Path Connectivity Research Articles

Inclusive leadership and employee innovative behavior: moderated by creative self-efficacy

In the academic and other sectors, Employee Innovative Behavior (EIB) is a significant problem. Employees in the e-commerce sector are experiencing more job instability as a result of the growing uncertainty imposed by COVID-19. Career sustainability (CS) is now in concern. Creative self-efficacy (CSE) is a person's confidence in their capacity to create. CSE creative thinking and problem-solving, which may lead to professional success and innovation. Additionally, CS must be taken into account because one's perception of the sustainability of a career affects their propensity to innovate. Based on the theory of job demands and resources (JDR), this study uses a combination of theoretical construction and quantitative analysis to examine how creative self-efficacy influences the relationship between inclusive leadership and employee innovation behavior in China's e-commerce sector, particularly livestream e-commerce. Employee perceptions of occupational sustainability were examined for their potential mediating effects. This research examined the role of CSE as a mediator in the aforementioned connections as well as the effect of CS leadership, which is EIB, on inclusive leadership (IL). The construct validity and path connections are examined by structural equation modeling. The findings demonstrate that the risk created by the COVID-19 epidemic for China's live streaming e-commerce, IL can only assist the translation of employment assets into workplace EIB when employees perceive CS. The findings demonstrated that IL enhances EIB through CSE. The research provides a theoretical basis for IL and EIB and conceptually overcomes the gap. We guide companies and executives on how to actually give workers tools at work that will support their CS while advancing their EIB.

Efficient Spatial Resampling Using the PDF Similarity

In real-time rendering, spatiotemporal reservoir resampling (ReSTIR) is a powerful technique to increase the number of candidate samples for resampled importance sampling. However, reusing spatiotemporal samples is not always efficient when target PDFs for the reused samples are dissimilar to the integrand. Target PDFs are often spatially different for highly detailed scenes due to geometry edges, normal maps, spatially varying materials, and shadow edges. This paper introduces a new method of rejecting spatial reuse based on the similarity of PDF shapes for single-bounce path connections (e.g., direct illumination). While existing rejection methods for ReSTIR do not support arbitrary materials and shadow edges, our PDF similarity takes them into account because target PDFs include BSDFs and shadows. In this paper, we present a rough estimation of PDF shapes using von Mises--Fisher distributions and temporal resampling. We also present a stable combination of our rejection method and the existing rejection method, considering estimation errors due to temporal disocclusions and moving light sources. This combination efficiently reduces the error around shadow edges with temporal continuities. By using our method for a ReSTIR variant that reuses shadow ray visibility for the integrand, we can reduce the number of shadow rays while preserving shadow edges.

Network Design Using Load Balancing Equal Cost Multi Path (ECMP) Method At Lexima Consultant Office

The development of technological advances also contributed to the advancement of Internet technology. Where the Internet is one of the needs that is considered important in all fields, this is evidenced by the number of Internet users from 2020 to 2023 having a significant increase. Lexima Consultant as one of the institutions engaged in information system creation services, of course, requires an internet connection. However, there are several obstacles faced, one of which is the absence of a load balancing and failover network system which sometimes makes the need for internet access with large bandwidth allocations to be disrupted and even cut off. Implementing the right technique at the Lexima Consultant office for sending data packets as the main factor supporting activities is certainly very much needed. In the research conducted, a load balancing technique was used using the ECMP method to optimize network performance and avoid internet network disturbances. From the research conducted, it can be concluded that the implementation of the load balancing method using the ECMP method has been able to divide connection paths and failover can run properly, so the possibility of disruption in the form of a network connection loss will be very small

Functional brain network based multi-domain feature fusion of hearing-Impaired EEG emotion identification

