nils-herrmann/clean_scirepeval huggingface dataset:
Comments on "A new controller design for a flexible one link manipulator"

In the original paper of W.T. Qian and C.C.H. Ma (ibid., vol. 37, p. 132-7, 1992), a variable structure sliding mode controller (VSSMC) design for the tip position control of a flexible one-link manipulator has been presented, where a switching line constructed from the tip position and its derivative was employed for the design. The claim was that if the slope of this line is chosen positive and the system variables are made to stay on this line, they will converge to zero exponentially, thus yielding a stable system in sliding mode (SM). The purpose of this comment is to show that the choice of a positive constant as the slope for this switching line will not guarantee the stability of the system in SM because, in view of the functional relationship of the tip position with the generalized coordinates of the system through the mode shape functions, what is presented as a switching line is in fact a switching hypersurface. Hence, the stability of the system in SM is guaranteed only if the motion on this hypersurface is asymptotically stable. A positive value for the slope of the switching line employed by Qian and Ma will not guarantee this stability because variations in the mode shape functions due to varying payload conditions or other disturbances at the tip will lead to a varying switching surface. These variations can be such that the resulting sliding motion becomes unstable. Also, the varying switching surface implies that the controller will fail to maintain sliding mode motion.
A novel estimation of feature-space MLLR for full-covariance models

In this paper we present a novel approach for estimating feature-space maximum likelihood linear regression (fMLLR) transforms for full-covariance Gaussian models by directly maximizing the likelihood function by repeated line search in the direction of the gradient. We do this in a pre-transformed parameter space such that an approximation to the expected Hessian is proportional to the unit matrix. The proposed algorithm is as efficient or more efficient than standard approaches, and is more flexible because it can naturally be combined with sets of basis transforms and with full covariance and subspace precision and mean (SPAM) models.
A mathematical toolbox for the software architect

It is suggested that category theory provides the right level of mathematical abstraction to address languages for describing software architectures. Contrarily to most other formalisations of SA concepts, category theory does not promote any particular formalism for component and connector description but provides instead the very semantics of the concepts that are related to the gross modularisation of complex systems like "interconnection": "configuration", "instantiation" and "composition": Two examples, a category of programs for a parallel program design language and a category of temporal logic specifications, together with comparisons with other work, namely by R. Allen and D. Garlan (1994), and M. Moriconi and X. Qian (1994), are adduced to justify this claim.
A tree search algorithm for target detection in image sequences

Given a time sequence of digital images of a high-noise environment, the authors address the problem of detecting pixel-sized, barely discernible moving objects whose position and trajectories are unknown. The sequences may be temporally sparse and contain significant frame-to-frame drifting background clutter as caused by relative motion between the sensor array and natural terrain, ocean, or clouds. A general, two-step approach is presented. First, time correlation and space-varying background structure are removed. Second, a large, dense set of pixel-sized space-time trajectories are hypothesized and tested in the innovations sequence. The search space is organized into a tree structure. A sequential statistical technique, multistage hypothesis testing, optimized for the innovations model, is used to test the multiple hypotheses and prune the tree-structured list of candidate trajectories.<<ETX>>
Cyber-physical situation awareness and decision support

Cyber-physical situation awareness is essential to management of government services and conduct of business processes. In particular, all of the nation's critical infrastructures depend upon proper operation of supervisory control and data acquisition (SCADA) devices and proper operation of these devices faces threats from possible occurrences of a variety of deliberate and inadvertent cyber events. This paper discusses an ongoing approach for incrementally improving cyber-physical situation awareness by (1) extending previous results for information architecture understanding, (2) sharing protected information among information owners whose knowledge (measurement) of their own state can be improved by choosing to share information with others, and (3) comparing measured cyber-physical system state to predicted cyber-physical system state.
Accelerated wave-reflection solver for traveling-wave-tube simulations

We present our progress on an accelerated algorithm for resolving wave reflections in the parametric, multi-frequency, TWT simulation code CHRISTINE. On the average, it achieves a speedup factor of at least 10 compared with the previously used Newton-type iterative algorithm.Wave reflections in CHRISTINE are modeled by the coupled wave equations for the forward and backward wave complex amplitudes of the associated Fourier modes. These equations must be solved subject to appropriate boundary conditions imposed at the ends of the interaction space, z=0 and z=L. Since CHRISTINE integrates the wave equations and the equations of motion of the beam in z from z=0 to z=L, the solutions for the forward and backward wave amplitudes may be obtained iteratively One way to do this is to employ a multi-dimensional Newton's method to find the initial amplitudes. The convergence of this method is very slow, however, when the number of Fourier modes is large. By expressing the reflected wave equations as a nonlinear fixed-point problem we were able to implement a much faster and more robust algorithm via an iterative, multi-dimensional, fixed point solver, based on the modified Powell's hybrid method2. For instance, using this new algorithm to resolve reflections for an input waveform with 64 Fourier modes, we have observed a speedup factor of about 10 compared to the previous version of CHRISTINE. We are currently investigating the numerical aspects of utilizing this approach to resolve wave reflections in the 3dimensional code CHRISTINE 3D. In this case we anticipate even larger speedup factors, given the increased runtime complexity of the 3D version.
An efficient home energy management algorithm for demand response analysis in Indian scenario

