Reviewerly/exHarmony huggingface dataset:
A collaborative filtering recommendation framework based on Wasserstein GAN

Abstract Compared with the original GAN, Wasserstein GAN minimizes the Wasserstein Distance between the generative distribution and the real distribution, can well capture the potential distribution of data and has achieved excellent results in image generation. However, the exploration of Wasserstein GAN on recommendation systems has received relatively less scrutiny. In this paper, we propose a collaborative filtering recommendation framework based on Wasserstein GAN called CFWGAN to improve recommendation accuracy. By learning the real user distribution, we can mine the potential nonlinear interactions between users and items, and capture users’ preferences for all items. Besides, we combine two positive and negative item sampling methods and add the reconstruction loss to the generator’s loss. This can well handle the problem of discrete data in recommendation (relative to the continuity of image data). By continuously approximating the generative distribution to the real user distribution, we can finally obtain better users’ preference information and provide higher accuracy in recommendation. We evaluate the CFWGAN model on three real-world datasets, and the empirical results show that our method is competitive with or superior to state-of-the-art approaches on the benchmark top-N recommendation task.
Freedom of Speech

Media and government accuse students of being libertarian (encouraging reckless free speech) or of too much no-platforming (banning external speakers). Both accusations are exaggerated but influential and make it difficult for students to develop face to face conversations about difficult and controversial topics. Government policies on securitization (Prevent) encourage risk averse behaviour, particularly but not exclusively among Muslims. Staff also feel constrained by these pressures and so staff and students self-censor. Analysis of free speech models available in a liberal democracy show two main types, each of which can become an extreme version of itself. The liberal model advocates legal free expression; however if exaggerated the liberal model becomes libertarian and can be offensive. The second approach is the guarded liberal model that seeks to protect minorities but if exaggerated it can turn into no platforming. Students and staff can learn to use combinations of all four approaches and increase face to face discussions.
Toward Efficient Bayesian Approaches to Inference in Hierarchical Hidden Markov Models for Inferring Animal Behavior

The study of animal behavioural states inferred through hidden Markov models and similar state switching models has seen a significant increase in popularity in recent years. The ability to account for varying levels of behavioural scale has become possible through hierarchical hidden Markov models, but additional levels lead to higher complexity and increased correlation between model components. Maximum likelihood approaches to inference using the EM algorithm and direct optimisation of likelihoods are more frequently used, with Bayesian approaches being less favoured due to computational demands. Given these demands, it is vital that efficient estimation algorithms are developed when Bayesian methods are preferred. We study the use of various approaches to improve convergence times and mixing in Markov chain Monte Carlo methods applied to hierarchical hidden Markov models, including parallel tempering as an inference facilitation mechanism. The method shows promise for analysing complex stochastic models with high levels of correlation between components, but our results show that it requires careful tuning in order to maximise that potential.
Protecting Smart Devices from the Bottom-up

Author(s): Machiry, Aravind | Advisor(s): Kruegel, Christopher; Vigna, Giovanni | Abstract: Modern systems are mainly composed of IoT devices and Smartphones.Most of these devices use ARM processors, which, along with flexiblelicensing, have new security architecture features, such as ARMTrustZone, that enables execution of a secure application in anuntrusted environment. Furthermore, with well-supported, extensible,open-source embedded operating systems like Android allows themanufactures to quickly customize their operating system with devicedrivers, thus reducing the time-to-market.Unfortunately, the proliferation of device vendors and race to the market has resulted in poor quality device drivers containing criticalsecurity vulnerabilities. Furthermore, the patches for thesevulnerabilities get merged into the end-products with a significantdelay resulting in the Patch Gap, which causes privacy andsecurity of billions of users to be at risk.In this dissertation, I will show how the new architecture features can leadto security issues by introducing new attack vectors.Second, I will show that the existing techniques are inadequate to find the security issues in Linux kernel drivers and how, with certain well-defined optimizations, we canprecisely find security issues.Third, I will present my solution to the problem of Patch Gap byshowing a principled approach to automatically port patches to vendor productrepositories.Finally, I will present our on-going work to automatically port C toChecked C, which provides a low overhead, backward-compatible, andmemory-safe C alternative that could be used on resource-constrained modern systems to prevent security vulnerabilities.Through this work, I presented effective ways to find, fix, propagate, and prevent vulnerabilities in modern system software, thus improving modern systems security.
A Family of Subfield Hyperelliptic Curves for Use in Cryptography

