Miracle-dz/UniFAR-FTUs huggingface dataset:
A Human-Vehicle Collaborative Driving Framework for Driver Assistance

With a goal to improve transportation safety, this paper proposes a collaborative driving framework based on assessments of both internal and external risks involved in vehicle driving. The internal risk analysis includes driver drowsiness detection and driver intention recognition that helps to understand the human driver’s behavior. Steering wheel data and facial expression are used to detect the driver’s drowsiness. Hidden Markov models are adapted to recognize the driver’s intention using the vehicle’s lane position, control, and state data. For the external risk analysis, a co-pilot utilizes a collision avoidance system to estimate the collision probability between the ego vehicle and other nearby vehicles. Based on the risk analyses, we design a novel collaborative driving scheme by fusing the control inputs from the human driver and the co-pilot to obtain the final control input for the ego vehicle under different circumstances. The proposed collaborative driving framework is validated in an assisted-driving testbed, which enables both autonomous and manual driving capabilities.
The Field of Ambidexterity Research: Perspective from Information Systems Domain

The study of ambidexterity continues to attract attention from scholars across multiple business domains. This has contributed to several reviews of the ambidexterity field being conducted and reported in the recent past. This article builds on the existing reviews and takes stock of the ambidexterity research, with a focus on Information Systems (IS) domain. Furthermore, this systematic review takes a unified perspective of the field and addresses some of the ongoing debates about the conceptualisation of the ambidexterity construct, trade-offs being addressed as well as its relevance and applicability for IS research.
Getting Consumers to Pay for Content: the Role of Value Discrepancy in Freemium Models

“Freemium” revenue models enable media companies to attract potential customers with restricted, but freely available, product versions while charging for premium versions. Whereas some companies have established viable businesses with this model, others, specifically news content providers, still struggle to convert free users into paying customers. The value discrepancy between the free and the premium versions is a major driver of users’ conversion decisions. Nevertheless, IS research lacks in understanding, how freemium design influences the value discrepancy when users are familiar with the product. News content providers create value discrepancy by means of digital paywalls, configuring quantity restriction, choice restriction, advertising, and price. In this study, we conduct a discrete choice exper-iment, in which consumers face decisions when comparing their status quo (a free version) with a sub-scription offer (a premium version). Our results reveal that decreasing the free version’s value and increasing the premium version’s value has a positive effect on conversion intentions. While restricting the quantity is only effective if more content is available, restricting the choice relatively increases in effectiveness if less content is available. Additionally, we find indications that combining a price of zero with a less severe quantity restriction could trigger an irrational zero-price effect.
Research on Automatic Archiving and CD-ROM Burning System of Massive Electronic Documents

According to the feature of huge data, massive files and complex handling in massive e-documents archiving, an auto archiving and burning system is developed. The multi-mission parallel mechanism based on multi-thread pipeline would solute the problem of resource competition by taking full advantage of multi-core processor, arithmetic unit and the I/O interface. It would shorten the time cost of classifying, compressing the files, generating disc data and burning disc, and thus improve the processing effectiveness of the massive E-documents archiving. The MD5 technology is used to guarantee the file security. A hierarchical structure is used to the database inquiry design to improve performance on data access. The blue-ray technology is used to accelerate the burning speed. A management system is developed to handle the process of disc archiving, accessing and inquiry. A disaster recovery system is used to solve the problem of invalid hard disc storage and database. A remote monitoring system is used to monitor the arching process in real-time. The whole system is running for more than one year and received high appraise. Keywords—massive electronic documents; automatic archiving; CD-ROM burning; multi-thread pipeline
Control strategy of an electrically actuated morphing flap for the next generation green regional aircraft

The design and application of adaptive devices are currently ambitious targets in the field of aviation research addressed at new generation aircraft. The development of intelligent structures involves aspects of multidisciplinary nature: the combination of compact architectures, embedded electrical systems and smart materials, allows for developing a highly innovative device. The paper aims to present the control system design of an innovative morphing flap tailored for the next generation regional aircraft, within Clean Sky 2 – Airgreen 2 European Research Scenario. A distributed system of electromechanical actuators (EMAs) has been sized to enable up to three operating modes of a structure arranged in four blocks along the chord-wise direction: •overall camber-morphing; •upwards/downwards deflection and twisting of the final tip segment. A state-of-art feedback logic based on a decentralized control strategy for shape control is outlined, including the results of dynamic stability analysis based on the blocks rational schematization within Matlab/Simulink® environment. Such study has been performed implementing a state-space model, considering also design parameters as the torsional stiffness and damping of the actuation chain. The design process is flowing towards an increasingly “robotized” system, which can be externally controlled to perform certain operations. Future developments will be the control laws implementation as well as the functionality test on a real flap prototype.
A self‐diplexing MIMO antenna for WLAN applications

