Reviewerly/exHarmony huggingface dataset:
Toward Multilingual Identification of Online Registers

We consider cross- and multilingual text classification approaches to the identification of online registers (genres), i.e. text varieties with specific situational characteristics. Register is the most important predictor of linguistic variation, and register information could improve the potential of online data for many applications. We introduce the first manually annotated non-English corpus of online registers featuring the full range of linguistic variation found online. The data set consists of 2,237 Finnish documents and follows the register taxonomy developed for the Corpus of Online Registers of English (CORE). Using CORE and the newly introduced corpus, we demonstrate the feasibility of cross-lingual register identification using a simple approach based on convolutional neural networks and multilingual word embeddings. We further find that register identification results can be improved through multilingual training even when a substantial number of annotations is available in the target language.
Creativity Support for Story Construction Play Experiences

My research involves the design and development of mixed-initiative AI tools that provide players with creativity support in the context of story construction play experiences, especially those driven by malleable simulations that the player has a chance to help design or configure. To that end, I also study existing storytelling practices within game communities as a way of understanding what a desirable computational creative partner might look like; what features of computational systems tend to facilitate and frustrate creativity in their human partners; and what new creative practices might emerge as we create computational creative partners for new domains.
ANALISIS KEPUASAN PENGGUNA SISTEM INFORMASI E-GOVERNMENT MENGGUNAKAN METODE WEBQUAL 4.0 (STUDI KASUS: WEBSITE SIMSARPRAS KEMENTERIAN AGAMA)

The service of a government institution to the community through an electronic or E-Government based information system needs to be analyzed to the satisfaction of its users, to determine the quality of the information system services, especially if the service is a necessity and is considered important for community development. This study analyzes the quality of a site belonging to the Ministry of Religion, namely the website for information systems and infrastructure (SIMSARPRAS). The study was conducted to determine the quality of the SIMSARPRAS website based on user perceptions. The method used in this research is WebQual 4.0 with data analysis using multiple linear regression. The results of this study provide conclusions that partially and simultaneously all dimensions of the WebQual 4.0 method have a positive and significant effect on user satisfaction from the SIMSARPRAS website. The regression coefficient shows that the dimensions of service interaction quality give the greatest value to user satisfaction with a value of 0.451. The coefficient of determination shows that all WebQual 4.0 dimensions are able to influence user satisfaction by 64.8%, and it is concluded that the quality of SIMSARPRAS websites is in good quality.
Data stewardship on the map : A study of tasks and roles in Dutch research institutes

Good research requires good data stewardship. Data stewardship encompasses all the different tasks and responsibilities that relate to caring for data during the various phases of the whole research life cycle. The basic assumption is that the researcher himself/herself is primarily responsible for all data.2 However, the researcher does need professional support to achieve this. To that end, diverse supportive data stewardship roles and functions have evolved in recent years. Often they have developed over the course of time. Their functional implementation depends largely on their place in the organization. This comes as no surprise when one considers that data stewardship consists of many facets that are traditionally assigned to different departments. Researchers regularly take on data stewardship tasks as well, not only for themselves but also in a wider context for a research group. This data stewardship work often remains unnoticed.
Skeletonographer

Understanding natural human behaviours in-the-wild are highly valued in HCI and CSCW communities. However, it is challenging to collect and analyze the field data due to public privacy. We present Skeletonographer, the tool that supports anonymous digital ethnography studies using skeletonized representations of people. Our system utilizes computer vision techniques to generate and visualize skeletons from video. Users can play back the skeleton data similar to a video player, and apply custom labels for analysis. We applied this tool to our project as a case study, and proved its feasibility to act as an ethnographic research tool.
Put that Hologram there - Probing Mobile Interaction Experiences for a Vision of Mixed Material Public Spaces