This paper proposes a family of hyperelliptic curves of genus two for public-key cryptographic primitives. Being subfield curves, the members of this family are easy to generate. Although slightly slower than elliptic curves at the same security level, hyperelliptic curves of our family exhibit performance comparable to widely used hyperelliptic curves over prime fields.
Modified Location Model Estimation using Content Based Medical Image Retrieval

Image has become more and more difficult to process for human beings. Perfect results cannot be obtained through Content Based Medical Image Retrieval (CBMIR). The CBMIR was implemented to find order effectively retrieve the picture from an enormous database. Deep learning has taken Artificial Intelligence (AI) at an unprecedented rate through revolution and infiltration in the medical field. It has access to vast quantities of information computing energy of effective algorithms of Machine Learning (ML). It enables Artificial Neural Network (ANN) to attain outcomes nearly every Deep Learning (DL) problems. It helps ANN to achieve results everywhere. It is a difficult task to obtain medical images from an anatomically diff dataset. The goal of the research is to automate the medical image recovery scheme that incorporates subject and place probabilities to improve efficiency. It is suggested to integrate the different data or phrases into a DL location model. It is also measuring a fresh metric stance called weighted accuracy (wPrecision). The experiment will be conducted on two big medical image datasets revealing that the suggested technique outperforms current medical imaging technologies in terms of accuracy and mean accuracy. The CBMIR have about 8,000 pictures, the proposed technique will attain excellent precision (nearly 90 percent). The proposed scheme will attain greater precision for the top ten pictures (97.5 percent) as compared to the last CBMIR recovery technologies with 15,000 picture dataset. It will assist doctors with better accuracy in obtaining medical images.
Characterization of Pneumatic Contractor for Softness/Hardness Display

It is important for the softness/hardness presentation of the fingertip to design of the contact part in the softness/hardness presentation device. In this study, we used shape changing airbag by air volume for contact part of the force feedback device. We examined the relationship between the contact area and the air volume for the four air bag structure and evaluated the effectiveness for the softness/hardness presentation. As a result, we found that the elliptical airbag with a single inflated part behaved similarly to the human perception curve and showed satisfactory characteristics for the expression of the contact area.
An Information Flow Modelling Approach for Critical Infrastructure Simulation

Building a realistic environment for simulating cascading effects in critical infrastructures depends heavily on information received from experts, as well as on an accurate representation of processes and assets related to critical infrastructures. The approach introduced in this paper provides the conceptualization and implementation of an information flow model as a foundation for the subsequent development of a multi-layered risk model. The designed models represent both a process view, with the focus on procedures carried out by critical infrastructures, and a more technical object view, by defining objects and parameters representing assets and interactions. Starting with an analysis of relevant threats and affected infrastructures, use case scenarios are prepared in textual form and subsequently evaluated together with critical infrastructure representatives in end-user workshops. Based on the respective use case, a process view is established in form of an activity diagram including information flows, displaying processes of critical infrastructures during a threat. The activity diagram supports the evaluation and collection of information during subsequent end-user workshops with the aim to review and substantiate the model. The object diagram provides technical aspects of the use cases, for supporting the realization of a simulation and a corresponding risk model. The approach was developed in the context of a national research project for analyzing cascading effects in and between critical supply networks. The resulting diagrams demonstrate how cascading effects can be modelled in a structured form to support discussions with and between experts of critical infrastructures and emergency services, and how such models can serve as a foundation for subsequent simulation.
Meningkatkan aktivitas dalam pembelajaran dengan pelatihan pengembangan media pembelajaran

The PKM program is carried out with the method of providing training and guidance to participants regarding the development of instructional media to enhance activities in carrying out learning with the aim of (1) to increase knowledge regarding the development of instructional media, (2) participants can implement the development of instructional media well in the learning process, and (3) participants can disseminate or disseminate knowledge about the development of instructional media. The main target audience for the PKM Program activities are school supervisors, school principals and school teachers in Tinggimoncong sub-district, Gowa district, South Sulawesi province. The results obtained in PKM program activities are increased knowledge and concept of learning media development for PKM program participants, increased learning media development skills in PKM program participants, PKM program participants can make examples and arrange learning media development activities in learning classes, and PKM program participants can implement development of instructional media in learning in schools. Other results obtained were increased motivation of participants in learning material for learning media development and high enthusiasm of participants in disseminating or disseminating PKM program results, especially learning media development material. Outputs of PKM activities are (1) increasing participant's knowledge regarding activity materials, (2) scientific articles published at national seminars, and (3) publications on PKM implementation on online media.
Time management as a way to ensure the psychological safety of a person

