A framework of PBL strategy integrated in LMS and a ubiquitous learning environment

[[abstract]]This study describes the design of problem-based learning strategy (PBL) integrated into LMS with mobile tools in a ubiquitous learning environment, which is called uPBL system. This paper discusses the analysis and design of PBL instructional steps for building a LMS system to create a new learning environment. A trial case was designed and implemented with elementary school teachers to obtain feedback and suggestions on the design of uPBL system structure. In the trail PBL outdoor activities coped with PDA devices, students were interested in mobile learning devices and the developed system. Also, students felt comfortable to solve the real live problems and communicate with team members without the obstacles of time and space. It is expected that students will be enhanced their learning performance with a well-designed learning environment via held technology devices. Experimental studies of students learning performance are ongoing in the next research step.[[incitationindex]]EI[[conferencetype]]國際[[conferencedate]]20100816~20100818[[iscallforpapers]]Y[[conferencelocation]]Seoul, Kore

PENGUJIAN COGNITIVE WALKTHROUGH ANTARMUKA PERPUSTAKAAN DIGITAL (E-LIBRARY) PUSAT DOKUMENTASI DAN INFORMASI ILMIAH – LIPI (PDII-LIPI)

Interface design has a significant role towards the successful of digital librarys application use. Digital libraryservices developed by Centre for Scientific Documentation and Information - Indonesian Institute of Sciences (PDII-LIPI) has yet to be evaluated. This research analyzed the design of the web interface of PDII-LIPI’s digitallibraries using the method of cognitive walkthrough (CW). The aim of the research is to identify user constraints inusing PDII-LIPI’s digital libraries. Object of this study are three menus in digital library web interface that is “KaryaIlmiah Indonesia”, “Buku Elektronik”, and “Jurnal Indonesia (ISJD)”. CW testing parameters for PDII-LIPI’s digitallibrary interface consists of the successful completion of the task, and the effectiveness of the task. The successfulcompletion of the task was assessed by comparing the standard time with task completion time by respondents. Effectiveness accessed based on the processing time of each stage and the number of mistakes made by therespondent. The test results showed that all respondents successfully completed the task with the time that goesbeyond the standard set time. The analysis was conducted on all test results indicate that the obstacles faced byusers in general are finding menu of “E-Library”, specify the search facility is used, and searching the articles

Decentralized Resource Scheduling in Grid/Cloud Computing

In the Grid/Cloud environment, applications or services and resources belong to different organizations with different objectives. Entities in the Grid/Cloud are autonomous and self-interested; however, they are willing to share their resources and services to achieve their individual and collective goals. In such open environment, the scheduling decision is a challenge given the decentralized nature of the environment. Each entity has specific requirements and objectives that need to achieve. In this thesis, we review the Grid/Cloud computing technologies, environment characteristics and structure and indicate the challenges within the resource scheduling. We capture the Grid/Cloud scheduling model based on the complete requirement of the environment. We further create a mapping between the Grid/Cloud scheduling problem and the combinatorial allocation problem and propose an adequate economic-based optimization model based on the characteristic and the structure nature of the Grid/Cloud. By adequacy, we mean that a comprehensive view of required properties of the Grid/Cloud is captured. We utilize the captured properties and propose a bidding language that is expressive where entities have the ability to specify any set of preferences in the Grid/Cloud and simple as entities have the ability to express structured preferences directly. We propose a winner determination model and mechanism that utilizes the proposed bidding language and finds a scheduling solution. Our proposed approach integrates concepts and principles of mechanism design and classical scheduling theory. Furthermore, we argue that in such open environment privacy concerns by nature is part of the requirement in the Grid/Cloud. Hence, any scheduling decision within the Grid/Cloud computing environment is to incorporate the feasibility of privacy protection of an entity. Each entity has specific requirements in terms of scheduling and privacy preferences. We analyze the privacy problem in the Grid/Cloud computing environment and propose an economic based model and solution architecture that provides a scheduling solution given privacy concerns in the Grid/Cloud. Finally, as a demonstration of the applicability of the approach, we apply our solution by integrating with Globus toolkit (a well adopted tool to enable Grid/Cloud computing environment). We also, created simulation experimental results to capture the economic and time efficiency of the proposed solution

Simheuristics to support efficient and sustainable freight transportation in smart city logistics

