.

An infrastructure impact assessment process relies on the analysis of multiple types of models, the performance of individual infrastructure networks and the interdependencies between multiple infrastructure networks. Several models are developed for their specific purposes and there is a need to link these models for the assessment of natural hazard impacts on distributed infrastructures to deliver the desired outcomes on network functionality and disruption levels that are suitable to assess socio-economic impact. In this paper, an ‘end-to-end’ linkage structure is proposed to link different models by which various features, data standards, parameters and structures are linked in a transparent and consistent manner. The framework has adopted a dedicated knowledge discovery and data analysis process to acquire information around input and output parameters for each of these models developed by various researchers and used in risk assessment tools. The framework is illustrated by applying the step-by-step procedure towards integrated impact assessments of electricity, potable water and road networks and their interdependencies.

The sports industry is considered the industry with the most vitality, participation, and penetration in the 21st century. From the perspective of practice on a global scale, the demand for the sports market has gradually developed from low-level simplification to high-level multi-polarity, and sports consumption has also shifted from single sports goods to sports services and entertainment sports. The sport industry has become modern society containing emerging industries with large business opportunities. This article mainly uses literature, expert interviews, data collation, logical analysis, and other methods to conduct a comparatively systematic study on the development of the new form of the “Internet+” sports industry. In the study, by comparing the commodity types, organizational forms, and management of the traditional sports industry in terms of management and other aspects, the connotation of the new format of the “Internet+” sports industry is introduced in detail, which is divided into four industries: network broadcasting, smart software and hardware, vertical e-commerce, and e-sports. The research in this article shows that, after accounting, the total scale (total output) of the national sports industry in 2019 was 2,948.3 billion yuan, with a year-on-year added value of 1,124.8 billion yuan. In terms of growth, total output increased by 10.9% over 2018 and 11.6% year-on-year. Among them, sports activities integrated with the Internet have reached 58%. Finally, it will help the transformation and upgrading of Internet+sports and improve its own development level. Returning to the real economy and serving the real economy have become a consensus for the future development of Internet finance.

The flood in Kashmir valley has a long history and is considered as recurrent phenomena, though the flood occurred in 2014 was extremely severe due to its extent, intensity and impact on mankind. T...

PurposeThe aim of this paper is to identify and analyse workforce development challenges in the digital age by first, presenting these challenges and relationship between them, and then proposing a structural model that categorizes these challenges and proposes suggestions for managers to improve human resources practices and firm performance.Design/methodology/approachFuzzy total interpretive structural modelling (TISM) is used as the methodology, which gives an interpretive structural model by presenting direct and transitive relationship between workforce development challenges and categorizes them under autonomous, dependent, independent and linkage groups.FindingsIn total, 13 different workforce development challenges are presented in this study. Results showed that lack of IT/digital skills has a critical role in workforce development in terms of affecting other challenges. Dependent group includes requirements for longer learning time and specialized training, lack of analytical thinking and dealing with complexity, and lack of interdisciplinary thinking and acting. On the other hand, lack of ability in decentralized decision-making and shortage of workforce with adequate skillset within the labour market have more macro-impacts on others. Most of the challenges located in the linkage group, which means that most of the challenges are interrelated with each other.Originality/valueOriginality of this paper is presenting a systematic structure for workforce development in Industry 4.0 that considers challenges systematically.

Purpose The purpose of this paper is to describe the design and development of a novel series-parallel robot, which aims to climb on the transmission tower. Design methodology approach This study introduces a hybrid robot, which consists of adsorption and two 3-degree of freedom (DOF) translation parallel legs connected by a body linkage. The DOF of the legs ensures that the robot can move on the climbing plane, also contribute to a compact design of the robot. An electromagnet is used to adsorb onto the transmission tower, simplifying the overall structure. Based on the robot design, this paper further defines its climbing gait and adopt the 6th B-spline curves for climbing trajectory planning under different working environments. Findings The developed prototype that implements the design of the robot, which was used in simulation and experiments, showing that the robot is capable of climbing in the test environments with the planned climbing gait. Originality value The hybrid robot is able to climb under varying degrees of inclinations and cross the obstacles, and the magnetic attraction can ensure stable climbing.

