Reviewerly/exHarmony huggingface dataset:
Self-reliance without self-satisfaction: Emerson, Thoreau, Dylan and the problem of inaction

The idea of self-reliance is important not only because it is often taken to be definitive of the ethics of democratic individualism, but because its greatest theorists have been uncommonly forthright about a problem that, though familiar to ordinary civic experience, frequently gets ignored: that self-reliant individuality is a basis for not fully supporting otherwise endorsed social justice causes. This article turns to Ralph Waldo Emerson, Henry David Thoreau and Bob Dylan who are unusual for so honestly reflecting upon this problem and who, because of the differences in the way they conceptualize it, are instructive for civic ethics. I demonstrate that Emerson and Thoreau imbue their self-reliant withdrawal from social action with a self-satisfaction that is lacking for Dylan, who is much readier to acknowledge the moral costs of self-reliance. This acknowledgement does not invalidate self-reliance but alters its epistemological, ethical and political features, providing a variant of self-reliance more suitable to contemporary conditions.
Cross-Cultural Image-Based Author Profiling in Twitter

Recent works have shown that it is possible to use information extracted from images to address the task of automatic gender identification. These proposals have validated their solutions using monolingual datasets, i.e., collections where images are shared by users having the same mother tongue. This paper aims to test the usefulness of images collected from users who do not share the same language. In principle, these users present cultural differences, which may be reflected in the images they share. However, a cross-cultural image-based approach would be very useful for languages where data is not available or scarce. The experiments presented demonstrate that characteristics obtained from the images, regardless of the users’ mother tongue, can be used for gender prediction. They mainly confirm the usefulness of a cross-cultural image-based approach, showing that culturally different individuals with equivalent profiles traits tend to share similar images.
Protecting RSA Hardware Accelerators against Differential Fault Analysis through Residue Checking

Hardware accelerators for cryptographic algorithms are ubiquitously deployed in nowadays consumer and industrial products. Unfortunately, the HW implementations of such algorithms often suffer from vulnerabilities that expose systems to a number of attacks, among which differential fault analysis (DFA). It is therefore crucial to protect cryptographic circuits against such attacks in a cost-effective and power-efficient way. In this paper, we propose a lightweight technique for protecting circuits implementing the RSA algorithm against DFA. The proposed solution borrows residue checking from the traditional fault tolerance and applies it to RSA circuits in order to first detect the occurrence a fault and then to react to the attack by obfuscating the output values. An experimental campaign demonstrated that the proposed solution detects the 100% of the possible fault attacks while leading to a 2.85% area overhead, a 16.67% power consumption increase and with no operating frequency decrease.
Affective Critical Play

This application for the doctoral consortium at CHI PLAY 2019 presents an exploration of critical play from aesthetic and affective perspectives. It uses art and history museums as its field, and the design of hybrid experiences as its experiments. The approach is concept-driven and takes its inspiration from theories of ritual, play and performance.
Witnessing Causal Nonseparability: Theory and Experiment

We develop a technique to witness a process that is not causally separable, in that it cannot be written as a fixed-order quantum circuit or a mixture of those. Using the process matrix formalism, we find a set of measurements within the process that proves causal non-separability. The problem of finding these measurements can be written as a SemiDefinite Program that can be solved efficiently. We apply our method in an experiment we performed in our labs, where we implemented a causally non-separable process and proved it to be so by performing unitary operations and final measurements.
Long Term Healthcare System for Elders by Using Internet of Things with Big Data

This paper proposes an elder care system that develops a multi-solution for Taiwan's current Long-Term Care 2.0. The system is designed by using the Internet of Things, Big data, cloud database, application of various sensors, and the integration of the experiences of the Long-Term Care Centers. We find a way to create the maximum effectiveness with the least resources, so that elders in long-term care centers can keep their ability of daily living activities (ADLs) and instrumental activities of daily living (IADLs), and it alleviates internal pressures and costs inside country under the continuing aging society.
KNOWLEDGE TRANSFER AS ONE OF THE FACTORS OF INCREASING UNIVERSITY COMPETITIVENESS

The paper deals with university knowledge transfer. The adjustment of relations between universities and enterprises makes knowledge transfer a necessary requirement for university development to ensure the implementation of market-oriented educational programs. The paper proposes use of modular competency-based and ontological approaches to ensure the university knowledge transfer. The initial data is presented in the databases of the university, authorized bodies of education and science, enterprises, business structures and professional standards. This data is processed and scanned for knowledge to be put into the knowledge database with technological (informational) and modular competency-based approaches. As part of a market-oriented innovation university concept the task is to improve the education system in relation to skills development. To solve this problem it is necessary to build a distributed information system of university knowledge transfer. It is necessary to create a unified educational space - an educational portal - to ensure the university knowledge transfer between all participants - teachers, students and employers. The study offers an architectural solution for a distributed information system.
Merging Cognitive and Sociocultural Approaches: Toward Better Understandings of the Processes of Developing Thinking and Reasoning