La logística urbana intel·ligent constitueix un factor crucial en la creació de sistemes de transport urbà eficients i sostenibles. Entre altres factors, aquests sistemes es centren en la incorporació de dades en temps real i en la creació de models de negoci col·laboratius en el transport urbà de mercaderies, considerant l’augment dels habitants en les ciutats, la creixent complexitat de les demandes dels clients i els mercats altament competitius. Això permet als que planifiquen el transport minimitzar els costos monetaris i ambientals del transport de mercaderies a les àrees metropolitanes. Molts problemes de presa de decisions en aquest context es poden formular com a problemes d’optimació combinatòria. Tot i que hi ha diferents enfocaments de resolució exacta per a trobar solucions òptimes a aquests problemes, la seva complexitat i grandària, a més de la necessitat de prendre decisions instantànies pel que fa a l’encaminament de vehicles, la programació o la situació d’instal·lacions, fa que aquestes metodologies no s’apliquin a la pràctica. A causa de la seva capacitat per a trobar solucions pseudoòptimes en gairebé temps real, els algorismes metaheurístics reben una atenció creixent dels investigadors i professionals com a alternatives eficients i fiables per a resoldre nombrosos problemes d’optimació en la creació de la logística de les ciutats intel·ligents. Malgrat el seu èxit, les tècniques metaheurístiques tradicionals no representen plenament la complexitat dels sistemes més realistes. En assumir entrades (inputs) i restriccions de problemes deterministes, la incertesa i el dinamisme experimentats en els escenaris de transport urbà queden sense explicar. Els algorismes simheurístics persegueixen superar aquests inconvenients mitjançant la integració de qualsevol tipus de simulació en processos metaheurístics per a explicar la incertesa inherent a la majoria de les aplicacions de la vida real. Aquesta tesi defineix i investiga l’ús d’algorismes simheurístics com el mètode més adequat per a resoldre problemes d’optimació derivats de la logística de les ciutats. Alguns algorismes simheurístics s’apliquen a una sèrie de problemes complexos, com la recollida de residus urbans, els problemes de disseny de la cadena de subministrament integrada i els models de transport innovadors relacionats amb la col·laboració horitzontal entre els socis de la cadena de subministrament. A més de les discussions metodològiques i la comparació d’algorismes desenvolupats amb els referents de la bibliografia acadèmica, es mostra l’aplicabilitat i l’eficiència dels algorismes simheurístics en diferents casos de gran escala.Las actividades de logística en ciudades inteligentes constituyen un factor crucial en la creación de sistemas de transporte urbano eficientes y sostenibles. Entre otros factores, estos sistemas se centran en la incorporación de datos en tiempo real y la creación de modelos empresariales colaborativos en el transporte urbano de mercancías, al tiempo que consideran el aumento del número de habitantes en las ciudades, la creciente complejidad de las demandas de los clientes y los mercados altamente competitivos. Esto permite minimizar los costes monetarios y ambientales del transporte de mercancías en las áreas metropolitanas. Muchos de los problemas de toma de decisiones en este contexto se pueden formular como problemas de optimización combinatoria. Si bien existen diferentes enfoques de resolución exacta para encontrar soluciones óptimas a tales problemas, su complejidad y tamaño, además de la necesidad de tomar decisiones instantáneas con respecto al enrutamiento, la programación o la ubicación de las instalaciones, hacen que dichas metodologías sean inaplicables en la práctica. Debido a su capacidad para encontrar soluciones pseudoóptimas casi en tiempo real, los algoritmos metaheurísticos reciben cada vez más atención por parte de investigadores y profesionales como alternativas eficientes y fiables para resolver numerosos problemas de optimización en la creación de la logística de ciudades inteligentes. A pesar de su éxito, las técnicas metaheurísticas tradicionales no representan completamente la complejidad de los sistemas más realistas. Al asumir insumos y restricciones de problemas deterministas, se ignora la incertidumbre y el dinamismo experimentados en los escenarios de transporte urbano. Los algoritmos simheurísticos persiguen superar estos inconvenientes integrando cualquier tipo de simulación en procesos metaheurísticos con el fin de considerar la incertidumbre inherente en la mayoría de las aplicaciones de la vida real. Esta tesis define e investiga el uso de algoritmos simheurísticos como método adecuado para resolver problemas de optimización que surgen en la logística de ciudades inteligentes. Se aplican algoritmos simheurísticos a una variedad de problemas complejos, incluyendo la recolección de residuos urbanos, problemas de diseño de la cadena de suministro integrada y modelos de transporte innovadores relacionados con la colaboración horizontal entre los socios de la cadena de suministro. Además de las discusiones metodológicas y la comparación de los algoritmos desarrollados con los de referencia de la bibliografía académica, se muestra la aplicabilidad y la eficiencia de los algoritmos simheurísticos en diferentes estudios de casos a gran escala.Smart city logistics are a crucial factor in the creation of efficient and sustainable urban transportation systems. Among other factors, they focus on incorporating real-time data and creating collaborative business models in urban freight transportation concepts, whilst also considering rising urban population numbers, increasingly complex customer demands, and highly competitive markets. This allows transportation planners to minimize the monetary and environmental costs of freight transportation in metropolitan areas. Many decision-making problems faced in this context can be formulated as combinatorial optimization problems. While different exact solving approaches exist to find optimal solutions to such problems, their complexity and size, in addition to the need for instantaneous decision-making regarding vehicle routing, scheduling, or facility location, make such methodologies inapplicable in practice. Due to their ability to find pseudo-optimal solutions in almost real time, metaheuristic algorithms have received increasing attention from researchers and practitioners as efficient and reliable alternatives in solving numerous optimization problems in the creation of smart city logistics. Despite their success, traditional metaheuristic techniques fail to fully represent the complexity of most realistic systems. By assuming deterministic problem inputs and constraints, the uncertainty and dynamism experienced in urban transportation scenarios are left unaccounted for. Simheuristic frameworks try to overcome these drawbacks by integrating any type of simulation into metaheuristic-driven processes to account for the inherent uncertainty in most real-life applications. This thesis defines and investigates the use of simheuristics as a method of first resort for solving optimization problems arising in smart city logistics concepts. Simheuristic algorithms are applied to a range of complex problem settings including urban waste collection, integrated supply chain design, and innovative transportation models related to horizontal collaboration among supply chain partners. In addition to methodological discussions and the comparison of developed algorithms to state-of-the-art benchmarks found in the academic literature, the applicability and efficiency of simheuristic frameworks in different large-scaled case studies are shown