The socio-environmental crisis and the complexity of urban problems highlight the importance of better understanding the emergence and configuration of social innovation ecosystems (SIEs) and their impact on cities. This article proposes a new theoretical–methodological approach that is inspired in a pragmatism perspective and presents results of its empirical application in the mapping and analysis of the SIE in the city of Florianopolis, Brazil. The study was put into practice through the creation and implementation of a collaborative digital platform that made it possible to make a cartography of the network that forms the city’s SIE, shedding light on the linkage between micro-meso-macro-scales of SIEs. The research findings contribute to raising key aspects in each scale of SIE that could foster or hinder social innovation dynamics. In this sense, besides contributing to understanding the dynamics of SIEs better, the purpose of this study was to analyze the configuration, scope, and limits of the SIE to reinforce the processes of democratic experimentation and to strengthen the sustainability of cities, especially in countries of the South, where these studies are still scarce.

Researchers and practitioners have been interested in solving real-world problems through clustering. The clustering of nodes in networks with unipartite or bipartite structure is important to explore real-world complex networks present in nature and society. Bipartite networks form an important class of complex networks because they reveal the heterogeneity of nodes in a network. However, most extant clustering methods focus only on unipartite networks. In this work, a novel constrained agglomerative clustering method applicable to unipartite and bipartite networks has been proposed. Initially, the topology of a network is modeled according to set-theoretic principles. Subsequently, the concepts related to rough set theory and relative linkage are used to cluster the set of nodes. The utility and effectiveness of the proposed approach are demonstrated through offline experiments on unipartite and bipartite networks. A comparison against ten state-of-the-art similarity measures over two different partitional clustering algorithms reveals the effectiveness of the proposed relative linkage measure. Moreover, a comparative analysis with state-of-the-art network clustering methods reveals the viability of the proposed rough set-based constrained agglomerative clustering algorithm. Finally, the proposed method has been applied for the detection of cohesive subgroups of banks in a real bipartite network formed by mapping credit relationships between Indian firms and banks.

There have been many recent fears of severe house-price decreases in some provinces in China causing a nationwide collapse of the housing market. Therefore, this paper aims to clarify the linkage structure of China's housing market and its risk contagion routes. Given monthly data of provincial housing and stock-market capital returns from 2001M01 to 2019M12, on the basis of graph theory, this paper first explores the linkage structure of provincial housing markets. Relying on the linkage structure, this paper then simulates the effect of unexpected negative shocks from the stock market on the probabilities of a housing-market collapse based on the epidemic model. The results show that (i) consistently with practical evidence, the probability of housing-market collapse is relatively high in the southwest of China and (ii) reducing housing-market linkage, such as through a blocking mechanism, to prevent collapse is helpful.

The mixed synthesis of motion and path generation, which is also known as the Alt–Burmester problem, is an attractive problem for study. However, such a problem for the four-bar linkages which possess more than M poses (M>5) and mixed N path points has not been well-solved. In this work, a mixed synthesis method is developed for planar four-bar linkages to cope with the above problem. The developed method can quickly select an optimal combination that contains five poses and N points by using the conic filtering algorithm, which is based on the similar characteristics of the value and direction between the conic and coupler curves in a certain neighborhood. Next, the selected five poses are substituted into a simplified equation system of motion synthesis which includes four equations and four variables to solve the parameters of the planar four-bar linkage. Finally, a case is provided to validate the effectiveness of the developed method in the mixed synthesis problem.

