Miracle-dz/UniFAR-FTUs huggingface dataset:
A note on bonus theory

Abstract The theory of safety loading and bonus in life insurance has been a major subject in actuarial research. In Norway Karl Faerden (1928) and Erling Sverdrup (1969) have studied the subject. In this paper their model is extended. Bonus given as additional insurance cover will affect the premium reserve and future gains and bonus. There will be “bonus from bonus”. This circumstance has been disregarded in earlier papers. In the present paper the safety loading elements, the bonus and the additional (guaranteed) benefits are adjusted simultaneously to each other by a system of equations. The treatment is restricted to endowment policies. A similar treatment of other life insurance products will then be trivial.
Interface structures and magnetoresistance in magnetic tunnel junctions

The interface structures of magnetic tunnel junctions were studied using x-ray photoelectron spectroscopy (XPS). The structures were correlated with magnetoresistance (MR) characteristics. For MR measurements, Fe(50 nm)/AlOx/CoFe(30 nm) junctions with an in situ naturally oxidized Al tunnel barrier were fabricated. The thickness of the Al layer, an important parameter in MR characteristics, was varied from 0 to 5 nm. MR curves showed that the largest MR ratio occurred when the Al layers were 2–3 nm in thickness. XPS analysis showed that an Al layer greater than 1 nm thick covers the entire surface of the Fe underlayer. However, if the Al layer is more than 1 nm thick, the unoxidized Al remaining after the oxidation process increases as the thickness is increased. For Al layers that are greater than 3 nm thick, the MR ratio is strongly affected by unoxidized Al, probably due to the decrease in spin polarization at the surface of an Fe/Al electrode. On the other hand, the hysteresis loops indicate that the .
Precise frequency estimation in a microelectromechanical parametric resonator

The authors report here on precise resonant frequency estimation using the nonlinear spectral features of parametric resonance. Demonstration of 100 parts per 109 frequency resolution at room temperature is accompanied by a technique to observe the phase trajectories of escape in bistable parametrically resonant systems. The system offers an expanded dynamic range over similar linear resonators. Precise frequency estimation has implications in resonant mass sensing.
Proposing a New Hybrid Controlled Loop

Counter controlled and condition controlled are main categories of iterative statements, with “for”, “while” and “do while” loops dominating the field. While there are clear distinctions between them, it is not uncommon for a programmer to practically convert a condition controlled loop to do counter controlled task or vice versa. For instance, there is a “while loop” that will be iterated a number of times or a “for loop” with an additional condition next to the counter checker. This paper proposes a new loop that will be both counter and condition controlled. The loop will include an in-built predefined counter and it will be able to iterate a user defined number of time, prior to checking the user defined condition. A detailed explanation and a C++ implementation of the proposed loop are included in this paper.
Conceptual development about motion and force in elementary and middle school students

Methods of physics education research were applied to find what kinds of changes in 4th, 6th, and 8th grade student understanding of motion can occur and at what age. Such findings are necessary for the physics community to effectively discharge its role in advising and assisting pre-college physics education. Prior to and after instruction the students were asked to carefully describe several demonstrated accelerated motions. Most pre-instruction descriptions were of the direction of motion only. After instruction, many more of the students gave descriptions of the motion as continuously changing. Student responses to the diagnostic and to the activity materials revealed the presence of a third “snapshot” view of motion not discussed in the literature. The 4th and 6th grade students gave similar pre-instructional descriptions of the motion, but the 4th grade students did not exhibit the same degree of change in descriptions after instruction. Our findings suggest that students as early as 6th grade can d.
Exergoeconomic analysis of an aircraft turbofan engine

This study deals with an exergoeconomic analysis of an aircraft turbofan engine utilising the kerosene as fuel. A new parameter is developed to define the thrust cost rate. The cost of exergy destruction, the relative cost difference and the exergoeconomic factor are investigated. The variation of the relative cost difference and exergoeconomic factor according to the operating and maintenance costs and the annual operating hour are also studied. For a high by-pass and high thrust rated engine, the cost rate of thrust is obtained to be 304.35 $(hkN) −1 for the hot thrust and 138.96 $ (hkN)−1 for the cold thrust, respectively.
Sensorless control and initial position estimation of salient-pole brushless DC motor

This paper presents a position sensorless drive and an initial rotor position estimation for a salient-pole brushless DC motor with a sinusoidal flux distribution. To estimate the position and back EMF, the controller calculates the motor current by using the estimated position and back EMF of the motor model. The difference between the actual and the calculated currents is used to estimate the position and back EMF. The initial rotor position at standstill should be estimated for stable starting without temporary reverse revolution. The principle of the initial position estimation relies on the saliency of the motor and uses the current response difference due to the rotor position. To confirm the effectiveness of the proposed algorithm, experimental results using a 6-pole 200 W test motor are shown.
Thresholds for turbo codes

