nils-herrmann/clean_scirepeval huggingface dataset:
Direct synthesis of cascaded quadruplet (CQ) filters

Previous designs for CQ filters have required matrix rotation operations on the coupling matrix of the canonic form of the cross-coupled filters. This is a rather awkward and not entirely satisfactory process since the theory is not general, requiring the application of equations specific to each order of filter, and in fact has been developed only as far as even order 10. A new direct CQ synthesis has now been discovered having no such limitations.<<ETX>>
Intuition: a fundamental bridging construct in the behavioural sciences.

The concept of intuition has, until recently, received scant scholarly attention within and beyond the psychological sciences, despite its potential to unify a number of lines of inquiry. Presently, the literature on intuition is conceptually underdeveloped and dispersed across a range of domains of application, from education, to management, to health. In this article, we clarify and distinguish intuition from related constructs, such as insight, and review a number of theoretical models that attempt to unify cognition and affect. Intuition's place within a broader conceptual framework that distinguishes between two fundamental types of human information processing is explored. We examine recent evidence from the field of social cognitive neuroscience that identifies the potential neural correlates of these separate systems and conclude by identifying a number of theoretical and methodological challenges associated with the valid and reliable assessment of intuition as a basis for future research in this burgeoning field of inquiry.
Identification of a threshold value for the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by a semiconductor intellectual property mall

0957-4174/$ see front matter 2009  Corresponding author.  E-mail addresses: samli0707@gmail.com (C.-W. L (G.-H. Tzeng). 1 Distinguished Chair Professor. To deal with complex problems, structuring them through graphical representations and analyzing causal influences can aid in illuminating complex issues, systems, or concepts. The DEMATEL method is a methodology which can confirm interdependence among variables and aid in the development of a chart to reflect interrelationships between variables, and can be used for researching and solving complicated and intertwined problem groups. The end product of the DEMATEL process is a visual representation— the impact-relations map—by which respondents organize their own actions in the world. In order to obtain a suitable impact-relations map, an appropriate threshold value is needed to obtain adequate information for further analysis and decision-making. In the existing literature, the threshold value has been determined through interviews with respondents or judged by the researcher. In most cases, it is hard and time-consuming to aggregate the respondents and make a consistent decision. In addition, in order to avoid subjective judgments, a theoretical method to select the threshold value is necessary. In this paper, we propose a method based on the entropy approach, the maximum mean de-entropy algorithm, to achieve this purpose. Using a real case to find the interrelationships between the services of a Semiconductor Intellectual Property Mall as an example, we will compare the results obtained from the respondents and from our method, and show that the impact-relations maps from these two methods could be the same.
A Survey of Underwater Optical Wireless Communications

Underwater wireless communications refer to data transmission in unguided water environment through wireless carriers, i.e., radio-frequency (RF) wave, acoustic wave, and optical wave. In comparison to RF and acoustic counterparts, underwater optical wireless communication (UOWC) can provide a much higher transmission bandwidth and much higher data rate. Therefore, we focus, in this paper, on the UOWC that employs optical wave as the transmission carrier. In recent years, many potential applications of UOWC systems have been proposed for environmental monitoring, offshore exploration, disaster precaution, and military operations. However, UOWC systems also suffer from severe absorption and scattering introduced by underwater channels. In order to overcome these technical barriers, several new system design approaches, which are different from the conventional terrestrial free-space optical communication, have been explored in recent years. We provide a comprehensive and exhaustive survey of the state-of-the-art UOWC research in three aspects: 1) channel characterization; 2) modulation; and 3) coding techniques, together with the practical implementations of UOWC.
Continuous-Time User Modeling in Presence of Badges: A Probabilistic Approach

User modeling plays an important role in delivering customized web services to the users and improving their engagement. However, most user models in the literature do not explicitly consider the temporal behavior of users. More recently, continuous-time user modeling has gained considerable attention and many user behavior models have been proposed based on temporal point processes. However, typical point process-based models often considered the impact of peer influence and content on the user participation and neglected other factors. Gamification elements are among those factors that are neglected, while they have a strong impact on user participation in online services. In this article, we propose interdependent multi-dimensional temporal point processes that capture the impact of badges on user participation besides the peer influence and content factors. We extend the proposed processes to model user actions over the community-based question and answering websites, and propose an inference algorithm based on Variational-Expectation Maximization that can efficiently learn the model parameters. Extensive experiments on both synthetic and real data gathered from Stack Overflow show that our inference algorithm learns the parameters efficiently and the proposed method can better predict the user behavior compared to the alternatives.
Design of a 100watt high-efficiency power amplifier for the 10-500MHz band

