nils-herrmann/clean_scirepeval huggingface dataset:
Co-Clustering for Multitask Learning

This paper presents a new multitask learning framework that learns a shared representation among the tasks, incorporating both task and feature clusters. The jointlyinduced clusters yield a shared latent subspace where task relationships are learned more effectively and more generally than in state-of-the-art multitask learning methods. The proposed general framework enables the derivation of more specific or restricted stateof-the-art multitask methods. The paper also proposes a highly-scalable multitask learning algorithm, based on the new framework, using conjugate gradient descent and generalized Sylvester equations. Experimental results on synthetic and benchmark datasets show that the proposed method systematically outperforms several state-of-the-art multitask learning methods.
Are blockchains immune to all malicious attacks ?

In recent years, blockchain technology has attracted considerable attention. It records cryptographic transactions in a public ledger that is difficult to alter and compromise because of the distributed consensus. As a result, blockchain is believed to resist fraud and hacking.  This work explores the types of fraud and malicious activities that can be prevented by blockchain technology and identifies attacks to which blockchain remains vulnerable.  This study recommends appropriate defensive measures and calls for further research into the techniques for fighting malicious activities related to blockchains.
Narcissistic subtypes and contingent self-esteem: do all narcissists base their self-esteem on the same domains?

It has been suggested that there are two forms of narcissism: a grandiose subtype and a vulnerable subtype. Although these forms of narcissism share certain similarities, it is believed that these subtypes may differ in the domains upon which their self-esteem is based. To explore this possibility, the present study examined the associations between these narcissistic subtypes and domain-specific contingencies of self-worth. The results show that vulnerable narcissism was positively associated with contingencies of self-worth across a variety of domains. In contrast, the associations between grandiose narcissism and domain-specific contingencies of self-worth were more complex and included both positive and negative relationships. These results provide additional support for the distinction between grandiose and vulnerable narcissism by showing that the domains of contingent self-esteem associated with grandiose narcissism may be more limited in scope than those associated with vulnerable narcissism.
Uranine: Real-time Privacy Leakage Monitoring without System Modification for Android

V. Rastogi, R. Shao, Y. Chen, X. Pan, S. Zou, and R. Riley, “Are These Ads Safe: Detecting Hidden Attacks through the Mobile App-Web Interfaces,” in Proceedings of the Network and Distributed System Security Symposium (NDSS), 2016. V. Rastogi, Z. Qu, J. McClurg, Y. Cao, and Y. Chen, “Uranine: Real-time Privacy Leakage Monitoring without System Modification for Android,” in  2015. B. He, V. Rastogi, Y. Cao, Y. Chen, V. N. Venkatakrishnan, R. Yang, and Z. Zhang, “Vetting SSL Usage in Applications with SSLint,” in Proceedings of the 36th IEEE Symposium on Security and Privacy (Oakland), 2015. Z. Qu, V. Rastogi, X. Zhang, Y. Chen, T. Zhu, and Z. Chen, “AutoCog: Measuring the Description-to-permission Fidelity in Android Applications,” in
Heart on the road: HRV analysis for monitoring a driver's affective state

Driving a vehicle is a task affected by an increasing number and a rising complexity of Driver Assistance Systems (DAS) resulting in a raised cognitive load of the driver, and in consequence to the distraction from the main activity of driving. A number of potential solutions have been proposed so far, however, although these techniques broaden the perception horizon (e. g. the introduction of the sense of touch as additional information modality or the utilization of multimodal instead of unimodal interfaces), they demand the attention of the driver too. In order to cope with the issues of workload and/or distraction, it would be essential to find a non-distracting and noninvasive solution for the emergence of information.
 In this work we have investigated the application of heart rate variability (HRV) analysis to electrocardiography (ECG) data for identifying driving situations of possible threat by monitoring and recording the autonomic arousal states of the driver. For verification we have collected ECG and global positioning system (GPS) data in more than 20 test journeys on two regularly driven routes during a period of two weeks.
 The first results have shown that an indicated difference of the arousal state of the driver for a dedicated point on a route, compared to its usual state, can be interpreted as a warning sign and used to notify the driver about this, perhaps safety critical, change. To provide evidence for this hypothesis it would be essential in the next step to conduct a large number of journeys on different times of the day, using different drivers and various roadways.
Unequal Wilkinson Power Dividers With Favorable Selectivity and High-Isolation Using Coupled-Line Filter Transformers

