Reviewerly/exHarmony huggingface dataset:
On improving the indexing of information systems based on web technologies

The article describes the approach to the modernization of information systems based on Web-technologies with the aim to improve their indexing by search engines, to increase the interconnection of such systems content, improving GUI in terms of interaction with social services and networks. The most important metrics for statistical data collection systems are described. The set of criteria to evaluate the work of SEO specialists is given.
Keystroke Dynamics Authentication Using Small Datasets

Keystroke dynamics is the analysis of timing information which describes exactly when each key was pressed or released by a user while typing. There have been various attempts to use this timing information to identify user’s typing pattern and authenticate the user in a system, but mostly from a research perspective. We present a new methodology which focuses on solving the practical problems associated with deploying a keystroke dynamics authentication system. In our proposed methodology, a user’s keystroke features are separated into two sets, namely high frequency and low frequency, based on the fraction of the total typing time the key takes. These two feature sets are then trained using OneClassSVM classifiers. Also, our proposed methodology requires minimal data and it is easily deployable on any computer.
Model Comparison for Semantic Grouping

We introduce a probabilistic framework for quantifying the semantic similarity between two groups of embeddings. We formulate the task of semantic similarity as a model comparison task in which we contrast a generative model which jointly models two sentences versus one that does not. We illustrate how this framework can be used for the Semantic Textual Similarity tasks using clear assumptions about how the embeddings of words are generated. We apply model comparison that utilises information criteria to address some of the shortcomings of Bayesian model comparison, whilst still penalising model complexity. We achieve competitive results by applying the proposed framework with an appropriate choice of likelihood on the STS datasets.
Family-Centered Exploration of the Benefits and Burdens of Digital Home Assistants

Parents receive conflicting information on the benefits and burdens of children's technology use, especially novel technologies such as digital home assistants. To understand parents' views, we analyzed relevant Amazon Echo device product reviews posted to Amazon.com, and deployed a User Benefit and Burden Survey to 131 parents on Amazon Mechanical Turk to explore their perspectives of Amazon Echo digital home assistants. Our work explores parents' perceptions of the devices with regards to their children and families, in terms of attributes such as benefits and burdens. This study contributes an empirical, family-centered understanding of and design opportunities for whole home personal assistants in support of a diversity of families.
Designing for the Self

I investigate how individuals can employ human centered design techniques to adopt positive behaviors in their everyday life. I have designed and built a tool that supports individuals in planning physical activity using design processes such as understanding other people's behavioral needs, ideating behavioral interventions and prototyping behavioral solutions using evidence-based techniques. In my dissertation I will demonstrate how tools can support iterative behavioral design by evaluating behavioral solutions, drawing insights from testing, and making iterations to a behavioral solution. This work will result in new tools and design methods that enable people to adapt evidence-based techniques in a way that fits with their everyday needs.
Multilayer Perceptron for Activity Recognition Using a Batteryless Wearable Sensor

Smart City is one of the trends around the world today. In order to achieve a smart city environment, we need everything to be connected and to be managed. As one of the aspects that have strong impact on people life is their own activities, a smart city should be accompanied by smart people which could be actualized by using sensors to recognize their activities. In this research, we present and evaluate a method to recognize the gesture of someone leaving bed using RFID device. We use a classification approach in our system to conduct the experiment. The method that we are using is MLP (Multi-Layer Perceptron). By using this method, we got 90.17% of accuracy, which is slightly better than Naive Bayesian that got 84.46% of accuracy.
Opportunities for In-Home Augmented Reality Guidance

The use of Augmented Reality (AR) systems has been shown to be beneficial in guiding users through structured tasks when compared to traditional 2D instructions. In this work, we begin to examine the potential of such systems for home improvement tasks, which present some specific challenges (e.g., operating at both large and small scales, and coping with the diversity in home environments). Specifically, we investigate user performance of a common low-level task in this domain. We conducted a user study where participants mark points on a planar surface (as if to place a nail, or measure from) guided only by virtual cues. We observed that participants position themselves so as to minimize parallax by kneeling, leaning, or side-stepping, and when doing so, they are able to mark points with a high degree of accuracy. In cases where the targets fall above one's line of vision, participants are less able to compensate and make larger errors. We discuss initial insights from these observations and participant feedback, and present the first set of challenges that we believe designers and developers will face in this domain.
Real-Time Kinodynamic Motion Planning for Omnidirectional Mobile Robot Soccer using Rapidly-Exploring Random Tree in Dynamic Environment with Moving Obstacles.

