nils-herrmann/clean_scirepeval huggingface dataset:
A low-temperature metal-doping technique for engineering the gate electrode of replacement metal gate CMOS transistors

This work describes a low-temperature metal annealing technique that can be a helpful tool for fabricating the gate electrode of replacement metal gate CMOS transistors. The goal of the technique is to form doped metal (TaSiN, TiSiN, TaCN, TaPN, etc.) to change the work function of the metal gate electrode. The low-temperature doping process was performed in an ambient containing the precursors of the dopants, including silane, phosphine, and carbon-rich organic precursors. Experiments have been conducted to incorporate dopants such as P, C, Si into TaN or TiN. The transistor and C-V data show the resultant doped metals are suitable materials for P- and N-MOSFETs by providing the right metal work function.
An effective scattering model for 3-D urban propagation: Application to moving target detection at high-frequency bands

In the present paper, we focus on the design of an effective 3-D modelling for the simulation of urban environment propagation, which integrates the Urban Building Model (UBM), Ray-Tracing (RT) technique and the Uniform Theory of Diffraction (UTD). UBM is an object-oriented data structure, in which each building is an object. Besides that, we also take into account some other urban elements such as car parking, traffic lights... Meanwhile, the RT technique helps us not only to delineate the propagation path but also to explain the interaction mechanism of rays through a complex area. In this work, we use the Shooting and Bouncing Ray (SBR) technique. Last of all, the asymptotic method UTD will be employed in order to calculate the scattered far-field attached to the rays. These rays propagated from the transmitter, after some interactions, mainly reflection and diffraction, inside an urban area, are intercepted by the receiver. This proposed model will be applied at high-frequency bands (X, K). As a consequence, we will evaluate the detection capability of the model for a target, i.e. a car, moving inside a realistic urban area. The simulated results have shown that the model can predict precisely the motion direction of the considered target.
A New 6-DOF Haptic Device for Teleoperation of 6-DOF Serial Robots

A new 6-DOF parallel haptic device is developed and presented in this paper. The haptic device consists of two 3-DOF parallel structures connected with a steering handle. The design satisfies requirements of low inertia, quick motion, large orientation angles, and large applied torques. Kinematics for position and differential motion is analyzed for the 6-DOF haptic device. Static force relation between the user force and motor torque is also analyzed and implemented on the controller. The control system for the teleoperation of 6-DOF serial robot is developed. The closed loop impedance force control system is analyzed and realized on the digital controller. Tele-operation of a 6-DOF serial robot using this haptic device is demonstrated. Experiments show that dynamic forces caused by the haptic device are well compensated with the closed loop force control.
Abandoned Object's Owner Detection: A Case Study of Hybrid Mobile-Fixed Video Surveillance System

In this paper, a new framework of hybrid mobile-fixed video surveillance system (HMFVSS) is introduced. The purpose of this framework is to overcome common problems of existing mobile or fixed video surveillance systems: (1) moral harassment: due to unfriendly or unnaturally installed mobile sensors, and (2) blind areas: due to narrow-scope moving of fixed cameras. A case study of abandoned object's owner alert system (AOOAS) is also presented to emphasize the framework's advantages. IP cameras and "Spyglass" (i.e. a mobile camera embedded on glasses) are used as fixed and mobile sensors, respectively. There are three main tasks are inherited, developed, and integrated: (1) image registration for automatically locating abandoned object, (2) common histogram based abandoned object's owner detection, and (3) faces recognition. The experimental results with careful evaluation and comparison with others shows that the proposed framework moves a step ahead in video surveillance system.
A Retina-Based Perceptually Lossless Limit and a Gaussian Foveation Scheme With Loss Control

In this paper, we propose a new limit that promises theoretically achievable data reduction ratios up to approximately 9:1 with no perceptual loss in typical scenarios. Also, we introduce a novel Gaussian foveation scheme that provides experimentally achievable gains up to approximately 2 times the compression ratio of typical compression schemes with less perceptual loss than in typical transmissions. Both the proposed limit and foveation scheme shares the same background material: a model of image projection onto the retina; a model of cones distribution; and, subsequently, a proposed pointwise retina-based constraint called pixel efficiency. Quantitatively, the lattermost is globally processed to reveal the perceptual efficiency of a display. Analytical results indicate that in general the perceptual efficiency of displays are low for typical image sizes and viewing distances. Qualitatively, the pixel efficiency is used together with a lossy parameter to locally control the spatial resolution of a foveated image. Practical results show that proper use of the lossy parameter in the foveation filtering can increase the subjective quality of images.
Analysis, design and experiment investigation of a novel wave energy converter

