Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and performance assessment of correlation filters for the detection of objects in high clutter thermal imagery

The research reported in this thesis has examined means of enhancing the performance of the Optimal Trade-off Maximum Average Correlation Height (OT-MACH) filter for target detection in Forward Looking Infra-Red (FLIR) imagery acquired from a helicopter and border security FLIR camera in northern Kuwait. The data acquired with these FLIR sensors allows real-world evaluation of the comparative performance of the various filters that have been developed in the thesis. The results obtained have been quantified using well known performance measures such as Peak to Side-lobe Ratio (PSR) and Total Detection Error (TDE). The initial focus was to study the effect of modifying the OT-MACH parameters on the correlation metrics. A new optimisation technique has been presented, which computes statistically the filter alpha parameter associated with controlling the response of the filter to clutter noise. A further modification of the OT-MACH filter performance using the Difference of Gaussian bandpass filter (named the D-MACH filter) as a pre-processing stage has been described. The D-MACH has been applied to several test images containing single and multiple targets in the scene. Enhanced performance of the modified filter is demonstrated with improved metrics being obtained with less false side peaks in the correlation plane, especially when multiple targets are present in the test images. A further pre-processing technique was investigated using the Rayleigh distribution as a pre-processing filter (named the R-MACH filter). The R-MACH filter has been applied to multiple target types with tests conducted across various image data sets. The filter demonstrated an improvement over the Difference of Gaussian filter in terms of 6 reducing the number of parameters needing to be tuned whilst producing further enhanced correlation plane metrics. Finally, recommendations for future work has been made to improve the use of the OT-MACH filter in target detection and identification. A novel training image representation is proposed for further investigation, which will minimise the computational intensity of using the MACH filter for unconstrained object recognition.
Topological rationality of supply chain networks

In this study, we apply a topologically distributed bounded rationality model to quantify the level of rationality in supply chain networks. We use the averaged Jensen-Shannon divergence values between Nash and Quantal Response equilibria for all inter-firm strategic interactions, which are represented as Prisoner’s Dilemma games, to characterise the average level of rationality in a given supply chain network. This is based on the game theoretic assumption that as the rationality of a particular interaction increases, it converges towards Nash equilibrium, in a certain strategic decision making scenario. Using this model, we demonstrate that hub-and-spoke topologies are collectively more rational compared to scale-free and random network topologies. Finally, we compare our theoretical results against the empirical findings reported for networked systems in various domains. In particular, it is shown that network topologies comprising higher average rationality levels emerge under increasingly competitive environments.
Construction time performance: an evaluation of contractors from Japan, the UK and the US

International comparisons of contractor performance allow contractors in different countries to distinguish their own strengths and weaknesses and improve their competitiveness accordingly. Based on a survey of contractors in Japan, the UK and the US, contractor time performance is evaluated and compared. It is found that Japanese contractors achieve shorter construction times and higher levels of time certainty than their UK and US counterparts. Furthermore, anticipated delays are far shorter in Japan and levels of client satisfaction are significantly higher than in the US and UK. The superior performance of Japanese contractors may be attributed to their working practices which were characterized by the use of a larger workforce on site, detailed planning, close working relationships with their subcontractors, and an overriding focus on time certainty.
Energy Harvesting For Wearable Devices: A Review

In recent years, wearable devices have attracted attention because of their ability to enhance the quality of life. This disruptive technology has helped healthcare professionals with intervening early in chronic diseases, especially amongst independently living patients, and has facilitated real-time monitoring of patients’ vital signs remotely. One of the major bottlenecks that hamper the adoption of wearable device is the continuous power supply. Most wearable devices solely depend on battery supply. When the energy stored in the battery is depleted, the operation of wearable devices is affected. To overcome this limitation, efficient energy harvesters for wearable devices are crucial. The paper primarily aims to present a comprehensive classification of different energy sources that can be capitalized to power wearable devices. In addition, this research paper deals with the key challenges that must be considered in the development of autonomous wearable devices for telemedicine applications with a proposed system design for wearable device that uses energy harvesting technology.
Design and Analysis of a Novel PM-Assisted Synchronous Reluctance Machine Topology With AlNiCo Magnets