In the past, Electroencephalography (EEG)-based emotion identification research mainly focused on healthy, disordered, or depressed subjects. Due to the lack of an emotion acquisition and expression channel, there may be a bias in affective cognition for the hearing impaired. In this work, 15 hearing-impaired subjects were recruited to participate in an emotional movie-induced experiment, while their EEG signals were collected for emotion recognition. Four types of movie clips, which contained happiness, calmness, sadness, and fear, were selected. We fused three kinds of features, differential entropy (DE), power spectral density (PSD), and functional brain network to integrate the frequency domain and the spatial domain information of EEG signals. To find the brain region connections of different emotions, different coupling methods, and binarization methods were explored. Moreover, the combination of different brain network attributes was used to find the representativeness of emotional information in the spatial domain. The experimental results show that the combination of phase-locked value (PLV) & 20% sparsity with four brain network attributes (clustering coefficient (CC), node degree (ND), node betweenness centrality (NBC), and node strength (NS)) achieved a higher accuracy of 94.17% for functional brain network-based emotion recognition. In addition, the method of feature fusion obtained a classification accuracy of 95.91% with an SVM-Linear classifier. Moreover, by constructing functional brain network, the key connectivity paths of different emotions are explored, which may provide insights into understanding the emotional processing of the hearing-impaired.

Key physical topology features for optical backbone networks via a multilayer correlation analysis

A communication network is a multilayer network comprising various layered technologies, and the underlying physical topology is an important aspect that determines the upper bound of overall system performance, including total communication capacity, cost, and robustness. We expect that understanding the impact of the physical topology on system performance will lead to better optical communication network design in the future, and we thus focus on clarifying the relationship between physical topology features and system performance. There have been various studies on the relationship between topology features and overall network performance. For example, the average number of hops and the cluster coefficient are well known to change network properties in complex networks. From the perspective of optical communication networks, it is known that the algebraic connectivity and average path length are related to total network capacity, and these findings have been applied in physical topology design models. On the other hand, there have been no quantitative comparisons among various topology features, and the comprehensiveness of the population from which these features are extracted is insufficient. Hence, we have developed a multilayer (physical topology and layer 1) correlation analysis framework that enables a quantitative comparison of topology features. We use this framework to numerically examine the relationships between physical topology features and the total communication capacity, cost, and robustness of optical communication networks, including graph features (especially graph spectra) that have not been investigated. The results show that the Laplacian spectral radius and geodesic distance Laplacian spectral radius are strongly related to system performance, in addition to the conventional average number of hops, cluster coefficient, algebraic connectivity, and average path length. We confirm that these correlations hold for the different network sizes and spatial nonuniformity of real optical backbone networks in different countries and regions. The results show that the average path length and cluster coefficient, or the Laplacian spectral radius and geodesic distance Laplacian spectral radius, are important guidelines for physical topology design of real optical backbone networks.

Path connectivity of spheres in the Gromov–Hausdorff class

The paper is devoted to geometrical investigation of Gromov–Hausdorff distance on the classes of all metric spaces and of all bounded metric spaces. The main attention is paid to path connectivity questions. The path connected components of the Gromov–Hausdorff class of all metric spaces are described, and the path connectivity of spheres is proved in several particular cases.

Queer Voids

Queer Voids

Empathic connectivity of exhibition technology and users in the digital Transformation: An integrated method of social network analysis and LDA model

Digital transformation has brought substantial innovation to traditional industries. As a new driving force for enhancing experiential environments, it has led to the symbiotic development of human and technical aspects on a new developmental journey. In the current discussion on digital transformation, scholars mainly focus on the internal logic of digital technology and its innovative role in social and economic development, but exploring the relationship between people and technology is lacking. Therefore, this research focuses on the technological innovation of outstanding exhibition technology in digital transformation. By collecting and analyzing technical feedback and related text materials from the Digital Museum, we build our research on two aspects: On one hand, we analyze the potential empathic empirical connectivity between exhibition technology and users, clarifying the systematic elements of technology, user experience, and sensory interaction involved in digital transformation. On the other hand, we compare the performance of empathy connection path relationships between exhibition technology and users, clarifying the advantages of each element in these paths and providing theoretical guidance for the selection of digital museum construction. As a result, the research constructs the logical framework of exhibition technology between exhibition technology and users, emphasizing the existence of environmental behavior performance and technology under digital transformation. Finally, the current study proposes the law of empathy between people and technology, revealing the crucial role of digital technology in upgrading user experiences and providing inspiration and guidance for the transformation and operation of digital museums.

