nils-herrmann/clean_scirepeval huggingface dataset:
5kW Weinberg Converter for Battery Discharging in High-Power Communication Satellites

To be competitive on the telecommunication commercial satellites market, the electrical power subsystems have to be more easily adaptable to the output power level and to the payloads specifications. A trend in recent years has been a steady increase of the payload power of telecommunication spacecraft. The communication satellites of the next generation will increase their capacity of power thus to be able to still lodge more payload on their platform. The powers that will be reached in the next years are above 25 kW. This has manifold implications. Among them we emphasized that it is not possible to use the used constituent modules at the present time whose power is of 1 kW or 2 kW, since up to 25 modules would be needed. To reduce the burden of the thermal control and to utilize more efficiently the power sources, solar arrays and batteries, higher bus voltage have been introduced also in order to reduce the circulating currents. In this paper we present an overall design and experimental results of a high-efficiency non-isolated 5 kW Weinberg converter with conductance control working as a battery discharge regulator module
Empirical formula for propagation loss in land mobile radio services

An empirical formula for propagation loss is derived from Okumura's report in order to put his propagation prediction method to computational use. The propagation loss in an urban area is presented in a simple form: A + B log10R, where A and B are frequency and antenna height functions and R is the distance. The introduced formula is applicable to system designs for UHF and VHF land mobile radio services, with a small formulation error, under the following conditions: frequency range 100-1500 MHz, distance 1-20 km, base station antenna height 30-200 m, and vehicular antenna height 1-10 m.
The accuracy of the Edinburgh diplopia diagnostic algorithm

PurposeTo assess the diagnostic accuracy of the Edinburgh diplopia diagnostic algorithm.MethodsThis was a prospective study. Details of consecutive patients referred to ophthalmology clinics at Falkirk Community Hospital and Princess Alexandra Eye Pavilion, Edinburgh, with double vision were collected by the clinician first seeing the patient and passed to the investigators. The investigators then assessed the patient using the algorithm. An assessment of the degree of concordance between the ‘algorithm assisted’ diagnosis and the ‘gold standard’ diagnosis, made by a consultant ophthalmologist was then carried out. The accuracy of the pre-algorithm diagnosis made by the referrer was also noted.ResultsAll patients referred with diplopia were eligible for inclusion. Fifty-one patients were assessed; six were excluded. The pre-algorithm accuracy of referrers was 24% (10/41). The algorithm assisted diagnosis was correct 82% (37/45) of the time. It correctly diagnosed: cranial nerve (CN) III palsy in 6/6, CN IV palsy in 7/8, CN VI palsy in 12/12, internuclear ophthalmoplegia in 4/4, restrictive myopathy in 4/4, media opacity in 1/1, and blurred vision in 3/3. The algorithm assisted diagnosis was wrong in 18% (8/45) of the patients.ConclusionsThe baseline diagnostic accuracy of non-ophthalmologists rose from 24 to 82% when patients were assessed using the algorithm. The improvement in the diagnostic accuracy resulting from the use of the algorithm would, hopefully, result in more accurate triage of patients with diplopia that are referred to the hospital eye service. We hope we have demonstrated its potential as a learning tool for inexperienced clinicians.
Data Mining for Cyber Security

This chapter provides an overview of the Minnesota Intrusion Detection System (MINDS), which uses a suite of data mining based algorithms to address different aspects of cyber security. The various components of MINDS such as the scan detector, anomaly detector and the profiling module detect different types of attacks and intrusions on a computer network. The scan detector aims at detecting scans which are the percusors to any network attack. The anomaly detection algorithm is very effective in detecting behavioral anomalies in the network traffic which typically translate to malicious activities such as denial-of-service (DoS) traffic, worms, policy violations and inside abuse. The profiling module helps a network analyst to understand the characteristics of the network traffic and detect any deviations from the normal profile. Our analysis shows that the intrusions detected by MINDS are complementary to those of traditional signature based systems, such as SNORT, which implies that they both can be combined to increase overall attack coverage. MINDS has shown great operational success in detecting network intrusions in two live deployments at the University of Minnesota and as a part of the Interrogator architecture at the US Army Research Labs Center for Intrusion Monitoring and Protection (ARL-CIMP).
Avionic Data acquisition system using MIL STD 1553B controller with IRIG-B timecode decoder

