nils-herrmann/clean_scirepeval huggingface dataset:
A Unified Framework of Latent Feature Learning in Social Media

The current trend in social media analysis and application is to use the pre-defined features and devoted to the later model development modules to meet the end tasks. Representation learning has been a fundamental problem in machine learning, and widely recognized as critical to the performance of end tasks. In this paper, we provide evidence that specially learned features will addresses the diverse, heterogeneous, and collective characteristics of social media data. Therefore, we propose to transfer the focus from the model development to latent feature learning, and present a unified framework of latent feature learning on social media. To address the noisy, diverse, heterogeneous, and interconnected characteristics of social media data, the popular deep learning is employed due to its excellent abstract abilities. In particular, we instantiate the proposed framework by (1) designing a novel relational generative deep learning model to solve the social media link analysis task, and (2) developing a multimodal deep learning to lambda rank model towards the social image retrieval task. We show that the derived latent features lead to improvement in both of the social media tasks.
An adaptive 16/64 kHz, 9-bit SAR ADC with peak-aligned sampling for neural spike recording

This paper presents a novel method and circuit for feature-driven data acquisition in single neuron recording. By dynamically adjusting the phase of the sampling clock in a Successive Approximation Register (SAR) Analogue to Digital Converter (ADC), the samples can be maximally aligned to the spike extrema (peaks). This is achieved by using spike detection to switch from a `coarse' to `fine' sampling clock, and triggering a peak-search algorithm to determine the offset between the peak occurrence and the coarse clock. Subsequent samples are then aligned to the peak by shifting the coarse clock by the measured offset. This adaptive sampling scheme thus allows for improved temporal precision on features of interest (i.e. peaks) whilst maintaining a coarse effective sampling rate, also minimising power consumption. The proposed method reduces the output data bandwidth by approximately 70% in comparison to a fixed-sampling rate data converter that would achieve similar precision in peak alignment. The circuit implementation achieves 9-bit resolution with a 93 fJ/conversion-step energy efficiency in a standard 0.35 μm CMOS technology.
Behavioral modeling and EMI analysis for airborne distance measuring equipment

Distance Measuring Equipment (DME) is one of the most useful navigation systems, and its performance such as stability and precision relates to the safety of an aircraft. As the electromagnetic environment of an aircraft is very complex, it is urgent to find out which kind of interference affects the DME seriously. This paper puts forward behavioral modeling to analyze the electromagnetic interference (EMI) existed in DME. By using behavioral model, the influence of pulse noise, narrowband noise and fluctuation noise to the performance of DME can be shown. The simulation result from ADS (Advanced Design System) shows that in time domain the pulse noise affects in a very short time and the fluctuation noise usually in low level lead to less EMI problem. And the in-band narrowband noise leads to EMI problem commonly, which accords with the real fact. So it turns out that behavioral modeling is a useful method to analyze EMI problems in a circuit or a system.
A Research and Application of Continuous Attributes Discretization Based on Cloud Model and Information Entropy

Discretization of continuous attributes is one of the most important issues in network data preprocessing. In this paper, a discretization algorithm of continuous attributes based on cloud model and information entropy is proposed. Making use of cloud transform, the proposed algorithm partitions the domain of every continuous attribute into many concepts represented by cloud models. The uncertain boundary of cloud model is more appropriate for actual data distribution. Define information entropy for every candidate cloud that treated as a measuring of importance. On the basis of that, select appropriate neighboring concepts and merge them. It could increase the information granularity of information system. Then utilize the fuzziness of cloud model for realizing the adaptive adjustment of boundary data, so as to improve consistency level in decision table. By employing the new algorithm, the experiments on Iris data set reached the expectation. The results show that the algorithm is feasible and efficient.
Adopting Text Clustering in web-based application to facilitate searching of education information

Clustering, as a part of the Data Mining field, has been in the center of the research attention for the last decade. It is the task of finding subsets of data that are sharing the same type of attributes. Text Clustering becomes one of the most critical and important solutions in data mining to discover knowledge from fast grow up web data and log files. There are many challenges, algorithms needs to be tailored specific for each domain and scale well with growing data sets. Another interesting aspect is the design of the system. A complex set components need to interact well together. This article proposes an elegant way of clustering university educations based on their text attributes. The solution is integrated directly into a Spring Web Application. A comprehensive architecture is proposed, providing the frameworks needed. Clustering techniques such as Canopy Generation [4] and k-Means are demonstrated.
A power converter integration approach with a multi-functional heat sink shaped inductor

