Miracle-dz/UniFAR-FTUs huggingface dataset:
Separating content and structure in humor appreciation : The need for a bimodal model and support from research into aesthetics

For a long time humor theorists have acknowledged that content and structure of humor (or: joke work vs. tendency, [4]; thematic vs. schematic, [12]; cognitive vs. orectic factors, [3]) have to be distinguished as two different sources of pleasure [6]. Nevertheless, against all evidence, taxonomies of humor are stuck in (serial) unimodal classifications rather than bior multimodal models. Intuitive classifications of humor typically distinguish between content classes (e.g., blonde jokes, dead baby jokes, Stalin jokes), neglecting the contributions of structural properties to appreciation of humor. Also rational taxonomies most frequently emphasize content features; e.g., when emotional features like disgust, fear or anger are highlighted in humor. Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-67033 Book Section Originally published at: Ruch, Willibald; Platt, Tracey (2012). Separating content and structure in humor appreciation: The need for a bimodal model and support from research into aesthetics. In: Nijholt, Anton. Computational humor 2012: extended abstracts of the (3rd international) workshop on computational humor. Enschede: Centre for Telematics and Information Technology <Enschede>, 23-28. Computational Humor 2012 EXTENDED ABSTRACTS OF THE (3 INTERNATIONAL) WORKSHOP ON COMPUTATIONAL HUMOR Amsterdam, June 8, 2012
Uncertainty mitigation in drone-based 3D scanning of defects in concrete structures

The measurement of defects in a concrete structures is highly relevant to determine how maintenance interventions should be performed. However, it could be difficult and potentially dangerous to inspect a certain structure by bringing trained operators, to places that are difficult to access. This issue could be overcome by framing the parts of interest of a building with a drone equipped with cameras. Nonetheless, a quantitative measure of a defect cannot be obtained with 2D cameras, since the pixel to millimeters scale and the estimation of depth are missing. To obtain a 3D shape measurement of a defect, 3D scanners, joined with 3D reconstruction, could be applied. In this article, we present a metrological evaluation of low-cost Time-Of-Flight (ToF) sensors for defects in concrete structures measurement. The defects of interest for this class of 3D scanners are mainly related to concrete spalling. This type of scanners was assembled on a drone with an onboard acquisition system. The testing benchmark for this study is based on a real structure with concrete spalling defects. A ground truth 3D model was obtained with a high-precision 3D scanner, used with a scaffolding. The effect of disturbances on measures were investigated, as well. The results of drone tests show that the systematic error of the 3D reconstruction with the selected sensors is about 0.5-2 mm, with a dispersion of raw data around the 3D reconstruction of about 2-4.5 mm, at a distance from the target of about 1.8-2 m.
Over-Speed and License Plate Detection of Vehicles

With the swift expansion of the global economy, cities in various nations may face day to day problems like road congestion, frequent accidents, deterioration of the traffic conditions, or other urban traffic concerns. Vehicle detection technology based on video can collect a wealth of information from video frame sequences, such as vehicle speed, vehicle type, and vehicle number plate, at a cheap cost and with great efficiency. These electronic technologies are not only useful in people’s daily lives, but they also provide management with safe and efficient services. If we solely rely on human resources, such as law enforcement officers, we may face numerous issues, including high costs and low efficiency. We have built an integrated system for speed and license plate detection of vehicles. In the method presented here, the vehicle is first segmented and extracted from a video feed, using YOLOv5 algorithm. Next, the speed of the car is calculated using a simple algorithm and then the license plate snapshots are detected. Finally, optical character recognition is applied on the license plate image. This paper presents a thorough analysis of the cutting-edge approaches for detecting and recognising vehicles, their speeds and number plates.
EMC Implications of Implementing WBG Devices in Battery Charger Modules for Electric Vehicles

GaN and SiC semiconductor devices have the potential of drastic downsizing of power converters in applications where size is strictly limited like in electromobility. In electric powertrains, on-board chargers need to operate in a wide voltage and power range limited by the battery and its conditions. In this context, both size and voltage-power range can be achieved through the effective utilization of GaN and SiC devices. Nevertheless, although GaN and SiC devices offer outstanding features in fast transitions, low on-resistances, and the ability to switch faster, these characteristics can generate much higher EM emissions that can affect the charger operation. Consequently, additional circuitry is required to mitigate such emissions although it can jeopardize the ultimate goal of compactness. In this paper, trasients, ringing, harmonic content, and conducted emissions in both GaN and SiC Devices and use of magnetic components is analyzed. Such analysis is conducted with experimental tests under real conditions of battery charging for Electric Vehicles.
Analyzing and Comparing Public Perception of Facial Recognition, Iris Verification and Fingerprints Based Authentication Systems

