Reviewerly/exHarmony huggingface dataset:
Kleptographic Attack on Elliptic Curve Based Cryptographic Protocols

Kleptography is the study of pilfering secure data secretly and subliminally. The concept of inserting backdoors was introduced two decades ago by Young and Yung. However, still it is a serious threat for modern cryptography. Different studies have proved that exploiting implementation errors of cryptographic algorithms needs less effort as compared to attacking its mathematical structure. Inserting the backdoor modifies the standard method of generating public and private key pairs in such away that the public information is meaningful for the attacker. This paper presents the kleptographic attack on cryptographic algorithm based on Elliptic curves. We show the technique of implementing backdoor against Edwards-curve Digital Signature Algorithm, Elliptic curve Diffie-Hellman key exchange scheme, Elliptic curve Digital Signature Algorithm, Elliptic curve Integrated Encryption Scheme, Elliptic curve ElGamal Encryption and Elliptic curve Qu-Vanstone implicit certificate scheme. In practical approach, backdoors are inserted in such a way that their identification is impossible by analyzing the output of an algorithm. Detection of kleptographic implementation is a complex task and very few studies can be found in this direction. We have explored the possibility of detection of malicious code inside the Elliptic curve based algorithms by using the idea of running time analysis. We have shown that by implementing strong Secretly Embedded Trapdoor with Universal Protection (SETUP) attack against Elliptic curve based algorithms, one can detect the presence of backdoor by analyzing the time difference in execution of an honest vs malicious version of code. We also modified the backdoor insertion mechanism in Edwards-curve Digital Signature Algorithm that results in negligible time difference making it impossible for the user to detect backdoor presence.
Designing for a pluralist and user-friendly live code language ecosystem with Sema

The growing popularity of the live coding and algorave scenes has inspired incentive and support for accessible, diverse and innovative approaches in expressing art through code. With live coding, the real-time composition of music and other art becomes a performance art by centering on the language of the composition itself, the code.Sema is a new open source system that aims to support user-friendly approaches to language design and machine learning in live coding practice. This paper reports on the latest technical advances and user research with Sema. We provide an overview and design rationale for the early technical implementation of Sema, including technology stack, architecture, user interface, integration of machine learning, and documentation and community resources. We also describe the activities of the MIMIC Artist Summer workshop, a full-week workshop with a group of 12 participants, which we designed and delivered to gather user feedback about the first design iteration of Sema. Findings from our workshop corroborate that language design and machine learning are advanced topics in computer science that may be challenging to users without such a background. Nevertheless, we found that such topics can inform the design of systems that may be both useful and usable to the live coding community.
E-LEARNING: MENGEMBANGKAN KONTEN STANDARISASI SCORM DENGAN ISPRING SUITE

e-learning is a form of teaching and learning activities that involve the use of informationand communication technology. Lack of innovation and creativity in producing interesting andinteractive content causes the e-learning system to be less beneficial to its users. The purpose ofthis research is to produce a SCORM standard format on e-learning content using the iSpringSuite 8 application. Content enrichment is indispensable and the use of content in various typesof e-learning platforms must receive special attention. Digital assets with standardized SCORMformats can produce more interesting and interactive content for lecturers and students. With theSCORM standard, learning material is packaged into a complete one so that it can be reused ondifferent LMS platform learning systems. In this research activity, the iSpring Suite applicationis only used to create standard SCORM content in the form of a zip file that is ready to be uploadedto moodle. The following research needs to develop audio video content such as using the iSpringCam feature to record lecturer activities like making a tutorial.Keywords— e-learning, SCORM, ISpring Suite, LMS
The semi-Markov beta-Stacy process: a Bayesian non-parametric prior for semi-Markov processes.

