Miracle-dz/UniFAR-FTUs huggingface dataset:
E-Index—A Bibliometric Index of Research Efficiency

A principal investigator is obligated not only to make academic impacts but also to do so in a cost-effective fashion. While popular bibliometric measures such as the journal impact factor (IF) and the H-index measure citation-oriented bibliometric impacts, here we propose the <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-index to reflect a principal investigator’s research efficiency also in terms of bibliometric data. Our <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-index incorporates both IF-citation-based output and “total equivalent time” that the principal investigator’s team takes to deliver the output so that the bibliometric output can be normalized by the involved research time. The <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-index is then evaluated using a large set of peer-reviewed journal papers by extramurally funded Chinese principal investigators in the field of life sciences. The <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-index values are compared relative to university rank and other factors. As expected, the highest average <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-index scores were achieved by principal investigators at top national universities. Being quantitative, the <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-index adds insight into common debates such as what the optimal team size should be, which career stage is the most prolific, and so on. The <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-index should be useful in assessing principal investigators in comparable fields and longitudinally.
Research on A Technology of Automatic Assembly Based on Uncalibrated Visual Servo System

This article examines the feasibility of applying an uncalibrated visual servo system to automatic assembly in a specific environment. A series of simulation and experiments will be applied into this article, for the purpose of achieving research object. This article mainly refers to those four components: overall design of control system, design of target and its recognition and processing algorithm, design of control algorithm and computer simulation and experiment. The results demonstrates that uncalibrated visual servo system has a certain anti-jamming ability to various factors in the environment, which can meet the demand of high-tech and other special industries for automatic assembly technology.
Partial Discharge Characteristics in Pre-Breakdown Processes of Oil-Pressboard Insulation with Needle-Plate Defect Under AC-DC Combined Voltage

The PD characteristics of oil-pressboard insulation with needle-plate defect at AC-DC combined voltage are unstable. In this paper, the time-variation trends of PD characteristics in pre-breakdown process at AC-DC combined voltage are studied via the tests in oil-pressboard insulation with needle-plate defect. The average PD repetition rate and average PD amplitude decrease with the PD developing, and the time-variation trends of them can be divided into fluctuation type and monotone type. The average PD amplitude has no obvious polarity effect, the average PD repetition rate has a polarity effect. In equivalent time-frequency spectrograms, most points move towards arch top with the developing of pre-breakdown processes, where PD equivalent time is 1300–1600 ns and PD equivalent frequency is 7.5-10 MHz. PD equivalent time-frequency spectrograms can be divided into half-arched type and whole-arched type at the end of pre-breakdown processes. The defect in pressboard caused by PD is a possible reason for the appearance of whole-arched time-frequency spectrogram.
LATEST RESEARCH AT THE ADVANCED DISPLAYS LABORATORY AT NTU

There are many basic ways of providing a glasses-free 3D display and the three methods considered most likely to succeed commercially were chosen for our current research, these are; multi-layer light field, head tracked and super multiview displays. Our multi-layer light field display enables a far smaller form factor than other types, and faster algorithms along with horizontal parallax-only will considerably speed-up computation time. A spin-off of this technology is a near-eye display that provides focus cues for maximizing user comfort. Head tracked displays use liquid crystal display panels illuminated with a directional backlight to produce multiple sets of exit pupil pairs that follow the user’s eyes under the control of a head position tracker. Our super multiview display (SMV) system uses high frame-rate projectors for spatio-temporal multiplexing that give dense viewing zones with no accommodation/convergence (A/C) conflict. Bandwidth reduction is achieved by discarding redundant information at capture. The status of the latest prototypes and their performance is described; and we conclude by indicating the future directions of our research.
Conceptual Approach to the Development of Technology Evolution Network Based on Structural and Semantic Analysis

Since technology plays a key role in new product/ service development, many techniques have been developed to analyze technology evolution. Among many techniques, citation network analysis has been actively used for identifying technological trajectory. Even if there have been numerous studies to employ citation network to analyze technological evolution, it still remains a void in the literature how to differentiate each citation's role in technology evolution network. Generally, a paper or patent cites twenty to thirty references. However, most studies consider the importance of these citations as homogeneous, with less consideration on the importance of each individual citation. This can cause significant misleading for technological evolution analysis. Even if some studies tried to employ content-based citation analysis, these still remain conceptual. In response, this study suggests a new approach to analyzing technology evolution network by reflecting the role of each citation, considering both structural and semantic perspectives. For this purpose, we use natural language processing and machine learning technique to identify the importance of each citation by analyzing descriptive styles and semantic meanings. Thus, how each citation differs in terms of mediating technological knowledge flow can be measured, considering the frequency, structural position, and descriptive styles of each citation. Using different weight of each citation, a new way of network analysis is suggested to analyze technology evolution.
Larviciding Culex spp. (Diptera: Culicidae) Populations in Catch Basins and Its Impact on West Nile Virus Transmission in Urban Parks in Atlanta, GA

