Semantic methods of intelligent assistant developing

This paper presents an adaptive e-learning system which supports collaborative learning based on a location-based social network and semantic modeling. In the system, a social network among e-learning learners is dynamically constructed on the basis of the location information of learners using GPS sensors for collaborative learning. In addition, user modeling for semantic social network and adaptive e-learning is supported. For these, a mechanism that supports the construction of a dynamic social network using the location information of smart phones is provided. The user modeling for the construction of a semantic social network and the support of adaptive e-learning considers the information such as the users' achievement, preference, and learning goal. Through this system, e-learners can find mentors who are able to facilitate their learning and create communities for collaborative learning offline and online. The support of a location-based social network service and semantic user model in our system would increase interactions among e-learners and improve satisfaction regarding their mobile learning environment.

Disabled people can benefit greatly from assistive digital technologies. However, this increased human-machine symbiosis makes it important that systems are personalized and transparent to users. Existing work often uses data-oriented approaches. However, these approaches lack transparency and make it hard to influence the system’s behavior. In this paper, we use knowledge-based techniques for personalization, introducing the concept of Semantic User Models for representing the behavior, values and capabilities of users. To allow the system to construct such a user model, we investigate the use of a conversational agent which can elicit the relevant information from users through dialogue. A conversational interface is essential for our case study of navigation support for visually impaired people, but in general, has the potential to enhance transparency as users know what the system represents about them. For such a dialogue to be effective, it is crucial that the user understands what the conversational agent is asking, i.e., that misalignments that decrease the transparency are avoided or resolved. In this paper, we investigate whether we can use a conversational agent for Semantic User Model elicitation, which types of misalignments can occur in this process and how they are related, and how misalignments can be reduced. We investigate this in two (iterative) qualitative studies (n = 7 & n = 8) with visually impaired people in which a personalized user model for navigation support is elicited via a dialogue with a conversational agent. Our results show four hierarchically structured levels of human-agent misalignment. We identify several design solutions for reducing misalignments, which point to the need for restricting the generic user model to what is needed in the domain under consideration. With this research, we lay a foundation for conversational agents capable of eliciting Semantic User Models.

The existing software engineering seldom considers software usability, and human-computer interaction (HCI) techniques which can improve the software usability cannot guarantee development efficiency. Recently, more and more stakeholders and users begin to regard the usability as an important software requirement. In order to bring respective advantages of software engineering and HCI techniques into full play to improve software usability and development efficiency, the paper presents user model driven software development, which integrates HCI techniques into software development method by eliciting user model under the participation of user, HCI designer and software engineer. Applications show that the method can be effectively applied to small software development team, and can raise software usability and development efficiency.

The selection of machining parameters is undertaken throughout the world on a daily basis. It remains an important activity that significantly impacts production cost. Alarmingly however, nearly all of this machining information is not recorded and there is a reliance on operators for its retention. To help address this problem, the present trend is to develop software systems able to record machining cycle data. However, this approach retains substantial data that is not optimal and a significant quantity of non-useful data is created. Selectivity provides a solution to the problem of data overload. This paper describes the structure, content, and relations employed in an intelligent grinding database developed to provide only selective and/or optimal data to the operator. The intelligent database was constructed in MS Access with Visual Basic support code. The database was developed as an integral feature of an intelligent grinding assistant (IGA©). The IGA© was implemented and evaluated on a cooperating partner’s CNC machine tool. The structure of the database is described in detail. An off-line feature to select grinding conditions for a workpiece material or workpiece dimension new to the database is also described. The offline feature was based on case-based reasoning (CBR) and rule-based reasoning (RBR).