When it comes to everyday living, biometric devices play an important part. It is, therefore, imperative to evaluate usability and vulnerability of biometric technologies. In Oct. 2021, UAE implemented facial recognition based authentication system in the public transportation sector to boost security, and public service delivery. The usage of facial recognition technology has sparked worries about biometric data security and privacy worldwide, and in many instances, has been even withdrawn. Further, there is a research gap on public perception of biometric technologies (iris identification, fingerprints, and facial recognition) and how it can affect the widespread adoption of technology. Our survey data, analyzed through comparative statistical model in SPSS, confirmed that public transport users have a low perception of facial recognition technology, compared to iris recognition and fingerprints authentication in UAE. Hence, it is argued that widespread adoption of technology can suffer a setback in the long run due to publicity effect. The study findings will not only support the widespread adoption of biometric technologies, but also provide unique insights to usability experts into the perceptions and understanding of biometrics, as well as areas where users may lack knowledge on biometric applications.
Mining Smart Meter Data: Opportunities and Challenges

Metering side of electricity distribution system has been one of the prime focus of industry and academia both. The most recent advancement in this field is installation of smart meters. The installation of smart meters enables collection of massive amounts of data regarding electricity generation and consumption. The analysis of this data could help generate actionable insights for the supply side and provide the consumers demand management-related inputs. The problem addressed in this chapter is to identify suitable data mining algorithm for applications like: estimating the demand and supply of electricity, user and use profiling of commercial, and industrial customers, and variables suitable for these purposes. This chapter, on the basis of rigorous literature review, presents a taxonomy of smart meter data mining. It includes the summary of application of smart meter data analytics, characteristics of dataset used, and smart meter business globally. This chapter could help researchers identify potential research opportunities, and practitioners can use it for planning and designing a smart electricity system. Mining Smart Meter Data: Opportunities and Challenges
Paving the Way to a Software-Supported Requirements Prioritization in Distributed Scrum Projects

Both, agile software development (e.g., Scrum) and the geographical distribution of project stakeholders have gained increasing significance in recent years. Establishing agile methods in distributed software development projects challenges science and practice as the characteristics of agile software development are not compatible with distributed project environments. Especially the task of requirements prioritization that incorporates a significant role in Scrum and that requires high communication and collaboration between stakeholders lacks an extensive software-supported methodology. This research-in-progress paper presents the first three steps of a design science research project. Based on an initial literature review combined with expert interviews addressing two software companies, the paper presents issues, requirements, and solution characteristics. Finally, it proposes a solution concept in form of a process model. These artifacts offer a solid foundation for further research, especially instantiating and evaluating the concept using a functional software prototype.CCS CONCEPTS• Software and its engineering → Software creation and management; • Information systems;
Internal Reference Compensation Technique for Constant On-time Buck Converter with Ceramic Capacitor

A ripple-based constant on-time (COT) buck converter with an additional current feedback path (ACFP) technique can relax the need of large equivalent series resistance (ESR) at the output capacitor. However, output regulation accuracy is degraded due to the output dc offset. Thus, this paper proposes an internal reference compensation (IRC) technique to enhance converter stability with ceramic capacitor while removing the load-dependent dc offset voltage on the output voltage. A test chip fabricated in 0.35-μm CMOS technology has demonstrated the validation of IRC technique. The experimental results show that the output voltage ripple is 3 mV and output dc offset can be eliminated while the transient recovery time is 4μs for load current change of 450 mA,
Three-Dimensional Axotomy and Regeneration on Open-Access Microfluidic Platform

An increasing number of patients are suffering from central nervous system (CNS) injury, including spinal cord injury. However, no suitable treatment is available for such patients as yet. Various platforms have been utilized to recapitulate CNS injuries. However, animal models and in vitro two-dimensional (2D)-based cell culture platforms have limitations, such as genetic heterogeneity and loss of the neural-circuit ultrastructure. To overcome these limitations, we developed a method for performing axotomy on an open-access three-dimensional (3D) neuron-culture platform. In this platform, the 3D alignment of axons in the brain tissue was recapitulated. For direct access to the cultured axons, the bottom of the 3D neuron-culture device was disassembled, enabling exposure of the neuron-laden Matrigel to the outside. The mechanical damage to the axons was recapitulated by puncturing the neuron-laden Matrigel using a pin. Thus, precise axotomy of three-dimensionally aligned axons could be performed. Furthermore, it was possible to fill the punctuated area by re-injecting Matrigel. Consequently, neurites regenerated into re-injected Matrigel. Moreover, it was confirmed that astrocytes can be co-cultured on this open-access platform without interfering with the axon alignment. The proposed open-access platform is expected to be useful for developing treatment techniques for CNS injuries.
Lossy Flange for Open-Ended Rectangular Waveguide Materials Characterization

