nils-herrmann/clean_scirepeval huggingface dataset:
Fabrication of Ni Microbumps With Small Feature Size on Au Using Electroless Ni Plating With Noncontact Induction

This paper reports a method of fabrication for small-feature-sized nickel (Ni) microbumps on gold (Au) using a newly developed technique called electroless Ni plating with noncontact induction (ENPNI). This technique, differing from conventional electroless Ni plating with contact induction (ENPCI), which directly connects an active metal with an inactive metal to induce Ni electrochemical reaction, is characterized by separation of the active metal and the target metal. The mechanism of ENPNI is interpreted by employing the electric-double layer theory, and some phenomena are explained by the proposed mechanism. Ni microbumps with a diameter of 3-6 μm and a height of 3-4 μm have been successfully fabricated using ENPNI. The resistance of the Ni microbumps is measured, and yield and uniformity are evaluated. By breaking the restriction of contact, ENPNI has the advantages of no need for pretreatment and contact induction, allowing fabrication of microbumps with small feature sizes for applications in which direct contact of an active induction metal is impossible.
Fuzzy logic based neural network models for load balancing in wireless networks

In this paper, adaptive channel borrowing approach fuzzy neural networks for load balancing (ACB-FNN) is presented to maximized the number of served calls and the depending on asymmetries traffic load problem. In a wireless network, the call's arrival rate, the call duration and the communication overhead between the base station and the mobile switch center are vague and uncertain. A new load balancing algorithm with cell involved negotiation is also presented in this paper. The ACB-FNN exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with other algorithms. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.
Enhanced Sensitivity With Five-Phase Heterostructure Magnetoelectric Sensor at Low Magnetic Bias Field

In this paper, we have proposed a five-phase heterostructure magnetoelectric (ME) sensor with high-permeability Fe-based nanocrystalline soft-magnetic alloy FeCuNbSiB, ferromagnetic alloy with constant elasticity FeNi and piezoelectric ceramic lead zirconium titanate (PZT). A built-in magnetic field induced by a spatially varying magnetization within the heterostructure leads to a zero-biased ME response. The corresponding zero-biased ME coefficient reaches as high as 43.75 V/cm·Oe (3.5 V/Oe). Meanwhile, an additional stress produced by FeCuNbSiB is transferred to FeNi, which enhances the effective resonant strain coefficient for FeCuNbSiB/FeNi at low magnetic bias and decreases the required optimum dc magnetic bias Hopt,dc. Hence, the maximum resonant ME coefficient is found to reach 51.5 V/cm · Oe (4.12 V/Oe) at Hopt,dc of only 33 Oe. Hopt,dc for our proposed ME sensor is about one-tenth of that for FeNi/PZT/FeNi. Correspondingly, the five-phase heterostructure ME sensor is able to possess the strong ME sensitivity at low bias or even zero bias.
An automorphic approach to verification pattern generation for SoC design verification using port-order fault model

Embedded cores are being increasingly used in the design of large system-on-a-chip (SoC). Because of the high complexity of SoC, the design verification is a challenge for system integrators. To reduce the verification complexity, the port-order fault (POF) model was proposed. It has been used for verifying core-based designs and the corresponding verification pattern generation has been developed. Here, the authors present an automorphic technique to improve the efficiency of the automatic verification pattern generation (AVPG) for SoC design verification based on the POF model. On average, the size of pattern sets obtained on the ISCAS-85 and MCNC benchmarks are 45% smaller and the run time decreases 16% as compared with the previous results of AVPG.
Individual pitch control strategy of wind turbine to reduce load fluctuations and torque ripples

Wind velocity distribution differences in wind wheel rotation plane caused by wind shear and tower shadow, not only causes load fluctuations of wind turbine blades, but also leads to pulsations of wind turbine aerodynamic torque and output power. In order to reduce the influence of wind shear and tower shadow on the fluctuations of three-bladed wind turbine, an individual pitch control strategy based on the pitch angle signal adjusted jointly by wind turbine output power and rotor azimuth angle is proposed. A band-pass filter is designed to filter out the three times pulsating component of the wind turbine output power, and a PID controller is used to obtain regulatory signal of pitch angle, which is then converted to tiny variable of each blade combining with the azimuth angle signal and superimposed to the reference pitch angle of the collective pitch control. Simulation results on GH Bladed platform show that the proposed individual pitch control strategy is effective to smooth blade load fluctuation, diminish aerodynamic torque ripple, reduce rotor fatigue damage, and prolong life time of wind turbine.
Image segmentation using overlapping group sparsity

