Search results for: user guidance

Authors: Aarnav Singh, Jatin Moolchandani

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The proposed research work aims to build a query-based AI chatbot that can answer any question related to any topic. A chatbot is software that converses with users via text messages. In the proposed system, we aim to build a chatbot that generates a response based on the user’s query. For this, we use natural language processing to analyze the query and some set of texts to form a concise answer. The texts are obtained through web-scrapping and filtering all the credible sources from a web search. The objective of this project is to provide a chatbot that is able to provide simple and accurate answers without the user having to read through a large number of articles and websites. Creating an AI chatbot that can answer a variety of user questions on a variety of topics is the goal of the proposed research project. This chatbot uses natural language processing to comprehend user inquiries and provides succinct responses by examining a collection of writings that were scraped from the internet. The texts are carefully selected from reliable websites that are found via internet searches. This project aims to provide users with a chatbot that provides clear and precise responses, removing the need to go through several articles and web pages in great detail. In addition to exploring the reasons for their broad acceptance and their usefulness across many industries, this article offers an overview of the interest in chatbots throughout the world.

Keywords: Chatbot, Artificial Intelligence, natural language processing, web scrapping

Procedia PDF Downloads 65

Authors: Minsun Kim

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This study uses the concepts of augmented reality, virtual reality, mirror world, and lifelogging to describe “Metaverse Kitchen” that can be defined as a space in the virtual world where users can cook the dishes they want using the meal kit regardless of location or time. This study examined expert’s perceptions of cooking and food delivery services using "Metaverse Kitchen." In this study, a consensus opinion on the concept, potential pros, and cons of "Metaverse Kitchen" was derived from 20 culinary experts through the Delphi technique. The three Delphi rounds were conducted for one month, from December 2022 to January 2023. The results are as follows. First, users select and cook food after visiting the "Metaverse Kitchen" in the virtual space. Second, when a user cooks in "Metaverse Kitchen" in AR or VR, the information is transmitted to nearby restaurants. Third, the platform operating the "Metaverse Kitchen" assigns the order to the restaurant that can provide the meal kit cooked by the user in the virtual space first in the same way among these restaurants. Fourth, the user pays for the "Metaverse Kitchen", and the restaurant delivers the cooked meal kit to the user and then receives payment for the user's meal and delivery fee from the platform. Fifth, the platform company that operates the mirror world "Metaverse Kitchen" uses lifelogging to manage customers. They receive commissions from users and affiliated restaurants and operate virtual restaurant businesses using meal kits. Among the selection attributes for meal kits provided in "Metaverse Kitchen", the panelists suggested convenience, quality, and reliability as advantages and predicted relatively high price as a disadvantage. "Metaverse Kitchen" using meal kits is expected to form a new food supply system in the future society. In follow-up studies, an empirical analysis is required targeting producers and consumers.

Keywords: metaverse, meal kits, Delphi technique, Metaverse Kitchen

Procedia PDF Downloads 221

Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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For security purposes, it is important to detect passwords entered by unauthorized users. With traditional alphanumeric passwords, if the content of a password is acquired and correctly entered by an intruder, it is impossible to differentiate the password entered by the intruder from those entered by the authorized user because the password entries contain precisely the same character set. However, no two entries for the gesture-based passwords, even those entered by the person who created the password, will be identical. There are always variations between entries, such as the shape and length of each stroke, the location of each stroke, and the speed of drawing. It is possible that passwords entered by the unauthorized user contain higher levels of variations when compared with those entered by the authorized user (the creator). The difference in the levels of variations may provide cues to detect unauthorized entries. To test this hypothesis, we designed an empirical study, collected and analyzed the data with the help of machine-learning algorithms. The results of the study are significant.

Keywords: authentication, gesture-based passwords, shoulder-surfing attacks, usability

Procedia PDF Downloads 139

Authors: Mostafa ‘Neo’ Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

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EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy of modern supervised methods falls rapidly as the number of users increases to a few thousand. Moreover, supervised methods require a large amount of labeled data for training which limits their applications in real-world scenarios where acquiring data for training should not take more than a few minutes. We show that using contrastive learning for pre-training, it is possible to maintain high accuracy on a dataset of 2130 subjects while only using a fraction of labels. We compare 5 different self-supervised tasks for pre-training of the encoder where our proposed method achieves the accuracy of 96.4%, improving the baseline supervised models by 22.75% and the competing self-supervised model by 3.93%. We also study the effects of the length of the signal and the number of channels on the accuracy of the user-identification models. Our results reveal that signals from temporal and frontal channels contain more identifying features compared to other channels.