Abrasive water jet (AWJ) technology has been more and more used in space curved surface machining. Dynamic angle compensation technology based on the five-axis linkage control system was the core to eradicate the errors caused by taper and jet lag in AWJ machining and enabled this technology to get into some precision fields. But the spatial kinematic rotation error of the cutting head in five-axis AWJ machine tool which has a direct impact on AWJ machining performance and accuracy has not been systematically studied. Aimed at this, this paper explored a new method based on spatial meshes to obtain the spatial kinematic rotation error of the cutting head. According to the visualization of the experimental data, the spatial kinematic rotation error was found with no obvious pattern. Then, a dimension reduction method was employed to mining these data and enabled this irregular error to be predicted with mapping method. According to the verification experiments, this new method was proved efficiently and useful in predicting the spatial kinematic rotation error.

This paper presents a geometric synthesis method for compliant mechanisms based on similarity transformation of pole maps. Motion generation is a typical and common mechanism synthesis task, so this study takes it as the design requirement to expound the proposed method. Most of the current research work relies on numerical solution of the nonlinear Bernoulli–Euler beam model, numerical simulations or physical experiments to study the synthesis method of compliant mechanisms. There is a lack of simpler and more efficient methods to achieve motion generation of compliant mechanisms with various topologies. This study is based on pole map which is a geometric tool to describe the motion of rigid-body mechanisms. In this paper, we first demonstrate the feasibility of applying the similarity transformation of pole map to compliant mechanisms. It is proved that the pole map of compliant mechanisms has the same characteristic as rigid-body mechanisms during similarity transformation. Then we present the procedure of synthesis method in detail and expound the establishment method of function module which can avoid the functional defects of the final designed mechanism. At last, we take the compliant geared linkages and compliant four-bar linkage as examples to illustrate the novel synthesis approach. The result is an applicable and effective synthesis method for motion generation of compliant mechanisms.

With a light-slender and superior dexterous body, the cable-driven segmented redundant manipulators (CSRMs) are excellent candidates for operations in narrow confined space. However, their application is still largely limited due to their weak stiffness, low load capacity, and complex modeling and planning. In this article, we design a new type of CSRM with high stiffness and load capacity using hybrid active and passive cables, and propose a simplified kinematics modeling and configuration planning method. The manipulator is composed of three active-linkage segments and one active tool end-effector. Each active segment, driven by three active driving cables, has two degrees of freedom (DOFs). By utilizing the passive linkage cables, the segment can be fully constrained with high stiffness, and move with equal joint angles in nearly continuous shape. Based on such structural features, the kinematics equations about the active segment-joint variables (i.e., the equalpitch and yaw angles of the whole segment) are derived. The direct, inverse kinematics and differential kinematics are greatly simplified. To find suitable solutions under environment constraints, extended virtual joint (EVJ) is introduced for quick regional solutions searching and equivalent kinematic constraint analysis. Furthermore, a configuration planning method based on the simplified kinematics and equivalent EVJs is proposed for single obstacle avoidance and continuous narrow space crossing tasks. Finally, a prototype system is developed and typical experiments are performed. The results show the high linkage accuracy, improved stiffness, and load capacity of the developed CSRM and verify the adaptability of the proposed configuration planning method.

This work analyzed the dynamic interactive causal links among urban agglomeration, economic performance, carbon emissions, and health expenditures across developmental disparities in China. To this end, this work developed a health expenditures-augmented growth model to introduce health expenditures and carbon emissions as a shift factor of total factor productivity. A block of simultaneous equations is developed based on the health expenditures-augmented growth modeling framework. The System-variant/Difference-variant Generalized Method of Moments is employed to estimate the block of simultaneous equations in order to deal with the potential endogeneity of the variables used. Based on empirical results, the core findings are as follows: first, a Pendroni cointegration-based long-run stable association is verified. Second, the urban agglomeration exhibited a bidirectional positive causal linkage with the gross domestic product (GDP) growth and health expenditures growth. Third, the health expenditures growth demonstrated a bidirectional positive causal linkage with carbon emissions growth and GDP growth. Fourth, a unidirectional mixed causal linkage—positive (negative) for linear form (squared form) of urban agglomeration—existed from urban agglomeration to carbon emissions growth. Fifth, there is a negative causal linkage operating from carbon emissions growth to GDP growth. However, there is mixed causal linkage—positive for a linear form of GDP growth, and negative for the squared form of GDP—operating from GDP growth to carbon emissions growth. These findings exhibited consistency in the type of causal linkages across the developmental disparities and hence showed robustness. Nevertheless, the findings showed disparities in the degree of impact across the developmental disparities. In this regard, the strength of causal linkage is the largest (moderate/lowest) for highly (moderately/least) developed regions of China. Based on empirical results, inferences are extracted and discussed.