Educational psychology research in general, as well as in terms of science education in the twentieth century, has generally followed one of three distinct and exclusionary approaches: laboratory-based studies of cognitive processes presumed important for education; observational field studies of classrooms and educational practices viewed from a sociocultural perspective; and psychometric-based analyses of student aptitudes and achievements as measured on standardized tests. However, recent advances in knowledge and theory have led researchers from all of these approaches to adopt more global views of their research, with the result that there is considerable potential for developing meaningful linkages among these different approaches. One such linkage has been an increased concern with understanding how to produce “far transfer” effects as a common goal of most educational interventions, i.e., to prepare students to perform well in new situations by adapting what they have been explicitly taught to solve problems and produce outcomes that are new or different from their specific training. In this chapter we consider some of the promising new directions and important research questions raised by this more integrated view of the nature of educational practices.
Symmetric Ternary Wavelet Transform and Its Application in Digital Information Processing

This paper deals with the discrete symmetric ternary wavelet transform. It was synthesized based on two systems of wavelet functions, each is based on the respective mother wavelet. A filter bank was calculated for the synthesized transform. Application effectiveness of the synthesized transform was estimated in comparison with the existing ones using mean squared error criterion.
Player Dominance Adjustment Motion Gaming AI for Health Promotion

This paper presents an opponent fighting game AI for promoting balancedness in use of body segments of the player during full-body motion gaming. The proposed AI, named PDAHP-AI, is based on Monte Carlo tree-search and employs a recently purposed concept called Player Dominance Adjustment, where the AI determines its actions based on the player’s inputs so as to adjust the player’s dominant power. The basic idea is to let the player dominate the game when they perform healthy movement and on the contrary to have the AI take a strong action against the player when she or he performs unhealthy movement. The AI outperforms an existing dynamic difficulty adjustment AI designed for the same propose.
OpenVirtualObjects: An open set of standardized and validated 3D household objects for virtual reality-based research, diagnostics, and therapy

Virtual reality (VR) technologies have become increasingly available to clinicians and researchers. However, standardized 3D content, like scenes and objects, is not widely and freely available. We introduce OpenVirtualObjects; a free and open set of 124 realistic 3-D household objects for VR-based testing, training, diagnostics and rehabilitation. The objects were rated by 34 younger and 25 older adults for recognizability, familiarity, visual complexity, contact, and usage in daily life. Participants also categorized and named the objects. We describe the procedures of the object creation and validation and we provide descriptive statistics for each rated dimension.
Digital Signature Schemes over the Ring Z[e2πi/5]

This paper proposes an extended RSA digital signature scheme and extended ElGamal digital signature schemes with appendix and with message recovery over the algebraic integer ring Z[e2πi/5] of the cyclotomic field Q[e2πi/5]. In these digital signature schemes, the extended Euler-phi function is φ(n) = (p4 - 1) (q4 - 1) compared to the classical Euler-phi function φ(n)=(p-1)(q-1) where n is a product of two large primes p and q. The encryption exponent is chosen to be coprime to the extended Euler-phi function. Thus, the encryption exponents have more options, which provides more security than that of the classical case. The securities of digital signature schemes depend on the difficulty of factoring large integers into a product of primes, and logarithmic computations in the ring Z[e2πi/5] Some numerical examples are given.
RubiCrypt: Image Scrambling Encryption System Based on Rubik’s Cube Configuration

This paper proposes an image-encryption algorithm based on the Rubik's cube configuration,allowing for multi-dimensional security keys. The input image is scrambled using the random configuration of a Rubik's cube. Here the aim is to encrypt or decrypt an image using a custom pixel scrambling algorithm. It uses a Rubik's Cube as the encryption & decryption key, which allows for 43,252,003,274,489,856,000 (43 quintillion) distinct key configurations. RubiCrypt makes use of several image processing algorithms from OpenCV for scanning the cube in real-time. Finally, Analysis along with experimental results shows that the proposed encryption scheme can achieve good encryption as well asconsiderable hide-ability. Which can resist all the elements related with statistical and differential attacks.
Towards Automated Patch Management in a Hybrid Cloud