Many critical parameters of rockets and satellite are obtained by means of telemetry system present onboard. For meaningful analysis of data these parameters are to be time stamped. This is achieved by means IRIG B time code proposed by Inter-range instrumentation group. The data obtained need to be transmitted to various sub systems present in ground. Bus based configuration is planned for this inter connection. This is achieved by MIL STD 1553B protocol. A data bus is used to provide a medium for the exchange of data and information between various systems. The MIL STD 1553B bus consists of Bus Controller, Remote Terminals and transmission media. The data received from telemetry system are Manchester encoded signals which needs to be decoded. The objective of the project was to design and develop MIL STD 1553B Bus controller to transmit command and data words to various other remote terminals. An IRIG B time decoder module was developed to decode the timing information transmitted from a reference so that the Data acquisition system can be used to process the data worldwide. A Manchester Data Decoder for decoding the data was developed. The system had better synchronization capability and clock independence.
From biological to social networks : Link prediction based on multiway spectral clustering 3 Q 1 4 5 O O

9 10 11 12 13 14 15 16 17 Article history: Received 25 February 2012 Received in revised form 16 May 2013  May 2013 Available online xxxx 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 423 R R E C T E D P Link prediction in protein–protein interaction networks (PPINs) is an important task in biology, since the vast majority of biological functions involve such protein interactions. Link prediction is also important for online social networks (OSNs), which provide predictions about who is a friend of whom. Many link prediction methods for PPINs/OSNs are local-based and do not exploit all network structure, which limits prediction accuracy. On the other hand, there are global approaches to detect the overall path structure in a network, being computationally prohibitive for huge-size PPINs/OSNs. In this paper, we enhance a previously proposed multi-way spectral clustering method by introducing new ways to capture node proximity in both PPINs/OSNs. Our new enhanced method uses information obtained from the top few eigenvectors of the normalized Laplacian matrix. As a result, it produces a less noisy matrix, which is smaller and more compact than the original one. In this way, we are able to provide faster and more accurate link predictions. Moreover, our new spectral clustering model is based on the well-known Bray–Curtis coefficient to measure proximity between two nodes. Compared to traditional clustering algorithms, such as k-means and DBSCAN, which assume globular (convex) regions in Euclidean space, our approach is more flexible in capturing the non-connected components of a social graph and a wider range of cluster geometries. We perform an extensive experimental comparison of the proposed method against existing link prediction algorithms and k-means algorithm, using two synthetic data sets, three real social networks and three real human protein data sets. Our experimental results show that our SpectralLink algorithm outperforms the local approaches, the k-means algorithm and another spectral clustering method in terms of effectiveness, whereas it is more efficient than the global approaches.
Prospects for inferring very large phylogenies by using the neighbor-joining method.

Current efforts to reconstruct the tree of life and histories of multigene families demand the inference of phylogenies consisting of thousands of gene sequences. However, for such large data sets even a moderate exploration of the tree space needed to identify the optimal tree is virtually impossible. For these cases the neighbor-joining (NJ) method is frequently used because of its demonstrated accuracy for smaller data sets and its computational speed. As data sets grow, however, the fraction of the tree space examined by the NJ algorithm becomes minuscule. Here, we report the results of our computer simulation for examining the accuracy of NJ trees for inferring very large phylogenies. First we present a likelihood method for the simultaneous estimation of all pairwise distances by using biologically realistic models of nucleotide substitution. Use of this method corrects up to 60% of NJ tree errors. Our simulation results show that the accuracy of NJ trees decline only by approximately 5% when the number of sequences used increases from 32 to 4,096 (128 times) even in the presence of extensive variation in the evolutionary rate among lineages or significant biases in the nucleotide composition and transition/transversion ratio. Our results encourage the use of complex models of nucleotide substitution for estimating evolutionary distances and hint at bright prospects for the application of the NJ and related methods in inferring large phylogenies.
The relationship between gamma frequency and running speed differs for slow and fast gamma rhythms in freely behaving rats.

In hippocampal area CA1 of rats, the frequency of gamma activity has been shown to increase with running speed (Ahmed and Mehta, 2012). This finding suggests that different gamma frequencies simply allow for different timings of transitions across cell assemblies at varying running speeds, rather than serving unique functions. However, accumulating evidence supports the conclusion that slow (∼25-55 Hz) and fast (∼60-100 Hz) gamma are distinct network states with different functions. If slow and fast gamma constitute distinct network states, then it is possible that slow and fast gamma frequencies are differentially affected by running speed. In this study, we tested this hypothesis and found that slow and fast gamma frequencies change differently as a function of running speed in hippocampal areas CA1 and CA3, and in the superficial layers of the medial entorhinal cortex (MEC). Fast gamma frequencies increased with increasing running speed in all three areas. Slow gamma frequencies changed significantly less across different speeds. Furthermore, at high running speeds, CA3 firing rates were low, and MEC firing rates were high, suggesting that CA1 transitions from CA3 inputs to MEC inputs as running speed increases. These results support the hypothesis that slow and fast gamma reflect functionally distinct states in the hippocampal network, with fast gamma driven by MEC at high running speeds and slow gamma driven by CA3 at low running speeds.
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong

