nils-herrmann/clean_scirepeval huggingface dataset:
Displacement sensing by direct mechanical modulation of shaped electro-active micro structures

The development of a class of transducers designed to measure the relative displacement between two mechanical members and transmit that information, in coordination with other transducers, over a multiplexed bus with a minimum number of wires is described. As their basis, these transducers use the measurement of the variation in capacitive coupling between very small circuit elements on the surface of a silicon chip and AC field emitting elements on an adjacent planar structure. The circuit elements, which function as field detectors, generate signals that are used to estimate the position of the field emitting structure in digital or analog form. The transducer package, detector systems, emitter system, and supporting electronic circuits are discussed.<<ETX>>
A filter based bit allocation scheme for subband compression of HDTV

The authors compare the subband compression capabilities of eight filter sets (consisting of linear-phase quadrature mirror filters (QMFs), perfect reconstruction filters, and nonlinear phase wavelets) at different bit rates, using-a filter-based bit allocation procedure. Using DPCM and PCM in HDTV subband coding, it is found that QMFs have an edge over the rest.
Construction and use of roadmaps that incorporate workspace modeling errors

Probabilistic Roadmap Methods (PRMs) have been shown to work well at solving high Degree of Freedom (DoF) motion planning problems. They work by constructing a roadmap that approximates the topology of collision-free configuration space. However, this requires an accurate model of the robot's workspace in order to test if a sampled configuration is in collision or not. In this paper, we present a method for roadmap construction that can be used in workspaces with uncertainties in the model. For example, these can be inaccuracies that are caused by sensor error when an environment model was constructed. The uncertainty is encoded into the roadmap directly through the incorporation of non-binary collision detection values, e.g., a probability of collision. We refer to this new roadmap as a Safety-PRM because it allows tunability between the expected safety of the robot and the distance along a path. We compare the computational cost of Safety-PRM against two planning methods for environments without modeling errors, basic PRM and Medial Axis PRM (MAPRM), known for low computational cost and maximizing clearance, respectively. We demonstrate that in most cases, Safety-PRM produces high quality paths maximized for clearance and safety with the least amount of computational cost. We show that these paths are tunable for both robot safety and clearance. Finally, we demonstrate the applicability of Safety-PRM on an experimental system, a Barrett Whole Arm Manipulator (WAM). On the WAM, we demonstrate the mapping of expected collision to robot speeds to enable the robot to physically test the safety of the roadmap and use torque estimation to make roadmap modifications.
The Amulet chips: Architectural development for asynchronous microprocessors

During the 1990s a series of asynchronous microprocessors based on the ARM architecture was developed at the University of Manchester. The objective was to demonstrate that it was feasible to implement a commercial architecture with asynchronous logic and that certain advantages could be gained from a self-timed processor. By carrying these designs through to silicon it was demonstrated that processors, caches and whole systems-on-chip could be built without clocks and could perform competitively with ‘conventional’, synchronous systems.
Beyond the shortest path: Unsupervised domain adaptation by Sampling Subspaces along the Spline Flow

Recently, a particular paradigm [18] in the domain adaptation field has received considerable attention by introducing novel and important insights to the problem. In this case, the source and target domains are represented in the form of subspaces, which are treated as points on the Grassmann manifold. The geodesic curve between them is sampled to obtain intermediate points. Then a classifier is learnt using the projections of the data onto these subspaces. Despite its relevance and popularity, this paradigm [18] contains some limitations. Firstly, in real-world applications, that simple curve (i.e. shortest path) does not provide the necessary flexibility to model the domain shift between the training and testing data sets. Secondly, by using the geodesic curve, we are restricted to only one source domain, which does not allow to take fully advantage of the multiple datasets that are available nowadays. It is then, natural to ask whether this popular concept could be extended to deal with more complex curves and to integrate multi-sources domains. This is a hard problem considering the Riemannian structure of the space, but we propose a mathematically well-founded idea that enables us to solve it. We exploit the geometric insight of rolling maps [30] to compute a spline curve on the Grassmann manifold. The benefits of the proposed idea are demonstrated through several empirical studies on standard datasets. This novel concept allows to explicitly integrate multi-source domains while the previous one [18] uses the mean of all sources. This enables to model better the domain shift and take fully advantage of the training datasets.
Per-Sequence Vector-Switching Matrix Converter Modules for Voltage Regulation

