Fuzzy Cognitive Map based Prediction Tool for Schedule Overrun

The main aim of any software development organizations is to finish the project within acceptable or customary schedule and budget Software schedule overrun is one of a question that needs more concentration Schedule overrun may affect the whole project success like cost quality and increases risks Schedule overrun can be reason of project failure In today s competitive world controlling the schedule slippage of software project development is a challenging task Effective handling of schedule is an essential need for any software project organization The main tasks for software development estimation are determining the effort cost and schedule of developing the project under consideration Underestimation of project done knowingly just to win contract results into loses and also the poor quality project So precise schedule prediction leads to efficient control of time and budget during software development In this paper we developed a new technique for the prediction of schedule overrun This paper also presents the comparison with other algorithms of schedule estimation and Tool developed by us and at last proved that Fuzzy cognitive map based prediction tool gives more accurate results than other training algorithm

ICE-B 2010:proceedings of the International Conference on e-Business

The International Conference on e-Business, ICE-B 2010, aims at bringing together researchers and practitioners who are interested in e-Business technology and its current applications. The mentioned technology relates not only to more low-level technological issues, such as technology platforms and web services, but also to some higher-level issues, such as context awareness and enterprise models, and also the peculiarities of different possible applications of such technology. These are all areas of theoretical and practical importance within the broad scope of e-Business, whose growing importance can be seen from the increasing interest of the IT research community. The areas of the current conference are: (i) e-Business applications; (ii) Enterprise engineering; (iii) Mobility; (iv) Business collaboration and e-Services; (v) Technology platforms. Contributions vary from research-driven to being more practical oriented, reflecting innovative results in the mentioned areas. ICE-B 2010 received 66 submissions, of which 9% were accepted as full papers. Additionally, 27% were presented as short papers and 17% as posters. All papers presented at the conference venue were included in the SciTePress Digital Library. Revised best papers are published by Springer-Verlag in a CCIS Series book

How chatbots are used in recruitment and selection practices?

In the modern era, Artificial Intelligence (AI) has affected different functions of businesses, including Human Resources, in recruitment processes. With Chatbots (conversational agents) systems in place, HR can perform tasks like identifying, selecting, and interviewing talented candidates with more speed and consequently focus on strategic goals more effectively. This study aims to assess the current state of chatbot usage in HR processes in organisations, particularly in Higher Education Institutions (HEIs). For Part Ⅰ, the chatbot’s role is evaluated in detail for each stage of recruitment (i.e., sourcing, screening, selection and onboarding of candidates). Moreover, we will discuss how chatbot providers develop this service in terms of needed technical technologies and communicational aspects. The findings will help identify the best practices in developing better chatbots that align with the demands of modern hiring. In addition, we investigate chatbots’ impact on higher education with the rise of online learning and the Covid-19 pandemic. In part two, we develop a chatbot using the Google DialogFlow platform to support the admission process for prospective PhD students in the Doctoral Management Program of the UPC. This FAQ bot will be implemented as a supplementary channel in the doctoral program website to understand students’ queries and provide predefined answers. A survey is conducted based on the TAM framework to assess the chatbot’s functionality, quality, and intention of use. Based on the responses and findings, we will discuss how chatbots are a viable option to create new innovative services that are helpful for both candidates and educators. In the end, based on lessons learned, we propose conclusions, discussion and several recommendations for these intelligent systems. It is hoped that this work will open up new research possibilities for future optimisations in the fields of chatbots and recruitment in the future.En la era moderna, la Inteligencia Artificial (IA) ha afectado a diferentes funciones de las empresas, incluida la de Recursos Humanos, en los procesos de contratación. Con los sistemas de Chatbots (agentes conversacionales) implementados, HR puede realiza r tareas como identificar, seleccionar y entrevistar a personas candidat as talentos a s con más velocidad y, en consecuencia, enfocarse en objetivos estratégicos de manera más efectiva. Este estudio tiene como objetivo evaluar el estado actual del uso de chatbots en los procesos de recursos humanos en las organizaciones, particularmente en las Instituciones de Educación Superior (IES). Para la Parte Ⅰ, el rol del chatbot se evalúa en detalle para cada etapa del reclutamiento (i.e., planificación, abastecimiento, selec ción, verificación de referencias, selección e incorporación de candidatos). Además, discutiremos cómo los proveedores de chatbots desarrollan este servicio en términos de tecnologías técnicas necesarias y aspectos de comunicación. Los hallazgos ayudarán a identificar las mejores prácticas para desarrollar mejores chatbots que se alineen con las demandas de la contratación moderna. Además, investigamos el impacto de los chatbots en la educación superior con el aumento del aprendizaje en línea y la pandemia de Covid19. En la segunda parte, desarrollamos un chatbot utilizando la plataforma Google DialogFlow para apoyar el proceso de admisión de futuros estudiantes de doctorado Doctorado de la UPC. Este bot de preguntas en el Programa de Gestión de frecuentes se implementará como un canal complementario en el sitio web del programa de doctorado para comprender las consultas de los estudiantes y proporcionar respuestas predefinidas. Se realiza una encuesta basada en el marco TAM para evaluar la funcio nalidad, la calidad y la intención de uso del chatbot. Según las respuestas y los hallazgos, analizaremos cómo los chatbots son una opción viable para crear nuevos servicios innovadores que sean útiles tanto para los personas como para los educadores. Al candidat as final, en base a las lecciones aprendidas, proponemos conclusiones, discusión y varias recomendaciones para estos sistemas inteligentes. Se espera que este trabajo abra nuevas posibilidades de investigación para futuras optimizaciones en los campos de los chatbots y el reclutamiento en el futur