Abstract In urban environments, road-side catch basins are common larval habitats of Culex spp. (Diptera: Culicidae) mosquitoes and important targets of larval control in areas subject to West Nile virus (WNv) transmission. We quantified the impact of larviciding basins on Culex spp. populations and WNv infection prevalence by treating basins in and around urban parks in Atlanta, GA, using Mosquito Dunks and Bits (active ingredient, a.i., Bacillus thuringiensis subsp. isrealensis, Dunks—10.31%, Bits—2.86%) and Altosid 30-Day Briquets (a.i., S-methoprene 8.62%) in two separate seasons. Treatments were coupled with WNv surveillance using gravid traps and aspiration of adults resting in basins. Larviciding led to >90% reductions in Culex spp. larval and pupal collections (Dunks/ Bits) and >90% pupal mortality (Briquets) in treated sites during treatment periods; however, we did not observe significant reductions in Culex spp. collections in gravid traps (general linear mixed-effects model [GLMM] result, P > 0.1) or in adults collected resting in basins (GLMM, P > 0.5). In addition, WNv infection prevalence in Culex spp. mosquitoes was similar between treated and untreated sites (GLMM, P > 0.05). Larval control remains important for controlling WNv in Atlanta; however, at the scale and frequency applied in our study, larval control alone may not lead to meaningful reductions in adult populations and WNv infection prevalence. A greater understanding of the annual dynamics of Culex spp. breeding and the importance of basins as Culex spp. larval habitats are needed to meaningfully affect WNv in cities such as Atlanta.
Trajectory-Based Hand Gesture Recognition Using Kinect via Deterministic Learning

The aim of this study is to develop a new trajectory-based method for hand gesture recognition using Kinect via deterministic learning. The recognition approach consists of two stages: a training stage and a recognition stage. In the training stage, trajectory-based hand gesture features are derived from Kinect. Hand motion dynamics underlying motion patterns of different gestures which represent capital English alphabets (A-Z) are locally accurately modeled and approximated by radial basis function (RBF) neural networks. The obtained knowledge of approximated hand motion dynamics is stored in constant RBF networks. In the recognition stage, a bank of dynamical estimators is constructed for all the training patterns. Prior knowledge of hand motion dynamics represented by the constant RBF networks is embedded in the estimators. By comparing the set of estimators with a test gesture pattern to be recognized, a set of recognition errors are generated. Finally, experiments are carried out to demonstrate the recognition performance of the proposed method. By using the 2-fold and 10-fold cross-validation styles, the correct recognition rates are reported to be 93.3% and 94.7%, respectively.
Fuzzy PID Control Based on Kalman Filter in the Stabilized Platform for Stratospheric Airship

This paper research on the working quality of the payload of a stratospheric airship at high altitudes. When the stratospheric airship working on the stratosphere, it is confronted with many complicated factors. Taking the stable platform equipped with the airship as the research object, combining Kalman filter and fuzzy PID control algorithm, we propose the algorithm which named fuzzy PID control algorithm based on Kalman filter. Simulink simulation results show that the proposed algorithm not only has the advantages of fast response, small overshoot, high control precision, but also can effectively restrain the interference in the environment, which make the stratospheric airship stability.
Secure Fusion Estimation Against Eavesdroppers

This paper studies distributed secure fusion estimation problem in presence of eavesdroppers, where an eavesdropper can collect the messages from sensors to the fusion center through communication networks. To prevent eavesdropping, an insertion method of artificial noises is developed based on the fusion estimation error covariance matrix such that: i) The local/fusion estimation error covariance of the eavesdropper is unbounded; ii) The fusion estimation error covariance of the defender is bounded. Moreover, a sufficient condition is derived to guarantee the effective noise insertion strategy. Simulations are given to show the effectiveness of the proposed methods.
Cooperative Behavior of Networked Harmonic Oscillators with Delayed Sampled Position States

This paper investigates the impulsive cooperative behaviors of networked harmonic oscillators by using sampled position states only. A distributed effective algorithm is proposed based on delayed sampled position states over both directed and undirected network topologies. Some necessary and sufficient conditions are established by using the graph theory, ordinary differential equations theory and Schur-Cohn stability criterion. Theoretical results show that the harmonic oscillators can be synchronized if the sampling period fall in an appropriate open interval. Finally, simulations further verify the effectiveness of the theoretical results.
Recategorizing Interdisciplinary Articles using Natural Language Processing and Machine/Deep Learning

