nils-herrmann/clean_scirepeval huggingface dataset:
Discrete chirp-Fourier transform and its application to chirp rate estimation

The discrete Fourier transform (DFT) has found tremendous applications in almost all fields, mainly because it can be used to match the multiple frequencies of a stationary signal with multiple harmonics. In many applications, wideband and nonstationary signals, however, often occur. One of the typical examples of such signals is chirp-type signals that are usually encountered in radar signal processing, such as synthetic aperture radar (SAR) and inverse SAR imaging. Due to the motion of a target, the radar return signals are usually chirps, and their chirp rates include the information about the target, such as the location and the velocity. In this paper, we study discrete chirp-Fourier transform (DCFT), which is analogous to the DFT. Besides the multiple frequency matching similar to the DFT, the DCFT can be used to match the multiple chirp rates in a chirp-type signal with multiple chirp components. We show that when the signal length is prime, the magnitudes of all the sidelobes of the DCFT of a quadratic chirp signal are 1, whereas the magnitude of the mainlobe of the DCFT is . With this result, an upper bound for the number of the detectable chirp components using the DCFT is provided in terms of signal length and signal and noise powers. We also show that the -point DCFT performs optimally when is a prime.
Hierarchical control for parallel bidirectional power converters of a grid-connected DC microgrid

The DC microgrid is connected to the AC utility by parallel bidirectional power converters (BPCs) to import/export large power, whose control directly affects the performance of the grid-connected DC microgrid. Much work has focused on the hierarchical control of the DC, AC, and hybrid microgrids, but little has considered the hierarchical control of multiple parallel BPCs that directly connect the DC microgrid to the AC utility. In this paper, we propose a hierarchical control for parallel BPCs of a grid-connected DC microgrid. To suppress the potential zero-sequence circulating current in the AC side among the parallel BPCs and realize feedback linearization of the voltage control, a d-q-0 control scheme instead of a conventional d-q control scheme is proposed in the inner current loop, and the square of the DC voltage is adopted in the inner voltage loop. DC side droop control is applied to realize DC current sharing among multiple BPCs at the primary control level, and this induces DC bus voltage deviation. The quantified relationship between the current sharing error and DC voltage deviation is derived, indicating that there is a trade-off between the DC voltage deviation and current sharing error. To eliminate the current sharing error and DC voltage deviation simultaneously, slope-adjusting and voltage-shifting approaches are adopted at the secondary control level. The proposed tertiary control realizes precise active and reactive power exchange through parallel BPCs for economical operation. The proposed hierarchical control is applied for parallel BPCs of a grid-connected DC microgrid and can operate coordinately with the control for controllable/uncontrollable distributional generation. The effectiveness of the proposed control method is verified by corresponding simulation tests based on Matlab/Simulink, and the performance of the hierarchical control is evaluated for practical applications.
RiskTeller: Predicting the Risk of Cyber Incidents

The current evolution of the cyber-threat ecosystem shows that no system can be considered invulnerable. It is therefore important to quantify the risk level within a system and devise risk prediction methods such that proactive measures can be taken to reduce the damage of cyber attacks. We present RiskTeller, a system that analyzes binary file appearance logs of machines to predict which machines are at risk of infection months in advance. Risk prediction models are built by creating, for each machine, a comprehensive profile capturing its usage patterns, and then associating each profile to a risk level through both fully and semi-supervised learning methods. We evaluate RiskTeller on a year-long dataset containing information about all the binaries appearing on machines of 18 enterprises. We show that RiskTeller can use the machine profile computed for a given machine to predict subsequent infections with the highest prediction precision achieved to date.
PMCW waveform and MIMO technique for a 79 GHz CMOS automotive radar

Automotive radars in the 77-81 GHz band will be widely deployed in the coming years. This paper provides a comparison of the bi-phase modulated continuous wave (PMCW) and linear frequency-modulated continuous wave (FMCW) waveforms for these radars. The comparison covers performance, implementation and other non technical aspects. Multiple Input Multiple Output (MIMO) radars require perfectly orthogonal waveforms on the different transmit antennas, preferably transmitting simultaneously for fast illumination. In this paper, we propose two techniques: Outer code and Range domain, to enable MIMO processing on the PMCW radars. The proposed MIMO techniques are verified with both simulation and lab experiments, on a fully integrated deep-submicron CMOS integrated circuit designed for a 79 GHz PMCW radar. Our analysis shows that, although not widely used in the automotive industry, PMCW radars are advantageous for low cost, high volume single-chip production and excellent performance.
A novel dual-rotor hybrid machine with synchronous reluctance and surface permanent magnet rotors