The interaction between time management and psychological safety of an individual is considered. It is analyzed which actions can waste time and energy to a greater extent. Time management is an easy-to-understand and effective method for a person to begin to use time constructively and thereby ensure his psychological safety of the individual.
Nonparametric clustering methods to identify latent structures from a sequence of dependent categorical data

Nonparametric clustering methods to identify latent structures from a sequence of dependent categorical data
Round-Optimal Secure Multiparty Computation from Minimal Assumptions

Author(s): Srinivasan, Akshayaram | Advisor(s): Garg, Sanjam | Abstract: Secure Multiparty Computation (MPC) allows a set of parties, each having its own private data, to compute a function of their joint data such that the parties only learn the output of this function and everything else about their data is hidden. MPC is a fundamental cryptographic abstraction that captures many other natural cryptographic primitives as special cases. It also has a wide range of practical applications such as conducting secure electronic auctions, delegating sensitive computation to untrusted cloud service providers, secure computation on genomic data and training machine learning models on private data.A long-standing open problem in this area is to construct MPC protocols that have {\it optimal} (two-round) round complexity under the {\it weakest} possible cryptographic hardness assumptions.We {\it completely resolve} this problem by showing lower bounds and matching upper bounds on the hardness assumptions required for constructing round-optimal MPC. Specifically, we obtain the following results.\begin{itemize}\item \textbf{Black-Box Separation.} We show that there exists no construction of two-round semi-honest MPC protocol for general functions that makes black-box use of a two-round oblivious transfer. As a corollary, a similar separation holds when starting with any 2-party functionality other than oblivious transfer. \item \textbf{Non-Black-Box Construction.} We show that the above negative result can be bypassed by making non-black-box use of a two-round oblivious transfer. Specifically, starting from a semi-honest (resp. malicious) secure two-round oblivious transfer protocol, we construct a two-round MPC protocol against semi-honest (resp. malicious) adversaries. \end{itemize}Since any two-round MPC protocol for general functionalities implies a two-round oblivious transfer as a special case, the above two results show that non-black-box use of oblivious transfer is {\it necessary and sufficient} to construct round-optimal MPC protocols.
BASICS OF ONLINE TEACHING, USAGE AND IMPLEMENTATION PROCESS

Undoubtedly, the positive aspect of online learning social sciences is that you can solve the problem of the lack of qualified teachers in your region. In addition, you have the opportunity to adjust to the work schedule of specialists who will be trained, and take into account their business trips. It should also be noted that the cost of one academic hour of a distance course is usually lower than the cost of one academic hour of a full-time course. However, you should be careful here, because due to technical problems during the remote lesson you can lose up to 40% of the time paid. Efficiency learning a educational depends on the degree of interest students in its study. The article provides a brief analysis of the advantages and disadvantages of this interactive learning method and an example is given tasks and exercises used in the lessons.
A type language for message passing component-based systems.

Component-based development is challenging in a distributed setting, for starters considering programming a task may involve the assembly of loosely-coupled remote components. In order for the task to be fulfilled, the supporting interaction among components should follow a well-defined protocol. In this paper we address a model for message passing component-based systems where components are assembled together with the protocol itself. Components can therefore be independent from the protocol, and reactive to messages in a flexible way. Our contribution is at the level of the type language that allows to capture component behaviour so as to check its compatibility with a protocol. We show the correspondence of component and type behaviours, which entails a progress property for components.
LibGuides: Maps: Map Links

This guide will help you find most of the maps held at the University Libraries and other sources.
Development Of Teaching Materials Electronic Module (E-Module) Based On Android The Subject Of Matriks

The use of the module can help overcome misconception and can help students learn to independently. With the advent of the technology, A printed book slowly eleminated because all the information can be acquired by a smartphone. Resulting in reading interest students declining. It is therefore, needed material of teaching interactive module with easly language undersanable students and packed in the pack interesting, So as to attract students interest in reading. Interactive module will be made based on the android to join the habit of students who obtain information use android. This research aimed at producing and develop materials of teaching electronic module based on the android subject of matriks. The research method used is Research and Development (RnD) that involved seven steps: 1) Need Analysis, 2) Researcher as Developer Capability, 3) Product to be Developed, 4) Concept of the Product, 5) Development of the Product, 6)Experts Judgements, 7) Field Testing in Natural Setting Environment. Expert judgements has been done by Technology Experts, Mathematical Education Experts, and Mathematics Experts, has showed that electronic module is receivable to be tested to the student MAN 2 Cilegon who have studied matriks. Field testing is done by the 15 student got the percentage rating 82,28%. From the result of the field testing, the electronic module are in state of very good category based on student’ assessment.
Possíveis impactos do modelo Records in Contexts para os usuários de arquivos

