Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatically Diagnosing Suspicious Regions in Skin Images Using Two-Stage Genetic Programming

Developing a computer-aided diagnostic system for detecting various skin malignancies from images has attracted many researchers. Unlike many machine learning approaches such as Artificial Neural Networks, Genetic Programming (GP) automatically evolves models with flexible representation. GP successfully provides effective solutions using its intrinsic ability to select prominent features (i.e. feature selection) and build new features (i.e. feature construction). Existing approaches have utilized GP to construct new features from the complete set of original features and the set of operators. However, the complete set of features may contain redundant or irrelevant features that do not provide useful information for classification. This study aims to develop a two-stage GP method where the first stage selects prominent features, and the second stage constructs new features from these selected features and operators such as multiplication in a wrapper approach to improve the classification performance. To include local, global, texture, color, and multi-scale image properties of skin images, GP selects and constructs features extracted from local binary patterns and pyramid-structured wavelet decomposition. The accuracy of this GP method is assessed using two real-world skin image datasets captured from the standard camera and specialized instruments, and compared with commonly used classification algorithms, three state-of-the-art, and an existing embedded GP method. The results reveal that this new approach of feature selection and feature construction effectively helps improve the performance of the machine learning classification algorithms. Unlike other black-box models, the evolved models by GP are interpretable, therefore the proposed method can assist dermatologists to identify prominent features, which has been shown by further analysis on the evolved models.
Intelligent acoustic interfaces for immersive audio

Oncoming audio technologies privilege the perceptive quality of audio signals, thus offering users an immersive audio experience, which involves listening and acquisition of audio signals. In such scenario a fundamental role is played by intelligent acoustic interfaces which aim at acquiring audio information, processing it, and returning the processed information under the fulfillment of quality requirements demanded by users. In this work we introduce intelligent acoustic interfaces for immersive audio experience and we prove their effectiveness within the context of immersive speech communications. In particular, we introduce an intelligent acoustic interface composed of a combined adaptive beamforming scheme in conjunction with a microphone array, which is able to enhance the processed signals in immersive scenarios.
Factors Influence Organization Management towards Using Electronic Recruitment Strategy

Recruitment is a set of activities and processes used to obtain a sufficient number of people who are eligible and can legally work in an organization in a well-timed manner. Recruitment enables applicants as well as an organization to identify and select each other on the basis of mutual best interests. E-recruitment takes a place alongside traditional recruitment and even exceeds it in some countries. The current paper addresses the factors that affect organization management in engaging human resource management policies and strategies towards E-recruitment to attract human capital in order to compete and survive in the market. The aims of this study were to explore, identify and classify the factors that influence management towards E-recruitment as well as develop a conceptual framework. Seven factors, among which Faster Recruitment Process, Easier Administration, and Cost Reduction, were projected as findings of this paper.
Endogenous Cognitive Tasks for Brain-Computer Interface: A Mini-Review and a New Proposal

Brain-Computer Interfaces allow interaction between the voluntarily produced human cerebral activity and a computer. The output produced by the user’s performance can serve as an input to the technologic device that can decode this information and transform it to a command. Literature has usually focused on processing and classification often neglecting the importance of the mental tasks used to elicit and modulate the cerebral activity. In this paper, we review previous mental tasks used in literature: motor imagery, spatial navigation, geometric figure rotation, imagery of familiar faces, auditory imagery and math imagery. Then, we propose a set of these tasks modified to maximize the user’s performance during the execution of mental tasks.
Utility-connected power converter for maximizing power transfer from a photovoltaic source while drawing ripple-free current

This paper presents a power converter for coupling photovoltaic arrays to the utility grid. The converter draws a programmable, ripple-free DC current from the photovoltaic array and injects power into the grid at unity power factor. The programmable input current feature makes this converter ideal for use with maximum power point tracking technology. The proposed converter has an additional unique feature in that the internal dc link carries a large (approximately 25%) ripple voltage. Allowing a large ripple on the DC link reduces the required size of the link capacitor. This paper includes basic system information, analysis of filter requirements, controller design and preliminary hardware results.
Turkish Validity and Reliability Study of Jessa Atrial Fibrillation Knowledge Questionnaire (JAKQ)

