bluuebunny/crossref_metadata_2025 huggingface dataset:
Superior Customer Value and Network size in Markets Characterized by Network effects
Authors: Tseng Fan-Chen , Teng Ching-I , Chiang David
Published: May 2011

Network effect indicates that the value of connecting to a network is positively associated with the current number of customers connected to that network. Network effect strengthens the strong firms, weakens the weak firms, and may lead to a winner-take-all market. Thus, managing customer perceived value is crucial in markets with network effects. This article models customer perceived value, presents ways to improve the value, and discusses the relationship between customer perceived value and network size. Implications for e-business practitioners are discussed.
Modelling in Clinical Practice with Web Services and BPEL
Authors: Morrison Iain , Lewis Bryn , Nugrahanto Sony
Published: May 2011

The aim of increasing the quality of healthcare has led to the development of a number of ‘guideline’ systems whereby clinicians receive assistance in decision making in a given care context – for example in areas such as prescribing or therapeutics. These guidelines range in complexity and functionality from simple textual references through to executable modules which can subsume some of the clinical decision making process. In the latter case, ensuring consistent and interoperable engagement between the guideline engine, clinical information system and patient record can become problematic. Critical areas include vocabulary and terminology (in differing use contexts) and the interfaces and interaction between different sub-systems where traditional approaches have been focussed on tightly coupling of sub-systems and in the generation of special purpose ‘glue’ languages and logic. In this paper, we briefly describe an approach to clinical, information and service modelling. This approach uses tools and techniques gaining increasing acceptance in the e-Commerce domain, which shares many of the technical and interoperability problems present in e-Health.
Event-Based and Publish/Subscribe Communication
Authors: Aitenbichler Erwin
Published: May 2011

Ubiquitous Computing assumes that users and their computing devices are highly mobile. Because it is unlikely that mobile networks will be equally available in the same quality everywhere, there may be varying levels of connectivity, ranging from full network availability through low-bandwidth connectivity, to no connection at all. As a consequence, software components in the system cannot assume that the connections between them are static and always available. The event-based style is essential for ubiquitous computing, since it offers a good decoupling of the communicating entities in terms of space, time, and program flow. This chapter starts with an introduction to the different interaction models found in distributed systems. Next, a classification of publish/subscribe-systems is presented. We then describe a formal data and filter model that allows us to precisely define the semantics of event filters. Based on this model, we discuss different routing algorithms for the efficient distribution of event notifications in a network. Finally, a number of examples for publish/subscribe systems are presented.
Adapting to the User
Authors: Jöst Matthias
Published: May 2011

Adaptation is one of the key requirements to handle the increasing complexity in today’s computing environments. This chapter focuses on the aspect of adaptation that puts the user into focus. In this context it introduces the different adaptation types possible for ubiquitous computing services like interaction, content, and presentation. To allow for an automatic adaptation it is important to get some means about the users. Basic requirements to model the users and approaches to personalize applications will be presented.
Accounting and Charging
Authors: Stiller Burkhard , Hausheer David , Gerke Jan , Racz Peter , Morariu Cristian , Waldburger Martin
Published: May 2011

Charging for IP-based communications determines the overall term for metering or monitoring, accounting, pricing, charge calculation, and billing. These five actions are detailed in this chapter to provide a clear view on their interdependencies as well as their relations to distributed computing. Since an ubiquitous computing approach does require communication means between all entities involved, the provisioning of these communication channels is supported typically by commercial service providers— covering network, transport, and value-added services. Thus, the legal and contractual relationships between customers and providers as well as technological choices of protocols, mechanisms, and parameters define the area of interest here.
CoBIs
Authors: Spieß Patrik , Müller Jens
Published: May 2011

This chapter describes example use cases for ubiquitous computing technology in a corporate environment that have been evaluated as prototypes under realistic conditions. The main example reduces risk in the handling of hazardous substances by detecting potentially dangerous storage situations and raising alarms if certain rules are violated. We specify the requirements, implementation decisions, and lessons learned from evaluation. It is shown that ubiquitous computing in a shop floor, warehouse, or retail environment can drastically improve real-world business processes, making them safer and more efficient.
Real-Time Location Tracking Mashup for Enterprise
Authors: Hamdi Louenas , Gurram Rama , Raiyani Samir
Published: May 2011

Real-time location applications are mainly desktop based and costly for development and maintenance. In this project we worked on a Web service based architecture for monitoring and driving real-time analysis of fire truck missions. We used Web 2.0 technologies on the client side and SAP NetWeaver enterprise service oriented platform on the server side.
Multimodal Warehouse Project
Authors: Raiyani Samir , Winkler Matthias
Published: May 2011