This paper proposes a novel dynamic voltage restorer (DVR) topology based on reduced-order matrix converter modules. The topology utilizes two modules for selective and independent sequence voltage synthesis. As a result, the DVR proposed herein can compensate for balanced as well as unbalanced voltage sags/swells. Each module is realized using a vector-switching matrix converter. The entire topology is energy storage free, and each module is pulsewidth modulated using simple dc duty ratios. This paper provides details on the DVR modeling, equivalent circuit, and feedback controller design. Thorough computer simulations and experimental prototyping are used to validate the approach.
Dynamic Ramping Model Including Intraperiod Ramp-Rate Changes in Unit Commitment

The growing increase of renewable generation worldwide is posing new challenges for a secure, reliable, and economic operation of power systems. In order to face the uncertain and intermittent production of renewable sources, operating reserves must be allocated efficiently and accurately. Nowadays, these reserves are mainly assigned to thermal units, especially gas-fired generators, due to their operation flexibility and fast response. However, the ramping capabilities of these units define the grade of flexibility offered to the system operation. In practical applications, ramping limits are dynamic, i.e., they are a function of the unit's generating output. Omitting this feature leads to suboptimal or even infeasible reserve allocations, thus increasing not only operating reserve requirements but also transactions in real-time balancing markets needed to back up deviations of renewable generation. This paper contributes with a mixed-integer linear programming model for units' dynamic ramping allowing intraperiod changes in the unit commitment problem. As a result, operating reserves are better allocated and the units' flexibility is managed more efficiently than traditional ramping models found in the literature. Different case studies illustrate the functioning and benefits of the proposed formulation.
Load forecasting via detrending and deseasoning

Load forecasting is a term usually applied to describe a process of estimation or prediction of future energy demand for a certain distribution grid or part of a grid. Large number of different methods and techniques used for load forecasting have been developed in the past and new and improved methods are regularly being reported in research literature. This paper describes one of traditional load forecasting approaches based on autoregressive moving average (ARMA) modelling of load demand time-series (TS). However, it reconsiders each step in this process and proposes some new procedures to improve and clarify the whole method. Effectives of described approach is demonstrated using energy consumption measurements recently recorded at substations in central London area.
High-Resolution Optical Thickness Measurement Based on Electro-Optic Dual-Optical Frequency Comb Sources

We propose an optical thickness measurement device based on electro-optic dual-optical frequency combs (dual-OFCs). Optical frequency combs (OFCs) are light sources that provide an optical signal consisting of many equidistant monochromatic tones. In this paper, we present an agile dual-OFC architecture with adjustable frequency separation of the comb modes and total frequency span, allowing high-resolution measurements of the thickness of transparent thick samples. This architecture is based on a single continuous-wave laser diode and external electro-optic devices to implement the dual-comb sensor, allowing easy control of the optical spectrum of the interrogation source (dual-OFC). As it is characteristic of dual-OFC systems, the optical transmittance function of the sample (etalon) is directly translated to the radiofrequency domain, where detection, demodulation, and processing of signals are performed. The shift in the complexity of implementation from the optical to the electronic domain yields many advantages, as acquisition and signal processing are made independently on the optical characteristics of the sample (thickness).
Accurate single view model-based head pose estimation

A framework for automatic human head pose estimation from single view images is proposed. The 6DOF head pose was estimated using pose from orthography and scaling with iterations (POSIT) where a statistical anthropometric 3D rigid model is used as an approximation of the human head, combined with active appearance models (AAM) for facial features extraction and tracking. The overall performance of the proposed solution was evaluated comparing the results with a ground-truth data obtained by a pose planar approach. The results show that orientations and head location were, on average, found within 2deg or 1 cm error standard deviations respectively.
Fully Adaptable Electro-Optic Dual-Comb Generation

In this letter, an all-electronic method that provides a precise control over the number of spectral lines of an electro-optic frequency comb is presented and experimentally validated. This feature, in conjunction with the straightforward configuration of the optical resolution (repetition frequency) inherent to electro-optic combs, enables the generation of optical comb sources with the unique capability of a complete adaptability to the targeted spectral feature/s that could ultimately maximize the SNR of any electro-optic comb-based spectroscopic measurement.
Stack Overflow in Github: Any Snippets There?

