nils-herrmann/clean_scirepeval huggingface dataset:
Overview of Electric Motor Technologies Used for More Electric Aircraft (MEA)

This paper presents an overview of motor drive technologies used for safety-critical aerospace applications, with a particular focus placed on the choice of candidate machines and their drive topologies. Aircraft applications demand high reliability, high availability, and high power density while aiming to reduce weight, complexity, fuel consumption, operational costs, and environmental impact. New electric driven systems can meet these requirements and also provide significant technical and economic improvements over conventional mechanical, hydraulic, or pneumatic systems. Fault-tolerant motor drives can be achieved by partitioning and redundancy through the use of multichannel three-phase systems or multiple single-phase modules. Analytical methods are adopted to compare caged induction, reluctance, and PM motor technologies and their relative merits. The analysis suggests that the dual (or triple) three-phase PMAC motor drive may be a favored choice for general aerospace applications, striking a balance between necessary redundancy and undue complexity, while maintaining a balanced operation following a failure. The modular single-phase approach offers a good compromise between size and complexity but suffers from high total harmonic distortion of the supply and high torque ripple when faulted. For each specific aircraft application, a parametrical optimization of the suitable motor configuration is needed through a coupled electromagnetic and thermal analysis, and should be verified by finite-element analysis.
Experience from the operation of the Pepper humanoid robots

This paper summarizes authors' experience with the operation of both versions of autonomous humanoid robot Pepper. The robot's construction, as well as its capabilities and limitations are discussed and compared to the NAO robot. Practical background of working with Pepper robots and several years of experience with NAO, result in specific know-how, which the authors would like to share in this article. It reviews not only the robots' technical aspects, but also practical use-cases that the robot has proven to be perfect for (or not).
Design of Low-Offset Voltage Dynamic Latched Comparator

The offset voltage of the dynamic latched comparator is analyzed in detailed and dynamic latched comparator design is optimized for the minimal offsetvoltage based on the analysis in this paper. As a result offset-voltage was reduced from 0.87μV (in conventional double tail latched comparator) to 0.3μV (in case of proposed comparator. The simulated results of the conventional as well as proposed comparator have been shown on pspice orcad 9.2 versions.
Scientific intuitions about the mind are wrong, misled by consciousness.

Logic is a fundamental reason why computational accounts of the mind have failed. Combinatorial complexity preventing computational accounts is equivalent to the Gödelian incompleteness of logic. The mind is not logical, but only logical states and processes in the mind are accessible to subjective consciousness. For this reason, intuitions of psychologists, cognitive scientists, and mathematicians modeling the mind are biased toward logic. This is also true about the changes proposed in After Phrenology (Anderson 2014).
A comparative study of control techniques for three phase PWM rectifier

In this paper, three different techniques which can be used for control of three phase PWM Rectifier are discussed. Those three control techniques are Direct Power Control, Indirect Power Control or Voltage Oriented Control and Hysteresis Control. The main aim of this paper is to compare and establish the merits and demerits of each technique in various aspects mainly regarding switching frequency hence switching loss, computation and transient state behavior. Each control method is studied in detail and simulated using Matlab/Simulink in order to make the comparison.
Coordinated development of leading biomass pretreatment technologies.

For the first time, a single source of cellulosic biomass was pretreated by leading technologies using identical analytical methods to provide comparative performance data. In particular, ammonia explosion, aqueous ammonia recycle, controlled pH, dilute acid, flowthrough, and lime approaches were applied to prepare corn stover for subsequent biological conversion to sugars through a Biomass Refining Consortium for Applied Fundamentals and Innovation (CAFI) among Auburn University, Dartmouth College, Michigan State University, the National Renewable Energy Laboratory, Purdue University, and Texas A&M University. An Agricultural and Industrial Advisory Board provided guidance to the project. Pretreatment conditions were selected based on the extensive experience of the team with each of the technologies, and the resulting fluid and solid streams were characterized using standard methods. The data were used to close material balances, and energy balances were estimated for all processes. The digestibilities of the solids by a controlled supply of cellulase enzyme and the fermentability of the liquids were also assessed and used to guide selection of optimum pretreatment conditions. Economic assessments were applied based on the performance data to estimate each pretreatment cost on a consistent basis. Through this approach, comparative data were developed on sugar recovery from hemicellulose and cellulose by the combined pretreatment and enzymatic hydrolysis operations when applied to corn stover. This paper introduces the project and summarizes the shared methods for papers reporting results of this research in this special edition of Bioresource Technology.
The Impact of the Allied Cryptographers on World War II : Cryptanalysis of the Japanese and German Cipher Machines

