nils-herrmann/clean_scirepeval huggingface dataset:
Admission control design for integrated WLAN and OFDMA-based cellular networks

We propose a QoS-aware admission control scheme (ACS) considering slow and fast calls for the integrated WLAN and OFDMA-based cellular network where only slow calls are allowed to connect with WLAN to maintain low handover overhead. The proposed ACS allows efficient traffic offloading from the macrocell to WLAN and considers QoS requirements for users in terms of minimum rates in all regions. The fractional frequency reuse (FFR) technique is assumed to be employed for interference mitigation in the cellular network. We also propose a novel bandwidth (BW) borrow-return strategy in the proposed ACS to improve the system performance. We then develop an analytical model to derive the blocking probabilities for calls in different areas. Numerical results demonstrate the performance enhancement of the ACS with the BW borrow-return strategy and the usefulness of the proposed analytical model in determining the size of WLAN offloading region.
A fan-beam array antenna with reflector back for 5 GHz outdoor Wi-Fi applications

This paper introduces a sprout-shaped fan beam linear array antenna for outdoor Wi-Fi access points. The proposal is made up of two main parts which are a linear array and a reflector. The array has been placed on Rogers RT/Duroid 5870 tm with the dimensions of 390 mm × 30 mm × 1.575 mm, and consists of 10 single elements in sprout-shape. The reflector, which is made of FR4-epoxy, is relatively wider with size of 390 × 70 × 1.6 mm3. The proposed antenna has really good simulation results with the wide bandwidth of 590 MHz, the gain of 17.2 dBi and the low side lobe level of -15.4 dB at 5.6 GHz. A prototype has been fabricated and measured to validate the simulation results. It is demonstrated that a good agreement between simulation and measurement has been obtained. The array antenna sample can be a good candidate for 5GHz outdoor Wi-Fi applications.
An effective flow aggregation for SDN-based background and foreground traffic control

Core networks have to contend with a huge amount of traffic, making the networks heavy, congested or even fail, specifically at peak times. However, not all traffic has to be processed immediately. BG) traffic can be delayed to yield network resources for foreground (FG) traffic when needed. This paper proposes an efficient approach to BG and FG traffic control leveraging software defined network (SDN) techniques. We devised an effective data structure, namely a flow tree, for flow aggregation, to reduce the inherent communication costs (between the Controller and Openflow switches) and the storage cost in the switch's expensive memory. Experimental results from both simulated and real datasets reveal the effectiveness and efficiency of the proposed scheme, confirming the viability of the proposed SDN-based BG and FG traffic control approach.
Bi-orthogonal filter banks with directional vanishing moments [image representation applications]

In this paper we study 2D nonseparable filter banks that annihilate information along a certain discrete direction. This is done by having filters with directional vanishing moments (DVM). We study the approximation property of such filters and the design problem providing conditions for its solvability. In particular, we completely characterize the solution and propose a design procedure utilizing the mapping technique. Nonlinear approximation experiments with the contourlet transform indicate that compared with the traditional filters, the new filters designed with DVM provide gains in SNR and visual quality due to their short size.
CNTs based lubricating oils for UAZ 31512 engines

The obtained results on application of the carbon nanotubes (CNTs) in lubricating oils for UAZ 31512 engine are presented. The calculation results showed that the thermal conductivity of lubricating oils increase about 10% when using lubricating oil with 0.12 vol% of CNTs concentration. The experimental results on Ulyanovskiy Avtomobilnyi Zavod 31512 (UAZ 31512) engine on pedestal at free load showed that the temperature of engine dropped about 10°C and the fuel saving was up to 10% when using lubricating oil with 0.12 vol% of CNTs concentration.
A novel micromixer with multimixing mechanisms for high mixing efficiency at low Reynolds number

In this paper, we propose a novel passive micromixer structure for high mixing efficiency based on the combination of multimixing principles. With a special structure, our proposed micromixer can create vortices, transversal flows and chaotic advections to provide high mixing efficiency event at low Reynolds number. Moreover, two narrow slits at two ends of each mixing unit remarkably reduce pressure drop, making it easy to be built into micro-devices. We conduct intensive simulation to evaluate the performance of our proposed micromixer by numerically solving the governing Navier-Stokes equation and convection-diffusion equation using COMSOL Multiphysics package. The simulation results indicate that our proposed micromixer may achieve stable mixing efficiency of 80% or above for a wide Reynolds number range from 0.5 to 100. Especially, at Reynolds number (Re) > 30, mixing efficiency is less dependent on Reynolds number. The mixing efficiency of our micromixer is two times higher than mixing efficiency of micromixer based on unbalanced splits and collisions of fluid at the same mixing channel length of 5mm. At Re = 30, our proposed micromixer has high mixing efficiency of 85% with moderate pressure drop ΔP = 12,600Pa.
A revisit to cost aggregation in stereo matching: How far can we reduce its computational redundancy?