The absence of field excitation on the rotor of the synchronous reluctance machine, results in poor power factor and low power density when compared to permanent magnet synchronous machines. To mitigate these problems, permanent magnet-assisted synchronous reluctance machines were introduced. The inserted permanent magnet boosts the machine's power factor and enhances its power density. In this paper, a new topology for permanent magnet-assisted synchronous reluctance machines using low cost AlNiCo magnets is proposed. The results of the proposed design with various magnet dimensions using AlNiCo magnets are compared with a previously designed and prototyped synchronous reluctance machine. Simulations for the same magnet dimensions are also carried out using a rare earth magnet material to study the effect of magnet type on the machine's performance. A final design using AlNiCo magnets is chosen based on the gain in the power density, manufacturing cost, torque ripple, and the power factor improvement. A rotor prototype is manufactured based on the selected topology and tested under various operating conditions.
Robust three‐vector‐based low‐complexity model predictive current control with supertwisting‐algorithm‐based second‐order sliding‐mode observer for permanent magnet synchronous motor

This study presents a robust three-vector-based low-complexity model predictive current control with supertwisting-algorithm-based second-order sliding-mode observer for permanent magnet synchronous motor (PMSM). First, to reduce the computational complexity of the three-vector-based model predictive current control, the optimal voltage vector combination is directly determined by the sector of desired voltage vector. Second, a supertwisting-algorithm-based second-order sliding-mode observer is designed to observe the lump disturbance caused by model mismatch and unmodelled dynamics. The estimated lump disturbance is considered as the compensation to the original PMSM model to reduce steady-state current error, which improves the robustness of the three-vector-based model predictive current control. Finally, the effectiveness of the proposed method is verified by experiments on a two-level-inverter-fed PMSM drive platform. Experimental results prove that, compared with three-vector-based model predictive current control, the proposed method can reduce the computational complexity and enhance robustness against motor parameters variation.
M3C: Multimodel-and-Multicue-Based Tracking by Detection of Surrounding Vessels in Maritime Environment for USV

It is crucial for unmanned surface vessels (USVs) to detect and track surrounding vessels in real time to avoid collisions at sea. However, the harsh maritime environment poses great challenges to multitarget tracking (MTT). In this paper, a novel tracking by detection framework that integrates the multimodel and multicue (M3C) pipeline is proposed, which aims at improving the detection and tracking performance. Regarding the multimodel, we predicted the maneuver probability of a target vessel via the gated recurrent unit (GRU) model with an attention mechanism, and fused their respective outputs as the output of a kinematic filter. We developed a hybrid affinity model based on multi cues, such as the motion, appearance, and attitude of the ego vessel in the data association stage. By using the proposed ship re-identification approach, the tracker had the capability of appearance matching via metric learning. Experimental evaluation of two public maritime datasets showed that our method achieved state-of-the-art performance, not only in identity switches (IDS) but also in frame rates.
Data Mining Practical Machine Learning Tools And Techniques With Java Implementations

Thank you for reading data mining practical machine learning tools and techniques with java implementations. As you may know, people have look hundreds times for their favorite novels like this data mining practical machine learning tools and techniques with java implementations, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some malicious bugs inside their laptop.
Coordinated Defense of Distributed Denial of Service Attacks against the Multi-Area Load Frequency Control Services

With the application of information and communication technology (ICT), the modern power system has gradually been updated to a typical cyber physical power system (CPPS). The deployment of distributed measurement devices enriches the application range of power communication services. However, due to the easy accessibility of distributed devices, it also creates favorable conditions for distributed denial-of-service (DDoS) attacks. In this paper, we focus on the security performance and defense strategies of the CPPS against DDoS attacks. In order to construct a coordinated defense in the power and information space, the cyber-attack process with a complete data flow of the CPPS needs to be described precisely. Therefore, a co-simulation technology-based platform is utilized to coordinate various layers in the CPPS and provide a unified research tool for the attack-defense test. On this basis, OPNET is used to replicate DDoS attacks in the information layer. Then, through the load frequency control (LFC) service of a multi-area interconnected power system, the influence of delays resulting from attacks on the control effect of the power layer is analyzed. Finally, to cope with the attack effects in both layers, detection measures of information and recovery measures of power quality are coordinated to eliminate attack consequences. Therefore, the stable operation of power services can be enabled.
Surface grafting of polyvinyl alcohol (PVA) cross-linked with glutaraldehyde (GA) to improve resistance to fouling of aromatic polyamide thin film composite reverse osmosis membranes using municipal membrane bioreactor effluent