Ongoing research has proposed several methods to defend neural networks against adversarial examples, many of which researchers have shown to be ineffective. We ask whether a strong defense can be created by combining multiple (possibly weak) defenses. To answer this question, we study three defenses that follow this approach. Two of these are recently proposed defenses that intentionally combine components designed to work well together. A third defense combines three independent defenses. For all the components of these defenses and the combined defenses themselves, we show that an adaptive adversary can create adversarial examples successfully with low distortion. Thus, our work implies that ensemble of weak defenses is not sufficient to provide strong defense against adversarial examples.
BatTracker: High Precision Infrastructure-free Mobile Device Tracking in Indoor Environments

Continuous tracking of the device location in 3D space is a popular form of user input, especially for virtual/augmented reality (VR/AR), video games and health rehabilitation. Conventional inertial based approaches are well known for inaccuracy caused by large error drifts. Computer vision approaches can produce accuracy tracking but have privacy concerns and are subject to lighting conditions and computation complexity. Recent work exploits accurate acoustic distance measurements for high precision tracking. However, they require additional hardware (e.g., multiple external speakers), which adds to the costs and installation efforts, thus limiting the convenience and usability. In this paper, we propose BatTracker, which incorporates inertial and acoustic data for robust, high precision and infrastructure-free tracking in indoor environments. BatTracker leverages echoes from nearby objects and uses distance measurements from them to correct error accumulation in inertial based device position prediction. It incorporates Doppler shifts and echo amplitudes to reliably identify the association between echoes and objects despite noisy signals from multi-path reflection and cluttered environment. A probabilistic algorithm creates, prunes and evolves multiple hypotheses based on measurement evidences to accommodate uncertainty in device position. Experiments in real environments show that BatTracker can track a mobile device's movements in 3D space at sub-cm level accuracy, comparable to the state-of-the-art infrastructure based approaches, while eliminating the needs of any additional hardware.
High-speed differential frequency-to-voltage converter

This paper proposes a high-speed integrating frequency-to-voltage converter. It overcomes the deficiencies of previous converters by removing 2 of their main bottlenecks: event sequencing using pulses and the use of full-swing signals. By using a single-phase algorithm and circuit-level improvements a frequency-to-voltage converter can operate up to 5 GHz and is able to discriminate between signals whose periods differ by as little as 0.5ps.
Design of a Dual-Band Microstrip Antenna With Enhanced Gain for Energy Harvesting Applications

In this letter, a dual-band circular patch antenna is introduced. The antenna consists of a circular patch with a direct feed through microstrip feedline designed to radiate at 2.45 GHz with fractional bandwidth of 4.5%. A circular slot is inserted into the ground plane that radiates by capacitive coupling between the patch and the ground plane. This slot radiates at 1.95 GHz with fractional impedance bandwidth of 5%. The antenna achieves good radiation characteristics by inserting a reflecting plane at optimum position behind it. The antenna has gain of 8.3 and 7.8 dBi at 1.95 and 2.45 GHz, respectively. This antenna is proposed for the rectenna; then it is designed to direct the main beam in a certain direction by increasing front-to-back (F/B) ratio with low cross-polarization levels by using defected reflector structure in the reflecting plane. The equivalent circuit of the proposed antenna is introduced to model the electrical behavior of the antenna. The proposed antenna can be used to harvest the energy from Wi-Fi and widely spread mobile networks. The proposed antenna was designed using CST Microwave Studio. The simulated and measured results show good agreement.
Wrist-worn heartbeat monitoring system based on bio-impedance analysis

In this paper, a bio-impedance analysis (BIA) based wrist-worn heartbeat monitoring system is proposed. The system is able to estimate heart rate from a subject's wrist with only four electrodes. The design is achieved with a standard BIA device and off-the-shelf components for signal conditioning. The measured heartbeat-related impedance signal is compared with a reference heart rate signal obtained from piezoelectric finger pulse transducer. The BIA results agree with the reference, which validates the feasibility of the proposed system. To the best of our knowledge, this is the first reported BIA heartbeat monitoring system in the wristband configuration.
Subjective Evaluation of Latency and Packet Loss in a Cloud-Based Game

On-demand multimedia services are more popular than ever and continue to grow. Consumers can now stream music, movies, television, and video games at the push of a button. Such services typically require a minimum connection speed to support streaming. However, transient network effects such as packet loss and delay variation can play a crucial role in determining the user quality of experience (QoE) in streaming multimedia systems. This paper will seek to establish the subjective impact of negative network effects on the user experience of a popular cloud-based on-demand video game service.
ACCIDENT AVOIDANCE AND DETECTION ON HIGHWAYS