Interdisciplinarity has become popular due to the novel approaches in academic research and papers as well as solutions to various social problems. Thus, research into interdisciplinary research itself and into interdisciplinarity has also become popular. However, it is difficult to identify a research discipline precisely, which is necessary for the evaluation of ‘interdisciplinarity. ’ For example, in general, research disciplines are categorized in accordance with the journals that cater to them. Thus, an important multidisciplinary science journal, such as Nature or Science, does not belong to the category of "general research disciplines. " Hence, a new category of "multidisciplinary science" is required for the fundamental evaluation of interdisciplinarity. " In this research, a new method of classification is conducted by analyzing the abstracts of research papers using machine learning and deep learning. All the data used is gathered from Web of Science (PY: 2016). The new classifier identifies research disciplines including "multidisciplinary science," in contrast to other current methodology.
Process Development and Failure Analysis for Chip-Last Panel Level Fan-out Packaging (PLP)

Nowadays, fan-out package is regarded as one of the most potential packaging technologies because of its thinner profile, lower cost, better thermal and electrical performance. However, there are still challenges for manufacturing process including precise alignment of die bonding and large warpage of the molded wafer/panel, etc. In this study, a novel 320mm×320mm panel level fan-out package based on die last process is developed. The challenges of this process technology, such as die jumping, die shift, delamination and warpage are studied, corresponding failure analysis was conducted accordingly. It is found that large warpage of the substrate and voids or bubbles (without proper taping by using vacuum methods) during reflow process are the main issues and may induce delamination of the substrate and FR4 carrier, and cause die jumping and non-wetting of solders. And die shift is also found to be a critical issue due to the limitation of die attachment precision. Therefore, reducing warpage of substrate, minimizing the trapped voids and bubbles and improving die bond accuracy are major solutions for achieving high yield and high quality of chip last processing during panel level packaging (PLP).
A Memetic Algorithm Approach to Deploy RSU s Based on the Gamma Deployment Metric

Vehicular ad hoc networks (VANETs) are considered a practical application of mobile and ad hoc networks. They have potential to ease traffic management, lower accident rates, and they are essential to autonomous vehicles. In this work, we propose a Memetic Algorithm, called Gamma-LSGA, for solving the allocation of roadside units (RSUs) in VANETs. The Gamma-LSGA algorithm uses two hill climbing-based heuristics. To assure quality of service, we use a metric called Gamma Deployment. That metric is based on two aspects: (i) the intercontact time between vehicles and RSUs and (ii) the percentage of vehicles fulfilling such inter-contact time. We run experiments using a mobility trace from the city of Cologne, Germany, and compared our results with the ones delivered by the deterministic heuristic Gamma-G, previously proposed. For almost all comparison cases, the memetic approach provided results with fewer RSUs than Gamma-G, with gains up to 32.7%.
Knowledge discovery out of text data: a systematic review via text mining

Purpose The aim of this work is to increase awareness of the potential of the technique of text mining to discover knowledge and further promote research collaboration between knowledge management and the information technology communities. Since its emergence, text mining has involved multidisciplinary studies, focused primarily on database technology, Web-based collaborative writing, text analysis, machine learning and knowledge discovery. However, owing to the large amount of research in this field, it is becoming increasingly difficult to identify existing studies and therefore suggest new topics. Design/methodology/approach This article offers a systematic review of 85 academic outputs (articles and books) focused on knowledge discovery derived from the text mining technique. The systematic review is conducted by applying “text mining at the term level, in which knowledge discovery takes place on a more focused collection of words and phrases that are extracted from and label each document” (Feldman et al., 1998, p. 1). Findings The results revealed that the keywords extracted to be associated with the main labels, id est, knowledge discovery and text mining, can be categorized in two periods: from 1998 to 2009, the term knowledge and text were always used. From 2010 to 2017 in addition to these terms, sentiment analysis, review manipulation, microblogging data and knowledgeable users were the other terms frequently used. Besides this, it is possible to notice the technical, engineering nature of each term present in the first decade. Whereas, a diverse range of fields such as business, marketing and finance emerged from 2010 to 2017 owing to a greater interest in the online environment. Originality/value This is a first comprehensive systematic review on knowledge discovery and text mining through the use of a text mining technique at term level, which offers to reduce redundant research and to avoid the possibility of missing relevant publications.
Representation of Horizontal Transport Processes in Snowmelt Modeling by Applying a Footprint Approach

