Non-expert Users Research Articles

A Methodology for Flexible Implementation of Collaborative Robots in Smart Manufacturing Systems

Small-scale production is relying more and more on personalization and flexibility as an innovation key for success in response to market needs such as diversification of consumer preferences and/or greater regulatory pressure. This can be possible thanks to assembly lines dynamically adaptable to new production requirements, easily reconfigurable and reprogrammable to any change in the production line. In such new automated production lines, where traditional automation is not applicable, human and robot collaboration can be established, giving birth to a kind of industrial craftsmanship. The idea at the base of this work is to take advantage of collaborative robotics by using the robots as other generic industrial tools. To overcome the need of complex programming, identified in the literature as one of the main issues preventing cobot diffusion into industrial environments, the paper proposes an approach for simplifying the programming process while still maintaining high flexibility through a pyramidal parametrized approach exploiting cobot collaborative features. An Interactive Refinement Programming procedure is described and validated through a real test case performed as a pilot in the Building Automation department of ABB in Vittuone (Milan, Italy). The key novel ingredients in this approach are a first translation phase, carried out by engineers of production processes who convert the sequence of assembly operations into a preliminary code built as a sequence of robot operations, followed by an on-line correction carried out by non-expert users who can interact with the machine to define the input parameters to make the robotic code runnable. The users in this second step do not need any competence in programming robotic code. Moreover, from an economic point of view, a standardized way of assessing the convenience of the robotic investment is proposed. Both economic and technical results highlight improvements in comparison to the traditional automation approach, demonstrating the possibility to open new further opportunities for collaborative robots when small/medium batch sizes are involved.

Systematic Literature Review on Cyber Situational Awareness Visualizations

The dynamics of cyber threats are increasingly complex, making it more challenging than ever for organizations to obtain in-depth insights into their cyber security status. Therefore, organizations rely on Cyber Situational Awareness (CSA) to support them in better understanding the threats and associated impacts of cyber events. Due to the heterogeneity and complexity of cyber security data, often with multidimensional attributes, sophisticated visualization techniques are needed to achieve CSA. However, there have been no previous attempts to systematically review and analyze the scientific literature on CSA visualizations. In this paper, we systematically select and review 54 publications that discuss visualizations to support CSA. We extract data from these papers to identify key stakeholders, information types, data sources, and visualization techniques. Furthermore, we analyze the level of CSA supported by the visualizations, alongside examining the maturity of the visualizations, challenges, and practices related to CSA visualizations to prepare a full analysis of the current state of CSA in an organizational context. Our results reveal certain gaps in CSA visualizations. For instance, the largest focus is on operational-level staff, and there is a clear lack of visualizations targeting other types of stakeholders such as managers, higher-level decision makers, and non-expert users. Most papers focus on threat information visualization, and there is a dearth of papers that visualize impact information, response plans, and information shared within teams. Interestingly, we find that only a few studies proposed visualizations to facilitate up to the projection level (i.e., the highest level of CSA), whereas most studies facilitated only the perception level (i.e., the lowest level of CSA). Most of the studies provide evidence of the proposed visualizations through toy examples and demonstrations, while only a few visualizations are employed in industrial practice. Based on the results that highlight the important concerns in CSA visualizations, we recommend a list of future research directions.

Evaluation of Natural Language Software Interfaces to Databases

Relational databases are still important in modern times due to their many advantages, such as ease of interaction, simplicity and data integrity. In this regard, structured query language (SQL) and technical knowledge about database schemas are the basic building blocks for retrieving information from relational databases. Generally, non-expert users cannot skillfully write technical queries on the target database. To this end, many database natural language interfaces (NLIDB) have been developed to greatly facilitate users. However, each system provides a different interface for new users, so beginners can use different interactive modes to enter keyword-based queries. For users, migrating from one NLIDB to another is a difficult problem. To solve this problem, NLIDB needs to be standardized so that novice users can easily enter queries in their native language. This paper proposes a standardized interface for NLIDB, which considers the three quality parameters of interface, query comparison and performance. Based on these parameters, we developed a standardized interface called the keyword-based frequent search engine (FKBSE). The DBLP data set has been evaluated experimentally. The results show the effectiveness of FKBSE compared with parallel systems in terms of quality parameters.