This paper presents a novel method for performing an efficient cost aggregation in stereo matching. The cost aggregation problem is re-formulated with a perspective of a histogram, and it gives us a potential to reduce the complexity of the cost aggregation significantly. Different from the previous methods which have tried to reduce the complexity in terms of the size of an image and a matching window, our approach focuses on reducing the computational redundancy which exists among the search range, caused by a repeated filtering for all disparity hypotheses. Moreover, we also reduce the complexity of the window-based filtering through an efficient sampling scheme inside the matching window. The trade-off between accuracy and complexity is extensively investigated into parameters used in the proposed method. Experimental results show that the proposed method provides high-quality disparity maps with low complexity. This work provides new insights into complexity-constrained stereo matching algorithm design.
An Approach for Decision Support on the Uncertainty in Feature Model Evolution

Software systems could be seen as a hierarchy of features which are evolving due to the dynamic of the working environments. The companies who build software thus need to make an appropriate strategy, which takes into consideration of such dynamic, to select features to be implemented. In this work, we propose an approach to facilitate such selection by providing a means to capture the uncertainty of evolution in feature models. We also provide two analyses to support the decision makers. The approach is exemplified in the Smart Grid scenario.
Bilateral Bargaining Game and Fuzzy Logic in the System Handling SLA-Based Workflow

In the business Grid, the owner of a workflow is assumed to ask an SLA Workflow broker to execute the workflow for him. The price for executing a workflow on the Grid is negotiated between the user and the broker. Determining a price that satisfies both, the user and the SLA workflow broker, is a difficult task. This paper proposes a method using bilateral bargaining game model based on fuzzy logic to determine the price that the user and the broker could accept after the first negotiation round. We also analyze many parameters affecting the price determination process. The validation results show that the approach is suitable with business rules.
Adaptive control for piezoelectric actuator using discrete-time Bouc-Wen model

In this paper, we consider hysteresis problem which is nonsmooth, nonlinear, and resided in piezoelectric actuators (PEA). A new discrete-time hysteretic model is introduced which is inspired by the famous Bouc-Wen model. We try to fuse the new model with the adaptive control techniques, where the unknown parameters in the model are not needed to be identified. The control algorithm guarantees the stability of system. Experimental results verify the effectiveness of the new model and the proposed algorithm.
Compressive wireless mobile sensing for data collection in sensor networks

In this paper, we exploit an integration between Compressive Sensing (CS) and the random mobility of sensors in distributed mobile sensor networks (MSN) to sparsely sample sensing areas. A small number of mobile sensors are deployed randomly in an area to observe a large number of positions. At each sampling time, the sensors collect data at their random positions and exchange their readings to the others through their neighbors within the sensor transmission range to form one CS measurement at each sensor. After M rounds of moving, sensing and sharing data, each mobile sensor has M CS measurements to be able to reconstruct all readings from all positions that need to be observed. Network performance is analyzed considering the number of sensors deployed in the networks, the convergence time and the sensor transmission range. Expressions for transmission power consumption are formulated and optimal low power cases are identified.
A Novel Computation for Supplementing Interference Analytical Model in 802.11-Based Wireless Mesh Networks

Interference impact problem in multi-hop networks such as Wireless Mesh Networks (WMNs) has been attracted many studies due to its challenges in recent years. Three-Markov chain model was a favorable model to analyze interference quantity around nodes. In this paper, we adopt a simple computation method to calculate steady states of node behavior's in three-state Markov chain and propose a novel computation for supplementing interference analytical model in 802.11-based wireless mesh networks.
Chaos synchronization on Visible Light Communication with application for secure data communications

This paper studies the possibility of implementing a chaos synchronization scheme in the context of Visible Light Communication (VLC) with potential application to message encryption. For this, a unidirectional transmitter-receiver configuration is employed whereby the encrypted data is sent over a VLC optical wireless channel. More precisely, the classical chaotic masking, with the use of a Rossler oscillator and a corresponding nonlinear observer, and the inverse system approach with Lorenz oscillators, have been employed to demonstrate the proof of concept of chaos synchronization in VLC. By employing a pseudo random binary data sequence as a message it is shown that acceptable message recovery is obtained despite the presence of delay, attenuation and noise in the channel. Simulations results using Matlab Simulink are provided to show the performance and the level of the synchronization achieved for both methods.
Compressive sensing based energy-efficient random routing in wireless sensor networks

