Conflict characterization and Analysis of Non Functional Requirements: An experimental approach

Prior studies reveal that conflicts among Non Functional Requirements (NFRs) are not always absolute. They can also be relative depending on the context of the system being developed. Given that existing techniques to manage the NFRs conflicts are mainly focused on cataloguing the interrelationships among various types of NFRs, hence a technique to manage the NFRs conflicts with respect to NFRs relative characteristic is needed. This paper presents a novel framework to manage the conflicts among NFRs with respect to NFRs relative characteristic. By applying an experimental approach, the quantitative evidence of NFRs conflicts will be obtained and modeled. NFRs metrics and measures will be used in the experiments as parameters to generate the quantitative evidence. This evidence can then allow developers to identify and reason about the NFRs conflicts. We also provide an example of how this framework could be applied. © 2013 IEEE

An ontological framework to manage the relative conflicts between security and usability requirements

Non Functional Requirements (NFRs) are relative, so are the conflicts among them. In our previously developed catalogue of NFRs conflicts it can be observed that a number of specific pairs of NFRs are claimed to be in conflicts in some cases but they are also claimed not to be in conflict in the other cases. These relative conflicts occur because the positive or negative relationships among NFRs are not always clear and obvious. These relationships might change depending on the meaning of NFRs within the system being developed. This paper focuses on the application of ontology in managing the relative conflicts among NFRs, particularly the relative conflicts between security and usability requirements. The aim is to develop a framework to identify, characterize, and define corresponding resolution strategies for the security-usability conflicts. This paper thus describes the sureCM framework to manage these conflicts; summarizes the security-usability conflicts ontology; and demonstrates how the ontology will be used as a basis to assist analysts in managing conflicts between security and usability requirements. ©2010 IEEE

Clinical decision support system for point of care use--ontology-driven design and software implementation

OBJECTIVES: The objective of this research was to design a clinical decision support system (CDSS) that supports heterogeneous clinical decision problems and runs on multiple computing platforms. Meeting this objective required a novel design to create an extendable and easy to maintain clinical CDSS for point of care support. The proposed solution was evaluated in a proof of concept implementation. METHODS: Based on our earlier research with the design of a mobile CDSS for emergency triage we used ontology-driven design to represent essential components of a CDSS. Models of clinical decision problems were derived from the ontology and they were processed into executable applications during runtime. This allowed scaling applications' functionality to the capabilities of computing platforms. A prototype of the system was implemented using the extended client-server architecture and Web services to distribute the functions of the system and to make it operational in limited connectivity conditions. RESULTS: The proposed design provided a common framework that facilitated development of diversified clinical applications running seamlessly on a variety of computing platforms. It was prototyped for two clinical decision problems and settings (triage of acute pain in the emergency department and postoperative management of radical prostatectomy on the hospital ward) and implemented on two computing platforms--desktop and handheld computers. CONCLUSIONS: The requirement of the CDSS heterogeneity was satisfied with ontology-driven design. Processing of application models described with the help of ontological models allowed having a complex system running on multiple computing platforms with different capabilities. Finally, separation of models and runtime components contributed to improved extensibility and maintainability of the system

Validation of a Content Analysis System Using an Iterative Prototyping Approach to Action Research

In the face of a more rapid pace of scientific development, academic societies and competitive organizations alike are seeking new methods for content analysis. This paper describes a theoretically driven action research study that delivers a technology-mediated solution for specifying, organizing, representing and using elements of meaning in a body of knowledge. The theoretical basis, \u27ontological specification\u27 is of particular interest to IS professionals, particularly those involved in analysis and design, because it guides the efficient transformation of tacit knowledge into an explicit form. The technology-mediated solution influenced by ontological specification was validated through an iterative prototyping form of action research. Users reported that the system was useful in their work, easy to use, and compatible with collaborative work when using it for content analysis in academic research

Computational Ontologies and Information Systems I: Foundations

This paper provides a state-of-the-art review about computational ontologies to raise awareness about this research area in the IS discipline and to explore areas where IS researchers can engage in fruitful research. This paper discusses the basic foundations and definitions pertaining to the field of computational ontologies. It reviews the intersection of computational ontologies with the IS discipline. It also discusses methods and guidelines for developing computational ontologies. The paper concludes with recommendations for important and emerging directions for research. The technical aspects of ontologies are presented in a companion paper (Volume 14, article 9). The companion paper provides a comprehensive review of the formalisms, languages, and tools used for specifying and implementing computational ontologies

Representing spatial and domain knowledge within a spatial decision support framework.

Experts are looking for ways to improve the monitoring of unstable slopes. A spatial decision support system (SDSS) is a software tool that can be used to support an expert in making complex decisions when solving problems. Many SDSSs use a geographic information system (GIS) to help analyze and manage spatial data. However, many GISs do not take advantage of expert knowledge. An expert system (ES) is a program that can be used to represent and reason with different kinds of knowledge when solving unstructured problems. The ability to find solutions to these problems can be enhanced by integrating a CIS and an ES. This research presents a candidate framework that represents basic spatial and domain knowledge through ontologies and integrates the knowledge within an ES-GIS environment. C Language Integrated Production System and ArcCIS provide the ES-GIS framework that is used to demonstrate this candidate framework through two small monitoring examples.Dept. of Earth Sciences. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2006 .R698. Source: Masters Abstracts International, Volume: 45-01, page: 0470. Thesis (M.Sc.)--University of Windsor (Canada), 2006

