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User studies have been conducted for many years in the information and library science fields. In the archival world, this phenomenon has not been as common and less emphasis has been placed on collecting and studying the user's perspective in general. However, there are studies showing the use of these types of studies, particularly in the justification for, and explanation of, archival resources. This review article will present the literature on user studies of archival finding aids, while incorporating some of the preliminary user theory that led to, and resulted from, archival user studies. It will then focus more specifically on Encoded Archival Description (EAD) finding aids, arguing that the lack of user studies in EAD has been a possible determinant to the more widespread acceptance of this descriptive standard among archivists. Have some well-intentioned archivists prematurely put the under-developed cart before fine-tuning the horse? Perhaps this will prove harmless in the long run, not alienating users from future online archival displays that use EAD. Perhaps users will easily learn how to use EAD finding aids and come to appreciate their unique qualities. This article explores what archival colleagues think and what they are advocating.

Interactive expert support for early stage full-year daylighting design: A user's perspective on Lightsolve

Semantic linking has a potential to enrich the audiovisual experience for users of television or radio broadcast archives. Recently, automatic semantic linking, has received increased attention, especially as second screen applications for television broadcasts are emerging. Semantic linking for radio broadcasts can enrich radio listening experience in a similar manner in combination with second screen-like applications. While the development of such applications is gaining popularity, little is known about the information in a radio program that may be interesting for link creation from a user perspective. We conducted a user study on semantic linking for radio broadcasts in order to know what information users regard as suitable anchors and what kind of information they like as targets. We found that users often regard topic and person as the best link anchors in the program. Additionally, we found that frequency and timing of information elements in a radio program do not dominate the users' selection of anchors. Furthermore, we found that there is a low agreement among users on regarding certain information elements as anchors. For practical reasons the study is conducted with 10 minutes of radio broadcast material of a particular program type, and with a total of 22 participants. The insights gained in the user study will help the understanding of user perspectives on semantic linking in the audio domain.

In this paper, we present Agent Assist, a virtual assistant which helps IT support staff to resolve tickets faster. It is essentially a conversation system which provides procedural and often complex answers to queries. This system can ingest knowledge from various sources like application documentation, ticket management systems and knowledge transfer video recordings. It uses an ensemble of techniques like question classification, knowledge graph based disambiguation, information retrieval, etc., to provide quick and relevant solutions to problems from various technical domains and is currently being used in more than 650 projects within IBM.

Virtual assistant is nothing but an independent contractor, who offers administrative services to the clients of a particular organisation while operating outside of the office of the client. Generally, a virtual assistant operates from a home-based office. This virtual assistant application has the ability to access the required planning documents, such as shared calendars. The contemporary retail organisations like e-commerce companies in this competitive global business environment are using virtual assistant to enhance omnichannel experience, 24/7 customer service, order tracking, and product recommendations. Overall, virtual assistant helps the organisations in enhancing social media management activities. This concept of the use of virtual assistant has been significantly emerged after the increase in demands for e-commerce business activities in this decade. Research objectives related to the title of this research are developed and listed. Relevant theories on virtual assistant are applied in the literature review section of this study. The researcher has decided to adopt qualitative research methodology to achieve the objectives of the research. Moreover, the researcher has considered secondary data analysis approach to conduct this research. In terms of findings, it has been identified that virtual assistant has a positive impact on the business operation activities of retail organisations. Authentic secondary sources are considered to collect and analyse the data. Some challenges associated with the utilisation of virtual assistant also have been identified in the findings section. Some valuable recommendations are suggested for the future researchers to overcome those identified associated challenges.

Customer service and engagement activities have significantly changed as a result of the growing use of chatbots and virtual assistants in the field of modern marketing. By leveraging these artificial intelligence-powered technologies, businesses can provide clients with customized interactions that happen in real-time. As a result, the standard of the client experience is raised overall. Chatbots can decrease response times and boost efficiency and effectiveness by automating routine questions and providing timely answers. As a result, this allows companies to interact with a far wider audience without sacrificing the caliber of their connections with those people. Furthermore, virtual assistants may comprehend and manage intricate questions from customers, providing customized solutions meant to encourage client loyalty and satisfaction. This study investigates how customer behavior, business operations, and overall marketing tactics have been impacted by chatbots and virtual assistants. The essay also looks at how chatbots and virtual assistants have affected customer service departments in the marketing business and how this has altered customer service delivery. This research aims to illustrate the notable advantages and possible obstacles that come with integrating these technologies within the scope of customer service. This goal will be accomplished by evaluating current advances, case studies, and technological breakthroughs.

