nils-herrmann/clean_scirepeval huggingface dataset:
A two-step keyword spotting method based on context-dependent a posteriori probability

Keyword weighting plays an important role in traditional keyword spotting (KWS) systems: it helps detect keyword candidates in an utterance so that they will not be missed. However, if the keywords are over-weighted, there will be a high number of false alarms, which will slow down the system and might introduce rejection errors; on the other hand, if the keywords are insufficiently weighted, the detection rate is not guaranteed. It is difficult to make a compromise with regard to keyword weighting. A two-step KWS method based on context-dependent a posteriori probability (CDAPP) is proposed in this paper as a way to solve this problem. The first step adopts a continuous speech recognition method, to generate a sequence of acoustic symbols for the second step, which performs a fuzzy keyword search. Preliminary experiments show that the proposed strategy is a promising one that needs additional investigation.
Who Are Your “Real” Friends: Analyzing and Distinguishing Between Offline and Online Friendships From Social Multimedia Data

The Internet has extended the physical boundary of people's social circles to manage an inordinate number of online friends. It is recognized that only a fraction of these online friends are also known with each other in offline circumstances, i.e., the offline friends. An important type of offline friend, onsite offline friend, is defined and addressed in this paper. We explores the possibility of utilizing users’ online photo sharing-related behaviors and network topologies to analyze and distinguish between online and onsite offline friendships. Different from traditional social science studies which rely on survey-based data, we employ users’ tagged people on the shared Instagram photos as the ground-truth for onsite offline friends. This enables a large-scale and objective analysis and experimental evaluation, which compares between different factors and identifies the features that are key to onsite offline friend identification.
Study on Development Kinetic Energy of Chinese Industry and Measure Model of Energy

Following the theory of kinetic energy in physics, the concept of development kinetic energy of regional economy and the concept of per-employed development kinetic energy were put forward, and it provided a useful tool for study regional economy. On the base of it, this paper develops and extends the kinetic energy of regional economy to industry, and put forward development kinetic energy and per-employed development kinetic energy of industry, and the corresponding measure models are established. They create a new method for analysis theory of development kinetic energy of industry. Furthermore, making use of this method, we analyze and study the second-order kinetic energy and the second-order per-employed kinetic energy of each industry of China in the paper. And the conclusions are accordant to the reality well and could explain and predict industry development well
Simulation research on hybrid energy storage system of hybrid electric vehicle

Battery is widely used as the only energy storage system for domestic hybrid electric vehicle (HEV). Short battery life is becoming the biggest obstacle in the rapid development of HEV, adding ultracapacitor pack into the HEV energy storage system can solve this problem. After analyzing the principles and characteristics of ultracapacitor, the model of hybrid energy storage system (HESS) had been established in matlab/simulink, battery and ultracapacitor was in parallel connection, joined with HESS control strategy, and also designed the topology of the HESS. Then selected components and conducted matching parameters of the system. By simulating the pulse power input, a single battery powered HEV had been compared with a HESS supplied HEV in power supply capacity. The results showed that the HESS powered hybrid vehicles can reduce high current charge and discharge times of the battery, and be able to meet the power requirements.
Design of microwave wave gain equalizer using microstrip shorted SIR

Gain equalizer is often used to adjust the output gain of traveling wave tubes (TWT) or high power solid state amplifiers. Traditionally, the resonant branch of microwave gain equalizer is a single short or open microstrip line. However, this structure is hard to reduce the reflection coefficient and, it cannot control the bandwidth easily. In this paper, the microwave gain equalizer is fulfilled by microstrip stepped impedance resonator (SIR) with thin film resistance integrated. This structure could easily overcome the defects in traditional equalizer. The measurement results show that the equalization curve meet requirements well, proved this structure is practical and effective.
Learning from Metadata: A Fuzzy Token Matching Based Configuration File Discovery Approach

Discovery of configuration files is one of the prerequisite activities for a successful workload migration to the cloud. The complicated and super-sized file systems, the considerable variance of configuration files, and the multiple-presence of configuration items make configuration file discovery very difficult. Traditional approaches usually highly rely on experts to compose software specific scripts or rules to discover configuration files, which is very expensive and labor-intensive. In this paper, we propose a novel learning based approach named MetaConf to convert configuration file discovery to a supervised file classification task using the file metadata as learning features such that it can be conducted automatically, efficiently, and independently of domain expertise. We report our evaluation with extensive and real-world case studies, and the experimental results validate that our approach is effective and it outperforms our baseline method.
High performance plasmonic waveguide with compact transition structure

