nils-herrmann/clean_scirepeval huggingface dataset:
A new type short circuit failures of high power IGBT's

The Next Linear Collider accelerator proposal at SLAC requires a high efficiency, highly reliable, and low cost pulsed-power modulator to drive the 500 KV, X band klystrons. A Solid State Induction Modulator to power the klystrons is under development uses high voltage 3.3 kV high current (3 KA pulses for 3 /spl mu/S) IGBT modules develop for traction and electric train application. Testing of these IGBTs under pulsed conditions have been very successful, however the IGBTs failed under short circuit testing. Unpredicted current and gate waveforms and eventual IGBT failures occur when short circuit tests were performed into extremely low short circuit inductances (< 50 nH). The failures appeared to be gate related and not the anticipated collector to emitter overvoltage. The internal connection structure of the IGBT package was analyzed and its performance simulated, which resulted in an understanding of the strange current response under short circuit and the resulting failures. Test results will be presented, IGBT package layout, circuit simulation and recommendation for modification to the standard IGBT layout to improve performance of IGBT's under extremely low inductance short circuits.
Design of a medical simulator for subcutaneous contraceptive implant insertion

New contraceptive methods like the subcutaneous implant offers a new kind of comfort for women with an efficiency similar to the contraceptive pill. Unfortunately, the few numbers of unintended pregnancies that have been reported, are generally due to a bad insertion of the implant. In order to give more security to patients, we have designed, in close collaboration with physicians, a new kind of medical simulator. This simulator can be used for two purposes: one for training novice physicians in the correct gesture and the other for doctor certification which will help to determine if they are capable of inserting the implant in vivo. This paper describes the approach which has led to the design of this simulator. It describes its functionalities, its several components but also methods used to analyze the gesture of the implant insertion inside the patient. Finally, first experimental results are reported and discussed.
Can SDN Technology Be Transported to Software-Defined WSN/IoT?

Wireless sensor networks (WSNs) are essential elements of the Internet of Things ecosystem, as such, they encounter numerous IoT challenging architectural, management and application issues. These include inflexible control, manual configuration and management of sensor nodes, difficulty in an orchestration of resources, and virtualizing sensor network resources for on-demand applications and services. Addressing these issues presents a real challenge for WSNs and IoTs. By separating the network control plane from the data forwarding plane, Software-defined networking (SDN) has emerged as network technology that addresses similar problems of current switched-networks. Despite the differences between switched network and wireless sensor network domains, the SDN technology has a real potential to revolutionize WSNs/IoTs and address their challenging issues. However, very little has been attempted to bring the SDN paradigm to WSNs. This paper identifies weaknesses of existing research efforts that aims to bring the benefits of SDN to WSNs by mapping the control plane, the OpenFlow protocol, and the functionality between the two network domains. In particular, the paper investigates the difficulties and challenges in the development of software-defined wireless sensor networking (SDWSN). Finally, the paper proposes VSensor, SDIoT controller, SFlow components with specific and relevant functionality for an architecture of an SDWSN or SDIoT infrastructure.
A Consensus Based Network Intrusion Detection System

Network intrusion detection is the process of identifying malicious behaviors that target a network and its resources. Current systems implementing intrusion detection processes observe traffic at several data collecting points in the network but analysis is often centralized or partly centralized. These systems are not scalable and suffer from the single point of failure, i.e. attackers only need to target the central node to compromise the whole system. This paper proposes an anomaly-based fully distributed network intrusion detection system where analysis is run at each data collecting point using a naive Bayes classifier. Probability values computed by each classifier are shared among nodes using an iterative average consensus protocol. The final analysis is performed redundantly and in parallel at the level of each data collecting point, thus avoiding the single point of failure issue. We run simulations focusing on DDoS attacks with several network configurations, comparing the accuracy of our fully distributed system with a hierarchical one. We also analyze communication costs and convergence speed during consensus phases.
Control of power inverter in islanded microgrids based on online line impedance estimation

In this paper, proposed an adaptive droop control method using estimated the line impedance in real time and compensate for the mismatch in voltage drops across line impedance, to enhance reactive power sharing accuracy in island microgrids. The block of line parameter estimation using the current and voltage parameters in the microgrid and estimation algorithm recursive least squares method (LSM). The Second-order generalized integrator-phase-locked loop (SOGI-PLL) is used to monitor such amplitude voltage phases and frequency at the point of common coupling (PCC) of the inverters. The line parameters are a mixture of resistance and reactance and has been estimated in real time. Therefore, the adaptive droop control method is more real, providing good performance under all conditions of load and line. The feasibility and effectiveness of the proposed method are demonstrated by using simulation on Matlab/Simulink.
An adaptive cache consistency strategy in a disconnected mobile wireless network