This study presents an innovative design for a wave energy converter (WEC). The system is based on a novel mechanical power take-off (PTO) device that can absorb wave energy by converting the bidirectional motion of an ocean wave into the one-way rotation of an electric generator. First, the PTO mechanism and configuration are described in detail. A coupled mechanical and hydrodynamic time-domain simulation of a hemispherical floating buoy connected to a bidirectional gearbox and torque generation device under regular waves were modelled in MATLAB®/Simulink®. The hydrodynamic forces acting on the semi-submerged floating buoy are calculated by employing linear potential wave theory. The friction behaviour in the PTO system is modelled by using Brian Armstrong's method. Next, an average wave energy and absorbed energy calculation was applied to investigate the conversion efficiency of the WEC. Finally, the experimental setup is carried out in a water tank under various conditions to evaluate the performance of WEC and validate the modelling. The results indicate that high-energy conversion efficiency of generating electricity from waves is approachable, thanks to the high efficiency of the proposed device.
Balancing Precision and Battery Drain in Activity Recognition on Mobile Phone

Many achievements have been announced with real time running capability for activity recognition (AR) using mobile accelerometer. However, they also have weak points including low accuracies especially in multiple-subject activity recognition and lacking of evidences about power consumption. In this paper, we contribute a novel method for extracting features on time domain and frequency domain. These different features were then respectively applied to Support Vector Machine (SVM) classifier and Dynamic Time Warping (DTW) method in order to find out the most effective combinations. Our own data and SCUTT-NAA dataset were used in our experiment. Accuracy rates of 95% and 97% in multiple-subject AR were achieved by respectively using SVM and DTW from time domain features (TF). These approaches were then implemented on a mobile phone to measure the power consumptions. SVM using time feature method was found as the most effective method for balancing accuracy and energy consumption.
A novel design of hollow microneedle for blood sample collection

In this study, a novel design of microneedle is proposed based on structural and fluidic analysis. For blood collection applications, a hollow microneedle is designed with optimal features. The features and size of this microneedle provide improved structural strength for optimal skin penetration. Mechanical evaluations are studied with intensive calculations of maximum allowance axial and transverse forces, followed by numerical simulation of the insertion process. In addition, the fluid behavior is also investigated. The dual diameter design of the hollow part was shown to maximize the extraction efficiency and minimize the clogging problem for high-volume collection of blood. Our study proposes a design guideline on making a high-performance microneedle for blood collection.
A detail-preserving mixture model for image segmentation

This paper presents a new finite mixture model for image segmentation. First, in order to take into account the spatial dependencies in an image, existing mixture models use a constant temperature parameter (β) throughout the image for every label. The constant value of β reduces the impact of noise in homogeneous regions but negatively affects segmentation along the border of two regions. We propose a new way to use a different value of β throughout the image. Secondly, in order to incorporate the correlation between each centre pixel and its neighboring pixels, existing mixture model gives the same importance to all pixels in a neighborhood window. We assign different weights to different pixels appearing in the window, which is based on the fact that the clique strength should be reduced with distance. Thirdly, our model is based on the Student's-t distribution, which is heavily tailed and more robust than Gaussian. We exploit Dirichlet distribution and Dirichlet law to incorporate the spatial relationships between pixels in an image. Finally, expectation maximization (EM) algorithm is adopted to maximize the data log-likelihood and to optimize the parameters. The performance is compared to other existing models based on the model-based techniques, demonstrating superiority of the proposed model for image segmentation.
Covariance-based texture description from weighted coherency matrix and gradient tensors for polarimetric SAR image classification

The present paper proposes a texture-based unsupervised classification algorithm for fully polarimetric SAR (PolSAR) images. Here, the main motivation is to combine polarimetric information and local structure gradients from PolSAR image data to describe textural features and then use them for classification purpose. In this work, the notion of PolSAR image textures is characterized by two key features. First, the polarimetric coherency matrix is estimated using a weighted averaging operator based on patch similarity. Second, the image local geometry is taken into account by exploiting the structure gradient tensors. These characteristics are then integrated into texture descriptors via the approach of covariance matrix. Unsupervised classification stage is finally achieved by employing an adapted distance measure for covariance-based descriptors. Experiments performed on very high resolution complex PolSAR images using the proposed algorithm provide very promising results in terms of terrain classification and discrimination.
Adaptive tracking in the time-frequency plane and its application in causal real-time speech analysis

This paper proposes a causal approach to adaptive estimation of time-frequency localized signals using Adaptive Notch Filters (ANF). By adaptively estimating the envelope of each sinusoidal component, it is possible to specify the tracking quality and restart the ANF unit whenever the tracked sinusoid disappears, as well as preventing the ANF from “tracking” non-existent sinusoids (the frequency mis-lock situation). Employing multiple ANFs allows an efficient approach to tracking time-frequency localized signals such as speech.
Collaborative and Compressed Mobile Sensing for Data Collection in Distributed Robotic Networks