Electroencephalography Based Microstate Functional Connectivity Analysis in Emotional Cognitive Reappraisal Combined with Happy Music.

Currently, research mainly focuses on the effects of happy music on the subjective assessment of cognitive reappraisal, but relevant results of the neural mechanism are lacking. By analysing the functional connectivity of microstates based on electroencephalography (EEG), we investigated the effect of cognitive reappraisal combined with happy music on emotional regulation and the dynamic characteristics of brain functional activities. A total of 52 healthy college students were divided into music group and control group. EEG data and behavioural scores were collected during an experiment of cognitive reappraisal combined with happy music. The dynamic time window of the brain functional network was determined by microstate analysis, and the metrics of functional connectivity, clustering coefficient (Cp) and characteristic path length (Lp), were calculated based on the phase-locked value. The arousal of cognitive reappraisal significantly increased (p = 0.005) in music group, but the valence did not change significantly. This suggested that happy music did not affect emotional regulation from the behavioural perspective. Four microstate global templates (A-D) were determined. With happy music, the duration (p = 0.043) and Lp (p = 0.033) of microstate B increased significantly, indicating that the transfection efficiency of the brain network decreased, reflecting a negative effect on cognitive reappraisal. The duration (p = 0.017) of microstate D decreased and of Cp (p < 0.001) increased significantly, indicating that the local information-processing ability of the brain network increased. We conclude that happy music can change the characteristics of brain functional networks and have a positive effect on cognitive reappraisal in specific period. The research provides a certain electrophysiological basis for applying happy music to cognitive reappraisal.

Zygote structure enables pluripotent shape-transforming deployable structure.

We propose an algorithmic framework of a pluripotent structure evolving from a simple compact structure into diverse complex 3D structures for designing the shape-transformable, reconfigurable, and deployable structures and robots. Our algorithmic approach suggests a way of transforming a compact structure consisting of uniform building blocks into a large, desired 3D shape. Analogous to a fertilized egg cell that can grow into a preprogrammed shape according to coded information, compactly stacked panels named the zygote structure can evolve into arbitrary 3D structures by programming their connection path. Our stacking algorithm obtains this coded sequence by inversely stacking the voxelized surface of the desired structure into a tree. Applying the connection path obtained by the stacking algorithm, the compactly stacked panels named the zygote structure can be deployed into diverse large 3D structures. We conceptually demonstrated our pluripotent evolving structure by energy-releasing commercial spring hinges and thermally actuated shape memory alloy hinges, respectively. We also show that the proposed concept enables the fabrication of large structures in a significantly smaller workspace.

Unveiling Charge-Transport Mechanisms in Electronic Devices Based on Defect-Engineered MoS2 Covalent Networks.

Device performance of solution-processed 2D semiconductors in printed electronics has been limited so far by structural defects and high interflake junction resistance. Covalently interconnected networks of transition metal dichalcogenides potentially represent an efficient strategy to overcome both limitations simultaneously. Yet, the charge-transport properties in such systems have not been systematically researched. Here, the charge-transport mechanisms of printed devices based on covalent MoS2 networks are unveiled via multiscale analysis, comparing the effects of aromatic versus aliphatic dithiolated linkers. Temperature-dependent electrical measurements reveal hopping as the dominant transport mechanism: aliphatic systems lead to 3D variable range hopping, unlike the nearest neighbor hopping observed for aromatic linkers. The novel analysis based on percolation theory attributes the superior performance of devices functionalized with π-conjugated molecules to the improved interflake electronic connectivity and formation of additional percolation paths, as further corroborated by density functional calculations. Valuable guidelines for harnessing the charge-transport properties in MoS2 devices based on covalent networks are provided.