Software patching is routinely employed for enterprise online applications to guard against ever-increasing security risks and to keep up with customer requirements. However, in a hybrid cloud setting, where an application deployment can span across diverse cloud environments, patching becomes challenging, especially since application components may be deployed as containers or VMs or bare-metal machines. Further, application tiers may have dependencies, which need to be respected. Worse, to minimize application downtime, selected patches need to be applied in a finite time period. This paper presents an automated patching strategy for hybrid-cloud—deployed applications that leverages a greedy algorithm design to optimally patch applications. Our implementation and evaluation results highlight the efficacy of our strategy and its superiority over alternative patching strategies.
Just Ask Me

To understand whether people can identify their optimal touchscreen target sizes, we asked older and younger adults to identify optimal target sizes on a questionnaire and compared these chosen sizes to performance on a target acquisition task. We found that older individuals (60+) were better than younger adults at choosing their optimal target sizes. In fact, younger adults underestimated the smallest target size they could accurately touch by almost 6mm. This study suggests that older adults may be able to better configure target size settings than younger adults.
Time optimal control of coupled spin dynamics: A global analysis

In this paper, we study some control problems that derive from time optimal control of coupled spin dynamics in NMR spectroscopy and quantum information and computation. Time optimal control helps to minimize relaxation losses. In a two qubit system, the ability to synthesize local unitaries much more rapidly than evolution of couplings, gives a natural time scale separation in these problems. The generators of unitary evolution g, are decomposed into fast generators k, (local Hamiltonians) and slow generators p, (couplings) as a Cartan decomposition g=p⊕k. Using this decomposition, we exploit some convexity ideas to completely characterize the reachable set and time optimal control for these problems. The main contribution of the paper is that we carry out a second order analysis of time optimality.
Predictive Modeling Of Erroneous Software Behavior In Embedded Digital Systems Due To Extreme Electromagnetic Interference

Predicting the behavior of digital electronic and embedded systems subjected to extreme electromagnetic interference (EEMI) is a growing concern for military and civilian systems operating in ever denser ambient electromagnetic (EM) or Radio Frequency (RF) environments. While the interaction of the EM/RF stimulus with the system circuitry occurs at the physical or hardware level (“glitch”), the manifestation of this interaction is often observed as an erroneous behavior in the software state of the system under EM/RF stress. In this paper, we present ongoing progress in developing Markov State Vector Machine (MSVM) modeling frameworks for describing the software state of a microcontroller-based digital electronic system subjected to an externally applied glitch. We also describe our ongoing work in developing predictive MSVM models for the erroneous responses of complex software scripts when the underlying digital electronic system is subjected to EEMI glitches. Our predictive capability will help EMI/EMC engineers develop quick assessment tools for modeling the behavior of higher complexity digital electronic and embedded systems exposed to extreme electromagnetic environments.
Moving Average Filter untuk Memisahkan Efek Dangkal Anomali Gravitasi Time Lapse

[Title: Moving Average Filter for Time Lapse Gravity Anomaly Separation]. Interpretation of time-lapse gravity anomaly due to fluid injection in the reservoir is difficult when it mixed with shallow source anomalies. To solve the kind of problem, anomaly separation is performed with the method of Moving Average Filter. This study was conducted to obtain an effective method to separate the gravity anomaly of shallow sources on time-lapse gravity anomaly. Trials are conducted on anomaly models derived from reservoirs with three distinct depths that are 300, 600 and 900 meters. This forward model is then mixed with gravitational anomaly from the shallow source obtained from the field data. The mixed anomaly is then separated by a Moving Average filter. Results show that Moving Average filters can separate the shallow effect from the deep source anomaly and are effective up to a depth of 900 meters. The research is also beneficial for classroom learning in the computer programming class based on Matlab.
Selection systems and the Reduction theorem

In Chapters 2 and 3, we saw how the HKV method can be used to expand and enrich analysis of even very well-known mathematical models by introducing heterogeneity. Now we want to show how the method can be further developed in application to more general models of “selection systems.” In this chapter, we collect together main mathematical assertions that form the basis for HKV method for selection systems as mathematical models of inhomogeneous populations and communities. This is a theory-heavy chapter, so a reader who is interested primarily in learning how to use the HKV method in different applications can skip it and move on to the next chapter.
Research Status and Prospective on Current Transformer Saturation Recognition

Saturation identification of current transformers (CT) has always been one of the most important issues in power system relay protection. At present, the saturation phenomenon of CT is widespread in China. In order to accurately grasp the current research status and future research directions of current transformer saturation identification, the author summarizes and classifies the existing methods of current transformer saturation identification: based on CT physical quantities identification method, based on other physical quantities identification method and based on waveform singularity identification method, respectively, introduces the research principles and characteristics of these methods. The research progress of each method is summarized, and the shortcomings of some methods are pointed out. Finally, several key issues in the future of CT saturation identification are summarized, and prospects for future research are put forward.
Towards Logically Progressive Dialog for Future TODS to Serve in Complex Domains