In this paper, we exploit an integration between the mobility of robots and the collaboration between them to sample sensing areas that need to be observed. A collaborative and compressed mobile sensing algorithm is proposed for distributed robotic networks to build scalar field maps. In order to move in the sensing field and to avoid collision with obstacles and with each other, a control law is embedded into the robots. At a sampling time, each robot senses and adds data within its sensing range and collaborates to the others by exchanging data with its neighbors. A compressed sensing (CS) measurement created is a sum of scalar values collecting by a connected group of robots. A certain number of CS measurements is required at each robot to reconstruct all sensory readings from points of interest visited by the group of robots. The method reduces significantly data traffic among robots. We further analyze and formulate power consumption for the robots, and suggest some optimal cases for the robot to consume the least power.
A joint network and server load balancing algorithm for chaining virtualized network functions

Chaining virtualized network functions (VNF) is an effective practice to deploy network services in network operator's data centers. Two common concerns arise in such a deployment are network load balancing and server load balancing. In this study, motivated by the argument that such two concerns should be jointly addressed for efficiently chaining VNFs in a data center environment, we propose a 2-phase algorithm, Nearest First and Local-Global Transformation (NF-LGT), which concurrently supports network and service load balancing. The algorithm firstly constructs service chains by a greedy strategy which both considers network latency and server latency. Then a searching technique is applied to improve the solutions. We have implemented the algorithm using Software-defined networking (SDN)/OpenFlow concept. The experimental results indicate that, compared with a sequential approach, NF-LGT improves the system bandwidth utilization up to 45%.
Combined external and internal electrodes in EIT for deep changes: A simulation study

Electrical Impedance Tomography can detect changes within human body like tumours, ventilation or cardiac abnormalities using electrodes on the surface. However, EIT images are poor when the changes occur far from the electrodes, in the deep, innermost tissue. A possible method to improve measurements is to position one or more internal electrodes near the expected location of the impedance change when this is known a priori such as during cardiac ablation or other image guided procedures. This paper aims to explore this idea by comparing three different electrode configurations: the conventional external electrodes, the combination of external and internal electrodes and only internal electrodes. The z-score, which expresses the level of distinguishability or sensitivity to an impedance change within the measured object, is used for comparison as it is not biased by the image reconstruction approach. We model a 3D simulated homogenous cylinder tank filled with 0.9% saline containing a small cylindrical anomaly. The internal electrodes were assumed to be located on a cardiac mapping catheter, modeled with electrodes placed on the boundary of a small non-conductive ball, placed near the tank's center. Zero-mean Gaussian noise of 100-500μV was added to simulated electrode voltage measurements. Finally, the results showed that the combination of internal and external electrodes offered the highest consistent distinguishability for most of the patterns of current and voltage measurement and noise levels. The configuration using only internal electrodes starts with worse distinguishability and it decreased dramatically corresponding to the further distance of object.
A Novel Multi-Terminal Based Evaluation Method for an HTS DC Power Cable

High current capacity is one of the advantages of a superconducting power cable system. However, it creates difficulties when experimenting to analyze its characteristics. Short-length superconducting cables for a laboratory-scale experiment system present problems: large operating current and current distribution by terminal resistance. Experimental conditions, such as transient states, are limited by power supply capacity. In this paper, the authors suggest a new experimental method for the high-temperature superconducting (HTS) power cable to reduce the capacity of a power supply and solve current distribution problems. For the suggested method of this paper, each HTS wire has separated terminal and each HTS wire was connected in series through the separated terminal. All of HTS wires in the HTS power cable are insulated and connected in series. The cross-sectional area of the HTS power cable is the same, but the terminal structure is different. Thus, all HTS wires have the same current and cross-sectional area of HTS power cable. It is possible to test a large capacity HTS power cable under the transient state or fault conditions using a small-size power source. The design concept, configuration of the experiment system, and the experimental results were discussed in detail in this paper.
Design and implementation of a RBF-based PI Controller for PMSM Drives

This work presents a hardware implementation of a RBF NN (Radial Basis Function Neural Network), then use this RBF NN to design a PI controller for PMSM (Permanent Magnet Synchronous Motor) drives. In this paper, firstly, the mathematical model of PMSM drives and the architecture of the RBF NN which consists of an input layer, a hidden layer of nonlinear processing neurons with Gaussian function and an output layer are described. Secondly, a very high speed IC hardware description language (VHDL) is adopted to describe the behavior of the RBF - PI Controller, and the data type applies 32bit length Q24 format and 2's complement operation. Additionally, finite state machine (FSM) is applied for reducing the hardware resource usage. Thirdly, to verify the correctness of the designed VHDL code for computing the RBF-PI, based on electronic design automation (EDA) simulator link, a co-simulation work is constructed by Simulink and ModelSim which the input stimuli and output responses are run in Simulink and the computation of the RBF-PI is performed in ModelSim. Finally, some simulation results validate the effectiveness of the proposed RBF-based PI (RBF-PI) Controller for PMSM Drives.
23.3 A highly integrated smartphone SoC featuring a 2.5GHz octa-core CPU with advanced high-performance and low-power techniques