Keywords: brainprint, contrastive learning, electroencephalo-gram, self-supervised learning, user identification

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Authors: Mohammed H. Karim, Bestoon M. Faraj

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Introduction: This study aimed to compare the effectiveness of a Dynamic Navigation System (DNS) and a three-dimensional microscope in retrieving broken rotary NiTi files when using trepan burs and the extractor system. Materials and Methods: Thirty maxillary first bicuspids with sixty separate roots were split into two comparable groups based on a comprehensive Cone-Beam Computed Tomography (CBCT) analysis of the root length and curvature. After standardized access opening, glide paths, and patency attainment with the K file (sizes 10 and 15), the teeth were arranged on 3D models (three per quadrant, six per model). Subsequently, controlled-memory heat-treated NiTi rotary files (#25/0.04) were notched 4 mm from the tips and fractured at the apical third of the roots. The C-FR1 Endo file removal system was employed under both guidance to retrieve the fragments, and the success rate, canal aberration, treatment time and volumetric changes were measured. The statistical analysis was performed using IBM SPSS software at a significance level of 0.05. Results: The microscope-guided group had a higher success rate than the DNS guidance, but the difference was insignificant (p > 0.05). In addition, the microscope-guided drills resulted in a substantially lower proportion of canal aberration, required less time to retrieve the fragments and caused minimal change in the root canal volume (p < 0.05). Conclusion: Although dynamically guided trephining with the extractor can retrieve separated instruments, it is inferior to three-dimensional microscope guidance regarding treatment time, procedural errors, and volume change.

Keywords: separated instruments retrieval, dynamic navigation system, 3D video microscope, trephine burs, extractor

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Authors: Madiha Khan, Sidrah Ramzan, Seemab Khan, Shahzad Hassan, Kamran Saeed

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Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.

Keywords: Graphviz representation, semantic relatedness, similarity measurement, WordNet similarity

Procedia PDF Downloads 237

Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

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This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence

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Authors: Abdul Basit Kiani, Maryam Kiani

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Online developers now have the tools necessary to create online apps that are not only reliable but also highly interactive, thanks to the introduction of JavaScript frameworks and APIs. The objective is to give a broad overview of the recent advances in the area. The fusion of machine learning (ML) and artificial intelligence (AI) has expanded the possibilities for web development. Modern websites now include chatbots, clever recommendation systems, and customization algorithms built in. In the rapidly evolving landscape of modern websites, it has become increasingly apparent that user engagement and personalization are key factors for success. To meet these demands, websites now incorporate a range of innovative technologies. One such technology is chatbots, which provide users with instant assistance and support, enhancing their overall browsing experience. These intelligent bots are capable of understanding natural language and can answer frequently asked questions, offer product recommendations, and even help with troubleshooting. Moreover, clever recommendation systems have emerged as a powerful tool on modern websites. By analyzing user behavior, preferences, and historical data, these systems can intelligently suggest relevant products, articles, or services tailored to each user's unique interests. This not only saves users valuable time but also increases the chances of conversions and customer satisfaction. Additionally, customization algorithms have revolutionized the way websites interact with users. By leveraging user preferences, browsing history, and demographic information, these algorithms can dynamically adjust the website's layout, content, and functionalities to suit individual user needs. This level of personalization enhances user engagement, boosts conversion rates, and ultimately leads to a more satisfying online experience. In summary, the integration of chatbots, clever recommendation systems, and customization algorithms into modern websites is transforming the way users interact with online platforms. These advanced technologies not only streamline user experiences but also contribute to increased customer satisfaction, improved conversions, and overall website success.

Keywords: Javascript, machine learning, artificial intelligence, web development

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Authors: Valentin P. Velikov

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Automatic program generation saves time, human resources, and allows receiving syntactically clear and logically correct modules. The 4-th generation programming languages are related to drawing the data and the processes of the subject area, as well as, to obtain a frame of the respective information system. The application can be separated in interface and business logic. That means, for an interactive generation of the needed system to be used an already existing toolkit or to be created a new one.