The goal of this paper is to investigate a proposed novel dual-rotor hybrid synchronous machine using two different types of rotors, i.e. the synchronous reluctance (SyR) and surface permanent magnet (SPM) rotors. Conventional design of dual-rotor machine utilizes SPM rotors on both inner and outer sides with toroidal winding configuration. However, there are limitations of using the permanent magnet in the inner rotor such as centrifugal forces on the magnets at high rotational speed conditions and relatively low torque density if ferrite permanent magnets are used. This research proposed a novel topology by using a well-designed SyR rotor to replace the inner SPM rotor in the conventional design. The principle of operation including combined space vector diagram of the novel dual-rotor hybrid machine is discussed. Sizing equations of the proposed machine are derived to show the calculation of output power from key dimensions and electrical and magnetic loading conditions. The N-N and N-S configurations of the novel dual-rotor machine are compared. The performance of the novel machines is studied against the conventional dual-rotor surface permanent magnet machine by finite element analysis (FEA) to demonstrate that the proposed machines achieve higher torque densities with less permanent magnet consumption. The proposed N-S machine is also scaled for the traction motor specification and compared to a conventional interior PM machine.
A framework for teaching software development methods

This article presents a study that aims at constructing a teaching framework for software development methods in higher education. The research field is a capstone project-based course, offered by the Technion’s Department of Computer Science, in which Extreme Programming is introduced. The research paradigm is an Action Research that involves cycles of data collection, examination, evaluation, and application of results. The research uses several research tools for data gathering, as well as several research methods for data interpretation. The article describes in detail the research background, the research method, and the gradual emergence process of a framework for teaching software development methods. As part of the comprehensive teaching framework, a set of measures is developed to assess, monitor, and improve the teaching and the actual process of software development projects.
Reengineering the Naval Ship Concept Design Process

Naval ship concept design is very much an “ad hoc” process. Selection of design concepts for assessment is guided primarily by experience, design lanes, rules-of-thumb, preference and imagination. Objective attributes are not adequately synthesized or presented to support efficient and effective decisions. Attributes are often qualitative, inconsistent, and not provided to design engineers in a format they can use. The design space is very large, non-linear, discontinuous, and bounded by a variety of constraints and thresholds. These problems make a structured search of design space difficult. Without a structured search, there is no rational way to measure the optimality of selected concepts relative to the millions of other concepts that have not been considered or assessed. Responsible decisions cannot be made without this information and perspective. This paper addresses these problems in the context of a systems approach to naval ship concept design. Multiattribute value theory (MAVT) and the Analytical Hierarchy Process (AHP) are used to synthesize an effectiveness function. A Pareto Genetic Algorithm (PGA) searches design parameter space and identifies non-dominated design concepts in terms of cost and effectiveness. Design concepts are presented graphically as points on a nondominated cost-effectiveness frontier for consideration by decision-makers. A simplified surfacecombatant design demonstrates the process.
Brand Name , Sales Promotion and Consumers ’ Online Purchase Intention for Cell-phone Brands

Although “Internet” has become a wide channel for commercial transactions, yet most people have different concerns in trading through this media, especially within developing countries. This research seeks to examine the final impact of brand name and sales promotion, as two powerful marketing strategies, on consumers’ online purchase intention, considering perceived quality, perceived value and store image as possible mediating variables affecting the decision making of consumers. For this purpose, two cell-phone brands (a well-known vs. to a less-known brand) were studied among 248 professors, employees and students from University of Tabriz, in IRAN. The required data was gathered by questionnaire and analyzed using SPSS and AMOS GRAPHICS soft-wares. The results indicate that online cell-phone stores in IRAN should respectively consider the importance of (1) strengthening their online store’s image, (2) managing advertisements and increasing public awareness toward their brand, (3) upgrading service quality and (4) providing effective promotions to attract consumers over time.
Answering Science Exam Questions Using Query Reformulation with Background Knowledge