Objective Atrial fibrillation (AF) is the most commonly encountered arhythmia in clinical practice and constitutes one-third of the hospitalizations related to cardiac dysrhythmia. Furthermore, it is the most common reason for hospital admissions involving dysrhythmia complaints and is associated with the decrease in quality of life, functional capacity, cardiac performance, and lifespan. Materials and Methods This methodological study, which aims to assess the validity and reliability of the JAKQ, was conducted with patients (n = 175) who were admitted to the emergency clinic of Atatürk University Research Hospital between December 2016 and June 2018 and who were diagnosed with atrial fibrillation and met the inclusion criteria. The data were collected using a “Personal Information Form” and the “Jessa Atrial Fibrillation Knowledge Questionnaire (JAKQ). Results The exploratory factor analysis carried out to determine the construct validity of the scale showed that it had a three-dimensional structure and that its factor loads were within the appropriate range. The internal consistency analyses of the scale revealed that the Cronbach’s alpha coefficient was 0.84 and that the item-total score correlations were at an adequate level. The correlation value of the test-retest conducted to test the time invariance of the scale was found to be 0.87, and there was a statistically significant relationship between the two applications (P < .001). Conclusion The study results showed that the structure of the Turkish version of the Jessa Atrial Fibrillation Questionnaire was similar to the structure of the original scale, that its validity and reliability were considerably high and that it could be used in Turkey.
Olympic Proportions: Cost and Cost Overrun at the Olympics 1960-2012

Do different types of megaprojects have different cost overruns? This apparently simple question is at the heart of research at the University of Oxford aimed at understanding the characteristics of megaprojects, particularly in terms of how they are established, run and concluded. In this study, we set out to investigate cost overruns in the Olympic Games. To do so, we examined the costs of the Games over half a century, including both summer and winter Olympics. We looked at the evolution of final reported costs and compared these to the costs established in the Games bids, submitted to the International Olympic Committee (IOC) up to seven years before the Games occurred. In so doing we established the largest dataset of its kind, and documented for the first time in a consistent fashion the costs and cost overruns for the Olympic Games, from 1960 to 2012. We discovered that the Games stand out in two distinct ways compared to other megaprojects: (1) The Games overrun with 100 per cent consistency. No other type of megaproject is this consistent regarding cost overrun. Other project types are typically on budget from time to time, but not the Olympics. (2) With an average cost overrun in real terms of 179 per cent – and 324 per cent in nominal terms – overruns in the Games have historically been significantly larger than for other types of megaprojects, including infrastructure, construction, ICT, and dams. The data thus show that for a city and nation to decide to host the Olympic Games is to take on one of the most financially risky type of megaproject that exists, something that many cities and nations have learned to their peril. For the London 2012 Games, we find that: (1) With sports-related real costs currently estimated at USD14.8 billion, London is on track to become the most costly Olympics ever. (2) With a projected cost overrun of 101 per cent in real terms, overrun for London is below the historical average for the Games, but not significantly so. (3) The London cost overrun is, however, significantly higher than overruns for recent Games since 1999. London therefore is reversing a positive trend of falling cost overruns for the Games.
Can Green Finance Development Reduce Carbon Emissions? Empirical Evidence from 30 Chinese Provinces

Dealing with the relationship between environment and economic development is the core issue of China’s sustainable development. At present, China’s economic transformation is urgent, and green finance is being widely concerned. This paper measured the development level of China’s green finance from the perspective of green credit, green securities, green investment, and green insurance. Then, it used a spatial dynamic panel model to empirically test the mechanism of the impact of green finance on carbon emissions with panel data of 30 Chinese provinces from 2005 to 2018. The following can be seen from the results: (1) The development of green finance contributes to carbon emission reduction. (2) The spatial spillover effect of green finance is significant. Specifically, the development of green finance can not only reduce the carbon emissions of the local region but also inhibit that of adjacent areas. (3) The development of green finance indirectly leads to a decrease in carbon emissions by reducing financing constraints and boosting green technology innovation. In order to stimulate the carbon emission reduction effect of green finance to a greater extent, we should further support the development of green finance, reduce the financing constraints of energy-saving and environmental-protection enterprises, and encourage the research and development of green innovative technologies.
Biomimetic Design of an Under-Actuated Leg Exoskeleton for Load-Carrying Augmentation

Abstract : Metabolic studies have shown that there is a metabolic cost associated with carrying a load. Previous work on exoskeleton design has not considered the passive dynamics of walking and has focused on fully actuated systems that are inefficient and heavy. In this thesis, an underactuated exoskeleton is presented that runs parallel to the human leg. The exoskeleton component design is based on the kinematics and kinetics of human walking. The joint components of the exoskeleton in the sagittal plane consist of a force-controllable actuator at the hip, a variable-damper mechanism at the knee, and a passive spring at the ankle. A state-machine control strategy is written based on joint angle and ground-exoskeleton force sensing. Positive non-conservative power is added at the hip during the walking cycle to help propel the mass of the human and payload forward. At the knee, the damper mechanism is turned on at heel strike as the exoskeleton leg is loaded and turned off during terminal stance to allow knee flexion. The spring at the ankle engages in controlled dorsiflexion to store energy that is later released to assist in powered plantarflexion. Kinetic and metabolic data are recorded from human subjects wearing the exoskeleton with a 75 lb. payload. These data are compared to data recorded from subjects walking without the exoskeleton. It is demonstrated that the exoskeleton transfers loads to the ground with a 90% and higher load transfer depending on the phase of gait. Further exoskeleton wearers report that the exoskeleton greatly reduces the stress on the shoulders and back. However, although a significant fraction of the payload is transferred through the exoskeleton structure, the exoskeleton is found to increase metabolic economy by 74%. By comparing distinct exoskeleton configurations, the relative effect of each exoskeleton component is determined.
Personal monitoring to reduce exposure to black carbon in children with asthma: a pilot study