In the conventional unequal-split Wilkinson power divider, poor selectivity for each transmission path is usually a problem. To surmount this obstacle, the parallel coupled-line bandpass filter structure is utilized as an impedance transformer as well as a band selector for each transmission path in the proposed unequal-split Wilkinson power dividers. However, the bandpass filters in the proposed dividers require careful design because they may not be functional under certain conditions. For example, the odd-order coupled-line filters are not appropriate for impedance transformers in the proposed unequal-split dividers and high-isolation requirement. Using the even-order coupled-line filter transformers, this study proposes two types of unequal-split Wilkinson power dividers. The first type of the proposed dividers arranges two filter transformers near two output ports, respectively, and is capable of achieving a highly remarkable isolation between the two output ports and a good band selection in each transmission path. Specifically, not only the operating band but also the lower and higher stopbands can achieve highly favorable isolation for this type of divider. By arranging the load impedance of each port properly, the second type of the proposed dividers, which has only one filter transformer to be shared by each transmission path near the input port, is also proposed to provide effective isolation between two output ports and favorable selectivity in each transmission path.
The Business Impact Of Social Media Analytics

Social media analytics (SMA) is a rapidly emerging capability that provides organisations with the ability to analyse and interpret large amounts of online content to determine the attitudes and behaviours of people. The adoption and impact of SMA by businesses is still largely unexplored. In this paper we develop a framework, based on organisational motivation theory and the resourcebased view that explains how SMA can bring benefits to organisations. The framework includes three key concepts: organisational motivations, SMA capabilities and benefits. The framework is developed from a synthesis of relevant literature and an analysis of 40 success stories published by SMA vendors. The framework provides a ranked catalogue of clearly defined motivations, SMA capabilities and benefits. It provides researchers with a theoretically grounded base for understanding how SMA impacts organisations, and provides a useful starting point for future empirical research. For practitioners, the framework provides a systematic means of understanding how SMA might be used to bring benefits.
Optimizing SPARQL Query Answering over OWL Ontologies

The SPARQL query language is currently being extended by the World Wide Web Consortium (W3C) with so-called entailment regimes. An entailment regime defines how queries are evaluated under more expressive semantics than SPARQL’s standard simple entailment, which is based on subgraph matching. The queries are very expressive since variables can occur within complex concepts and can also bind to concept or role names. In this paper, we describe a sound and complete algorithm for the OWL Direct Semantics entailment regime. We further propose several novel optimizations such as strategies for determining a good query execution order, query rewriting techniques, and show how specialized OWL reasoning tasks and the concept and role hierarchy can be used to reduce the query execution time. For determining a good execution order, we propose a cost-based model, where the costs are based on information about the instances of concepts and roles that are extracted from a model abstraction built by an OWL reasoner. We present two ordering strategies: a static and a dynamic one. For the dynamic case, we improve the performance by exploiting an individual clustering approach that allows for computing the cost functions based on one individual sample from a cluster. We provide a prototypical implementation and evaluate the efficiency of the proposed optimizations. Our experimental study shows that the static ordering usually outperforms the dynamic one when accurate statistics are available. This changes, however, when the statistics are less accurate, e.g., due to nondeterministic reasoning decisions. For queries that go beyond conjunctive instance queries we observe an improvement of up to three orders of magnitude due to the proposed optimizations.
Bounded Rationality, Abstraction, and Hierarchical Decision-Making: An Information-Theoretic Optimality Principle

ion and hierarchical information processing are hallmarks of human and animal intelligence underlying the unrivaled flexibility of behavior in biological systems. Achieving such flexibility in artificial systems is challenging, even with more and more computational power. Here, we investigate the hypothesis that abstraction and hierarchical information processing might in fact be the consequence of limitations in information-processing power. In particular, we study an information-theoretic framework of bounded rational decision-making that trades off utility maximization against information-processing costs. We apply the basic principle of this framework to perception-action systems with multiple information-processing nodes and derive bounded-optimal solutions. We show how the formation of abstractions and decision-making hierarchies depends on information-processing costs. We illustrate the theoretical ideas with example simulations and conclude by formalizing a mathematically unifying optimization principle that could potentially be extended to more complex systems.
Toward a Rational and Mechanistic Account of Mental Effort.

In spite of its familiar phenomenology, the mechanistic basis for mental effort remains poorly understood. Although most researchers agree that mental effort is aversive and stems from limitations in our capacity to exercise cognitive control, it is unclear what gives rise to those limitations and why they result in an experience of control as costly. The presence of these control costs also raises further questions regarding how best to allocate mental effort to minimize those costs and maximize the attendant benefits. This review explores recent advances in computational modeling and empirical research aimed at addressing these questions at the level of psychological process and neural mechanism, examining both the limitations to mental effort exertion and how we manage those limited cognitive resources. We conclude by identifying remaining challenges for theoretical accounts of mental effort as well as possible applications of the available findings to understanding the causes of and potential solutions for apparent failures to exert the mental effort required of us.
Behavior Based Manipulation : Theory and Prosecution Evidence