When programmers look for how to achieve certain programming tasks, Stack Overflow is a popular destination in search engine results. Over the years, Stack Overflow has accumulated an impressive knowledge base of snippets of code that are amply documented. We are interested in studying how programmers use these snippets of code in their projects. Can we find Stack Overflow snippets in real projects? When snippets are used, is this copy literal or does it suffer adaptations? And are these adaptations specializations required by the idiosyncrasies of the target artifact, or are they motivated by specific requirements of the programmer? The large-scale study presented on this paper analyzes 909k non-fork Python projects hosted on Github, which contain 290M function definitions, and 1.9M Python snippets captured in Stack Overflow. Results are presented as quantitative analysis of block-level code cloning intra and inter Stack Overflow and GitHub, and as an analysis of programming behaviors through the qualitative analysis of our findings.
Virtual and augmented reality game-based applications to civil engineering education

Gaming scenarios and virtual environments have shown beneficial results in Engineering Education. Various activities conducted in different fields demonstrate that students reveal appraisal for the integration of innovative technologies such as Virtual or Augmented Reality in the learning process. In this paper, Virtual Reality (VR) applications developed by first year students during an introductory class of the Integrated Masters in Civil Engineering are described. Additionally, two trials concerning the application of VR and Augmented Reality (AR) to Civil Engineering held at a local school (K-12 students) are also detailed. After the tests, students were surveyed and data was collected. Results and considerations are revealed in the final sections of this paper.
FPGA-Based Implementation of a Predictive Current Controller for Power Converters

Predictive control is generating considerable interest when it comes to implementing current control strategies in power converters. Remarkable accuracy and fast dynamic response are its main characteristics. However, this technique is computationally demanding compared to classic control schemes. This is particularly true in multilevel converters, where several variables of the system such as currents, switching frequency and neutral-point voltage balancing, to name a few, are controlled simultaneously. An important issue is to reduce the delay between the variable sampling and the instant at which the switching state is applied to the converter. Although DSP-based implementations have been proven to be an effective solution, the parallel nature of predictive controllers better fits with the architecture of field-programmable gate array (FPGA) devices. This paper presents a new approach to the FPGA-based implementation of a predictive current controller for a multilevel converter. This approach also aims to reduce the average switching frequency and obtain neutral-point voltage balancing. The switching state is applied in the same sampling period in which the controlled variables are measured thereby enhancing the dynamic response of the system.
Induced magnetoelectric effect driven by magnetization in BaFe12O19/P(VDF-TrFE) composites

In the last years the fabrication of multifunctional composite materials like the mixture of piezoelectric polymers with magnetic/magnetostrictive nanoparticles to give as result magnetoelectric (ME) composites has received great effort . P(VDF-TrFE), in the poled ferroelectric phase, exhibits one of the highest piezoelectric responses among polymer materials over a wide range of temperature depending on its composition. Among ferrites, the ferrimagnetic material barium ferrite (BaFe12O19) shows particular magnetic properties as high coercive force and hysteresis losses. Despite its very low magnetostriction (9 ppm), Barium ferrite has very high magnetocrystalline anisotropy in the low-symmetry hexagonal magnetoplumbite crystal structure with hexagonal unit cell. Although barium ferrite particles have the shape of thin hexagonal platelets, the easy direction of magnetization remains along the c axis, which is perpendicular to the plates.
Remote Laboratory for Experimentation With Multilevel Power Converters

This paper describes the hardware and software modules of a remote Internet-based laboratory for experimentation with a 120-kVA multilevel power converter. The key feature of this laboratory is the utilization of a multilevel converter that can be controlled and supervised remotely in a secured way. A wide variety of laboratory experiments are supported, from grid connection to AC motor control. Users can choose the control structure, the control parameters, and the kind of load and get the graphical results of the measurements, all in real time.
SmellSheet detective: A tool for detecting bad smells in spreadsheets

This tool demo paper presents SmellSheet Detective: a tool for automatically detecting bad smells in spreadsheets. We have defined a catalog of bad smells in spreadsheet data which was fully implemented in a reusable library for the manipulation of spreadsheets. This library is the building block of the SmellSheet Detective tool, that has been used to detect smells in large, real-world spreadsheets within the EUSES corpus, in order to validate and evolve our bad smells catalog.
Sampling Rate and Data Quality Issues: Experiments from Ginseng Industrial Deployment