A basic problem about a constant dimension subspace code is to find its maximal possible size $A_{q}(n, d, k)$ . Linkage construction and inserting construction are two effective methods to improve lower bounds for constant dimension codes. This letter concentrates on parallel linkage construction by He and direct inserting construction by Lao and generalizes the previous results to obtain new lower bounds of constant dimension codes, such as Aq(12,4,6).

The mesomorphic properties of linear shaped homologous series based on two linkage group have been designed and synthesized with different side chain substituents (-OR) on the one end of terminal s...

The link between trade and sustainable development has been largely analyzed on a piecemeal basis. A comprehensive study simultaneously examining economic, social and environmental aspects of sustainable development is needed to ensure coherence between the competing results of previous studies. This study aims to examine the relevance of trade openness in defining sustainable development, with special focus on five emerging countries known as BRICS, using the dynamic panel autoregressive distributed lag (ARDL) approach. The results indicate that economic growth has a tendency to enhance sustainability in both the long and short run. However, trade openness, energy consumption and foreign direct investment are extremely detrimental for sustainable development.

For loss and theft in the transport of radioactive materials by a single vehicle, this article summarizes the characteristics of “illegal movement” and establishes a security system that senses its inter-relationship and responds though the group network relationship. The security system reminds the vehicle crew through on-site response and linkage response. A failure detection method for on-site response is proposed, that is, the push model is used first, and when the measurement results are suspected, the pull model is used to further confirm the failure. The failure detection for linkage response adopts the push model. According to the different security requirements of the basic and enhanced transportation, the principle of setting the timeout threshold in the failure detection algorithm is proposed. In the enhanced type, the value is smaller, otherwise the value is larger. A specific timeout threshold quantification scheme is proposed. Experiments show that the method proposed in this article is effective.

Extracting information about Web entities has become commonplace in the academy and industry alike. In particular, data about places distinguish themselves as rich sources of geolocalized information and spatial context, serving as a foundation for a series of applications. This data, however, is inherently noisy and has several issues, such as data replication. In this work, we aim to detect replicated places using a deep-learning model, named PlacERN, that relies on multi-view encoders. These encoders learn different representations from distinct information levels of a place, using intermediate mappings and non-linearities. They are then compared in order to predict whether a place pair is a duplicate or not. We then indicate how this model can be used to solve the place linkage problem in an end-to-end fashion by fitting it into a pipeline. PlacERN is evaluated on top of two distinct datasets, containing missing values and high class imbalance. The results show that: (1) PlacERN is effective in performing place deduplication, even on such challenging datasets; and (2) it outperforms previous place deduplication approaches, and competitive algorithms, namely Random Forest and LightGBM using pairwise features, on both datasets in regards to different metrics (F score, Gini Coefficient and Area Under Precision-recall Curve).

