A Survey on End-User Robot Programming

As robots interact with a broader range of end-users, end-user robot programming has helped democratize robot programming by empowering end-users who may not have experience in robot programming to customize robots to meet their individual contextual needs. This article surveys work on end-user robot programming, with a focus on end-user program specification. It describes the primary domains, programming phases, and design choices represented by the end-user robot programming literature. The survey concludes by highlighting open directions for further investigation to enhance and widen the reach of end-user robot programming systems.

GeCoAgent: A Conversational Agent for Empowering Genomic Data Extraction and Analysis

With the availability of reliable and low-cost DNA sequencing, human genomics is relevant to a growing number of end-users, including biologists and clinicians. Typical interactions require applying comparative data analysis to huge repositories of genomic information for building new knowledge, taking advantage of the latest findings in applied genomics for healthcare. Powerful technology for data extraction and analysis is available, but broad use of the technology is hampered by the complexity of accessing such methods and tools. This work presents GeCoAgent, a big-data service for clinicians and biologists. GeCoAgent uses a dialogic interface, animated by a chatbot, for supporting the end-users’ interaction with computational tools accompanied by multi-modal support. While the dialogue progresses, the user is accompanied in extracting the relevant data from repositories and then performing data analysis, which often requires the use of statistical methods or machine learning. Results are returned using simple representations (spreadsheets and graphics), while at the end of a session the dialogue is summarized in textual format. The innovation presented in this article is concerned with not only the delivery of a new tool but also our novel approach to conversational technologies, potentially extensible to other healthcare domains or to general data science.

The Ultimate Bond

Being introduced in India in 1956 as an easy –to-use white glue for carpenters in replacement of Saresh (fat-based adhesives), the ULTIBOND company started its journey and never looked back. As The ULTIBOND Company was well known to recognize the need of their product and convert it into a marvelous opportunity, the company started manufacturing AI glue products for students as well as for professional and educational institutes. In order to shift end-users from natural glues and other synthetic adhesives available at the time, AI glue embarked on a bold marketing game plan. Instead of selling through stores, AI glue approached carpenters directly. This direct marketing initiative was one of the most successful strategies employed by the company and helped the brand gain a strong foothold in the white glue market. By 1965, the brand was big enough to develop its own manufacturing plant in Maharashtra. Primarily the company decided to enter into the retail market with a packaging of 33 grams collapsible tube in early 1970’s, later came up with many other unique packaging styles to cater the need and requirements of different segments of its customer base.

Saluran Distribusi Pemasaran Asuransi

Product distribution is one of the marketing process's activities. Many product manufacturers do not sell to end users directly. This is due to the fact that cost distribution is typically the primary reason corporations do not sell items to end customers. The marketing channel is in charge of getting the product from the manufacturer (the insurance company) to the consumer/customer. This can overcome the owner of a product or service's isolation from the people who require it in terms of time, location, and property. This marketing channel, in reality, necessitates product marketing channel management in compliance with OJK standards. In addition, any rivalry that emerges in the marketing channel while selling insurance goods. As a result, the goal of this article is to go into detail about the marketing channels for insurance products in public marketing. Keywords: Marketing Channels, Distribution, Insurance

Cyber Attacks Visualization and Prediction in Complex Multi-Stage Network

In network security, various protocols exist, but these cannot be said to be secure. Moreover, is not easy to train the end-users, and this process is time-consuming as well. It can be said this way, that it takes much time for an individual to become a good cybersecurity professional. Many hackers and illegal agents try to take advantage of the vulnerabilities through various incremental penetrations that can compromise the critical systems. The conventional tools available for this purpose are not enough to handle things as desired. Risks are always present, and with dynamically evolving networks, they are very likely to lead to serious incidents. This research work has proposed a model to visualize and predict cyber-attacks in complex, multilayered networks. The calculation will correspond to the cyber software vulnerabilities in the networks within the specific domain. All the available network security conditions and the possible places where an attacker can exploit the system are summarized.

End-User Perspectives on Using Quantitative Real-Time PCR and Genomic Sequencing in the Field

Quantitative real-time PCR and genomic sequencing have become mainstays for performing molecular detection of biological threat agents in the field. There are notional assessments of the benefits, disadvantages, and challenges that each of these technologies offers according to findings in the literature. However, direct comparison between these two technologies in the context of field-forward operations is lacking. Most market surveys, whether published in print form or provided online, are directed to product manufacturers who can address their respective specifications and operations. One method for comparing these technologies is surveying end-users who are best suited for discussing operational capabilities, as they have hands-on experience with state-of-the-art molecular detection platforms and protocols. These end-users include operators in military defense and first response, as well as various research scientists in the public sector such as government and service laboratories, private sector, and civil society such as academia and nonprofit organizations performing method development and executing these protocols in the field. Our objective was to initiate a survey specific to end-users and their feedback. We developed a questionnaire that asked respondents to (1) determine what technologies they currently use, (2) identify the settings where the technologies are used, whether lab-based or field-forward, and (3) rate the technologies according to a set list of criteria. Of particular interest are assessments of sensitivity, specificity, reproducibility, scalability, portability, and discovery power. This article summarizes the findings from the end-user perspective, highlighting technical and operational challenges.