This letter presents a slot‐based self‐diplexing MIMO (multiple‐input multiple‐output) antenna for dual‐band operation. In the first step, a self‐diplexing antenna is designed with two microstrip fed quarter wavelength slot‐antenna elements. Next, this self‐diplexing antenna is replicated to obtain the characteristics of a MIMO antenna. The designed self‐diplexing MIMO antenna with optimized dimensions operates at 5.1 GHz and 5.7 GHz. The peak gains obtained at two frequencies are 2.02 dBi and 2.96 dBi. Minimum isolation at both the operating bands is better than 15 dB. The proposed antenna offers a frequency ratio of 1‐1.62.
Optimal Collision-Free Grip Planning for Biped Climbing Robots in Complex Truss Environment

Biped climbing robots (BiCRs) can overcome obstacles and perform transition easily thanks to their superior flexibility. However, to move in a complex truss environment, grips from the original point to the destination, as a sequence of anchor points along the route, are indispensable. In this paper, a grip planning method is presented for BiCRs generating optimal collision-free grip sequences, as a continuation of our previous work on global path planning. A mathematic model is firstly built up for computing the operational regions for negotiating obstacle members. Then a grip optimization model is proposed to determine the grips within each operational region for transition or for obstacle negotiation. This model ensures the total number of required climbing steps is minimized and the transition grips are with good manipulability. Lastly, the entire grip sequence satisfying the robot kinematic constraint is generated by a gait interpreter. Simulations are conducted with our self-developed biped climbing robot (Climbot), to verify the effectiveness and efficiency of the proposed methodology.
Design of a Novel Dual-Axis Micromanipulator With an Asymmetric Compliant Structure

This paper presents a novel piezoelectrically actuated dual-axis micromanipulator with an asymmetric compliant structure. The mechanical design of the micromanipulator is first presented. A novel guiding bridge-type mechanism was proposed and utilized in the left part of the micromanipulator to improve the dynamic performance of the micromanipulator. The analytical model has been established based on the pseudorigid-body model and matrix-based compliance modeling method. The kinematic and the precision of the micromanipulator have been analyzed, and the input and output couplings have been investigated. The prototype of the micromanipulator has been fabricated by wire electrodischarge machining. Then, open-loop experimental tests have been performed. The experimental results match well with the analytical calculation, and the amplification ratios are 11.12 and 4.64 for the left part and right part, respectively. Proportional-integral controller has been used to regulate the output displacement and grasping force, and a series of closed-loop experiments have been conducted to investigate the performance of the micromanipulator. The results show that the position resolution for both the right and left parts is 0.15 μm, and the force resolution is 4 mN.
Novel ink for ambient condition printing of liquid crystal elastomers for 4D printing

Structures capable of reversible shape changes directly after 3D printing are highly desirable for myriad of applications ranging from soft robotics to implantable medical devices. Liquid crystal elastomers (LCEs) have been studied for their large, reversible mechanical actuations in response to temperature. Recently, several efforts were carried out to direct ink write (DIW) 3D print LCE, however, these methods require high temperatures for printing and actuation. Here, we present a novel LCE ink formulation which allows LCE to be printed at room temperature with a maximum actuation temperature of 75 °C. These advantages allow the 3D printed LCEs to be integrated with other 3D printing methods and materials to create more complex shape changes. By 3D printing LCE and conductive wires, which provide Joule heating, we demonstrated an active hinge, a reversibly opening and closing box, a soft robotic gripper for pick and place, and a printed hand for sign language.
Increasing Cyber Resiliency of Industrial Control Systems

Industrial control systems (ICS) are designed to be resilient, capable of recovering from process faults and failures with limited impact to operations. Current ICS resiliency strategies use redundant PLCs. However, these redundant PLCs, being of similar make and model, can be exploited by the same cyber attack, defeating the ICS’s resiliency strategy. This research proposes a resiliency strategy for ICS that employs an active defense technique to remove the cyber common cause failure. The resiliency of the active defense strategy is compared to traditional ICS resiliency by implementing both strategies in a semi-simulated wastewater treatment plant aeration basin that experiences a cyber attack. The active defense technique was shown to maintain effective treatment of the wastewater through the cyber attack where the traditional implementation allowed a process disruption that prevented the effective treatment of the wastewater.
Characterization of Piezoelectric Material Parameters Through a Global Optimization Algorithm