Using random walk (RW) to collect data in wireless sensor networks (WSN) has been proven to be an energy-efficient method. The integration between compressive sensing (CS) and RW provides some different points of view about data collection in WSNs. Based on a small certain number of CS measurements (M), all raw sensor readings from N nodes can be recovered at the base-station (M ≪ N). In this paper, we analyze RW based on theory and practice. We investigate the trade-off between exploring the measurement matrix and setting up the length for RWs to achieve the energy consumption smallest for WSNs. In addition, we formulate the total power consumption that contains the average consumed energy of each RW and the average consumed energy to send measurements in multi-hop through intermediate nodes from RWs to the base-station (BS). We analyze and suggest the optimal case for the networks to spend the lowest energy that helps sensors to prolong their lifetime or the network connection.
Automatic test framework for video streaming quality assessment

To understand better what happens when video streaming takes place, this paper introduces a framework to simulate a real-time video streaming over wireless channels. The system is divided into many modules and is simulated with different tools. DUMMYNET is used for the network simulator while FFMPEG is for coder/encoder and sender/receiver module. The video quality is measured by spatial (SSIM and PSNR) metrics. To permit automatic characteristic, a system controller with JENKINS is used to control the encoder, sender, network, receiver and decoder. A script at this server can be run to simulate automatically the system with many test cases for the practical network setting. The simulation results show that the simulated system can estimate accurately the quality of the videos transmitted over wireless network.
3D impact-based ALN/SUS microenergy harvesters for multi-directional and low-frequency vibrations

In this study, we developed the novel three-dimensional (3D) impact-based microenergy harvesters for harvesting random vibrations from multiple directions. The device consisted of a 3D box built up from the flexible AlN/SUS-based microcantilevers and the free-moving SUS ball. When the ball receives external vibration energy, it might strike the cantilevers on the surrounding walls and then the device generates electricity. The merit of this configuration is the device could generate the electricity from low frequency and multi-directional vibrations. The developed device provided the peak output power 70 nW on average for the triaxial vibrations at the extremely low frequency of 4.5 Hz which frequency regime is very difficult to be harvested by the published microenergy harvesters.
A Fast Discrete Wavelet Transform Using Hybrid Parallelism on GPUs

Wavelet transform has been widely used in many signal and image processing applications. Due to its wide adoption for time-critical applications, such as streaming and real-time signal processing, many acceleration techniques were developed during the past decade. Recently, the graphics processing unit (GPU) has gained much attention for accelerating computationally-intensive problems and many solutions of GPU-based discrete wavelet transform (DWT) have been introduced, but most of them did not fully leverage the potential of the GPU. In this paper, we present various state-of-the-art GPU optimization strategies in DWT implementation, such as leveraging shared memory, registers, warp shuffling instructions, and thread- and instruction-level parallelism (TLP, ILP), and finally elaborate our hybrid approach to further boost up its performance. In addition, we introduce a novel mixed-band memory layout for Haar DWT, where multi-level transform can be carried out in a single fused kernel launch. As a result, unlike recent GPU DWT methods that focus mainly on maximizing ILP, we show that the optimal GPU DWT performance can be achieved by hybrid parallelism combining both TLP and ILP together in a mixed-band approach. We demonstrate the performance of our proposed method by comparison with other CPU and GPU DWT methods.
Design of reduced-order observers for neutral time-delay systems

This paper presents a method for the design of reduced-order observers for a class of linear time-delay systems of the neutral-type. Conditions for the existence of reduced-order observers that are capable of asymptotically estimating any given function of the state vector are derived. A step-by-step design procedure is given for the determination of the observer parameters. A numerical example is given to illustrate the design procedure.
Applying Virtual Reality for In-Door Jogging

We propose an "In-place Virtual Tour" system that generates the smart virtual environment adapting to a user's activities when jogging. Our proposed system automatically detects the main region of frames captured from a regular camera, analyses the difference in foreground in the main region of consecutive frames to estimate the user's intensity level, then renders virtual scene with appropriate speed. The system does not require any special devices as existing interactive fitness games. Experimental results demonstrate the effectiveness and the realtime manner of the proposed system. Our proposed method can also be applied to develop various exciting interactive games to stimulate excitement for users when doing in-door fitness exercises or to create virtual environment for museums where visitors just stay in place to explore scenes in museums.
A multi-storey building actuator and sensor system using 6L0WPAN based Internet of Things: Practical design and implementation

The development of IPv6 has enabled the idea of IP-based Internet of Things where the every embedded device connected to the Internet has its unique IPv6 address. 6LoWPAN is proposed and defined by Internet Engineering Task Force (IETF) to be an adaption layer to apply IPv6 to the IEEE 802.15.4 standard, which allows direct access to control and monitor smart devices from over the world through Internet. 6LoWPAN-based Internet of Things technology is a scalable system which can help to lower expense and decrease the complexity of smart building monitoring and controlling system. This paper describes the design and implementation of a multi-storey building actuator and sensor system using 6LoWPAN-based Internet of Things. The system consists of low-power wireless building network based on 6LoWPAN using Contiki real-time operating system and COAP application protocol. The building HTTP-COAP proxy is implemented in gateway node provides an efficient data packet transferring which makes the system scalable and accessible to the world based on Ethernet or Wi-Fi Medium. A prototype smart building system has been implemented and evaluated in real multi-storey building environment which has the functions to monitor and control the electrical usage in the smart building. The testing results show that 6LoWPAN-based Internet of Things is a good solution for scalable actuator and sensor networks which can be applied not only multi-storey smart building but also for large scale smart city.
A novel approach for preprocessing analog signal using number theoretic transform