The energy balance of an alpine snow cover significantly changes once the snow cover gets patchy. The local advection of warm air causes above-average snow ablation rates at the upwind edge of the snow patch. As lateral transport processes are typically not considered in models describing surface exchange, e.g. for hydrological or meteorological applications, small-scale variations in snow ablation rates are not resolved. The overall model error in the hydrological model Alpine3D is split into a contribution from the pure “leading edge effect” and a contribution from an increase in the mean air temperature due to a positive snow-albedo feedback mechanism. We found an overall model error for the entire ablation period of 4 % for the almost flat alpine test site Gletschboden and 14 % for the Wannengrat area, which is located in highly complex terrain including slopes of different aspects. Terrestrial laser scanning measurements at the Gletschboden test site were used to estimate the pure “leading edge effect” and reveal an increase in snow ablation rates of 25-30 % at the upwind edge of a snow patch and a total of 4-6 % on a catchment scale for two different ablation days with a snow cover fraction lower than 50 %. The estimated increase of local snow ablation rates is then around 1-3 % for an entire ablation period for the Gletschboden test site and approximately 4 % for the Wannengrat test site. Our results show that the contribution of lateral heat advection is smaller than typical uncertainties in snow melt modelling due to uncertainties in boundary layer parameters but increases in regions with smaller snow patch sizes and long-lasting patchy snow covers in the ablation period. We introduce a new temperature footprint approach, which reproduces a 15 % increase of snow ablation rates at the upwind edge of the snow patch, whereas observations indicate that this value is as large as 25 %. This conceptual model approach could be used in hydrological models. In addition to improved snow ablation rates, the footprint model better represents snow mask maps and turbulent sensible heat fluxes from eddy-covariance measurements.
A Vision-Based Robotic Grasping Approach under the Disturbance of Obstacles

This paper presents a vision-based robotic grasping approach with complex obstacles environments. A deep learning-based object detection algorithm is used to detect object in the image and obtain the object's category and position. Then the Euclidean cluster extraction algorithm is adopted to segment scenes composed of 3D point clouds to obtain the positions and size of obstacles. According to the acquired information of the object and obstacles, one can judge whether the object can be directly grasped. If there is no direct solution, the obstacles that interfere with the grasping shall be firstly moved to other positions, then the object is grasped. These new positions of interference obstacles are selected based on artificial potential field. The experimental results on the Kinova MICO2 arm demonstrate that the approach can effectively achieve the grasping of target object even with severe interference from obstacles.
Ship Model Recognition Based on Convolutional Neural Networks

Due to its advantages, the deep convolutional neural network has achieved good results in the field of target recognition and classification. It provides new approaches and methods for ship target recognition. Since the training of convolutional neural networks requires a large amount of data and high-performance hardware support, this paper proposes an efficient training scheme for convolutional neural networks training on the small capacity of ship data sets. The effectiveness of the scheme is verified through experiments, and the accuracy is improved. It can reach 99%. Finally, the feature map of convolutional neural network is analyzed, which further proves that the proposed scheme is effective.
Pose Optimization of a Single Ball Self-Balancing Mobile Robot Based on IMU and Visual Fusion

The single ball self-balancing mobile robot is a typical multivariable, high-order, nonlinear and static instability system, IMU inertial devices are generally used to obtain attitude parameters of the system. The data errors obtained by the inertial devices will accumulate over time, and the long-term pose estimation is rather unreliable. But for some quick motion over a short period of time, inertial sensors can get very accurate estimates. Monocular cameras are often used as image real-time monitoring sensors by single ball self-balancing mobile robots. The camera's data does not accumulate errors over time, so there is essentially no drift. Therefore, camera pose estimation can effectively correct the inertial sensor error. In a fast-moving environment, the shutter-roller camera cannot capture the image clearly and there may be ghosting or overlapping of two areas too little, resulting in mismatched or unmatched conditions. So that the robot makes a wrong estimate. In this paper, the non-linear optimization method is used to fuse the IMU and monocular attitude data to obtain the optimal pose estimation of the robot. Based on the modeling of robot using Lagrange's equation method, the control of single ball robot is realized by using fuzzy PID algorithm. Experiments show that this scheme can respond quickly to the change of the attitude of the ball self-balancing robot and keep the attitude of the robot relatively stationary, so that the robot can move steadily.
Relationship Between Hip Morphology and Hip‐Related Patient‐Reported Outcomes in Young and Middle‐Aged Individuals: A Population‐Based Study

Radiographic measurements of the alpha angle and the lateral center edge (LCE) angle in the hip joint are important for the diagnosis of femoroacetabular syndrome, a potential risk factor for hip osteoarthritis. Our objective was to determine whether these measurements are associated with hip‐related patient‐reported outcomes in young and middle‐aged individuals.