The International Archives Council is developing the new archival description standard, Records in Contexts (RiC), to meet the current reality of archives, paying particular attention to digital documents. The present work studies the possible impacts to archives users, either people or information systems, caused by the replacement of the current archival description standards by the RiC.Keywords: Records in Contexts; archival description; archives users; conceptual model.
Update on ASTM standards on heavy hard impact testing on fitness flooring

Currently there are two fitness related heavy hard impact standards under development at ASTM. One is a field-based method that uses standard objects of know geometry and mass to generate and vibration that can be measured in 1/3 octave bands. The second is a laboratory-based standard that uses a calibrated drop tower to measure the force pulse, or blocked force, due to an object impacting on the flooring surface. The Institute of Acoustics in the United Kingdom and ASHRAE are both also working on fitness noise related standards as well. This presentation will cover the current state of all of these standards, as well as information as to how to get involved in their development. The author will also share his thoughts on the importance of standards, the current state of standard development and who should get involved.
Adjectives on –i in Japanese language corpora: Distribution, patterns and lexical constraints

This book presents empirical methodologies and insights into the field of spoken and written discourse, in syntax, lexis, in corpus-based research and its applications to Japanese language education, and an exploration of the differences across time and register in diachronic Japanese language corpora. As such, it is divided into four parts, which are presented below with a brief overview of each chapter.
Connection-Adaptive Meta-Learning

Meta-learning enables models to adapt to new environments rapidly with a few training examples. Current gradient-based meta-learning methods concentrate on finding good initialization (meta-weights) for learners, but ignore the impact of neural architectures. In this paper, we aim to obtain better meta-learners by co-optimizing the architecture and meta-weights simultaneously. Existing NAS-based methods apply a two-stage strategy,i.e., first searching architectures and then re-training meta-weights for the searched architecture. However, this two-stage strategy would lead to a suboptimal meta-learner, since the meta-weights are overlooked during searching architectures for meta-learning. Differently, we propose a more efficient and effective method for meta-learning, namely Connection-Adaptive Meta-learning (CAML), which jointly searches architectures and train the meta-weights on consolidated connections. During searching, we consolidate the architecture connections layer by layer, in which the layer with the largest weight value would be fixed first. With searching only once, our CAML is able to obtain both adaptive architecture and meta-weights fo meta-learning. Extensive experiments show that CAML achieves state-of-the-art performance with 130x less computational cost, revealing our method’s effectiveness and efficiency.
Penulisan Artikel Ilmiah Sederhana

This activity is as an attempt to improve the professionalism of  educators that are teachers, principals, and superintendents who followed by 67 participants in Sub District Education of Tahunan-Jepara Regency. This devotion is packaged in the form of a scientific article writing workshop given by 3 persons  for  3  days. This workshop as a of continuous proffessional development, mandated by Permen PAN and RB. Also Regulations of President of Indonesia. During workshop session, paMicipants were enthusiastic to follow this event and hope to have the advanced form of accompaniment activities so that participants are ready to produce ready-scientific article submitted to a scientific journal.
Crypto-Enforcement Around the World

The blockchain revolution in capital and financial markets attracted the attention of enforcement agencies in many jurisdictions. This Article elaborates the results of an international enforcement survey of the Blockchain and Fintech Research Program of the Rutgers Center for Corporate Law and Governance. It provides a detailed analysis of enforcement in major crypto-market jurisdictions. The data suggest that, despite an extended network of agreements facilitating international cooperation, the United States Securities and Exchange Commission (“SEC”) maintains its historically active enforcement posture. The SEC brings more enforcement actions against cryptoasset issuers, broker-dealers, crypto-exchanges, and other digital-asset market participants than most other major crypto-jurisdictions, as well as the United States Commodity Futures Trading Commission. SEC enforcement results in considerably more serious penalties.Our data raise theoretical questions on regulation via enforcement, its effect on financial innovations, and regulatory competition. The U.S. does not have a separate regulation designed for the decentralized ledger technology industry and related financial markets, which effectively creates a pure regulation via enforcement environment. To the extent that the U.S. agencies pursue actions not only against domestic companies but also foreign firms, which raise only part of their capital from United States investors, their actions impact global crypto-markets and raise regulatory competition concerns.