Home energy management system (HEMS) came out as an important tool for enhancing residential customer demand response applications in smart grid. This paper proposes an efficient algorithm for HEMS which considers customer load priorities and preferences and maintains the power consumption below the sanctioned limit such that minimum comfort violation occurs. The application of proposed algorithm is done for demand response of the selected loads for Indian residential customers. Demand response of the selected appliances based on different utility signal, comfort level status and the loads priority is also analysed for different cases. The paper also discusses hardware design for efficacious handling of household appliances.
Automation of 11 kv substation using raspberry pi

Electricity plays an inevitable role in the development of the nation. In the conventional methodology, substation automation is done by using PLCs and SCADA systems, but for a small substation automation, this system is considerably expensive. This project adopts low cost automation solutions based on recent IOT technology using embedded processors like raspberry pi for automation of a small 11 kV substation. This gives the advantage of cost reduction plus a plethora of connectivity options. In this paper, Codesys IEC 61131-3 software is used to convert a Raspberry pi as a soft PLC. Analog and digital parameters from field are monitored and controlled using GPIOs pins, interfacing relays and communication ports available in raspberry pi. The automation sequences for control monitoring and protection of the system is defined using ladder diagram programming in IEC 61131-3 Codesys development platform. User interface and HMI screens are developed using Codesys web visualization segment which can be accessed both locally as well as over a wired or wireless network.
Effective joint training of denoising feature space transforms and Neural Network based acoustic models

Neural Network (NN) based acoustic frontends, such as denoising autoencoders, are actively being investigated to improve the robustness of NN based acoustic models to various noise conditions. In recent work the joint training of such frontends with backend NNs has been shown to significantly improve speech recognition performance. In this paper, we propose an effective algorithm to jointly train such a denoising feature space transform and a NN based acoustic model with various kinds of data. Our proposed method first pretrains a Convolutional Neural Network (CNN) based denoising frontend and then jointly trains this frontend with a NN backend acoustic model. In the unsupervised pretraining stage, the frontend is designed to estimate clean log Mel-filterbank features from noisy log-power spectral input features. A subsequent multi-stage training of the proposed frontend, with the dropout technique applied only at the joint layer between the frontend and backend NNs, leads to significant improvements in the overall performance. On the Aurora-4 task, our proposed system achieves an average WER of 9.98%. This is a 9.0% relative improvement over one of the best reported speaker independent baseline system's performance. A final semi-supervised adaptation of the frontend NN, similar to feature space adaptation, reduces the average WER to 7.39%, a further relative WER improvement of 25%.
Comparison of Co-temporal Modeling Algorithms on Sparse Experimental Time Series Data Sets

Multiple approaches for reverse-engineering bio-logical networks from time-series data have been proposed in the computational biology literature. These approaches can be classified by their underlying mathematical algorithms, such as Bayesian or algebraic techniques, as well as by their time paradigm, which includes next-state and co-temporal modeling. The types of biological relationships, such as parent-child or siblings, discovered by these algorithms are quite varied. It is important to understand the strengths and weaknesses of the various algorithms and time paradigms on actual experimental data. We assess how well the co-temporal implementations of three algorithms, continuous Bayesian, discrete Bayesian, and computational algebraic, can 1) identify two types of entity relationships, parent and sibling, between biological entities, 2) deal with experimental sparse time course data, and 3) handle experimental noise seen in replicate data sets. These algorithms are evaluated, using the shuffle index metric, for how well the resulting models match literature models in terms of siblings and parent relationships. Results indicate that all three co-temporal algorithms perform well, at a statistically significant level, at finding sibling relationships, but perform relatively poorly in finding parent relationships.
60 GHz ultrawideband front-ends with gain control, phase shifter, and wave guide transition in LTCC technology