Sparse decomposition has been widely used for different applications, such as source separation, image classification and image denoising. This paper presents a new algorithm for segmentation of an image into background and foreground text and graphics using sparse decomposition. First, the background is represented using a suitable smooth model, which is a linear combination of a few smoothly varying basis functions, and the foreground text and graphics are modeled as a sparse component overlaid on the smooth background. Then the background and foreground are separated using a sparse decomposition framework and imposing some prior information, which promote the smoothness of background, and the sparsity and connectivity of foreground pixels. This algorithm has been tested on a dataset of images extracted from HEVC standard test sequences for screen content coding, and is shown to outperform prior methods, including least absolute deviation fitting, k-means clustering based segmentation in DjVu, and shape primitive extraction and coding algorithm.
Possibilistic Petri Nets as a Basis for CNP-Based Bidding Mechanism

As the number of agents increases rapidly on the Internet, discovering appropriate service agents with required capabilities for request agents becomes a crucial issue in multi-agent systems. Two major discovering approaches have been developed: centralized matchmaking approaches and distributed bidding approaches. However, the former approaches may suffer the problem of middle agent overload and can not reflect the dynamic characteristic of agent capabilities, while the later has the problems of the overhead for maintaining contact lists of service agents in each request agent and sending ineffective CFP messages to non-qualified service agents. To address the above problems, in this paper, we propose a CNP-based bidding mechanism based on Possibilistic Petri Nets that facilitates request agents to find preferred service agents. Moreover, our mechanism provides more flexible match that not only supports exact match but also takes the degree of satisfaction into account.
Flexible traction power system adopting energy optimisation controller for AC-fed railway

A flexible traction power system is proposed for AC-fed railway due to its benefits in power flow optimisation, online catenary anti-icing and power quality improvement. In this system, an energy optimisation controller in section post is adopted to provide reactive anti-icing current and control the energy flow in regenerative braking of the locomotives. The energy optimisation controller in traction substations is adopted to eliminate three-phase unbalance in power grid and perform reactive power compensation. The mathematic model of the proposed system is built based on a power transformation analysis and the validity of compensation algorithms is verified by case studies.
A Generalized Model for Robust Tensor Factorization With Noise Modeling by Mixture of Gaussians

The low-rank tensor factorization (LRTF) technique has received increasing attention in many computer vision applications. Compared with the traditional matrix factorization technique, it can better preserve the intrinsic structure information and thus has a better low-dimensional subspace recovery performance. Basically, the desired low-rank tensor is recovered by minimizing the least square loss between the input data and its factorized representation. Since the least square loss is most optimal when the noise follows a Gaussian distribution,  $L_{1}$ -norm-based methods are designed to deal with outliers. Unfortunately, they may lose their effectiveness when dealing with real data, which are often contaminated by complex noise. In this paper, we consider integrating the noise modeling technique into a generalized weighted LRTF (GWLRTF) procedure. This procedure treats the original issue as an LRTF problem and models the noise using a mixture of Gaussians (MoG), a procedure called MoG GWLRTF. To extend the applicability of the model, two typical tensor factorization operations, i.e., CANDECOMP/PARAFAC factorization and Tucker factorization, are incorporated into the LRTF procedure. Its parameters are updated under the expectation–maximization framework. Extensive experiments indicate the respective advantages of these two versions of MoG GWLRTF in various applications and also demonstrate their effectiveness compared with other competing methods.
A Wafer-Level 3D Integration Using Bottom-Up Copper Electroplating and Hybrid Metal-Adhesive Bonding

We report a wafer-level 3D integration scheme using bottom-up copper electroplating (BCE) and hybrid metal-adhesive wafer bonding. Through-silicon-vias (TSVs) with aspect ratio as high as 13 are plated using BCE without forming voids/seams. Cu-Sn bumps electroplated on the TSVs are used together with polymer adhesive for hybrid bonding. A two-layer 3D integration is achieved using BCE and hybrid bonding, validating the feasibility in fabricating wafer-level 3D integration with high aspect ratio TSVs.
Supporting image and video applications in a multihop radio environment using path diversity and multiple description coding

This paper examines the effectiveness of combining multiple description coding (MDC) and multiple path transport (MPT) for video and image transmission in a multihop mobile radio network. The video and image information is encoded nonhierarchically into multiple descriptions with the following objectives. The received picture quality should be acceptable, even if only one description is received and every additional received description contributes to enhanced picture quality. Typical applications will need a higher bandwidth/higher reliability connection than that provided by a single link in current mobile networks. To support these applications, a mobile node may need to set up and use multiple paths to the desired destination, either simply because of the lack of raw bandwidth on a single channel or because of its poor error characteristics, which reduce its effective throughput. The principal reason for considering such an architecture is to provide high bandwidth and more robust end-to-end connections. We describe a protocol architecture that addresses this need and, with the help of simulations, we demonstrate the feasibility of this system and compare the performance of the MDC-MPT scheme to a system using layered coding and asymmetrical paths for the base and enhancement layers.
Improved Dual-Protected Ring Signature for Security and Privacy of Vehicular Communications in Vehicular Ad-Hoc Networks