This paper presents a design for a high-efficiency power amplifier with an output power of more than 100W, and an ultra-broad bandwidth from 10 to 500MHz. The amplifier has a 4-way push-pull configuration using Guanella's 1∶1 transmission line transformer. A negative feedback network is adopted to make the power gain flat enough over the operating bandwidth. The implemented power amplifier exhibits a power gain of 29.2±1.8dB from 10 to 500MHz band with its power-added efficiency (PAE) being greater than 43%, and the second-and third-harmonic distortions are below −29dBc and −9.78dBc, respectively, at an output power of 100W over the entire frequency band.
Push Recovery by stepping for humanoid robots with force controlled joints

In order to interact with human environments, humanoid robots require safe and compliant control which can be achieved through force-controlled joints. In this paper, full body step recovery control for robots with force-controlled joints is achieved by adding model-based feed-forward controls. Push Recovery Model Predictive Control (PR-MPC) is presented as a method for generating full-body step recovery motions after a large disturbance. Results are presented from experiments on the Sarcos Primus humanoid robot that uses hydraulic actuators instrumented with force feedback control.
Understanding and Treating Procrastination : A Review of a Common Self-Regulatory Failure

Procrastination is a pervasive self-regulatory failure affecting approximately one-fifth of the adult population and half of the student population. It is defined as one’s voluntarily delay of an intended course of action despite being worse off as a result of that delay. Procrastination has a negative impact on performance and is associated with poorer mental health. Stress, worry, and feelings of guilt are common among those who procrastinate recurrently. In addition, procrastination is associated with fewer mental health-seeking behaviors and increased treatment delay, leading to greater distress and the exacerbation of illness. The current paper seeks to provide a theoretical and clinical understanding of procrastination by reviewing prior research. Procrastination can be understood using different motivational theories, learning theory, self-efficacy theory, as well as biases and heuristics. Temporal motivational theory is proposed as an integrated explanation for procrastination, consisting of the interaction of four different variables: expectancy, value, impulsiveness, and time, each of which affects the tendency to procrastinate. A general implication is that procrastination should be regarded as an idiosyncratic behavioral problem that requires a cognitive case conceptualization or a functional analysis in order to guide therapists in their work. A number of treatment interventions might be used in relation to procrastination—for example, efficacy performance spirals, automaticity, stimulus control, stimulus cues, learned industriousness, and cognitive restructuring. Furthermore, the current paper explores the evidence on using cognitive behavior therapy for procrastination, discussing the scarcity of randomized controlled trials and the lack of validated outcome measures, and highlighting the need for further research.
A novel design of ultra-wideband strip-line power divider for 2–18 GHz

A new modified ultra-wideband in-phase power divider for frequency band 2-18 GHz has been designed, successfully fabricated and tested. The power divider is based on the coupled strip-lines. Only two balanced resistors are used in the proposed structure. So the power divider has very low insertion loss. The capacitive strips placed over the resistors have been introduced in the suggested design as the novel elements. Due to the introduced capacitive strips the isolation and impedance matching of the divider outputs were improved at the high frequencies. The manufactured power divider shows very high measured performances (amplitude imbalance is ±0.2 dB, phase imbalance is 5°, insertion loss is 0.4 dB, isolation is -18 dB, VSWR = 1.5.
Comparison of Fuzzy Control Rules Using MATLAB Toolbox and Simulink for DC Induction Motor-Speed Control

This paper presents a fuzzy logic control for a speed control of DC induction motor. The simulation developed by using Fuzzy MATLAB Toolbox and SIMULINK. The fuzzy logic controller is also introduced to the system for keeping the motor speed to be constant when the load varies. Because of the low maintenance and robustness induction motors have many applications in the industries. The speed control of induction motor is more important to achieve maximum torque and efficiency. The result of the 3x3 matrix fuzzy control rules and 5x5 matrix fuzzy control rules of the theta and speed will do comparison in this paper. Observation the effects of the fuzzy control rules on the performance of the DC- induction motor-speed control.
The light field stereoscope: immersive computer graphics via factored near-eye light field displays with focus cues