In this chapter, we present the Multimodal Warehouse Project, which aimed at applying multimodal interaction to a warehouse picking process. We provide an overview of the warehouse picking procedure as well as the overall architecture of the multimodal picking application and technologies applied to design the application. Furthermore, we describe the execution of user tests of the picking application at a warehouse and present the results of these tests. In this way, the authors hope to provide the reader with a better understanding of how multimodal systems can be built and the opportunities as well as the challenges of applying multimodal technology to real-world application scenarios.
Number Theory and Finite Fields
Authors: Mogollon Manuel
Published: May 2011

Mathematics plays an important role in encryption, public-key, authentication, and digital signatures. Knowing certain basic math concepts such as counting techniques, permutations, plotting a curve, raising a number to a power, modular arithmetic, and congruence would help to understand the material in this book.
Knowledge-Based Planning Using Planning Support Systems
Authors: Vonk Guido , Geertman Stan
Published: May 2011

Planning support systems are geo-information-based tools to support those involved in planning tasks. Many see planning support systems capable of improving the handling of knowledge and information in planning processes. Better handling of knowledge and information could help those involved in planning to handle the ever-increasing complexity of planning tasks. In spite of these potential benefits, planning support systems have not yet become widely used in planning practice. A major problem contributing to the arrear in planning support systems use is the profound miscommunication that exists between planners, planning support systems developers, and researchers. Currently there exists little insight in how to solve this problem and enhance the use of planning support systems. This chapter provides practiceoriented lessons about PSS use. Those willing to apply planning support systems in planning practice may use these lessons to enhance the successful use of planning support systems and the handling of knowledge and information in planning.
E-Sevan in Hyderabad, India
Authors: Srinivasan Sumeeta , Rogers Peter , Padam Sudarsanam
Published: May 2011

In 1996, Srinivasan surveyed the use of the Web as a dissemination tool by Indian government agencies and found that there was little Web-based participation by either government or non-government agencies. By 2002, there was at least one Indian city that offered citizens the opportunity to pay property taxes on the Web (http://www.esevaonline.com). Clearly, even in a developing country like India, e-government has come a long way in a very short time. In this chapter, the authors survey the use of this facility in Hyderabad, a rapidly growing city in India. They look in particular at the implications of e-Seva for local planning agencies. The authors also suggest a geographical information systemsbased framework whereby virtual agencies could create data ‘portals’ that allow for inter-agency data sharing. The study relies on interviews with the users of e-Seva and other government officials who are interested in its use for planning at the metropolitan and regional levels. While the study focuses on Hyderabad, India, as its case study, the implications to planning in other cities in India are also an important aspect of the research.
Spatial Transformations in Istanbul CBD
Authors: Geçer Feral , Avar Adile Arslan , Velibeyoglu Koray , Saygin Ömür
Published: May 2011

Now with the intensive use of information and communication technologies, many cities around the world are competing to become a global city. Istanbul is enumerated within the first 50 cities in the globalization process, other than the triad of New York, London, and Tokyo. This chapter explores urban space transformation of Maslak, the contemporary central business district of Istanbul, with respect to information and communication technologies, by using deconcentration and economic restructuring approaches of urban theory. Compared to other global cities, Istanbul has distinctive characteristics, since it has been passing through a unique transformation process. More specifically, its economic, political, and social characteristics distinguish Istanbul from other cities within the same category (Gamma) of world cities. This study has revealed that transformations in Istanbul were not primarily driven by information and communication technologies. In contrast information and communication technology’s role in the transformation of the Istanbul central business district is only a contributing factor.
Activity-Based Costing System for a Small Manufacturing Company
Authors: Januszewski Arkadiusz
Published: May 2011

The selection of the right cost calculation method is of critical importance when it comes to determining the real product profitability (as well as clients and other calculation objects). Traditional cost calculation methods often provide false information. The literature offers many examples of big companies that have given up traditional methods and applied a new method: activity-based costing (ABC). They discovered that many products that are manufactured generate losses and not profits. Managers, based on incorrect calculations, mistakenly believed in the profitability of each product. Turney (1991) reports on an example of an American manufacturer of over 4,000 different integrated circuits. The cost calculation with the allocation of direct production costs as machinery-hour markup demonstrated a profit margin of over 26% for each product. Implementing ABC showed that the production of more than half of the products was not profitable, and having factored in additional sales and management costs (which accounted for about 40% of the total costs), it was as much as over 75%.
Balanced Scorecard Concepts, Technology, and Applications
Authors: Palacios Ricardo Colomo , Gómez Berbís Juan Miguel , Crespo Ángel García
Published: May 2011