Open-ended rectangular waveguides are widely used for near-field measurements and in particular for microwave nondestructive testing (NDT) applications pertaining to materials characterization. This method is capable of simultaneously evaluating the thickness and material properties of various layers within multi-layer dielectric structures and composites. After collecting measurement data, a full-wave electromagnetic model is used to calculate the estimated properties of the structure. One of the electromagnetic constraints considered by the model (i.e., an infinite flange) is practically satisfied using an engineered flange. However, the engineered flange has certain limitations when dealing with certain layered structures, namely; those that are conductor-backed and electrically thin. In such cases where the measured response cannot be replicated by the electromagnetic model, there is significant error in thickness and material property estimation. This work presents the use of a lossy dielectric material as an engineered flange cover for performing open-ended rectangular waveguide measurements specifically for use on such structures through the use of a lossy flange cover. The performance of the engineered flange with and without a lossy flange cover are compared through electromagnetic simulation and measurement of thin and conductor-backed structures.
A Practical Approach to Mitigate the Harmonic Distorsion in a Microgrid, Case Study

The actual study proposes a power quality analysis of a medium-sized industrial microgrid which in turn generates harmonic disturbances on the medium voltage side of a 110kV/20kV substation. Due to the interconnection of different loads on similar medium voltage busbars, the harmonic distortion propagates along the circuit affecting the stability of the local grid. Using advanced simulation tools based on numerical analysis an equivalent circuit of the microgrid is created. According to the computed results levels of total harmonic distortion exceeding the limit values imposed by the national performance standards were discovered within the load understudy. In this regard, a complex analysis procedure targeting the variable speed drives is deployed in order to identify the proper technical solutions for attenuation and filtering of harmonics in the system. Therefore, this study highlights solutions for mitigating the higher-order harmonics and the impact of their implementation, i.e. the best solution.
Influence of Dead-Time and Diode's Reverse Recovery on the Input Current Ripple of Three-phase Voltage Source Inverters

This paper provides analytical equations to model the influence of dead-time and diode's reverse recovery on the input current ripple of a three-phase voltage source inverter. Analytical equations are derived and then verified by simulation and experiments. The influence of dead-time is also modeled heuristically as a linear relationship between the dead-time and the input current ripple values. A comparative analysis shows that the analytical equations proposed here are more accurate in predicting the input current ripple value than the heuristic method.
Indoor Positioning System Based on Wi-Fi and Bluetooth Low Energy

With the increase in the popularity of wireless technology, almost all utilize their handset for much more than just making phone calls. One of the easy-to-implement applications is to locate objects and place them under surveillance, such as children, patients, or even valuable possessions. The idea is to exploit the possibility of routers that work with a Wi-Fi or Bluetooth signal for additional applications to perform tasks without an added cost. In this paper, a proposed model that included 3 Access Points (APs) and one target are installed in a case study room with a dimension of 8*8 m2 to localize and track the target within it. The 3 APs are installed in a chosen location to apply the Trilateration algorithm in order to, detect the location of such target. Also, the APs signal is used Wi-Fi and Bluetooth to compare which one is precise. The tools used for measuring the received signal (AirPort Utility) and (Bluetooth Received Signal Strength Indicator (RSSI) Analyzer) for Wi-Fi and Bluetooth respectively. The results show that the average errors are 1.3 m and 1.7 m for Wi-Fi and Bluetooth respectively. From this result, we conclude that estimating coordinates inside the room using Wi-Fi technology is more accurate than using Bluetooth technology under the same conditions. This model can be added as an additional application to the Wi-Fi and Bluetooth devices that are available in our life.
A Family of High Step-up Isolated DC-DC Converters based on Fibonacci Switched-capacitor Cell

In this paper, a family of high step-up isolated DC-DC converters based on the traditional 3X Fibonacci switched-capacitor converter (SCC) is proposed by replacing one active switch with the secondary wingding of a high frequency (HF) transformer. Other replaceable active switches are substituted by diodes, while the primary circuit is built up with an active switch and the transformer primary winding. Compared with the traditional Fibonacci SCC, the proposed converters feature wider voltage-gain variation range, high step-up voltage gain, electrical isolation and fewer components, which make them potential for photovoltaic power generation system. Compared with the Flyback converter, the proposed converters obtain higher power density by incorporating switched-capacitor cell. The analysis of operating modes and voltage gain derivation is given, together with the passive components volume comparison between the proposed converters and the Flyback converter. A 40V~60V to 400V prototype was designed and tested to verify the theoretical analysis.
Entropy Based Generative Adversarial Network for PolSAR Image Classification