Industrial plants such as oil refineries typically use wired sensor systems to monitor and control the production processes. As the deployment and maintenance of such cabled systems are expensive, it is desirable to replace or augment these systems using wireless technology. Wireless sensor networks (WSNs) are deployed to sense, monitor and act on the environment. Especially in industrial sense and react scenarios that require fairly fast sampling rates, minimum losses and minimum latency on messages. Considering that a few sensors may share a common sink, sharing part of their path on the way to the sink may result in undesirable message losses and delays. Our research focuses on planning a WSN to avoid excess traffic during sensing and acting to guarantee the minimal delay for critical scenarios, such as industrial applications and closed-loop control applications. In this paper we report on our experience with both a simple plan for adapting a WSN for high-rate sampling objectives and with experimental tests. Simple theoretical results let us know whether a network plan will be able to handle data processing as required. With this first-cut plan we can then test the performance of the network and if necessary reconfigure it. Basic data quality issues are also taken into account. Different characteristics can be chosen depending on application needs, resulting in reconfiguration of network parameters (number of nodes, network partitions or reduction of the sampling rate or application of filters to the data). We report on the experimental results in a test bed and industrial environment.
A configurable middleware for processing in heterogeneous industrial intelligent sensors

Sensor and Actuator Networks (SAN) are distributed systems deployed to sense, monitor and act on the environment. They may include any of the following: sensors, wiring, embedded system components, wireless communication and backbone servers. Given current technological advances, costs and flexibility advantages of wireless sensor networks technology, wireless SAN (WSAN) deployments are being considered in such environments. WSAN nodes are small embedded devices that provide sensing, acting and (limited) in-network processing capabilities. From a system point-of-view the whole industrial network is a hardware and software heterogeneous distributed system with some computation-capable nodes (WSAN nodes and servers). A significant research challenge is how to provide a single homogeneous interface that allows configuration and operation of any computation-capable node or group of nodes and hides node heterogeneity, as opposed to hand-coding every component of the system for every minor or major configuration change and/or having multiple configuration systems. In this paper we propose a homogeneous configuration approach over heterogeneous WSAN networks. Our approach was successfully tested in an industrial refinery setting, allowing deployers to configure and re-configure the system to meet specific needs.
Dynamic modeling and control of an AC-link dynamic voltage restorer

This paper introduces the dynamic modeling along with a control strategy for a novel dynamic voltage restorer (DVR). This DVR is realized using phase-shifting transformers, an AC-link, and a vector switching matrix converter as building blocks. It has the ability of independently and selectively generating positive as well as negative sequence voltages, and hence it can compensate for different kinds of sags. The dynamic model along with a feedback controller design procedure are discussed in detail. Experimental waveforms under closed-loop regulation using a laboratory prototype are presented in order to validate the approach.
PLAMER: Information system for bids analysis and forecasting of the Iberian Electricity Market

This paper describes a strategic information platform developed for the German electric utility Eon, to provide historical bidding analysis and medium-term forecasting of the Iberian Electricity Market. This platform, PLAMER, has three main modules: Initialization module, consisting of different sub-modules to define the electrical system structure and to organize the input data of the rest of modules, PLAMER-bids, to read, aggregate and visualize market historical bids and also to prepare them for their future forecasted values, and PLAMER-clearing, for market clearing emulation using forecasted bids. PLAMER-clearing models the Iberian market based on a bid clearing mechanism with an inherent market splitting procedure. This market splitting is built with a bi-nodal simplification, one node representing the Spanish System and the other the Portuguese one. Both are simply connected by a unique equivalent interconnection line. The medium term clearing model uses a generation portfolio per generation company in terms of technologies, for supplying monthly demand for different load levels, and labour and non-labour periods. Some technical constraints, such as minimum outputs and pumping energy balance, are also taking into account. The mathematical problem of PLAMER-clearing is a quadratic programming model solved using GAMS language and CPLEX optimizer. Finally, a real Iberian case study is detailed and some market splitting outputs are analyzed.
Single view head pose estimation

This work addresses the problem of human head pose estimation from single view images. 3D rigid head pose is estimated combining Active Appearance Models(AAM) with Pose from Orthography and Scaling with ITerations(POSIT). AAM shape landmarks are tracked over time and used in POSIT for pose estimation. A statistical anthropometric 3D model is used as reference. Several experiences were performed comparing our approach with a planar ground truth. It was achieved average standard deviations about 2 degrees in orientation and 1 centimeter in distance.
A high step-up DC-DC converter with MPPT for PV application

This paper exhibits the performance of a high step-up converter employed for maximum power extraction in a photovoltaic system. The proposed converter is conformed by a conventional boost followed by a diode-capacitor-based multiplier for increasing the nominal voltage gain of the boost converter, resulting in a lower duty cycle at the maximum power point. The main characteristics of the converters are analyzed in order to determine an optimal equivalent input impedance. Evaluation of the proposed converter using standard Perturb and Observe algorithm is carried out. Switching simulations evidence the good performance of the whole system under irradiance disturbances.