Keywords: computer science, graphical user interface, user dialog interface, dialog frames, data modeling, subject area modeling

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Authors: M. S. Jimah, A. C. Achuenu, M. Momodu

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Group communications over public infrastructure are prone to a lot of security issues. Existing network protocols like Protocol Independent Multicast Sparse Mode (PIM SM) and Protocol Independent Multicast Dense Mode (PIM DM) do not have inbuilt security features. Therefore, any user or node can easily access the group communication as long as the user can send join message to the source nodes, the source node then adds the user to the network group. In this research, a hybrid method of salting and hashing to encrypt information in the source and stub node was designed, and when stub nodes need to connect, they must have the appropriate key to join the group network. Object oriented analysis design (OOAD) was the methodology used, and the result shows that no extra controlled bandwidth overhead cost was added by encrypting and the hybrid model was more securing than the existing PIM SM, PIM DM and Zhang secure PIM SM.

Keywords: group communications, multicast, PIM SM, PIM DM, encryption

Procedia PDF Downloads 162

Authors: Farah Al-Fityani, Aljohara Alsowail, Shatha Bindawood, Heba Balrbeah

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Locket is a popular app that lets users share spontaneous photos with a close circle of friends. The app offers a unique way to stay connected with loved ones by allowing users to see glimpses of their day through photos displayed on a widget on their home screen. This summary outlines the process of developing an app like Locket, highlighting the importance of user privacy and security. It also details the findings of a study on user engagement with the Locket app, revealing positive sentiment towards its features and concept but also identifying areas for improvement. Overall, the summary portrays Locket as a successful app that is changing the way people connect on social media.

Keywords: locket, app, machine learning, connect

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Authors: Ajeni Ari

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In addressing gender and transport, considerations of mobility disparities amongst users are important. Public transport (PT) policy and design do not efficiently account for the varied mobility practices between men and women, with literature only recently showing a movement towards gender inclusion in transport. Arrantly, transport policy and designs remain gender-blind to the variation of mobility needs. The global movement towards sustainability highlights the need for expeditious strategies that could mitigate biases within the existing system. At the forefront of such plan of action may, in part, be mandated inclusive infrastructural designs that stimulate user engagement with the transport system. Fundamentally access requires a means or an opportunity to entity, which for PT is an establishment of its physical environment and/or infrastructural design. Its practicality may be utilised with knowledge of shortcomings in tangible or intangible aspects of the service offerings allowing access to opportunities. To inform on existing biases in PT planning and design, this study analyses qualitative data to examine the opinions and lived experiences among transport user in Ireland. Findings show that infrastructural design plays a significant role in users’ engagement with the service. Paramount to accessibility are service provisions that cater to both user interactions and those of their dependents. Apprehension to use the service is more so evident with women in comparison to men, particularly while carrying out household duties and caring responsibilities at peak times or dark hours. Furthermore, limitations are apparent with infrastructural service offerings that do not accommodate the physical (dis)ability of users, especially universal design. There are intersecting factors that impinge on accessibility, e.g., safety and security, yet essentially, infrastructural design is an important influencing parameter to user perceptual conditioning. Additionally, data discloses the need for user intricacies to be factored in transport planning geared towards gender inclusivity, including mobility practices, travel purpose, transit time or location, and system integration.

Keywords: public transport, accessibility, women, transport infrastructure

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Authors: Dominik Krimpmann

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Cloud computing has provided the impetus for change in the demand, sourcing, and consumption of IT-enabled services. The technology developed from an emerging trend towards a ‘must-have’. Many organizations harnessed on the quick-wins of cloud computing within the last five years but nowadays reach a plateau when it comes to sustainable savings and performance. This study aims to investigate what is needed from an organizational perspective to make cloud computing a sustainable success. The study was carried out in Germany among senior IT professionals, both in management and delivery positions. Our research shows that IT executives must be prepared to realign their IT workforce to sustain the advantage of cloud computing for today and the near future. While new roles will undoubtedly emerge, roles alone cannot ensure the success of cloud deployments. What is needed is a change in the IT workforce’s business behaviour, or put more simply, the ways in which the IT personnel works. It gives clear guidance on which dimensions of an employees’ working behaviour need to be adapted. The practical implications are drawn from a series of semi-structured interviews, resulting in a high-level workforce enablement plan. Lastly, it elaborates on tools and gives clear guidance on which pitfalls might arise along the proposed workforce enablement process.