Better understanding of the loss mechanisms and higher confidence in material data for piezoelectric materials are very important for transducer manufacturers. In this paper, a method is described to characterize these loss mechanisms using a global optimization algorithm, a 1-D equivalent circuit, and a simple experimental measurement. Two different cost functions were used in the optimization algorithm, one based on impedance and the other based on admittance. The sensitivities of these cost functions to the parameters being characterized are shown to be nonuniform. The results are compared to the results obtained from a local optimization method to show the advantage of using a global optimization algorithm. A way to quantify the uncertainty of the results is introduced by looking at the difference between the results obtained from the two different cost functions. It is shown here that the more ambient noise there is in the data, the wider the gap between the results found by the two cost functions. However, although the results from the individual cost functions diverge from the correct values with increasing noise, the average of the two cost function results remains within $5\%$ of the original value. Hence, even with noise in the measured data, the use of two cost functions can yield accurate material parameters.
On the validity of plane state assumptions in the bending of bimorph piezoelectric cantilevers

We assess the accuracy of plane state assumptions in modeling the bending of bimorph piezoelectric cantilevers. Reference solutions are obtained by means of fully three-dimensional simulations. We solve a model, compliant with the standard theoretical background, able to deal with large deflections, and aimed at estimating the electrical energy harvesting potential. We show that the two assumptions of plane stress and plane strain yield very different results in terms of strain and therefore lead to substantially different estimates of electrical power. The plane stress state is the best approximation of narrow cantilevers, while the plane strain is suited for wide ones. The validity ranges are defined for each of the two, in terms of the generated electrical power. More specifically, the plane stress assumption better approximates the reference solution in the range W / H < 10 . By contrast, the plane strain condition yields results closer to three-dimensional solution for ratios W / H > 10 3 with W the width and H the total thickness of the solid. Other aspects are affected by the modeling approach, such as the estimation of maximum deformation and, to a minor extent, of resonance frequencies.
Research on Gas Concentration Prediction Models Based on LSTM Multidimensional Time Series

Effective prediction of gas concentrations and reasonable development of corresponding safety measures have important guiding significance for improving coal mine safety management. In order to improve the accuracy of gas concentration prediction and enhance the applicability of the model, this paper proposes a long short-term memory (LSTM) cyclic neural network prediction method based on actual coal mine production monitoring data to select gas concentration time series with larger samples and longer time spans, including model structural design, model training, model prediction, and model optimization to implement the prediction algorithm. By using the minimum objective function as the optimization goal, the Adam optimization algorithm is used to continuously update the weight of the neural network, and the network layer and batch size are tuned to select the optimal one. The number of layers and batch size are used as parameters of the coal mine gas concentration prediction model. Finally, the optimized LSTM prediction model is called to predict the gas concentration in the next time period. The experiment proves the following: The LSTM gas concentration prediction model uses large data volume sample prediction, more accurate than the bidirectional recurrent neural network (BidirectionRNN) model and the gated recurrent unit (GRU) model. The average mean square error of the prediction model can be reduced to 0.003 and the predicted mean square error can be reduced to 0.015, which has higher reliability in gas concentration time series prediction. The prediction error range is 0.0005–0.04, which has better robustness in gas concentration time series prediction. When predicting the trend of gas concentration time series, the gas concentration at the time inflection point can be better predicted and the mean square error at the inflection point can be reduced to 0.014, which has higher applicability in gas concentration time series prediction.
The Development of Collaborative Jig Saw ProjectBasedLearning Model to Improve Students’ Learning Outcomes in Thermodynamics on Vocational College