ABSTRACT: The advancement of Artificial Intelligence (AI) and Natural Language Processing (NLP) has led to the development of voice- controlled systems that enhance Human–Computer Interaction (HCI). This paper presents the design and implementation of a Voice Controlled Desktop Assistant, capable of performing various tasks such as opening applications, searching the web, playing multimedia content, sending messages, and providing real-time system feedback. The assistant uses speech recognition for voice input and text- to-speech synthesis for generating responses. Developed using Python and integrated APIs, it aims to automate desktop functions through intuitive voice commands. The project demonstrates an effective approach for creating user-friendly, hands-free computing environments. Additionally, the system emphasizes lightweight processing to ensure efficient real-time performance without dependency on cloud-based services. It further contributes to the ongoing evolution of intelligent personal assistants designed for offline and secure desktop automation. KEYWORD: Voice Assistant, Artificial Intelligence, Natural Language Processing, Speech Recognition, Automation, Human– Computer Interaction. ABSTRACT: The advancement of Artificial Intelligence (AI) and Natural Language Processing (NLP) has led to the development of voice- controlled systems that enhance Human–Computer Interaction (HCI). This paper presents the design and implementation of a Voice Controlled Desktop Assistant, capable of performing various tasks such as opening applications, searching the web, playing multimedia content, sending messages, and providing real-time system feedback. The assistant uses speech recognition for voice input and text- to-speech synthesis for generating responses. Developed using Python and integrated APIs, it aims to automate desktop functions through intuitive voice commands. The project demonstrates an effective approach for creating user-friendly, hands-free computing environments. Additionally, the system emphasizes lightweight processing to ensure efficient real-time performance without dependency on cloud-based services. It further contributes to the ongoing evolution of intelligent personal assistants designed for offline and secure desktop automation. KEYWORD: Voice Assistant, Artificial Intelligence, Natural Language Processing, Speech Recognition, Automation, Human– Computer Interaction.

One of the most urgent problems of natural language processing -formalization and creation ontological models of subject domains based on the text corpora is considered. In this work, a new approach for determining the weights of links in the network of terms that correspond to certain concepts of the considered subject domain is considered. In particular, applying the proposed approach for determining the weights of links in the network of terms, the terminological ontology of the subject domain that related to an ecological footprint was created as an approbation. Further analysis of the created model made it possible to determine the most influential and significant links between the corresponding nodes in the network of terms that in turn correspond to certain concepts of the considered subject domain. The proposed and considered approaches and methods were programmed and using the software for modeling and visualization of graphs – Gephi the built directed networks of terms were visualized for better visual perception. The weighted directed networks of terms built according to the proposed approach can be used for automatically creating terminological ontologies of subject domains with the participation of experts. Also, the research result can be used to create personal search interfaces for users of information retrieval systems and also can be used in navigation systems in data-bases. It should help users of such systems simplify the process of searching the relevant information.

Guidelines to the Requirement engineering along with the Agile team regarding improvement of Agile practices incorporated with Case based reasoning (CBR). Context: Applying Artificial Intelligence (AI) techniques on Agile practices to software development have acknowledged slight attention until now. Objective: In this research, we present a model which has been introduced for evolution of the Agile Software Development practices by using AI technique. Method: In this research, we have used published reports, articles, and existing case studies. Expert’s review method is used to accomplish the appraisal of this model. Result: This model has been resulted in improving the agile practices by using the concept of CBR. An addition to the SCRUM process it is beneficial to cope with reusability of requirements solutions in an Agile Development environment. Conclusion: The framework provides guidelines to the requirement engineering and also to the agile team regarding improvement of agile practices incorporated with CBR.

Many software development companies, especially small and medium-sized ones, still need to be more aware of and understand Human–Computer Interaction (HCI) values, methods, techniques, and concepts. Recent studies have shown that companies are demanding internal self-assessment of HCI practices within the software development industry. However, only a few models are available for assessing HCI practices, and they lack sufficient validation to be widely applicable. The models are mainly based on staged assessments by experts, but continuous representation models are more suitable for self-assessment. To bridge these gaps, we have developed a new process model, HCI Reflect—a self-assessment method, and structurally assessed it as a model encompassing four dimensions for self-assessing HCI practices in software development companies: human-centeredness, process and infrastructure, usability performance, and usability impact. In this article, we present the model’s theoretical foundation and the results from an international assessment study of the first version of the model, where 118 software development professionals evaluated the model’s four dimensions. The results demonstrated the significance of these dimensions, and based on this, we present a revised version. The development and assessment are the first steps towards the validation of the model, and we plan to test the underlying questionnaire for usability next. The model, when validated, would be helpful for self-assessing HCI practices in software development companies to foster knowledge and understanding of HCI practices in development teams. ACM CCS: Human-centered computing— > Human computer interaction (HCI)— > HCI design and evaluation methods.

