nils-herrmann/clean_scirepeval huggingface dataset:
Elimination of Transformer Inrush Currents by Controlled Switching Part I-Theoretical Considerations

Transformer inrush currents are highmagnitude, harmonic-rich currents generated when transformer cores are driven into saturation during energization. These currents have undesirable effects, including potential damage or loss-of-life to the transformer, protective relay misoperation, and reduced power quality on the system. Controlled transformer switching can potentially eliminate these transients if residual core and core flux transients are taken into account in the closing algorithm. This paper explores the theoretical considerations of core flux transients. Based on these studies algorithms were developed which allow controlled energization of most transformers without inrush current.
Application of LSVT BIG intervention to address gait, balance, bed mobility, and dexterity in people with Parkinson disease: a case series.

Lee Silverman Voice Treatment Big (LSVT BIG) is characterized by intensive exercising of high-amplitude movements to overcome bradykinesia and hypokinesia in patients with Parkinson disease (PD). The aim of the present case series was to explore possible beneficial effects of LSVT BIG training on gait, balance, bed mobility, and dexterity.



Three patients with mild to moderate PD (all male; aged 52, 54, and 70 years; Hoehn & Yahr stages I-III) completed a 4-week LSVT BIG training program (16 individual 1-hour sessions) and an intensive home training program in accordance with the LSVT BIG protocol. Two certified LSVT BIG physical therapists delivered the LSVT BIG training sessions.



The outcome measures for gait and balance included the Functional Gait Assessment (FGA), Functional Reach Test (FRT), Timed "Up & Go" Test (TUG), Freezing of Gait Questionnaire (FOGQ), and motor score on part III of the Unified Parkinson's Disease Rating Scale (UPDRS III). Bed mobility was addressed using the Lindop Parkinson's Disease Mobility Assessment (LPA). The Nine-Hole Peg Test (9HPT) was used to measure dexterity. The 3 patients performed better on balance and gait assessments, as indicated by increased scores on the FRT and FGA (all 3 patients) and decreased scores on the TUG, FOGQ, and UPDRS III, of which scores of the FRT and UPDRS III achieved the minimal detectable change. Furthermore, the patients were quicker in tasks related to bed mobility (LPA). The patients' dexterity skills did not improve for their dominant (right) hand (9HPT).



This case series suggests that the LSVT BIG may be beneficial for gait, balance, and bed mobility. Future work is needed to ascertain the effectiveness by means of randomized controlled trials.
Update on typical and atypical antipsychotic drugs.

Antipsychotic drugs (APDs) are best classified as typical or atypical. The distinction is based solely on their ability to cause extrapyramidal side effects (EPS), including tardive dyskinesia (TD). The two classes differ in mechanism of action, with atypical APDs providing important modulation of serotonergic neurotransmission. TD increases the death rate and can be minimized by limiting use of typical APDs. Clozapine is unique among the atypical APDs in its efficacy for ameliorating psychosis in patients with treatment-resistant schizophrenia (TRS), for reduction of suicide, and for improving longevity. The typical and atypical APDs do not differ in improving psychopathology in non-TRS. The atypicals vary in metabolic side effects: some have little burden. Cognitive benefits of the atypical APDs may be superior for some domains of cognition and require less use of anticholinergic drugs, which impair memory, for treatment of EPS. Overall, choosing among the atypical APDs as first-line treatment represents the best course for schizophrenia and most likely other disorders for which APDs are used.
Dual-Transfer Face Sketch–Photo Synthesis

Recognizing the identity of a sketched face from a face photograph dataset is a critical yet challenging task in many applications, not least law enforcement and criminal investigations. An intelligent sketched face identification system would rely on automatic face sketch synthesis from photographs, thereby avoiding the cost of artists manually drawing sketches. However, conventional face sketch–photo synthesis methods tend to generate sketches that are consistent with the  styles. Identity-specific information is often overlooked, leading to unsatisfactory identity verification and recognition performance. In this paper, we discuss the reasons why conventional methods fail to recover identity-specific information. Then, we propose a novel dual-transfer face sketch–photo synthesis framework composed of an inter-domain transfer process and an intra-domain transfer process. In the inter-domain transfer, a regressor of the test photograph with respect to the training photographs is learned and transferred to the sketch domain, ensuring the recovery of common facial structures during synthesis. In the intra-domain transfer, a mapping characterizing the relationship between photographs and sketches is learned and transferred across different identities, such that the loss of identity-specific information is suppressed during synthesis. The fusion of information recovered by the two processes is straightforward by virtue of an ad hoc information splitting strategy. We employ both linear and nonlinear formulations to instantiate the proposed framework. Experiments on The Chinese University of Hong Kong face sketch database demonstrate that compared to the current state-of-the-art the proposed framework produces more identifiable facial structures and yields higher face recognition performance in both the photo and sketch domains.
Service Oriented Architecture based connectivity of automotive ECUs