Data caching strategies become more and more attractive in mobile environment. Mobile clients cache frequently accessed data items to save communication bandwidth, resource usage, and data latency. However, the important problem is how to guarantee the consistency of the data cached at the clients. Most of existing cache invalidation policies in wireless environment based on broadcasting invalidation reports to maintain the consistency between sever and mobile clients. However, they ignore the problem that mobile clients may be lost the connection during the synchronization process. In this paper, we propose an adaptive strategy for consistent cache at client-side upon data updating at server-side. Our strategy does not only focus on scheduling updated data broadcasting at server but also attempts to increase cache reusability among mobile clients in the disconnection cases. We carried out simulation experiments to evaluate the effectiveness of our proposed approach.
Applications of system identification to paper machine model development and controller design

The evolution of the computer-based data collection and analysis systems has lead to significant advancements in the application of modern system identification techniques to paper machine model development. Process data obtained from paper machines excited with pseudo-random binary sequences (PRBS) can be used to determine process dynamics, isolate multivariable process interactions and develop advanced computer models to evaluate existing and new control strategies. This paper examines some of the traditional parametric identification techniques such as least squares, maximum likelihood or instrumental variable methods applied to data collected from a paper machine. The resulting paper machine model includes the process dynamics, the shape of the responses in a cross machine direction sense and defines the interactions between the machine direction and cross machine direction control elements. Finally, the paper illustrates the application of the models to minimum variance methods of coordinating multiple actuators to reduce overall finished paper variability.<<ETX>>
Bum scar detection using cloudy MODIS images via low-rank and sparsity-based models

In this paper, we propose a general framework to detect burned area using multiple partially occluded Moderate Resolution Imaging Spectroradiometer (MODIS) images. By treating each MODIS image as the superimposition of 3 layers: background, burned area, and cloud, we first apply a low-rank and sparse matrix decomposition technique known as Robust Principal Component Analysis (RPCA) to separate cloud from the other two components. Secondly, a joint sparsity-based representation for classification algorithm is employed to determine the burned area. We further robustify the algorithm by proposing a novel combined model that can separate and suppress the cloud information while simultaneously detecting the burn scar. Preliminary results using actual MODIS images clearly demonstrated the efficacy of the proposed technique. The probability of correct detection of burned area can reach more than 80% with less than 10% false alarm rate, even in an extremely cloudy day.
Bayesian model for mobility prediction to support routing in Mobile Ad-Hoc Networks

This paper introduces a Bayesian model to predict and classify the mobility of a node in Mobile Ad-hoc Networks (MANETs). The proposed model does not use the additional information from Global Positioning System (GPS) for its prediction as some existing models did. Instead, it relies on the “average encounter rate” and “node degree” calculated at each node. However, the outcome is still recorded at high accuracy, i.e. prediction error is fewer than 10% at high speed level (above 15m/s). The aim of this model is to help a routing protocol in MANETs avoid broadcasting request messages from a high mobility node/region relied on the outcome of the prediction. Through simulation experiments, route error rate observed reduced significantly compared to normal broadcast scheme of the Ad-hoc On-demand Distance Vector (AODV) protocol. The packet delivery ratio improved up to 46.32% at the maximum velocity of 30m/s (equal to 108km/h) in the density of 200nodes/km2.
Compressed Sensing MRI Reconstruction Using a Generative Adversarial Network With a Cyclic Loss

Compressed sensing magnetic resonance imaging (CS-MRI) has provided theoretical foundations upon which the time-consuming MRI acquisition process can be accelerated. However, it primarily relies on iterative numerical solvers, which still hinders their adaptation in time-critical applications. In addition, recent advances in deep neural networks have shown their potential in computer vision and image processing, but their adaptation to MRI reconstruction is still in an early stage. In this paper, we propose a novel deep learning-based generative adversarial model, <italic>RefineGAN</italic>, for fast and accurate CS-MRI reconstruction. The proposed model is a variant of fully-residual convolutional autoencoder and generative adversarial networks (GANs), specifically designed for CS-MRI formulation; it employs deeper generator and discriminator networks with cyclic data consistency loss for faithful interpolation in the given under-sampled <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-space data. In addition, our solution leverages a chained network to further enhance the reconstruction quality. <italic>RefineGAN</italic> is fast and accurate—the reconstruction process is extremely rapid, as low as tens of milliseconds for reconstruction of a <inline-formula> <tex-math notation="LaTeX">$256\times 256$ </tex-math></inline-formula> image, because it is one-way deployment on a feed-forward network, and the image quality is superior even for extremely low sampling rate (as low as 10%) due to the data-driven nature of the method. We demonstrate that <italic>RefineGAN</italic> outperforms the state-of-the-art CS-MRI methods by a large margin in terms of both running time and image quality via evaluation using several open-source MRI databases.
Application of QR decomposition to design of space-time codes for MIMO systems