RoboCup Middle Size League (RoboCup MSL) provides a standardized testbed for research on mobile robot navigation, multi-robot cooperation, communication and integration via robot soccer competition in which the environment is highly dynamic and adversarial. One of important research topic in such area is kinodynamic motion planning that plan the trajectory of the robot while avoiding obstacles and obeying its dynamics. Kinodynamic motion planning for omnidirectional robot based on kinodynamic-RRT* method is presented in this work. Trajectory tracking control to execute the planned trajectory is also considered in this work. Robot motion planning in translational and rotational direction are decoupled. Then we implemented kinodynamic-RRT* with double integrator model to plan the translational trajectory. The rotational trajectory is generated using minimum-time trajectory generator satisfying velocity and acceleration constraints. The planned trajectory is then tracked using PI-Control. To address changing environment, we developed concurrent sofware module for motion planning and trajectory tracking. The resulting system were applied and tested using RoboCup simulation system based on Robot Operating System (ROS). The simulation results that the motion planning system are able to generate collision-free trajectory and the trajectory tracking system are able to follow the generated trajectory. It is also shown that in highly dynamic environment the online scheme are able to re-plan the trajectory.
Spatially Constrained Generative Adversarial Networks for Conditional Image Generation

Image generation has raised tremendous attention in both academic and industrial areas, especially for the conditional and target-oriented image generation, such as criminal portrait and fashion design. Although the current studies have achieved preliminary results along this direction, they always focus on class labels as the condition where spatial contents are randomly generated from latent vectors. Edge details are usually blurred since spatial information is difficult to preserve. In light of this, we propose a novel Spatially Constrained Generative Adversarial Network (SCGAN), which decouples the spatial constraints from the latent vector and makes these constraints feasible as additional controllable signals. To enhance the spatial controllability, a generator network is specially designed to take a semantic segmentation, a latent vector and an attribute-level label as inputs step by step. Besides, a segmentor network is constructed to impose spatial constraints on the generator. Experimentally, we provide both visual and quantitative results on CelebA and DeepFashion datasets, and demonstrate that the proposed SCGAN is very effective in controlling the spatial contents as well as generating high-quality images.
Modify Data with Advanced DML

Now that we learned how to write advanced SQL statements to retrieve data, it is time to learn how to write advanced SQL statements to change data. Oracle Data Manipulation Language (DML) lets us insert, update, and delete data.
Outlier Detection Technique for IoT Sensor-Driven Big Data Systems

With the development of big data analysis technologies and the utilization of sensor data through Internet of Things (IoT) and wireless sensor networks (WSNs), users can easily analyze and use huge amounts of data. However, occasional sensor errors can lead to failures in maintaining optimum conditions, and also smart systems without user intervention are likely to be vulnerable to intrusions via external networks. Therefore, in this paper, a method to maintain the optimal state is proposed even when the sensor network fails due to sensor failure or external intrusion in big data systems.
Machine Learning in Geoscience: Riding a Wave of Progress

2nd Annual Machine Learning in Solid Earth Geoscience Conference; Santa Fe, New Mexico, 18–22 March 2019
A Gigapixel Image Browsing Scheme in Edge Computing Environment

Gigapixel images have drawn many attentions recently as it can supply ultra-high-definition visual experience, however the strict requirements for user’s terminal to display makes the gigapixel image difficult to enter people’s daily life. Aiming at this problem, we proposed a novel picture browsing scheme under the edge-computing environment. By receiving the control command from users’ terminal, the edge server corresponds the instruction to generate the current field of view (FOV) which needed to be transmitted back to the terminal. Two ways to generate the FOV including block-based image stitching with super resolution reconstruction and quasi video coding are proposed in this paper. Experimental results showed the performances of the two ways on the compression rate and interaction delay, meantime analyzed the relative merits of each way.
Application of Extreme Learning Machine to Visual Diagnosis of Rapeseed Nutrient Deficiency

The nondestructive and accurate diagnosis of nutrient deficiency is the key to the adoption of appropriate remedial measures in agriculture. This paper proposes an intelligent visual diagnosis technique for the diagnosis of nutrient deficiency in rapeseed based on the leaf features. To this end, the experimental image library of four types of deficiencies was established, including normal, nitrogen deficiency, phosphorus deficiency and kalium deficiency. First, through employing the GrabCut algorithms, an image with remarkable features was divided into the foreground and background images. Then, the foreground one was employed to extract color, texture and shape features using the average grayscale and color moments in R/G/B and H/I channels, grayscale co-occurrence matrix and wavelet moments, respectively. Second, the initial features were normalized and filtered based on the gain for recognition rate so as to reduce their dimensions for improving the speed and accuracy of the diagnosis. Finally, the core features were imported into the extreme learning machine and the diagnosis of the input rapeseed leaf image could be accomplished. The experimental results showed that the proposed method could accurately identify the common nutrient deficiency, which sets a good example for the diagnosis technique of nutrient deficiency based on image analysis.
Controlling astroturfing on the internet: a survey on detection techniques and research challenges