The balanced scorecard (BSC) harnesses the potential of checking and verifying the status of a company by evaluating and carefully assessing strategic aspects beyond the purely financial indicators. The significant impact of the BSC from a business standpoint has brought critical mass in use and the emergence of a number of technologies that will make a technology-supported BSC a reality. This article presents an overview of the concept and its history, evolution, major applications, and implications with a particular emphasis in decision making and decision support technologies.
Decision Support and Problem Formulation Activity
Authors: Paradice David
Published: May 2011

While decision choices are certainly important and warrant appropriate attention, early stages of the decisionmaking process may be even more critical in terms of needing adequate support. The alternatives from which a decision maker may be able to choose are integrally tied to the assumptions made about the problem situation. Consequently, decision support systems (DSSs) may be more effective in helping decision makers to make good choices when support for problem formulation is provided. Research validates the notion that support for problem formulation and structuring leads to better decisions. This article explores this concept and looks at opportunities in emerging software trends to continue development of problem formulation support in DSS-type settings.
Decision Support Systems Concept
Authors: Power Daniel J.
Published: May 2011

Since the late 1960s, researchers have been developing and implementing computerized systems to support management decision makers. A number of decision support system (DSS) typologies were proposed in the early 1980s (Alter, 1980; Sprague & Carlson, 1982), but technology developments and new applications led to an expanded DSS framework (Power, 2000a, 2000b, 2001). The expanded DSS framework that is explained in detail in Power (2002b) helps decision makers and DSS developers understand and categorize decision support projects as well as existing decision support systems. Many terms are used to describe decision support systems. For example, some vendors and managers use the terms business intelligence, collaborative systems, computationally oriented DSS, data warehousing, model-based DSS, and online analytical processing (OLAP) software to label decision support systems. Software vendors use these more specialized terms for both descriptive and marketing purposes. The terms used to describe decision support capabilities are important in making sense about what technologies have been deployed or are needed. Some DSSs are subsystems of other information systems and this integration adds to the complexity of categorizing and identifying DSSs. In general, decision support systems are a broad class of information systems used to assist people in decision- making activities (Power, 2004).
Distributed Model Management
Authors: El-Gayar Omar F. , Deokar Amit V.
Published: May 2011

Modern organizations are faced with numerous information management challenges in an increasingly complex and dynamic environment. Vast amounts of data and myriads of models of reality are routinely used to predict key outcomes. Decision support systems (DSS) play a key role in facilitating decision making through management of quantitative models, data, and interactive interfaces (Power, 2000). The basic thrust of such applications is to enable decision-makers to focus on making decisions rather than being heavily involved in gathering data and conceiving and selecting analytical decision models. Accordingly, the number and complexity of decision models and of modeling platforms has dramatically increased, rendering such models a corporate (and national) resource (Muhanna & Pick, 1994). Further, Internet technology has brought many new opportunities to conduct business electronically, leading to increased globalization. Managers and decision makers are increasingly collaborating in distributed environments in order to make efficient and effective use of organizational resources. Thus, the need for distributed decision support in general, and model sharing and reuse in particular, is greater today than ever before. This has attracted significant attention from researchers in information systems-related areas to develop a computing infrastructure to assist such distributed model management (Krishnan & Chari, 2000). In this article, we focus on distributed model management advances, and the discussion is organized as follows. The next section provides a background on model management systems from a life-cycle perspective. This is followed by a critical review of current research status on distributed decision support systems from a model management viewpoint with a particular emphasis on Web services. Future trends in this area are then discussed, followed by concluding remarks.
Dynamic System Simulation for Decision Support
Authors: Pendegraft Norman , Rounds Mark
Published: May 2011

Simulation is a powerful methodology for decision support because it allows managers to experiment with models prior to implementing a policy or decision. There are several approaches to computer simulation: continuous event simulation, discrete event simulation, and Monte Carlo simulation. Continuous event simulation can be used to model dynamic system which cannot otherwise be easily modeled.
Ethical Decision Making
Authors: Mustamil Norizah , Quaddus Mohammed
Published: May 2011

Studies have shown that organizations are putting more effort in enforcing the ethical practices in their decision making activities (Janet, Armen, & Ted, 2001). An increasing number of models have also been proposed that have attempted to explore and explain various philosophical approaches to ethical decision making behaviour. In addition, many empirical studies have been presented in various scholarly journals focusing on this subject with the aim of putting theory into practice (O’Fallon & Butterfield, 2005). Nevertheless, unethical practices including fraud, corruption, and bribery continue to be reported (Trevino & Victor, 1992). Bartlett (2003) claims that there is a large gap between theory and practice in ethical decision making research, as existing models are trapped either in undersocialized view (focus on individual factors only) or oversocialized view (focus on situational factor only). Development of a theoretical framework in the ethical decision making area has proven to be very challenging due to the multitude of complex and varied factors that contribute to ethical behaviour. This article attempts to contribute in this challenging area by reviewing and examining the major existing models and presenting an integrated model of ethical decision making model.
The Evaluation of Decision-Making Support Systems' Functionality
Authors: Forgionne Giusseppi , Russell Stephen
Published: May 2011