Conversational Agents are increasingly integrated into our daily routines, assisting us with various tasks, from simple commands such as scheduling events to more complex conversational search interactions. Such conversational search systems are traditionally evaluated with word-overlap metrics such as F1 score and accuracy. The full-day workshop on Search-Oriented Conversational Artificial Intelligence (SCAI) at CHIIR 2024 explored the evaluation of conversational search systems from the user's perspective. This interactive workshop included multiple panel discussions and working groups focused on developing and discussing innovative, user-centered evaluation methods for these systems. This paper, co-authored by both organizers and participants of the workshop, presents a summary of the insights gathered from the panel discussions and working groups. Date : 14 March 2024. Website : https://scai.info/scai-2024/.

Natural Language Processing (NLP) involves the use of algorithms and models and various computational techniques to analyze, process, and generate natural language data, including speech and text. NLP helps computers interact with humans in a more natural way, which has become increasingly important as more humancomputer interactions take place. NLP allows machines to process and analyze voluminous unstructured data, including social media posts, newspaper articles, reviews from customers, emails, and others. It helps organizations extract insights, automate tasks, and improve decision-making by enabling machines to understand and generate human-like language. A linguistic background is essential for understanding NLP. Linguistic theories and models help in developing NLU systems, as NLP specialists need to understand the structure and rules of language. NLU systems are organized into different components, including language modelling, parsing, and semantic analysis. NLU systems may be assessed through the use of metrics that includes measures like precision and recall, as well as indicators that convey meaningful information that include F1 score and others. Semantics and knowledge representation are central to NLU, as they involve understanding the meaning of words and sentences and representing this information in a way that machines can use. Approaches to knowledge representation include semantic networks, ontologies, and vector embeddings. Language modelling is an essential step in NLP that sees usage in applications like speech recognition, text generation, and text completion and also in areas such as machine translation. Ambiguity Resolution remains a major challenge in NLP, as language is often ambiguous and context-dependent. Some common applications of NLP include sentiment analysis, chatbots, virtual assistants, machine translation, speech recognition, text classification, text summarization, and information extraction. In this chapter, we show the applicability of a popular unsupervised learning technique, viz., clustering through K-Means. The efficiency provided by the K-Means algorithm can be improved through the use of an optimization loop. The prospects for NLP are promising, with an increasing demand for AI-powered language technologies in various industries, including healthcare, finance, and e-commerce. There is also a growing need for ethical and responsible AI systems that are transparent and accountable.

We present a novel Mixed Reality (MR) remote collaboration system that integrates a telepresence drone to overcome viewpoint limitations in previous approaches. Current remote collaboration systems often restrict remote users to the local user's perspective or a fixed viewpoint, which may reduce spatial awareness and collaboration effectiveness. Our proposed system enables a remote user wearing a VR headset to independently navigate the local environment through a drone while guiding a local AR headset user. The drone represents the remote user physically and virtually with an AR avatar. The system provides the remote user with a 3D reconstruction of the local environment, the local user's avatar, and real-time drone camera video to facilitate drone operation and collaboration. A user study comparing our drone-enhanced MR system with 2D video and 360-degree video MR systems during inspection tasks revealed that the telepresence drone significantly improved collaboration efficiency and enhanced users' social presence and spatial presence. However, the remote users perceived a higher workload. Our findings demonstrate the benefits of independent spatial navigation through drones in remote collaboration and offer insights for future drone-enhanced MR remote collaboration systems.

The increasing demand to customize vehicles and thus the higher product variety affects the workplaces at the automobile industry. The work tasks become more complex due to an increasing information density and modern production technologies, i.e. robots, linked production facilities and the progress towards the digitalization of production steps. Assistive information systems, that provide relevant information to the worker, have been widely researched, but there is little research on evaluating working stations beforehand regarding their potential of implementing assistive systems. Within this paper, we propose a modified application of a standard evaluation method for comparing different representatives of assistive systems, i.e. paper instructions, IT glasses and hand-held devices. Based on a user study at a manual assembly workplace, we compare these assistive systems. Using the Methods-Time Measurement method for comparison, our results reveal that the IT glass and the tablet, as the representatives for IT-supported systems, lead to significant faster task completions and significant differences in the information processes compared to the paper-based instructions. Additional questionnaires concerning the cognitive load and the assessment of the assistive systems regarding the ease of use, level of satisfaction and performance, support the previous findings.