Keywords: cloud computing, organization design, organizational change, workforce enablement

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Authors: Prisecaru Diana-Sorina

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The paper will show that, while the EU legislator tackled a series of UX patterns used in e-commerce to induce the consumers take actions that they would not normally undertake, it leaves out many other aspects related to misuse or poor UX design that adversely affect EU consumers. Further, the paper proposes a reevaluation of the regulatory addressability of the issue and hand and focuses on explaining why a joint strategy, based on the interplay between provisions aiming consumer protection and personal data protection is the key approach to this matter.

Keywords: algorithms, consumer protection, European Union, user experience design

Procedia PDF Downloads 136

Authors: Sergio V Davalos, Alison L. Watkins

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User generated content (UGC) such as website post has data associated with it: time of the post, gender, location, type of device, and number of words. The text entered in user generated content (UGC) can provide a valuable dimension for analysis. In this research, each user post is treated as a collection of terms (words). In addition to the number of words per post, the frequency of each term is determined by post and by the sum of occurrences in all posts. This research focuses on one specific aspect of UGC: sentiment. Sentiment analysis (SA) was applied to the content (user posts) of two sets of political forums related to the US presidential elections for 2012 and 2016. Sentiment analysis results in deriving data from the text. This enables the subsequent application of data analytic methods. The SASA (SAIL/SAI Sentiment Analyzer) model was used for sentiment analysis. The application of SASA resulted with a sentiment score for each post. Based on the sentiment scores for the posts there are significant differences between the content and sentiment of the two sets for the 2012 and 2016 presidential election forums. In the 2012 forums, 38% of the forums started with positive sentiment and 16% with negative sentiment. In the 2016 forums, 29% started with positive sentiment and 15% with negative sentiment. There also were changes in sentiment over time. For both elections as the election got closer, the cumulative sentiment score became negative. The candidate who won each election was in the more posts than the losing candidates. In the case of Trump, there were more negative posts than Clinton’s highest number of posts which were positive. KNIME topic modeling was used to derive topics from the posts. There were also changes in topics and keyword emphasis over time. Initially, the political parties were the most referenced and as the election got closer the emphasis changed to the candidates. The performance of the SASA method proved to predict sentiment better than four other methods in Sentibench. The research resulted in deriving sentiment data from text. In combination with other data, the sentiment data provided insight and discovery about user sentiment in the US presidential elections for 2012 and 2016.

Keywords: sentiment analysis, text mining, user generated content, US presidential elections

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Authors: E. Ielegems, J. Herssens, J. Vanrie

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Designers require knowledge and data about a diversity of users throughout the design process to create inclusive design solutions which are usable, understandable and desirable by everyone. Besides understanding users’ needs and expectations, the ways in which users perceive and experience the built environment contain valuable knowledge for architects. Since users’ perceptions and experiences are mainly tacit by nature, they are much more difficult to express in words and therefore more difficult to externalise. Nevertheless, literature confirms the importance of articulating embodied knowledge from users throughout the design process. Hence, more insight is needed into the ways architects can build knowledge on Universal Design through direct user contact. In a project called ‘light up for all’ architecture students are asked to design a light switch and socket, elegant, usable and understandable to the greatest extent possible by everyone. Two workshops with user/experts are organised in the first stages of the design process in which students could gain insight into users’ experiences through direct contact. Three data collection techniques are used to analyse the teams’ design processes. First, students were asked to keep a design diary, reporting design activities, personal experiences, and thoughts about users throughout the design process. Second, one of the authors observed workshops taking field notes. Finally, focus groups are conducted with the design teams after the design process was finished. By means of analysing collected qualitative data, we first identify different design aspects that make the teams’ proposals more inclusive than standard design solutions. For this paper, we specifically focus on aspects that externalise embodied user knowledge from users’ experiences. Subsequently, we look at designers’ approaches to learn about these specific aspects throughout the design process. Results show that in some situations, designers perceive contradicting knowledge between observations and verbal conversations, which shows the value of direct user contact. Additionally, findings give indications on values and limitations of working with selected prototypes as ‘boundary objects’ when externalising users’ experiences. These insights may help researchers to better understand designers’ process of eliciting embodied user knowledge. This way, research can offer more effective support to architects, which may result in better incorporating users’ experiences so that the built environment gradually can become more inclusive for all.