We prove the existence of thresholds for turbo codes and we prove concentration of the performance of turbo codes within the ensemble determined by the random interleaver. In effect, we show that the results obtained for low-density parity-check codes extend to turbo codes. The main technical innovation is to rigorously show that dependence of output extrinsic information on input priors decays with distance along the trellis. In an infinitely long turbo code the densities of the extrinsic information fulfill a certain symmetry condition which we call the consistency condition. This condition provides the basis for an efficient Monte-Carlo algorithm for the determination of thresholds for turbo codes. Thresholds of all symmetric parallel concatenated codes of memory up to 6 have been determined.
A simple improved full search for vector quantization based on Winograd's identity

Vector quantization (VQ) technique is a well known method in image compression. Employing Winograd's (1968) identity, this article presents a simple improved method in order to cut the computation time in the full search method for VQ nearly 50%. Some experiments are carried out to confirm the theoretical analysis.
Thermal fluctuations and boundary conditions in the lattice Boltzmann method

The lattice Boltzmann method is a popular approach for simulating hydrodynamic interactions in soft matter and complex fluids. The solvent is represented on a discrete lattice whose nodes are populated by particle distributions that propagate on the discrete links between the nodes and undergo local collisions. On large length and time scales, the microdynamics leads to a hydrodynamic flow field that satisfies the Navier-Stokes equation. In this thesis, several extensions to the lattice Boltzmann method are developed. In complex fluids, for example suspensions, Brownian motion of the solutes is of paramount importance. However, it can not be simulated with the original lattice Boltzmann method because the dynamics is completely deterministic. It is possible, though, to introduce thermal fluctuations in order to reproduce the equations of fluctuating hydrodynamics. In this work, a generalized lattice gas model is used to systematically derive the fluctuating lattice Boltzmann equation from statistical mechanics principles. The stochastic part of the dynamics is interpreted as a Monte Carlo process, which is then required to satisfy the condition of detailed balance. This leads to an expression for the thermal fluctuations which implies that it is essential to thermalize all degrees of freedom of the system, including the kinetic modes. The new formalism guarantees that the fluctuating lattice Boltzmann equation is simultaneously consistent with both fluctuating hydrodynamics and statistical mechanics. This establishes a foundation for future extensions, such as the treatment of multi-phase and thermal flows. An important range of applications for the lattice Boltzmann method is formed by microfluidics. Fostered by the “lab-on-a-chip” paradigm, there is an increasing need for computer simulations which are able to complement the achievements of theory and experiment. Microfluidic systems are characterized by a large surface-to-volume ratio and, therefore, boundary conditions are of special relevance. On the microscale, the standard no-slip boundary condition used in hydrodynamics has to be replaced by a slip boundary condition. In this work, a boundary condition for lattice Boltzmann is constructed that allows the slip length to be tuned by a single model parameter. Furthermore, a conceptually new approach for constructing boundary conditions is explored, where the reduced symmetry at the boundary is explicitly incorporated into the lattice model. The lattice Boltzmann method is systematically extended to the reduced symmetry model. In the case of a Poiseuille flow in a plane channel, it is shown that a special choice of the collision operator is required to reproduce the correct flow profile. This systematic approach sheds light on the consequences of the reduced symmetry at the boundary and leads to a deeper understanding of boundary conditions in the lattice Boltzmann method. This can help to develop improved boundary conditions that lead to more accurate simulation results.
Cloud radiative characteristic parameter calculation for space-based remote sensing sensors

Cloud coverage is a significant clutter source impacting on space-based infrared remote sensing sensors. In most existing literature, cloud coverage was simply assumed to be homogeneous with Lambertian surface. However, real-world clouds are inhomogeneous. In this work, we focus on the reflection and transmission of solar radiation from inhomogeneous cloud coverage. The paper use Mie scattering theory and radiative transfer theory to calculate bidirectional distribution functions of reflection and transmission. The spectral distributions of transmission and reflection functions within spectral band from 0. 4μm to 14μm for stratocumulus cloud are calculated. Results are compared with that of two-stream approximation, demonstrating the effectiveness and accuracy.
Machine Learning-Based Intrusion Detection System for the Internet of Vehicles