Adoption Factors of Artificial intelligence in Human Resource Management

Tesis por compendio[ES] El mundo es testigo de nuevos avances tecnológicos que afectan significativamente a las organizaciones en diferentes departamentos. La inteligencia artificial (IA) es uno de estos avances, visto como una tecnología revolucionaria en la gestión de recursos humanos (RRHH). Profesionales y académicos han discutido el brillante papel de la IA en RRHH. Sin embargo, el análisis profundo de esta tecnología en el proceso de RRHH es aún escaso. Con todo ello, el objetivo principal de esta tesis es investigar el estado de la IA en RRHH y así identificar factores clave de implementación concretos. Primero, construyendo un marco académico para la IA en RRHH; segundo, analizar las aplicaciones de IA más utilizada en los procesos de RRHH; tercero, identificar las formas óptimas de transferir el conocimiento en los procesos de implementación de IA. La metodología utilizada para la investigación combina la revisión sistemática de la literatura y técnicas de investigación cualitativa. Como base y medida preparatoria para abordar las preguntas de investigación, se llevó a cabo un extenso análisis de la literatura en el campo AI-RRHH, con un enfoque particular en las publicaciones de algoritmos de IA en HRM, análisis de HR-Big data, aplicaciones/soluciones de IA en HRM e implementación de IA. En la misma línea, el autor publicó artículos en varias conferencias que contribuyeron a mejorar la madurez de las preguntas de investigación. Con base en este conocimiento, los estudios publicados ilustraron la brecha entre la promesa y la realidad de la IA en RRHH, teniendo en cuenta los requisitos técnicos de la implementación de la IA, así como las aplicaciones y limitaciones. Posteriormente, se entrevistó a expertos en recursos humanos y consultores de IA que ya habían adquirido experiencia de primera mano con los procesos de recursos humanos en un entorno de IA para descubrir la verdad de la aplicación de la IA dominante en el proceso de RRHH. Los principales hallazgos de esta tesis incluyen la derivación de una definición completa de IA en RRHH, así como el estado de las estrategias de adopción de aplicaciones de IA en RRHH. Como resultado adicional, se explora la utilidad y las limitaciones de los chatbots en el proceso de contratación en la India. Además, factores clave para transferir el conocimiento del proceso de implementación de IA a los gerentes y empleados de recursos humanos. Finalmente, se concluye identificando desafíos asociados con la implementación de IA en el proceso de recursos humanos y el impacto de COVID-19 en la implementación de IA.[CA] El món és testimoni de nous avanços tecnològics, que afecten significativament les organitzacions en diferents departaments. La intel·ligència artificial (IA) és un d'aquests avanços que s'anuncia àmpliament com una tecnologia revolucionària en la gestió de recursos humans (HRM). Professionals i acadèmics han discutit el brillant paper de la IA en HRM. No obstant això, encara és escàs l'anàlisi profund d'aquesta tecnologia en el procés de HRM. Per tant, l'objectiu principal d'aquesta tesi és investigar l'estat de la IA en HRM i derivar factors clau d'implementació concrets. Primer, construint un marc acadèmic per a la IA en HRM; segon, analitzar l'aplicació de IA més utilitzada en el procés de recursos humans; tercer, identificar les formes òptimes de transferir el coneixement dels processos d'implementació de IA. La metodologia utilitzada per a la investigació es combina entre una revisió sistemàtica de la literatura i una tècnica d'investigació qualitativa. Com a base i mesura preparatòria per a abordar les preguntes d'investigació, es va dur a terme una extensa anàlisi de la literatura en el camp IA-HRM, amb un enfocament particular en les publicacions d'algorismes de IA en HRM, anàlisis de HR-Big data, aplicacions/soluciones de IA en HRM i implementació de IA. En la mateixa línia, l'autor va publicar articles en diverses conferències que van procedir a millorar la maduresa de les preguntes d'investigació. Amb base en aquest coneixement, els estudis publicats van illustrar la bretxa entre la promesa i la realitat de la IA en HRM, tenint en compte els requisits tècnics de la implementació de la IA, així com les aplicacions i limitacions. Posteriorment, es va entrevistar experts en recursos humans i consultors de IA que ja havien adquirit experiència de primera mà amb els processos de recursos humans en un entorn de IA per a descobrir la veritat de l'aplicació de la IA dominant en el procés de recursos humans. Les principals troballes d'aquesta tesi són la derivació d'una definició completa de IA en HRM, així com l'estat de les estratègies d'adopció d'aplicacions de IA en HRM. Com a resultat addicional, explore la utilitat i les limitacions dels chatbots en el procés de contractació a l'Índia. A més, factors clau per a transferir el coneixement del procés d'implementació de IA als gerents i empleats de recursos humans. També es van concloure els desafiaments associats amb la implementació de IA en el procés de recursos humans i l'impacte de COVID-19 en la implementació de IA.[EN] The world is witnessing new technological advancements, which significantly impacts organizations across different departments. Artificial intelligence (AI) is one of these advancements that is widely heralded as a revolutionary technology in Human Resource Management (HRM). Professionals and scholars have discussed the bright role of AI in HRM. However, deep analysis of this technology in the HR process is still scarce. Therefore, the main goal of this thesis is to investigate the status of AI in HRM and derive concrete implementation key factors. Through, first, building an academic framework for AI in HRM; second, analyzing the most commonly used AI applications in HR process; third, identifying the optimal ways to transfer the knowledge of AI implementation processes. The methodology used for the investigation combines a systematic literature review and a qualitative research technique. As a basis and preparatory measure to address the research questions, an extensive literature analysis in the AI-HRM field was carried out, with a particular focus on publications of AI in HRM, HR-Big data analysis, AI applications/solutions in HRM and AI implementation. Along similar lines, the author published papers in several conference proceedings to improve the maturity of research questions. Based on this work, the published studies illustrate the gap between the promise and reality of AI in HRM, taking into account the requirements of AI implementation as well as the applications and limitations. Subsequently, HR experts and AI consultants, who had already gained first-hand experience with HR processes in an AI environment, were interviewed to find out the truth of the dominant AI's application in HR process. The main findings of this thesis are the derivation of a complete definition of AI in HRM as well as the status of the adoption strategies of AI applications in HRM. As a further result, it explores the usefulness and limitations of chatbots in the recruitment processes in India. In addition, derived the key factors to transfer the knowledge of AI implementation process to HR managers and employees. Challenges associated with AI implementation in the HR process and the impact of COVID-19 on AI implementation were also concluded.Tuffaha, M. (2022). Adoption Factors of Artificial intelligence in Human Resource Management [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/185909Compendi