The literature on Bayesian methods for the analysis of discrete-time semi-Markov processes is sparse. In this paper, we introduce the semi-Markov beta-Stacy process, a stochastic process useful for the Bayesian non-parametric analysis of semi-Markov processes. The semi-Markov beta-Stacy process is conjugate with respect to data generated by a semi-Markov process, a property which makes it easy to obtain probabilistic forecasts. Its predictive distributions are characterized by a reinforced random walk on a system of urns.
Effectiveness of Organizing a Non-Face to Face Tutorial Package System in Distance Education

At this time, the number of students of elementary school teacher programs at the Universitas Terbuka (UT) in one study group as many as 20-30 people in some places there is a tendency challenging to be fulfilled. This challenge because most elementary school teachers already have a bachelor's degree. Meanwhile, the location of students at this time tends to be increasingly scattered with distant geographical areas, so it is necessary to provide a particular service called the Non-Face to Face Tutorial Package System (NFFTPS) for Practical/Practicum courses. The sample in this study was the undergraduate students of elementary school teacher programs in the regional office of Pangkalpinang, Serang, Bandung, Denpasar, Ambon, amounting to 75 respondents. This research is categorized as a qualitative descriptive study. From the results of this study, it can be concluded that the NFFTPS program has been implemented quite well. However, in its implementation, there are still many obstacles encountered and need to be refined in the future. Besides, there is a need for a synergy of academic guidance services for NFFTPS programs in regional office and UT central so that they can provide quality, appropriate, timely, and targeted services.
Climbing the Hill with ILP to Grow Patterns in Fuzzy Tensors

Fuzzy tensors encode to what extent n-ary predicates are satisfied.The disjunctive box cluster model is a regression model where sub-tensors are explanatory variables for the values in the fuzzy tensor.In this article, locally optimal patterns for that model, with high areas times squared densities, are grown by hill-climbing from fragments of them.A forward selection then chooses among the discovered patterns a non-redundant subset that fits, but does not overfit, the tensor.
Audio-Visual Understanding of Passenger Intents for In-Cabin Conversational Agents

Building multimodal dialogue understanding capabilities situated in the in-cabin context is crucial to enhance passenger comfort in autonomous vehicle (AV) interaction systems.To this end, understanding passenger intents from spoken interactions and vehicle vision systems is an important building block for developing contextual and visually grounded conversational agents for AV.Towards this goal, we explore AMIE (Automated-vehicle Multimodal In-cabin Experience), the in-cabin agent responsible for handling multimodal passenger-vehicle interactions.In this work, we discuss the benefits of multimodal understanding of in-cabin utterances by incorporating verbal/language input together with the non-verbal/acoustic and visual input from inside and outside the vehicle.Our experimental results outperformed text-only baselines as we achieved improved performances for intent detection with multimodal approach.
A Contract-Theoretic Cyber Insurance for Withdraw Delay in the Blockchain Networks with Shards

As the basis of the most existing blockchain networks, Proof of Work (PoW) consensus protocol highly relies on the computational resources, and thus causing a huge waste of energy. Proof of Stake (PoS) is the alternative to relieve the PoW dilemma. However, it is also under threat, i.e., discouragement attack, which is a way to bring down the blockchain networks without any effective defense against it. To prevent the discouragement attack, the founders of Ethereum argue that the system should set a withdraw delay instead of allowing the validators entry/exit quickly. But how to determine the delay is still an open question. In this paper, we adopt the cyber insurance idea and propose the insurance contract to help determine the withdraw delay, as well as the insurance claim to relieve the loss of victims. Specifically, instead of requiring the insurance premium from the validators, the cyber insurer first signs the contract with the blockchain representative (e.g., beacon chain). Then the blockchain representative would sign a series of contracts with the validators. By such design, the validators can obtain the insurance claim without paying the premium, while the blockchain networks can keep the validators staying online to resist the discouragement attack. Finally, through the simulations, we demonstrate that the proposed model is capable of providing adaptive insurance contracts for the different validators and keeping the profits of the blockchain network and the cyber insurer.
Provincial Clustering in Indonesia Based on Plantation Production Using Fuzzy C-Means