Keywords: universal design, architecture, design process, embodied user knowledge

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Authors: Thedy Yogasara, Fredy Agus

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In designing a product, it is currently crucial to focus not only on the product’s usability based on performance measures, but also on user experience (UX) that includes pragmatic and hedonic aspects of product use. These aspects play a significant role in fulfillment of user needs, both functionally and psychologically. Pragmatic quality refers to as product’s perceived ability to support the fulfillment of behavioral goals. It is closely linked to functionality and usability of the product. In contrast, hedonic quality is product’s perceived ability to support the fulfillment of psychological needs. Hedonic quality relates to the pleasure of ownership and use of the product, including stimulation for personal development and communication of user’s identity to others through the product. This study evaluates the pragmatic and hedonic aspects of gaming mice G600 and Razer Krait using AttrakDiff tool to create an improved design that is able to generate positive UX. AttrakDiff is a method that measures pragmatic and hedonic scores of a product with a scale between -3 to +3 through four attributes (i.e. Pragmatic Quality, Hedonic Quality-Identification, Hedonic Quality-Stimulation, and Attractiveness), represented by 28 pairs of opposite words. Based on data gathered from 15 participants, it is identified that gaming mouse G600 needs to be redesigned because of its low grades (pragmatic score: -0.838, hedonic score: 1, attractiveness score: 0.771). The redesign process focuses on the attributes with poor scores and takes into account improvement suggestions collected from interview with the participants. The redesigned mouse G600 is evaluated using the previous method. The result shows higher scores in pragmatic quality (1.929), hedonic quality (1.703), and attractiveness (1.667), indicating that the redesigned mouse is more capable of creating pleasurable experience of product use.

Keywords: AttrakDiff, hedonic aspect, pragmatic aspect, product design, user experience

Procedia PDF Downloads 157

Authors: Hsin-Yun Lee

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In this study, the pedestrian simulation VISWALK integration and application platform ant algorithms written program made to construct a renovation engineering schedule planning mode. The use of simulation analysis platform construction site when the user running the simulation, after calculating the user walks in the case of construction delays, the ant algorithm to find out the minimum delay time schedule plan, and add volume and unit area deactivated loss of business computing, and finally to the owners and users of two different positions cut considerations pick out the best schedule planning. To assess and validate its effectiveness, this study constructed the model imported floor of a shopping mall floor renovation engineering cases. Verify that the case can be found from the mode of the proposed project schedule planning program can effectively reduce the delay time and the user's walking mall loss of business, the impact of the operation on the renovation engineering facilities in the building to a minimum.

Keywords: pedestrian, renovation, schedule, simulation

Procedia PDF Downloads 413

Authors: Silvia Tamayo-Moreno, Diana Pérez-Marín

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In this paper, the possibility of children studying by using an interactive learning technology called Pedagogic Conversational Agent is presented. The main benefit is that the agent is able to adapt the dialogue to each student and to provide automatic feedback. Moreover, according to Math teachers, in many cases students are unable to solve the problems even knowing the procedure to solve them, because they do not understand what they have to do. The hypothesis is that if students are helped to understand what they have to solve, they will be able to do it. Taken that into account, we have started the development of Dr. Roland, an agent to help students understand Math problems following a User-Centered Design methodology. The use of this methodology is proposed, for the first time, to design pedagogic agents to teach any subject from Secondary down to Pre-Primary education. The reason behind proposing a methodology is that while working on this project, we noticed the lack of literature to design and evaluate agents. To cover this gap, we describe how User-Centered Design can be applied, and which usability techniques can be applied to evaluate the agent.

