TELMA: Technology enhanced learning environment for minimally invasive surgery

Background: Cognitive skills training for minimally invasive surgery has traditionally relied upon diverse tools, such as seminars or lectures. Web technologies for e-learning have been adopted to provide ubiquitous training and serve as structured repositories for the vast amount of laparoscopic video sources available. However, these technologies fail to offer such features as formative and summative evaluation, guided learning, or collaborative interaction between users. Methodology: The "TELMA" environment is presented as a new technology-enhanced learning platform that increases the user's experience using a four-pillared architecture: (1) an authoring tool for the creation of didactic contents; (2) a learning content and knowledge management system that incorporates a modular and scalable system to capture, catalogue, search, and retrieve multimedia content; (3) an evaluation module that provides learning feedback to users; and (4) a professional network for collaborative learning between users. Face validation of the environment and the authoring tool are presented. Results: Face validation of TELMA reveals the positive perception of surgeons regarding the implementation of TELMA and their willingness to use it as a cognitive skills training tool. Preliminary validation data also reflect the importance of providing an easy-to-use, functional authoring tool to create didactic content. Conclusion: The TELMA environment is currently installed and used at the Jesús Usón Minimally Invasive Surgery Centre and several other Spanish hospitals. Face validation results ascertain the acceptance and usefulness of this new minimally invasive surgery training environment

A STUDY OF KNOWLEDGE MANAGEMENT SYSTEM ACCEPTANCE IN HALO BCA

Contact Center adalah salah satu bentuk Customer Relationship Management, di mana pelanggan dapat  berinteraksi dengan perusahaan melalui satu pintu. Contact Center juga berperan terutama sebagai alat bagi perusahaan untuk mengelola pelayanan terhadap pelanggan. Contact Center pada umumnya dioperasikan oleh banyak Agent Contact Center, dan dapat menerima ribuan panggilan telepon tiap harinya, tergantung pada skala perusahaan dan banyaknya pelanggan perusahaan tersebut. Agar dapat melayani pelanggan dengan baik, Agent perlu memahami banyak pengetahuan yang dimiliki perusahaan. Maka dari itu, Agent harus menguasai Knowledge Management System (KMS) yang dimiliki perusahaan. Ketidakmampuan Agent dalam menggunakan KMS akan menjadi masalah bagi operasional Contact Center dan perusahaan. Dalam penelitian ini kami mempelajari penerimaan Halo Info, salah satu bentuk KMS yang digunakan di Halo BCA, salah satu Contact Center perusahaan perbankan terbesar di Indonesia. Kami menggunakan Technology Acceptance Model (TAM) versi 2 yang kami modifikasi, mengunakan total 11 variabel, 31 indikator, dan 12 hipotesis. Instrumen penelitian berupa kuesioner dengan 31 indikator. Kami berhasil mengumpulkan 283 data responden, kemudian menganalisa data tersebut menggunakan PLS-SEM. Hasil penelitian adalah sebagai berikut: Usage Behaviour (UB) dipengaruhi secara signifikan oleh Intention to Use (IU); IU sangat dipengaruhi oleh Perceived Ease of Use (PEU), Perceived Usefulness (PU), dan Subjective Norm (SN); PEU dipengaruhi secara signifikan oleh System Self-Efficacy (SSE) dan Interface Usability (IUSB); PU dipengaruhi secara signifikan oleh Job Relevance (JR) dan PEU, namun tidak dipengaruhi secara signifikan oleh Output Quality (OQ), Image (I), Result Demonstrability (RD), dan SNContact Center is a form of Customer Relationship Management, where customers can interact with a company through its single point of contact and serves mainly as a tool for the company to maintain its service to the customers. Contact center is generally operated by many Agents and can accepts thousands of phone calls every day, depending on the company’s scale and customer base. In order to correctly serve the customers, Agents need to understand many knowledge which the company has, and this is the main reason why Agents need to master the company’s Knowledge Management System (KMS). Inability of Agents to interact with the KMS will be a serious problem for the company. In this paper, we studied the acceptance of Halo Info, a form of KMS in one of the biggest banking contact center in Indonesia, called Halo BCA. We used modified TAM version 2, with a total of 11 variables, 31 indicators, and 12 hypotheses. The research instrument was a 31 items questionnaire. We gathered 283 respondent data, and analyzed it using PLS-SEM. The research findings are: Usage Behaviour (UB) is significantly affected by Intention to Use (IU); IU is proven to be greatly affected by Perceived Ease of Use (PEU), Perceived Usefulness (PU), and Subjective Norm (SN); PEU is significantly affected by System Self-Efficacy (SSE) and Interface Usability (IUSB); PU is significantly affected by Job Relevance (JR) and PEU, but is not significantly affected by Output Quality (OQ), Image (I), Result Demonstrability (RD), and SN

