Reviewerly/exHarmony huggingface dataset:
Intermodal Improvement: Nudging Users to Use Keyboard Shortcuts

Keyboard shortcuts have been proven to be the most efficient method of issuing commands in computer software. Using the mouse in graphical user interfaces provides an intuitive but slow method for executing functions in a software. Many fail to make the transition to faster modalities, such as keyboard shortcuts. This is not just the case for novices, but also users with years of experience. This study examines the research on this behavior, as well as how the concepts of nudging and ambient suggestion can be used to actively encourage and support the usage of keyboard shortcuts. Based on this research, a design is proposed and implemented in a simple word processor application. A user experience evaluation was done, by having participants perform writing and formatting tasks inside the application. Using the Microsoft Reaction Card Method followed by a semi-structured interview, the users elaborated on their experience. In the interviews topics and questions of motivation, distraction, and annoyance were raised. The results showed that most participants found the system convenient and helpful in learning shortcuts without being too obtrusive. There are promising first indications of it having potential in promoting the usage of keyboard shortcuts, however further research is required in order to make any generalizations.
Docker: containerize your application

This chapter is primarily dedicated to Docker, the popular containerization environment. In the first half of this chapter, we explain the advantages and disadvantages of containers compared to virtual machines. This discussion is complemented by an introduction to the orchestration of large container clusters using Kubernetes and Docker Swarm. The second part consists of a detailed tutorial and hands-on example detailing how to containerize an application in Docker from scratch.
Intelligent and Innovative Product Design and Application

Since the development of artificial intelligence, how to find a mechanism to detect the interactive relationship between people and objects, and provide a better user experience and product design through the understanding of users, has always been the future of innovative design. Things, how to make people's emotions and design can be further combined through a good use mechanism and operation method, so that the use of the product is a kind of enjoyment, rather than a simple task completion, is the next development in the development of AI artificial intelligence. Important thinking, this research will explore the relationship between a person and the product through the real development process of a product, and look forward to providing a reference for the design and development of innovative products in the future.
Spectator Experience Design for AR Sport Events from a Service Design Perspective – Using HADO as an Example

Augmented reality (AR) has been used to improve spectator experience in traditional sport events. For the first AR sport in the world, Meleap's HADO, the discussion of spectator experience is lacking. To understand the problems in the spectator experience of AR sports, we have conducted a two-phase investigation into HADO match. The first phase investigated HADO's live sports events, while the second phase examined their online sports events. We conducted an integrated analysis based on the quantitative and qualitative results to determine how to optimize HADO's spectator experience. To help designers and researchers of AR sports in the future, we summarized challenges and issues found in spectator experience within integrated AR sport. Moreover, six interdisciplinary designers were invited to a co-creation workshop to identify related design concepts. These concepts were further provided to and discussed with stakeholders from Meleap. Finally, we suggested building digital channel tools in AR sports events to connect online and offline spectator. or even establish a link between the event and the spectator for better user experience.
Tracking of small infrared targets based on convolutional neural network

Abstract As an important application of computer vision, visual tracking has been studied more and more. However, there are still many problems to be solved for infrared target detection, especially for weak infrared target detection and tracking. In addition, convolutional neural networks are widely used in visual applications such as target detection, recognition, and tracking. Therefore, in this paper, an infrared weak target detection and tracking method is designed. Based on the criteria of visual saliency, the real target can estimate by calculating the Euclidean distance between the target and its neighbours. The detected position of the target is sent to a fully convolutional siamese network DeepCF for tracking. As we know, the factors such as lighting changes, scale changes and occlusion cause the tracking failure. Therefore, a tracking confidence T is proposed to judge whether the target is lost. The motion trajectory of the target is continuously estimated if it is lost. The experimental results show that the above method can effectively detect and track infrared weak targets.
Method of rock mass quality classification in ancient underground engineering based on three-parameter interval grey number

Abstract Rock mass quality classification is an important basis for long-term protection and tourism development of ancient underground engineering, however, the existing rock mass quality classification methods are difficult to apply to the special project of ancient underground engineering. Based on the in-depth analysis of the characteristics of ancient underground engineering and the influencing factors of rock mass quality, an evaluation index system for rock mass quality classification of ancient underground engineering is established by taking the long-term tensile strength of rock and the weathering velocity of rock mass as indicators. Secondly, for the evaluation index value has the character of bounded-but-unknown uncertainty, and in order to avoid information loss in interval numbers, the three-parameter interval grey number theory is introduced, based on the concept of three-parameter interval grey number distance measure, a rock mass quality classification calculation model for ancient underground engineering is established. Then, because of the complexity of ancient underground engineering, the idea of group decision-making is introduced, and based on the variation coefficient method, the weight calculation method of evaluation index is established to improve the reliability of weight calculation. Finally, a rock mass quality classification method for ancient underground engineering based on three-parameter interval grey number is established. The method is used to analysis the practical engineering, it shows that the method proposed here is feasible and reasonable.
Towards an Ambient Intelligent Environment for Multimodal Human Computer Interactions