Modern automotive industry uses embedded systems and corresponding Electronic Control Units (ECU) for a wide variety of purposes from entertainment to vehicle control. The use of these embedded systems became crucial to an extent that the performance of these embedded systems can severely affect the performance of the automobile. So the industry tries to develop new and efficient systems periodically, to improve the performance of the whole system. As the number of ECUs in an automobile increased, new technologies were developed to interconnect these ECUs. As a result of much efficient ECUs, the data produced by these ECUs and the data to be transmitted between these ECUs increased to a very large scale. The industry tried to select new connectivity solutions which provide higher bandwidth. The automotive embedded system industry thus ended up in using the well accepted and highly standardized Ethernet connectivity. This paved the way to develop new technologies for automotive embedded system. Service Oriented Architecture (SOA) has proved to be an efficient and flexible software design paradigm for high level systems. The main factors behind its success were the amount of scalability and reusability provided by this platform. The usage of SOA over the automotive Ethernet can provide the benefit of SOA to the automotive embedded world. Such an approach needs a deep feasibility study to identify whether such integration is possible, and to discover architectures and protocols which support it.
DNA Cryptography and Deep Learning using Genetic Algorithm with NW algorithm for Key Generation

Cryptography is not only a science of applying complex mathematics and logic to design strong methods to hide data called as encryption, but also to retrieve the original data back, called decryption. The purpose of cryptography is to transmit a message between a sender and receiver such that an eavesdropper is unable to comprehend it. To accomplish this, not only we need a strong algorithm, but a strong key and a strong concept for encryption and decryption process. We have introduced a concept of DNA Deep Learning Cryptography which is defined as a technique of concealing data in terms of DNA sequence and deep learning. In the cryptographic technique, each alphabet of a letter is converted into a different combination of the four bases, namely; Adenine (A), Cytosine (C), Guanine (G) and Thymine (T), which make up the human deoxyribonucleic acid (DNA). Actual implementations with the DNA don’t exceed laboratory level and are expensive. To bring DNA computing on a digital level, easy and effective algorithms are proposed in this paper. In proposed work we have introduced firstly, a method and its implementation for key generation based on the theory of natural selection using Genetic Algorithm with Needleman-Wunsch (NW) algorithm and Secondly, a method for implementation of encryption and decryption based on DNA computing using biological operations Transcription, Translation, DNA Sequencing and Deep Learning.
Powers of tensors and fast matrix multiplication

This paper presents a method to analyze the powers of a given trilinear form (a special kind of algebraic construction also called a tensor) and obtain upper bounds on the asymptotic complexity of matrix multiplication. Compared with existing approaches, this method is based on convex optimization, and thus has polynomial-time complexity. As an application, we use this method to study powers of the construction given by Coppersmith and Winograd [Journal of Symbolic Computation, 1990] and obtain the upper bound ω < 2.3728639 on the exponent of square matrix multiplication, which slightly improves the best known upper bound.
A Study into the Cybersecurity Awareness Initiatives for School Learners in South Africa and the UK

This research reports on a study into the cybersecurity awareness initiatives for school learners in South Africa and the UK, which are supported by government, industry and academia. Furthermore, this article provides an overview of similarities and differences between initiatives across countries, and posits as to the reasons why they may exist. The research concludes by presenting recommendations for both countries to improve school cybersecurity initiatives.
Evaluating dopamine reward pathway in ADHD: clinical implications.

Attention-deficit/hyperactivity disorder (ADHD)--characterized by symptoms of inattention and hyperactivity-impulsivity--is the most prevalent childhood psychiatric disorder that frequently persists into adulthood, and there is increasing evidence of reward-motivation deficits in this disorder.



To evaluate biological bases that might underlie a reward/motivation deficit by imaging key components of the brain dopamine reward pathway (mesoaccumbens).



We used positron emission tomography to measure dopamine synaptic markers (transporters and D(2)/D(3) receptors) in 53 nonmedicated adults with ADHD and 44 healthy controls between 2001-2009 at Brookhaven National Laboratory.



We measured specific binding of positron emission tomographic radioligands for dopamine transporters (DAT) using [(11)C]cocaine and for D(2)/D(3) receptors using [(11)C]raclopride, quantified as binding potential (distribution volume ratio -1).