With the advancement in vehicular technology, security has become a significant concern. Attacks in the network can be minimised if an attack can be detected earlier. The proposed model, with the help of the Intrusion Detection Model using various distinct Machine Learning algorithms along with an ensemble model, is presented to help predict any attack in the network. The goal is to perform a comparative study of different feature selection techniques and machine learning models. After that, the model that gives better accuracy in classifying or detecting various types of network attacks will be chosen as the final model. The ML algorithms selected are based on Decision Tree, Naive Bayes, K-Nearest Neighbors, Logistic Regression, Random Forest and Support Vector Machine. A comparative analysis between all these six algorithms is also performed. In order to achieve the goal, the NSL-KDD dataset was downloaded from the Kaggle repository. The proposed model was compared with existing models and found to be more effective than the existing models in terms of accuracy.
A Semantic Review on Challenges, Trends towards Defensive IDS in Internet of Things

Securing data over the network is one of the major issues among network users. Therefore, intrusion detection systems (IDS) were developed that become an important tool in security mechanism for Internet of Things (IoT). Over the years, a significant number of IDS have been developed; however, choosing the best can be tough sometimes. In this paper, different IDS developed over the last few years have been reviewed. The major focus of this review is to analyze the importance of IDS in computer networks and IoT, issues and possible solutions to overcome these challenges. In addition to this, role of machine learning (ML) and deep learning (DL) algorithms in detecting intrusions is also analyzed and discussed. Moreover, the key findings after reviewing the literature study are also mentioned in this work in which we find that majority of the researchers are moving towards the DL based algorithms for detecting intrusions because of their ability to handle large datasets. Therefore, by selecting a suitable method will enhance the detection rate.
Design of circular economy enhancing journeys for automotive manufacturing industry

Currently in Europe a very large number of Tier 1 and Tier 2 suppliers serve a few large OEMs in the automotive industry. Most of them are SMEs with no or limited experience in design and manufacturing of lightweight products and scarce knowledge on circular economy. On the other hand, many of these companies are inventive and willing to transform and adapt new materials and methods, being part of the fast transformation towards electrical cars containing new lightweight materials designed considering circular economy practices. However, the adoption of circular practices may result in changing the business model leading to an increase in costs, especially in the initial phase as for redesigning the production plant or including the recycling of resources. It is therefore necessary that the company that decides to implement a plan of action based on the circular economy has understood the possible motivations, benefits and difficulties that may arise during implementation. An analytical framework has been defined and proposed to four companies' suppliers in the automotive sector to identify an appropriate plan of actions that are necessary for the effective implementation of a circular business model in this context. The methodology includes the analysis of different factors and different stages of the product (material phase, product design, production, and distribution, use and end of life phases) verifying three dimensions of circularity: circular practices, circular maturity, and circular strategies. This reference scheme is subsequently taken up in a development and implementation roadmap, where the principles set out are developed during the different life phases.
Quantitative tools for perfecting species lists

A substantial body of literature has accumulated on the topic of the estimation of species richness by extrapolation. However, most of these methods rely on an objective sampling of nature. This condition is difficult to meet and seldom achieved for large regions. Furthermore, scientists conducting biological surveys often already have preliminary but subjectively gathered species lists, and would like to assess the completeness of such lists, and/or to find a way to perfect them. We propose several strategies for utilizing external data (such as might be obtained using GIS) to aid in the completion of species lists. These include: (i) using existing species lists to develop predictive models; (ii) using the uniqueness of the environment as a guide to find underrepresented species; (iii) using spectral heterogeneity to locate environmentally heterogeneous regions; (iv) combining surveys with statistical model‐building in an iterative manner. We demonstrate the potential of these approaches using simulation and case studies from Oklahoma. Copyright © 2002 John Wiley & Sons, Ltd.
Eating Activity Monitoring in Home Environments Using Smartphone-Based Video Recordings

Food intake monitoring plays an important role in personal dietary systems. Existing video based eating activity monitoring systems typically use recordings taken with an identical device in a single laboratory settings. In contrast, we explore videos recorded using smartphones for recognizing eating gestures in home environments. For this purpose, we collected 20 eating sessions from 14 participants using different smartphones. Specifically, the data is labelled into eating and no-eating classes. To recognize eating activity from video we have employed three deep learning approaches namely, 3D CNN, SlowFast network, and CNN-LSTM. Our approach has achieved the best F1-score of 0.560 with SlowFast network when evaluated using the Leave-One-Subject-Out (LOSO) scheme. Our preliminary results suggest that the video-based food intake monitoring can be used in home environments. However, our models failed to recognize the eating activity when the user tend to bend to pick food from the plate. More videos with such eating styles need to be incorporated in training data to enhance the performance.
Dauntless Research and Development Investments of Deficit Senior-Star Biotech Firms in the Valley of Death