Complex domains demand task-oriented dialog system (TODS) to be able to reason and engage with humans in dialog and in information retrieval. This may require contemporary dialog systems to have improved conversation handling capabilities. One stating point is supporting conversations which logically advances, such that they could be able to handle sub dialogs meant to elicit more information, within a topic. This paper presents some findings on the research that has been carried out by the authors with regard to highlighting this problem and suggesting a possible solution. A solution which intended to minimize heavy reliance on handcrafts which have varying challenges. The study discusses an experiment for evaluating a novel architecture envisioned to improve this conversational requirement. The experiment results clearly depict the extent to which we have achieved this desired progression, the underlying effects to users and the potential implications to application. The study recommends combining Agency and Reinforcement learning to deliver the solution and could guide future studies towards achieving even more natural conversations.
Societies in Games: How do Players Perceive Groups of Game Characters?

In recent years, game worlds are getting increasingly larger. With their expansion, the number of characters populating these virtual environments promotes a vast interaction space. To guarantee that interactions between characters do not compromise players' experience, they must exhibit coherent social behavior. Currently, game developers rely on scripted content to create the illusion of social behavior. However, we argue that a heavy authoring approach does not suit the generation of large populations of characters. In this work, we will use a computational model called Cognitive Social Frames to understand how players perceive and interpret the social dimensions of game characters' actions. In this document, we describe how we applied a socio-cognitive agent architecture to a population of game characters. Using a game-like environment, we intend to study what aspects of social behavior are perceived by players as relevant when generating societies in games. We elaborate on a proposal for a user study that will focus on the adjustment of characters' behavior based on their interpretation of the world and the coherence of their actions within groups of characters.
Person Search Based on Improved Joint Learning Network

Person re-identification has received more and more attention in recent years. However, the pedestrian images used in most existing algorithms are always produced by cropping the integral surveillance images in manual or machining ways, and there is usually only one person in each of the cropped images. In this paper, person re-identification based on the integral surveillance images is researched, which is more close to the real-world scenario. The challenge of person search mainly comes from: (1) unavailable bounding boxes for pedestrians, (2) large consumption on time and hardware. To address these two issues, we propose a multi-level feature fused framework (MLF), which can deal with pedestrian detection and person re-identification in a unified network. The first module of the framework is served as the common module for both pedestrian detection and person re-identification. The second module is designed for pedestrian detection, in which three scales of feature maps from different layers are fused to get precise pedestrian bounding boxes; In addition, we use appropriate anchors and introduce soft-NMS into our algorithm to reduce missed-detections and false-detections, especially for small pedestrians. The third module is designed for person re-identification, we use an aggregated residual transformation for deep neural network in some convolutional layers, in which way the convolutional layers' parameters and training time could be decreased. Experiments based on CUHK-SYSU and PRW show the effectiveness of the proposed method.
Semantic Role Elaboration

Thematic relations are of two main kinds: semantic roles and elaborate thematic relations (ETRs). Semantic roles (such as Agent, Patient, and Instrument) are linguistic relations, and may be present in the statement of grammatical rules. ETRs (such as “eaten thing,” “scratcher,” “with his foot”) are cognitive relations and are present in cognitive representations but have no role in the grammatical structure. These two kinds of thematic relations are connected by elaboration, which is composed of hyponymic tracks—thus, in a sentence containing the verb scratch the “scratcher” is a hyponym of the Agent and is correspondingly coded as the subject of the sentence, which is the prototypical coding for the Agent. We say then that “scratcher” is one of the elaborations of the Agent. The same occurs with the “eater” (if the verb is eat), and so on. Semantic roles are important because some grammatical rules must be stated in terms of them; and ETRs are important because only they are directly accessible to the language user’s introspection.
Application of Co-simulation of ProE and SimMechanics in Teaching

For the abstraction of control theory course, ProE and SimMechanics are introduced into control theory teaching. ProE and SimMechanics toolbox are used for joint modeling, showing the simulation process with 3D animation, which greatly improves students' learning enthusiasm and classroom teaching efficiency.
Authenticated Encryption Schemes on Java Card

Authenticated encryption algorithms will be the main workhorse for secret-key cryptography in the future. The ever increasing use of smart cards requires that authenticated encryption schemes are also available on smart cards. In this paper, five authenticated ciphers from the CAESAR competition are implemented and evaluated on Java card platform. The performance and memory footprint are determined for each cipher which is relevant to low compute-power, memory-constrained embedded devices. This work enables availability of authenticated ciphers on Java card. The paper also motivates the case for providing authenticated encryption on cryptographic co-processors of smart cards.