nils-herrmann/clean_scirepeval huggingface dataset:
Gain enhancement of butler matrix fed antenna array system by using planar circular EBG units

In this paper planar circular Electromagnetic Band Gap (EBG) structures have been implemented in the Butler matrix fed antenna array system to improve the radiation performance of the system. Initially a conventional 4×4 Butler matrix fed antenna array system has been designed at 14.5 GHz. Asymmetricity in the gain values of major beams of the antenna array system has been observed both in simulation and measurement. Generally due to the design simplicity, light weight and compactness, the rectangular patch microstrip antenna has been used as the radiating element in the Butler matrix fed antenna array system. At higher frequencies microstrip antenna suffers from losses due to surface wave excitation. It degrades the radiation efficiency of the antenna array system and also increases the level of mutual coupling between the radiating elements in the antenna array. EBG (Electromagnetic Band Gap) units are used to improve the radiation performance of the system by the generation of stop band. The propagation of surface wave will be suppressed in this stop band region and may improve the performance of the system. To fulfill this requirement, 3 × 1 planar circular EBG unit has been designed. A stop band of 2.15 GHz with the centre frequency of 14.5 GHz has been obtained by the proposed EBG unit. The 3×1 planar circular EBG unit has been integrated between the radiating elements of the antenna array system. As a result the gain enhancement has been achieved for the 1R, 2L, 2R and 1L beams both in simulation and measurement at 14.5 GHz.
LightProbe: A 64-channel programmable ultrasound transducer head with an integrated front-end and a 26.4 Gb/s optical link

Medical ultrasound processing features two main components: A transducer head to generate the ultrasound wave and acquire the reflected signals and a processing system that will generate the final image. The connection between these two components is established using digital communication over a USB link for smaller mobile systems whereas large stationary systems operating with 4–16x more channels use analog signals over micro-coaxial cables to avoid link rates of 16–100 Gb/s. In this paper, we present LightProbe, a programmable ultrasound transducer head with an integrated 64-channel frontend and operating on an estimated 12 W worst-case power budget. LightProbe is the first transducer head equipped with a 26.4 Gb/s optical link. Moreover, it features a configurable FPGA that can be configured to pre-process the data on the transducer head and allows a flexible, inexpensive, light digital optical link that is immune to interference and can be tailored to fit a variety of devices from small mobile devices all the way to large stationary devices with high throughput requirements.
Memory reduction method for deep neural network training

Training deep neural networks requires a large amount of memory, making very deep neural networks difficult to fit on accelerator memories. In order to overcome this limitation, we present a method to reduce the amount of memory for training a deep neural network. The method enables to suppress memory increase during the backward pass, by reusing the memory regions allocated for the forward pass. Experimental results exhibit our method reduced the occupied memory size in training by 44.7% on VGGNet with no accuracy affection. Our method also enabled training speedup by increasing the mini batch size up to double.
Combined Arcus Marginalis Release, Preseptal Orbicularis Muscle Sling, and SOOF Plication for Midfacial Rejuvenation

Improvements have been made throughout the history of medicine, causing physicians to abandon a technique or medications clearly shown to be suboptimal. Unfortunately, this has not happened with rejuvenative surgery. Conventional lower eyelid procedures continue to include removal of orbital fat in most cases, and facelift procedures remain primarily a lateral vector pull. The unfortunate results of these traditional procedures are becoming easy to recognize. Optimal rejuvenation of the lower eyelid complex should be based on the principle that the contour changes characterizing aging involve not only prolapse of orbital fat, but also descent of the cheek tissues, resulting in accentuation of the orbital rim and tear trough groove. Although the necessity of preserving fat and repositioning the soft tissues of the midface has been widely accepted, there still is wide disagreement among authors as to the best approach and surgical technique. This report describes a surgical technique for lower lid midfacial rejuvenation that is a composite of several previously published approaches with some modifications, particularly in the way the Sub-Superficial Musculo Aponeurotic System (SMAS) fat pad is plicated and the midfacial tissues suspended. The technique is simple and safe, resulting in a pleasing natural midface contour.
A Novel Attack Graph Posterior Inference Model Based on Bayesian Network

Network attack graphs are originally used to evaluate what the worst security state is when a concerned network is under attack. Combined with intrusion evidence such like IDS alerts, attack graphs can be further used to perform security state posterior inference (i.e. inference based on observation experience). In this area, Bayesian network is an ideal mathematic tool, however it can not be directly applied for the following three reasons: 1) in a network attack graph, there may exist directed cycles which are never permitted in a Bayesian network, 2) there may exist temporal partial ordering relations among intrusion evidence that cannot be easily modeled in a Bayesian network, and 3) just one Bayesian network cannot be used to infer both the current and the future security state of a network. In this work, we improve an approximate Bayesian posterior inference algorithm–the likelihood-weighting algorithm to resolve the above obstacles. We give out all the pseudocodes of the algorithm and use several examples to demonstrate its benefit. Based on this, we further propose a network security assessment and enhancement method along with a small network scenario to exemplify its usage.
Edge-Coloring Partial k-Trees