This paper focuses on “senior-star” biotech firms as the study target instead of the recently designed NASDAQ Junior Biotechnology Index. We are more interested in the limited number of top-performing “star” players in “senior” biotech firms rather than the much younger and promising next-generation firms. In the market capitalization, these senior biotech firms comprise the top-tier elite class in the head part of the Zipf distribution. Some senior negative-profit (N.P.) biotech firms are willing to increase the deficits for more active investment in research and development (R&D). According to the Bayesian Markov chain Monte Carlo analysis applied to the FY2020 US Securities and Exchange Commission dataset of the electronic data-gathering, analysis, and retrieval system, the R&D productivity of the N.P. Biotech firms are higher than their positive-profit counterparts. Thus, for senior-star biotech firms to overcome the valley of death, R&D investment can be considered a call option in real options by regarding the cash-on-hand as an underlying asset and the deficit as a strike price.
Uncertainties Management from the Hard and Soft approach, in projects of Brazilian Aerospace Sector

Over the past three decades, the discipline of project management has evolved in the sense of considering the differences between projects. The traditional management approach has given rise to a more flexible approach adapted to the project characteristics, considering its contingencies. The aerospace sector has recognized the importance of the contingency approach since the projects in this sector are complex, with different degrees of innovation and, therefore, varying levels of uncertainty. This article provides an empirical advance on uncertainty management in aerospace projects from the Hard and Soft approach. The research method used was the Case Study. Four cases from the Brazilian aerospace sector were analyzed, two from Embraer and two from INPE. For these cases, the Hard and Soft categorization system was applied at different stages of the life cycle, through different methods and to meet different purposes. The results show that the Hard and Soft approach is effective in identifying and managing project uncertainties.
Towards an analytical framework to analyse the evolution of innovation systems

The global manufacturing industry plummeted in 2020 due to the COVID-19 pandemic. To ensure the resilient and sustainable fostering of novel manufacturing innovations, the innovation system within which innovations are developed should be nurturing and supportive. Therefore, an analytical framework may be developed to guide innovators through the evaluation of manufacturing innovation systems. To develop the framework, the Design Science Research methodology is utilised, this paper presenting the theoretical framework development phase. The literature on the innovation system framework is utilised to develop a synthesis of innovation system tools to develop a CIMO-based EHA framework - an evolutionary guide to study a system's development over time to determine the influence of context, how and where transformation occurred, and the impact it had on the system's development. The framework also provides a method to define a system's outputs and socio-economic outcomes.
Fatigue detection for public transport drivers under the normalization of epidemic prevention

Several studies have shown that fatigue driving is one of the important causes of public transport safety accidents. With the outbreak of the COVID-19, the wearing of masks by public transport drivers presents new challenges for computer-based visual fatigue detection. In order to achieve the goal of accurately capturing the landmark information of the face even when the face is occluded by a large area, we adopt the DNN-based face detection method which has the highest accuracy and the best occlusion resistance. When the driver's face is blocked, the landmark information of the blocked face can be accurately detected by using our optimized face landmark detector. The accuracy rate of landmark recognition can reach 97.80%. On this basis, we calculate the driver's eye information, mouth information and the driver's head deflection angle information in real time as the judgment indicators of the degree of fatigue to comprehensively evaluate the driver's fatigue state. And use mathematical methods to fuse indicators in real time, classify the driver's fatigue state according to the value of the fusion indicators, and adopt different early warning methods for different levels of fatigue. In addition, in order to further improve the accuracy of the detection results and exclude the influence of other facial behaviors on our fatigue judgment indicators, we propose a kinetic energy calculation formula for facial organs based on the improved optical flow method. According to the different kinetic energy of facial organs in different states, which can accurately distinguish the different behaviors of the same facial organs such as blinking and closing eyes, yawning and speaking, which significantly increases the robustness and generalization ability of the detection program. The final experimental results show that the correct rate of the method for determining the degree of fatigue of the driver and passengers can reach 98.40% and 92.30% respectively when the driver does not wear a mask or wears a mask.
Self‐consistent modeling of accumulation layers and tunneling currents through very thin oxides

Poisson and Schrodinger equations are solved self‐consistently for accumulated layers in metal‐oxide‐semiconductor devices and applied to the calculation of tunneling currents at 300 K and 77 K and extraction of parameters for very thin oxides. Calculations at 300 K show strong agreement with measured tunneling currents and also point out the sources of inaccuracies in extracting thicknesses of oxides by electrical methods such as through measurement of capacitance. Direct tunneling current in thin oxides (1.5–2.0 nm) are shown to achieve larger than 1 A /cm2 current density for applied voltages smaller than 3 V, pointing to possibilities of achieving high endurance injection across thin oxides. Comparison of calculations using a classical approach and self‐consistent approach shows fortuitous agreements in tunneling currents despite large differences in the physical models. Appropriate methods for calculating tunneling currents from bound and extended quantum states are also described.