Throughout history, cryptography has played an important role during times of war. The ability to read enemy messages can lead to invaluable knowledge that can be used to lessen casualties and secure victories. The Allied cryptographers during World War II had a major impact on the outcome of the war. The Allies’ ability to intercept and decrypt messages encrypted on the Japanese cipher machine, Purple, and the German cipher machine, Enigma, empowered the Allies with a major advantage during World War II. Without this advantage, the war may have had a different end result. 1 A Brief Introduction on Cryptography Cryptography is the art and science of secret communication [4]. It involves sending a message in such a way so that only the intended audience should be able to read the message with ease. Cryptography has affected many parts of history, including the outcome of World War II. Steganography is the earliest known form of secret communication, which involves hiding the existence of a message, not the meaning of it . An example of concealing a message can be found in ancient China. A sender would use a messenger whose hair would be shaved off, then the message would be tattooed to the messenger’s head. Once the hair grew back thick enough, the existence of the message was concealed. The messenger was then free to travel to the destination to deliver the message. Once there, the messenger would shave his head again so that the message could be read by the intended recipients. This type of secret communication provides little security to a message, since if a message is found, the meaning is known immediately . Consequently, a more secure system was needed to ensure the meaning of a message was not revealed to a potential eavesdropper. Cryptography, hiding the meaning of a message instead of its existence, is a more secure way of sending a message. In order to send a secret message using cryptographic techniques, one would start with the message that is to be sent, called the plaintext [5]. Before encoding, the sender and receiver agree on the algorithm, the rules by which the message is encoded, to use in order to ensure that both parties can read the message. These rules include the type of cipher that is used and
The Impact of TV Advertising on Buying Behaviour : A Comparative Study of Urban and Rural Teenagers

This study aims to establish whether the residential background of consumers has a varying influence on their buying decisions due to the influence of TV advertising. The study was conducted on 866 teenagers of Haryana (431 male and 435 female) of which 440 were rural and 426 were urban. The data was analysed by applying counts, percentages, means and ANOVA. The study suggests that rural teenagers like television advertising more than their urban counterparts. TV advertising has enhanced their involvement in product selection and purchase, they prefer to buy TV advertised products and it is helpful in buying the new products. The urban teenagers do not buy TV advertised products if they do not require those brands. They also like the advertisements of the products that they are using and believe that products are as good as expected from TV advertisements. Male teenagers’ buying behaviour is more influenced by television advertisements than their female counterparts.
Why Do People Regulate Their Emotions? A Taxonomy of Motives in Emotion Regulation.

Emotion regulation involves the pursuit of desired emotional states (i.e., emotion goals) in the service of superordinate motives. The nature and consequences of emotion regulation, therefore, are likely to depend on the motives it is intended to serve. Nonetheless, limited attention has been devoted to studying what motivates emotion regulation. By mapping the potential benefits of emotion to key human motives, this review identifies key classes of motives in emotion regulation. The proposed taxonomy distinguishes between hedonic motives that target the immediate phenomenology of emotions, and instrumental motives that target other potential benefits of emotions. Instrumental motives include behavioral, epistemic, social, and eudaimonic motives. The proposed taxonomy offers important implications for understanding the mechanism of emotion regulation, variation across individuals and contexts, and psychological function and dysfunction, and points to novel research directions.
Building nation-wide information infrastructures in healthcare through modular implementation strategies

0963-8687/$ see front matter 2011 Elsevier B.V doi:10.1016/j.jsis.2011.03.006 ⇑ Corresponding author.  22852545; fax: E-mail addresses: margunn@ifi.uio.no (M. Aanes 1 Tel.. Initiatives that seek to realize the vision of nation-wide information infrastructures (II) in healthcare have often failed to achieve their goals. In this paper, we focus on approaches used to plan, conduct, and manage the realization of such visions. Our empirical material describes two Danish initiatives, where a national project failed to deliver interoperable Electronic Patient Record (EPR) systems while a small, local solution grew and now offers a nation-wide solution for sharing patient record information. We apply II theory, specifically the five design principles proposed by Hanseth and Lyytinen, to contrast the organization and implementation strategies of the two projects. Our findings highlight how implementation strategies differ with respect to how stakeholders are mobilized. We argue that the realization of nation-wide IIs for healthcare not only requires a gradual transition of the installed base, which current II theory advocates. Here we articulate and exemplify a modular implementation strategy as an approach that also addresses the challenges related to mobilization and organization of multiple stakeholders.
A Short Executive Function Training Program Improves Preschoolers’ Working Memory