Ž Many combinatorial problems can be efficiently solved for partial k-trees graphs . of treewidth bounded by k . The edge-coloring problem is one of the well-known combinatorial problems for which no efficient algorithms were previously known, except a polynomial-time algorithm of very high complexity. This paper gives a linear-time sequential algorithm and an optimal parallel algorithm which find an edge-coloring of a given partial k-tree with the minimum number of colors for fixed k. Q 1996
Technical Analysis on Financial Forecasting

Financial forecasting is an estimation of future financial outcomes for a company, industry, country using historical internal accounting and sales data. We may predict the future outcome of BSE_SENSEX practically by some soft computing techniques and can also optimized using PSO (Particle Swarm Optimization), EA (Evolutionary Algorithm) or DEA (Differential Evolutionary Algorithm) etc. PSO is a biologically inspired computational search & optimization method developed in 1995 by Dr. Eberhart and Dr. Kennedy based on the social behaviors of fish schooling or birds flocking. PSO is a promising method to train Artificial Neural Network (ANN). It is easy to implement then Genetic Algorithm except few parameters are adjusted. PSO is a random & pattern search technique based on populating of particle. In PSO, the particles are having some position and velocity in the search space. Two terms are used in PSO one is Local Best and another one is Global Best. To optimize problems that are like Irregular, Noisy, Change over time, Static etc. PSO uses a classic optimization method such as Gradient Decent & Quasi-Newton Methods. The observation and review of few related studies in the last few years, focusing on function of PSO, modification of PSO and operation that have implemented using PSO like function optimization, ANN Training & Fuzzy Control etc. Differential Evolution is an efficient EA technique for optimization of numerical problems, financial problems etc. PSO technique is introduced due to the swarming behavior of animals which is the collective behavior of similar size that aggregates together.  Financial Forecasting, Neural Network, Particle Swarm Optimization, Global Best, Particle Best
A 107 GHz 55 dB-Ohm InP Broadband Transimpedance Amplifier IC for High-Speed Optical Communication Links

We report a 107 GHz baseband differential transimpedance amplifier IC for high speed optical communication links. The amplifier, comprised of two Darlington resistive feedback stages, was implemented in a 500 nm InP HBT process and demonstrates 55 dBΩ differential transimpedance gain, 30 ps group delay, P1dB = 1 dBm, and is powered by a 5.2 V supply. Differential input and output impedances are 50Ω. The IC interfaces to -2V DC at the input for connections to high-speed photodiodes and -450 mV DC at the output for interfaces to Gilbert-cell mixers and to ECL logic.
Light emitting diodes reliability review

0026-2714/$ see front matter 2011  ⇑ Corresponding author at: CALCE Center for Adva University of Maryland, College Park, MD 20742, Un 5323; fax: +1 301 314 9269. E-mail address: pecht@calce.umd.edu (M. Pecht). The increasing demand for light emitting diodes (LEDs) has been driven by a number of application categories, including display backlighting, communications, medical services, signage, and general illumination. The construction of LEDs is somewhat similar to microelectronics, but there are functional requirements, materials, and interfaces in LEDs that make their failure modes and mechanisms unique. This paper presents a comprehensive review for industry and academic research on LED failure mechanisms and reliability to help LED developers and end-product manufacturers focus resources in an effective manner. The focus is on the reliability of LEDs at the die and package levels. The reliability information provided by the LED manufacturers is not at a mature enough stage to be useful to most consumers and end-product manufacturers. This paper provides the groundwork for an understanding of the reliability issues of LEDs across the supply chain. We provide an introduction to LEDs and present the key industries that use LEDs and LED applications. The construction details and fabrication steps of LEDs as they relate to failure mechanisms and reliability are discussed next. We then categorize LED failures into thirteen different groups related to semiconductor, interconnect, and package reliability issues. We then identify the relationships between failure causes and their associated mechanisms, issues in thermal standardization, and critical areas of investigation and development in LED technology and reliability.
Sleep stage classification based on multi-level feature learning and recurrent neural networks via wearable device

Automatic sleep stage classification is essential for long-term sleep monitoring. Wearable devices show more advantages than polysomnography for home use. In this paper, we propose a novel method for sleep staging using heart rate and wrist actigraphy derived from a wearable device.