Contemporary decision-making support systems (DMSSs) are large systems that vary in nature, combining functionality from two or more classically defined support systems, often blurring the lines of their definitions. For example, in practical implementations, it is rare to find a decision support system (DSS) without executive information system (EIS) capabilities or an expert system (ES) without a recommender system capability. Decision-making support system has become an umbrella term spanning a broad range of systems and functional support capabilities (Alter, 2004). Various information systems have been proposed to support the decision-making process. Among others, there are DSSs, ESs, and management support systems (MSSs). Studies have been conducted to evaluate the decision effectiveness of each proposed system (Brown, 2005; Jean-Charles & Frédéric, 2003; Kanungo, Sharma, & Jain, 2001; Rajiv & Sarv, 2004). Case studies, field studies, and laboratory experiments have been the evaluation vehicles of choice (Fjermestad & Hiltz, 2001; James, Ramakrishnan, & Kustim, 2002; Kaplan, 2000). While for the most part each study has examined the decision effectiveness of an individual system, it has done so by examining the system as a whole using outcome- or user-related measures to quantify success and effectiveness (Etezadi-Amoli & Farhoomand, 1996; Holsapple & Sena, 2005; Jain, Ramamurthy, & Sundaram, 2006). When a study has included two or more systems, individual system effects typically have not been isolated. For example, Nemati, Steiger, Lyer, and Herschel (2002) presented an integrated system with both DSS and AI (artificial intelligence) functionality, but they did not explicitly test for the independent effects of the DSS and AI capabilities on the decision-making outcome and process. This article extends the previous work by examining the separate impacts of different DMSSs on decision effectiveness.
Finite-Base Revision Supporting Knowledge Management and Decision Making
Authors: Dargam Fátima C.C.
Published: May 2011

Generation and most of all sustainability of organizational success rely heavily on proper decision making and on the application of knowledge management (KM) concepts, where knowledge-based structures are fundamental components. KM can also be viewed as a means to support enhanced decision making through effective control of organizational knowledge. One of the main goals of KM is to capture, codify, organize, and store relevant knowledge into repositories, knowledge bases (KB), for later retrieval and use by organizations. However, there is always the danger of accumulating knowledge in an increasingly vast way, such that it becomes impossible to process it when necessary. Therefore, appropriate technologies have to be identified to protect us from irrelevant information. As the study in Handzic (2004) shows, decision-makers need to pursue primarily one KM strategy in order to use knowledge effectively. Moreover, the codification KM strategy using procedural knowledge maps was proven to be quite appropriate for solving decision problems of a complex nature. It is commonly agreed that KM can bridge the existing information and communication gaps within organizations, consequently improving decision making (Dargam & Rollett, 2007).
Fuzzy Thermal Alarm System for Venus Express
Authors: Serra P. , Ribeiro R. A. , Pereira R. Marques , Steel R. , Niezette M. , Donati A.
Published: May 2011

In the aerospace field, where satellites and spacecraft contain numerous components that require constant, yet indirect, surveillance of large amounts of data, monitoring tools give the operators constant access to the state of the machinery, facilitating prompt and appropriate responses to any problems that may arise. The objective of developing a Venus Express alarm system (Steel, 2006) is to monitor the thermal characteristics of each spacecraft face with respect to spacecraft altitude relative to the sun’s position. A thermal alarm monitoring tool assumes particular importance in the Venus Express mission as the spacecraft will be subject to high levels of solar radiation due to its proximity to the sun. In the space context, in particular for missioncontrol purposes, fuzzy inference systems provide a suitable technique to build this type of alarm system because the knowledge is imprecise or partial, going beyond the use of traditional, that is, crisp, methods (Ribeiro, 2006). Furthermore, the fuzzy linguistic approach used (Mendel, 2001; Ross, 2004) allows for an effective complement to human operators by creating systems that can support their actions in case of any fault detected.
Intelligent DSS Under Verbal Decision Analysis
Authors: Ashikhmin Ilya , Furems Eugenia , Petrovsky Alexey , Sternin Michael
Published: May 2011