Membrane surface modification is a favourable method to handle fouling during wastewater treatment processes. In this study, grafting of polyvinyl alcohol (PVA) through cross-link with Glutaraldehyde was applied to a thin film composite reverse osmosis membrane to enhance the resistance to flux decline. The analytical analyses attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and scanning electron microscopy were performed to evaluate the impact of surface modification. Biofouling using Escherichia coli (E. coli) bacterial solution and fouling tests using a bench scale reverse osmosis system with a simulated secondary effluent from a membrane bioreactor were used to assess the impact of the surface modification initiated on antifouling properties of the membrane. It was shown that the morphological structure and the chemical properties of the membrane were altered, whereas the pure water flux slightly decreased after modification. Although a slight decrease of salt rejection was observed, the membrane resistance to fouling improved and the biofouling model used revealed the anti-biofouling capacity of the membrane. The flux decline and flux recovery ratios improved with an increase in PVA concentration. The sterilization ratio increased from 33.8 to 36.8% and the pure water flux decline decreased from 46.04 to 25.94% after modification.
An Integrated Threat Assessment Algorithm for Decision-Making of Autonomous Driving Vehicles

In order to decide a safe and reliable trajectory for autonomous driving vehicles, the threat of surrounding vehicles need to be assessed quantitatively and consider the potential risk. This paper proposes a novel integrated threat assessment algorithm for the decision-making system. First, the motion of the surrounding vehicle is predicted probabilistic based on the interact multiple model (IMM) to consider the potential threat. Then, we build an integrated threat assessment function to assess the threat in each state quantitatively and objectively, which synthesizes the existing time-to-collision (TTC), time-headway (TH), and the original proposed time-to-front (TTF). Based on this, the decision-making system is established according to the Markov decision process (MDP) and the feedback value of each decision sequence is calculated by the integrated threat assessment function, thus the safest trajectory for the current moment can be determined by optimal search. Finally, the decision-making system is verified in the overtaking and cut-in scenario by Carsim and Simulink co-simulation. The results show that the proposed threat assessment algorithm for the decision-making system can help autonomous vehicles decide a safe trajectory in real-time and maintain good maneuverability.
Spatial Association of Lemming Burrows with Landforms in the Swedish Subarctic Mountains: Implications for Periglacial Feature Stability

Abstract Burrowing mammals often have considerable geomorphological impacts, and their tunneling activities may decrease the stability of landforms. We document the spatial distribution of Norwegian lemming burrows in a subarctic alpine meadow to determine the preferred locations for burrow entrances and to examine the potential for burrowing to decrease the stability of periglacial landforms at the site. Burrow entrances were disproportionately common into the base and sides of landforms (>68% of burrows), probably reflecting the lower energetic cost of moving soil horizontally, rather than vertically, out of burrows. Most burrow entrances (>60%) were also located under large rocks, which probably improve burrow stability by providing a firm ceiling to the entrance. Field observations show that these burrows are relatively stable, as only 3% were associated with any signs of increased erosion or landform instability. Therefore, in contrast to some previous studies, and despite burrowing being concentrated on landforms, we suggest that these rodents have little direct impact on landform integrity at this site.
The relationship between engineering students’achievement goals, reflection behaviors, and learning outcomes

Prior studies have shown that students’ achievement goals play a key role in their learning strategies, decision-makingprocesses, and learning outcomes. However, a majority of these studies were conducted with undergraduate psychologystudents. Thus, there is a need to explore the role of students’ achievement goals on their reflection behaviors and learningoutcomes in different fields, including engineering education. Based on our literature review in engineering education, thereare a limited number of studies that investigated the relationship between achievement goals and students’ learningoutcomes. Therefore, we conducted this exploratory research study to investigate the relationship between achievementgoals, reflection behaviors, and learning outcomes of engineering students. We used the Achievement Goal Questionnaire-Revised (AGQ-R) scale to measure 69 sophomore engineering students’ achievement goals. Six response variables wereincluded: average reflection quality, the total number of reflections submitted, two exam scores, the final exam score, andthe total weighted learning outcomes. Based on our analyses, we found that the mastery approach was significantly relatedto the total number of reflections, the final exam score, and the total weighted learning outcome variables. Theperformance approach was also significantly related to the final exam and total weighted learning outcome. Masteryavoidance was significantly related to the total number of reflections, the second exam, and the total weighted learningoutcome. Finally, performance avoidance was significantly related to the second exam, final exam, and the total weightedlearning outcome. Overall, our findings are informative to researchers in the engineering education field for betterunderstanding students’ learning strategies, reflection behaviors, and learning outcomes relating to their goal orientation.Thus, this study provides benefits to researchers and other stakeholders such as faculty members or administrators inengineering education to develop more effective intervention programs that positively impact student motivation and theirlearning strategies as well as learning outcomes.
Analog and Digital Self-Interference Cancellation for Full-Duplex Transceivers