Hiring new student employees is a task that many IT help desks face every semester, and finding quality applicants can often be a chore. How do you pick the best candidates from a pool where everyone seems so similar?The interview process at the CITES Help Desk at the University of Illinois at Urbana-Champaign has been designed to accomplish two things. The first goal is to get to know the applicant and ascertain whether they would be a good fit for the Help Desk. The second is to sell the Help Desk's role on our campus. If the applicant isn't buying our customer service philosophy, we can avoid later headaches.Our three-part interview weaves together both these goals. Students are asked to complete a hands-on technical portion, a rapid-fire Q&A about IT services on campus and then answer some scenario based questions. Each piece gives us an idea of the applicant's knowledge, poise, attitude, communication abilities and customer service skills. But, we can also learn a lot about the applicant from the subtleties. Does the number of tabs they open in a browser matter? What does their choice of search engine tell us? Do they show composure during the walk down the long, awkward hallway on the way to the interview room? These questions and answers help us get into the head of the applicant.This paper will explore the interview questions we ask and the answers that give us the best impressions of an applicant. We'll also discuss the little things that may go unnoticed that can add up to make the difference between hiring or passing on an applicant.

Many art forms present visual content as a single image captured from a particular viewpoint. How to select a meaningful representative moment from an action performance is difficult, even for an experienced artist. Often, a well-picked image can tell a story properly. This is important for a range of narrative scenarios, such as journalists reporting breaking news, scholars presenting their research, or artists crafting artworks. We address the underlying structures and mechanisms of a pictorial narrative with a new concept, called the action snapshot, which automates the process of generating a meaningful snapshot (a single still image) from an input of scene sequences. The input of dynamic scenes could include several interactive characters who are fully animated. We propose a novel method based on information theory to quantitatively evaluate the information contained in a pose. Taking the selected top postures as input, a convolutional neural network is constructed and trained with the method of deep reinforcement learning to select a single viewpoint, which maximally conveys the information of the sequence. User studies are conducted to experimentally compare the computer-selected poses and viewpoints with those selected by human participants. The results show that the proposed method can assist the selection of the most informative snapshot effectively from animation-intensive scenarios.

Cognitive assistance of a rollator (wheeled walker) user tends to reduce the attentional capacity of the user and may impact her stability. Hence, it is important to understand and track the pose of rollator users before augmenting a rollator with some form of cognitive assistance. While the majority of current markerless vision systems focus on estimating 2D and 3D walking motion in the sagittal plane, we wish to estimate the 3D pose of rollator users' lower limbs from observing image sequences in the coronal (frontal) plane. Our apparatus poses a unique set of challenges: a single monocular view of only the lower limbs and a frontal perspective of the rollator user. Since motion in the coronal plane is relatively subtle, we explore multiple cues within a Bayesian probabilistic framework to formulate a posterior estimate for a given subject's leg limbs. In this work, our focus is on evaluating the appearance model (the cues). Preliminary experiments indicate that texture and colour cues conditioned on the appearance of a rollator user outperform more general cues, at the cost of manually initializing the appearance offline.

BackgroundIt is important to involve older people in evaluating public programmes that affect their lives. This includes those with physical and cognitive impairments (such as dementia) who may need support to live at home. Many countries have implemented new approaches to support older people to live well at home for longer. However, it can be challenging to involve disabled people in service evaluation, so we are unclear whether services are meeting their needs.AimThis study explored how a cascading methodology, offering different supports enabled the involvement of home care users with cognitive and physical impairments in the assessment of their care‐related quality of life.MethodWe used multiple tools from the Adult Social Care Outcomes Toolkit (ASCOT) with n = 63 older adults who were recipients of home care in the Illawarra. We also offered different physical and cognitive supports as needed.ResultsWe started with the standard ASCOT questionnaire to assess the care‐related quality of life, but then offered alternative formats (including Easy Read) and supports (including physical and cognitive assistance) if the older person needed them to participate. This allowed us to involve a greater diversity of older people in the evaluation, and changed what we found out about whether their care needs were being met.ConclusionThere is a need to implement more flexible and inclusive methods to increase the involvement of vulnerable users of long‐term care in the assessment of service outcomes. This is important to ensure that the perspectives of all service users inform the delivery of person‐centred care. It is also critical to understand the extent to which programmes are meeting the needs of vulnerable service users.Patient or Public ContributionService users with dementia were involved in the design of the ‘Easy Read’ questionnaire used in the study.

The rapid digitalization of the world has affected engineering and design in a variety of ways, including the introduction of new computer-aided ideation tools. Cognitive assistants (CA), an increasingly common digital technology, use natural-language processing and artificial intelligence to provide computational support. Because CAs are capable of emulating humans in some tasks, they may be suited to support ideation activities when trained coaches or facilitators are not available. However, the effects and perception of CA-facilitated ideation are not fully understood. This study compared co-located brainstorming groups facilitated by human facilitators and a CA facilitator. We found that human facilitation was associated with the blocks/interruptions state because they used these moments to initiate facilitation; conversely, cognitive assistant facilitation was associated with the deviations and silence state. Human facilitation was also found to produce a more equal distribution of speaking time. Finally, post-task interviews showed that participants became frustrated due to the lack of affordances to indicate the status and functionality of the device.