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Like most books, this book represents the work of many people In this case, however, an unusually large number of people around the world have worked to make the Java 2 Platform, Micro Edition nd also this book reality In five short years, a humble, two-person research project at Sun Labs grew rapidly into a highly collaborative product development and standardization effort involving hundreds of companies and thousands of people all over the world The summary that follows is an attempt to give a glimpse into the different groups of people who participated in this journey To these and many others too numerous to mention, we give our thanks and appreciation for what they did to make these ideas and this book possible Attempting to name these people in no way diminishes the contributions of those who we also meant to name but in the pressure of time and the failure of memory somehow overlooked Many people read draft versions of this book and sent us comments that improved the book substantially The authors would like to thank all the reviewers for their willingness to send comments and constructive criticism on the various versions of the book and the sample applications The authors would also like to thank Lisa Friendly for allowing us to publish this book in Sun's Java book series and for lending us capable technical writing resources to finish this book Jim Holliday, our technical writer and editor at Sun Microsystems, edited various versions of this book tirelessly Without his expertise in the mysteries of desktop publishing, grammar, and that pesky topic known as punctuation, this work would have been much worse for the wear Three other people at Sun Microsystems deserve special mention: Cindy Bloch, Senior Technical Writer, who contributed greatly in editing several chapters; Tasneem Sayeed, Staff Engineer, who provided very detailed comments on the various versions of the book; and Tim Dunn, Visual Designer, who devoted many long hours to perfecting the graphics in this book Numerous companies have been involved in the standardization efforts related to the Java 2 Platform, Micro Edition We would like to thank all the CLDC and MIDP expert group members for their active participation and valuable contributions In addition to the official members of the CLDC and MIDP expert groups, hundreds of other companies and individuals sent us feedback while the CLDC and MIDP standardization efforts were in progress The authors found it amazing how much of their time people were willing to contribute to ensure the progress of the Java technology in the wireless space Someone once said that hardware without software is a space heater Similarly, without products, the CLDC and MIDP specifications would be limited in their value The authors would like to thank wireless device manufacturers, wireless network operators, and software developers for widely embracing the CLDC and MIDP standards, thereby allowing software developers all over the world to finally have a common platform for mobile software development Various product groups in Sun's Consumer and Mobile Systems Group (CMSG) organization participated in the design and implementation of the CLDC and MIDP reference implementations The authors would like to thank Sun's CLDC team, MIDP team, and Wireless Toolkit team members who worked on the reference implementations of the standards and products discussed in this book The TCK (Technology Compatibility Kit) and Quality Assurance teams at CMSG also played a critical role in ensuring the quality and compatibility f the products The Nokia authors would like to thank the following Nokia people who have been closely involved in the MIDP 20 standardization work: Kari Syst Kimmo L t Markku Tamski, Anna Zhuang, and Antti Rantalahti Special thanks go to all the Nokia Java teams who have made it possible for Nokia to launch over 30 products with J2ME support and to ship tens of millions of J2ME devices The Motorola authors would like to thank all the people in Motorola who helped make CLDC and MIDP a success Special thanks go to the team members in Motorola's WSAS and iDEN groups that had the vision, developed the first CLDC/MIDP device to reach the market, and still continue to push the envelope in terms of performance and capabilities.