Recent years have seen an explosion in the academic and commercial applications of digital assistants. These technologies have become increasingly prolific, and their use has resulted in fairly rigid and standardized techniques for achieving a desired result. Whether this includes physical actions, or direct voice queries to the system via pre-defined wake words and queries, there is a stark boundary between the human and the system. We aim to explore a shift in the paradigm of these current implementations, to that of an Ambient Intelligent (AmI) environment in which users can interface with the system in a more natural, seamless, and multi-modal manner. Applications of this type of technology range from assisted living, to smart conference rooms and meeting spaces. In this paper we introduce an architectural framework for building an ambient intelligent platform using a combination of video and audio sensors to capture and process the data in a given area of interest.
Smells as an Interactive Material for Spatial Designing

This paper explores design strategies to use smells as a medium of interaction between the body and the space. In a living environment, encounters and experience of smells creates and manifests connections to the space. Along with the other sensory stimuli, smells communicates information about the space. Olfactory interactions can be expressed through its experiential relationship with the body. Design examples as discussed in this paper, express the aesthetics of interaction with smells that are dynamic and temporal. Human perception connects through the patterns and weave the fluid movements across the soft boundaries of smells. Over a range from discrete to ambient presence of smells, this paper discusses tangible and intangible interaction with smells in the design examples. Through active or passive actuation of smells, designing for smell diversity in a living environment would create interactions at many different levels and will add to experiencing spaces in a multisensorial way.
The Use of Digital Technologies and the Transformation of Work in a Hemodialysis Clinic

This study aimed to identify how technology transforms the work of hemodialysis nurses. The methodology was field research with a qualitative approach using the analysis of the subject’s speech. Eleven questionnaires were administered to nurses working in hemodialysis clinics in the city of São Paulo, Brazil. The results pointed out that technology evolution gives conflicting expectations to the nurses that can be positive and negative. A positive expectation is the hope of enhancing care through the improvement of the contact nurse-patient. However, they also fear that technology causes dependence and expertise loss.
The Impact of Foursquare Checkins on Users’ Emotions on Twitter

Performing observational studies based on social network content has recently gained attraction where the impact of various types of interruptions has been studied on users’ behavior. There has been recent work that have focused on how online social network behavior and activity can impact users’ offline behavior. In this paper, we study the inverse where we focus on whether users’ offline behavior captured through their check-ins at different venues on Foursquare can impact users’ online emotion expression as depicted in their tweets. We show that users’ offline activity can impact users’ online emotions; however, the type of activity determines the extent to which a user’s emotions will be impacted.
A Vision-based Measurement System for Semi-Finished Cylindrical Geometries

This work describes a vision-based system for measuring the dimensions of a semi-finished cylinder in open forging, as a function of the rotation angle, in near real-time conditions. To evaluate the performance of the system, we designed a laboratory setup consisting of patterned cylinder at room temperature, with a diameter of approximately 70 mm that can rotate around a horizontal axis. A single camera observes the rotating cylinder and detects simultaneously the diameter and the rotation angle. Images were acquired with different resolutions, as well as at different distances from the cylinder. The tests have shown that, at a distance of 0.7 m from the measurand, the measurement systematic error in the diameter estimation is 0.22 mm with maximum resolution whereas uncertainty of the rotation angle was close to 5°.
Percolation framework reveals limits of privacy in conspiracy, dark web, and blockchain networks