As illegal access control, privacy disclosure and other threats in vehicular ad-hoc networks become more prevalent, and the importance of safety and privacy protection in vehicular communications grows significantly. The current communication protocols in vehicular communications primarily guarantee infrangibility and unconditional anonymity to achieve security. On board units in vehicular ad-hoc networks form a shared loop called ring signature. In this paper, we propose a dual-protected ring signature algorithm to protect both sending and receiving of a message with secure transmission. We also introduce road side unit-assisted looping to increase ringing probability. The performance of these algorithms is analyzed theoretically and compared with the standard ring signature algorithm in a real vehicle environment. The analysis and comparison results show that the dual-protected ring signature algorithm is superior to the standard ring signature in security, ringing probability, and communication efficiency, and it satisfactorily meets the requirements of secure communication and privacy protection.
Modelling power consumption of a H.263 video encoder

As video transmission is integrated into wireless communication systems, the theory of power control should also be expanded to consider both signal processing power and transmission power when designing new algorithms, since video coding consumes a significant portion of power. To better understand the interaction between signal processing and transmission, it helps to develop power consumption models for video coding. The goal of this work is to model the power consumption of an H.263 video encoder, in which motion estimation is the most computation intensive component. Different models for algorithms using 1) full search motion estimation; and 2) a fast algorithm using spiral order motion estimation are presented for a software H.263 encoder. We observe that one set of model parameters fits all test sequences for full search, whereas the model parameters are sequence specific for the fast algorithm.
Environment and home care for photosensitive patients

The market trend is being driven forward by the need for energy savings and life science, as well as the impressive futuristic aesthetics which smart windows offer. Smart glasses can dynamically change the colors of glass to control the amount of lights and heats that enter a building. They can also be used to create on-demand private for office buildings and living spaces. This article reports the integrated system of smart glasses, the major role of the proposed system plays and the potential protection for photosensitive patients.
Layered cooperative source and channel coding

Cooperative techniques form a new wireless communication paradigm in which terminals help each other in relaying information to combat the random fading and to provide diversity in radio channels. Past work has focused on improving channel reliability through cooperation. We propose to jointly allocate bits among source coding, channel coding and cooperation to minimize the expected source distortion. Recognizing that not all source bits are equal, we further propose to protect the more important bits through user cooperation. To evaluate the gain of layered cooperation, we simulate four modes of communications that differ in their error protection strategy (equal vs. layered, with vs. without cooperation) with a practical channel coder, and show that, for i.i.d. Gaussian sources, layered cooperation can achieve significant performance gains over non-layered/non-cooperative communication. We also carry out an information theoretic analysis illustrating fundamental benefits of layered cooperation.
A neighborhood decoupling algorithm for truncated sum minimization

A heuristic, called the neighborhood decoupling (ND) algorithm, is described. It first selects a minterm and then selects an implicant, a two-step process employed in previous heuristics. The approach taken closely resembles the G.W. Dueck and D.M. Miller (1987) heuristic; however, it makes more efficient use of minterms truncated to the highest logic value. The authors present the algorithm, discuss its implementation, show that it performs consistently better than others, and explain the reason for its improved performance.<<ETX>>
A fast algorithm for the Fourier transform over finite fields and its VLSI implementation

The Fourier transform over finite fields is mainly required in the encoding and decoding of Reed-Solomon and BCH codes. An algorithm for computing the Fourier transform over any finite field GF(p/sup m/) is introduced. It requires only O(n(log n)/sup 2//4) additions and the same number of multiplications for an n-point transform and allows in some fields a further reduction of the number of multiplications to O(n log n). Because of its highly regular structure, this algorithm can be easily implementation by VLSI technology.
Ideas for Detection in Two-Dimensional Magnetic Recording Systems

In two-dimensional magnetic recording, detection for a perfect writer and perfect reader based on an iterative threshold technique are compared to detection employing single threshold and adaptive threshold techniques. The simulation indicates that the algorithm can reach a BER of 9.3% compared to 11.2% and 10.5% for the latter cases when the bit size is 8 by 8 nm with a grain of 8.7 nm diameter. This increases data capacity by 11% to 6.6 TBits/inch2. Additionally, detection with an array of three conventional heads has been studied: the simulation shows that for bits with dimension of 12 × 12 nm, grains of 8.7 nm diameter and reader width of 18 nm, the BER drops from 11.3% for a single conventional head to 5.4% for the head array with a two-dimensional generalized partial response equalizer at the optimum offset of 10 nm. The density is increased by 42%, reaching 4.0 Tbits/Inch2 .
A novel envelope edge detector for ultra-low power sensor wake-up circuit