Contemporary progress in mobile augmented reality technologies has already introduced novel pervasive displays, such as Microsoft's HoloLens, which allows to display mixed realities containing tangible real and "intangible" holographic objects. In order to allow prototyping and probing such seemingly near-future (urban) interaction experiences, we built a system, which combines a mobile phone with Microsoft's HoloLens and enables exemplary interaction techniques to manipulate "holograms" by combining the capabilities of both these personal and mobile devices. In this paper, we first describe details of this system and then report on a study with 12 participants probing participants' experiences and expectations of a future urban mixed material space. Results of a thematic analysis highlight a two-sided view, in which despite some "fears" of radical change, which may cause a disparity of what (materials) matter more, participants demonstrated a desire to benefit from material complementarity.
Understanding Data in the Blink of an Eye

Many data analysis and knowledge mining tasks require a basic understanding of the content of a dataset prior to any data access. In this demo, we showcase how data descriptions---a set of compact, readable and insightful formulas of boolean predicates---can be used to guide users in understanding datasets. Finding the best description for a dataset is, unfortunately, both computationally hard and task-specific. This demo shows that not only we can generate descriptions at interactive speed, but also that diverse user needs---from anomaly detection to data exploration---can be accommodated through a user-driven process exploiting dynamic programming in concert with a set of heuristics.
Il Perfetto Composto negli <i>Atti del podestà</i> di Lio Mazor: condizioni testuali e diacronia

This short essay deals with the analysis of verb tenses’ functions in the language variety testified by the Atti del podestà di Lio Mazor. It is a series of judicial documents written at the beginning of the 14th century in a small village in the Venice Lagoon. They show an archaic state of language, in which the Simple Past is still productive, while nowadays in Northern Italy it has disappeared from the varieties spoken in the area, that use only the Present Perfect. In the 1980s, some typological studies on Romance languages identified in the expansion of the semantic functions related to the Present Perfect a diachronic process named aoristic drift. In this paper, we analyze the linguistic distribution between Present Perfect and Simple Past showed by the Atti in the light of the aoristic drift’s theory. We also integrate this theoric background by applying a refined textual analysis to the documents. The combination of linguistic theory and text analysis to investigate ancient language varieties is the innovative element of the present work, with respect to the traditional studies about aoristic drift.
Leadership and Performance of the Software Development Team: Influence of the Type of Project Management

Purpose -The objective of this article is to identify the influence of the type of leadership on the performance of the project team, according to the methods applied in the management of software development projects.Design/methodology/approach -We used a quantitative method, applying a survey to project practitioners in software development teams.The sample consisted of 245 valid answers, divided into traditional and non-traditional methods.The responses were analyzed through structural equation modeling using a confirmatory methodological approach.Findings -We identified that the three styles of leadership evaluated (transactional, transformational, and empowering) are positively related to team performance, as already identified in previous studies.However, the project management method does not influence the relationship between leadership and team performance.Originality/value -The theoretical and practical contribution of this article is the finding that the type of project management used in software development (agile or traditional method) is not relevant to the choice of team leader, emphasizing that the important thing is the investment in the development of this leadership, as a measure to increase team performance, allowing flexibility in the performance of managers.
Quantum Period Finding is Compression Robust

We study quantum period finding algorithms such as Simon and Shor (and its variant Ekerå-Håstad). For a periodic function f these algorithms produce – via some quantum embedding of f – a quantum superposition ∑x |x〉 |f(x)〉, which requires a certain amount of output qubits that represent |f(x)〉. We show that one can lower this amount to a single output qubit by hashing f down to a single bit in an oracle setting.Namely, we replace the embedding of f in quantum period finding circuits by oracle access to several embeddings of hashed versions of f. We show that on expectation this modification only doubles the required amount of quantum measurements, while significantly reducing the total number of qubits. For example, for Simon’s algorithm that finds periods in f : Fn2 → Fn2 our hashing technique reduces the required output qubits from n down to 1, and therefore the total amount of qubits from 2n to n + 1. We also show that Simon’s algorithm admits real world applications with only n + 1 qubits by giving a concrete realization of a hashed version of the cryptographic Even-Mansour construction. Moreover, for a variant of Simon’s algorithm on Even-Mansour that requires only classical queries to Even-Mansour we save a factor of (roughly) 4 in the qubits.Our oracle-based hashed version of the Ekerå-Håstad algorithm for factoring n-bit RSA reduces the required qubits from (3/2 + o(1))n down to (1/2+ o(1))n.
DETERMINATION OF WHITE BLOOD CELLS USING FOLDSCOPE WITH SMARTPHONE