Cognitive training has been shown to improve executive functions (EFs) in middle childhood and adulthood. However, fewer studies have targeted the preschool years-a time when EFs undergo rapid development. The present study tested the effects of a short four session EF training program in 54 four-year-olds. The training group significantly improved their working memory from pre-training relative to an active control group. Notably, this effect extended to a task sharing few surface features with the trained tasks, and continued to be apparent 3 months later. In addition, the benefits of training extended to a measure of mathematical reasoning 3 months later, indicating that training EFs during the preschool years has the potential to convey benefits that are both long-lasting and wide-ranging.
A Review of Physical and Perceptual Feature Extraction Techniques for Speech, Music and Environmental Sounds

Endowing machines with sensing capabilities similar to those of humans is a prevalent quest in engineering and computer science. In the pursuit of making computers sense their surroundings, a huge effort has been conducted to allow machines and computers to acquire, process, analyze and understand their environment in a human-like way. Focusing on the sense of hearing, the ability of computers to sense their acoustic environment as humans do goes by the name of machine hearing. To achieve this ambitious aim, the representation of the audio signal is of paramount importance. In this paper, we present an up-to-date review of the most relevant audio feature extraction techniques developed to analyze the most usual audio signals: speech, music and environmental sounds. Besides revisiting classic approaches for completeness, we include the latest advances in the field based on new domains of analysis together with novel bio-inspired proposals. These approaches are described following a taxonomy that organizes them according to their physical or perceptual basis, being subsequently divided depending on the domain of computation (time, frequency, wavelet, image-based, cepstral, or other domains). The description of the approaches is accompanied with recent examples of their application to machine hearing related problems.
Brain and Social Networks: Fundamental Building Blocks of Human Experience

How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models.
LGBTI Variations in Crime Reporting : How Sexual Identity Influences Decisions to Call the Cops

Research shows that people vary in their willingness to report crime to police depending on the type of crime experienced, their gender, age, and their race or ethnicity. Whether or not lesbian, gay, bisexual, transgender, and intersex (LGBTI) and heterosexual people vary in their willingness to report crime to the police is not well understood in the extant literature. In this article, I examine variations in LGBTI respondents’ attitudes, subjective norms, and perceived behavioral control on their intentions to report crimes to the police. Drawing on a survey of LGBTI individuals sampled from a Gay Pride community event and online LGBTI community forums (N = 329), I use quantitative statistical methods to examine whether LGBTI people’s beliefs in police homophobia are also directly associated with the behavioral intention to report crime. Overall, the results indicate that LGBTI and heterosexual people differ significantly in their intention to report crime to the police, and that a belief in police homophobia strongly influences LGBTI people’s intention to underreport crime to the police.
Genetic Algorithm in Search and Optimization : The Technique and

A genetic algorithm (GA) is a search and optimization method developed by mimicking the evolutionary principles and chromosomal processing in natural genetics. A GA begins its search with a random set of solutions usually coded in binary string structures. Every solution is assigned a tness which is directly related to the objective function of the search and optimization problem. Thereafter, the population of solutions is modiied to a new population by applying three operators similar to natural genetic operators|reproduction, crossover, and mutation. A GA works iteratively by successively applying these three operators in each generation till a termination criterion is satissed. Over the past one decade, GAs have been successfully applied to a wide variety of problems, because of their simplicity, global perspective, and inherent parallel processing. In this paper, we outline the working principle of a GA by describing these three operators and by outlining an intuitive sketch of why the GA is a useful search algorithm. Thereafter, we apply a GA to solve a complex engineering design problem. Finally, we discuss how GAs can enhance the performance of other soft computing techniques|fuzzy logic and neural network techniques.
AMI-Net: Convolution Neural Networks With Affine Moment Invariants

Affine moment invariant (AMI) is a kind of hand-crafted image feature, which is invariant to affine transformations. This property is precisely what the standard convolution neural network (CNN) is difficult to achieve. In this letter, we present a kind of network architecture to introduce AMI into CNN, which is called AMI-Net. We achieved this by calculating AMI on the feature maps of the hidden layers. These AMIs will be concatenated with the standard CNN's FC layer to determine the network's final output. By calculating AMI on the feature maps, we can not only extend the dimension of AMIs, but also introduce affine transformation invariant into CNN. Two network architectures and training strategies of AMI-Net are illuminated, one is two-stage, and the other is end-to-end. To prove the effectiveness of the AMI-Net, several experiments have been conducted on common image datasets, MNIST, MNIST-rot, affNIST, SVHN, and CIFAR-10. By comparing with the corresponding standard CNN, respectively, we verify the validity of AMI-net.
Taking risky opportunities in youthful content creation: teenagers' use of social networking sites for intimacy, privacy and self-expression