Adaptable Poly-Articulated Bionic Hands EnhanceBoth Performance and User's Perception in Bilateral Amputation: A Case Study.

This article evaluates and compares the performance and perception of prosthetic devices based on different design principles, a traditional rigid gripper and an adaptable poly-articulated hand, in a pre- and post-training protocol with an individual with bilateral amputation. As a representative of the first class, we use commercial hands (Ottobock's MyoHand VariPlus Speed), which is a widely adopted model by prosthesis users worldwide. We compare these with two SoftHand Pro hands, which are experimental prototypes exhibiting 19 articulations actuated by one single motor, and are inspired by human hand motor control models. Results show that the individual with bilateral amputation, who was a non-expert myoelectric user, achieved better performance with adaptive poly-articulated hands. Furthermore, the acceptation, satisfaction and perceived functionality of the user were considerably higher for the SoftHand Pro. An observational analysis of the patient's behaviour by experienced therapists suggests that adaptable poly-articulated hands reduced compensatory movements and cognitive load. Using soft technologies may be especially advantageous for individuals with bilateral amputation, who present a very limited residual mobility and can largely benefit from the active use of their artificial arms in everyday life.

Large-scale group decision-making method based on knowledge differentiation and the grouping of alternatives into modifiable scenarios

Nowadays, group decision-making is an everyday event, since we usually live in a community. Nevertheless, when the number of participants is large, it starts to generate a lot of information that is complex to manage, and unlike group decision-making, where the participants are usually experts, when the number of participants increases, not all of them are, which generates a conflict of interest because the value of the vote of an expert and a (non-expert) user is worth the same. Moreover, it may happen that not all participants who start a process will finish it and not all of them will be able to make all the assessments, since they do not know all the options. Therefore, to solve all the drawbacks, this paper presents a large-scale group decision-making system in a modifiable scenario environment that groups participants according to their preferred alternative and also performs knowledge differentiation, clustering them into experts and users. This allows for optimising the consensus process, as the consensus is made by comparing the clusters and the participants with each other.

OneModel: an open-source SBML modeling tool focused on accessibility, simplicity and modularity

With the advent of the Systems Biology Markup Language (SBML), a large community of SBML-compliant tools has been created. However, these tools can only be used to their full potential by expert users with advanced programming knowledge. OneModel is an open-source text-based tool for defining SBML models in a modular and incremental way that minimizes the user's programming knowledge requirements. It is focused on accessibility, simplicity, and modularity. OneModel syntax allows the user to define models based on chemical (and pseudo-chemical) reactions, differential equations, and algebraic equations. OneModel is written in Python, and it provides two interfaces: a command-line interface for expert-users, and a graphical user interface for non-expert users. Here, we show two OneModel syntax use case scenarios for modeling an antithetic controller and then integrating it into a host-aware model, which is freely distributed with OneModel.

Semantic Snapping for Guided Multi-View Visualization Design.

Visual information displays are typically composed of multiple visualizations that are used to facilitate an understanding of the underlying data. A common example are dashboards, which are frequently used in domains such as finance, process monitoring and business intelligence. However, users may not be aware of existing guidelines and lack expert design knowledge when composing such multi-view visualizations. In this paper, we present semantic snapping, an approach to help non-expert users design effective multi-view visualizations from sets of pre-existing views. When a particular view is placed on a canvas, it is "aligned" with the remaining views-not with respect to its geometric layout, but based on aspects of the visual encoding itself, such as how data dimensions are mapped to channels. Our method uses an on-the-fly procedure to detect and suggest resolutions for conflicting, misleading, or ambiguous designs, as well as to provide suggestions for alternative presentations. With this approach, users can be guided to avoid common pitfalls encountered when composing visualizations. Our provided examples and case studies demonstrate the usefulness and validity of our approach.

Advances in 3D printing of food and nutritional products.