The proposed method consists of two phases: multi-level feature learning and recurrent neural networks-based (RNNs) classification. The feature learning phase is designed to extract low- and mid-level features. Low-level features are extracted from raw signals, capturing temporal and frequency domain properties. Mid-level features are explored based on low-level ones to learn compositions and structural information of signals. Sleep staging is a sequential problem with long-term dependencies. RNNs with bidirectional long short-term memory architectures are employed to learn temporally sequential patterns.



To better simulate the use of wearable devices in the daily scene, experiments were conducted with a resting group in which sleep was recorded in the resting state, and a comprehensive group in which both resting sleep and non-resting sleep were included. The proposed algorithm classified five sleep stages (wake, non-rapid eye movement 1-3, and rapid eye movement) and achieved weighted precision, recall, and F1 score of 66.6%, 67.7%, and 64.0% in the resting group and 64.5%, 65.0%, and 60.5% in the comprehensive group using leave-one-out cross-validation. Various comparison experiments demonstrated the effectiveness of the algorithm.



Our method is efficient and effective in scoring sleep stages. It is suitable to be applied to wearable devices for monitoring sleep at home.
Paving green passage for emergency vehicle in heavy traffic: Real-time motion planning under the connected and automated vehicles environment

This paper describes a real-time multi-vehicle motion planning (MVMP) algorithm for the emergency vehicle clearance task. To address the inherent limitations of human drivers in perception, communication, and cooperation, we require that the emergency vehicle and the surrounding normal vehicles are connected and automated vehicles (CAVs). The concerned MVMP task is to find cooperative trajectories such that the emergency vehicle can efficiently pass through the normal vehicles ahead. We use an optimal-control based formulation to describe the MVMP problem, which is centralized, straightforward, and complete. For the online solutions, the centralized MVMP formulation is converted into a multi-period and multi-stage version. Concretely, each period consists of two stages: the emergency vehicle and several normal CAVs ahead try to form a regularized platoon via acceleration or deceleration (stage 1); when a regularized platoon is formed, these vehicles act cooperatively to make way for the emergency vehicle until the emergency vehicle becomes the leader in this local platoon (stage 2). When one period finishes, the subsequent period begins immediately. This sequential process continues until the emergency vehicle finally passes through all the normal CAVs. The subproblem at stage 1 is extremely easy because nearly all the challenging nonlinearity gathers only in stage 2; typical solutions to the subproblem at stage 2 can be prepared offline, and then implemented online directly. Through this, our proposed MVMP algorithm avoids heavy online computations and thus runs in real time.
Automatic Classification of Change Requests for Improved IT Service Quality

Faulty changes to the IT infrastructure can lead to critical system and application outages, and therefore cause serious economical losses. In this paper, we describe a change planning support tool that aims at assisting the change requesters in leveraging aggregated information associated with the change, like past failure reasons or best implementation practices. The thus gained knowledge can be used in the subsequent planning and implementation steps of the change. Optimal matching of change requests with the aggregated information is achieved through the classification of the change request into about 200 fine-grained activities. We propose to automatically classify the incoming change requests using various information retrieval and machine learning techniques. The cost of building the classifiers is reduced by employing active learning techniques or by leveraging labeled features. Historical tickets from two customers were used to empirically assess and compare the accuracy of the different classification approaches (Lucene index, multinomial logistic regression, and generalized expectation criteria).
A Fast Regular Expression Indexing Engine

Some people may be laughing when looking at you reading in your spare time. Some may be admired of you. And some may want be like you who have reading hobby. What about your own feel? Have you felt right? Reading is a need and a hobby at once. This condition is the on that will make you feel that you must read. If you know are looking for the book enPDFd fast regular expression indexing engine as the choice of reading, you can find here.
High speed series resonant converter (SRC) using multilayered coreless printed circuit board (PCB) step-down power transformer

In this paper, simulation and experimental results of an isolated low profile, series resonant converter (SRC) using multilayered coreless printed circuit board (PCB) step-down power transformer are described. The designed converter prototype was operated in MHz switching frequency region. For obtaining the stringent height switch mode power supplies (SMPS), a new multilayered coreless PCB power transformer of approximately 4∶1 turn's ratio was designed in a four layered PCB laminate. The outermost radius of the step-down power transformer is 10mm with achieved power density of 16W/cm2. The energy efficiency of the power transformer is found to be in the range of approximately 87–96% with the output power level of 0.1–50W in the frequency range of 1.5–4MHz. This designed step-down power transformer was utilized in SRC and evaluated. The supply voltage of converter is varied from 60–120V DC with a nominal input voltage of 90V. The SRC has been tested successfully upto the output power level of 34.5W. The energy efficiency from the converter prototype under Zero Voltage Switching (ZVS) condition is found to be in the range of 80–86.5% with the switching frequency range of 2.4–2.75MHz. By using constant off-time frequency modulation technique the output voltage of converter is regulated to 20V DC for different load conditions. Thermal profile and the loss estimation of SRC at nominal voltage are also presented.
Can one TV show make a difference? Will & Grace and the Parasocial Contact Hypothesis.