PurposeThe study tries to identify the barriers influencing supply chain resilience and examine the inter-relationships between them. These relationships are built on the basis of how one barrier drives or is driven by the changes in another barriers.Design/methodology/approachIn the first phase, literature review and with due discussion with experts, the barriers have been identified and shortlisted for an Indian automotive case company. In the second phase, total interpretive structural modelling (TISM) has been applied to examine inter-relationships between the barriers for an Indian automobile case company. Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis has also been performed to analyse the driving and dependence power of the barriers.FindingsIn total, 11 barriers are identified from the first phase of the study. In the second phase, the TISM digraph is created which qualitatively explains the reason behind how one barrier leads to another. MICMAC analysis classifies these variables in four clusters namely autonomous, linkage, dependent and independent. These clusters characterise the barriers based on their driving and dependent power which helps managers in strategically tackling them while taking understanding from the TISM digraph.Research limitations/implicationsThree research implications can be made from the study. First, a comprehensive definition of supply chain which helps in understanding of resilience based on disruption phases and recovery. Second, 11 barriers are identified which hinder resilience in automotive sector. Their relationships are modelled using TISM which also gives why a particular relationship exists. Last, MICMAC analysis classifies barriers based on how high or low the driving and dependence power exists.Practical implicationsThe study offers significant implications for supply chain managers helping them in building resilience by identifying barriers and reducing their effect. Barriers are identified for case company which might help managers to tackle them during disruptions. The final TISM digraph depicts the “why” between the inter-relationships between the barriers to resilient supply chains. TISM shows that non-commitment of top management is the major root barrier which has been causing the other problems. MICMAC analysis is also performed along with discussion as to how autonomous, linkage, dependent and independent barriers can be tackled to build resilience.Originality/valueTISM is considered as an effective methodology for conceptual framework development as it also explains “why” between the relationships besides explaining the “what” as against ISM. Identification and understanding of barriers and their interrelationship will help supply chain managers to analyse the influence and inter-dependence of barriers on the resilience of the supply chain. Such understanding will help in mitigating/averting these barriers hence improving the resilience capability. It also adds to the knowledge base in the area of supply chain resilience where several authors have pointed the lack of research.

Multidisciplinary topology optimization (TO) for additive manufacturing (AM) exhibits unprecedented design and manufacturing freedom as an effective lightweight methodology. In order to fully utilize the AM advantages of materialized arrangement in spatial and voxel-by-voxel digitalized printing, multidisciplinary TO for AM requires a full understanding of the process-structure-property-performance (PSPP) relationship to establish the quantitative correlation of part property and multiple process factors, including laser-, process-, and material-related parameters. This study incorporates the PSPP relationships of laser sintered material with topology optimizer so as to provide a guideline for TO collaborative AM design. The proposed workflow involves mapping functions of PSPP relationships via a data-driven approach and then optimizes the multiple process parameters and structural topology by the gradient-based algorithm. Compared with conventional optimization approaches, three case-dependent optimizations demonstrate the effectiveness of the proposed approach yielding encouraging improvements of lightweight performance. The multidisciplinary TO can be generally applied to types of AM technologies, establishing a strong linkage of physical product and digital design.

Waterfront accessibility is one of the major planning aspects of cities. However, tackling this issue from the Human Well-Being (HWB) perspective is relatively new. Alexandria is one of the leading Mediterranean cities that was planned, shaped, and configured as based on its direct linkage to the waterfront. Nowadays, city extensions make many of its newly developed zones detached from the waterfront. This paper investigates the correlations between waterfront accessibility and HWB in Alexandria. It uses an analytical approach -based on statistical investigations- to compare HWB in two zones based on their proximity to the waterfront. The results show that detailed configuration of street pattern and travel duration are the most influencing attributes on waterfront accessibility. Consequently, these attributes have a higher impact on residents’ satisfaction or negative affect, and therefore their HWB than other attributes. The paper concludes with guidelines to policymakers, urban planners, and researchers’ contributions to waterfront accessibility.

