Fasteners Standard Bolts and Nuts: American National Standard bolts and nuts, both inches and metric, are produced in hexagon form. Square head bolts and nuts are only produced in the inch series. Square bolts and nuts, hexagon bolts, and hexagon flat nuts are unfinished. Unfinished bolts and nuts are not machined on any surface except for the threads. Finished bolts and nuts are characterized by a “washer face” machined on the bearing surface. The washer face is 1/64” thick but drawn at 1/32”. The diameter is equal to 1 ½ times the body diameter.
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The Layers of Computing The “User” (you) Application Software (the “apps”) Systems Software (Windows, MacOS, Linux) Hardware (the nuts and bolts)
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Mike Meyers’ CompTIA A+® Guide to Managing and Troubleshooting PCs Fifth Edition Table 12.4 Upgrade Paths (continued) Upgrading from Windows 7/8/8.1 to Windows 8.1 From Windows 7/8/8.1 Upgrade to Windows 8.1 Windows 71 Windows 8.1 Windows 8 Windows 8 Pro Windows 8.1, Windows 8.1 Pro2 Copyright © 2016 by McGraw-Hill 8.1 Pro, Windows 8.1 Enterprise Education. All rightsWindows reserved. Windows 8 Pro with Media Center Windows 8.1 Pro, Windows 8.1 Enterprise Windows 8 Enterprise Windows 8.1 Pro, Windows 8.1 Enterprise Windows 8.1 Windows 8.1 Pro Table 12.4 Upgrading from Windows 7/8/8.1 to Windows 8.1 Windows 8.1 Pro Windows 8.1 Enterprise Copyright © 2016 by McGraw-Hill Education. All rights reserved.
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DBs, DWs are merging as In-memory DBs: SAP® In-Memory Computing Enabling Real-Time Computing SAP® In-Memory enables real-time computing by bringing together online transaction proc. OLTP (DB) and online analytical proc. OLAP (DW). Combining advances in hardware technology with SAP InMemory Computing empowers business – from shop floor to boardroom – by giving real-time bus. proc. instantaneous access to data-eliminating today’s info lag for your business. In-memory computing is already under way. The question isn’t if this revolution will impact businesses but when/ how. In-memory computing won’t be introduced because a co. can afford the technology. It will be because a business cannot afford to allow its competitors to adopt the it first. Here is sample of what in-memory computing can do for you: • Enable mixed workloads of analytics, operations, and performance management in a single software landscape. • Support smarter business decisions by providing increased visibility of very large volumes of business information • Enable users to react to business events more quickly through real-time analysis and reporting of operational data. • Deliver innovative real-time analysis and reporting. • Streamline IT landscape and reduce total cost of ownership. Product managers will still look at inventory and point-of-sale data, but in the future they will also receive,eg., tell customers broadcast dissatisfaction with a product over Twitter. Or they might be alerted to a negative product review released online that highlights some unpleasant product features requiring immediate action. From the other side, small businesses running real-time inventory reports will be able to announce to their Facebook and Twitter communities that a high demand product is available, how to order, and where to pick up. Bad movies have been able to enjoy a great opening weekend before crashing 2nd weekend when negative word-of-mouth feedback cools enthusiasm. That week-long grace period is about to disappear for silver screen flops. Consumer feedback won’t take a week, a day, or an hour. The very second showing of a movie could suffer from a noticeable falloff in attendance due to consumer criticism piped instantaneously through the new technologies. It will no longer be good enough to have weekend numbers ready for executives on Monday morning. Executives will run their own reports on revenue, Twitter their reviews, and by Monday morning have acted on their decisions. The final example is from the utilities industry: The most expensive energy a utilities provides is energy to meet unexpected demand during peak periods of consumption. If the company could analyze trends in power consumption based on real-time meter reads, it could offer – in real time – extra low rates for the week or month if they reduce their consumption during the following few hours. In manufacturing enterprises, in-memory computing tech will connect the shop floor to the boardroom, and the shop floor associate will have instant access to the same data as the board [[shop floor = daily transaction processing. Boardroom = executive data mining]]. The shop floor will then see the results of their actions reflected immediately in the relevant Key Performance Indicators (KPI). This advantage will become much more dramatic when we switch to electric cars; predictably, those cars are recharged the minute the owners return home from