Keywords: pedagogic conversational agent, human-computer interaction, user-centered design, natural language interface

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Authors: Hafid Smaili, Wilfred Rouwhorst, Paul Frost

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The trend of recent accident and incident cases worldwide show that the state-of-the-art automation and operations, for current and future demanding operational environments, does not provide the desired level of operational safety under crew peak workload conditions, specifically in complex situations such as loss-of-control in-flight (LOC-I). Today, the short term focus is on preparing crews to recognise and handle LOC-I situations through upset recovery training. This paper describes the cockpit integration aspects and piloted assessment of both a manually assisted and automatic upset detection and recovery system that has been developed and demonstrated within the European Advanced Cockpit for Reduction Of StreSs and workload (ACROSS) programme. The proposed system is a function that continuously monitors and intervenes when the aircraft enters an upset and provides either manually pilot-assisted guidance or takes over full control of the aircraft to recover from an upset. In order to mitigate the highly physical and psychological impact during aircraft upset events, the system provides new cockpit functionalities to support the pilot in recovering from any upset both manually assisted and automatically. A piloted simulator assessment was made in Oct-Nov 2015 using ten pilots in a representative civil large transport fly-by-wire aircraft in terms of the preference of the tested upset detection and recovery system configurations to reduce pilot workload, increase situational awareness and safe interaction with the manually assisted or automated modes. The piloted simulator evaluation of the upset detection and recovery system showed that the functionalities of the system are able to support pilots during an upset. The experiment showed that pilots are willing to rely on the guidance provided by the system during an upset. Thereby, it is important for pilots to see and understand what the aircraft is doing and trying to do especially in automatic modes. Comparing the manually assisted and the automatic recovery modes, the pilot’s opinion was that an automatic recovery reduces the workload so that they could perform a proper screening of the primary flight display. The results further show that the manually assisted recoveries, with recovery guidance cues on the cockpit primary flight display, reduced workload for severe upsets compared to today’s situation. The level of situation awareness was improved for automatic upset recoveries where the pilot could monitor what the system was trying to accomplish compared to automatic recovery modes without any guidance. An improvement in situation awareness was also noticeable with the manually assisted upset recovery functionalities as compared to the current non-assisted recovery procedures. This study shows that automatic upset detection and recovery functionalities are likely to positively impact the operational safety by means of reduced workload, improved situation awareness and crew stress reduction. It is thus believed that future developments for upset recovery guidance and loss-of-control prevention should focus on automatic recovery solutions.

Keywords: aircraft accidents, automatic flight control, loss-of-control, upset recovery

Procedia PDF Downloads 210

Authors: Farah Fazlinda Binti Mohamad, Ahmad Saifizul Abdullah, Mohamed Rehan Karim , Jamilah Mohamad, Siti Hikmah Musthar

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Road safety is an important issue in Malaysia. It become important as it is discussed widely throughout printed and electronic media. Most of the news portrays on road accident and fatalities have increased the concern of everyone. This issue affects everyone's life as everyone shares the roads. The most vulnerable victims are the road user who uses the roads every day. It is appalling when World Health Organization (WHO) reported that in every 100,000 of population in Malaysia, 23 fatalities recorded due to road accident alone. This figure is quite alarming and requires serious attention. Furthermore, research by Malaysian Institute of Road Safety Research concluded that that speeding has contributed to 60% of all road accident in the country. Therefore, this study aims to elucidate the factors that influence road users’ speeding behaviour on selected roads in Peninsular Malaysia. To achieve this, set of questionnaires has distributed to 500 respondents on selected roads in Peninsular Malaysia. The respondents came from various demographic backgrounds in order to have a fair opinion on the issue. Using descriptive analysis, the results have indicated that psychological factors such as emotion and attitude of road user are the prominent factors that influence the road user’s speeding behaviour. Furthermore, the results have shown that male road users were dominant in speeding compared to female, which led to increased vulnerability to road injuries and fatalities. These findings are very useful in order for us to understand road users’ driving behaviour. Relevant authorities should also revise the existing countermeasures and find ways to reduce road accident. Engineers and road experts could cooperate in designing new road specifications for the road user. Nevertheless, it is important to comprehend this speeding issue and factors associated with it. Each road user should take this matter seriously and responsibly as road safety is a responsibility of all.