Fundamental research on Japanese language education and career path connectivity in ASEAN countries

Although Japan is a major powerhouse, it is experiencing issues with a low birth rate and ageing population. The impact of these issues on the workforce could be significant. There are other ASEAN countries that are still considered developing nations and there is potential that Japan could bolster its workforce by employing students and workers from these countries. For this to be feasible, these individuals would need to be good Japanese language speakers. Associate Professor Tatsuya Niimi and his team at the Faculty of Economics, Nagoya Gakuin University, Japan, are conducting fundamental research on Japanese language education and career path connectivity in ASEAN countries. The researchers are seeking to understand how to improve teaching programmes that are geared towards resolving the shortage of local higher educated human resources for Japanese firms, especially small-to-medium enterprises. They want to establish exactly how Japanese language teachers can ensure that their lessons are adequate and what Japanese firms require of their employees in order to make language students an adequate fit. The research involves using computing technology to conduct remote interviews, web questionnaires and analyses. It will ascertain the requirements of Japanese business and then use this information to inform how students in ASEAN countries learn the Japanese language.

Efficient Single-image Super-resolution Using Dual path Connections with Multiple scale Learning

Deep convolutional neural networks have been demonstrated to be effective for single-image super-resolution in recent years. On the one hand, residual connections and dense connections have been used widely to ease forward information and backward gradient flows to boost performance. However, current methods use residual connections and dense connections separately in most network layers in a sub-optimal way. On the other hand, although various networks and methods have been designed to improve computation efficiency, save parameters, or utilize training data of multiple scale factors for each other to boost performance, they either do super-resolution in high-resolution space to have a high computation cost or cannot share parameters between models of different scale factors to save parameters and inference time. To tackle these challenges, we propose an efficient single-image super-resolution network using dual path connections with multiple scale learning (EMSRDPN). By introducing dual path connections inspired by Dual path Networks into EMSRDPN, it uses residual connections and dense connections in an integrated way in most network layers. Dual path connections have the benefits of both reusing common features of residual connections and exploring new features of dense connections to learn a good representation for single-image super-resolution. To utilize the feature correlation of multiple scale factors, EMSRDPN shares all network units in low-resolution space between different scale factors to learn shared features and only uses a separate reconstruction unit for each scale factor, which can utilize training data of multiple scale factors to help each other to boost performance, meanwhile, which can save parameters and support shared inference for multiple scale factors to improve efficiency. Experiments show EMSRDPN achieves better performance and comparable or even better parameter and inference efficiency over state-of-the-art methods. Code will be available at https://github.com/yangbincheng/EMSRDPN .

An Atrous Convolved Hybrid Seg-Net Model with residual and attention mechanism for gland detection and segmentation in histopathological images