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Ten decision makers commented favorably on the difference made by the MCHM All 10 of those sampled agreed that there was a desire for this technology, and seven SMEs had favorable general MCHM importance comments The initial impression given by the respondents to the survey indicates that the MCHM has smart data collection capabilities This conclusion can be drawn from the preponderance of favorable comments by the decision makers regarding importance, effectiveness, and suitability The MCHM met several areas of importance in addressing the requirements of the military medical mission It was demonstrably effective in documentation of mass-patient encounters It was felt to be more suitable than the current paper-based status quo The possibility of further hardening adapting the unit for use in other extreme environments is reasonable Finally, the initial and sustaining costs are under consideration According to our research, importance is the highest weighted factor of smart data collection The importance of the MCHM has been sustained by the surveys The decision makers surveyed recommended that the MCHM continue to be developed Their comments lend credence to the importance of the MCHM in the tasks performed, the importance of the tasks, the difference made by the MCHM, the importance of technology, and favorable MCHM importance comments in general These factors alone would warrant further consideration of the MCHM prototype for experimentation in other exercises It is strongly recommended that the MCHM be identi ed and marketed to the sponsors of all exercises worldwide for potential use and experimentation Based on the surveys, the MCHM performed effectively However, with minor changes to the screens and pick lists, the tool was perceived to have extraordinary potential effectiveness The decision makers gave favorable comments about their perceptions that the MCHM performed as advertised The decision makers also commented favorably on the effectiveness of the actual MCHM performance and the ease of training Several decision makers offered unfavorable comments concerning the ability to personally see results and the overall effectiveness of the MCHM To this end, it is recommended that a panel of subject matter experts be established in a 3-day session to review and study the screens and pick lists and recommend necessary changes Generally, the top three suitability factors are usability, compatibility, and cost Several unfavorable perceptions related to these factors were reported by the decision makers Problems regarding security, battery life, use in other environments, and technical support were identi ed Usability can be associated with effectiveness as detailed earlier Compatibility must be ddressed in detail In order to move the MCHM closer to operational deployment, it must be integrated with the Navy Medical Enterprise Architecture MCHM must be able to access and accept data from legacy applications and share data with appropriate systems The preceding case study illustrates the fact that all enterprises exist for a purpose, that is expressed in mission and value statements, goals, and objectives, otherwise summarized into business plans Once desired outcomes are identi ed, leaders organize resources into functions In this case, according to our research, importance is the highest weighted factor of smart data collection, followed by effectiveness and.

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suitability Functions identify the work that needs to be done to produce outcomes How the work is accomplished is de ned as processes, where process activities constitute proprietary differentiation In this case example, proprietary differentiation or a unique way of accomplishing things is achieved through a variety of ways that begin with creative leadership in the military command The MCHM was used to select the right customers to service, that is, the Thai people Selecting the right things to do by performing humanitarian services and organizing these activities into a superior mix of people and technology, while applying scarce resources in an optimal manner, lead to the collection of smart data that pointed out the importance, effectiveness, and suitability of the system for delivering optimal healthcare performance By structuring the balance of consequences such that doing the right things the right way is rewarded and deviations are dissuaded, the MCHM ensured that the Thai customers received valuable results and assured stakeholders that the military enterprise is performing optimally in the delivery of medical services Data is at the heart of each of these management activities and that is why we focus on smart data as a principal contributor to optimizing performance Difference Between Smart and Dumb Data Example There are limitations with capital budgeting problems that use the traditional approach and assume the future will be an extrapolation of the present We will provide an arti cial intelligence (AI) and simulation method for capital budgeting that is a smart data approach to show executives the right way to use data for increasing interoperability and enterprise performance optimization An example of dumb data is the traditional accounting methods that led to the 2008 Wall Street debacle This accounting information provides little help for reducing costs and improving productivity and quality and may even be harmful These systems do not produce accurate product costs for pricing, sourcing, product mix, and responses to competition The system encourages managers to contract to the short-term cycle of the monthly pro t and loss statement This accounting data is dumb data that is too aggregated, too late, and too distorted to be relevant for managers planning and control decisions Therefore smart data is actionable It will be the product of a more cost effective approach to delivering higher quality information Smart ata is engineered for high states of interoperability among disparate users, which includes semantic mediation that translates meaning from one enterprise lexicon to another despite differences Activity based costing (ABC), which is similar to cost management accounting practices, utilizes smart data because it allocates costs to the products and services that use them Knowing the costs of activities supports efforts to improve processes Once activities can be traced to individual products or services, then additional strategic smart data is made available The effects of delays and inef ciencies become readily apparent and the company can focus on reducing hidden costs To understand the difference between dumb data and smart data, the executive must (1) know how information is exchanged by the enterprise today, including the.

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