Open-domain question answering (QA) is an important problem in AI and NLP that is emerging as a bellwether for progress on the generalizability of AI methods and techniques. Much of the progress in open-domain QA systems has been realized through advances in information retrieval (IR) methods and corpus construction. In this paper, we focus on the recently introduced ARC Challenge dataset, which contains 2,590 multiple choice questions authored for grade-school science exams. These questions are selected to be the most challenging for current QA systems, and current state of the art performance is only slightly better than random chance. We present a system that reformulates a given question into queries that are used to retrieve supporting text from a large corpus of science-related text. Our rewriter is able to incorporate background knowledge from ConceptNet. In tandem with a generic textual entailment system trained on SciTail that identifies support in the retrieved results, our system outperforms several strong baselines on the end-to-end QA task despite only being trained to identify essential terms in the original source question. We use a generalizable decision methodology – over the retrieved evidence and answer candidates – to select the best answer. By combining query reformulation, background knowledge, and textual entailment, our system is able to outperform several strong baselines on the ARC dataset.
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices

Discrimination via algorithmic decision making has received considerable attention. Prior work largely focuses on defining conditions for fairness, but does not define satisfactory measures of algorithmic unfairness. In this paper, we focus on the following question: Given two unfair algorithms, how should we determine which of the two is more unfair? Our core idea is to use existing inequality indices from economics to measure how unequally the outcomes of an algorithm benefit different individuals or groups in a population. Our work offers a justified and general framework to compare and contrast the (un)fairness of algorithmic predictors. This unifying approach enables us to quantify unfairness both at the individual and the group level. Further, our work reveals overlooked tradeoffs between different fairness notions: using our proposed measures, the overall individual-level unfairness of an algorithm can be decomposed into a between-group and a within-group component. Earlier methods are typically designed to tackle only between-group un- fairness, which may be justified for legal or other reasons. However, we demonstrate that minimizing exclusively the between-group component may, in fact, increase the within-group, and hence the overall unfairness. We characterize and illustrate the tradeoffs between our measures of (un)fairness and the prediction accuracy.
On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services

Firms in the financial services industry have been faced with the dramatic and relatively recent emergence of new technology innovations, and process disruptions. The industry as a whole, and many new fintech start-ups are looking for new pathways to successful business models, the creation of enhanced customer experience, and new approaches that result in services transformation. Industry and academic observers believe this to be more of a revolution than a set of less impactful changes, with financial services as a whole due for major improvements in efficiency, in customer centricity and informedness. The long-standing dominance of leading firms that are not able to figure out how to effectively hook up with the “Fintech Revolution” is at stake. This article presents a new fintech innovation mapping approach that enables the assessment of the extent to which there are changes and transformations in four key areas of the financial services industry. We discuss: (1) operations management in financial services, and the changes that are occurring there; (2) technology innovations that have begun to leverage the execution and stakeholder value associated with payments settlement, cryptocurrencies, blockchain technologies, and cross-border payment services; (3) multiple fintech innovations that have impacted lending and deposit services, peer-to-peer (P2P) lending and the use of social media; (4) issues with respect to investments, financial markets, trading, risk management, robo-advisory and related services that are influenced by blockchain and fintech innovations.
Control of Rotary Series Elastic Actuator for Ideal Force-Mode Actuation in Human–Robot Interaction Applications

To realize ideal force control of robots that interact with a human, a very precise actuating system with zero impedance is desired. For such applications, a rotary series elastic actuator (RSEA) has been introduced recently. This paper presents the design of RSEA and the associated control algorithms. To generate joint torque as desired, a torsional spring is installed between a motor and a human joint, and the motor is controlled to produce a proper spring deflection for torque generation. When the desired torque is zero, the motor must follow the human joint motion, which requires that the friction and the inertia of the motor be compensated. The human joint and the body part impose the load on the RSEA. They interact with uncertain environments and their physical properties vary with time. In this paper, the disturbance observer (DOB) method is applied to make the RSEA precisely generate the desired torque under such time-varying conditions. Based on the nominal model preserved by the DOB, feedback and feedforward controllers are optimally designed for the desired performance, i.e., the RSEA: (1) exhibits very low impedance and (2) generates the desired torque precisely while interacting with a human. The effectiveness of the proposed design is verified by experiments.
Expected goals in soccer:explaining match results using predictive analytics