Technological approaches for detecting and monitoring fatigue levels of driver fatigue continue to emerge and many are now in the development, validation testing, or early implementation stages. Previous studies have reviewed available fatigue detection and prediction technologies and methodologies. As the name indicates this project is about advanced technologies in cars for making it more intelligent and interactive for avoiding accidents on roads. By using ARM7 this system becomes more efficient, reliable & effective. There are very less number of systems implemented on human behaviour detection in or with cars. In this paper, we describe a real-time online safety prototype that controls the vehicle speed under driver fatigue. The purpose of such a model is to advance a system to detect fatigue symptoms in drivers and control the speed of vehicle to avoid accidents. The main components of the system consist of number of real time sensors like gas, eye blink, alcohol, fuel, impact sensors and a software interface with GPS and Google Maps APIs for location.
Design and Implementation of a Secure Modbus Protocol

The interconnectivity of modern and legacy supervisory control and data acquisition (SCADA) systems with corporate networks and the Internet has significantly increased the threats to critical infrastructure assets. Meanwhile, traditional IT security solutions such as firewalls, intrusion detection systems and antivirus software are relatively ineffective against attacks that specifically target vulnerabilities in SCADA protocols. This paper describes a secure version of the Modbus SCADA protocol that incorporates integrity, authentication, non-repudiation and anti-replay mechanisms. Experimental results using a power plant testbed indicate that the augmented protocol provides good security functionality without significant overhead.
Multiagent traffic management: an improved intersection control mechanism

Traffic congestion is one of the leading causes of lost productivity and decreased standard of living in urban settings. Recent advances in artificial intelligence suggest vehicle navigation by autonomous agents will be possible in the near future. In a previous paper, we proposed a reservation-based system for alleviating traffic congestion, specifically at intersections. This paper extends our prototype implementation in several ways with the aim of making it more implementable in the real world. In particular, we 1) add the ability of vehicles to turn, 2) enable them to accelerate while in the intersection, and 3) augment their interaction capabilities with a detailed protocol such that the vehicles do not need to know anything about the intersection control policy. The use of this protocol limits the interaction of the driver agent and the intersection manager to the extent that it is a reasonable approximation of reliable wireless communication. Finally, we describe how different intersection control policies can be expressed with this protocol and limited exchange of information. All three improvements are fully implemented and tested, and we present detailed empirical results validating their effectiveness.
Enhanced photoluminescence and solar cell performance via Lewis base passivation of organic-inorganic lead halide perovskites.

Organic-inorganic metal halide perovskites have recently emerged as a top contender to be used as an absorber material in highly efficient, low-cost photovoltaic devices. Solution-processed semiconductors tend to have a high density of defect states and exhibit a large degree of electronic disorder. Perovskites appear to go against this trend, and despite relatively little knowledge of the impact of electronic defects, certified solar-to-electrical power conversion efficiencies of up to 17.9% have been achieved. Here, through treatment of the crystal surfaces with the Lewis bases thiophene and pyridine, we demonstrate significantly reduced nonradiative electron-hole recombination within the CH(3)NH(3)PbI(3-x)Cl(x) perovskite, achieving photoluminescence lifetimes which are enhanced by nearly an order of magnitude, up to 2 μs. We propose that this is due to the electronic passivation of under-coordinated Pb atoms within the crystal. Through this method of Lewis base passivation, we achieve power conversion efficiencies for solution-processed planar heterojunction solar cells enhanced from 13% for the untreated solar cells to 15.3% and 16.5% for the thiophene and pyridine-treated solar cells, respectively.
Fast Alternating LS Algorithms for High Order CANDECOMP/PARAFAC Tensor Factorizations

CANDECOMP/PARAFAC (CP) has found numerous applications in wide variety of areas such as in chemometrics, telecommunication, data mining, neuroscience, separated representations. For an order- N tensor, most CP algorithms can be computationally demanding due to computation of gradients which are related to products between tensor unfoldings and Khatri-Rao products of all factor matrices except one. These products have the largest workload in most CP algorithms. In this paper, we propose a fast method to deal with this issue. The method also reduces the extra memory requirements of CP algorithms. As a result, we can accelerate the standard alternating CP algorithms 20-30 times for order-5 and order-6 tensors, and even higher ratios can be obtained for higher order tensors (e.g., N ≥ 10). The proposed method is more efficient than the state-of-the-art ALS algorithm which operates two modes at a time (ALSo2) in the Eigenvector PLS toolbox, especially for tensors with order N ≥ 5 and high rank.