work. Hardware: blade servers and multicore CPUs and memory capacities measured in terabytes. Software: in-memory database with highly compressible row / column storage designed to maximize in-memory comp. tech. SAP BusinessObjects Event Insight software is key. In what used to be called exception reporting, the software deals with huge amounts of realtime data to determine immediate and appropriate action for a real-time situation. [[Both row and column storage! They convert to column-wise storage only for Long-Lived-High-Value data?]] Parallel processing takes place in the database layer rather than in the app layer - as it does in the client-server arch. Total cost is 30% lower than traditional RDBMSs due to: • Leaner hardware, less system capacity req., as mixed workloads of analytics, operations, performance mgmt is in a single system, which also reduces redundant data storage. [[Back to a single DB rather than a DB for TP and a DW for boardroom dec. sup.]] • Less extract transform load (ETL) between systems and fewer prebuilt reports, reducing support required to run sofwr. Report runtime improvements of up to 1000 times. Compression rates of up to a 10 times. Performance improvements expected even higher in SAP apps natively developed for inmemory DBs. Initial results: a reduction of computing time from hours to seconds. However, in-memory computing will not eliminate the need for data warehousing. Real-time reporting will solve old challenges and create new opportunities, but new challenges will arise. SAP HANA 1.0 software supports realtime database access to data from the SAP apps that support OLTP. Formerly, operational reporting functionality was transferred from OLTP applications to a data warehouse. With in-memory computing technology, this functionality is integrated back into the transaction system. Adopting in-memory computing results in an uncluttered arch based on a few, tightly aligned core systems enabled by service-oriented architecture (SOA) to provide harmonized, valid metadata and master data across business processes. Some of the most salient shifts and trends in future enterprise architectures will be: • A shift to BI self-service apps like data exploration, instead of static report solutions. • Central metadata and masterdata repositories that define the data architecture, allowing data stewards to work across all business units and all platforms Real-time in-memory computing technology will cause a decline Structured Query Language (SQL) satellite databases. The purpose of those databases as flexible, ad hoc, more business-oriented, less IT-static tools might still be required, but their offline status will be a disadvantage and will delay data updates. Some might argue that satellite systems with in-memory computing technology will take over from satellite SQL DBs. SAP Business Explorer tools that use in-memory computing technology represent a paradigm shift. Instead of waiting for IT to work on a long queue of support tickets to create new reports, business users can explore large data sets and define reports on the fly.
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CAINE 2013 Call for Papers 26th International Conference on Computer Applications in Industry and Engineering September 25{27, 2013, Omni Hotel, Los Angles, Califorria, USA Sponsored by the International Society for Computers and Their Applications (ISCA) Provides an international forum for presentation and discussion of research on computers and their applications. The conference also includes a Best Paper Award. CAINE{2013 will feature contributed papers as well as workshops and special sessions. Papers will be accepted into oral presentation sessions. The topics will include, but are not limited to, the following areas: Agent-Based Systems Image/Signal Processing Autonomous Systems Information Assurance Big Data Analytics Information Systems/Databases Bioinformatics, Biomedical Systems/Engineering Internet and Web-Based Systems Computer-Aided Design/Manufacturing Knowledge-based Systems Computer Architecture/VLSI Mobile Computing Computer Graphics and Animation Multimedia Applications Computer Modeling/Simulation Neural Networks Computer Security Pattern Recognition/Computer Vision Computers in Education Rough Set and Fuzzy Logic Computers in Healthcare Robotics Computer Networks Fuzzy Logic Control Systems Sensor Networks Data Communication Scientic Computing Data Mining Software Engineering/CASE Distributed Systems Visualization Embedded Systems Wireless Networks and Communication Important Dates Workshop/special session proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .May 2.5,.2.01.3 Full Paper Submission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .June 5,.2.0.1.3. Notication of Acceptance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .July.5 , 2013. Pre-registration & Camera-Ready Paper Due . . . . . . . . . . . . . . . . . . . . . .August 5, 2013. Event