Where data based decision making is taking over businesses and elite sports, elite soccer is lacking behind. In elite soccer, decisions are still often based on emotions and recent results. As results are, however, dependent on many aspects, the reasons for these results are currently unknown by the elite soccer clubs. In our study, a method is proposed to determine the expected winner of a match. Since goals are rare in soccer, goal scoring opportunities are analyzed instead. By analyzing which team created the best goal scoring opportunities, a feeling can be created which team should have won the game. Therefore, it is important that the quality of goal scoring opportunities accurately reflect reality. Therefore, the proposed method ensures that the quality of a goal scoring opportunity is given as the probability of the goal scoring opportunity resulting in a goal. It is shown that these scores accurately match reality. The quality scores of individual goal scoring opportunities are then aggregated to obtain an expected match outcome, which results in an expected winner. In little more than 50% of the cases, our method is able to determine the correct winner of a match. The majority of incorrect classified winners comes from close matches where a draw is predicted. The quality scores of the proposed method can already be used by elite soccer clubs. First of all, these clubs can evaluate periods of time more objectively. Secondly, individual matches can be evaluated to evaluate the importance of major events during a match e.g. substitutions. Finally, the quality metrics can be used to determine the performance of players over time which can be used to adjust training programs or to perform player acquisition. Expected Goals in Soccer: Explaining Match Results using Predictive Analytics iii
Marketing Models of Service and Relationships 1

Given the growth of the service sector, and advances in information technology and communications that facilitate the management of relationships with customers, models of service and relationships are a fast-growing area of marketing science. This article summarizes existing work in this area and identifies promising topics for future research. Models of service and relationships can help managers manage service more efficiently, customize service more effectively, manage customer satisfaction and relationships, and model the financial impact of those customer relationships. Models for managing service have often emphasized analytical approaches to pricing, but emerging issues such as the tradeoff between privacy and customization are attracting increasing attention. The tradeoffs between productivity and customization have also been addressed by both analytical and empirical models, but future research in the area of service customization will likely place increased emphasis on e-service and truly personalized interactions. Relationship models will focus less on models of customer expectations and length of relationship, and more on modeling the effects of dynamic marketing interventions with individual customers. The nature of service relationships increasingly leads to financial impact being assessed within customer and across product, rather than the traditional reverse, suggesting the increasing importance of analyzing customer lifetime value and managing the firm’s customer equity.
Assessing the Impact of Climate Change on Migration and Conflict

This paper has been commissioned by the World Bank Group for the "Social Dimensions of Climate Change" workshop. Views represented are those of the authors, and do not represent an official position of the World Bank Group or those of the Executive Directors of the World Bank or the overnments they represent. The World Bank does not guarantee the accuracy of data presented in g this paper. This paper was written under contract 7145451 between PRIO and the World Bank for the program on 'Exploring the Social Dimensions of Climate Change'. The opinions expressed in this document represent the views of the authors and do not necessarily state or reflect those of the World Bank. Bibliography 41 iii Executive Summary Climate change is expected to bring about significant changes in migration patterns throughout the developing world. Increases in the frequency and severity of chronic environmental hazards and sudden onset disasters are projected to alter the typical migration patterns of communities and entire countries. We examine evidence for such claims and roundly conclude that large scale community relocation due to either chronic or sudden onset hazards is and continues to be an unlikely response. We propose an alternate framework through which to examine the likely consequences of increased hazards. It is built upon the five major conclusions of this paper: First, disasters vary considerably in their potential to instigate migration. Moreover, individual, community and national vulnerabilities shape responses as much as disaster effects do. Focussing on how people are vulnerable as a function of political, economic and social forces leads to an in-depth understanding of post-disaster human security. Second, individuals and communities in the developing world incorporate environmental risk into their livelihoods. Their ability to do so effectively is contingent upon their available assets. Diversifying income streams is the predominant avenue through which people mitigate increased hazards from climate changes. Labour migration to rural and urban areas is a common component of diversified local economies. In lesser developed countries, labour migration is typically internal, temporary and circular. Third, during periods of chronic environmental degradation, such as increased soil salinization or land degradation, the most common responses by individuals and communities is to intensify labour migration patterns. By doing so, families increase remittances and lessen immediate burdens to provide. Fourth, with the onset of a sudden disaster or the continued presence of a chronic disaster (i.e. drought or famine), communities engage in …