If investors are not fully rational, what can smart money do? This paper provides an example in which smart money can strategically take advantage of investors’ behavioral biases and manipulate the price process to make profit. The paper considers three types of traders, behavior-driven investors who are less willing to sell losers than to sell winners (dispositional effect), arbitrageurs, and a manipulator who can influence asset prices. We show that, due to the investors’ behavioral biases and the limit of arbitrage, the manipulator can profit from a “pump-and-dump” trading strategy by accumulating the speculative asset while pushing the asset price up, and then selling the asset at high prices. Since nobody has private information, manipulation here is completely trade-based. The paper also endogenously derives several asset-pricing anomalies, including excess volatility, momentum and reversal. As an empirical test, the paper presents some empirical evidence from the U.S. SEC prosecution of “pump-and-dump” manipulation cases that are consistent with our model.
Modified global k-means algorithm for minimum sum-of-squares clustering problems

k-means algorithm and its variations are known to be fast clustering algorithms. However, they are sensitive to the choice of starting points and inefficient for solving clustering problems in large data sets. Recently, a new version of the k-means algorithm, the global k-means algorithm has been developed. It is an incremental algorithm that dynamically adds one cluster center at a time and uses each data point as a candidate for the k-th cluster center. Results of numerical experiments show that the global k-means algorithm considerably outperforms the k-means algorithms. In this paper, a new version of the global k-means algorithm is proposed. A starting point for the k-th cluster center in this algorithm is computed by minimizing an auxiliary cluster function. Results of numerical experiments on 14 data sets demonstrate the superiority of the new algorithm, however, it requires more computational time than the global k-means algorithm.
E-broidery: Design and fabrication of textile-based computing

Highly durable, flexible, and even washable multilayer electronic circuitry can be constructed on textile substrates, using conductive yarns and suitably packaged components. In this paper we describe the development of e-broidery (electronic embroidery, i.e., the patterning of conductive textiles by numerically controlled sewing or weaving processes) as a means of creating computationally active textiles. We compare textiles to existing flexible circuit substrates with regard to durability, conformability, and wearability. We also report on: some unique applications enabled by our work; the construction of sensors and user interface elements in textiles; and a complete process for creating flexible multilayer circuits on fabric substrates. This process maintains close compatibility with existing electronic components and design tools, while optimizing design techniques and component packages for use in textiles. E veryone wears clothing. It conveys a sense of the wearer's identity, provides protection from the environment, and supplies a convenient way to carry all the paraphernalia of daily life. Of course, clothing is made from textiles, which are themselves among the first composite materials engineered by humans. Textiles have mechanical, aesthetic, and material advantages that make them ubiquitous in both society and industry. The woven structure of textiles and spun fibers makes them durable, washable, and conformal, while their composite nature affords tremendous variety in their texture, for both visual and tactile senses. Sadly, not everyone wears a computer, although there is presently a great deal of interest in " wear-able computing. " 1 Wearable computing may be seen as the result of a design philosophy that integrates embedded computation and sensing into everyday life to give users continuous access to the capabilities of personal computing. Ideally, computers would be as convenient, durable, and comfortable as clothing, but most wearable computers still take an awkward form that is dictated by the materials and processes traditionally used in electronic fabrication. The design principle of packaging electronics in hard plastic boxes (no matter how small) is pervasive, and alternatives are difficult to imagine. As a result, most wearable computing equipment is not truly wearable except in the sense that it fits into a pocket or straps onto the body. What is needed is a way to integrate technology directly into textiles and clothing. Furthermore, textile-based computing is not limited to applications in wearable computing; in fact, it is broadly applicable to ubiquitous computing, allowing the integration of interactive elements into furniture and decor in general. In …
Dietary intakes and lifestyle factors of a vegan population in Germany: results from the German Vegan Study

Evaluation of dietary intakes and lifestyle factors of German vegans. Subjects were recruited through journal advertisements. Of 868 volunteers, only 154 participated in all study segments (pre- and main questionnaire, two 9-day food frequency questionnaires, blood sampling) and fulfilled the following study criteria: vegan dietary intake at least 1 year prior to study start, minimum age of 18 y, no pregnancy or childbirth during the last 12 months. No interventions. All the 154 subjects had a comparatively low BMI (median 21.2 kg/m2), with an extremely low mean consumption of alcohol (0.77±3.14 g/day) and tobacco (96.8% were nonsmokers). Mean energy intake (total collective: 8.23±2.77 MJ) was higher in strict vegans than in moderate ones. Mean carbohydrate, fat, and protein intakes in proportion to energy (total collective: 57.1:29.7:11.6%) agreed with current recommendations. Recommended intakes for vitamins and minerals were attained through diet, except for calcium (median intake: 81.1% of recommendation), iodine (median: 40.6%), and cobalamin (median: 8.8%). For the male subgroup, the intake of a small amount of food of animal origin improved vitamin and mineral nutrient densities (except for zinc), whereas this was not the case for the female subgroup (except for calcium).Conclusion: In order to reach favourable vitamin and mineral intakes, vegans should consider taking supplements containing riboflavin, cobalamin, calcium, and iodine. Intake of total energy and protein should also be improved.
Semi-Supervised Learning with Generative Adversarial Networks