Abstract We consider the limits of privacy based on the knowledge of interactions in anonymous networks. In many anonymous networks, such as blockchain cryptocurrencies, dark web message boards, and other illicit networks, nodes are anonymous to outsiders, however the existence of a link between individuals is observable. For example, in blockchains, transactions between anonymous accounts are published openly. Here we consider what happens if one or more individuals in such a network are deanonymized by an outside investigator. These compromised individuals could then potentially leak information about others with whom they interacted, leading to a cascade of nodes’ identities being revealed. We map this scenario to percolation and analyze its consequences on three real anonymous networks—(1) a blockchain transaction network, (2) interactions on the dark web, and (3) a political conspiracy network. We quantify, for different likelihoods of individuals possessing information on their neighbors, p , the fraction of accounts that can be identified in each network. We then estimate the minimum and most probable number of steps to a desired anonymous node, a measure of the effort to deanonymize that node. In all three networks, we find that it is possible to deanonymize a significant fraction of the network ( $&gt;50\%$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>&gt;</mml:mo> <mml:mn>50</mml:mn> <mml:mi>%</mml:mi> </mml:math> ) within less than 5 steps for values of $p&gt;0.4$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> <mml:mo>&gt;</mml:mo> <mml:mn>0.4</mml:mn> </mml:math> . We show how existing measures and approaches from percolation theory can help investigators quantify the chances of deanonymizing individuals, as well as how users can maintain privacy.
Realtime Handwritten Digit Recognition Using Keras Sequential Model and Pygame

Handwritten recognition has received the greater attention in deep learning research community due to its vast applications and ambiguity in learning methods. CNN in deep learning is now becoming one of the most appealing approaches and has been a crucial factor in the variety of recent success and challenging machine learning applications such as object detection. This research paper is about the extended application of handwritten digit recognition, i.e., realtime detection of the handwritten digits. CNN is used as the model for the classification of the image and more specifically Keras sequential model is used as a classifier. The interface is created by Pygame. The layout of the interface is kept simple and is divided into two frames one for input and other for output. The image pre-processing is the most important step which has done with the help of OpenCV and Scipy. MNIST is the dataset used for training and testing. Handwritten digit recognition has various real-life time uses. It is used in the detection of vehicle number, banks for reading cheques, post offices for arranging letter, and many other tasks.
Exploring Video Engagement in an Intelligent Tutoring System

Abstract This paper presents the results of student engagement with eBRAVO, an Intelligent Tutoring System designed to support students’ development of reading comprehension strategies. The eBRAVO curriculum is a personalized experience based on the students’ previous engagement with the tool as well as their demonstration of deep comprehension of the current materials. This personalization may include support in the form of video lessons that target the comprehension strategy with which the reader has recently struggled embedded within the chapter context the reader was currently working. This paper outlines the results from a deployment during a summer program supporting students reading ecology content, and shows that students are clearly distinguishable into categories that denote their patterns of engagement with these videos. It also discusses how these results connect to comprehension assessment results within the system and at a unit level and the implications these results have for the design of future classroom intervention systems.
Regulated Body-Sharing Virtual Trips for Pleasure and Business

Nowadays, people believe that not only the remote body operation by one direction control (Tele-existence) but also the remote body sharing by mutual control (Body-Sharing) will increase within few upcoming years. In the future, users -including elderly and disabled- can work and enjoy sightseeing using remote body sharing. Meanwhile, when many users deeply concentrate to act through remote bodies, their conscious is transferred to a remote place. As more users get immersed in the Body-Sharing, the number of unconscious users increases in arbitrary areas, leaving these areas unsafe. We aim to avoid the hazard resulting from high rates of unconscious users. In this research, the outcomes of five proposed rules that organize the unconscious users' rate are revealed. These rules are (I) Time Limit Rule "limiting the Body-Sharing time of each user per day", (II) Visitors Limit Rule "limiting the number of simultaneous remote Body-Sharing visitors into an area", (III) Departures Limit Rule "limiting the number of allowed Body-Sharing users to depart from an area simultaneously", (IV) Increase Charm Level Rule "granting larger budgets to the least attractive places", and (V) Decrease Charm Level Rule "deducting budgets assigned to the most attractive places". On the other hand, unconscious users rates are monitored when no rule (i.e. free Body-Sharing) is applied as a baseline for evaluation. In order to anticipate users' popular Body-Sharing destinations, we use a sigmoid function for decision making whether or not he or she travels. The attractiveness levels of different areas are set using the statistical data provided by the Japanese government. With the sigmoid probability function for decision making, the attractiveness of probable destinations, the five proposed rules, and the organization of unconscious users rate are simulated. The inhabitants of the Japanese 47 prefectures are the study case; a total population of 126.9 million according to the announced statistics in 2016. Rules I and II were found, by simulation, effective to suppress depopulation/overpopulation areas compared to free Body-Sharing. We realized that like the widely adopted parental rule that limits the time spent online daily by children, applying the Time Limit Rule on the unconscious users' rate organization outperformed other rules.
Transient Ground Potential Rise Impact on Reliability of Sensor and IED