Keywords: countermeasures, psychological, road safety, speeding

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Authors: Yara Bajnaid, Malak Zaidan, Eman Dakkak

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This research explores the use of Artificial Intelligence in Duolingo, a popular mobile application for language learning. Duolingo's success hinges on its gamified approach and adaptive learning system, both heavily reliant on AI functionalities. The research also analyzes user feedback regarding Duolingo's AI functionalities. While a significant majority (70%) consider Duolingo a reliable tool for language learning, there's room for improvement. Overall, AI plays a vital role in personalizing the learning journey and delivering interactive exercises. However, continuous improvement based on user feedback can further enhance the effectiveness of Duolingo's AI functionalities.

Keywords: AI, Duolingo, language learning, application

Procedia PDF Downloads 47

Authors: Julius Brejohn Calvert

Abstract:

This Study Aimed to Investigate the Ecological Nature of Extremism Online. The Construction of a Far-Right Ecosystem Was Successful Using a Sample of Posts, Each With Separate Narrative Domains. Most of the Content Expressed Anti-black Racism and Pro-white Sentiments. Many Posts Expressed an Overt Disdain for the Recent Progress Made Regarding the United States and the United Kingdom’s Expansion of Civil Liberties to People of Color (Poc). Of Special Note, Several Anti-lgbt Posts Targeted the Ongoing Political Grievances Expressed by the Transgender Community. Overall, the Current Study Is Able to Demonstrate That Direct Measures of User Engagement, Such as Shares and Reactions, Can Be Used to Predict the Effect of a Post’s Radicalization Capabilities, Although Single Posts Do Not Operate on the Cognitive Processes of Radicalization Alone. In This Analysis, the Data Supports a Theoretical Framework Where Individual Posts Have a Higher Radicalization Capability Based on the Amount of User Engagement (Both Indirect and Direct) It Receives.

Keywords: cognitive psychology, cognitive radicalization, extremism online, domestic extremism, political science, political psychology

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Authors: Dhiraj Neupane

Abstract:

Decentralized policy and practices have largely concentrated on the transformation of decision-making authorities from central to local institutions (or people) in the developing world. Such policy and practices always aimed for the equitable and efficient management of resources in the line of poverty reduction. The transformation of forest decision-making autonomy has also glorified as the best forest management alternatives to maximize the forest benefits and improve the livelihood of local people living nearby the forests. However, social heterogeneity and poor decision-making capacity of local institutions (or people) pose a nexus while managing the resources and sharing the forest benefits among the user households despite the policy objectives. The situation is severe in the lowland of Nepal, where forest resources have higher economic potential and user households have heterogeneous socio-economic conditions. The study discovered that utilizing the power of decision-making autonomy, user households were putting low values of timber considering the equitable access of timber to all user households as it is the most valuable product of community forest. Being the society is heterogeneous by socio-economic conditions, households of better economic conditions were always taking higher amount of forest benefits. The low valuation of timber has negative consequences on equitable benefit sharing and poor support to livelihood improvement of user households. Moreover, low valuation has possibility to increase the local demands of timber and increase the human pressure on forests.

Keywords: decentralized forest policy, Nepal, poverty, social heterogeneity, Terai

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Authors: Naman Jain, Shaun Fernandes

Abstract:

With the increasing prevalence of online healthcare services, selecting the most suitable doctor has become a complex task, requiring careful consideration of both public sentiment and personal preferences. This paper proposes a sentiment analysis-driven method that integrates public reviews with user-specific criteria and correlated attributes to recommend online doctors. By leveraging Natural Language Processing (NLP) techniques, public sentiment is extracted from online reviews, which is then combined with user-defined preferences such as specialty, years of experience, location, and consultation fees. Additionally, correlated attributes like education and certifications are incorporated to enhance the recommendation accuracy. Experimental results demonstrate that the proposed system significantly improves user satisfaction by providing personalized doctor recommendations that align with both public opinion and individual needs.