This paper describes the development steps of The Collaborative Jig Saw Project-Based Learning (CJPjBL) Model in thermodynamics on vocational college. The development of the CJPjBL model applies five steps of the ADDIE model ie: 1) analyzing current thermodynamics learning model, 2) designing the new learning model, 3) developing model and internal validation, 4) implementing CJPjBL model, and 5) comparing achievement of students learning outcomes using CJPjBL model to conventional model. The product of this research was the results of a learning model with nine syntaxes in thermodynamics through validity, practicality and effectiveness test. Expert validity test results on the construction and content of the CJPJBL model with Aiken V were 0.863 and 0.84. The practicality test results by lecturers and students were 83,67 and 80,94 in very practical category. The results of effectiveness test through t-test on student learning outcomes using CJPjBL and conventional model showed significant differences. The means value of student learning outcomes using the CJPjBL and conventional models at the end of the lecture were 88.28 and 74.80. In conclusion, this study showed that the CJPjBL model was valid, highly practical and more effectively used in thermodynamics' course in vocational college.
Decoupling the aliased spectra of rolling bearing with multispeed multiple frequency correlation

A multispeed multiple frequency correlation method for decoupling aliased spectra when defect frequencies are approximate to integral multiple of the shaft speed is proposed for fault diagnosis of rolling bearing. Firstly, multiple frequencies at various shaft rotation speeds are obtained using the fast Fourier transform (FFT). Secondly, the correlation coefficients between the amplitude growth trend of the multiple frequencies and the expected trend are calculated. Thirdly, correlation coefficients of assumed inner and outer race fault multiple frequencies are acquired by averaging correlation coefficients of possible aliased multiple frequencies for each bearing failure state. Finally, the correlation coefficient curves of different assumed fault multiple frequencies are compared, enabling operational assessment of the rolling bearing. The experimental results show that the multispeed multiple frequency correlation method is an effective tool for decoupling aliased spectra and diagnosing bearing faults.
Collaboration in Design Research: An Analysis of Co-Authorship in 13 Design Research Journals, 2000–2015

Abstract This paper utilizes social network analysis and multivariate statistical methods to quantitatively analyse co-authorship patterns between 2000 and 2015 in 13 influential design research journals. The results indicate that the importance and propensity of co-authorship is expanding in design research. Furthermore, the impact of an article, measured by year-adjusted citation counts, is significantly greater when it is co-authored. The structure of the co-authorship network is mostly comprised of small yet unconnected groups of authors, who seldom collaborate beyond a single article.
Channel correlation-based relay attack avoidance in vehicle keyless-entry systems

In passive keyless entry and start (PKES) systems, the car unlocks or starts the car when the key is in the proximity of the car. In conventional PKES systems, the car determines the physical proximity of the key on the basis of the received signal strength or the round-trip time (RTT). However, the conventional schemes are vulnerable to relay attacks because the relay amplifies the signal and minimises the processing time. A solution to avoid the relay attacks in PKES systems is proposed, where the car verifies the proximity of the key on the basis of the correlation of the channel state information as well as the RTT.
Electric transmission infraestructure implementation process in Paraguay

The implementation process of infrastructure works in the electric power transmission system of Paraguay has been described in this work, analyzing its various stages and the interrelationships between them, considering the specificities inherent to the national electricity sector, constituted mainly by a vertically integrated monopolistic state company. The works implementation process determines the conditions of availability of electric power in quality and quantity adequate to sustain the socioeconomic development of the country, constituting a complex phenomenon that is related to several systems, sectors and agents, being able to mention, among others, the public procurement system, the political system, the economic system, the financial administration system of the state, the socio-environmental system, etc. Thus, the approach adopted was qualitative, descriptive in scope, with bibliographic research and interviewing key informants as the main tools for data collection. The integral description of the process has allowed us to know and interpret the various phases of the process, the interrelationships and dependencies, the restrictions, the associated times and the main actors involved, among other relevant characteristics of the process. This knowledge reasonably enables one modeling infrastructure works in the electric power transmission system of Paraguay implementation process, paving the way for the introduction of improvements in it, and the simulation of scenarios that allow verifying the impact of proposed alternatives in the different stages of process management.
Increasing Productivity– a Way to Improve Efficiency of Operational Management in Hard Coal Mines

The article contains considerations on possible actions directed at increasing productivity of hard coal mining industry. It is necessary to improve the state of the industry, and ensure its survival. Basic definitions and measures concerning productivity and management were presented to illustrate examples referring to a mining enterprise. Then, basing on organizing, one of the management functions, the issue of productivity in a mining enterprise and its influence on improving effectiveness of operational management, was analysed. An assumption was presented that solutions concerning identification of sources and volume of costs, hitherto existing in mining enterprises, ought to be complemented with the planning function following process approach. It can be the starting point for decisions of economic feasibility of given deposits, seams or parts of them, before mining operations start, and to control incurred costs in process approach. The article is summed up with a process algorithm of cost management.