This paper presents a novel multi-functional component which combines the features of heat sink and magnetic device in the power converters. Inspired by the functional integration concept, the proposed heat sink component is well designed in order to also serve as an inductor. With the modified winding and magnetic circuit design, the inductance can accommodate the requirement of power converter without increasing the DC condition loss. This proposed heat sink-inductor device can significantly save the total volume of power module and improve the thermal performance at the meanwhile. In the studied point of load power module, the total volume is decreased by 40% and the temperature of voltage regulation IC is decreased by 14°C.
Asymptotic performance analysis of multiuser MIMO system in Rayleigh fading channels

In this paper, the bit error rate (BER) performance of multiuser multiple-input multiple-output (MIMO) systems over Rayleigh fading channels is studied, and corresponding asymptotic performance is analyzed. Based on the asymptotic analysis at high signal to noise ratio (SNR), using the probability density functions (PDF) of the instantaneous channel power gain, the diversity gain and coding gain of the system with transmit antenna selection (TAS) scheme and space-time block coding (STBC) scheme are derived, respectively. As a result, the same full diversity gain is achieved for two transmission schemes, but their coding gains are different. With the obtained diversity gain and coding gain, the asymptotic BER expressions for two transmission schemes are respectively derived, which are in good agreement with the corresponding simulation results. The results show that the multiuser MIMO system with TAS scheme has better BER performance than that with STBC scheme due to higher coding gain.
An adaptive multi-objective bacterial swarm optimzer

This paper proposes an adaptive multi-objective bacterial swarm optimizer (AMBSO) for multi-objective problems. The proposed AMBSO method implements the search for Pareto optimal set of multi-objective optimization problems. The AMBSO has been compared with the MBFO over a test suite of five ZDT numerical benchmarks with respect to the two performance measures: Generational Distance and Diversity Measure. The simulation results show that the AMBSO is able to find a much better Pareto front solutions.
A general unified large signal model for current programmed DC-to-DC converters

A general and unified large signal averaged circuit model for current programmed DC-to-DC converters is proposed. In the averaged circuit model, the active switch is modeled by a current source, with its value equal to the averaged current flowing through it, and the diode is modeled hy the voltage source, with its value equal to the averaged voltage across it. The averaged circuit model has the same topology as the switching converter. The large signal averaged circuit model for current programmed buck, boost, buck-boost and Cuk converters are proposed, from which the large signal characteristics can be obtained. The steady-state and small signal transfer functions of the current programmed DC-to-DC converters can all be derived from their large signal averaged circuit models. The large signal characteristics of the current programmed buck converter are studied by both the phase plane trajectory and the time domain analysis. Experimental prototypes for a current programmed buck converter, with and without an input filter, are breadboarded to verify the analysis.
A Spatially Selective Correlative Filtration Method Based on the Multiscale Edge Shift-Correlative Technique

In terms of signal denoising, filtering out high-frequency noise while effectively preserving the useful high-frequency information is a hot topic for research. In this paper, we propose a wavelet modulus maxima spatially selective correlative filtration (SSCF) algorithm to filter out the high-frequency noise mixed in the useful signals. The proposed algorithm is different from traditional noise filtration algorithms in that it need not estimate noise and is not easily affected by noise. The SSCF algorithm first searches the modulus maxima from the multiscale wavelet coefficients of the signal and analyzes the corresponding edge information. Then, it identifies the noise components and useful components from the edge information. For noise components, the algorithm smoothes them away. For useful edge information, the algorithm aligns the corresponding modulus maxima in the wavenumber domain using the shift-related technique. This process amends the “drift” phenomenon of modulus maxima across scales. Next, the proposed algorithm multiplies the aligned multiscale wavelet coefficients that can strengthen the useful signal and attenuate the noise information. We apply the proposed SSCF algorithm to denoise the infrared absorption spectrum of electric insulation gas SF6. Experiments show that the proposed scheme can effectively suppress noise and, at the same time, preserving the useful components.
Adaptive Neural Network Control for a Class of Uncertain Nonlinear Systems

An adaptive neural network control scheme is developed for a class of nonlinear systems in the strict-feedback form. Compared with the existing approaches, the main advantage is that the developed scheme can be implemented by utilizing only one neural network approximator. Thus, the designed controller structure is simplified. In addition, less neural network can reduce the running cost in practical application. The developed neural network control scheme can achieve that all the signals of the closed-loop system are uniformly bounded and the tracking errors converge to an arbitrary small neighborhood around zero by selecting suitably design parameters.
Control Allocation for an Over-Actuated Aircraft Based on Within-Visual-Range Air Combat Agility