In order to solve the problem that the effect of generator feature learning is not paid enough attention in generative adversarial network(GAN) for Polarimetric synthetic aperture radar(PolSAR) data, a new GAN called Entropy-based Auxiliary Classifier Generative Adversarial Networks (E-ACGAN) was proposed in this paper. The decomposition discrepancy was obtained by calculating the entropy decomposition of the real data and the generated data. Then the decomposition discrepancy is used to measure the similarity between the generated data and the real data. This discrepancy will be introduced into the model as an additional optimization goal of the generator. Therefore, the generator can learn more characteristics of PolSAR data to generate more realistic data. In the step of adversarial learning, the discrimination and classification capabilities of the discriminator are also improved with the generator. The experimental results on the Flevoland2 data set show that the classification accuracy of E-ACGAN is 2.36% higher than that of the original ACGAN and it is also improved to different degrees than other traditional classification methods.
Two-stage Battery Energy Storage Power Conversion System Based on Dual Active Bridge

In this paper, the basic principle and control strategy of a 110V/3kW two-stage dual-active-bridge-based battery energy storage power conversion system are introduced. The parameter design of its control loop is provided in detail. Meanwhile, a small-signal impedance model of power conversion system is established to analyze the stability under the condition of weak grid. In the end, the simulation and experimental results are given to confirm the feasibility of designed control loop and the correctness of proposed impedance model.
A New Family of Non-Isolated Single-Inductor Three-Port Converter Based on A Storage Port Switch-Commutated Unit

Three-port converters are widely used in the renewable power generation system, served as the connection equipment among the renewable source, the energy storage cell and the load. Where, the port connected with the energy storage cell should be bidirectional. In this paper, a storage port switch-commutated unit is proposed. Further, a family of single-inductor three-port converters are generated based on the proposed storage port unit, and a new topology generation method for three-port converters are proposed. Only four switches at most are needed for the new single-inductor three-port converters, which have very simple structure. Finally, a 200W prototype is established to verify the correctness of the new single-inductor three-port converters.
Cost Inference of Discrete-time Linear Quadratic Control Policies using Human-Behaviour Learning

In this paper, a cost inference algorithm for discrete-time systems using human-behaviour learning is pro-posed. The approach is inspired in the complementary learning that exhibits the neocortex, hippocampus, and striatum learning systems to achieve complex decision making. The main objective is to infer the hidden cost function from expert's data associated to the hippocampus (off-policy data) and transfer it to the neocortex for policy generalization (on-policy data) in different systems and environments. The neocortex is modelled by a Q-learning and a least-squares identification algorithms for on-policy learning and system identification. The cost inference is obtained using a one-step gradient descent rule and an inverse optimal control algorithm. Convergence of the cost inference algorithm is discussed using Lyapunov recursions. Simulations verify the effectiveness of the approach.
Feasibility Study on Wireless Power Transfer for AUV with Novel Pressure-Resistant Ceramic Materials

Wireless power transfer (WPT) technology attracts increasing attention to becoming a reliable and safe underwater charging method for Autonomous underwater vehicle (AUV). Metallic hull brings negative effects to WPT systm for AUV charging, tradtional AUV hull made of high-stength steel, aluminum alloy or titanium alloy would cause failure to wireless charging. SiAlON ceramics with high compressive strength, high resistance against corrosion, low specific gravity is considered as a promising pressure-resistant material for AUV. This paper studies the feasibility of wireless charging for AUV with novel pressure-resistant ceramics and makes comparison with glass hull. A 1 kW experimental prototype is implemented to validated the power transmission performance. Compared with glass hull, the SiAlON ceramics hull has little effect on WPT system for AUV.
Long-short term traffic prediction under road incidents using deep learning networks

This paper investigates the effectiveness of multi-variate deep learning models for traffic flow prediction with road incidents. Multiple features of the data are considered in the analysis including traffic features, road incident features and cyclical features. Three multivariate deep learning models based on the stacked LSTM network, the CNN LSTM network, and the Autoencoders-LSTM network are developed for long-short term traffic forecasting under road incidents. The results obtained from the analysis are then compared to determine the best suitable approach.
A Consideration on Efficiency Maximization for Inductive Power Transfer System with Dual Converters

As an efficiency improvement method for inductive power transfer systems, there is a method that appropriately controls the load resistance of the resonant network by the connected converters. However, it is indi-cated that the power loss in the converters becomes domi-nant in a specific part of the operation range. In this range, the whole system efficiency worsens by the load-optimization control. Therefore, in this paper, the whole system efficiency is analyzed considering the converter losses, and a guideline for efficiency improvement is shown. In the experiments, the validity of the guideline is verified by a comparison with the conventional control. As a result, the whole system efficiency was improved over the wide operation range by the proposed guideline. Especially at 2.3 kW with constant current charging, the efficiency was improved by 1.2 points. At 2.3 kW with constant voltage charging, the efficiency was improved by 1.1 points.