Verbal decision analysis (VDA) is a relatively new term introduced in Larichev and Moshkovich (1997) for a methodological approach to discrete multi-criteria decision making (MCDM) problems that was under elaboration by Russian researchers since the 1970s. Its main ideas, principles, and strength in comparison with other approaches to MCDM problems are summarized in Moshkovich, Mechitov, and Olson (2005) and in posthumous book (Larichev, 2006) as follows: problem description (alternatives, criteria, and alternatives’ estimates upon criteria) with natural language without any conversion to numerical form; usage of only those operations of eliciting information from a decision maker (DM) that deems to be psychologically reliable; control of DM’s judgments consistency, and traceability of results, that is, the intermediate and final results of a problem solution have to be explainable to DM. The main objective of this chapter is to provide an analysis of the methods and models of VDA for implementing them in intellectual decision support systems. We start with an overview of existing approaches to VDA methods and model representation. In the next three sections we present examples of implementing the methods and models of VDA for intellectual decision support systems designed for such problems solving as discrete multi-criteria choice, construction of expert knowledge base, and multi-criteria assignment problem. Finally, we analyze some perspective of VDA-based methods to implement them for intellectual decision support systems.
Introduction to Fuzzy Logic and Fuzzy Linear Programming
Authors: Vasant Pandian , Kale Hrishikesh S.
Published: May 2011

Fuzzy logic (FL) is a mathematical technique for dealing with imprecise data and problems that have many solutions rather than one. Although it is implemented in digital computers which ultimately make only yesno decisions, FL works with ranges of values, solving problems in a way that more resembles human logic. FL is a multi-valued (as opposed to binary) logic developed to deal with imprecise or vague data. Classical logic holds that everything can be expressed in binary terms: 0 and 1, black and white, yes or no; in terms of Boolean algebra, everything is in one set or another but not in both. FL allows for partial membership in asset values between 0 and 1, shades of gray, and introduces the concept of the “fuzzy set.” When the approximate reasoning of FL (Zadeh, 1965) is used with an expert system, logical inferences can be drawn from imprecise relationships. FL theory was developed by Lofti A. Zadeh at the University of California in the mid 1960s. However, it was not applied commercially until 1987 when the Matsushita Industrial Electric Co. used it to automatically optimize the wash cycle of a washing machine by sensing the load size, fabric mix, and quantity of detergent and has applications in the control of passenger elevators, household applications, and so forth.
Knowledge Representation to Empower Expert Systems
Authors: Jones James D.
Published: May 2011

Knowledge representation is a field of artificial intelligence that has been actively pursued since the 1940s.1 The issues at stake are that given a specific domain, how do we represent knowledge in that domain, and how do we reason about that domain? This issue of knowledge representation is of paramount importance, since the knowledge representation scheme may foster or hinder reasoning. The representation scheme can enable reasoning to take place, or it may make the desired reasoning impossible. To some extent, the knowledge representation depends upon the underlying technology. For instance, in order to perform default reasoning with exceptions, one needs weak negation (aka negation as failure. In fact, most complex forms of reasoning will require weak negation. This is a facility that is an integral part of logic programs but is lacking from expert system shells. Many Prolog implementations provide negation as failure, however, they do not understand nor implement the proper semantics. The companion article to this article in this volume, “Logic Programming Languages for Expert Systems,” discusses logic programming and negation as failure.
Multi-Agent Simulation and Management Practices
Authors: Siebers Peer-Olaf , Aickelin Uwe , Celia Helen , Clegg Chris
Published: May 2011

Intelligent agents offer a new and exciting way of understanding the world of work. Agent-based simulation (ABS), one way of using intelligent agents, carries great potential for progressing our understanding of management practices and how they link to retail performance. We have developed simulation models based on research by a multidisciplinary team of economists, work psychologists, and computer scientists. We will discuss our experiences of implementing these concepts working with a well-known retail department store. There is no doubt that management practices are linked to the performance of an organisation (Reynolds, Howard, Dragun, Rosewell, & Ormerod, 2005; Wall & Wood, 2005). Best practices have been developed, but when it comes down to the actual application of these guidelines considerable ambiguity remains regarding their effectiveness within particular contexts (Siebers, Aickelin, Battisti, et al., 2008). Most operational research (OR) methods can only be used as analysis tools once management practices have been implemented. Often they are not very useful for giving answers to speculative “what-if” questions, particularly when one is interested in the development of the system over time rather than just the state of the system at a certain point in time. Simulation can be used to analyse the operation of dynamic and stochastic systems. ABS is particularly useful when complex interactions between system entities exist, such as autonomous decision making or negotiation. In an ABS model the researcher explicitly describes the decision process of simulated actors at the micro level. Structures emerge at the macro level as a result of the actions of the agents and their interactions with other agents and the environment. We will show how ABS experiments can deal with testing and optimising management practices such as training, empowerment or teamwork. Hence, questions such as “will staff setting their own break times improve performance?” can be investigated.
Neural Network Time Series Forecasting Using Recency Weighting
Authors: Morantz Brad , Whalen Thomas , Zhang G. Peter
Published: May 2011