The control allocation problems of an over-actuated aircraft are studied to fully utilize the within-visual-range (WVR) air combat agility. By analyzing the agility requirements of modern WVR air combat, a control effector superiority evaluating method is proposed to identify the control effectors participated in control allocation. An optimized control allocation model is constructed based on the air combat agility. As a case study, the control effector superiority parameters of a typical canard-delta-wing aircraft are evaluated, and the optimized control allocation configuration is built. The combat cycle times of the optimized and other two control allocation configurations are evaluated by pilot-in-the-loop simulation on a ground-based flight simulator. The simulation results show that the optimized control allocation model constructed in this paper can efficiently make use of the agility potentials of the target aircraft, which indicates that the control effector superiority evaluating method and the control allocation model proposed are sound and effective.
A 3D Parallel Monte Carlo Simulator for Semiconductor Devices

We developed a 3D parallel full band Monte Carlo simulator for semiconductor devices. This enables us to simulate 3D devices on high performance multiprocessor machines. By utilizing the JASMIN  software package, parallel execution issues such as processors communication, grid partitioning and load balancing are handled easily and efficiently. The 3D MC simulator is validated by comparing its results with that from 2D 70nm SOI MOSFET simulations. We present speedup and load balancing results of our 3D simulator to show the parallel efficiency. A FinFet model ,  is simulated for application.
Adaptive Fuzzy Tracking Control Based Barrier Functions of Uncertain Nonlinear MIMO Systems With Full-State Constraints and Applications to Chemical Process

An adaptive control approach based on the fuzzy systems for a class of uncertain nonlinear multi-input multi-output (MIMO) systems is presented in this paper. This class of systems is in the nested multiple coupling structure and their states are constrained in the corresponding compact sets. The properties of the system structure are inevitable to bring about a complicated design and a difficult task. The fuzzy logic systems are employed to approximate the unknown functions of systems, and the decoupling backstepping way is proposed to design the stability controller and adaptation laws. Barrier Lyapunov functions (BLFs) are constructed in the backstepping design to guarantee that the constraint bounds are not violated. Based on Lyapunov analysis in barrier form, we can prove the stability of the closed-loop system. Two simulation examples are viewed to verify the feasibility of the approach.
Analysis of image frequency interference in altimeter front-end receiver

A major problem of the superheterodyne receivers is their response to the undesired frequencies, such as harmonic, image frequency signal. In this paper, special attention is paid to the image frequency interference. In order to analysis the effect of the image frequency signal to the superheterodyne, a behavioural model of a superheterodyne receiver of altimeter is presented and its electromagnetic compatibility is analyzed from the aspects of spectrum and power under the condition of image frequency interference. According to the simulation results, the methods of EMC reinforcement are given. The performance of the improved receiver is simulated and analyzed under the same condition. And the results based on the reinforcement system further verify the effectiveness of the method and the receiver achieves a higher image rejection ration.
A self-reconfiguration control regarding recovery effect to improve the discharge efficiency in the distributed battery energy storage system

The battery energy storage system in the MicroGrid tends to be distributed in the future, to solve the voltage sharing and overcharge/overdischarge problem, achieve high compatibility and reliability, etc. Based on the distributed architecture, this paper proposes a self-reconfiguration discharge strategy regarding the battery recovery effect to further enhance the battery performance and discharge efficiency of the battery energy storage system. The specific control strategy and principle analysis is presented in details, and the experimental result has verified the proposed concept.
Dynamic order strategy(R, st, ST) for automobile spare parts on a target service level

This paper studies on dynamic order strategy for auto spare parts on a target service level. A new three-dimensional classification is proposed integrated order policy of spare parts. It improves the present the weakness of ABC classification and combines with three control variables influenced the order policy, X demand, Y item price and Z variation of demand, to classify all spare parts. Unlike most extant inventory-control approaches, Strategy(R, st, ST) offered is a kind of dynamic order strategy integrated with inventory control parameters with inventory check cycle (R), dynamic reorder point (st) and dynamic order quantity (ST) and is set the goal with a target service level while minimizing of total inventory cost. It takes into accounts the dynamic requirements in category, time and quantity in accordance with automobile spare parts. Simulation experiments were performed by ARENA 10.0 to represent the performance of strategy (R, st, ST) and the optimized strategy is given. Outcomes simulating show that dynamic strategy (R, st, ST) enables to carry out dynamic inventory management and control by parameters R, st, ST for automobile spare parts. Also a goal under a certain target service level while satisfied the minimization of total inventory cost can be come true.
Compartmental low-rank filtering of radio-echo sounding data