Astroturfing is one of the most impactful threats on today's internet. It is the process of masking and portraying a doctored message to the general population in a way as though it originated from the grass-root level. The concept of astroturfing detection is started to gain popularity among researchers in social media, e-commerce and politics. With the recent growth of crowdsourcing systems, astroturfing is also creating a profound impact on people's opinions. Political blogs, news portals and review websites are being flooded with astroturfs. Some groups are using astroturfing to promote their interest and some are using it to demote the interest of competitors. Researchers have adopted many approaches to detect astroturfing on the web. These approaches include content analysis techniques, individual and group identification techniques, analysing linguistic features, authorship attribution techniques, machine learning and so on. We present a taxonomy of these approaches based on the key issues in online astroturfing detection techniques and discuss the relevant approaches in each category. The paper also summarises the discussed literature and highlights research challenges and directions for future work that have not aligned with the currently available research.
Quantum Information Processing with Frequency-Bin Qubits: Progress, Status, and Challenges

Frequency-bin encoding has emerged as a promising approach for fiber- and chip-compatible quantum information processing. We overview the basic theory and experiments, as well as offer perspectives on opportunities for continued advances.
Learning Description Logic Axioms from Discrete Probability Distributions over Description Graphs

Description logics in their standard setting only allow for representing and reasoning with crisp knowledge without any degree of uncertainty. Of course, this is a serious shortcoming for use cases where it is impossible to perfectly determine the truth of a statement. For resolving this expressivity restriction, probabilistic variants of description logics have been introduced. Their model-theoretic semantics is built upon so-called probabilistic interpretations, that is, families of directed graphs the vertices and edges of which are labeled and for which there exists a probability measure on this graph family. Results of scientific experiments, e.g., in medicine, psychology, or biology, that are repeated several times can induce probabilistic interpretations in a natural way. In this document, we shall develop a suitable axiomatization technique for deducing terminological knowledge from the assertional data given in such probabilistic interpretations. More specifically, we consider a probabilistic variant of the description logic $$\mathcal {E\!L}^{\!\bot }$$ , and provide a method for constructing a set of rules, so-called concept inclusions, from probabilistic interpretations in a sound and complete manner.
Optimization of Models of Quantum Computers Using Low-Level Quantum Schemes and Variability of Cores and Nodes

Basic concepts in the field of quantum information such as quantum circuits, logic gates and qubits were identified and analyzed in the present paper. It provides a basis for the development of several concepts (line, node, interaction of qubits and their neighborhood) of the theoretical and practical components of low-level random quantum circuits. Also, various optimizations, regulated by quantitative correlations of cores (one or several cores) and nodes (one or several), are derived. It can be used to implement simulation of a multi-node quantum circuit. Despite the fact that the theory of quantum computation is not yet ready for a conversion from theory to practice, one can imagine a possible form of the future quantum computer and its interface. In addition, it is proved that most non-trivial tasks cannot be solved without the use of entanglement. Recently there has been a rapid growth of interest in quantum computers, especially after the sale of operating quantum computers. The main advantage of quantum computation in comparison with traditional calculations is that they use the property of quantum particles to be simultaneously in many states, which is called superposition. The use of quantum computers can significantly increase the speed of solving computational problems and, most importantly, exponentially increase the speed of NP-complete problems solving, which can be solved for unacceptable time on classic computers.
Unified Generator-Classifier for Efficient Zero-Shot Learning.