For high-data-rate multimedia access and measurement applications (such as channel sounding and radar) the 60 GHz unlicensed band is of interest for short range applications. Currently, there is enormous progress in the field of monolithic-millimeter-wave-integrated-circuits (MMIC) for 60 GHz technology, but there are still many challenges related to reliability and usable bandwidth for compact packaging solutions. The aim of this work is to demonstrate the implementation of miniaturized 60 GHz front-ends, including fully differential MMICs, with gain control and phase-shifting capabilities, interconnected to a broadband differentially fed waveguide for the WR-15 standard. The front-ends were designed based on MMICs using 0.25 μm SiGe BiCMOS and packaging on low-temperature-cofired-ceramics (LTCC) technology. We have designed, simulated, fabricated, and tested the front-ends showing a useable bandwidth of more than 12 GHz at the 60 GHz band fulfilling the requirements of the IEEE 802.11ad standard.
60 GHz in-cabin real-time channel sounding

New wireless communications systems at 60 GHz are a promising solution to reach Giga-bit data rates for short range communications, e.g., for in-flight-entertainment (IFE) systems. For shadowed 60 GHz IFE systems, high resolution and multi-antenna time-varying channel characterisation are mandatory. This paper presents the first wideband 60 GHz real-time multi-antenna channel sounder (MCS) and measurement results within an Airbus-340 aircraft cabin. The MCS is a 3 GHz bandwidth system based on a modular architecture with 2 real-time acquisition channels enabled with a dynamic range up to 40 dB. This system architecture allowed the study of different in-cabin access point (AP) configurations and the inclusion of correlated shadowing by human bodies (SHB) for macro-diversity implementations. The frequency, phase and impulse response of the MCS has been tested based on back-to-back calibration data and its dynamic range verified. As example of the 60 GHz MCS application, the delay spread and the coherent bandwidth have been calculated for the in-cabin channel. Besides, comparisons between static and time-variant conditions are presented.
A 12Volt, 12GHz Complementary Bipolar Technology for High Frequency Analogue Applications

In this paper we report a new 12volt, high performance, highly competitive silicon complementary bipolar technology. NPN and vPNP devices have been fabricated with cut-off frequencies greater than 12GHz and breakdowns not less than 12volts. Two optimization techniques are discussed that can be used to improve the cut-off frequency of the vPNP device independently of the NPN. The resulting process is considered ideally suited to the manufacture of highly linear 1GHz operational amplifiers.
Advanced Remote-sensing Imaging Emission Spectrometer (ARIES): AIRS Spectral Resolution with MODIS Spatial Resolution

The Advanced Remote-sensing Imaging Emission Spectrometer (ARIES) will measure a wide range of earth quantities fundamental to the study of global climate change. It will build upon the success of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) instruments currently flying on the EOS Aqua Spacecraft. Both instruments are facility instruments for NASA providing data to thousands of scientists investigating land, ocean and atmospheric Earth System processes. ARIES will meet all the requirements of AIRS and MODIS in a single compact instrument, while providing the next-generation capability of improved spatial resolution for AIRS and improved spectral resolution for MODIS.
Collective process circuit that sorts

Comparing and sorting are common functions in natural and artificial systems. Many known algorithms that sort m numbers require time from O(m/sup 2/) to O(m). Algorithms to find the greatest number have been realised in neural networks and discrete time systems. Presented in the paper is a new circuit, the MAXOR, which incorporates a continuous time recursive collective process for finding the maximum of many inputs and sort inputs, like the spaghetti sort algorithm, when furnished with synchronous control. The resulting output is broadcast throughout the process. The precision /spl eta/ required of the circuit is only that needed to distinguish between the maximum and next lower inputs. Stability is assured within practical parameters where the output is observed to settle in linearised time O(m//spl eta/).
Aworldwide tourism recommendation system based on geotaggedweb photos

This work aims to build a system to suggest tourist destinations based on visual matching and minimal user input. A user can provide either a photo of the desired scenary or a keyword describing the place of interest, and the system will look into its database for places that share the visual characteristics. To that end, we first cluster a large-scale geotagged web photo collection into groups by location and then find the representative images for each group. Tourist destination recommendations are produced by comparing the query against the representative tags or representative images under the premise of ”if you like that place, you may also like these places“.
A high-performance shot boundary detection algorithm using multiple cues

A central step in content-based video retrieval is the temporal segmentation of video. An application independent approach to video segmentation is to detect temporally contiguous segments without significant content change between successive frames. Each such segment is termed a shot. A high-performance shot boundary detection-based video segmentation algorithm is proposed. The technique uses unsupervised clustering on a multiple feature input space, followed by a heuristic elimination process to detect, with almost perfect accuracy, shot boundaries in the video. With an extremely high accuracy coupled with a very small number of false positives, this algorithm outperforms most of the existing techniques.
A 96 Mbit/sec, 15.5 pJ/bit 16-QAM modulator for UHF backscatter communication