The main advantage of both 3D printing (3DP) and 3D food printing (3DFP) over other technologies is the enormous capacity of both techniques for customization. Its use makes it possible to obtain products without planning and implementing a complex and costly manufacturing process. This makes 3DFP a technology of choice for the preparation of food products that meet specific needs, such as controlled nutritional or rheological properties. However, further technological developments are still needed before 3DFP can be considered fully useful for innovative and demanding applications. If both preparation and post-processing of materials based on 3D printing are optimized, aiming to reduce production time and/or complication for non-expert users, this would open a whole new range of possibilities. It is in this sense that the development of advanced 3DFP systems becomes a must. This chapter reviews current advances in extrusion-based 3D food printing systems, with in situ gelation and mixing as key aspects to better exploit the potential of 3DFP. On one hand, 3DFP systems based on in situ gelation (G3DFP) provide greater control over the final properties of the printed products, as the selection of adequate printing parameters gives the possibility of influencing the gelation process. On the other hand, mixing is indispensable for true 3DFP automation, so that the formulations do not have to be prepared by the user. Different innovative 3DFP systems based on gelling and/or mixing are presented in this chapter. Finally, the status and future of extrusion-based 3DFP, and its application in the production of customized foods for specific needs, are also overviewed.

BML: a versatile web server for bipartite motif discovery.

Motif discovery and characterization are important for gene regulation analysis. The lack of intuitive and integrative web servers impedes the effective use of motifs. Most motif discovery web tools are either not designed for non-expert users or lacking optimization steps when using default settings. Here we describe bipartite motifs learning (BML), a parameter-free web server that provides a user-friendly portal for online discovery and analysis of sequence motifs, using high-throughput sequencing data as the input. BML utilizes both position weight matrix and dinucleotide weight matrix, the latter of which enables the expression of the interdependencies of neighboring bases. With input parameters concerning the motifs are given, the BML achieves significantly higher accuracy than other available tools for motif finding. When no parameters are given by non-expert users, unlike other tools, BML employs a learning method to identify motifs automatically and achieve accuracy comparable to the scenario where the parameters are set. The BML web server is freely available at http://motif.t-ridership.com/ (https://github.com/Mohammad-Vahed/BML).

Recognition of arm and body postures as social cues for proactive HRI

AbstractArtificial agents can uplift the living standards of domestic population considerably. One hindrance for this is that the robot is less competent to perceive complex human behaviors. With such perceptive skills in the robot, nonexpert users will find it easier to cope with their robot companion with less and less instructions to follow. Perception of the internal state of a user or “user situation” before interaction is crucial in this regard. There are a variety of factors that affect this user situation. Out of these, posture becomes prominent in displaying the emotional state of a person. This article presents a novel approach to identify diverse human postures often encountered in domestic environments and how a robot could assess its user’s emotional state of mind before an interaction based on postures. Therefore, the robot evaluates posture and the overall postural behavior of its user throughout the period of observation before initiating an interaction with its user. Aforementioned user evaluation is nonverbal and decisions are made through observation as well. We introduced a variable called “valence” to measure how “relaxed” or “stressed” a user is, in a certain encounter. The robot decides upon an appropriate approach behavior accordingly. Furthermore, the proposed concept was capable of recognizing both arm and body postures and both postural behaviors over time. This leads to an interaction initiated by robot itself in a favorable situation so that the scenario looks more intelligent. Hence more humanlike. The system has been implemented, and experiments have been conducted on an assistive robot placed in an artificially created domestic environment. Results of the experiments have been used to validate the proposed concept and critical observations are discussed.

Why robots should be technical

Abstract Research in social robotics is commonly focused on designing robots that imitate human behavior. While this might increase a user’s satisfaction and acceptance of robots at first glance, it does not automatically aid a non-expert user in naturally interacting with robots, and might hurt their ability to correctly anticipate a robot’s capabilities. We argue that a faulty mental model, that the user has of the robot, is one of the main sources of confusion. In this work, we investigate how communicating technical concepts of robotic systems to users affect their mental models, and how this can increase the quality of human-robot interaction. We conducted an online study and investigated possible ways of improving users’ mental models. Our results underline that communicating technical concepts can form an improved mental model. Consequently, we show the importance of consciously designing robots that express their capabilities and limitations.