The plantation sector is one sector that plays an important role in the economy in Indonesia, which is to increase the country’s foreign exchange. This study aims to cluster plantation products in Indonesia by province in 2017 using fuzzy c-means and silhouette index method. In this cluster, the data will be grouped into 3 clusters. The result of three clusters were obtained by 1 province in the first cluster with high plantation products, 27 province in the second cluster with low plantation products and 6 province in the third cluster with medium plantation products. In the silhouette index test, the silhouette index value of all clusters is 0,84321191 which means that the result of the grouping are appropriate.
Gaze-Based Self-Confidence Estimation on Multiple-Choice Questions and Its Feedback

Self-confidence - an assurance of one's personal decision and ability - is one of the most important factors in learning. When there is a gap between a learner's confidence and comprehension, the learner loses a chance to review a learning subject correctly. To solve this problem, we propose a system which estimates self-confidence while solving multiple-choice questions by eye tracking and gives feedback about which question should be reviewed carefully. The system was evaluated in our experiment involving 20 participants. We observed that correct answer rates of questions were increased by 14% and 17% by giving feedback about correct answers without confidence and incorrect answers with confidence, respectively.
Static Hand Gesture Recognition Using Multi-Layer Neural Network Classifier on Hybrid of Features

Hand gesture recognition has gotten so many areas of application such as in human-computer interaction, hearing impaired communication and systems control. Recognizing gestures in videos however is a challenging task. Many techniques and features have been adopted in the literature but some of the methods still need to be improved upon. There are basically two types of gestures: the static and the dynamic gestures. In this work, a computer vision-based system for recognition of static hand gesture is proposed using a fusion of the histogram of oriented gradient and the Hu invariant moments as features. The proposed system consists of three phases: preprocessing, feature extraction and classification. The images are first pre-processed using segmentation and morphological operations. The histogram of oriented gradient and the Hu invariant moments are then extracted as features. The extracted features are concatenated and passed as input into a multilayer neural network model to recognize the static hand gesture. The proposed system is implemented and tested on the hand gesture database collected online. The model was trained using 500 features which consist of 20 gestures each from 25 gesture types. The model is then tested with another 500 gestures which also consist of 20 gestures each from the 25 gesture types. The experimental results show that the proposed system is able to recognize the static gestures with accuracy of 96.4%.
Adaptive and Complementary Correlation Filter With Dynamic Contextual Constraints

Correlation filter-based trackers have gained more and more attention because of their great performances and relative high tracking speeds. However, this kind of trackers may suffer model drifting due to learning limited background information during filter training. This may lead to tracking failures in some complex scenes, such as background clutter, deformation, illumination variation and so on. In this article, we propose an adaptive and complementary correlation filter with dynamic contextual constraints. First, we introduce contextual information around the target as a dynamic constrained term to alleviate model drifting in complex scenes, the optimal function of which can be solved by an iterative method. Then, we integrate a color histogram-based tracker to compensate the inaccurate tracking of correlation filtering. In addition, we present metrics to combine the two complementary trackers with adaptive fusion coefficients. Finally, extensive experiments on OTB2013, OTB2015, VOT2016 and UAV123 benchmark datasets demonstrate that our tracker can improve the performance of our baseline and can perform favorably against some state-of-the-art trackers.
ROBOTIC TOYS AND KITS IN PRIMARY SCHOOL EDUCATION

Appears in: EDULEARN20 Proceedings Publication year: 2020Pages: 3275-3285ISBN: 978-84-09-17979-4ISSN: 2340-1117doi: 10.21125/edulearn.2020.0942Conference name: 12th International Conference on Education and New Learning TechnologiesDates: 6-7 July, 2020Location: Online Conference
Sign rank vs discrepancy