We describe a low power vector backscatter modulator capable of transmitting 16-QAM at a rate of 96 Mbps while consuming only 1.49 mW (15.5 pJ/bit). While designed around a center frequency of 915 MHz, the modulator is capable of operation over the worldwide 868-950 MHz UHF band. We present experimental results from the modulator operating in 4-QAM/4-PSK, 4-PAM, and 16-QAM modes. Achieved data rates are comparable to WiFi (IEEE 802.11) with a measured tag-side power consumption over 50 times lower than a WiFi chipset. Potential applications for low power, high bit rate modulators include biotelemetry, high-bandwidth data transfer from camera tags or audio tags, uplink from mass storage tags, and exchange of large amounts of encryption or authentication data. Given a +36 dBm EIRP transmitter operating at 915 MHz, the semi-passive (battery-assisted) prototype tag is return link limited and has a theoretical maximum operating range of 17.01 m at 96 Mbps or 21.25 m at 40 Mbps.
AIRS - the Atmospheric Infrared Sounder

The Atmospheric Infrared Sounder (AIRS) was launched in 2002, along with two companion microwave sounders. This AIRS sounding suite is the most advanced atmospheric sounding system to date, with measurement accuracies far surpassing those of current weather satellites. From its Sun synchronous polar orbit, the AIRS system provides more than 300,000 all-weather soundings covering more than 90% of the globe every 24 hours. Much of the post-launch period has been devoted to optimizing the "retrieval" system used to derive atmospheric and other parameters from the observations and to validate those parameters. The geophysical parameters have been produced since the beginning of 2003 - the first data were released to the public in mid-2003, and future improved versions be released periodically. The ongoing calibration/validation effort has confirmed that the system is very accurate and stable. There are a number of applications for the AIRS products, ranging from numerical weather prediction - where positive impact on forecast accuracy has already been demonstrated, to atmospheric research - where the AIRS water vapor products near the surface and in the mid and upper troposphere promise to make it possible to characterize and model phenomena that are key for atmospheric processes, from weather patterns to long-term phenomena, such as interannual variability and climate change.
Aluminum Bond Pad Contamination by Thermal Outgassing of Organic Material from Silver-Filled Epoxy Adhesives

Effects of outgassing from commercial die attach adhesive systems on the mechanical strength of gold aluminum bonds were studied. Bond pad metallizations on unpackaged test dice were exposed to the die attach media under standard cure conditions, and gold bonds were subjected to a steam pressure pot storage. Bond pull strength as well as resistance data were obtained to determine the extent of bond degradation. Bonds exposed to die attach systems containing reactive epoxy diluents were found to cause faster mechanical degradation of the Au/Al bond under steam pressure pot storage as compared with the die attach systems formulated with ester type or other nonreactive solvents. Cleaning the bond pad with N 2 /O 2 plasma prior to wire bonding was found to dramatically improve the mechanical strength of the bonds. It was determined that the epoxy reactive diluents in some of the die attach systems could deposit on the bond pad during the cure and cause growth and reinforcement of the native Al 2 O 3 film on the pad surface with a rigid self-polymerized organic resin. This could prevent complete exposure of the underlying metal during the wire bonding process and leave debris within the bond. Wire bonds made under such a condition would be chemically vulnerable to attack by the moisture and the ionic species present in a plastic package.
Comparing MFCC and MPEG-7 audio features for feature extraction, maximum likelihood HMM and entropic prior HMM for sports audio classification

We present a comparison of 6 methods for classification of sports audio. For feature extraction, we have two choices: MPEG-7 audio features and Mel-scale frequency cepstrum coefficients (MFCC). For classification, we also have two choices: maximum likelihood hidden Markov models (ML-HMM) and entropic prior HMMs (EP-HMM). EP-HMMs, in turn, have two variations: with and without trimming of the model parameters. We thus have 6 possible methods, each of which corresponds to a combination. Our results show that all the combinations achieve classification accuracy of around 90% with the best and the second best being, respectively, MPEG-7 features with EP-HMM and MFCC with ML-HMM.
Construction of Volume Meshes from Computed Tomography Data

In this paper, we present a new method, called marching volume elements (MVE), for automatically constructing a volume mesh from three-dimensional (3-D) high-resolution computed tomography (CT) data. The volume mesh generated by the MVE algorithm is suitable for computational fluid dynamics (CFD) simulations. The MVE algorithm is based on the marching cubes (MC) algorithm which is a surface generation algorithm for 3-D intensity data. The mesh created with the MVE algorithm is composed of pyramids, cubes and tetrahedrons with common faces that fit together to form a topologically consistent volume. We validate the MVE algorithm on a synthetic object and demonstrate it on CT scans of a human nasal cavity