Complex, but in a good way? How to represent encryption to non-experts through text and visuals – Evidence from expert co-creation and a vignette experiment

An ongoing discussion in the field of usable privacy and security debates whether security mechanisms should be visible to end-users during interactions with technology, or hidden away. This paper addresses this question using a mixed-methods approach, focusing on encryption as a mechanism for confidentiality during data transmission on a smartphone application. In study 1, we conducted a qualitative co-creation study with security and Human-Computer Interaction (HCI) experts (N = 9) to create appropriate textual and visual representations of the security mechanism encryption in data transmission. We investigated this question in two contexts: online banking and e-voting. In study 2, we put these ideas to the test by presenting these visual and textual representations to non-expert users in an online vignette experiment (N = 2180). We found a statistically significant and positive effect of the textual representation of encryption on perceived security and understanding, but not on user experience (UX). More complex text describing encryption resulted in higher perceived security and more accurate understanding. The visual representation of encryption had no statistically significant effect on perceived security, UX or understanding. Our study contributes to the larger discussion regarding visible instances of security and their impact on user perceptions.

How is avalanche danger described in textual descriptions in avalanche forecasts in Switzerland? Consistency between forecasters and avalanche danger

Abstract. Effective and efficient communication of expected avalanche conditions and danger to the public is of great importance, especially where the primary audience of forecasts are recreational, non-expert users. In Europe, avalanche danger is communicated using a pyramid, starting with ordinal levels of avalanche danger and progressing through avalanche-prone locations and avalanche problems to a danger description. In many forecast products, information relating to the trigger required to release an avalanche, the frequency or number of potential triggering spots, and the expected avalanche size is described exclusively in a textual danger description. These danger descriptions are, however, the least standardized part of avalanche forecasts. Taking the perspective of the avalanche forecaster and focusing particularly on terms describing these three characterizing elements of avalanche danger, we investigate first which meaning forecasters assign to the text characterizing these elements and second how these descriptions relate to the forecast danger level. We analyzed almost 6000 danger descriptions in avalanche forecasts published in Switzerland and written using a structured catalogue of phrases with a limited number of words. Words and phrases representing information describing these three elements were labeled and assigned to ordinal classes by Swiss avalanche forecasters. These classes were then related to avalanche danger. Forecasters were relatively consistent in assigning labels to words and phrases with Cohen's kappa values ranging from 0.64 to 0.87. Avalanche danger levels were also described consistently using words and phrases, with for example avalanche size classes increasing monotonically with avalanche danger. However, especially for danger level 2 (moderate), information about key elements of avalanche danger, for instance the frequency or number of potential triggering spots, was often missing in danger descriptions. In general, the analysis of the danger descriptions showed that extreme conditions are described in more detail than intermediate values, highlighting the difficulty of communicating conditions that are neither rare nor frequent or neither small nor large. Our results provide data-driven insights that could be used to refine the ways in which avalanche danger could be communicated. Furthermore, through the perspective of the semiotic triangle, relating a referent (the avalanche situation) through thought (the processing process) to symbols (the textual danger description), we provide an alternative starting point for future studies of avalanche forecast consistency and communication.

Integrating tsunami simulations in web applications using BROWNI, an open source client-side GPU-powered tsunami simulation library