In this work, a compact transition which can efficiently convert guided waves to spoof surface plasmon polaritons (SSPPs) is proposed. By using the S-parameter retrieval technique, the bloch impedance of the SSPP unit cell is extracted and tuned around 50 ohm in a wide frequency band to achieve good impedance matching. Then, the momentum can be matched with fewer gradient matching grooves leading to smaller size. For demonstration, a planar plasmonic waveguide based on the proposed transition structure is designed and simulated. The excellent simulation results validate high-efficiency excitation and propagation of SSPPs in broadband. The proposed plasmonic waveguide can find potential applications in plasmonic devices and integrated circuits in microwave and terahertz frequencies.
Simulating a $2M Commercial Server on a $2K PC

As dependence on database management systems and Web servers increases, so does the need for them to run reliably and efficiently-goals that rigorous simulations can help achieve. Execution-driven simulation models system hardware. These simulations capture actual program behavior and detailed system interactions. The authors have developed a simulation methodology that uses multiple simulations, pays careful attention to the effects of scaling on workload behavior, and extends Virtutech AB's Simics full system functional simulator with detailed timing models. The Wisconsin Commercial Workload Suite contains scaled and tuned benchmarks for multiprocessor servers, enabling full-system simulations to run on the PCs that are routinely available to researchers.
Purification and Some Properties of Superoxide Dismutase from Aloe saponaria (Ait) Haw.

Superoxide dismutase (SOD) from Aloe saponaria (Ait) Haw was purified to electrophoretic homogeneity by a sequential steps ,including of acetone and heat of treatment, DEAE-sepharose and Sephacryl S-200 column chromatography. Three SOD components were obtained, designated as SOD-I,SOD-II,SOD-III with the molecular weight of 46,000D, 35,000D and 40,000D, and isoelectric point of 8.9, 7.6, 7.35 respectively. The three components were consisted of two identical subunits. All three SOD components from A. saponaria (Ait) Haw were Fe-SOD as confirmed by its sensitivity to KCN and H2O2, elemental analyses and the absorption spectrum analyses. Key word aloe�ƒ Aloe saponaria (Ait) Haw.�≈ ; purification; properties; superoxide dismutase (SOD)
Measuring and modeling the effects of substrate noise on the LNA for a CMOS GPS receiver

The influence of substrate noise generated in a digital circuit on the low-noise amplifier (LNA) of a CMOS GPS receiver has been experimentally characterized and theoretically analyzed. A frequency domain approach is used to model noise injection into the substrate from the digital circuitry and the mechanisms by which that noise can affect analog circuit behavior. The results reveal that substrate noise can modulate the LNA input signals as well as directly couple to the LNA output.
Analysis and design of a novel coupled-line wideband Wilkinson power divider

This paper presents the design of a novel Wilkinson power divider for wideband applications. The proposed structure is composed of one coupled line with different even- and odd-mode characteristic impedance and a multi-stage λ/4 impedance transformer. Using rigorous even- and odd-mode analysis, the analytical design equations for this proposed power divider are obtained. To validate the analysis, dividers centered at 3 GHz with different number of impedance transformation stages N are simulated and a comparison is made between them. For ultra-wideband (UWB) application, the comparison result shows that N≥3 is needed, and a divider with N=3 is ultimately designed with the return loss better than -20 dB over 3.1-10.6 GHz range.
Inversion-Type Enhancement-Mode InP Mosfets with ALD High-K Al2O3 and HFO2 as Gate Dielectrics

Enhancement-mode (E-mode) n-channel InP metal-oxide-semiconductor field-effect-transistors (MOSFETs) with 0.75 to 40 mum gate length fabricated on semi-insulating substrates and p-type doped InP epi-layers with atomic-layer-deposited (ALD) Al2O3 and HfO2 as gate dielectrics are demonstrated. The ALD process on III-V compound semiconductors enables the formation of high- quality gate oxides and unpinning of Fermi-level on compound semiconductors. A 1-mum gate-length E-mode n- channel MOSFET with a HfO2 gate oxide thickness of 10 nm shows a maximum drain current of 130 mA/mm and a trans- conductance of 40 mS/mm at the highest gate bias of 6 V.
Research on the reconstruction method of B-spline surface based on radius basis function neural networks

Surface reconstruction is the key technology in the geometry reverse engineering. In order to obtain the object's geometrical model, we have to construct surface by large numbers of measured data points. This paper introduces a new method for the reconstruction of free-form surface. Firstly, it profits scattered and measured data points which come from free-form surface archetype by radius basis function neural networks algorithm. Secondly, it maps the mathematical model of free-form surface by the linear combination of radius basis function and the weights of the hidden layer. Finally it transforms the mathematical model to bicubic B-spline surface. This paper also commentates the feasibility of the above idea that resolves the problems of surface fitting by radius basis function neural networks
An Application Framework for Business Developers to Create Service Based Business Applications