We introduce the concept of "nulling diversity gains" for a space-time code via QR decomposition of the corresponding channel matrix. This concept enables us to roughly estimate the performance of the space-time code when it is detected by interference suppression and interference cancellation techniques. Based on this concept, we also devise a space-time code for MIMO systems that not only has a high performance and high spectral efficiencies but also allows the simple detection technique to be employed. Computer simulation is provided to demonstrate the nulling diversity gains of some space-time codes as well as to verify performances of our proposed code.
Analysis of human fibroadenomas using three-dimensional impedance maps

Three-dimensional impedance maps (3DZMs) are virtual volumes of acoustic impedance values constructed from histology to represent tissue microstructure acoustically. From the 3DZM, estimations can be made for ultrasonic backscatter and scatterer properties, such as effective scatterer diameter (ESD). Additionally, the 3DZM can be exploited to visualize and identify possible scattering sites, which may aid in the development of more effective scattering models to better represent the ultrasonic interaction with underlying tissue microstructure. In this study, 3DZMs were created from several human fibroadenoma samples. ESD estimates were obtained using the fluid-filled sphere form factor model. These estimates were made using two regions of interest (ROIs) sizes: cubes of side length 300 µm and 150 µm. This estimation technique allowed a better understanding of the spatial distribution and variability of the estimates throughout the volume. For a collection of 33 3DZMs, the ESD was estimated to be 99±43 µm with the large ROI and 65±30 µm when using the small ROI. The 3DZMs were then investigated visually to identify possible scattering sources, which conformed to the estimated characteristic scatterer dimensions. This visualization and comparison resulted in the identification of possible ultrasonic scattering sources within human fibroadenomas.
A comparison of W-band MMIC mixers using InP HEMT technology

This paper compares the performance of three different W-band mixer designs in the same InP HEMT technology. A resistive HEMT mixer, an active HEMT mixer, and a rat-race diode mixer are designed and measured for conversion, intermodulation and noise performance for an LO frequency of 94 GHz and IF frequencies ranging from 0.5 to 5 GHz. This is the first direct comparison of three high-performance W-band mixers fabricated in the same InP HEMT technology.
Compressive and collaborative mobile sensing for scalar field mapping in robotic networks

In this paper, we propose a compressive and collaborative sensing (CCS) algorithm for distributed robotic networks to build scalar field map. A collaborative control law is utilized to steer the robots to move on the field while avoiding collision with each other and with obstacles. At each time instant, the robots collect, add measurements within their sensing range and exchange data with their neighbors to form compressive sensing (CS) measurements at each robot. After a certain times of moving and sampling, each robot can achieve that number of CS measurements to be able to reconstruct all sensory readings from the positions that the group of robots visited to build a scalar map. We further analyze and formulate the total communication power consumption associated with the number of robots, sensor communication range and provide suggestions for more energy saving.
An Exponentially$epsilon$-Convergent Control Algorithm for Chained Systems and Its Application to Automatic Parking Systems

In this brief, a simple control approach is proposed for the multichain systems based on a switching algorithm of two sets of steering laws. Global exponential convergence to any prescribed norm bound (epsi-convergence) is guaranteed and the convergence rate is explicitly given. This approach has a distinctive feature that one of the inputs (driving input) is free. This feature plays a key role in achieving realistic parking tasks. For the design of steering laws, a method based on backstepping is proposed and analyzed in detail. Further, this control algorithm is applied to the automatic parking systems. The corresponding system package is developed which is composed of control laws for the steering angle and the driving velocity, algorithms for various kinds of parking tasks under steering angle and parking space limitations. A prototype system is built to validate this package, and the system works well in experiments subject to various parking situations
Autonomic fine-grained migration and replication of component-based applications across multi-clouds