This paper presents a compartmental filtering method to improve signal-to-noise ratio (SNR) of the radio-echo sounding (RES) data of ice sheets while preserve weak signals in the deep layers. The proposed method performs local low-rank filtering on different internal layers of ice sheet to avoid weak signals from being filtered by global denoising methods. Experimental results show that the proposed method not only suppresses noise more effectively, but also better preserves the localized weak signals in the deep layers.
4H-SiC Trench IGBT With Back-Side n-p-n Collector for Low Turn-OFF Loss

In this paper, an n-p-n collector incorporated in the back side of a 4H-SiC trench IGBT is presented to reduce the turn-off energy loss. A comparative study between the proposed structure and the conventional structure is conducted through ATLAS. The simulation results have demonstrated that the turn-off energy loss is reduced by more than 82.96% with a slight degradation in the on-state voltage drop.
A multiperiod fuzzy production planning and sourcing problem with service level constraints

In this paper, we consider a multiperiod fuzzy production and sourcing problem that a manufacturer has a number of plants and subcontractors. The manufacturer has to meet the products demand according to the service level requirements set by its customers. The demand for each product in each period is assumed to be a fuzzy variable. Since the proposed model is too complex that the conventional optimization methods cannot be used. To solve the problem, a heuristic solution method, which combines approximation method, genetic algorithm (GA) and neural network (NN), is proposed. We provide a numerical example to illustrate the feasibility and effectiveness of the designed algorithm.
Design of PLC Control System for Manufacturing Coal Slurry

coal slurry is a new kind of fluid fuel, and Coal slurry manufacturing with PLC control is needed for its unique property. This paper focuses on Design of PLC Control System for Manufacturing Coal Slurry, and present some design schemes. It includes how to design Coal slurry manufacturing with PLC control system. In addition, it introduces main blocks of Coal slurry manufacturing with PLC control system and its software design.
Commercial Housing Sales Forecasting Model Based on Grey System

The study of this paper begins from the real status of commercial housing market in our country. According to the research of commercial housing demand in certain firsttier city, we choose the method of grey theory and computer simulation. We develop our scheme around grey system theory and establish GM(1,1) model to forecast the sales of commercial housing market. It can further make determination on the production scale of regional commercial housing market, to provide a scientific base for enterprise investment and decision. It can also strength the risk resistance capacity of real estate developers and improve the profitability level of commercial housing project.
A high sensitivity strain sensor based on a selective-filling high birefringent photonic crystal fiber Sagnac interferometer

A high sensitivity strain sensor based on a selective-filling photonic crystal fiebr (SF-PCF) Sagnac interferometer was demonstrated. The SF-PCF was achieved by infiltrating a high index liquid into two symmetrical air holes of the innermost layer. Numetrical results revealed an ultrahigh even theoretically infinite strian sensitivity. A high strain sensitivity with 25 pm/με was experimentally achieved.
A novel pre-clean process of BEOL barrier-seed process to enhance reliability performance of advanced 40nm node

With scaling down of device geometry and keeping improvement of the chip resistance capacitance (RC) delay, it is necessary to reduce k value. A porous ultra low k-value (ULK) dielectric film is integrated into Cu interconnects of advanced 40 nm. There are several papers discussing about the interface effect between ULK film and barrier on reliability performance [1][2]. This paper will discuss the effect of pre-clean process on reliability performance before barrier and Cu-seed layer deposition that will strong affect the interface properties. Also, the early failure mode of each pre-clean process will be discussed as well to clarify the proposed mechanism.
Automating Web Service Development Using a Unified Model

Web service standards are being developed in a loosely coordinated and constantly evolving manner and there is a lack of Web service modeling approaches that efficiently reflect the status of the standardization. Consequently the development and deployment of Web services tend to be ad-hoc and platform-oriented. This introduces potential interoperability issues and maintenance overhead. This paper proposes a model-driven framework that includes a Web service modeling language describing functionality and non-functional properties of service-oriented applications in unified models. This Web service modeling language is based on a Web service meta-model extracted directly from the WS-* standards. We developed a corresponding tool that generates code stubs, configurations and deployment heuristics, along with standard-based artifacts from models. We conducted a real-world case study to validate our approach.
Effective voiding control of QFN via solder mask patterning

Voiding under QFNs is a major challenge in the electronics industry. However, voiding can be suppressed by improving venting accessability on the thermal pad by using solder mask dividing strips. Venting accessability is defined as the perimeter length per unit area of the metal pad. Regardless of the shape and the number of subpads, increasing venting accessability results in a decrease in the total number of voids, the largest voids, and discontinuity. Voiding caused by peripheral vias is comparable to voids caused by hidden vias. Voiding increases with decreasing print coverage and is attributed to insufficient solder. Voiding also decreases with an increase in the number of thermal vias. This phenomenon is attributed to volatiles bleeding through the small voids around the thermal via.