Enabling business developers to create business applications greatly reduces development cost and increases business adaptiveness. However, lacking of an application framework that is amenable to business people makes it hard for business developers to create decent business applications. This paper presents such a business application framework that consists of application components primarily including business artifacts, forms and tasks that business developers can easily work with. The different types of components are automatically composed into a service based application with Model-View-Controller (MVC) paradigm. The advanced business developers are allowed to write scripts to manipulate the behavior of the components and mash-up with external services for better customization and integration. The design considerations for the supporting tools and run-time are also discussed in detail in the paper. At the end, the feedback we got and consolidated from practitioners is analyzed for identifying potential enhancement and major future work.
The influence parameters /spl beta//sub 1 / and /spl beta//sub 2 / have on bibeta spline curved surface

This paper discusses how Beta spline curve with geometric continuity is influenced by the change of parameters beta1 and beta2, offers the range of parameters beta1 and beta2 and presents the algorithm principles of bibeta spline curved surface that is controlled by double parameters. Based on all above, a freedom surface modeling system (FSMS) is designed and some examples are verified and analyzed
Characterization of high-frequency noise performance of GaN double heterojunction HEMT

A systematic GaN single heterojucntion HEMT (SH-HEMT) physical based numerical model is established in this paper. This model includes field-dependent mobility, polarization effect, interface state, surface state, and traps. The model has been implemented into TCAD Silvaco. And the simulated DC and RF characterization fit the measured results well. The high frequency noise performance of AlGaN/GaN/AlGaN double heterojuction HEMT (DH-HEMT) is studied based on the established SH-HEMT model. The results show that, because of the enhancement of carrier confinement in DH-HEMT, better high frequency noise performance can be achieved.
A unified framework for semantic shot classification in sports video

The extensive amount of multimedia information available necessitates content-based video indexing and retrieval methods. Since humans tend to use high-level semantic concepts when querying and browsing multimedia databases, there is an increasing need for semantic video indexing and analysis. For this purpose, we present a unified framework for semantic shot classification in sports video, which has been widely studied due to tremendous commercial potentials. Unlike most existing approaches, which focus on clustering by aggregating shots or key-frames with similar low-level features, the proposed scheme employs supervised learning to perform a top-down video shot classification. Moreover, the supervised learning procedure is constructed on the basis of effective mid-level representations instead of exhaustive low-level features. This framework consists of three main steps: 1) identify video shot classes for each sport; 2) develop a common set of motion, color, shot length-related mid-level representations; and 3) supervised learning of the given sports video shots. It is observed that for each sport we can predefine a small number of semantic shot classes, about 5-10, which covers 90%-95% of broadcast sports video. We employ nonparametric feature space analysis to map low-level features to mid-level semantic video shot attributes such as dominant object (a player) motion, camera motion patterns, and court shape, etc. Based on the fusion of those mid-level shot attributes, we classify video shots into the predefined shot classes, each of which has clear semantic meanings. With this framework we have achieved good classification accuracy of 85%-95% on the game videos of five typical ball type sports (i.e., tennis, basketball, volleyball, soccer, and table tennis) with over 5500 shots of about 8 h. With correctly classified sports video shots, further structural and temporal analysis, such as event detection, highlight extraction, video skimming, and table of content, will be greatly facilitated.
Fast information matrix process of SEIF based on tri-diagonal matrix splitting

There have been a number of variant Simultaneous Localization and Mapping (SLAM) algorithms which have made substantial progress towards large-area scalability by parameterizing the SLAM posterior within the information (canonical /inverse covariance) form. The most well-known and popular approach is the Sparse Extended Information Filter (SEIF) by Thrun et al. SEIF has been successfully implemented with a variety of challenging real-world data sets and has lead to new insights into scalable SLAM. The paper presents a new approach based upon tri-diagonal matrix splitting for solving the computational complexity problem of inverse information matrix. In this paper, by analyzing the every steps of information matrix update in SEIF process, we find that the most computational cost is in recovery information matrix (inverse matrix). According to this characteristics which the normalized information matrix exhibits a natural sparseness and the many of the off-diagonal elements are relatively weak (nearly to zero) in information matrix, we enforce the elements into zero according to setting a threshold and computer inverse information matrix with the method of tri-diagonal matrix splitting. As the new processing does not need direct matrix inversion, the computational complexity is much lower. The Computer simulation results indicate that SEIF process is faster and localization precision is no influence.
Towards Session-Aware RBAC Administration and Enforcement with XACML