Analog and digital self-interference (SI) cancellation in full-duplex transceivers is considered in this paper. Analog SI isolation is performed at radio frequency using electrical balance circuitry. Remaining SI is then cancelled at baseband. For the baseband SI cancellation an estimate of the SI channel is needed. Since the receiver has full knowledge of the transmitted signal no extra pilot nor silent periods are used for the SI cancellation. Three different channel estimators are tested. Bit-error-rate (BER) results show that sufficient SI cancellation can be achieved when the SI channel is estimated during the signal reception.
Multi-Objective Optimal Charging Control of Plug-In Hybrid Electric Vehicles in Power Distribution Systems

With the increasing popularity of plug-in hybrid electric vehicles (PHEVs), the coordinated charging of PHEVs has become an important issue in power distribution systems. This paper employs a multi-objective optimization model for coordinated charging of PHEVs in the system, in which the problem of valley filling and total cost minimization are both investigated under the system’s technical constraints. To this end, a hierarchical optimal algorithm combining the water-filling-based algorithm with the consensus-based method is proposed to solve the constrained optimization problem. Moreover, a moving horizon approach is adopted to deal with the case where PHEVs arrive and leave randomly. We show that the proposed algorithm not only enhances the stability of the power load but also achieves the global minimization of vehicle owners charging costs, and its implementation is convenient in the multi-level power distribution system integrating the physical power grid with a heterogeneous information network. Numerical simulations are presented to show the desirable performance of the proposed algorithm.
UWB antenna with dynamically reconfigurable notch band using rectenna and active booster

In this study, an ultra-wideband (UWB) monopole antenna with a dynamically reconfigurable notch band, along with the associated RF-triggered power management unit (PMU) that enables the dynamic reconfigurability, are presented. The UWB monopole antenna has a rectangular slot which hosts a J-shaped stub, electrically connected with the radiator using one PIN diode switch. When the diode is OFF, the monopole antenna has a UWB characteristic, while when it is turned ON a frequency notch is created at 5.6 GHz. The diode is fed from a PMU that consists of a rectenna and a DC-to-DC active booster. When the rectenna that consists of a patch antenna and a rectifier receives a -11 dBm or higher 5.6 GHz signal, it rectifies the RF signal into a sufficiently high DC voltage. The rectified DC voltage is applied to the cascaded DC-to-DC booster as enabling signal, and the booster provides at its output terminal sufficient DC power to actuate the PIN diode and thus dynamically reconfigure the UWB antenna. The dynamically reconfigurable notch band is created immediately in response to the reception of an external, -11 dBm RF signal at 5.6 GHz, and it disappears in real time immediately after the external RF signal is removed.
Deciding to Apply for Federal Disaster Assistance: A Preliminary Investigation of Disaster Decision-Making using a Bounded Rationality Framework

Abstract Among disaster victims, the decision to apply for assistance with the Federal Emergency Management Agency (FEMA) is not straight forward. It is typically affected a variety of factors beyond individual demographic characteristics. Using Texas in the aftermath of Hurricane Harvey, this study utilizes bounded rationality as a theoretical framework for exploring what may affect the decision to apply for individual assistance with FEMA. A representative sample of generally affected individuals and a subsample of individuals with home damage are used to investigate various factors thought to be important in decision-making and compare differences between the groups. As a byproduct of the analysis, it is observed that although the loss of employment and being able to rely on one’s immediate network is a significant predictor of applying for aid among individuals with home damage, these variables are not significant among those that were generally affected. Recommendations for future research are provided to enhance our understanding of decision-making in the aftermath of disasters.