This paper describes the high-performance CPU design of a heterogeneous octa-core CPU complex, incorporated into a highly integrated mobile SoC for smartphone applications. The SoC is fabricated in a 28nm high-x metal-gate CMOS, and has a die size of 89mm2. Cu pillars are used for the die-to-substrate interface with fine substrate trace pitch. The SoC is packaged in a 14mmx14mm, 832 ball, 0.4mm pitch BGA. An integrated cellular modem supports rei. 9, cat. 4 LTE (FDD and TDD), while additional cellular and RF connectivity includes DC-HSPA+, TD-SCDMA, EDGE, 802.11ac, Bluetooth LE, multi-GNSS (GPS, GLONASS, Beidou, Galileo & QZSS), and ANT+. Multimedia features are highlighted by a high-performance Power-VR Series6 GPU, support for WQXGA displays (2560×1600), a 20Mpixel image processor and camera interface, and ultra-HD video playback support for H.264 and VP9.
Cluster-Based Energy-Efficient Data Collection in Wireless Sensor Networks Utilizing Compressive Sensing

In this paper, an integration of compressive sensing (CS) and clustering in wireless sensor networks (WSNs) is proposed to significantly reduce the energy consumption related to data collection in such networks. Both compressive sensing (CS) and clustering have been proved to be efficient ways to reduce the energy consumptions in WSNs, however, there is little study about the integration of them for further gains. The idea is to partition a WSN into clusters, in which each cluster head collects the sensor readings within its cluster and forms CS measurements to be forwarded to the base station. The spatial correlation of the readings in a WSN results in an inherent sparsity of data in a proper basis such as discrete cosine transform (DCT) or Wavelet. This sparsity can then facilitate the application of the CS in data collection in WSNs. This way, we only need to forward &laquo; N CS measurements from N sensor nodes. An important issue that needs to be considered for applying CS in the data collection problem is the underlying routing mechanism. Some related studies employ minimum spanning tree, random walk, or gossiping as the routing mechanism. However, we propose applying CS on top of a clustering algorithm to reduce the energy consumption. Under this novel framework, we study different clustering techniques and the properties of the block diagonal measurement matrix that is formed based on the clustering algorithm. We further formulate and analyze the total power consumption, based on that we can obtain the optimal number of clusters for reaching the minimum power consumption.
Capacity of the energy harvesting channel with a finite battery

We consider an energy harvesting channel, in which the transmitter is powered by an exogenous stochastic energy arrival process, which can be stored in a battery of finite size. We provide an n-letter expression for the capacity of this channel under various assumptions on the availability of energy arrival information: causal and noncausal knowledge of the energy arrivals at the transmitter with and without knowledge at the receiver. We then proceed to deriving lower and upper bounds on the capacity that are easier to compute and are within a constant gap of each other. In particular, we show that the power control problem for energy-harvesting communication, extensively studied in the communication theory literature over the recent years, provides an upper bound on the true information-theoretic capacity of the channel. For example, the offline power control problem provides an upper bound on the information-theoretic capacity with noncausal knowledge of the energy arrivals at the transmitter and the receiver, while the online problem is an upper bound on the capacity with causal information. Perhaps more surprisingly, we also show that given an optimal power control policy there is a natural way to construct an explicit scheme which achieves a rate within a constant gap of the upper bound for any i.i.d. energy harvesting process and any battery size. This shows that these two different formulations of the energy-harvesting communication problem, so far studied in isolation, are strongly coupled; solving the power control problem is almost sufficient to solve the information-theoretic problem.
A novel solution for global connectivity in MANET

Providing an effective Internet access solution for mobile nodes in a mobile ad hoc network (MANET) is a challenging task because of the dynamic nature of the ad hoc network. This dynamic nature leads to difficulties in addressing, routing and data delivery. In this paper, we proposed a new solution for Internet access by using multiple access routers (ARs) simultaneously. This brings a lot of benefits such as effective soft-handoff, throughput improvement, load balancing between ARs, etc. In addition, hierarchical mobile IP (HMIP) is incorporated into our solution to speed up handoff, and to maintain the Internet connection using the regional care of address (RCoA). The simulation results for both proactive and reactive ad hoc routing protocols with two ARs show an improvement of network throughput, especially in the small sized network.