Over the last few years, virtual reality (VR) has re-emerged as a technology that is now feasible at low cost via inexpensive cellphone components. In particular, advances of high-resolution micro displays, low-latency orientation trackers, and modern GPUs facilitate immersive experiences at low cost. One of the remaining challenges to further improve visual comfort in VR experiences is the vergence-accommodation conflict inherent to all stereoscopic displays. Accurate reproduction of all depth cues is crucial for visual comfort. By combining well-known stereoscopic display principles with emerging factored light field technology, we present the first wearable VR display supporting high image resolution as well as focus cues. A light field is presented to each eye, which provides more natural viewing experiences than conventional near-eye displays. Since the eye box is just slightly larger than the pupil size, rank-1 light field factorizations are sufficient to produce correct or nearly-correct focus cues; no time-multiplexed image display or gaze tracking is required. We analyze lens distortions in 4D light field space and correct them using the afforded high-dimensional image formation. We also demonstrate significant improvements in resolution and retinal blur quality over related near-eye displays. Finally, we analyze diffraction limits of these types of displays.
A deep reinforcement learning approach to character segmentation of license plate images

Automated license plate recognition (ALPR) has been applied to identify vehicles by their license plates and is critical in several important transportation applications. In order to achieve the recognition accuracy levels typically required in the market, it is necessary to obtain properly segmented characters. A standard method, projection-based segmentation, is challenged by substantial variation across the plate in the regions surrounding the characters. In this paper a reinforcement learning (RL) method is adapted to create a segmentation agent that can find appropriate segmentation paths that avoid characters, traversing from the top to the bottom of a cropped license plate image. Then a hybrid approach is proposed, leveraging the speed and simplicity of the projection-based segmentation technique along with the power of the RL method. The results of our experiments show significant improvement over the histogram projection currently used for character segmentation.
Backdoor attacks against learning systems

Many of today's machine learning (ML) systems are composed by an array of primitive learning modules (PLMs). The heavy use of PLMs significantly simplifies and expedites the system development cycles. However, as most PLMs are contributed and maintained by third parties, their lack of standardization or regulation entails profound security implications. In this paper, for the first time, we demonstrate that potentially harmful PLMs incur immense threats to the security of ML-powered systems. We present a general class of backdoor attacks in which maliciously crafted PLMs trigger host systems to malfunction in a predictable manner once predefined conditions are present. We validate the feasibility of such attacks by empirically investigating a state-of-the-art skin cancer screening system. For example, it proves highly probable to force the system to misdiagnose a targeted victim, without any prior knowledge about how the system is built or trained. Further, we discuss the root causes behind the success of PLM-based attacks, which point to the characteristics of today's ML models: high dimensionality, non-linearity, and non-convexity. Therefore, the issue seems industry-wide.
Digital clock and data recovery circuit design: Challenges and tradeoffs

Digital clock and recovery circuits (CDRs) have recently emerged as an alternative to their more classical analog counterparts. This paper seeks to elucidate the design challenges and trade-offs involved in the design of digital CDRs. The jitter performance metrics such as jitter generation, jitter transfer, and jitter tolerance are related to digital CDR parameters and design guidelines are provided. The impact of digital phase detector non-linearity and quantization error, the digitally-controlled oscillator frequency quantization error, and loop latency on a digital CDR performance is analyzed and demonstrated using accurate behavioral simulations.
Gamification Framework for Personalized Surveys on Relationships in Online Social Networks

The estimation of psychological properties of relationships (e.g., popularity, influence, or trust) only from objective data in online social networks (OSNs) is a rather vague approach. A subjective assessment produces more accurate results, but it requires very complex and cumbersome surveys. The key contribution of this paper is a framework for personalized surveys on relationships in OSNs which follows a gamification approach. A game was developed and integrated into Facebook as an app, which makes it possible to obtain subjective ratings of users' relationships and objective data about the users, their interactions, and their social network. The combination of both subjective and objective data facilitates a deeper understanding of the psychological properties of relationships in OSNs, and lays the foundations for future research of subjective aspects within OSNs.
Learning and teaching with social network sites: A decade of research in K-12 related education

The increasingly widespread use of social network sites to expand and deepen one’s social connections is a relatively new but potentially important phenomenon that has implications for teaching and learning and teacher education in the 21st century. This paper surveys the educational research literature to examine: How such technologies are perceived and used by K-12 learners and teachers with what impacts on pedagogy or students' learning. Selected studies were summarized and categorized according to the four types introduced by Roblyer (2005) as studies most needed to move the educational technology field forward. These include studies that establish the technology’s effectiveness at improving student learning; investigate implementation strategies; monitor social impact; and report on common uses to shape the direction of the field. We found the most prevalent type of study conducted related to our focal topic was research on common uses. The least common type of study conducted was research that established the technology’s effectiveness at improving student learning. Implications for the design of future research and teacher education initiatives are discussed.
Adaptive segmentation of MRI data

