Miracle-dz/UniFAR-FTUs huggingface dataset:
A scientific research topic trend prediction model based on multi‐LSTM and graph convolutional network

Predicting the development trend of future scientific research not only provides a reference for researchers to understand the development of the discipline, but also provides support for decision‐making and fund allocation for decision‐makers. The continuous growth of scientific publications has brought challenges to track the development trends of scientific research topics. The existing topic trend prediction methods have proved that the research topic trend of a publication is influenced by other peer publications. However, they ignore the fact that the research topics of different publications belong to different research topic space. Moreover, the existing topic prediction methods do not fully consider the interactive influence among publications that the research topic of one publication affects the topics of other publications, it is also influenced by the research topics of other publications. In line with this, this paper proposes a scientific research topic trend prediction model based on multi‐long short‐term memory (multi‐LSTM) and Graph Convolutional Network. Specifically, multiple LSTMs are employed to map research topics of different publications into their respective topic space. Then, the graph convolutional neural network is applied to learn the scientific influence context of each publication, so that the research topic of each publication not only integrates the influence of neighbor nodes, but also considers the influence of the neighbors of the neighbor node on the research topic of the publication, so as to more accurately fuse scientific influence context of research topic of peer publications. Experiments results on the data set of scientific research papers in the field of artificial intelligence and data mining demonstrate that the model improves the prediction precision and achieves the state‐of‐the‐art research topic trend prediction effect compared with the other baseline models.
Application of coupled electric field method for eddy current non-destructive inspection of multilayer structures

The development of fast and accurate method describing the electromagnetic phenomena intervening in eddy current non-destructive systems is very interesting, since it permits the design of reliable systems permitting the detection and the characterisation of defect in conductive materials. The coupled electric field method presented in this article can assume a large part of these objectives, because it is fast in comparison to the finite element method and easily invertible since the sensor impedance variation is an explicit function of target physical and geometrical characteristics. These advantages have motivated us to extend this method for multilayered structures, very interesting in aeronautic industry, by superposing the inductive effects in different layers. The impedance of an absolute sensor operating above three conducting layers will be calculated and compared to those obtained with finite element method. Afterwards, we shall exploit the model to study the effect of defect characteristics on the sensor impedance. Furthermore, regarding to the depth penetration effect, we shall make into evidence the necessity of accomplishing an optimal choice of the exciting field frequency during the inspection of multilayered materials. The essential importance of this method, besides of its rapidity, resides in its possibility to be extended to 2D irregular and 3D asymmetric configurations.
Coordinating multiagent teams in uncertain domains using distributed pomdps

Distributed Partially Observable Markov Decision Problems (POMDPs) have emerged as a popular decision-theoretic approach for planning for multiagent teams, where it is imperative for the agents to be able to reason about the rewards (and costs) for their actions in the presence of uncertainty. However, finding the optimal distributed POMDP policy is computationally intractable (NEXP-Complete). This dissertation presents two independent approaches which deal with this issue of intractability in distributed POMDPs. The primary focus is on the first approach, which represents a principled way to combine the two dominant paradigms for building multiagent team plans, namely the “belief-desire-intention” (BDI) approach and distributed POMDPs. In this hybrid BDI-POMDP approach, BDI team plans are exploited to improve distributed POMDP tractability and distributed POMDP-based analysis improves BDI team plan performance. Concretely, we focus on role allocation, a fundamental problem in BDI teams—which agents to allocate to the different roles in the team. The hybrid BDI-POMDP approach provides three key contributions. First, unlike prior work in multiagent role allocation, we describe a role allocation technique that takes into account future uncertainties in the domain. The second contribution is a novel decomposition technique, which exploits the structure in the BDI team plans to significantly prune the search space of combinatorially many role allocations. Our third key contribution is a significantly faster policy evaluation algorithm suited for our BDI-POMDP hybrid approach. Finally, we also present experimental results from two domains: mission rehearsal simulation and RoboCupRescue disaster rescue simulation. In the RoboCupRescue domain, we show that the role allocation technique presented in this dissertation is capable of performing at human expert levels by comparing with the allocations chosen by humans in the actual RoboCupRescue simulation environment. The second approach for dealing with the intractability of distributed POMDPs is based on finding locally optimal joint policies using Nash equilibrium as a solution concept. Through the introduction of communication, we not only show improved coordination but also develop a novel compact policy representation that results in savings of both space and time which are verified empirically.
Design of asymmetric flexible micro-gripper mechanism based on flexure hinges