PurposeA clinically compatible computerized segmentation model is presented here that aspires to supply clinical gland informative details by seizing every small and intricate variation in medical images, integrate second opinions, and reduce human errors. ApproachIt comprises of enhanced learning capability that extracts denser multi-scale gland-specific features, recover semantic gap during concatenation, and effectively handle resolution-degradation and vanishing gradient problems. It is having three proposed modules namely Atrous Convolved Residual Learning Module in the encoder as well as decoder, Residual Attention Module in the skip connection paths, and Atrous Convolved Transitional Module as the transitional and output layer. Also, pre-processing techniques like patch-sampling, stain-normalization, augmentation, etc. are employed to develop its generalization capability. To verify its robustness and invigorate network invariance against digital variability, extensive experiments are carried out employing three different public datasets i.e., GlaS (Gland Segmentation Challenge), CRAG (Colorectal Adenocarcinoma Gland) and LC-25000 (Lung Colon-25000) dataset and a private HosC (Hospital Colon) dataset. ResultsThe presented model accomplished combative gland detection outcomes having F1-score (GlaS(Test A(0.957), Test B(0.926)), CRAG(0.935), LC 25000(0.922), HosC(0.963)); and gland segmentation results having Object-Dice Index (GlaS(Test A(0.961), Test B(0.933)), CRAG(0.961), LC-25000(0.940), HosC(0.929)), and Object-Hausdorff Distance (GlaS(Test A(21.77) and Test B(69.74)), CRAG(87.63), LC-25000(95.85), HosC(83.29)). In addition, validation score (GlaS (Test A(0.945), Test B(0.937)), CRAG(0.934), LC-25000(0.911), HosC(0.928)) supplied by the proficient pathologists is integrated for the end segmentation results to corroborate the applicability and appropriateness for assistance at the clinical level applications. ConclusionThe proposed system will assist pathologists in devising precise diagnoses by offering a referential perspective during morphology assessment of colon histopathology images.

Raw Material Weighing Application Through Visual-Based RS-232 Cable Port

Officers who record incoming weighing data using a manual weighing machine experience difficulties when interacting with the weighing device. It is difficult to press the buttons, the storage memory cannot be more than three digits, and the display is difficult for officials to understand which can hinder the performance of recording the scales. Lack of capacity to store scale data on Officers who record incoming weighing data using a manual weighing machine experience difficulties when interacting with the weighing device. It is difficult to press the buttons, the storage memory cannot be more than three digits, and the display is difficult for officials to understand which can hinder the performance of recording the scales. Lack of capacity to store scale data on machine, so it can only store a maximum of 3 data scales. Inflexible on-machine data storage system. That is, the data scales that have been stored cannot be moved apart from within the machine itself. The large size of the machine is enough to take up space. So it is necessary to design a signal connection path from the scales to the computer via cable. With a computerized weighing application through the RS-232 communication port, where data input can be done using a visual-based weighing application. This data is then processed and produces an accurate report according to the data recorded by the scales. The testing process is carried out by entering data on the scales 19 times along with the check-in and check-out process for each incoming truck of raw materials for transportation. The testing process is carried out so that the application can run properly. machine, so it can only store a maximum of 3 data scales. Inflexible on-machine data storage system. That is, the data scales that have been stored cannot be moved apart from within the machine itself. The large size of the machine is enough to take up space. So it is necessary to design a signal connection path from the scales to the computer via cable. With a computerized weighing application through the RS-232 communication port, where data input can be done using a visual-based weighing application. This data is then processed and produces an accurate report according to the data recorded by the scales. The testing process is carried out by entering data on the scales 19 times along with the check-in and check-out process for each incoming truck of raw materials for transportation. The testing process is carried out so that the application can run properly.

Various Control Strategies Performance Assessment of the DFIG wind turbine connected to a DC grid

AbstractThis paper deals with the integration and control of the doubly fed induction generator‐based wind turbine (DFIG‐WT) in a DC grid. In this way, the stator of the DFIG‐WT is integrated with the DC grid via an uncontrolled diode‐bridge rectifier as well as a buck converter to provide a flexible connection path. In addition, the rotor of the DFIG‐WT exchanges power with the DC grid through a rotor‐side converter (RSC). By considering the DFIG‐WT system topology, three control strategies based on the stator flux‐oriented vector control are developed for the RSC and buck converter. The control schemes consist of the outer and the inner control loops with the proportional–integral (PI) controllers. Additionally, the stability of control strategies and their dependence on the generator parameters are evaluated and compared using modal analysis and numerical simulations in the MATLAB/SIMULINK environment. Finally, a real‐time hardware‐in‐the‐loop emulation‐based OPAL‐RT 5600 is accomplished to assess the performance of the superior control method from a practical perspective.