In the smart substation, transient ground potential rise caused by lightning current is one of the main factors that affect the measurement accuracy and reliability of high voltage equipment sensor and IED (Intelligent Electronic Device). The paper established mathematical model for Impulse Generator and analyzes the variation trend of sensor and IED grounding shell potential under different parameters of impulse current. According to the equivalent circuit and simulation result, the paper designed a test apparatus which is used for the reliability test of sensor and IED, the test apparatus is composed of impulse generator, waveform adjusting unit and sample mounting platform. The results showed that under the standard current wave 8/20us, 10/350us, 10/1000us, the peak voltage of the platform to ground could up to 10kV, under the standard combination wave, the maximum peak voltage of the platform to ground could up to 12.1kV, and met the requirements of reliability test of transient ground potential rise for sensor and IED in substation.
Analysis of the Exposing Media Pattern that Affect Accessing Own Website

Recently, due to the expansion of TV or smart phone, the frequency of exposing media has increased. Also, the way of interacting with the media is diversifying by life stages or life balance. In such situations, people get much information about products and services on media. Therefore, it is important to select the best media for advertisement. In this study, we analyze the characteristics of exposing media using media exposure data. First, we performed Non-negative Matrix Factorization (NMF) to extract pattern of exposing media. Second, we used random forest to analyze the characteristics of the exposing media pattern. From our result, we discussed how to advertise on TV and website.
Research on User Experience Classification Based on Phenomenological Method

An important issue in the construction of the basic theory on user experience is that user experience classification has not yet received a satisfactory answer. This makes it difficult for user experience researchers and designers to practice without clear recognition on research objects. This article points out the existing classification methods are inadequate to explain an independent and clear experience phenomenon. The key challenge lies in the current research methods are not suitable for the user experience task. To overcome it, we utilize a phenomenological method of inductive reasoning method to construct a new framework including 20 experience classification. In the qualitative research based on phenomenological methods, researcher’s own knowledge background tends to have an important impact on the quality and effectiveness of the research. The aim of this research is not trying to provide a once and for all solution, but make the applicability of phenomenological research methods applicable. The proposed framework can provide a possible platform for the discussion of experience classification issues.
The Network of Resources - facilitating a simplified and efficient exploitation of EO data in cloud environments

Abstract As a combination of exploitation and processing platforms, the Network of Resources will support the user in procuring services and outsourcing requirements while increasing integration of EO data and information for a broader use, for scientific, social and economic purposes, as well as for the generation of new commercial applications and services. Selected as prime contractor by ESA, Cloudeo will create a portfolio of available EO resource tier and platform services and act as a facilitator to the “Network of Resources” for both providers and end users.
A Reusable Approach to Software Support for Adaptive Navigation

Adaptive navigation intends to guide users to their specific objectives within the application by altering the normal way the application allows to navigate, aiming to provide better experience for users with diverse needs and in different context conditions. Knowledge about activities that the user performs at runtime is crucial for adaptation decision making. It not only serves as a basis for evaluating relevance of the available information (such as user status, usage patterns, and context of use), but also facilitates reasoning about user needs. However, implementation of the user activity tracking capability often relies on intimate knowledge of the target application, which makes it difficult to develop loosely coupled modules to address separate concerns. In this paper, we describe a reusable approach to the development of the user activity tracking capability with the intent to support adaptive navigation. We use aspect-oriented instrumentation to capture user interface events and conduct model-based analysis to identify tasks that the user performs. A proof-of-concept experiment shows that our approach makes it possible to develop adaptation code that is reusable when the user interface and its adaptation logic evolve.
PMS-Sharing : Framework for Automatically Authenticating users in a Group to Allow Sharing Storage

Cloud storage is a very famous buzz word nowadays. There are many cloud storage service providers in the market and millions of mobile users are accessing cloud storage to store and access various personal data such as photos, videos and documents. In this era of smart mobile devices, every user is having devices with various storage capacity i.e. 8, 16, 32, 64, 128 GB and even more storage is going to be embedded in next generation of devices. These storage are widely used for storing and sharing data among multiple people. In this paper, a model and framework is proposed to automatically authenticate users within a group to allow sharing data while connected to same wireless network where initial group is formed by user (group owner) to allow set of users to access shared contents thereafter users in a group are automatically authenticated. The proposed solution is called personal mobile storage sharing (PMS-Sharing). The application and framework is developed and tested on android mobile phones supporting Android version 4.4 and above.