Sign-rank and discrepancy are two central notions in communication complexity. The seminal work of Babai, Frankl, and Simon from 1986 initiated an active line of research that investigates the gap between these two notions. In this article, we establish the strongest possible separation by constructing a boolean matrix whose sign-rank is only 3, and yet its discrepancy is 2-Ω(n). We note that every matrix of sign-rank 2 has discrepancy n-O(1).Our result in particular implies that there are boolean functions with O(1) unbounded error randomized communication complexity while having Ω(n) weakly unbounded error randomized communication complexity.
A Case Study of Consolidating Two Database A–Z Lists for Better Staff and User Experiences

This case study describes the consolidation and migration of the University of New Mexico’s University Libraries’ database A-Z lists. A subject librarian lead the nine-month project that included most subject librarians, the electronic resources team, the Director of Collections, and the web &amp; discovery librarian. The project also provided the UL the opportunity to review all the resources in the lists, and update all descriptions, and create new workflows for adding and managing a single list.
Automatic Feature Extraction for Human Activity Recognitionon the Edge

This thesis evaluates two methods for automatic feature extraction to classify the accelerometer data of periodic and sporadic human activities. The first method selects features using individual h ...
Collective and Communicative Memory of The Scientific Community: Features of Formation and Research

The article analyzes the ambivalent nature of the phenomenon of collective memory in the some aspects: transpersonal and interpersonal, general and singu­lar, as the sum of individual memories and as an independent structure. It is shown that it is its constructed nature that is a key feature of collective memory, which distinguishes it from historical memory, cultural memory, making the col­lective an essential part of social memory. The role of communication in the for­mation of collective memory is emphasized on the example of the analysis of the memory of social communities, in particular, the scientific community, the study of which allows us to demonstrate the ambivalent nature of collective memory. Following Jan Assmann, we are considering the communication memory as a&nbsp;collection of memories of the recent past, summarizing the personal experience of contemporaries of the events and several subsequent generations. It is con­cluded that to study the characteristics of the functioning of the scientific com­munity, it is possible to equate the value of collective and communicative mem­ory, using as the most promising narrative approach. This will allow to reflect the features of such a memory – scientific and professional, which is being formed at the same time in the context of the formation of the vital world of man
Stratus: Clouds with microarchitectural resource management

The emerging next generation of cloud services like Granular and Serverless computing are pushing the boundaries of the current cloud infrastructure. In order to meet the performance objectives, researchers are now leveraging low-level microarchitectural resources in clouds. At the same time these resources are also a major source of security problems that can compromise the confidentiality and integrity of sensitive data in multi-tenant shared cloud infrastructures. The core of the problem is the lack of isolation due to the unsupervised sharing of microarchitectural resources across different performance and security boundaries. In this paper, we introduce Stratus clouds that treat the isolation on microarchitectural elements as the key design principle when allocating cloud resources. This isolation improves both performance and security, but at the cost of reducing resource utilization. Stratus captures this trade-off using a novel abstraction that we call isolation credit, and show how it can help both providers and tenants when allocating microarchitectural resources using Stratus's declarative interface. We conclude by discussing the challenges of realizing Stratus clouds today.
The Modest Philosopher Adolf Lazarev: Life, Ideas, Correspondence (Review on “A Hardworking Interpreter of Shestov’s Groundlessness”: Adolf Markovich Lazarev. Letters. Articles on Lev Shestov, ed. by V. Khazan. Moscow: Vodolei Publ., 2019. 440 p.)