Generative models have achieved state-of-the-art performance for the zero-shot learning problem, but they require re-training the classifier every time a new object category is encountered. The traditional semantic embedding approaches, though very elegant, usually do not perform at par with their generative counterparts. In this work, we propose an unified framework termed GenClass, which integrates the generator with the classifier for efficient zero-shot learning, thus combining the representative power of the generative approaches and the elegance of the embedding approaches. End-to-end training of the unified framework not only eliminates the requirement of additional classifier for new object categories as in the generative approaches, but also facilitates the generation of more discriminative and useful features. Extensive evaluation on three standard zero-shot object classification datasets, namely AWA, CUB and SUN shows the effectiveness of the proposed approach. The approach without any modification, also gives state-of-the-art performance for zero-shot action classification, thus showing its generalizability to other domains.
PENGEMBANGAN MOBILE EDUGAME MATEMATIKA UNTUK MENINGKATKAN KEMAMPUAN ARITMATIKA DASAR SISWA SD KELAS 4 DAN 5

The lack of attention to basic arithmetic calculation mastery intuitively causes count stuttering to be found among elementary school students. Counting stuttering is a slow counting condition. To overcome this calculating stutter, one of the instruments that can be used is the Test of Second Mathematics. TOSM is an instrument of Secondary Mathematics in the form of a measuring sheet intended to increase the basic arithmetic calculation speed. In addition to the printed version (written), TOSM has also been created in the mobile application version. However, due to visual limitations, both written TOSM and applications make students gradually become bored and bored. Seeing the popularity of mobile games and the ease of getting them, TOSM will be adopted into mobile edugame with a more attractive visual style. Through the game approach, students will not be aware of doing TOSM. The results of mobile edugame design show that students feel more comfortable and relaxed when working on TOSM in the form of edugame. The adoption of TOSM into edugame provides an entertainment aspect without leaving the initial goal of edugame design, namely as a media to learn basic arithmetic intuitively.
Library in 3D virtual world: a critical review

Purpose The purpose of the present study is to explore the possibility of introducing a 3D environment in the library by reviewing current literature and to provide a good understanding of different purposes of using this immersive environment. Design/methodology/approach The present paper is a narrative account of libraries’ presence in the virtual world in combination with an overview of how libraries respond to the 3D environment. Relevant data for the review paper have been collected from library websites, books, journal articles, interview, etc. Findings The study found purposive involvement of libraries in this immersive environment which indicates that users use this exciting 3D medium to satisfy their information requirement. Research limitations/implications The paper basically considers publications containing observations of broader research community in the relevant field and contents in websites dealing with virtual world and outlines the major features as discussed in available documents. The review study infers that the implementation of 3D project in libraries requires a mindset for the specific approach, from the end of both librarians and users, together with involvement of funds. Therefore, a library may start with a beta project and observe the effectiveness from the users’ perspective before embarking on a full-fledged project. Originality/value With numerous examples, as evident from publications and websites, the current review study makes an attempt to improve the understanding of librarians towards informed selection of projected purposes to be integrated with the virtual world from library perspective. The study also presents different approaches of libraries motivating users in the virtual world that other libraries may follow while considering their 3D library project.
A construction for clique-free pseudorandom graphs

A construction of Alon and Krivelevich gives highly pseudorandom $K_k$-free graphs on $n$ vertices with edge density equal to $\Theta(n^{-1/(k -2)})$. In this short note we improve their result by constructing an infinite family of highly pseudorandom $K_k$-free graphs with a higher edge density of $\Theta(n^{-1/(k - 1)})$.
Traditional Values of Criminal Procedure in Terms of IT Development

This chapter is devoted to the study of the main lines of IT development in criminal procedure. The purpose of the study is to reveal possible threats to traditional values, as well as to show to what extent information technologies can change the current system of the criminal proceeding. The chapter applies a method of system and complex analysis as well as comparative-law one.
Novel method to forecast software aging problems

As software system becomes complex and large, some phenomena, performance degradation, error service, and even the abrupt system outage, have been found in the operating system, web server, and even in the security system. These phenomena can be called software ageing problems. In order to make software re-enter into a robust state, some prediction methods need be used to find an optimal time to do rejuvenation. Since the prediction method used now is linear or non-linear, a hybrid method is proposed in this work to improve the prediction accuracy. The proposed method contains three phases. Firstly, a linear method is applied to capture the linear characteristics of resource consumption series. Secondly, a non-linear method is used to fit non-linear features in the original data and residual data. Finally, the characteristic of the linear and non-linear part will be fitted by a non-linear model. In the experiments, the results show that the proposed method outperforms the other two single models.
The Cataloging of Self-Published Items

This article presents the results of a 2015 survey of librarians who catalog self-published items. The survey was conducted in response to the growing popularity of self-publishing and the increasing prevalence of self-published items in libraries. Survey respondents were asked to describe how they are cataloging these items and to provide representative examples of the records they have created. An analysis of both the survey responses and the records is presented, followed by suggestions for best practices for cataloging these items.