In building a decision support system (DSS), an important component is the modeling of each potential alternative action to predict its consequence. Decision makers and automated decision systems (i.e., modelbased DSSs) depend upon quality forecasts to assist in the decision process. The more accurate the forecast, the better the DSS is at helping the decision maker to select the best solution. Forecasting is an important contributor to quality decision making, in both the business world and for engineering problems. Retail stores and wholesale distributors must predict sales in order to know how much inventory to have on hand. Too little can cause lost sales and customer dissatisfaction—If too much is on hand, then other inventory problems can occur (i.e., cash flow, ad valorem tax, etc.). If the goods are perishable, it could most certainly be a financial loss. Items that occur over time, as in the number of cars sold per day, the position of an airplane, or the price of a certain stock are called “time series.” When these values are forecast, the accuracy can vary, depending on the data set and the method. This subject has been greatly discussed in the literature and many methods have been presented. Artificial neural networks (ANN) have been shown to be very effective at prediction. Time series forecasting is based upon the assumption that the underlying causal factors are reflected in the lagged data values. Many times, a complete set of the causal factors either is not known or is not available. Predictions are made based upon the theory that whatever has occurred in the near past will continue into the near future. Time series forecasting uses past values to try and predict the future. A slight modification to this concept is the application of recency. What happened more recently is closer to the current situation than the more distant past. The older data still contain knowledge, it just is not as important (or as correct) as the newest information. Things change, life is dynamic, and what used to be may be no more or may be to a different extent. Modification of the training algorithm of a neural network forecaster to consider recency has been proven on real economic data sets to reduce residual by as much as 50%, thereby creating a more accurate model which would allow for better decision making.
Probabilistic Methods for Uncertainty Quantification
Authors: Chugunov N. , Shepelyov G. , Sternin M.
Published: May 2011

The complexity and interdisciplinary nature of modern problems are often coupled with uncertainty inherent to real-life situations. There is a wide class of real-world problems described by well-formulated quantitative models for which a decision maker (DM) has to deal with uncertainty in values of initial parameters for these models. A good example of such a problem is hydrocarbon reservoir assessment in the exploration stage, which requires the involvement and joint consideration of geological, petroleum engineering, and financial models of reservoir exploration. The consequences of some unreasonable decisions can lead to millions of dollars in loss to the companies as it happens in the oil business, where industry sources on investment decision analysis continue to report surprise values (outside the [P10;P90] range) far more than the 20% indicated by this interval (Welsh, Begg, Bratvold, & Lee, 2004).
Towards a Framework for Assisting Decision-Makers Assess the Potential of E-Business Models
Authors: Finnegan Pat , Hayes Jeremy
Published: May 2011

The electronic business landscape is confusing for many new entrants, and many of them face the paradox that hesitation would run the risk of being left behind, but rushing in and making an incorrect choice regarding e-business initiatives could have dire consequences for organisations (Wise & Morrison, 2000). E-business poses significant challenges for organisations as it affects both how organisations relate to external parties, and how they operate internally in managing activities, processes, and systems (Rayport & Jaworski, 2001). Porter (2001) argues that the companies that succeed with e-business will be those that use the Internet in conjunction with their traditional business models and activities. Osterwalder, Ben Lagha, and Pigneur (2002) and Osterwalder, Pigneur, and Tucci (2005) argue that “after an initial phase of euphoria and the following disillusionment” (in relation to e-business) it is important to understand fully how business models function. Linder and Cantrell (2000) argue that existing frameworks are not sufficient to describe the rich array of business model choices facing managers in e-business environments. In particular, decisionmakers have a difficult task in assessing the range of proposed models in order to determine those that are most suitable. The objective of this research is to develop a ‘prerequisites framework’ for assisting decision-makers assess the suitability of e-business models during the intelligence phase of the decision-making process. Following this introduction, the business model concept is discussed and the range of models proposed by researchers explored. The issue of deciding on appropriate business models is then outlined. This is followed by an explanation of the theoretical grounding for the proposed framework, and a discussion of its operationalisation as a series of Likert scales. The research concludes with thoughts on refining and testing the framework.
B2B E-Commerce Development in Syria and Sudan
Authors: Kardaras Dimitris K.
Published: May 2011