Keywords: sentiment analysis, online doctors, personal preferences, correlated attributes, recommendation system, healthcare, natural language processing

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Authors: Yen-Mei Lee

Abstract:

The concept of a knowledge-behavior gap has been discussed for several years. It is addressed that an individual’s knowledge does not sufficiently transfer to his or her actual actions. This concept is mostly focused on fields related to medicine or applied to health care issues to explain how people or patients connect their personal knowledge to actual health care behaviors. To our knowledge, seldomly has this research been applied to discuss people’s online information seeking behavior. In the current study, the main purpose is to investigate the relationship between web users’ personal values and their actual performances when seeking information on the Internet. The total number of twenty-eight participants, divided into one experienced group (n=14) and one novice group (n=14), were recruited and asked to complete a self-report questionnaire of fifty items related to information seeking actions and behaviors. During the execution, participants needed to rate the importance level (how important each item is) and the performance level (how often they actually do each item) from 1 to 10 points on each item. In this paper, the mean scores of the importance and the performance level are analyzed and discussed. The results show that there is a gap between web user’s knowledge and their actual online seeking behaviors. Both experienced group and novice group have higher average scores of the importance level (experienced group = 7.57, novice group = 6.01) than the actual performance level (experienced group = 6.89, novice group = 5.00) in terms of the fifty online information seeking actions. On the other hand, the experienced group perceives more importance of the fifty online seeking actions and performs actual behaviors better than the novice group. Moreover, experienced participants express a consistent result between their concept knowledge and actual behaviors. For instance, they feel extending a seeking strategy is important and frequently perform this action when seeking online. However, novice participants do not have a consistency between their knowledge and behaviors. For example, though they perceive browsing and judging information are less important than they get lost in the online information seeking process. However, in the actual behavior rating, the scores show that novices do browsing and judge information more often than they get lost when seeking information online. These results, therefore, help scholars and educators have a better understanding of the difference between experienced and novice web users regarding their concept knowledge and actual behaviors. In future study, figuring out how to narrow down the knowledge-behavior gap and create practical guidance for novice users to increase their online seeking efficiency is crucial. Not only could it help experienced users be aware of their actual information seeking behaviors, but also help the novice become mastery to concisely obtain information on the Internet.

Keywords: experienced web user, information seeking behavior, knowledge-behavior gap, novice, online seeking efficiency

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Authors: Amel Hannech, Mehdi Adda, Hamid Mcheick

Abstract:

In this paper, we propose a generic model of user profile integrating several elements that may positively impact the research process. We exploit the classical behavior of users and integrate a delimitation process of their research activities into several research sessions enriched with contextual and temporal information, which allows reflecting the current interests of these users in every period of time and infer data freshness. We argue that the annotation of resources gives more transparency on users' needs. It also strengthens social links among resources and users, and can so increase the scope of the user profile. Based on this idea, we integrate the social tagging practice in order to exploit the social users' behavior to enrich their profiles. These profiles are then integrated into a recommendation system in order to predict the interesting personalized items of users allowing to assist them in their researches and further enrich their profiles. In this recommendation, we provide users new research experiences.

Keywords: user profiles, topical ontology, contextual information, folksonomies, tags' clusters, data freshness, association rules, data recommendation

Procedia PDF Downloads 264

Authors: Vincent Ballola, Raymund Dilan, Thelma Palaoag

Abstract:

The Smart Online Library Catalog System with Query Expansion seeks to address the low usage of the library because of the emergence of the Internet. Library users are not accustomed to catalog systems that need a query to have the exact words without any mistakes for decent results to appear. The graphical user interface of the current system has a rather skewed learning curve for users to adapt with. With a simple graphical user interface inspired by Google, users can search quickly just by inputting their query and hitting the search button. Because of the query expansion techniques incorporated into the new system such as stemming, thesaurus search, and weighted search, users can have more efficient results from their query. The system will be adding the root words of the user's query to the query itself which will then be cross-referenced to a thesaurus database to search for any synonyms that will be added to the query. The results will then be arranged by the number of times the word has been searched. Online queries will also be added to the results for additional references. Users showed notable increases in efficiency and usability due to the familiar interface and query expansion techniques incorporated in the system. The simple yet familiar design led to a better user experience. Users also said that they would be more inclined in using the library because of the new system. The incorporation of query expansion techniques gives a notable increase of results to users that in turn gives them a wider range of resources found in the library. Used books mean more knowledge imparted to the users.

Keywords: query expansion, catalog system, stemming, weighted search, usability, thesaurus search

Procedia PDF Downloads 388