A KNOWLEDGE MANAGEMENT SYSTEM FOR ORGANIZATIONAL ACTIVITY SUPPORT

L’attuale realt`a imprenditoriale `e fortemente influenzata dalla dinamicit`a dei mercati e dai continui progressi tecnologici. Queste tendenze trovano pratica realizzazione nel modello di organizzazione flessibile, che punta a massimizzare la capacit`a di rispondere con efficacia alle sfide della complessit`a ambientale. La conoscenza, considerata un nuovo fattore di produzione, diventa un elemento chiave nei processi aziendali. Sempre di pi`u, negli ultimi anni `e cresciuta la consapevolezza delle imprese dell’effettivo valore di una corretta gestione della conoscenza. L’uso di strumenti propri del Knowledge Management nelle organizzazioni `e divenuto una pratica comune. Una caratteristica fondamentale della conoscenza, inoltre, `e l’essere strettamente legata alla capacit`a di compiere azioni. Solo chi conosce `e infatti capace di prendere le giuste decisioni ed agire di conseguenza. Prendere decisioni riguardanti sistemi complessi (come per esempio, gestire attivit`a organizzative e processi industriali o controllare dispositivi robotici in ambienti dinamici) `e un compito che, molto spesso, va oltre le capacit`a cognitive umane. Questo `e dovuto al fatto che le variabili che influenzano il sistema sono, generalmente, soggette a complesse interdipendenze. Per questo motivo predire il risultato finale pu`o risultare piuttosto complicato. Il giudizio di un esperto umano, dunque, si discosta dalla decisione ottima al crescere della complessit`a dei processi decisionali. In quelle situazioni in cui la precisione `e fondamentale, la qualit`a delle decisioni `e molto importante. Una sfida per la comunit`a scientifica `e infatti riuscire ad elaborare tecniche e modelli per superare il limite umano. Nella tesi presentata vengono affrontati essenzialmente due grossi problemi riguardanti le organizzazioni dell’Information and Communication Technology: il riuso del software e la selezione dei progetti aziendali. Il riuso del software (Software Reuse) non `e semplicemente un problema tecnico ma anche e soprattutto un problema di gestione della conoscenza. Il Riuso `e comunemente definito come un ulteriore utilizzo o un ripetuto uso di un artefatto. Un nuovo prodotto pu`o, quindi, essere realizzato utilizzando una serie di elementi (nel caso in esame, possono essere componenti software o hardware) prodotti in precedenza. Gestire in maniere efficiente la conoscenza aziendale permette, per esempio, di trovare possibili candidati per il riuso da un’apposita repository. La selezione dei progetti aziendali (Project Selection) riguarda la scelta della migliore tra le alternative possibili sulla base di un’analisi costi/benefici. Per decidere quali tra i progetti proposti `e pi`u conveniente sviluppare, occorre tenere in considerazione determinati fattori. Ogni progetto, infatti, ha una propria complessit`a e specifiche caratteristiche, per esempio vantaggi e svantaggi, benefici tangibili e non, costi, impegno di risorse umane e cosi via. La presente tesi propone un sistema per la gestione della conoscenza che affronta diversi aspetti del Knowledge Management, dalla rappresentazione della conoscenza ai processi decisionali (Decision Making). In particolare, `e mostrato come le ontologie sono applicabili ed effettivi mezzi per supportare la rappresentazione della conoscenza; come sia possibile ricercare componenti software riutilizzabili utilizzando un sistema esperto basato su regole; ed infine come le reti Bayesiane e i sistemi Fuzzy possono integrare conoscenza utile per il supporto alle decisioni in condizioni di incertezza. Il modello di ragionamento incerto che propongo tiene in considerazioni sia la vaghezza e la soggettivit`a del giudizio umano che l’aleatoriet`a di alcuni eventi che sono intrisecamente legati al mondo degli affari. Per questo motivo, sono state implementate tecniche di ragionamento fuzzy, tramite le quali il sistema deduce la complessit`a di un progetto software considerando una serie di fattori che influenzano un progetto. Inoltre, la realizzazione di una rete bayesiana permette di stimare la fattibilit`a di un dato progetto a partire dall’evidenza derivata dal ragionamento fuzzy. Il lavoro di ricerca condotto in questi anni di dottorato ed in questa tesi illustrato, ha portato alla realizzazione di Kromos, un sistema prodotto in collaborazione con il Dipartimento di Ingegneria Informatica dell’Universit`a di Palermo e di Sicilia e-Innovazione, una societ`a della Regione Sicilia finalizzata all’informatizzazione degli uffici della Pubblica Amministrazione.The modern business world is characterized by dynamic markets and continuous technological advances. To cope with these trends, organizations must become more flexible. The knowledge, considered as a new factor of production, becomes a key element in business processes. In the last few years, the enterprises awareness about the worth of a correct knowledge management is grown exponentially. The use of Knowledge Management tools within the organization is became a best practice. The knowledge, additionally, is strictly linked to the capability to perform effective actions. Who knows is able to make a correct decision and to act consequently. Making decisions concerning complex systems (e.g., the management of organizational activities, industrial processes or the control of robotic device in complex environment etc...) often is a task that exceeds human cognitive capabilities. This is because many variables of the system are involved in complex interdependencies and predicting the total outcome may be very difficult. The human intuitive judgment and decision making become far from optimal to grow of complexity of the decision process. In many situations the quality of decisions is important, overcoming the deficiencies of human judgment is an important issue in the scientific community. Two main problems concerning ICT enterprises are deeply addressed in this dissertation: Software Reuse and Project Selection. Software Reuse is not only a technology problem but fundamentally a knowledge management problem. Reuse can be defined as further use or repeated use of an artefact. A new product is created by taking applicable assets from the asset base. A correct knowledge management allows finding candidate assets for reuse from asset base. Project Selection concerns the choose of the best among alternative proposals on the basis of cost-benefit analysis. In order to decide which of the proposed projects should be selected, a number of factors must be considered. In fact, each project has its own complexity and includes environmental advantages and disadvantages, tangible and intangible benefits, costs, allocation of human and hardware resources and many others. In this thesis, I present a novel fusion of Artificial Intelligence techniques in order to cope different aspects of knowledge management from knowledge representation to decision making. I show how the ontologies are applicable and effective means for supporting knowledge representation, how to find reusable software components by means of a rule based expert system and how the Bayesian networks and Fuzzy systems can be integrate knowledge to support decision processes under uncertainty. I proposed a model for uncertainty reasoning, in order to cope not only to the unpredictability of some events that are intrinsically linked to the market environment, but also to overcome the vagueness and subjectivities of human judgments. This model is based on a fuzzy reasoning, which allows evaluating the complexity of an ICT projects unifying the contribution of several factors that complicate a project, and on a Bayesian network able to estimate the feasibility of a project on the basis of the evidence derived from fuzzy reasoning. This research was applied to the realization of Kromos, a product of collaboration between the Computer Engineering Department of Palermo University and the Sicilian local Government ICT society, Sicilia e-Innovazione