A Contract Service Provider Model for Virtual Assets

With the recent rise in the cost of transactions on blockchain platforms, there is a need to explore other service models that may provide a more predictable cost to customers and end-users. We discuss the Contract Service Provider (CSP) model as a counterpart of the successful Internet Service Provider (ISP) model. Similar to the ISP business model based on peered routing-networks, the CSP business model is based on multiple CSP entities forming a CSP Community or group offering a contract service for specific types of virtual assets. We discuss the contract domain construct which encapsulates well-defined smart contract primitives, policies and contract-ledger. We offer a number of design principles borrowed from the design principles of the Internet architecture.

Context-Aware End-User Development Review

Context-aware application development frameworks enable context management and environment adaptation to automatize people’s activities. New technologies such as 5G and the Internet of Things (IoT) increase environment context (from devices/services), making functionalities available to augment context-aware applications. The result is an increased deployment of context-aware applications to support end-users in everyday activities. However, developing applications in context-aware frameworks involve diverse technologies, so that it traditionally involves software experts. In general, context-aware applications are limited in terms of personalization for end-users. They include configurations to personalize applications, but non-software experts can only change some of these configurations. Nowadays, advances in human–computer interaction provide techniques/metaphors to approach non-software experts. One approach is end-user development (EUD)—a set of activities and development tools that considers non-software experts as application builders. In this paper, we present our analysis of existing EUD approaches for building context-aware applications. We present a literature review of 37 screened papers obtained from research databases. This review aims to identify the methods, techniques, and tools proposed to build context-aware applications. Specifically, we reviewed EUD building techniques and implementations. Building techniques include metaphors/interaction styles proposed for application specification, composition, and testing. The implementations include a specification method to integrate and process context on the target application platforms. We also present the adoption trend and challenges of context-aware end-user development.

Participatory Design and Process Testing to Optimize Utility, Usability, and Acceptability of a Mobile Game for Promoting Evidence-Driven Public Health Decision-Making in Resource-Constrained Settings

Innovative game-based training methods that leverage the ubiquity of cellphones and familiarity with phone-based interfaces have the potential to transform the training of public health practitioners in low-income countries such as Liberia. This article describes the design, development, and testing of a prototype of the Figure It Out mobile game. The prototype game uses a disease outbreak scenario to promote evidence-based decision-making in determining the causative agent and prescribing intervention measures to minimize epidemiological and logistical burdens in resource-limited settings. An initial prototype of the game developed by the US team was playtested and evaluated by focus groups with 20 University of Liberia Masters of Public Health (UL MPH) students. Results demonstrate that the learning objectives—improving search skills for identifying scientific evidence and considering evidence before decision-making during a public health emergency—were considered relevant and important in a setting that has repeatedly and recently experienced severe threats to public health. However, some of the game mechanics that were thought to enhance engagement such as trial-and-error and choose-your-own-path gameplay, were perceived by the target audience as distracting or too time-consuming, particularly in the context of a realistic emergency scenario. Gameplay metrics that mimicked real-world situations around lives lost, money spent, and time constraints during public health outbreaks were identified as relatable and necessary considerations. Our findings reflect cultural differences between the game development team and end users that have emphasized the need for end users to have an integral part of the design team; this formative evaluation has critically informed next steps in the iterative development process. Our multidisciplinary, cross-cultural and cross-national design team will be guided by Liberia-based public health students and faculty, as well as community members who represent our end user population in terms of experience and needs. These stakeholders will make key decisions regarding game objectives and mechanics, to be vetted and implemented by game design experts, epidemiologists, and software developers.

Informed Decision Making on the Uptake of Evidence-Based Smoking Cessation Assistance by Individuals Motivated to Quit Smoking

Evidence-based cessation assistance increases cessation rates. Activating preferences during decision making could improve effectiveness further. Decision aids (DAs) facilitate deciding by taking preferences into account. To develop effective DAs, potential end users' (i.e., individuals motivated to quit) needs and experts' viewpoints should be considered. Therefore, the aim of this needs assessment was: (1) To explore end users' needs and (2) to obtain consensus among smoking cessation counsellors and scientific experts to develop a self-administered DA to support end users in choosing cessation assistance. Data was gathered via two approaches: (1) twenty semi-structured interviews with potential end users and (2) two three-round Delphi studies with 61 counsellors and 44 scientific experts. Interview data and the first Delphi rounds were analysed qualitatively, the other Delphi rounds were analysed quantitatively. Potential end users acquired information in different ways, e.g., via own experiences. Important characteristics to decide between tools varied, however effectiveness and costs were commonly reported. Experts reached consensus on 38 and 40 statements, e.g., tools should be appropriate for users' addiction level. Although some trends emerged, due to the variation among stakeholders, a 'one size fits all'-approach is undesirable. This heterogeneity should be considered, e.g., by enabling users to customise the DA.