The explosion in social networking sites such as MySpace, Facebook, Bebo and Friendster is widely regarded as an exciting opportunity, especially for youth. Yet the public response tends to be one of puzzled dismay regarding, supposedly, a generation with many friends but little sense of privacy and a narcissistic fascination with self-display. This article explores teenagers” practices of social networking in order to uncover the subtle connections between online opportunity and risk. While younger teenagers relish the opportunities to continuously recreate a highly decorated, stylistically elaborate identity, older teenagers favour a plain aesthetic that foregrounds their links to others, thus expressing a notion of identity lived through authentic relationships. The article further contrasts teenagers” graded conception of “friends” with the binary 1 Published as Livingstone, S. (2008) Taking risky opportunities in youthful content creation: teenagers’ use of social networking sites for intimacy, privacy and self-expression. New Media & Society, 10(3): 393-411.  2 Thanks to the Research Council of Norway for funding the Mediatized Stories: Mediation Perspectives On Digital Storytelling Among Youth of which this project is part. I also thank David Brake, Shenja van der Graaf, Angela Jones, Ellen Helsper, Maria Kyriakidou, Annie Mullins, Toshie Takahashi, and two anonymous reviewers for their comments on an earlier version of this article. Last, thanks to the teenagers who participated in this project. 3 Sonia Livingstone is Professor of Social Psychology in the Department of Media and Communications at the London School of Economics and Political Science. She is author or editor of ten books and 100+ academic articles and chapters in the fields of media audiences, children and the internet, domestic contexts of media use and media literacy. Recent books include Young People and New Media (Sage, 2002), The Handbook of New Media (edited, with Leah Lievrouw, Sage, 2006), and Public Connection? Media Consumption and the Presumption of Attention (with Nick Couldry and Tim Markham, Palgrave, 2007). She currently directs the thematic research network, EU Kids Online, for the EC’s Safer Internet Plus programme. Email s.livingstone@lse.ac.uk
AWML: adaptive weighted margin learning for knowledge graph embedding

Knowledge representation learning (KRL), exploited by various applications such as question answering and information retrieval, aims to embed the entities and relations contained by the knowledge graph into points of a vector space such that the semantic and structure information of the graph is well preserved in the representing space. However, the previous works mainly learned the embedding representations by treating each entity and relation equally which tends to ignore the inherent imbalance and heterogeneous properties existing in knowledge graph. By visualizing the representation results obtained from classic algorithm TransE in detail, we reveal the disadvantages caused by this homogeneous learning strategy and gain insight of designing policy for the homogeneous representation learning. In this paper, we propose a novel margin-based pairwise representation learning framework to be incorporated into many KRL approaches, with the method of introducing adaptivity according to the degree of knowledge heterogeneity. More specially, an adaptive margin appropriate to separate the real samples from fake samples in the embedding space is first proposed based on the sample’s distribution density, and then an adaptive weight is suggested to explicitly address the trade-off between the different contributions coming from the real and fake samples respectively. The experiments show that our Adaptive Weighted Margin Learning (AWML) framework can help the previous work achieve a better performance on real-world Knowledge Graphs Freebase and WordNet in the tasks of both link prediction and triplet classification.
Integrating time from experience in the lateral entorhinal cortex

The encoding of time and its binding to events are crucial for episodic memory, but how these processes are carried out in hippocampal–entorhinal circuits is unclear. Here we show in freely foraging rats that temporal information is robustly encoded across time scales from seconds to hours within the overall population state of the lateral entorhinal cortex. Similarly pronounced encoding of time was not present in the medial entorhinal cortex or in hippocampal areas CA3–CA1. When animals’ experiences were constrained by behavioural tasks to become similar across repeated trials, the encoding of temporal flow across trials was reduced, whereas the encoding of time relative to the start of trials was improved. The findings suggest that populations of lateral entorhinal cortex neurons represent time inherently through the encoding of experience. This representation of episodic time may be integrated with spatial inputs from the medial entorhinal cortex in the hippocampus, allowing the hippocampus to store a unified representation of what, where and when. Temporal information that is useful for episodic memory is encoded across a wide range of timescales in the lateral entorhinal cortex, arising inherently from its representation of ongoing experience.