There is a revolution transforming the global economy. Web technology is transforming all business activities into information-based. The rate of technological change is so rapid that electronic commerce (eC) is already making fundamental changes in the electronic land-escape. eC over the Internet is a new way of conducting business. It has the potential to radically alter economic activities and social environment and it has already made a major impact on large sectors such as communications, finance, and retail-trade. eC has also been hailed as the promise land for small and medium sized enterprises. Therefore, it will no longer be possible, operationally or strategically, to ignore the information-based virtual value chain for any business. eC promises that smaller or larger companies as well as developed or developing countries can exploit the opportunities spawned by eC technologies and compete more effectively. The introduction of the Internet for commercial use in 1991 had created the first real opportunity for electronic markets. It offered a truly global publicly available computer network infrastructure with easy and inexpensive access. After nearly three decades of notfor- profit operations, the network was transformed into a worldwide digital market place practically overnight. This shift from physical market place to a digital one had contributed a great deal to cost reductions, speeding up communication, and provision of users with more timely information (Shaw, Gardner, & Thomas, 1997; Timmers, 1999).
Data Caching Patterns
Authors: Shan Tony C. , Hua Winnie W.
Published: May 2011

As information technology (IT) has become part of business in today’s globalized economy, increasingly higher performance of information systems is demanded by the business models to support various business operations and help the business compete and succeed. IT must strive to be nimble and adaptive to provide a higher level of services and, at the same time, reduce the total cost of ownership (TCO). In most situations, the current enterprise infrastructure must be extended to get the most out of the existing investments. Creating innovative solutions is an effective approach to achieve this goal, and scalable data management is one of the most valuable innovations.
Data Flow Diagram Use to Plan Empirical Research Projects
Authors: Mende Jens
Published: May 2011

Yourdon and Constantine (1979), De Marco (1979), and Gane and Sarson (1979) introduced the data flow diagram (DFD) more than a quarter of a century ago, as a systems planning tool that is particularly useful in the fields of software engineering and information systems development. But the DFD is not restricted to those fields. Empirical research projects are systems too (which consist of interconnected sources, data, collection processes, files, analysis processes, knowledge, and users), and those systems are similar to information systems. This article reports how the DFD can also be useful in planning empirical research projects. This finding should be advantageous to research planners, individual researchers, research advisors, research supervisors, or research managers. And it should be especially advantageous to research planners in information and communication technology (ICT) because they know DFDs already, so they can get the planning advantages with little or no extra learning effort. This finding was obtained from two research projects. The first was planned without the aid of a DFD and failed. It was then replanned with a DFD and redone in a second project, which succeeded.
E-Commerce Recommendation Systems
Authors: Markellos Konstantinos , Markellou Penelope , Mertis Aristotelis , Panayiotaki Angeliki
Published: May 2011

In the last decade electronic and wireless technologies have changed the way companies do business forever. E-commerce (electronic commerce) and e-business (electronic business) feature as extremely dynamic economic sectors and at the same time, as the most appealing ways of beginning or expanding a business activity. Successful companies today recognize these technologies and the Internet as mainstream to business success. Indeed, their future will continue to be promising to companies seeking means for cost cutting, enhanced productivity, improved efficiency, and increased customers’ satisfaction. On the other hand, this networked economy is notably characterized by the impersonal nature of the online environment and the extensive use of IT (information technology), as opposed to face-to-face contact for transactions.
E-Knowledge
Authors: Sorrentino Fortunato
Published: May 2011

Change is driving the new millennium along many paths. There is one particular place where the change is especially deep, and that is the path in which knowledge is heading. However, this is not always perceivable and it takes an act of detachment to appreciate it. The same is happening with the main cause of that change, which is technology: it is so much a part of our daily life, that we are no longer aware of it. Contemporary digital media and digital technologies, that is, the most innovating front of ICT, have a characteristic: they reciprocally function as triggers, giving way to sudden waves of adoption, which in turn start others, all much more rapid and frequent than in the past. We are flooded, often unwillingly, by storms of technological stimuli: even though we may not be conscious of them, the result is an empowerment of our faculties of action, communication and cognition. The term “e-knowledge” has been coined, as several others of similar structure, to catch, via the “e-” extension (electronic), the new shape of knowledge which is peculiar of a deeply technology-driven world. In such a world, technes (re. technology) is no longer “the art of making” and it becomes the “art of knowing”.
An E-Learning Project for a Basic Mathematics Course at the University
Authors: Torriero Anna , Scancarello Immacolata
Published: May 2011

This article provides an evaluation of the impact of a specific e-learning platform (www.blackboard.com) upon pass rates, in particular on the MidTerm tests pass rate of “Calculus I”, a math course held at the Catholic University of Milan. An ICT project for a basic math course was developed and introduced in 2001 at the Catholic University, Faculty of Economics. Designed for freshmen, the course currently involves as many as 1,200 students, which is quite an achievement when compared with other e-learning blended courses available at the same university. The chief objective of the course is to supplement face-to-face lessons with the online learning activities implemented inside and/or outside the traditional classroom. The innovation of this project consists not only in its technological features but also in its tracking facilities. In fact, student online activities can be tracked down and teachers are provided with continuous feedback for the same to be redesigned. In addition, students can widen their knowledge of the subject matter through additional learning materials such as interactive self-assessment tests, guided assignments, and so forth.
Is Electronic Knowledge a Plural Thought?
Authors: Frabboni Franco
Published: May 2011