An administrative role-based access control (ARBAC) model specifies administrative policies over a role-based access control(RBAC) system, where an administrative permission may change an RBAC policy by updating permissions assigned to roles, or assigning/revoking users to/from roles. Consequently, enforcing ARBAC policies over an active access controller while some users are using protected resources would result in conflicts: a policy may be in effect in the RBAC system while being updated by an ARBAC operation. Towards solving this concurrency problem, we propose a session-aware administrative model for RBAC. We show how the concurrency problem can be resolved by enhancing the eXtensible Access Control Markup Language (XACML) reference implementation.In order to do so, we develop an XACML-ARBAC profile to specify ARBAC policies, and enforce these polices by building an ARBAC enforcement module and a session administrative module. The former synchronizes with the evaluation of access control requests. The latter revokes conflicting ongoing user sessions immediately prior to enforcing administrative operations. Experimental studies show reasonable performance characteristics of our initial enhancement to Sun's reference implementation.
Tracking and classification of dynamic obstacles with laser range finder in indoor environments

It is a key issue for a service robot to deal with different kinds of dynamic obstacles in indoor environments. An approach to track and classify dynamic obstacles in indoor environments is proposed in this paper. A laser range finder (LRF) is used to detect and acquire information of dynamic obstacles. Accordingly dynamic obstacles are grouped into three categories: active obstacles, inactive obstacles and inactive obstacles combined with active obstacles. Three typical obstacles belonging to three categories are analysed based on frequency analysis respectively. According to relative power spectrums, two attributes are put forward to classify three classes of dynamic obstacles. The classification approach could be beneficial to navigation when coping with dynamic obstacles in the indoor environment.
An Optimal Nonlinear Variable Structure Guidance Law Considering Missile Dynamics of Autopilot

A new nonlinear variable structure guidance law considering missile dynamics of autopilot against the space maneuver target is presented. Considering the target maneuverability as a disturbance with boundary,this guidance law constructs the switching surface by adding a nonlinear function which is confirmed by feedback optimization theory at the linear switching surface based on the proportional navigation law.Considering one order autopilot dynamic model,the actual guidance command is derived.Simulation results show that this designed guidance law has good trajectory performance,is robust for maneuver targets and overcomes the shortcoming of the linear switching surface that causes excessive overload at initial guidance phase.It is simple and more convenient for practical implementation.
Applications of nonuniform fast transform algorithms in numerical solutions of differential and integral equations

We review our efforts to apply the nonuniform fast Fourier transform (NUFFT) and related fast transform algorithms to numerical solutions of Maxwell's equations in the time and frequency domains. The NUFFT is a fast algorithm to perform the discrete Fourier transform of data sampled nonuniformly (NUDFT). Through oversampling and fast interpolation, the forward and inverse NUFFTs can be achieved with O(N log/sub 2/ N) arithmetic operations, asymptotically the same as the regular fast Fourier transform (FFT) algorithms. Using the NUFFT scheme, we develop nonuniform fast cosine transform (NUFCT) and fast Hankel transform (NUFHT) algorithms. These algorithms provide an efficient tool for numerical differentiation and integration, the key in the solutions to differential equations and volume integral equations. We present sample applications of these nonuniform fast transform algorithms in the numerical solution to Maxwell's equations.
Wind/Photovoltaic hybrid power generator based on fuzzy control

A new kind of wind/photovoltaic(PV) hybrid generator was designed for effectively and reliably utilizing the renewable resources. It was designed to be an auto-interference controller. To capture the wind and the light in the greatest degree, the method of nonlinear transform of aerodynamic force was used, as well as the theory of brushless double-fed wind generator and the principle of extremum control on solar inverter were adopted. The hierarchical fuzzy controller algorithm was presented for controlling the loading and unloading of wind generators, solar cells and the grid, considering the multi-input and multi-output of the distributed hybrid power system. It's shown by the simulations that: on the premise of utilizing renewable resources to the greatest extent, system can realize the equilibrium between the supply and demand of the electric energy automatically according to its load.
A close-up detection method for movies

Close-up (CU) is a photographic technique which tightly frames a person or an object. In movies, it is applied to guide audience attention and to evoke audience emotion. In this paper, we detect face CU, object CU, and lean of movies, which are widely used to romance emotions. A lean consists of shots in a sequence, with a close-up shot as focus. A set of features are extracted by considering movie making techniques and human attention for CU detection. The features are average saliency, color entropy, color variance, face height, skin area, and texture scales. These features are tested through statistical hypothesis test to be significantly discriminating for CUs. Then, Support Vector Machine (SVM) is applied on these features to detect face CU and object CU. Based on the face CU and object CU detection result, lean is further detected by investigating the changing of the face/object size. Lean detection is of challenge due to the technique of montage. We solve this problem through color similarity estimation and SIFT point matching. Experimental results on four full length movies verify the effectiveness of the proposed method.