An improved energy management methodology for the mining industry.

The focus for this work was the development of an improved energy management methodology tailored for the mining sector. Motivation for this research was driven by perception of slow progress in adoption of energy management practices to improve energy performance within the mining sector. Energy audits conducted for an underground mine, a mineral processing facility, and a pyrometallurgical process were reviewed and recommendations for improved data gathering, reporting and interpretation were identified. An obstacle for conducting energy audits in mines without extensive sub-metering is a lack of disaggregated data indicating end use. Thus a novel method was developed using signal processing techniques to disaggregate the end-use electricity consumption, exemplified through isolation of a mine hoist signal from the main electricity meter data. Further refinements to the method may lead to its widespread adoption, which may lower energy auditing costs via a reduced number of meters and infrastructure, as well as lower data storage requirements. Mine ventilation systems correspond to the largest energy demand center for underground mines. Thus a detailed analysis ensued with the development of a techno-economic model that could be used to assess various fan and duct options. Furthermore, the need for a standardized methodology for determination of duct friction factors from ventilation surveys was proposed, which included a method to verify the validity of the resulting value from asperity height measurements. A method was also suggested for determination of leakage and duct friction factor values from ventilation survey data. Dissemination of best practice is a strategy that could be employed to improve energy performance throughout the mining sector, thus a Best Practice database was developed to iv improve communication and provide a standardized reporting framework for sharing of energy conservation initiatives. Demonstration of continuous improvement is an underpinning element of the ISO 50001 energy management standard but as mines extract ore from deeper levels energy use increases. Thus ensued the development of a benchmarking metric, with the use of appropriate support variables that included mine depth, production, and climate data, that demonstrated the benefit of implemented energy conservation measures for an underground mine. The development of an ultimate energy management methodology for all stages of mineral processing from ‘Mine to Bullion’ is beyond the scope of this work. However, this research has resulted in several recommendations for improvement and identified areas for further improvements.Doctor of Philosophy (PhD) in Natural Resources Engineerin

A resource-oriented architecture for business process systems

Background: The REpresentational State Transfer (REST) design principles treat all concepts in the world as link-connected resources, and support ROA (Resource-Oriented Architecture) for the Web applications. REST and ROA are responsible for the adaptability achieved in the Web. Some design approaches of Web-based business process systems recently evolved towards RESTful to inherit adaptability. However, none of the approaches can improve the adaptability of the produced systems. Aims: Propose a systematic approach for design and execution of Web-based business processes to improve adaptability of the produced systems. Methods: This research followed an empirical research methodology, which evaluates research solutions with real-world cases. On one hand, the research solution was derived by 1) tailoring the REST principles towards business process systems; 2) proposing REST annotations on existing business process modelling; 3) mapping the concepts of business process to HTTP/URI specifications; and 4) designing a format for process context information. On the other hand, the research solution was evaluated through three real-world case studies. Two of the case studies conducted comparative analysis in terms of adaptability of the systems produced by the proposed approach and two alternatives, namely, SOA and MEST (MESsage Transfer). The analysis is based on metrics, including LOC difference, change locality, coupling and cohesion, and an analysis framework called BASE. Results: The research solution is ROA4BP, which includes 1) an architecting approach for design and implementation of Web-based business processes to provide a development guideline; 2) a set of REST-related annotations on existing process modelling to ensure the compatibility with existing techniques; 3) A systematic mapping between business process and HTTP/URI specifications to utilize the advanced mechanisms provided by the Web infrastructure; and 4) a communication format to exchange structured process context information during runtime among process participants. A modelling tool, a programming API and a runtime engine were implemented to support the approach and simplify the implementation of case studies. The case studies demonstrated that ROA4BP can produce more adaptable business process systems compared to the other two alternatives. Conclusion: ROA4BP can help to design and execute RESTful business process systems with better adaptability at design-time and runtime