For both ligands, statistical parametric mapping showed that specific binding was lower in ADHD than in controls (threshold for significance set at P < .005) in regions of the dopamine reward pathway in the left side of the brain. Region-of-interest analyses corroborated these findings. The mean (95% confidence interval [CI] of mean difference) for DAT in the nucleus accumbens for controls was 0.71 vs 0.63 for those with ADHD (95% CI, 0.03-0.13, P = .004) and in the midbrain for controls was 0.16 vs 0.09 for those with ADHD (95% CI, 0.03-0.12; P < or = .001); for D(2)/D(3) receptors, the mean accumbens for controls was 2.85 vs 2.68 for those with ADHD (95% CI, 0.06-0.30, P = .004); and in the midbrain, it was for controls 0.28 vs 0.18 for those with ADHD (95% CI, 0.02-0.17, P = .01). The analysis also corroborated differences in the left caudate: the mean DAT for controls was 0.66 vs 0.53 for those with ADHD (95% CI, 0.04-0.22; P = .003) and the mean D(2)/D(3) for controls was 2.80 vs 2.47 for those with ADHD (95% CI, 0.10-0.56; P = .005) and differences in D(2)/D(3) in the hypothalamic region, with controls having a mean of 0.12 vs 0.05 for those with ADHD (95% CI, 0.02-0.12; P = .004). Ratings of attention correlated with D(2)/D(3) in the accumbens (r = 0.35; 95% CI, 0.15-0.52; P = .001), midbrain (r = 0.35; 95% CI, 0.14-0.52; P = .001), caudate (r = 0.32; 95% CI, 0.11-0.50; P = .003), and hypothalamic (r = 0.31; CI, 0.10-0.49; P = .003) regions and with DAT in the midbrain (r = 0.37; 95% CI, 0.16-0.53; P < or = .001).



A reduction in dopamine synaptic markers associated with symptoms of inattention was shown in the dopamine reward pathway of participants with ADHD.
Weighted summarization of Student Feedback using Sentiment Analysis

Every year massive amount of feedback is gathered from students regarding subjects and its respective faculty. The amount of time to analyze this data manually is a very tedious and time consuming. This is where the summarization feature comes into picture. It extracts important information found in every feedback document. Automatic summarization based on word frequency statistics takes comments and weights them to produce word frequency and then sentence frequency. Also, the sentiment information in these documents belongs to a wide spectrum ranging from positive to negative. SentiWordNet assigns sentiment numerical scores: positive or negative. Thus, providing clues for sentiment analysis. The spell-checker helps to rectify the incorrect words for proper implementation of those two concepts.
A novel explicit multi-focus image fusion method

We propose a multi-focus image fusion method. The energy of Laplacian of input images is obtained to decide which portions of the input images are in better focus, and the majority filter offers a means of spreading the focused regions to neighborhood. The edge-preserving guided image filter is applied to reduce the block effect. We conduct several experiments which demonstrate that it provided a better performance than the state of the art fusion methods in visual and quantitative evaluations.
Interactive ramp merging planning in autonomous driving: Multi-merging leading PGM (MML-PGM)

Cooperative driving behavior is essential for driving in traffic, especially for ramp merging, lane changing or navigating intersections. Autonomous vehicles should also manage these situations by behaving cooperatively and naturally. The challenge of cooperative driving is estimating other vehicles' intentions. In this paper, we present a novel method to estimate other human-driven vehicles' intentions with the aim of achieving a natural and amenable cooperative driving behavior, without using wireless communication. The new approach allows the autonomous vehicle to cooperate with multiple observable merging vehicles on the ramp with a leading vehicle ahead of the autonomous vehicle in the same lane. To avoid calculating trajectories, simplify computation, and take advantage of mature Level-3 components, the new method reacts to merging cars by determining a following target for an off-the-shelf distance keeping module (ACC) which governs speed control of the autonomous vehicle. We train and evaluate the proposed model using real traffic data. Results show that the new approach has a lower collision rate than previous methods and generates more human driver-like behaviors in terms of trajectory similarity and time-to-collision to leading vehicles.
Quantum Inspired Genetic Algorithms

|A novel evolutionary computing method | quantum inspired genetic algorithms | is introduced, where concepts and principles of quantum mechanics are used to inform and inspire more eecient evolutionary computing methods. The basic terminology of quantum mechanics is introduced before a comparison is made between a classical genetic algorithm and a quantum inspired method for the travelling salesperson problem. It is informally shown that the quantum inspired genetic algorithm performs better than the classical counterpart for a small domain. The paper concludes with some speculative comments concerning the relationship between quantum inspired genetic algorithms and various complexity classes.
Potentials and limits of high-speed PM motors

This paper illustrates potentials and limits of high-speed permanent-magnet (PM) motors. The influence of materials chosen for PM, stator core, and retaining sleeve is highlighted. Slotted and slotless topologies are considered and compared, computing magnetic, electrical, mechanical, and thermal quantities by means of both analytical and finite-element approach. Thermal and PM demagnetization limits as well as rotor losses are evaluated. A criteria of optimization of the motor structure is described, with the diameter ratio and the iron flux density as main design variables.
Modeling of split-phase machines in Park's coordinates. Part II: Equivalent circuit representation