We are traditionally used Microscope in clinical laboratory for determination of white blood cells of human blood smear. Now, in this study we were used Foldscope with Smartphone in the place of Microscope and examine many samples of human blood smear which was collected from local diagnostic centers. We were very easily quantity &amp; morphology analysis of all types of WBC cells such as Neutrophils, Lymphocytes, Monocytes, Eosionophils, Basophils in blood smear with the help of Foldscope &amp; image taken by Smartphone. The main objective of this study is to use Foldscope for quantity &amp; morphology analysis of human WBCs at field level especially poor resource area where healthcare services or centers is not available &amp; where carry of microscope is not possible.
Formation of Media Competence of Future Teachers by Means of ICT and Mobile Technologies

The paper is devoted to the problem of formation of media competence of future teachers by means of ICT and mobile technologies. It discusses the concepts of media competence, media education and media culture. Motivational, cognitive, technological, reflective components within the structure of media competence are revealed in the article. The results of experimental work of formation of media competence of future teachers by means of ICT and mobile learning technologies are presented. The authors conclude that study of modern methodological and technological methods of media education, history of their emergence and development, creative use within the educational process opens new perspectives for the application of the educational and developmental potential of media education at school and universities.
ALERT: Accurate Anytime Learning for Energy and Timeliness

An increasing number of software applications incorporate runtime Deep Neural Networks (DNNs) to process sensor data and return inference results to humans. Effective deployment of DNNs in these interactive scenarios requires meeting latency and accuracy constraints while minimizing energy, a problem exacerbated by common system dynamics. Prior approaches handle dynamics through either (1) system-oblivious DNN adaptation, which adjusts DNN latency/accuracy tradeoffs, or (2) application-oblivious system adaptation, which adjusts resources to change latency/energy tradeoffs. In contrast, this paper improves on the state-of-the-art by coordinating application- and system-level adaptation. ALERT, our runtime scheduler, uses a probabilistic model to detect environmental volatility and then simultaneously select both a DNN and a system resource configuration to meet latency, accuracy, and energy constraints. We evaluate ALERT on CPU and GPU platforms for image and speech tasks in dynamic environments. ALERT's holistic approach achieves more than 13% energy reduction, and 27% error reduction over prior approaches that adapt solely at the application or system level. Furthermore, ALERT incurs only 3% more energy consumption and 2% higher DNN-inference error than an oracle scheme with perfect application and system knowledge.
A Privacy-Preserving Method Based on Server-Aided Reverse Oblivious Transfer Protocol in MCS

With the popularity of the smart phones embedded in a large number of sensors, mobile crowd sensing (MCS) applications have developed rapidly. These applications often require the participants to collect the location-related data. However, this process faces the risk of the privacy leakage. The existing anonymous and cloaking methods can still analyze the user’s identity and sensing locations by obtaining enough data with spatiotemporal correlation. In addition, the existing encryption methods not only take a lot of computation cost but also need to assume a full trusted sensing platform. In order to preserve the users’ privacy, we need to separate the user’s true identity and the sensing location. We propose a privacy-preserving method based on server-aided (or cloud-assisted) reverse oblivious transfer (ROT) protocol containing a cloud server which can compute the results of the encrypted sensing data to avoid the full trust in the sensing platform and enhance the computing efficiency in MCS. It overcomes the derivation of the malicious users in the standard malicious model through constructing the coefficients of the polynomial. Finally, the analysis demonstrates that the proposed method possesses the most efficient computing time, communication overhead and storage overhead comparing with other methods and can achieve the quality-privacy tradeoff optimization.
Three-photon polarized entanglement and interference generated using six-wave mixing and polarized dressing atomic coherence control

In a spontaneous process, laser-polarized dressings produce characteristic triphoton waveforms regarding the oscillation period and coherence time. Correspondingly, circularly polarized dressings make it have longer oscillation periods compared to the effect of linearly polarized dressings attributed to dispersion relation changes, and shorter coherence times owing to the larger dressing field. Given that the optical response of the polarization state of incident light is the dressing field, we can control the averaged three-photon coincidence count rate by adjusting the polarization of the incident light. By performing quantum tomography, we can obtain W and W-like polarization entanglement states. Accordingly, strong and weak visibilities can be evoked for circularly and linearly polarized dressings.
International Workshop on Model Selection and Parameter Tuning in Recommender Systems