As society continues to accumulate more and more data, demand for machine learning algorithms that can learn from data with limited human intervention only increases. Semi-supervised learning (SSL) methods, which extend supervised learning algorithms by enabling them to use unlabeled data, play an important role in addressing this challenge. In this thesis, a framework unifying the traditional assumptions and approaches to SSL is defined. A synthesis of SSL literature then places a range of contemporary approaches into this common framework. Our focus is on methods which use generative adversarial networks (GANs) to perform SSL. We analyse in detail one particular GAN-based SSL approach. This is shown to be closely related to two preceding approaches. Through synthetic experiments we provide an intuitive understanding and motivate the formulation of our focus approach. We then theoretically analyse potential alternative formulations of its loss function. This analysis motivates a number of research questions that centre on possible improvements to, and experiments to better understand the focus model. While we find support for our hypotheses, our conclusion more broadly is that the focus method is not especially robust.
Design guidelines for a wearable robotic extra-finger

Wearable robotics is strongly oriented to humans. New applications for wearable robots are encouraged by the lightness and portability of new devices and the progress in human-robot cooperation strategies. In this paper, we propose the different design guidelines to realize a robotic extra-finger for human grasping enhancement. Such guidelines were followed for the realization of three prototypes obtained using rapid prototyping techniques, i.e., a 3D printer and an open hardware development platform. Both fully actuated and under-actuated solutions have been explored. In the proposed wearable design, the robotic extra-finger can be worn as a bracelet in its rest position. The availability of a supplementary finger in the human hand allows to enlarge its workspace, improving grasping and manipulation capabilities. This preliminary work is a first step towards the development of robotic extra-limbs able to increase human workspace and dexterity.
Finite Position Set-Phase Locked Loop for Sensorless Control of Direct-Driven Permanent-Magnet Synchronous Generators

This paper presents a novel finite position set-phase locked loop (FPS-PLL) for sensorless control of surface-mounted permanent-magnet synchronous generators (PMSGs) in variable-speed wind turbines. The proposed FPS-PLL is based on the finite control set-model predictive control concept, where a finite number of rotor positions are used to estimate the back electromotive force of the PMSG. Then, the estimated rotor position, which minimizes a certain cost function, is selected to be the optimal rotor position. This eliminates the need of a fixed-gain proportional-integral controller, which is commonly utilized in the conventional PLL. The performance of the proposed FPS-PLL has been experimentally investigated and compared with that of the conventional one using a 14.5 kW PMSG with a field-oriented control scheme utilized as the generator control strategy. Furthermore, the robustness of the proposed FPS-PLL is investigated against PMSG parameters variations.
Mixture of Expert Agents for Handling Imbalanced Data Sets

Many real-world data sets exhibit skewed class distributions in which almost all cases are allotted to a class and far fewer cases to a smaller, usually more interesting class. A classifier induced from an imbalanced data set has, typically, a low error rate for the majority class and an unacceptable error rate for the minority class. This paper firstly provides a systematic study on the various methodologies that have tried to handle this problem. Finally, it presents an experimental study of these methodologies with a proposed mixture of expert agents and it concludes that such a framework can be a more effective solution to the problem. Our method seems to allow improved identification of difficult small classes in predictive analysis, while keeping the classification ability of the other classes in an acceptable level.
Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): a reevaluation of the Life Orientation Test.

Research on dispositional optimism as assessed by the Life Orientation Test (Scheier & Carver, 1985) has been challenged on the grounds that effects attributed to optimism are indistinguishable from those of unmeasured third variables, most notably, neuroticism. Data from 4,309 subjects show that associations between optimism and both depression and aspects of coping remain significant even when the effects of neuroticism, as well as the effects of trait anxiety, self-mastery, and self-esteem, are statistically controlled. Thus, the Life Orientation Test does appear to possess adequate predictive and discriminant validity. Examination of the scale on somewhat different grounds, however, does suggest that future applications can benefit from its revision. Thus, we also describe a minor modification to the Life Orientation Test, along with data bearing on the revised scale's psychometric properties.