Developing a Modular Hydrogeology Ontology Extending the Sweet Ontologies

Application of ontologies in the environmental science will allow experts in this field to model their domain knowledge for more efficient exchange and reuse. This thesis presents a modular approach in reengineering existing upper-level ontologies to conceptualize specific domain knowledge. The aim of extending these upper-level ontologies is to tailor and transform the existing conceptual models into new ones designed for the use in a specific domain in the earth sciences. This thesis extends the upper-level Semantic Web for Earth and Environmental Terminology (SWEET)ontologies to develop ontologies for part of the hydrogeology domain. The existing SWEET ontologies are developed by NASA’s Jet Propulsion lab for Earth system science (http://sweet.jpl.nasa.gov/ontology/). In the new model, presented in this thesis, the architecture and orthogonal design of the SWEET ontologies is not disturbed but restructured at certain levels. New concepts are added to the old structure and the consistency is maintained for use by other domains. This thesis discusses the useful steps,necessary tools and other procedures involved in ontological reengineering of existing upper-level ontologies. The hydrogeology domain modeled in this thesis by means of reengineering, exemplifies the reusability methodology for the Earth system science knowledge base

Development of adaptive chatbot based on artificial intelligence

Nakon blagog pada pojedinih društvenih mreža istraživanja ukazuju da su krajnji korisnici najveću količinu svoje pažnje usmerili na komunikacione platforme (Viber, Whatsapp, FB messenger, Instagram, itd). Pojam digitalna transformacija zajedno sa veštačkom inteligencijom, predstavlja ogroman iskorak u pravcu unapređenja poslovanja kompanija iz različitih industrija. U borbi protiv KOVID-19, a u cilju razvoja inovativnih rešenja koja obezbeđuju dodatnu vrednost, u digitalni svet je lansiran četbot. On predstavlja program koji imitira ljudski razgovor i pomaže korisniku da dobije prave informacije i pruži svakodnevne usluge. U poslednjoj deceniji, ogromno unapređenje komunikacionih platformi i mrežnih tehnologija pružile su nove tehničke mogućnosti za usvajanje četbota u različitim sektorima, kao što su: e-trgovina, korisnička podrška, marketing i obrazovanje. Četbot predstavlja softver koji simulira konverzaciju koristeći veštačku inteligenciju i učestvuje u dijalogu sa čovekom koristeći prirodni jezik i pri tome razume tekstualne i glasovne poruke. Četbot koristi veštačku inteligenciju u cilju pronalaženja odgovora i rešavanja korisničkih zahteva. U koraku sa novim trendovima u radu je definisan metodološki okvir za razvoj savremene arhitekture četbota zasnovanog na veštačkoj inteligenciji za sledeću generaciju Internet zajednice. U skladu sa tim najveći problem razvoja adaptivne platforme je rešavanje problema fleksibilnosti integrisanja, odnosno definisanje mehanizma nezavisnosti četbota od samo jednog servisa za razumevanje prirodnog jezika (engl. Natural Language Understanding - NLU) čime bi se obezbedila adekvatna adaptivnost. Predložena metodologija daje opšti postupak i rezultat je kombinacije različitih metodoloških pristupa. Prateći metodologiju, razvoj adaptivnog četbota zasnovan na NLU se sastoji iz dve faze: projektni i aplikacioni inženjering. Svaka od ovih faza je zatim podeljena na aktivnosti koje treba da urade u okviru faza. Prednost ove podele je realizacija prilagodljive platforme za generisanje četbotova. Napredna arhitektura četbota koja podržava metodologiju je lako proširljiva, skalabilna i podržava različite servise za razumevanje prirodnog jezika i komunikacione platforme za razmenu poruka. Teza opisuje logičku i fizičku arhitekturu četbota. Kroz odgovarajuće metamodele i njihova mapiranje obezbeđena je nezavisnot NLU servisa. Kroz predloženi pristup daje se sopstveni nezavisni okvir za razvoj četbota čiji je cilj smanjenje zavisnosti od proizvođača koji se bave servisima za razumevanje prirodnog jezika i kanalima komunikacija. Na ovaj način se stiče nezavisnost od bilo kog servisa za razumevanje prirodnog jezika, čime se rešenje neće vezati za jedan servis već će se predloženim mehanizmom obezbediti lako mapiranje i prebacivanje sa jednog na drugi novi i/ili stari servis. Konačno, jedna implementacija predložene arhitekture četbota je ukratko prikazana kroz studiju slučaja. Akademska Digitalna Asistentkinja (ADA) je prva implementacija četbota u prosveti na Balkanu koja kroz prirodnu komunikaciju pruža efikasniju realizaciju usluga i uštedu vremena. ADA prima poruke sa različitih komunikacionih platformi za razmenu poruka (Viber, FB mesindžer, Instagram i vebčet preko sajta BAPUSS). Četbot platform obavlja veliki broj važnih zadataka pre nego što pošalje poruku NLU. NLU zatim analizira tekst i na osnovu tehnika mašinskog učenja upoređuje, a zatim generiše nameru i njene entitete. Generisani rezultat se šalje nazad u četbot platformu, koja određenim algoritmom koristi nameru, entitete, kontekst i šalje odgovor korisniku u odgovarajućem formatu za prikazivanje poruke. ADA je dostupna 24 sata i daje odgovare na česta pitanja studenata i budućih studenata. ADA zna nešto više od 250 scenarija u vezi sa pitanjima na koje studenti i ostali korisnici žele da dobiju odgovor ili da izvrše odgovarajuću uslugu. Neki od scenarija su: prijava ispita, promena ispitivača, overa semestra, informacije o konsultacijama nastavnika, rokovima, rangiranju akademije, rasporedu predavanja, rejtingu studenata, događajima, dostupnosti usluga, akademskom okruženju, datumu predavanja i ispita, aktivnostima koje se dešavaju unutar akademije i druge korisne akademske informacije