Finite-set model predictive current control (FS-MPCC) has been employed for machine drives owing to the good dynamic performance. Sensitivity to parameter variation is one of the main barriers to its widespread application. To overcome this barrier, this article proposes an improved FS-MPCC for surfaced permanent magnet synchronous machines (SPMSMs). The contribution of this article is developing a novel current update mechanism, where the variation of resistance, rotor flux linkage, and inductance is considered, in which a modified coordinate system that contains a stationary and rotary axis frame is introduced. In this case, the predicted parameter can be obtained more accurately based on this mechanism, which can suppress the disturbances caused by model parameter mismatch. In addition, SPMSM parameter mismatch effect on FS-MPCC performance is analyzed in this article, which testifies that resistance mismatch influence on current prediction error can be neglected in practical system. The proposed FS-MPCC is validated and compared with different state-of-the-art methods. Improvement of the proposed control strategy is validated by means of experimental results on a 2-kW test rig.

Cooperating in low-carbon linkage development is an inevitable choice for manufacturing and logistics enterprises in emerging economies and government plays an important role in the cooperation. Th...

PurposeThe purpose of this paper is to propose an interactive 2D–3D garment parametric pattern-making and linkage editing scheme that integrates clothing design, simulation and interaction to design 3D garments and 2D patterns. The proposed scheme has the potential to satisfy the individual needs of fashion industry, such as precise fit evaluation of the garment, interactive style editing with ease allowance and constrained contour lines in fashion design.Design/methodology/approachThe authors first construct a parametric pattern-making model for flat pattern design corresponding to the body dimensions. Then, the designing 2D patterns are stitched on a virtual 3D mannequin by performing a virtual try-on. If the customer is unsatisfied after the virtual try-on, the adjustable parameters (appearance parameters and fit parameters) can be adjusted using the 2D–3D linkage editing with hierarchical constrained contour lines, and the fit evaluation tool interactively provides the feedback.FindingsThe authors observed that the usability and efficiency of the existing garment pattern-making method simplifies the garment pattern-making process. The authors utilize an interactive garment parametric flat pattern-making model to generate an individualized garment flat pattern that effectively adjust and realize the local editing of the garment pattern-making. The 2D–3D linkage editing is then employed, which alters the size and shape of garment pattern for a precise human model fit of the 3D garment using hierarchical constrained contour lines. Various instances have validated the effectiveness of the proposed scheme, which can increase the reusability of the existing garment styles and improve the efficiency of fashion design.Research limitations/implicationsFirst, the authors do not consider the garment pattern-making design of sophisticated styles. Second, the authors do not directly consider complex garment shapes such as wrinkles, folds, multi-layer models and fabric physical properties.Originality/valueThe authors propose a pattern adjustment scheme that uses the 3D virtual try-on technology to avoid repetitions of reality-based fit tests and garment sample making in the designing process of clothing products. The proposed scheme provides interactive selections of garment patterns and sizes and renders modification tools for 3D garment designing and 2D garment pattern-making. The authors present the 2D–3D interactive linkage editing scheme for a custom-fit garment pattern based on the hierarchical constraint contour lines. The spatial relationship among the human body, pattern pieces and 3D garment model is adequately expressed, and the final design result of the garment pattern is obtained by constraint solving. Meanwhile, the tightness tension of different parts of the 3D garment is analyzed, and the fit and comfort of the garment are quantitatively evaluated.

The study aims to explore the causal linkage between CO2 emissions, economic growth and energy consumption in Thailand utilizing the wavelet coherence approach, conventional Granger and the Toda-Yamamoto causality techniques. In this study, In this study, time-series data spanning the period between 1971 and 2018 were used. No prior study has used the wavelet coherence approach to collect information on the association and causal interrelationship among these economic variables at different frequencies and timeframes in Thailand. The study objectives are structured to answer the following question: Does economic growth and energy consumption lead to CO2 emissions in Thailand?. The findings revealed that: (a) Changes in economic growth led to changes in CO2 emissions in Thailand at different frequencies (different scales) between 1971 and 2018. (b) A bidirectional causal relationship between CO2 emissions and energy consumption. (c) A positive correlation between CO2 emissions and energy usage in the short and long-run between 1971 and 2018. (d) A positive correlation between GDP growth and CO2 emissions in the short and long-run between 1971 and 2018. The study suggested that Thailand should initiate stronger policies towards enhancing the efficiency of energy and energy-usage programs to minimize unnecessary energy waste.