Heat extraction performance of fractured geothermal reservoirs considering aperture variability

It is still a challenging task to explain the uncertainty of the production of fractured geothermal reservoirs by using a parallel plate model without considering the variable aperture. Hence, we incorporated a heterogeneous aperture field with contact obstacles into a discrete fracture network (DFN) with different connection paths and densities and executed a medium-scale fluid flow and heat transfer simulation. The results show that severe flow channelization occurs in fracture systems with variable apertures, and the effective flow area is less than 40%. The increase in correlation length and contact obstacles leads to a decrease in the flow rate. The flow topology network reveals the reselection of dominant flow channels in the DFN. The effective flow intensity is independent of the fracture density and connection path length but has a negative correlation with the correlation length. The production temperature and cumulative heat energy production of the DFN model show a linear relationship with the correlation length. Finally, the strong correlation between cumulative heat production and the effective flow area emphasizes the critical role of flow channelization in the heat extraction of complex fracture systems. This study provides useful help for understanding how the micro heterogeneous aperture impacts macro production.

Dynamic Evolution and Collaborative Development Model of Urban Agglomeration in Hexi Corridor from the Perspective of Economic Flow

Under the green goals of the carbon peak and carbon neutrality, understanding how to develop the economy with high quality is an important issue facing regional development. Based on the years 2000, 2010, and 2020, this paper studies the industrial function connection path and economic network characteristics of the Hexi Corridor through an urban flow model, dominant flow analysis, modified gravity model, and social network analysis method, and puts forward an economic synergistic development model. It is of great significance to strengthen the urban connection in the Hexi Corridor and give full play to the overall competitive advantage. The results are as follows. (1) The overall function of the urban agglomeration is weak, the outward function of manufacturing is outstanding, the complementary network is highly complicated and evolving, and the environment and public service and tourism industry have apparent advantages. (2) The backbone correlation axes of the “three industries” show the characteristics of a closed triangular connection, dual-core linkage development, and multi-center multi-axis interaction. (3) The economic network has a greater agglomeration effect than diffusion effect, with prominent grouping characteristics, forming a network structure of “one man, three vices, and many nodes” and a significant spatial proximity effect. (4) Based on geographical proximity, the “one axis, four circles, multiple points, and multiple channels” synergistic development model, which breaks administrative barriers, becomes the endogenous driving force for the evolution of the economic network.

The Influences of Socio-Cultural Characteristics on Public Low-Cost Residents’ Satisfaction: A Case Study on PPR Seri Aman Kuala Lumpur, Malaysia

The development of housing often needed to be considered both economic and socio- cultural elements. Certain variables, such as residents' experience and socio-cultural backgrounds, have influenced how people perceive their living environment. Past researchers have highlighted several issues associated with low-cost housing and showed that Malaysia's housing policies still failed to provide a comfortable living area for the low- cost income group. Moreover, previous studies mainly focused on the residents' demographic characteristics as the influential factors. Therefore, this paper tries to fill this gap by (i) identify the socio-cultural characteristics of residents (ii) analyse the relationship between residents’ satisfaction and their socio-cultural characteristics. This is important since the study related to this aspect remains insufficient and their characteristics might affect the level of satisfaction of residents in terms of housing necessity. Based on the purposive sampling, the low-cost housing residents were selected. A questionnaire survey has been conducted on 93 residents of PPR Seri Aman in Kuala Lumpur and the data was analyzed using factor analysis and Pearson's correlation analysis. Findings from the study revealed that the residents were fairly satisfied with the dwelling unit features and neighborhood facilities. The low level of satisfaction among residents was heavily influenced by the yard, kitchen, dining space, parking available, sidewalks and connectivity of paths, traffic nearby, and the distance to take public transport. Further suggestions or recommendations are proposed to improve these situations or to help for future development planning.

The Internal Connection and Connection Path between Rural Revitalization and Community Support for Rural Elderly Living Alone

The Internal Connection and Connection Path between Rural Revitalization and Community Support for Rural Elderly Living Alone