Television has an opportunity to influence beliefs about groups with which individuals typically may have little direct social contact. This study describes a synthesis of the Contact Hypothesis and the concept of Parasocial Interaction to pose what we call the Parasocial Contact Hypothesis to test whether exposure to gay men on Will & Grace can influence attitudes toward gay men in general. Based on a study of 245 university students, this study examines the relationships among number and intimacy of gay social contacts, parasocial interaction, viewing frequency of Will & Grace, and scores on Herek's Attitudes Toward Gay Men and Lesbians scale. Increased viewing frequency and parasocial interaction were found to correlate with lower levels of sexual prejudice-a relationship that was most pronounced for those with the least amount of social contact with lesbians and gay men.
Visual Tracking via Boolean Map Representations

In this paper, we present a simple yet effective Boolean map based representation that exploits connectivity cues for visual tracking. We describe a target object with histogram of oriented gradients and raw color features, of which each one is characterized by a set of Boolean maps generated by uniformly thresholding their values. The Boolean maps effectively encode multi-scale connectivity cues of the target with different granularities. The fine-grained Boolean maps capture spatially structural details that are effective for precise target localization while the coarse-grained ones encode global shape information that are robust to large target appearance variations. Finally, all the Boolean maps form together a robust representation that can be approximated by an explicit feature map of the intersection kernel, which is fed into a logistic regression classifier with online update, and the target location is estimated within a particle filter framework. The proposed representation scheme is computationally efficient and facilitates achieving favorable performance in terms of accuracy and robustness against the state-of-the-art tracking methods on a large benchmark dataset of 50 image sequences.
FraudBuster: Reducing Fraud in an Auto Insurance Market.

Nonstandard insurers suffer from a peculiar variant of fraud wherein an overwhelming majority of claims have the semblance of fraud. We show that state-of-the-art fraud detection performs poorly when deployed at underwriting. Our proposed framework "FraudBuster" represents a new paradigm in predicting segments of fraud at underwriting in an interpretable and regulation compliant manner. We show that the most actionable and generalizable profile of fraud is represented by market segments with high confidence of fraud and high loss ratio. We show how these segments can be reported in terms of their constituent policy traits, expected loss ratios, support, and confidence of fraud. Overall, our predictive models successfully identify fraud with an area under the precision-recall curve of 0.63 and an f-1 score of 0.769.
Pictogrammar: an AAC device based on a semantic grammar

As many as two-thirds of individuals with an Autism Spectrum Disorder (ASD) also have language impairments, which can range from mild limitations to complete non-verbal behavior. For such cases, there are several Augmentative and Alternative Communication (AAC) devices available. These are computer-designed tools in order to help people with ASD to palliate or overcome such limitations, at least partially. Some of the most popular AAC devices are based on pictograms, so that a pictogram is the graphical representation of a simple concept and sentences are composed by concatenating a number of such pictograms. Usually, these tools have to manage a vocabulary made up of hundreds of pictograms/concepts, with no or very poor knowledge of the language at semantic and pragmatic level. In this paper we present Pictogrammar, an AAC system which takes advantage of SUpO and PictOntology. SUpO (Simple Upper Ontology) is a formal semantic ontology which is made up of detailed knowledge of facts of everyday life such as simple words, with special interest in linguistic issues, allowing automated grammatical supervision. PictOntology is an ontology developed to manage sets of pictograms, linked to SUpO. Both ontologies make possible the development of tools which are able to take advantage of a formal semantics.
Dynamic Behaviour of an Electronically Commutated ( Brushless DC ) Motor Drive with Back-emf Sensing

Conventionally, BLDC motors are commutated in six-step pattern with commutation controlled by position sensors. To reduce cost and complexity of the drive system, sensorless drive is preferred. The existing sensorless control scheme with the conventional back EMF sensing based on motor neutral voltage for BLDC has certain drawbacks, which limit its applications. This paper presents the dynamic behaviour of an analytical and circuit model of a Brushless DC (BLDC) motors with back emf sensing. The circuit model was simulated using LTspice and the results obtained were compared with the experimental results. The value of the motor constant and the back emf measured from the experiment agreed with the simulated model. The starting behaviour of the motor, changing of load torque when current are varied and disturbance of sensing method at peak load shows that the dynamic behaviour results of the experiment obtained from oscilloscope are similar to the simulated value.