Tsunami simulation software is a key component of state-of-the-art early warning systems but the inherent complexities in phases of installation, execution, pre and post-processing prevent their use in other areas of risk management such as communication and education. Recent advances in software and computational capacities such as the efficiency of GPU computing and the ubiquity of web browsers bring new opportunities to bridge the gap between expert and non-expert users. Here we present a Javascript library to enable a web browser to facilitate gathering and analyzing data from tsunami simulations, by means of interactive and efficient visualizations. At its core, the library uses WebGL, the browser’s standard 3D graphics API, to run GPU accelerated computations of a tsunami model. A far-field tsunami model is implemented (linear shallow water equations discretized on spherical coordinates), and its implementation is validated against real tsunami observations, and benchmarked with two other tsunami software-packages. Two software platforms that use this library are presented to illustrate the powerful applications that can be developed for risk communication and education. These applications are characterized by their interactivity and fast computations, which enable users to focus on the understanding of the phenomena of tsunami propagation and iterate quickly to assess different scenarios and potential implications to tsunami risk management. Some limitations on this approach are discussed, in aspects such as scalability, performance, multi-threading and batch-processing, that can be relevant for other users. In our experience, the before mentioned benefits very well compensate the discussed limitations for this kind of applications. The library has an open source license, and is meant to be imported without modifying its source code to facilitate the creation of new applications as the ones herein presented.

Comparison between rigid and soft poly-articulated prosthetic hands in non-expert myo-electric users shows advantages of soft robotics

Notwithstanding the advancement of modern bionic hands and the large variety of prosthetic hands in the market, commercial devices still present limited acceptance and percentage of daily use. While commercial prostheses present rigid mechanical structures, emerging trends in the design of robotic hands are moving towards soft technologies. Although this approach is inspired by nature and could be promising for prosthetic applications, there is scant literature concerning its benefits for end-users and in real-life scenarios. In this work, we evaluate and assess the role and the benefits of soft robotic technologies in the field of prosthetics. We propose a thorough comparison between rigid and soft characteristics of two poly-articulated hands in 5 non-expert myo-electric prosthesis users in pre- and post-therapeutic training conditions. The protocol includes two standard functional assessments, three surveys for user-perception, and three customized tests to evaluate the sense of embodiment. Results highlight that rigid hands provide a more precise grasp, while soft properties show higher functionalities thanks to their adaptability to different requirements, intuitive use and more natural execution of activities of daily living. This comprehensive evaluation suggests that softness could also promote a quick integration of the system in non-expert users.

A decision support tool for multi-attribute evaluation of demand-side commercial battery storage products

With the diversification of commercial energy storage technologies, choosing a suitable technology is becoming a complex decision-making process. The complexity is rooted in the many decision criteria such as technology, brand reputation, energy capacity, volume, weight, aging, and warranty among many others. As such, for non-expert users, particularly small households or enterprises, the act of energy storage adoption is becoming growingly cumbersome. To address this problem, this paper introduces a decision support tool for the evaluation of commercial (small-scale) energy storage products. It then identifies the most suitable option(s) based on the users' preferences.For the reasons elaborated in the paper, nine multi-criteria decision-making (MCDM) methodologies have been employed. Altogether, 19 attributes are identified for the evaluation of (battery) energy storage technologies. The decision support tool is developed in the Matlab environment and includes a graphical user interface for easier interaction of non-expert users. For the demonstration, three scenario cases have been studied for users with different preferences. The ranking results clearly show the marked impact of users preferences on the recommended energy storage technologies. This implies that a tool like this can help small users in the selection of their right technology and avoid resource loss due to inappropriate technology selection, which can be neither economical nor sustainable.

Public Works Heritage 3D Model Digitisation, Optimisation and Dissemination with Free and Open-Source Software and Platforms and Low-Cost Tools

This paper describes an innovative, accessible, and sustainable method for enhancing cultural heritage. Documenting and disseminating the public works heritage have now come of age, digitally speaking, with the adoption of new technologies both to further research on and heighten the esteem attributed to the public works heritage. Nonetheless, academic discourse rarely describes procedures for the 3D digitisation of heritage works comprehensible to non-expert readers with limited resources. Taking that premise as a starting point, with special attention to the determinants of the public works heritage, this article aims to define the general, open-source methodology covering 3D model data capture, information processing and optimisation. The article also discusses model dissemination strategies using free platforms and low-cost tools. The general discussion is illustrated with the case study of Ariza Bridge in Spain. This Renaissance-style structure dates from the second half of the sixteenth century. Despite its listing as a cultural heritage asset, the monument was flooded by the Giribaile reservoir waters in 1998 and is now only wholly visible during droughts. The application, developed with open-source software and implemented with free platforms and low-cost tools, features geo-referencing and is designed to be accessible to non-expert users. The methodology proposed is intended as a suitable instrument for the sustainable study, valorisation and dissemination of the built heritage.