Although migration and replication of applications in a distributed environment have been discussed by many researchers, the implementations of these features are rarely focused when deployed in the Cloud. Distributed computing started with the cluster, evolved into the grid and now in the era of Cloud computing, where services are provided on demand and used with a pay-as-you-go style. In the Cloud, the enterprises usually have to migrate or replicate partly or fully their services because of economical or disaster preventing reasons. Because the cost of copying/moving the whole virtual machines is too high due to their big size, the replication/migration at application level is a possible approach. This work proposes an autonomically fine-grained framework for migrating/replicating the service components on the Clouds, which is a multi-cloud distributed deployment platform. Our proposed framework ensures the high availability and scalability of services, and complies with the service-oriented architecture. Our experiments conducted in real scenarios of elastic demands show that the proposed fine-grained migration/replication is more efficient than the coarse-grained ones when an autonomic system responds to fluctuation of webapp's workload.
An efficient cascaded system for latent fingerprint recognition

This paper proposes a cascaded scheme to improve the efficiency of latent fingerprint identification system. In this scheme, the feature set of latent fingerprint such as finger codes, basic patterns, ridge counts and minutia with their local structures are sequentially exploited in four cascaded layers. In the first layer, possible finger codes of latent fingerprint are recognized based on basic pattern features and then reordered to determine their database access priority. In the second layer, its minutiae are extracted and assessed to affine matching in the third layer. In the fourth layer, any case having too many candidates in the previous layer is further matched based on exploiting local structure in order to downsizing the result list. On the verification layer, the minutiae information and local structure of corresponding pairs are presented to human experts for further verification. Experimental results on C@FRIS database show that our proposed method obtains high matching accuracy and considerably low identification time.
Analysis of effectiveness of communication overheads in the parallel computing system using the closed product form queueing network

Assessment, computation and establishment of methods for decreasing communication overheads in parallel computing systems using multi-processor architectures are important problems. In the current research, the communication overhead was assessed using a new method that was executed based on components such as: effectiveness of the interconnecting network architecture, delay of nodes, initial communication time and transferring time of one data. The effectiveness of the communication overhead in the parallel computing system was also analyzed using the closed product form queueing network.
16.8 GB/s LPDDR4-3200@32-bit memory access bandwidth

Today's In-Vehicle Infotainment system requires more external memory access bandwidth (MABW)  especially for high definition (HD) video/audio. It demands maximum utilization for SDRAM access instead of expansion for SDRAM capacity due to limitation of chip size. An LPDDR4-3200 @32-bit SDRAM supports 12.8GB/s , and efficiency is limited to around 95% by SDRAM AC timing. An idea to achieve even more MABW than the limitation is introduced. Placing lossless compression unit  at source of requests, and decompression unit (DCU) integrated inside memory controller (MC), the number of SDRAM command has been deducted while increasing bus data bandwidth. However, latency becomes a critical issue for real-time request which may be non-decompression while going through DCU with big number of processing cycles. The adaptive solution is applied in this work so that both bandwidth and latency requirement are satisfied. The non-decompression transaction is separated and processed out-of-order to relax the latency, whereas the decompression transaction goes through DCU for decompression processing. Simulation result on LPDDR4-3200 @ 32-bit shows average 16.8 GB/s MABW for data rate after decompression using video playback data stream, with real-time requirement maintaining.
An Empirical Study of Architectural Change in Open-Source Software Systems

From its very inception, the study of software architecture has recognized architectural decay as a regularly occurring phenomenon in long-lived systems. Architectural decay is caused by repeated changes to a system during its lifespan. Despite decay's prevalence, there is a relative dearth of empirical data regarding the nature of architectural changes that may lead to decay, and of developers' understanding of those changes. In this paper, we take a step toward addressing that scarcity by conducting an empirical study of changes found in software architectures spanning several hundred versions of 14 open-source systems. Our study reveals several new findings regarding the frequency of architectural changes in software systems, the common points of departure in a system's architecture during maintenance and evolution, the difference between system-level and component-level architectural change, and the suitability of a system's implementation-level structure as a proxy for its architecture.
An assume-guarantee model checker for component-based systems

This paper introduces an assume-guarantee model checker, named AGMC, for verifying correctness of designs of component-based systems. Given UML 2.0 sequence diagrams that describe behaviors of the system components and a required property, AGMC generates accurate models of the components represented by labeled transition systems (LTSs) automatically. AGMC then model checks that whether the system satisfies the property by using the assume-guarantee verification method. AGMC has been implemented and tested by applying some typical component-based systems. The implemented AGMC is not only useful to verify component-based systems in practice but also has a potential to solve the state space explosion problem in model checking.