Intelligent design assistant (IDA): a case base reasoning system for material and design

Individuals with specific learning difficulties such as dyslexia have below-average learning performance. The state regulations require such learners to be integrated in public schools, but they need specific teaching methods, additional lessons with specially trained teachers, etc. We present a conceptual model of environment for facilities development that serves teachers in providing personalized e-teaching (Fig. 1). The model of Subject Domain (SD) defines a framework for educational process in two aspects – psychologists’ and educators’. The teacher’s representation of SD is goal-oriented. It determines basic requirements to e-learning facilities. The model Cognitive Ability shows the specific cognitive abilities necessary for achievement of main educational objectives in a concrete subject. They are fixed through mapping SD description on the basic human cognitive abilities. In that way a learner’s cognitive profile is determined by adequate to this SD learning characteristics. Model Pedagogical Room designs suitable methodology for learning activities in interaction with the models Teaching Methods and Pedagogical Instruments. The model Teaching − Learning Goals, which depends on the corresponding SD educational goals, influences on the aforesaid two models. The models are context-independent (global), so the learning facilities’ production requires contextualization. The model Learner serves for personalization.

The MPS for Software reference model (MR-MPSSW) is one of the models currently used in Brazilian industry. This software process capability maturity (SPCM) model describes Software Engineering (SE) practices that are applied in the software development by the use of approaches (such as methods, techniques and so on). The Human-Computer Interaction (HCI) community has defined specific approaches (methods, techniques, patterns, and standards) for the conception, design, implementation, and evaluation of interactive systems development. Nevertheless, the literature points out that those approaches are not sufficiently used in industry. Taking advantage of the large use of SPCM models, we have identified HCI approaches that could support SPCM practices related to five processes (Requirements Development, Design and Construction of the Product, Product Integration, Verification and Validation) advocated by the MR-MPS-SW. Analyzing the HCI literature and MR-MPS-SW, we identified a set of HCI approaches for interactive systems development. We interviewed twenty HCI experts to validate and improve this initial set. Thus, we identified 14 HCI categories with examples of methods, techniques, patterns, and standards adequate for performing SE practices of the MR-MPS-SW when developing interactive systems.

A human's words, facial expressions, gestures, tone of voice, and even keyboard force can all be used in conjunction with artificial intelligence technologies to perform emotion intelligence (EI) identification. The development of artificial emotional intelligence has made it possible for people and robots to interact in a manner that is more natural, similar to the way that humans engage with one another. The expansion of the internet of things and wearable technology has a positive impact on the development of emotion detection software in the healthcare sector. This system contributes to society by making use of many forms of technology. There is always going to be a trade-off between price and functionality. The development of software with emotional intelligence relies on the collection of extensive datasets and the development of reliable modelling techniques. This chapter uses case studies, computing, and AI-based research methods to analyze emotional intelligence systems and their effects on human-computer interaction in the healthcare sector.

What's the relationship between the new communicative technology and the society? Instead of a macro perspective, this article tries to use a micro perspective to analyze human-computer interaction. By the micro analysis, I answer the question of how to design human-computer interface. This article focuses on a new technology, the Skype's webcam, and uses affordance theory to examine biological and cultural constraints and creativities. The examination focuses on the nonverbal communicative element-gaze. How do people change their visual perception and the rules of interaction? How do people create embodied interaction and new rules? The data transcribes the conversation and gaze in the use of Skype. The research finds that special media space influences people's visual perception and changes the ways of communication. The human- computer interaction designers should be concerned about these issues. Finally, this article tries to answer the basic question of communication, i.e., where the meaning is from. Language is no longer the privileged communicative element in new technology. Verbal and nonverbal elements intertwine with each other in the symphony of meanings. No element is more important than another. This article emphasizes the importance of nonverbal communicative element in human-computer interaction interface design.

An empirical validation of a neural network model for software effort estimation

We describe how an environment can be extended to support the process of software development. Our approach is based on the AI planning paradigm. Processes are formally defined hierarchically via plan operators, using multiple levels of abstraction. Plans are constructed dynamically from the operators; the sequences of actions in plans are tailored to the context of their use, and conflicts among actions are prevented. Monitoring of the development process, to detect and avert process errors, is accomplished by plan recognition ; this establishes a context in which programmer-selected goals can be automated via plan generation . We also show how nonmonotonic reasoning can be used to make an independent assessment of the credibility of complex process alternatives, and yet accede to the programmer's superior judgment. This extension to intelligent assistance provides deeper understanding of software processes.