In December 2020, Her Majesty's Assistant Coroner for Inner South London, UK, Philip Barlow, ruled that traffic-related particulate matter and nitrogen dioxide were contributary factors in the death of a young girl from asthma whose house was on London's South Circular Road [1]. The coroner's subsequent Prevention of Future Deaths report highlights the need for all health professionals to communicate the risks of air pollution to parents and children with asthma. Generic advice is available for use in consultations. Using an advice-based intervention in a cohort of children with asthma, designed to reduce personal pollution exposure, a mean reduction in black carbon exposure of 34% was found, the primary reduction happening within the home environment https://bit.ly/301Xemt
HiPE: Hierarchical Initialization for Pose Graphs

Pose graph optimization is a non-convex optimization problem encountered in many areas of robotics perception. Its convergence to an accurate solution is conditioned by two factors: the non-linearity of the cost function in use and the initial configuration of the pose variables. In this letter, we present HiPE, a novel hierarchical algorithm for pose graph initialization. Our approach exploits a coarse-grained graph that encodes an abstract representation of the problem geometry. We construct this graph by combining maximum likelihood estimates coming from local regions of the input. By leveraging the sparsity of this representation, we can initialize the pose graph in a non-linear fashion, without computational overhead compared to existing methods. The resulting initial guess can effectively bootstrap the fine-grained optimization that is used to obtain the final solution. In addition, we perform an empirical analysis on the impact of different cost functions on the final estimate. Our experimental evaluation shows that the usage of HiPE leads to a more efficient and robust optimization process, comparing favorably with state-of-the-art methods.
ULTRASONIC PHASED ARRAY TOOLS FOR LARGE AREA COMPOSITE INSPECTION DURING MAINTENANCE AND MANUFACTURING

Aircraft manufacturers, maintenance service providers, and airline operators have recently started to use ultrasonic phased‐array technology to ensure the quality of their composite parts during maintenance and manufacturing. Olympus NDT has developed various solutions with its phased‐array instruments like the OmniScan PA and the Focus LT to meet the most demanding requirements. These tools combined with composite specific software features provide greater productivity with respect to scanning and defect characterization such as sizing while maintaining a high degree of reliability. This paper summarizes the advantages and the benefits obtained by the use of this technology on samples provided by the FAA Airworthiness Assurance Center (AANC) operated by Sandia National Labs.
A Hardware Architecture for SVPWM Digital Control With Variable Carrier Frequency and Amplitude

A novel digital controller for the space-vector pulsewidth modulation (SVPWM) algorithm used in three-phase power inverters is shown. From an analysis of the vector representation of the three-phase triad, the dwell-times evaluation is optimized reducing the needed resource of the hardware. Our proposal is based on the use of only one-sixth of the vectorial plane and on a precalculation of the dwell-times in terms of the maximum modulation index and the minimum carrier frequency. Once obtained the normalized dwell-times, an optimized hardware architecture is proposed to evaluate the effective dwell-times by changing in real time the wanted values of the carrier frequency and of the amplitude. Our architecture excludes the use of external reference signals or processors. We experimentally implement it both on a low-cost field programmable gate array Artix-VII and on a more performing Cyclone-V. Finally, classical and advanced SVPWM techniques are proposed to show the flexibility of our architecture.
Primary-User-Friendly Dynamic Spectrum Anti-Jamming Access: A GAN-Enhanced Deep Reinforcement Learning Approach

This letter studies the problem of deep reinforcement learning (DRL)-based dynamic spectrum anti-jamming access in overlay cognitive radio networks. To prevent secondary user (SU) from interfering with primary user (PU) and being jammed by jammer, we propose a PU-friendly dynamic spectrum anti-jamming access scheme. First, a generative adversarial network (GAN)-based virtual environment is proposed to simulate spectrum environment. Then, a DRL-based channel decision network (CDN) is trained to learn the optimal spectrum access policy in the virtual environment. Finally, SU accesses spectrum environment under the guidance of the trained CDN. Simulation results show that the proposed scheme is able to elude both PU signals and jamming completely and converges much faster than the scheme that trains the CDN in spectrum environment from scratch.
The time-area fishing closure impacts on fish stock; Qiantang River before and after a four-month fishing closure