Voltage comparators have been widely used in low-power sensor wake-up circuits for extracting digital bits from the envelope of received RF signals. This paper presents an alternative circuit to such comparators. The proposed circuit extracts digital bits by detecting the falling edge of the envelope signal. Since it essentially compares the values of the same signal at different times, it is potentially more robust than the comparator based approach, which compares the peak voltage of the envelope signal with another reference voltage. The design issues for using the proposed edge detection circuit into different wake-up receiver architectures are discussed and simulation results are also presented to demonstrate the performance of the proposed circuit.
Error resilient video multicast using Randomized Distributed Space Time Codes

In this paper we study a two-hop cooperative transmission scheme where multiple relays forward the data simultaneously using Randomized Distributed Space Time Codes (R-DSTC). We propose to integrate this randomized cooperative transmission with layered video coding and packet level Forward Error Correction (FEC) to enable error resilient video multicast. Data rates in both hops as well as the FEC rate are adopted to maximize the video quality. Our results show that while rate-adaptive direct transmission provides better video quality than conventional multicast, randomized cooperative scheme outperforms both strategies significantly.
Rerouting schemes for dynamic traffic grooming in optical WDM mesh networks

Traffic grooming in optical WDM mesh networks is a two-layer routing problem to pack low-rate connections effectively onto high-rate lightpaths, which, in turn, are established on wavelength links. We employ the rerouting approach to improve the network throughput under the dynamic traffic model. We propose two rerouting schemes, rerouting at lightpath level (RRAL) and rerouting at connection level (RRAC). A qualitative comparison is made between RRAL and RRAC. We also propose the critical-wavelength-avoiding one-lightpath-limited (CWA-1L) and critical-lightpath-avoiding one-connection-limited (CLA-1C) rerouting heuristics, which are based on the respective rerouting schemes. Simulation results show that rerouting reduces the connection blocking probability significantly.
Fast CU partition decision using machine learning for screen content compression

Screen Content Coding (SCC) extension is currently being developed by Joint Collaborative Team on Video Coding (JCT-VC), as the final extension for the latest High-Efficiency Video Coding (HEVC) standard. It employs some new coding tools and algorithms (including palette coding mode, intra block copy mode, adaptive color transform, adaptive motion compensation precision, etc.), and outperforms HEVC by over 40% bitrate reduction on typical screen contents. However, enormous computational complexity is introduced on encoder primarily due to heavy optimization processing, especially rate distortion optimization (RDO) for Coding Unit (CU) partition decision and mode selection. This paper proposes a novel machine learning based approach for fast CU partition decision using features that describe CU statistics and sub-CU homogeneity. The proposed scheme is implemented as a "preprocessing" module on top of the Screen Content Coding reference software (SCM-3.0). Compared with SCM-3.0, experimental results show that our scheme can achieve 36.8% complexity reduction on average with only 3.0% BD-rate increase over 11 JCT-VC testing sequences when encoded using "All Intra" (AI) configuration.
Estimating distortion of coded and non-coded frames for frameskip-optimized video coding

This paper focuses on the problem of estimating the distortion for coded and non-coded frames in a video coder that employs variable frameskip. The distortion for coded frames is given by classic rate-distortion models, however the distortion for non-coded frames has not been considered. Based on the optical flow equation, we formulate a method for estimating the distortion of the non-coded frames. Simulations verify that our estimation is quite accurate over a range of sequences with varying scene complexity. Such methods can be used to optimize the trade-off between spatial and temporal quality in the video coding process.
Optimal coding rate and power allocation for the streaming of scalably encoded video over a wireless link

Scalably encoded information results in files which can be truncated at an arbitrary point and decoded, as supported by the JPEG-2000 (image) and MPEG-4 (video) standards. This work introduces a tractable, yet flexible analytical model for resource management involving scalably encoded video. Each segment of video of a predetermined length yields a file that can be truncated and decoded independently of other segments. The problem is set up as a joint optimization of transmission power, and coding rate (where to truncate?). The analysis reveals that any one of these variables uniquely determines the other. The terminal should truncate the file at the point that maximizes quality per unit of power employed.
QoE-Aware Intelligent Vertical Handoff Scheme Over Heterogeneous Wireless Access Networks

As a measurement, quality of service (QoS) has been commonly taken into account in the traditional vertical handoff schemes for the heterogeneous wireless access networks. However, the QoS is not sufficient to correlate well with the user satisfaction. In this paper, quality of experience (QoE) is introduced into the decision mechanism of the vertical handoff and a random neural network -based QoE estimation is proposed to determine the correlation between the QoE and the QoS in the heterogeneous networks. In addition, a Q-learning-based vertical handoff algorithm, designated as a QoE-Q algorithm, is presented in order to maximize the QoE utility for users. It can be observed from the simulation results that the proposed method not only outperforms the existing schemes with enhanced call blocking probability and handoff dropping probability property but also obtains better QoE performance in the service charges and the terminal power consumption than other schemes.