Symmetric micro-gripper mechanism is very easy way to destroy the micro-components or parts for nonuniform force in the processing of micro-assembly. Aiming at the requirements of micro-assembly for the microtubule (diameter of 0–200 μm) components, a new type of asymmetric flexible micro-gripper mechanism based on flexure hinges was designed and studied. The asymmetric micro-gripper mechanism was driven by piezoelectric actuator, whose output displacement was amplified and transmitted by flexure hinges, and the flexible parallel four-bar mechanism was used to ensure that the micro-clamp moves and is held parallel. The displacement amplification ratio of the asymmetric flexible micro-gripper mechanism was deduced theoretically, and the finite element analysis and the experiment were also carried out to study the displacement amplification ratio in detail. The experiment results show that the displacement amplification ratio of the asymmetric flexible micro-gripper mechanism is 4.16, compared with the finite element analysis result and the theoretical calculation result; the error between them is 1.89% and 5.67%, respectively. The experiment results also show that the step-wise resolution of the micro-gripper is 7.50 μm, and the output force of the right micro-clamp was measured at 0.28 N. The asymmetric flexible micro-gripper mechanism is able to perform the micro-assembly tasks for the microtubule parts, and it is helpful to design this type of micro-gripper mechanism.
Identification of honey bee (Apis mellifera) larvae in the hive with faster R-CNN for royal jelly production

Abstract Royal jelly is actively used in healthcare products, healthy nutrition, cosmetics industry, strengthening the immune system, treatment of cancer, and many other diseases and new studies are being conducted on its usability in new areas. However, the production of such a useful product is technical and laborious. The most time-consuming process in production is larva grafting performed by hand. For this, a tool that can detect and graft the ideal sized larvae should be developed. The aim of this study, as the first step of such a tool, is to detect the larvae, which are ideal for the production of royal jelly. In the study, initially, a camera setup that can take clear photographs of honeycomb cells was prepared. With this setup, honeycomb photographs were taken containing larvae of different sizes. Later, the larvae with ideal size in the photographs were labelled and the convolutional neural network was trained. Finally, honeycomb cells and centre points were identified with Hough circle, and the locations of the larvae according to the honeycomb cell were determined. In conclusion, a system that can successfully identify ideal sized larvae and their locations to be used in the production process for royal jelly was created.
Hierarchical Absorbing Interface Conditions for Wave Propagation on Non-Uniform Meshes

In this paper, we propose hierarchical absorbing interface conditions to solve the problem of wave propagation in domains with a non-uniform space discretization or grid size inhomogeneity using Padé Via Lanczos (PVL) method. The proposed interface conditions add an auxiliary variable in the wave system to eliminate the spurious reflection at the interface between regions with different mesh sizes. The auxiliary variable with proper boundary condition can suppress the spurious reflection by cancelling the boundary source term produced by the space inhomogeneity in variational perspective. The new hierarchical interface conditions with the help of PVL implementation can effectively reduce the degree of freedom in solving the wave propagation problem. AMS subject classifications: 65K10, 65N22, 35L05
Ocular Surface Disease Signs and Symptoms in Patients with Pseudoexfoliative Glaucoma: A Case—Control Study

Purpose: The present study evaluates the differences in the prevalence of the signs and symptoms of ocular surface disease (OSD) in patients with PEX glaucoma (PEXG), compared to other glaucoma types (non-PEXG). Methods: Patients with non-PEXG and PEXG were prospectively examined for the presence and severity of OSD signs and questioned for symptoms using the OSDI (ocular surface disease index) questionnaire. Results: 116 patients were prospectively enrolled (58 non-PEXG and 58 PEXG). PEXG subjects who were older, had lower central corneal thickness (CCT) values, at a more advanced glaucoma stage and required more IOP lowering drops. OSD signs were prevalent in both groups: conjunctival hyperemia (74.5% non-PEXG vs. 94.8% PEXG), eyelid redness (70.7% vs. 96.6%), conjunctival (74.1% vs. 93.1%) and corneal fluorescein staining (81% vs. 93.1%) and abnormal TFBUT (82.8% vs. 87.9%). When adjusted for potential confounders, (older age, thinner CCT, more advanced glaucoma in PEXG) eyelid redness remained the only parameter significantly associated with PEXG, being 11 times more likely to occur in this group (p = 0.037). Conclusion: Subjects with PEXG presented a higher frequency of signs of OSD compared to other glaucoma types. When accounting for confounding factors, the only difference between the groups was the significantly higher presence (11 times more likely) of eyelid redness in PEXG, suggesting, in addition to glaucoma treatment, the impact of PEX on ocular surface integrity.
Modeling Fluid-Structure Interaction in Cavitation Erosion: Preliminary Results