A split-phase machine is a special electric machine whose stator winding is split into multiple (N) three-phase sets. The possibility to supply it through N independent inverters makes it attractive especially when high power and reliability are required. So far, the dq0 refeence frame representation, originally introduced for three-phase machines, has been applied in detail to split-phase configurations in the N=2 case only. In this paper, the extension to an arbitrary number of stator sets is investigated from an equivalent circuit representation viewpoint. The equivalent circuit topologies proposed in this paper to represent a split-phase machine with N three-phase sets is directly derived from the theory presented in Part I. In particular, it will be stressed that as long as N is equal to 1 or 2, dq equivalent circuits remain decoupled as known from the literature, otherwise for N higher than or equal to 3, dq cross couplings must be taken into account in the equivalent circuit representation.
Consensus protocols for blockchain-based data provenance: Challenges and opportunities

Blockchain has recently attracted tremendous interest due to its ability to enhance security and privacy through a immutable shared distributed ledger. Blockchain's ability to detect integrity violations are particularly key in providing assured data provenance in cloud platform. The practical adoption of blockchain will largely hinge on consensus protocols meeting performance and security guarantees. In this paper, we present the design issues for consensus protocols for blockchain based cloud provenance. We present the blockchain based data provenance framework for cloud. We find that there are performance and security challenges in adopting proof-of-work consensus protocol within this framework. We present unique design challenges and opportunities in developing proof-of-stake for data provenance in cloud platform.
Professional Development and Teacher Learning : Mapping the Terrain Author ( s ) :

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Database System Support for Personalized Recommendation Applications

Personalized recommendation has become popular in modern web services. For instance, Amazon recommends new items to shoppers. Also, Netflix recommends shows to viewers, and Facebook recommends friends to its users. Despite the ubiquity of recommendation applications, classic database management systems still do not provide in-house support for recommending data stored in the database. In this paper, we present the anatomy of RecDB an open source PostgreSQLbased system that provides a unified approach for declarative data recommendation inside the database engine. RecDB realizes the personalized recommendation functionality as query operators inside the database kernel. That facilitates applying the recommendation functionality and typical database operations (e.g., Selection, Join, Top-k) side-by-side. To further reduce the application latency, RecDB pre-computes and caches the generated recommendation in the database. In the paper, we present extensive experiments that study the performance of personalized recommendation applications based on an actual implementation inside PostgreSQL 9.2 using real Movie recommendation and location-aware recommendation scenarios. The results show that a recommendation-aware database engine, i.e., RecDB, outperforms the classic approach that implements the recommendation logic on-top of the database engine in various recommendation applications.
Wideband and Low Sidelobe Slot Antenna Fed by Series-Fed Printed Array

A combination of slots and series-fed patch antenna array is introduced leading to an array antenna with wide bandwidth, low sidelobe level (SLL), and high front-to-back ratio (F/B). Three structures are analyzed. The first, the reference structure, is the conventional series-fed microstrip antenna array that operates at 16.26 GHz with a bandwidth of 3%, SLL of -24 dB, and F/B of 23 dB. The second is similar to the reference structure, but a large slot that covers the patch array is removed from the ground plane. This results in a wide operating bandwidth of over 72% for , with a 3 dB gain bandwidth of over 15.9%. The SLL of this structure is improved to more than at 16.26 GHz, and stable SLL of over 15.5-16.4 GHz band is also exhibited. This structure has a bi-directional radiation pattern. To make the pattern uni-directional and increase the F/B, a third structure is analyzed. In this structure, rather than one single large slot, an array of slots is used and a reflector is placed above the series-fed patch array. This increases the F/B to 40 dB. The simulated and measured results are presented and discussed.
TRANSFORMERLESS HIGH STEP-UP DC-DC COCKCROFT-WALTON VOLTAGE MULTIPLIER FOR A HYBRID SYSTEM APPLICATION 1

In a hybrid system of photo voltaic and fuel cell, the fuel cell can be kept as a back-up source replacing a battery. The hydrogen for the fuel cell can be produced from an electrolyser which runs by the excess solar power during the off peak hours. The hydrogen fuel can be stored in a storage tank and can be used during the absence of solar energy. The low output voltages of solar and fuel cell can be boosted by a high step up dc-dc converter based on a Cockcroft-Walton(CW) voltage multiplier without a step-up transformer. A CW converter has a very high voltage gain. This converter operates in continuous conduction mode (CCM), so that the switch stresses can be reduced. By increasing the number of stages, higher values for output voltage can be obtained. A 5-stage simulation of a Cockcroft-Walton voltage multiplier is conducted and the result shows a high stepped up value of output voltage. KeywordsHybrid system, Fuel cell, Electrolyser, Cockcroft-Walton multiplier, Continous conduction mode.
Modeling Survival Data: Extending the Cox Model

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