Dates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .September 25-27, 2013 The 22nd SEDE Conference is interested in gathering researchers and professionals in the domains of Software Engineering and Data Engineering to present and discuss high-quality research results and outcomes in their fields. SEDE 2013 aims at facilitating cross-fertilization of ideas in Software and Data Engineering, The conference also encourages research and discussions on topics including, but not limited to: . Requirements Engineering for Data Intensive Software Systems. Software Verification and Model of Checking. Model-Based Methodologies. Software Quality and Software Metrics. Architecture and Design of Data Intensive Software Systems. Software Testing. Service- and Aspect-Oriented Techniques. Adaptive Software Systems . Information System Development. Software and Data Visualization. Development Tools for Data Intensive. Software Systems. Software Processes. Software Project Mgnt . Applications and Case Studies. Engineering Distributed, Parallel, and Peer-to-Peer Databases. Cloud infrastructure, Mobile, Distributed, and Peer-to-Peer Data Management . Semi-Structured Data and XML Databases. Data Integration, Interoperability, and Metadata. Data Mining: Traditional, Large-Scale, and Parallel. Ubiquitous Data Management and Mobile Databases. Data Privacy and Security. Scientific and Biological Databases and Bioinformatics. Social networks, web, and personal information management. Data Grids, Data Warehousing, OLAP. Temporal, Spatial, Sensor, and Multimedia Databases. Taxonomy and Categorization. Pattern Recognition, Clustering, and Classification. Knowledge Management and Ontologies. Query Processing and Optimization. Database Applications and Experiences. Web Data Mgnt and Deep Web Submission procedures May 23, 2013 Paper Submission Deadline June 30, 2013 Notification of Acceptance July 20, 2013 Registration and Camera-Ready Manuscript Conference Website: http://theory.utdallas.edu/SEDE2013/ September 25-27, 2013 Omni Hotel, Los Angeles, California, USA The International Conference on Advanced Computing and Communications (ACC-2013) provides an international forum for presentation and discussion of research on a variety of aspects of advanced computing and its applications, and communication and networking systems. ACC-2013 will feature contributed as well as invited papers in all aspects of advanced computing and communications and will include a BEST PAPER AWARD given to a paper presented at the conference. Important Dates May 5, 2013 - Special Sessions Proposal Papers on Current FAUST Cluster (functional gap based) and on revisions to FAUST Classification. June 5, 2013 - Full Paper Submission Who will lead what? July 5, 2013 - Author Notification Aug. 5, 2013 - Advance Registration & Camera Ready Paper Due
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Design Insights Continued This time, the researchers put 18 healthy volunteers on two carefully controlled diets for two months. One was a nut-free version of a standard low-cholesterol diet. The other was nutritionally similar, except 20% of the calories came from about 3 ounces of walnuts per day. ...... On the no-nuts diet, the volunteers’ cholesterol levels fell 6 percent. When they switched to the walnut diet, their cholesterol declined an additional 12 percent. Everyone’s cholesterol dropped while eating nuts, and the average decrease was 22 points, from 182 to 160. Her analysis: While not a fatal flaw, eighteen subjects is a very small study. The subjects were put on a low-cholesterol diet, which means their cholesterol was going to drop no matter what. Think about eating three ounces of walnuts every day. It comes to more than fifty pounds a year. ... They lost me. Did all the subjects first eat no-nuts, then the nuts regime? Or were there two groups, one starting with no nuts and one starting with nuts? Did the 22-point cholesterol drop include the decrease attributable to the low-cholesterol diet alone? How long did the study go on -- that is, would the cholesterol level have continued to drop from the low-cholesterol diet with or without the nuts? Those walnuts displaced other food -- was the drop a substitution effect alone? In other words, because of the bias in which the data were collected and summarized, we actually know nothing from either study. However, upon first reading, it appears as though information is unbiased. It is this subtle bias, that is unintentional to the decision maker, which can cause significant problems for a DSS. Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010