Intensity-based classification of MR images has proven problematic, even when advanced techniques are used. Intrascan and interscan intensity inhomogeneities are a common source of difficulty. While reported methods have had some success in correcting intrascan inhomogeneities, such methods require supervision for the individual scan. This paper describes a new method called adaptive segmentation that uses knowledge of tissue intensity properties and intensity inhomogeneities to correct and segment MR images. Use of the expectation-maximization (EM) algorithm leads to a method that allows for more accurate segmentation of tissue types as well as better visualization of magnetic resonance imaging (MRI) data, that has proven to be effective in a study that includes more than 1000 brain scans. Implementation and results are described for segmenting the brain in the following types of images: axial (dual-echo spin-echo), coronal [three dimensional Fourier transform (3-DFT) gradient-echo T1-weighted] all using a conventional head coil, and a sagittal section acquired using a surface coil. The accuracy of adaptive segmentation was found to be comparable with manual segmentation, and closer to manual segmentation than supervised multivariant classification while segmenting gray and white matter.
Hydroxyapatite scaffolds for bone tissue engineering made by 3D printing.

Nowadays, there is a significant need for synthetic bone replacement materials used in bone tissue engineering (BTE). Rapid prototyping and especially 3D printing is a suitable technique to create custom implants based on medical data sets. 3D printing allows to fabricate scaffolds based on Hydroxyapatite with complex internal structures and high resolution. To determine the in vitro behaviour of cells cultivated on the scaffolds, we designed a special test-part. MC3T3-E1 cells were seeded on the scaffolds and cultivated under static and dynamic setups. Histological evaluation was carried out to characterise the cell ingrowth. In summary, the dynamic cultivation method lead to a stronger population compared to the static cultivation method. The cells proliferated deep into the structure forming close contact to Hydroxyapatite granules.
Maximum weight matching via max-product belief propagation

The max-product "belief propagation" algorithm is an iterative, local, message passing algorithm for finding the maximum a posteriori (MAP) assignment of a discrete probability distribution specified by a graphical model. Despite the spectacular success of the algorithm in many application areas such as iterative decoding and computer vision which involve graphs with many cycles, theoretical convergence results are only known for graphs which are tree-like or have a single cycle. In this paper, we consider a weighted complete bipartite graph and define a probability distribution on it whose MAP assignment corresponds to the maximum weight matching (MWM) in that graph. We analyze the fixed points of the max-product algorithm when run on this graph and prove the surprising result that even though the underlying graph has many short cycles, the maxproduct assignment converges to the correct MAP assignment. We also provide a bound on the number of iterations required by the algorithm
Discovering Latent Network Structure in Point Process Data

Networks play a central role in modern data analysis, enabling us to reason about systems by studying the relationships between their parts. Most often in network analysis, the edges are given. However, in many systems it is difficult or impossible to measure the network directly. Examples of latent networks include economic interactions linking financial instruments and patterns of reciprocity in gang violence. In these cases, we are limited to noisy observations of events associated with each node. To enable analysis of these implicit networks, we develop a probabilistic model that combines mutuallyexciting point processes with random graph models. We show how the Poisson superposition principle enables an elegant auxiliary variable formulation and a fully-Bayesian, parallel inference algorithm. We evaluate this new model empirically on several datasets.
Active Ageing: An Empirical Approach to the WHO Model

In the beginning of the 21st century, the world summit on population taking place in Madrid approved active ageing, WHO (2002) as the main objective of health and social policies for old people. Few studies have been done on the scientific validity of the construct. This study aims to validate the construct of active ageing and test empirically the WHO (2002) model of Active Ageing in a sample of community-dwelling seniors.  1322 old people living in the community were interviewed using an extensive assessment protocol to measure WHO's determinants of active ageing and performed an exploratory factor analysis followed by a confirmatory factor analyses.  We did not confirm the active ageing model, as most of the groups of determinants are either not independent or not significant. We got to a six-factor model (health, psychological component, cognitive performance, social relationships, biobehavioural component, and personality) explaining 54.6% of total variance.  The present paper shows that there are objective as well as subjective variables contributing to active ageing and that psychological variables seem to give a very important contribute to the construct. The profile of active ageing is expected to vary between contexts and cultures and can be used to guide specific community and individually based interventions.