This paper is devoted to cavitation erosion modeling. It presents some recent numerical developments made in the code initially developed in collaboration with E.Johnsen and collaborators at University of Michigan [1] in order to account for fluid-structure interaction. The considered test case is that of a single air bubble collapsing near a wall due to an incident shock wave in the surrounding water. In our investigation, we focus on the code implementation and optimization and the bubble implosion mechanism. The paper is focused on the various events occurring during bubble collapse and the computation of the time evolution of the pressure distribution. The influence of the amplitude of the incident wave and the distance of the bubble to the wall are investigated.
Unsteady Aerodynamics of Miniature Trailing-Edge Effectors Based on Indicial Methods

The aerodynamics of miniature trailing-edge effectors (MiTEs), or active Gurney flaps, is explored in many aspects with regards to their applicability to rotorcraft. MiTEs hold strong potential to be used as active devices to improve performance, reduce vibrations, and reduce noise of rotors. Analysis of available computational fluid-dynamic (CFD) predictions for MiTEs positioned upstream from the trailing edge indicates the formation and convection of an unsteady vortex in the lower surface of the airfoil, immediately following a MiTE deployment. This disturbance can introduce non-harmonic components in the aerodynamic response, substantially affecting the loads and complicating the analysis. In order to account for these effects during routine helicopter performance and design studies, available CFD results are used to develop a reduced-order, less computationally-intensive model based on indicial concepts. The model extends a work previously done for trailing-edge MiTEs by incorporating a vortex model to predict the unsteady lift of upstream MiTEs. A physicsbased approach is adopted to minimize the number of constants and improve overall generality. The results from the unsteady-lift model are compared with CFD and experiments for different airfoils, MiTE deployment schedules, MiTE chordwise positions, and Mach numbers. Very good agreement is shown for a wide range of conditions that are typical of rotorcraft.
Research on infrared light screen in obstacle detection of subway platform screen doors

Aiming at shortage of method existed in subway platform screen door(PSD)detects the minimum size of obstacles is 4 mm×40 mm when using the method of door speed curve changes a method to detect obstacles using infrared light screen is proposed,combined with DSP control technology of brushless DC motor(BLDCM)and fuzzy PID control algorithm to realize obstacle detection of subway platform screen door.Mathematical model of the whole system is constructed and simulation in Matlab/Simulink.The simulation results show that the subway platform screen door obstacles detecting system based on infrared screen can solve the shortage which existed in the existing subway platform screen door obstacles detecting system.
Technology-Scanning Capability - A Scale to Measure Firms’’ Ability to Sense or Respond to Changing Technology Landscape

A construct called technology-scanning capability has been conceptualized that measures firm’s ability to sense or respond to the changing technology landscape. The second-order reflective construct was found to have four first-order constructs named as TechInfo (i.e., information gathering about ongoing technological development), TechAlign (i.e., aligning future technology development with technology trend in the market and compatible with internal technology assets), TechRespond (i.e., responsiveness to collected technology related information) and TechExploit (i.e., exploitation of existing technology portfolio). The components provide a theoretical understanding useful to the practitioners who want to design the business processes and encourage cultures that facilitate development of stronger technology-scanning capability in their organizations.
Weed Detection using Computer Vision and Artificial Intelligence in the Raspberry Pi Platform as an Edge Device

: Retaining the balance between high productivity and quality while efficiently managing available resources is one of the biggest challenges facing the agricultural sector. As a possible so-lution to overcome these challenges and obstacles, precision agriculture has emerged in recent years. Among the promising solutions that precision agriculture offers, is the use of edge computing devices for monitoring and acquiring data in the rural environment, processing information locally and in real time. Computer Vision and Artificial Intelligence, more specifically referred to as Deep Learning, have also being applied recently in agriculture for different tasks such as image classification, object detection and semantic segmentation. However, there is a challenge and limitation in transferring this technology to more affordable platforms to process large quantities of data. Therefore, in this work, we explored the use of Computer Vision and Deep Learning applied to the object detection task in edge devices, specifically the Raspberry PI 4 platform, without hardware acceleration. We decided to apply this methodology for weed detection, since weeds are currently one of the pests that result in greatest loss of productivity in agriculture, and also have rapidly developed resistance to commercial herbicides. Also, in order to evaluate the performance gain for real-time weed detection on the Raspberry Pi platform, quantizaion of the deep neural network architectures using TensorFlow Lite was tested. The experimental results suggests that the proposed methodology is functional, and it was achieve real time weed detection on Raspberry
Trade and Technology in Soviet-Western Relations

Let's read! We will often find out this sentence everywhere. When still being a kid, mom used to order us to always read, so did the teacher. Some books are fully read in a week and we need the obligation to support reading. What about now? Do you still love reading? Is reading only for you who have obligation? Absolutely not! We here offer you a new book enPDFd trade and technology in soviet western relations to read.
Design of 70% PAE Class‐F 1.2–1.4 GHz 10 W GaN power amplifier MMIC