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Time Barbie Tootle Hayes Cape Cartoon Room I Cartoon Room II Suzanne M. Scharer Rosa M. Ailabouni Monday Aug 5th, 2013 10:10-11:50 A1L-A Analog Circuits I Chr: Ming Gu, Shantanu Chakrabartty Track: Analog and Mixed Signal Integrated Circuits A1L-B Low Power Digital Circuit Design Techniques A1L-C Chr: Joanne Degroat Student Contest I Track: Digital Integrated Chr: Mohammed Ismail Circuits, SoC and NoC Track: INVITED ONLY A1L-D Design and Analysis for Power Systems and Power Electronics Chr: Hoi Lee, Ayman Fayed Track: Power Systems and Power Electronics A1L-E Design and Analysis of Linear and Non-Linear Systems Chr: Samuel Palermo Track: Linear and Non-linear Circuits and Systems A1L-F Emerging Technologues Chr: Khaled Salama Track: Emerging Technologies Monday Aug 5th, 2013 13:10-14:50 A2L-A Analog Circuits II Chr: Ming Gu, Shantanu Chakrabartty Track: Analog and Mixed Signal Integrated Circuits A2L-B Low Power VLSI Design Methodology Chr: Genevieve Sapijaszko Track: Digital Integrated Circuits, SoC and NoC A2L-C Student Contest II Chr: Sleiman Bou-Sleiman Track: INVITED ONLY A2L-D Power Management and Energy Harvesting Chr: Ayman Fayed, Hoi Lee Track: Power Management and Energy Harvesting A2L-E Oscillators and Chaotic Systems Chr: Samuel Palermo, Warsame Ali Track: Linear and Non-linear Circuits and Systems A2L-F Bioengineering Systems Chr: Khaled Salama Track: Bioengineering Systems and Bio Chips A4L-A Analog Design Techniques I Chr: Dong Ha Track: Analog and Mixed Signal Integrated Circuits A4L-B Imaging and Wireless Sensors Chr: Igor Filanovsky Track: Analog and Mixed Signal Integrated Circuits A4L-C Special Session: Characterization of Nano Materials and Circuits Chr: Nayla El-Kork Track: SPECIAL SESSION A4L-D Special Session: Power Management and Energy Harvesting Chr: Paul Furth Track: SPECIAL SESSION A4L-E Communication and Signal Processing Circuits Chr: Samuel Palermo Track: Linear and Non-linear Circuits and Systems A4L-F Sensing and Measurement of Biological Signals Chr: Hoda Abdel-Aty-Zohdy Track: Bioengineering Systems and Bio Chips B2L-A Analog Design Techniques II Chr: Valencia Koomson Track: Analog and Mixed Signal Integrated Circuits B2L-B VLSI Design Reliability Chr: Shantanu Chakrabartty, Gursharan Reehal Track: Digital Integrated Circuits, SoC and NoC B2L-D B2L-C Special Session: University and Delta-Sigma Modulators Industry Training in the Art of Chr: Vishal Saxena Electronics Track: Analog and Mixed Signal Chr: Steven Bibyk Integrated Circuits Track: SPECIAL SESSION B2L-E Radio Frequency Integrated Circuits Chr: Nathan Neihart, Mona Hella Track: RFICs, Microwave, and Optical Systems B2L-F Bio-inspired Green Technologies Chr: Hoda Abdel-Aty-Zohdy Track: Bio-inspired Green Technologies B3L-A Analog Design Techniques III Chr: Valencia Koomson Track: Analog and Mixed Signal Integrated Circuits B3L-B VLSI Design, Routing, and Testing Chr: Nader Rafla Track: Programmable Logic, VLSI, CAD and Layout B3L-C Special Session: High-Precision and High-Speed Data Converters I Chr: Samuel Palermo Track: SPECIAL SESSION B3L-D B3L-E Special Session: Advancing the RF/Optical Devices and Circuits Frontiers of Solar Energy Chr: Mona Hella, Nathan Neihart Chr: Michael Soderstrand Track: RFICs, Microwave, and Track: SPECIAL SESSION Optical Systems B5L-A Nyquist-Rate Data Converters Chr: Vishal Saxena Track: Analog and Mixed Signal Integrated Circuits B5L-B Digital Circuits Chr: Nader Rafla Track: Programmable Logic, VLSI, CAD and Layout B5L-C Special Session: High-Precision and High-Speed Data Converters II Chr: Samuel Palermo Track: SPECIAL SESSION B5L-D Special Session: RF-FPGA Circuits and Systems for Enhancing Access to Radio Spectrum (CAS-EARS) Chr: Arjuna Madanayake, Vijay Devabhaktuni Track: SPECIAL SESSION B5L-E B5L-F Analog and RF Circuit Memristors, DG-MOSFETS and Techniques Graphine FETs Chr: Igor Filanovsky Chr: Reyad El-Khazali Track: Analog and Mixed Signal Track: Nanoelectronics and Integrated Circuits Nanotechnology C2L-A Phase Locked Loops Chr: Chung-Chih Hung Track: Analog and Mixed Signal Integrated Circuits C2L-B Computer Arithmetic and Cryptography Chr: George Purdy Track: Programmable Logic, VLSI, CAD and Layout C2L-C Special Session: Reversible Computing Chr: Himanshu Thapliyal Track: SPECIAL SESSION C2L-D Special Session: Self-healing and Self-Adaptive Circuits and Systems Chr: Abhilash Goyal, Abhijit Chatterjee Track: SPECIAL SESSION C2L-E Digital Signal Processing-Media and Control Chr: Wasfy Mikhael, Steven Bibyk Track: Digital Signal Processing C2L-F Advances in Communications and Wireless Systems Chr: Sami Muhaidat Track: Communication and Wireless Systems C3L-A SAR Analog-to-Digital Converters Chr: Vishal Saxena Track: Analog and Mixed Signal Integrated Circuits C3L-B Real Time Systems Chr: Brian Dupaix, Abhilash Goyal Track: System Architectures C3L-C Image Processing and Interpretation Chr: Annajirao Garimella Track: Image Processing and Multimedia Systems C3L-D Special Session: Verification and Trusted Mixed Signal Electronics Development Chr: Greg Creech, Steven Bibyk Track: SPECIAL SESSION C3L-E Digital Signal Processing I Chr: Ying Liu Track: Digital Signal Processing C3L-F Wireless Systems I Chr: Sami Muhaidat Track: Communication and Wireless Systems C5L-A Wireless Systems II Chr: Sami Muhaidat