Using Knowledge-based Information Systems to Support Management of Wireless Sensor Networking Systems

Currently, researches on Wireless Sensor Networks (WSN) mainly focus on how to efficiently gather sensing data from WSN, but little attention has been paid to how to effectively manage the large amount of collected sensing data. Information Systems (IS) are appropriatetools for data input, storage, processing, and output. Knowledge Management (KM) further transforms useful information into domain knowledge for decision making by domain experts. In this paper, we propose an approach to management of sensing data and transformation of sensing data into valuable knowledge using knowledge-based information systems. Firstly we propose a frameworkfor knowledge-based information systems which deals with internal and external information using intelligent agents to generate domain knowledge with KM methods. Then we definite a model of knowledge-based information system for WSN to implement intensive sensing data storage, knowledge discovery, statistical analysis, sharing, inquiry, decision support. Finally, a prototype system is developed and tested for the aforementioned ideas

A Knowledge Management and Decision Support Model for Enterprises

We propose a novel knowledge management system (KMS) for enterprises. Our system exploits two different approaches for knowledge representation and reasoning: a document-based approach based on data-driven creation of a semantic space and an ontology-based model. Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty

The Component Packaging Problem: A Vehicle for the Development of Multidisciplinary Design and Analysis Methodologies

This report summarizes academic research which has resulted in an increased appreciation for multidisciplinary efforts among our students, colleagues and administrators. It has also generated a number of research ideas that emerged from the interaction between disciplines. Overall, 17 undergraduate students and 16 graduate students benefited directly from the NASA grant: an additional 11 graduate students were impacted and participated without financial support from NASA. The work resulted in 16 theses (with 7 to be completed in the near future), 67 papers or reports mostly published in 8 journals and/or presented at various conferences (a total of 83 papers, presentations and reports published based on NASA inspired or supported work). In addition, the faculty and students presented related work at many meetings, and continuing work has been proposed to NSF, the Army, Industry and other state and federal institutions to continue efforts in the direction of multidisciplinary and recently multi-objective design and analysis. The specific problem addressed is component packing which was solved as a multi-objective problem using iterative genetic algorithms and decomposition. Further testing and refinement of the methodology developed is presently under investigation. Teaming issues research and classes resulted in the publication of a web site, (http://design.eng.clemson.edu/psych4991) which provides pointers and techniques to interested parties. Specific advantages of using iterative genetic algorithms, hurdles faced and resolved, and institutional difficulties associated with multi-discipline teaming are described in some detail

A NEW APPROACH FOR CONFLICT RESOLUTION AND RULE PROCESSING IN A KNOWLEDGE-BASED SYSTEM

In a knowledge-based system, rules can be defined to derive virtual attributes. Conflicts occur if multiple rules are applicable and one must be selected based on some criterion, such as priority. We identify important properties of a conflict resolution method and describe a technique for resolving conflicts and efficiently processing queries involving virtual attributes in a knowledge-based system. It is shown that by transforming a given, prioritized set of rules into a conflict-free, priority independent form it is possible to do query processing in a set-at-a-time manner. Algorithms for conflict resolution and query processing are given