This letter presents a novel design of a Class‐F monolithic microwave integrated circuit (MMIC) power amplifier (PA) operating at L‐band with a power‐added‐efficiency (PAE) better than 70%. The MMIC PA is designed via load/source‐pull techniques to locate the optimal impedances at fundamental and harmonic frequencies on not only output but also input terminations. Moreover, rather than quarter wavelength stubs used in conventional designs, several parallel/series LC resonators are utilized to behave open/short at certain harmonics and to reform the drain waveform, yielding highly efficient performance of the PA MMIC. A prototype PA MMIC validating the proposed method is designed, fabricated and measured, which implemented on a 0.25 μm gallium nitride high electron mobility transistor technology. The measurement results of the PA under a drain voltage of 28 V at 1 ms pulse width with 30% duty cycle demonstrated a PAE better than 70% over 1.2–1.4 GHz with an output power greater than 40 dBm (10 W). The chip size is 2.5 mm × 3.5 mm (8.75 mm2).
Clinical Supervision Based on Spiritual Quotient to Improve the Performance of Madrasah Teachers

The research aimed to analyze the implementation of clinical supervision based on spiritual quotient in improving teachers' performance at State Madrasah Aliyah of Way Kanan Lampung. The research method used was descriptive qualitative. The informants in the research were principals, teachers, and supervisors. The data collections were observation, interviews, and documentation. Furthermore, it was analyzed through three stages: data presentation, data reduction, and data collection. The research showed that first, clinical supervision based on Spiritual Quotient had not been implemented, but ordinary supervision was often implemented. Second, clinical supervision based on Spiritual Quotient adapted to the diversity of teachers will impact self-awareness of their duties, so it was able to improve teachers' performance. The research implications for teachers were self-awareness, a strong desire to change for the better, and overcoming obstacles.
Environmental Entrepreneurial Orientation and Firm Performance: The Role of Environmental Innovation and Stakeholder Pressure

In response to the deterioration of the global environment, more and more firms are adopting eco-friendly strategies such as an environmental entrepreneurial orientation. We use the resource-based view of the firm and stakeholder theory to examine how environmental entrepreneurial orientation improves firm performance. We construct and test a moderated mediation model using survey data from 416 Chinese firms and find that environmental innovation mediates the positive effect of environmental entrepreneurial orientation on firm performance, stakeholder pressure positively moderates the influence of environmental entrepreneurial orientation on environmental innovation, and environmental entrepreneurial orientation influences firm performance through environmental innovation. This study makes theoretical contributions to the literature and provides management insights.
Fostering Social Interaction Through Sound Feedback: Sentire

Sentire is a body–machine interface that sonifies motor behaviour in real time and a participatory, interactive performance in which two people use their physical movements to collaboratively create sound while constantly being influenced by the results. Based on our informal observation that basal social behaviours emerge during Sentire performances, the present article investigates our principal hypothesis that Sentire can foster basic mechanisms underlying non-verbal social interaction. We illustrate how coordination serves as a crucial basic mechanism for social interaction, and consider how it is addressed by various therapeutic approaches, including therapeutic use of real-time auditory feedback. Then we argue that the implementation of Sentire may be fruitful in healthcare contexts and in promoting general well-being. We describe how the Sentire system has been developed further within the scope of the research project ‘Social interaction through sound feedback–Sentire’ that combines human–computer interaction, sound design and real-world research, against the background of the relationship between sound, sociality and therapy. The question concerning how interaction is facilitated through Sentire is addressed through the first results of behavioural analysis using structured observation, which allows for a quasi-quantitative sequential analysis of interactive behaviour.
A Novel Similarity-Based Link Prediction Approach for Transaction Networks

A network consists of nodes and links, which represent components of a system and interactions between them, respectively. An example of networks is transaction networks, in which nodes and links represent firms and transactions, respectively. Link prediction in transaction networks is an important problem, which aims to estimate the likelihood of a transaction between two firms. It can be used to predict missing link information between firms to gain fuller knowledge as transaction information is not easily accessible between firms. In addition, firms can use it to predict future transactions as transactions evolve over time for various reasons such as a shift in customer demand, resource availability, etc. Many link prediction methods have been proposed for networks. However, to the best of our knowledge, there is no existing link prediction method for transaction networks. Existing methods are not suitable for transaction networks as they assume homophily, the tendency of individuals to associate with similar others, which may not be true in transaction networks. In addition, they do not consider the hierarchy structure exhibited in transaction networks. In this article, we propose a new similarity score for transaction networks that account for multiple, temporal, and directed transactions. We then propose a link prediction procedure based on the proposed similarity score to predict new transactions in transaction networks, which avoids the homophily assumption and exploits the hierarchical structure of transaction networks. The proposed method is tested on real-world transaction networks and yields better area under the receiver operating characteristic curve compared to existing methods.