Track: Communication and Wireless Systems C5L-B System Architectures Chr: Swarup Bhunia, Abhilash Goyal Track: System Architectures C5L-C Image Embedding Compression and Analysis Chr: Annajirao Garimella Track: Image Processing and Multimedia Systems C5L-D Low Power Datapath Design Chr: Wasfy Mikhael Track: Digital Integrated Circuits, SoC and NoC C5L-E Digital Signal Processing II Chr: Moataz AbdelWahab Track: Digital Signal Processing C5L-F Advances in Control Systems, Mechatronics, and Robotics Chr: Charna Parkey, Genevieve Sapijaszko Track: Control Systems, Mechatronics, and Robotics Monday Aug 5th, 2013 16:00-17:40 Tuesday Aug 6th, 2013 10:10-11:50 Tuesday Aug 6th, 2013 13:10-14:50 Tuesday Aug 6th, 2013 16:00-17:40 Wednesday Aug 7th, 2013 10:10-11:50 Wednesday Aug 7th, 2013 13:10-14:50 Wednesday Aug 7th, 2013 16:00-17:40 B3L-F Carbon Nanotube-based Sensors and Beyond Chr: Nayla El-Kork Track: Nanoelectronics and Nanotechnology 5
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Final example is from the utilities industry: The most expensive energy that a utilities company provides is energy to meet unexpected demand during peak periods of consumption. If the company could analyze trends in electrical power consumption based on real-time meter reading, it could offer its consumers – in real time – extra low rates for the week or month if they reduce their consumption during the following few hours. This advantage will become much more dramatic when we switch to electric cars; predictably, those cars are going to be recharged the minute the owners return home from work, which could be within a very short period of time. In-memory computing technology combines hardware and software technology innovations. Hardware innovations include blade servers and CPUs with multicore architecture and memory capacities measured in terabytes for massive parallel scaling. Software innovations include an in-memory database with highly compressible row and column storage specifically designed to maximize in-memory computing tech. Parallel processing takes place in the database layer rather than in the application layer as we know it from the client-server architecture. Total cost is to be 30% lower than traditional relational database technology due to: • Leaner hardware and less system capacity required, as mixed workloads of analytics, operations, performance mgmt are handled within a single system, which also reduces redundant data storage. Adopting in-memory computing results in an uncluttered architecture based on a few, tightly aligned core systems enabled by serviceoriented architecture (SOA) to provide harmonized, valid metadata and master data across business processes. Some of the most • Reduced extract, transform, and load (ETL) salient shifts and trends in future enterprise processes between systems and fewer prebuilt architectures will be: reports, reducing the support effort required to • A shift to BI self-service apps like data run the software. exploration, instead of static report solutions. • Central metadata and master-data Replacing traditional databases in SAP repositories that define the data architecture, applications with in-memory computing allowing data stewards to work effectively technology resulted in report runtime across all business units and all platforms improvements of up to a factor of 1000 and • Instantaneous analysis of real-time trending compression rates of up to a factor of 10. algorithms with direct impact on live execution of business processes Performance improvements are expected to be even higher in SAP apps natively developed Real-time in-memory computing technology for inmemory DBs, with initial results will most probably cause a decline in sheer showing a reduction of computing time numbers of Structured Query Language (SQL) from several hours to a few seconds. satellite databases. The purpose of those databases as flexible, ad hoc, more businessHowever, in-memory computing will not oriented, less IT-static tools might still be eliminate the need for data warehousing. A required, but their offline status will be a real-time reporting function will solve old disadvantage and will delay data updates. challenges and create new opportunities, but Some might argue that satellite systems with new challenges will arise. SAP HANA 1.0 in-memory computing technology will take software supports realtime database access to over from satellite SQL DBs. data from the SAP apps that support OLTP. SAP Business Explorer tools that use inFormerly, operational reporting functionality memory computing technology represent a was transferred from OLTP applications to a paradigm shift. Instead of waiting for IT to data warehouse. With in-memory computing work on a long queue of support tickets to technology, this functionality is integrated create new reports, business users can access back into the transaction system. large data sets for data exploration and defining reports on the fly.