Fishing closures, commonly used to manage fisheries’ catch, involve temporarily closing a body of water to particular fishing gears to control fishing effort and protect feeding and spawning areas. In recent years in Qiantang River of China, with the socio-economic development, protection of fish stock has become increasingly urgent. The year 2019 was the first year that Qiantang River was included in the unified fishing ban system for the south of Yangtze River basin. Here, fish captures and hydroacoustic surveys were carried out in the research area of Qiantang River in order to present comparative descriptions of the dominant fish species, the temporal changes of fish size, density, biomass, and distribution affected by the four-month fishing closure in 2019. The results showed that Pseudobrama simoni (Bleeker, 1864) was the most dominant species both before and after the closure by using the traditional capture method. The mean target strength (TS) of overall fish after closure was –50.28 ± 0.19 dB, which was lower than that before, resulting in a significantly shorter derived mean length (13.42 ± 0.74 cm). The mean fish density and calculated biomass after closure were both significantly higher than that before it. More than 50% of fish species were distributed in the water of 5–20 m depth after the closure, which likely occurred in water deeper than 20 m before. Meanwhile, fewer outliers were found in different depth categories after closure. It is concluded that the four-month closure in 2019 had a positive effect on fish size, density, and biomass, leading to protection of pelagic fishes and a more even distribution of fish.
A Modified Particle Swarm Optimization for Optimal Power Flow

The optimal power flow (OPF) problem was introduced by Carpentier in 1962 as a network constrained economic dispatch problem. Since then, it has been intensively studied and widely used in power system operation and planning. In the past few decades, many stochastic optimization methods such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm Optimization (PSO) have been applied to solve the OPF problem. In particular, PSO is a newly proposed population based stochastic optimization algorithm. The main idea behind it is based on the food-searching behavior of birds and fish. Compared with other stochastic optimization methods, PSO has comparable or even superior search performance for some hard optimization problems in real power systems. Nowadays, some modifications such as breeding and selection operators are considered to make the PSO superior and robust. In this paper, we propose the Modified PSO (MPSO), in which the mutation operator of GA is incorporated into the conventional PSO to improve the search performance. To verify the optimal solution searching ability, the proposed approach has been evaluated on an IEEE 30-bus test system. The results showed that performance of the proposed approach is better than that of the standard PSO.
Robot motion planning for time-varying obstacle avoidance using view-time concept

An approach to solving the time-varying obstacle avoidance problem is pursued. The mathematical formulation of the problem is given in robot joint space (JS). The view-time concept is introduced to deal with time-varying obstacles. The view-time is the period in which a time-varying obstacle is viewed and approximated by an equivalent stationary obstacle. The equivalent stationary obstacle is the volume swept by the time-varying obstacle for the view-time. The swept volume is transformed into the JS obstacle that is the set of robot configurations causing the collision between the robot and the swept volume. In JS, the path avoiding the JS obstacle is planned, and a trajectory satisfying the constraints on robot motion planning is planned along the path. This method is applied to the collision-free motion planning of two SCARA robots, and the simulation results are given. <<ETX>>
An integrated simulation environment for human gait analysis and evaluation

Instrumental gait analysis allows a quantifiable documentation of human gait and motion characteristics. For this reason, this method is widely used for the diagnosis of pathological walking patterns and the rating of therapeutic measures. A drawback of existing systems is their closed architecture, as well as the special knowledge necessary for interpretation and processing of the results. Furthermore, radiological measurements are rarely fused with the gait motion data. This paper describes a new simulation environment suitable for human gait analysis which uses methods of kinematics, dynamics, segmentation and optimization to provide an evaluation of gait motion and radiological data which can be employed for direct medical interpretation. The objective of the simulation environment is a gait‐analysis software that can be used to produce clinically employable results in hospitals, surgeries and individual practice without the need of additional technical staff.
NARD: NUMERICAL ANALYSIS OF ROADSIDE DESIGN, VERSION 2.0. VOLUME 2. PROGRAMMERS MANUAL. FINAL REPORT

NARD 2.0 is a finite element code with the capability of simulating vehicle dynamics and maneuvering and vehicle crashes with roadside objects. The vehicle is modeled as a three-dimensional lumped parameter articulated body consisting of multiple units. The barrier is modeled as a three-dimensional object represented by displacement finite elements. Large deflections and rotations are accommodated in the program through nonlinear material behavior. The vehicle/barrier interaction is modeled by geometrically determining the interference between the two surfaces. The volume is the programming manual for NARD 2.0.