Lca_algebraic: a library bringing symbolic calculus to LCA for comprehensive sensitivity analysis

PurposeIn this paper, we present new tools to ease the analysis of the effect of variability and uncertainty on life cycle assessment (LCA) results.MethodsThe tools consist of a standard protocol and an open-source library: lca_algebraic. This library, written in Python and based on the framework Brightway2 (Mutel in J Open Source Softw 2(12):236, 2017) provides functions to support sensitivity analysis by bringing symbolic calculus to LCA. The use of symbolic calculus eases the definition of parametric inventories and enables a very fast evaluation of impacts by factorizing the background activities. Thanks to this processing speed, a large number of Monte Carlo simulations can be generated to evaluate the variation of the impacts and apply advanced statistic tools such as Sobol indices to quantify the contribution of each parameter to the final variance (Sobol in Math Comput Simul 55(1–3):271–280, 2001). An additional algorithm uses the key parameters, identified from their high Sobol indices, to generate simplified arithmetic models for fast estimates of LCA results.Results and discussionThe protocol and library were validated through their application to the assessment of impacts of mono crystalline photovoltaic (PV) systems. A comprehensive sensitivity analysis was performed based on the protocol and the complementary functions provided by lca_algebraic. The proposed tools helped building a detailed parametric reference LCA model of the PV system to identify the range of variation of multi-criterion LCA results and the key foreground-related parameters explaining these variations. Based on these key parameters, we generated simplified arithmetic models for quick and simple multi-criteria environmental assessments to be used by non-expert LCA users. The resulting models are both compact and aligned with the reference parametric LCA model of crystalline silicon PV systems.ConclusionThis work brings powerful and practical tools to the LCA community to better understand, identify, and quantify the sources of variation of environmental impacts and produce simplified models to spread the use of LCA among non-experts. The library mainly explores the uncertainties of the foreground activities. Further work could also integrate the uncertainty of background activities, described, for example, by pedigree matrices.

Ocean Lagrangian Trajectories (OLTraj): Lagrangian analysis for non-expert users.

Lagrangian analysis is becoming increasingly important to better understand the ocean's biological and biogeochemical cycles. Yet, biologists and chemists often lack the technical skills required to set up such analyses. Here, we present a new product of pre-computed ocean Lagrangian trajectories (OLTraj) targeting non-expert users, and demonstrate how to use it by means of worked examples. OLTraj is based on satellite-derived geostrophic currents, which allows one to directly compare it with other in-situ or satellite products.We anticipate that OLTraj will foster a new interest in Lagrangian applications in ocean biology and biogeochemistry.

Development and validation of guidelines for safety in human-robot collaborative assembly systems

Industrial collaborative robotics is one of the most promising technologies of Industry 4.0. In particular, human-robot collaboration in assembly will be particularly interesting for manufacturing companies. In this context, the interaction between humans and robots opens new possibilities but also challenges. A major problem is related to safety: unwanted and unexpected contacts between the human and the robotic system may cause injuries and therefore limit the potential for collaboration. Nowadays, there is a lack of simple and practical tools for helping system designers in overcoming such limiting conditions. In this work, guidelines for the design of safe human-robot collaborative assembly are developed and classified, particularly focusing on the features characterizing the entire system. These are validated by means of a laboratory case study and a digital twin. The validation process is based on the assumption that a team of manufacturing engineers (not-experts in occupational health and safety) should be able to autonomously and gradually apply the given guidelines reducing the mechanical risk in a collaborative assembly system. The proposed solutions have been virtually modelled allowing the evaluation of their effectiveness. According to the results, the proposed guidelines effectively help non-expert users in the development and improvement of collaborative assembly systems from the safety perspective.