Recommender systems have strongly attracted the attention of the machine learning research community with prosperous real-life deployments in the last few decades. The performance and success of most applications developed in this domain highly depend on an elaborate selection of models and configuration of their hyperparameters. The international MoST-Rec 2019 workshop addresses the issues of algorithm selection and parameter tuning for recommender systems. The workshop aims to bring together researchers from the model selection and hyperparameter tuning community in the general scope of machine learning with researchers from the recommender systems community for discussing and exchanging recent advances and open challenges in the field.
Role of Different Integer Virtual Machine in Cloud Data Center

In modern data centres of cloud computing contains virtualization system. In order to improve network stability, energy efficiency, and makespan proper virtualization need. The virtual machine is one of the examples of virtualizations. Cloud computing data centres consist of millions of virtual machine to manage load balancing. In this study check the different number of virtual machine role in data centres, for that purpose, we established a network with the help of cloudsim and compare different data centres at each zones taking a different number of the virtual machine with different paramater and network banwith.After the simulation the result shows that increasning in the number of VM can affect the netwok accuracy in term of energy ,processing time ,coast and network stabality .Â
Multilingual Model Using Cross-Task Embedding Projection

We present a method for applying a neural network trained on one (resource-rich) language for a given task to other (resource-poor) languages.We accomplish this by inducing a mapping from pre-trained cross-lingual word embeddings to the embedding layer of the neural network trained on the resource-rich language.To perform element-wise cross-task embedding projection, we invent locally linear mapping which assumes and preserves the local topology across the semantic spaces before and after the projection.Experimental results on topic classification task and sentiment analysis task showed that the fully task-specific multilingual model obtained using our method outperformed the existing multilingual models with embedding layers fixed to pre-trained cross-lingual word embeddings. 1
Tutorial: Deploying Secure Multi-Party Computation on the Web Using JIFF

Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. This tutorial is open to anyone interested in learning how to build and deploy secure multi-party computation within the context of a web application. All levels of experience are welcome. Since the tutorial entails writing code in JavaScript and Node.js, audience members should at a minimum have familiarity with JavaScript.
Proving partial-correctness and invariance properties of transition-system models

We propose an approach for proving partial-correctness and invariance properties of transition systems, and illustrate it on a model of a security hypervisor. Regarding partial correctness, we generalise the recently introduced formalism of Reachability Logic, currently used as a language-parametric logic for programs, to transition systems. We propose a coinductive proof system for the resulting logic, which can be seen as performing an “infinite symbolic execution” of the transition-system model under verification. We embed the proof system in the Coq proof assistant and formally prove its soundness and completeness. The soundness result provides us with a Coq-certified Reachability-Logic prover for transition-system models. The completeness result, although more theoretical in nature, also has a practical value, as it suggests a proof strategy that is able to deal with all valid formulas on a given transition system. The complete proof strategy reduces partial correctness to invariance. For the latter we propose an incremental verification technique for dealing with the case-explosion problem that is known to affect it. All these combined techniques were instrumental in enabling us to prove, within reasonable time and effort limits, that the nontrivial algorithm implemented in a simple hypervisor that we designed in earlier work meets its expected functional requirements.
Distant Supervised Relation Extraction with Separate Head-Tail CNN

Distant supervised relation extraction is an efficient and effective strategy to find relations between entities in texts.However, it inevitably suffers from mislabeling problem and the noisy data will hinder the performance.In this paper, we propose the Separate Head-Tail Convolution Neural Network (SHTCNN), a novel neural relation extraction framework to alleviate this issue.In this method, we apply separate convolution and pooling to the head and tail entity respectively for extracting better semantic features of sentences, and coarseto-fine strategy to filter out instances which do not have actual relations in order to alleviate noisy data issues.Experiments on a widely used dataset show that our model achieves significant and consistent improvements in relation extraction compared to statistical and vanilla CNN-based methods.