The design and evaluation of distributed virtual environment to support learning in global operations management

The primary goal of this research is to design and develop an education technology to support learning in global operations management. The research implements a series of studies to determine the right balance among user requirements, learning methods and applied technologies, on a view of student-centred learning. This research is multidisciplinary by nature, involving topics from various disciplines such as global operations management, curriculum and contemporary learning theory, and computer aided learning. Innovative learning models that emphasise on technological implementation are employed and discussed throughout this research

Human Factors in Agile Software Development

Through our four years experiments on students' Scrum based agile software development (ASD) process, we have gained deep understanding into the human factors of agile methodology. We designed an agile project management tool - the HASE collaboration development platform to support more than 400 students self-organized into 80 teams to practice ASD. In this thesis, Based on our experiments, simulations and analysis, we contributed a series of solutions and insights in this researches, including 1) a Goal Net based method to enhance goal and requirement management for ASD process, 2) a novel Simple Multi-Agent Real-Time (SMART) approach to enhance intelligent task allocation for ASD process, 3) a Fuzzy Cognitive Maps (FCMs) based method to enhance emotion and morale management for ASD process, 4) the first large scale in-depth empirical insights on human factors in ASD process which have not yet been well studied by existing research, and 5) the first to identify ASD process as a human-computation system that exploit human efforts to perform tasks that computers are not good at solving. On the other hand, computers can assist human decision making in the ASD process.Comment: Book Draf

The 1988 Goddard Conference on Space Applications of Artificial Intelligence

This publication comprises the papers presented at the 1988 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland on May 24, 1988. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in these proceedings fall into the following areas: mission operations support, planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; modeling and simulation; and development tools/methodologies