In this paper, a preprocessing architecture for folding Analog-to-Digital converter (ADC) based on a new number system called Robust Folding Number System (RFNS) is presented. The RFNS is developed from robust symmetrical number system (RSNS) that was proposed by Pace et al . The enhanced Dynamic Range (DR) of RFNS due to the introduction of the folding bit results in higher ADC resolution. The Symmetrical Residues (SRs) that are obtained in the intermediate step during processing of analog signals are converted to equivalent residues by simple mapping. This results in a conversion architecture that is less complex compared to that proposed in .
An algorithm to improve the robustness of imperceptible watermarks against JPEG compression

This paper proposes a novel watermarking algorithm in digital images to ensure the imperceptible characteristics of the watermarks, reducing the effects on images quality while maintaining recoverability. The proposed method is performed by embedding watermarks in the DCT domain. DCT coefficients, which are selected to be embedded, or not, are based on an evaluation of watermark robustness during the quantization phase of the JPEG Baseline method. Results of the algorithm have been evaluated using Matlab.
A resource allocation algorithm and system architecture to extend the cell coverage and alleviate the inter-cell interference

In this paper, we propose an improved orthogonal resource allocation algorithm (iORAA), which is designed to incorporate with the OFDMA-based cellular wireless system architecture using relays (OCWSAR) in order to reduce the inter-cell interference (ICI) significantly for mobile stations (MSs), especially, cell-edge MSs while maintaining the sector frequency reuse factor at 1. Thanks to that, the cell data throughput is also improved. The performance of the proposed algorithm is evaluated in a multicell/multi-user environment, where the effect of the iORAA can be evaluated precisely in the presence of ICI. Numerical results show that the new system with the associated algorithm yield high SINR distribution and data throughput for cell-edge MSs over the conventional algorithms.
Asymptotic optimization for a class of nonlinear stochastic hybrid systems on infinite time horizon

A problem of optimal control of a stochastic hybrid system on an infinite time horizon is considered. The parameters of the system may jump at discrete moments of time according to a Markov decision process which has finite state and action spaces. The problem is approximated by some deterministic optimal control problem and a near optimal control Markov policy is constructed under assumption that the length of the intervals between the jumps is defined by a small parameter /spl epsiv/.
A new MPPT method for stand-alone wind energy conversion system

In this paper, a maximum power point tracking (MPPT) method for a stand-alone variable speed wind turbine using permanet magnet synchronous generator (PMSG) is proposed. Fuzzy logic control (FLC) is employed to achieve the MPPT of wind generator using hill climb searching (HCS) method, which does not require any information about the generator's characteristics or climatic conditions. Simulation results are given to show the effectiveness and the good performances of the proposed method in various climatic and operating conditions.
An MRF-Poselets Model for Detecting Highly Articulated Humans

Detecting highly articulated objects such as humans is a challenging problem. This paper proposes a novel part-based model built upon poselets, a notion of parts, and Markov Random Field (MRF) for modelling the human body structure under the variation of human poses and viewpoints. The problem of human detection is then formulated as maximum a posteriori (MAP) estimation in the MRF model. Variational mean field method, a robust statistical inference, is adopted to approximate the MAP estimation. The proposed method was evaluated and compared with existing methods on different test sets including H3D and PASCAL VOC 2007-2009. Experimental results have favourbly shown the robustness of the proposed method in comparison to the state-of-the-art.
Design of a New Instrumented Forceps: Application to Safe Obstetrical Forceps Blade Placement

Today, medical simulators are increasingly gaining appeal in clinical settings. In obstetrics childbirth simulators provide a training and research tool for comparing various techniques that use obstetrical instruments or validating new methods. Especially in the case of difficult deliveries, the use of obstetrical instruments - such as forceps, spatulas, and vacuum extractors - has become essential. However, such instruments increase the risk of injury to both the mother and fetus. Only clinical experience acquired in the delivery room enables health professionals to reduce this risk. In this context, we have developed, in collaboration with researchers and physicians, a new type of instrumented forceps that offers new solutions for training obstetricians in the safe performance of forceps deliveries. This paper focuses on the design of this instrumented forceps, coupled with the BirthSIM simulator. This instrumented forceps allows to study its displacement inside the maternal pelvis. Methods for analyzing the operator repeatability and to compare forceps blade placements to a reference one are developed. The results highlight the need of teaching tools to adequately train novice obstetricians.