The review is dedicated to the new book of Vladimir Khazan, which collects the correspondence of the “forgotten” existential thinker from the “Shestov” circle A.M. Lazarev with G.G. Shpet, N.A. Berdyaev, A.M. Remizov, J. Papini, Lev Shestov, J. Grenier and B. de Schloezer; also included are unknown articles on Lev Shestov’s philosophy. From the introduction and published letters we learn about Lazarev’s biography, the direction of his views, his environment, the life and work of Russian thinkers and writers in exile, as well as the reception of Russian philosophy in Europe. Despite the fact that the views of Shestov and Lazarev have much in common (interest in the personalities of philosophers, “peregrination through souls” as a philosophical method, philosophizing about the “one thing is necessary” (Luke, 10: 42), the struggle for personality and its freedom, criticism of rationalism and intellectualism, religious searches and etc.), Lazarev’s interests are not limited to Shestov’s philosophy: he is the author of one of the first thorough studies of pragmatism in Russia and one of the most successful domestic works about Bergson, he also wrote an article that played a significant role in the history of the study of philosophy J. Lequier. The book of Khazan opens up for the history of Russian thought and culture the name and writings of a philosopher who fell outside the field of view of researchers and readers.
Consensus-Based Distributed Multitarget Tracking with Probabilistic Track-to-Track Association

In this paper a novel consensus algorithm for distributed multi-sensor multi-target tracking is proposed, adaptive in the context of sensors having limited sensing range in a cluttered environment. The algorithm is composed of two consensus schemes working in parallel; it assumes intersensor communication of target state estimates, together with adaptive scalars used for weighting the estimates. A new track-to-track association and fusion methodology, matching the communicated estimates of different sensors, is also proposed. It is based on the all neighbors approach and the Integrated Probabilistic Data Association methodology. An accompanying theoretical analysis of stability and reduction of noise influence gives an insight into the interplay between the local trackers and the global algorithm. Numerical simulations illustrate specific properties of the algorithm and show that it exhibits very good tracking performance, close to the centralized solution.
OPEN EDUCATIONAL RESOURCES FOR THE STRENGTHENING OF DIGITAL COMPETENCES IN HIGHER EDUCATION

J. Delgado1, R. Samaniego1, J. Salinas2, M. Acosta1, A. Avila1 1Universidad Técnica de Machala (ECUADOR) 2Universidad de las Islas Baleares (SPAIN)
Inhabiting Different Realities: Incrementalism, Paradigms and the New Prospect

The emergence of cryptographic consensus technology has enabled new prospects for the formation of commercial relationships, institutional arrangements and interactions (the New Prospect). This paper queries whether the current vector of regulatory thinking about crypto-assets is capable of achieving the public policy objectives of regulation while not obstructing the exploration of the New Prospect and the possible benefits it might bring to society. Key precursors to ecosystem development are discussed, and their dependence on the nature and quality of regulatory oversight structures considered. It is argued that an incrementalist approach to regulatory development has supported a “fit-to-existing-regulation” (FER) taxonomy of crypto-assets ill-suited to fostering the ecosystem, despite changed fact patterns that challenge the underlying assumptions of incrementalism. The analysis suggests applying financial regulation to crypto-assets may be inhibiting rather than facilitating innovation along possible new pathways. How society’s past experiences of responding to change in the formation of commercial relationships is considered. Shortcomings in current policy approaches suggest a need for fundamental regulatory reform to be placed more firmly on the global discussion agenda. As a more complex ecosystem begins to emerge, its ability to evolve and flourish will depend on whether the design of a more fit-for-purpose regulation is ready. A “Determined-By-Architecture” (DBA) taxonomy is presented that has the potential to bring new perspectives on the internal and external operations of the technology and hence regulatory design considerations such as technology neutrality. Five proposals for policy development are made.
Uncovering CHI Reviewers Needs and Barriers

A peer review process is an essential part of not only in the CHI conference but also in many scientific research areas to determine which paper submitted should be accepted. In order to improve the peer review process, tools have been developed to support reviewers by reducing the paper they should review or by highlighting key sentences to read faster. However, only a few studies investigated reviewers' perspectives regarding their tasks during the peer review process. In this paper, we conducted semi-structured interviews with CHI reviewers who have experienced in reviewing paper submitted to the CHI conference. As a result, we better understand how paper-reviewing tasks are performed, which tasks reviewers felt most challenging, and reviewers' needs for a better peer review experience.