A constant-dimension code (CDC) is a set of subspaces of constant dimension in a common vector space with upper bounded pairwise intersection. We improve and generalize two constructions for CDCs, the improved linkage construction and the parallel linkage construction , to the generalized linkage construction and the multiblock generalized linkage construction which in turn yield many improved lower bounds for the cardinalities of CDCs; a quantity not known in general.

This article proposes a compact ankle exoskeleton with a multiaxis parallel linkage mechanism. By applying torques to the ankle joint, it can generate dorsi- and plantar-flexion motions. The design variables of the mechanism were analyzed and optimized to accommodate up to 12 N·m of torque within a thickness constraint of 40 mm. The parallel linkage structure of the proposed mechanism requires that moving mechanical parts must be thin and located at the front of the shank. Using the data from foot pressure sensors, the device can recognize the gait phases. The output torque and angle data were collected to evaluate the performance of the device.

Many malicious activities require a large number of IP addresses for altering user identities. It is well known that a large number of IP addresses could be obtained through compromising numerous machines and building botnets. However, we recently found that a special type of off-the-shelf virtual private server (VPS), which we refer to as dynamic VPSs, can retrieve a huge number of IP addresses using just a single virtual machine. Although dynamic VPSs are intended for legitimate purposes, whether they are actually misused in malicious activities has never been investigated. In this article, we take the first step to study dynamic VPSs, with an emphasis on their security implications. We reveal that dynamic VPSs are surprisingly and extensively involved in malicious activities, explore their internal working mechanisms, and suggest that the linkage of dynamic VPSs to the security domain deserves adequate attention.

Finger Clamping Unit (FCU) is a small-sized single-point clamp developed to clamp thin object of various thicknesses. It has a six-bar linkage with one compliant link, uses an electric motor as an actuator and induces toggle-lock motion by singular configuration. The main purpose of the FCU is to clamp car bodies in car assembly lines, while adapting to various thicknesses of car body. Unlike other clamping devices in the industry, it has a large clamping range (defined as the thickness range that the FCU can clamp). In this paper, the overall process of FCU development is presented. The six-bar linkage was chosen in type synthesis, and compliance was added for toggle-lock motion. Static analysis of the compliant FCU was completed, and results were plotted in a three-dimensional (3D) plot which expresses the behavior of the FCU. The lengths of each link were optimized in dimension synthesis. An FCU was constructed to reinforce the simulated results. The unique design of both the six-bar linkage FCU and the compliant link were presented. Simulated and experimental 3D plots were compared and analyzed. An appropriate friction model that best fits the experiment data was found. The advantage of the FCU—its clamping range—was proved by experiment.

The relationship between climate change and human mobility is generating increased public, academic and policy recognition. This linkage has captured the collective imagination, with forced mobilit...

Porous liquids (PLs), an emerging kind of liquid materials with permanent porosity, have attracted increasing attention in gas capture. However, directly turning metal–organic frameworks (MOFs) int...

Three-way group decisions provide an efficient method to settle complex and high risk decision-making problems. To obtain reasonable decision results that satisfy different backgrounds and knowledge of decision makers, it is necessary to design a proper consensus reaching process (CRP) for loss functions of decision-theoretic rough sets (DTRSs). Unlike existing researches, this paper not only extends the group relationship among decision makers to the social network, but also considers the externality of social trust network in group decision making. In light of this idea, we design a new CRP with the externality of social network for three-way group decisions. In the CRP, the adjustment of a decision maker who is persuaded by the moderator can influence other decision makers to accordingly adjust evaluations. Thus, by using the linkage externality influence among decision makers, we establish a two-stage mixed 0–1 linear optimization consensus model for the determination of loss functions of DTRSs. Then, based on Bayesian decision procedure, we construct a complete decision procedure for three-way group decisions with social network. Finally, we apply our proposed method to assess desert locust invasion areas and verify its validity.