With the third millennium a new and attractive scenario has opened up, giving voice to an old face of culture: knowledge. Its “new” identity—holistic, multidimensional, and ecosystemic—was highlighted by the European Union in 2000 at the Lisbon conference. In the 21st century there is a star carrying out on its tail these words: welcome to the knowledge society. Knowledge is an immaterial good needed by any nation, because it’s like a bank account that any complex and changing society needs to have. It’s a capital with three faces: economic, social and human (Frabboni, 2006). a. As an economic resource, knowledge promotes a mass-school, a school for everybody: the competitiveness and reliability of a productive system are based on schooling and on the “well-made heads” of younger generations, b. As a social resource it promotes democracy, because knowledge provides all citizens with the necessary alphabets to create a widespread social cohesion; therefore education must be spread during all the seasons of life, from childhood to old age, c. As a human resource it helps the person-subject to move away from the devastating mass-subject. A school of knowledge and of values (i.e., of mind and heart) will have to invest on a person that is nonduplicable, noneasily influenced, and nonuseful; with his or her eyes open on dreams, utopias, and enchantment. School has the task of forming a plural mind and an ethic of solidarity.
Enhancement of Recorded Respiratory Sound Using Signal Processing Techniques
Authors: Jin Feng , Sattar Farook
Published: May 2011

Pulmonary auscultation has been the key method to detect and evaluate respiratory dysfunctions for many years. However, auscultation with a stethoscope is a subjective process that depends on the individual’s own hearing, experience, and ability to differentiate between different sounds (Sovijarvi et al, 2000). Therefore, the computerized method for recording and analysis of pulmonary auscultative signals, being an objective way, are recently playing a more and more important role in the evaluation of patients with pulmonary diseases. Noise interference is one of the most influential factors when dealing with respiratory sound recordings. By definition of (Rossi et al, 2000), any sound not directly induced by breathing is regarded as background noise (BN). BN is divided into two types: environmental noise, which consists of continuous noise and transient noise, and nonrespiratory sounds and body sounds (muscle contraction sounds, skin friction, and heart sounds). The adaptive filtering is usually used to reduce the background noise. However, the problem of existing proposed filtering methods are either not able to minimize the interference or provides distortion which is especially undesirable for biomedical signals (Donoho, 1992).
Higher Education's New Frontier for the E-University and Virtual Campus
Authors: Cartelli Antonio
Published: May 2011

Technologies entered in education since their first appearance and were used both for improving the efficacy and efficiency of traditional teaching and for creating new teaching-learning opportunities (Galliani et al., 1999). The definition “educational technologies” was coined in the 1950s to describe the equipments to be used in teaching-learning controlled environments. The introduction of the computer in teaching led to the definition of “new educational technologies” to mark the overcoming of traditional systems like audio-visual media (i.e., cinema, radio and television) with the new digital medium. In the 1970s the Association for Educational Communications and Technology (AECT) formulated the definition of instructional technology as “… the theory and practice of design, development, utilization, management, and evaluation of processes and resources for learning. ... We can think about it as a discipline devoted to techniques or ways to make learning more efficient based on theory but theory in its broadest sense, not just scientific theory”. The Internet in the 1990s introduced further elements of innovation in the use of technologies for education with an exponential growth of instruments and resources leading to the transition from face to face (f2f) teaching to online teaching-learning experiences. The Internet more than other technological experiences entered in the educational systems all over the world and is today marking a revolution in continuous education and lifelong learning.
ICT Literacy in the Information Age
Authors: Macefield Ritchie
Published: May 2011

The development of homosapien man can be classified into ages. These ages fundamentally affect the patterns of how humans work, play and interact. Some social anthropologists (e.g., Toffler & Toffler, 1994) have identified three such ages: agricultural, industrial, and information. Definitions of these ages are complex, and a detailed discussion of them lies outside the scope of this chapter, however, they can usefully be typified as follows: • The agricultural age affected us through systems geared to processing and distributing food. • The industrial age affected us through systems geared to processing and distributing energy; energy that is harnessed to provide large-scale travel and automation. • The information age affects us through systems for processing and distributing information. Therefore, in the Information Age many people will work and play exclusively using ICT systems and use this technology as a primary means of interacting with other people.