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Architecture  Our overall architectural strategy is based on our technical principles. Our strategy addresses protection at various levels within a same system from the application layer down to the OS, Virtual Machine Monitor (VMM), and hardware. It is our contention that single-layer solutions typically improve one layer by pushing performance and security limitations to other layers, with questionable overall results. Key aspects of our strategy are the following:  Layered ATI Architecture. Conceptually, we organize the (untrusted) system software into layers, and for each layer, we propose the separation of a small, verifiable abstract trusted interface (ATI) from the functionality-rich remaining untrusted software components at that layer. This multi-layer separation can be seen as a generalization of the MILS (multiple independent levels of security) model, where the implementation of the ATI at each layer is analogous to the single-layer MILS separation kernel. We prefix a layer’s ATI with a two-letter acronym: HW-ATI for the hardware layer, VM-ATI for the virtual machine and hypervisor layer, OS-ATI for the operating system layer, MW-ATI for the middleware layer, DB-ATI for the database management system layer, and AP-ATI if an application is exporting a trusted application programmer interface. This is an application of the Isolation and Independence Principles.  Natural and Artificial Diversity. The ATI architecture does not mandate a uniquely defined ATI at each layer. There may be multiple, overlapping ATIs at any layer. Furthermore, concrete diverse implementations may exist for the same or different ATIs (e.g., Intel TXT and AMD SVM at the hardware layer). One of the main design goals of the ATI Architecture is the active incorporation of diverse designs and implementations at each layer. For diverse implementations, we will use artificial diversity tools (e.g., compiler tools for creating different program representations as discussed in [31]). For diverse designs, we will rely on natural diversity of different system components (e.g., variants of Unix and possibly Windows at the OS layer). This natural diversity offers protection beyond the implementation-level protection of artificial diversity tools.  Figure 2 The Abstract Trusted Interface (ATI) Architecture  HW-ATI (Intel TXT, AMD SVM, secure co-processors)  HW-Untrusted  VM-ATI (Xen, VMware)  VMM-Untrusted  OS-ATI (seL4 microkernel)  OS-Untrusted  MW-ATI (secure comm.)  Middleware-Unt1  DB-ATI (co-DBMS)  DBMS-Untrusted  AP-ATI  Application-Untrusted  Composition of ATIs. The main constraint of the implementation of an ATI is that it may only use the facilities provided by ATIs of lower layers. This is indicated by the downward arrows on the right side of Figure 2. The advantage of this restriction is that by utilizing only trusted components, the implementation of ATI of higher layers remains trusted. The requirement is that the ATIs at each layer must have specific functionality, such that the resulting ATI implementation can be formally verified. This follows from the Isolation Principle. The ATI architecture is flexible and dynamically reconfigurable. As new software or hardware components are verified to be secure at each layer, that layer’s ATI may be expanded by incorporating the new components. Conversely, if a new vulnerability is discovered in some implementation of ATIs, the affected components (and higher level components that use this implementation) should be excluded from the trusted side. Until the problem is fixed, the system falls back to reduced ATI functionality that remains trusted. In real-time computing, when a precise computation is under the risk of missing a deadline, alternative modules implemented with reduced computational precision in an approach called Imprecise Computation [18] can still complete a simplified task within the time constraint. Analogously, we will explore alternative designs that use different underlying ATIs for a given critical functionality (perhaps more limited than the original one). When a full-functionality application is affected by attacks or newly discovered vulnerabilities, these alternative design and implementations based on different ATIs provide secure critical
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REFLECTIVE JOURNALING TOOLS Reflective J ournalingTools LEARNING: • How is practice different from theory? Did this exercise help you to understand your theory and the application of theory better? How? Why? • Did you learn anything that helped you to better understand a theory, the use of a test that you were taught in lectures/labs? • What did you learn that were not taught in lectures (e.g. communication with patients), and how did you cope or learn more about this to improve your performance? Or how can this be incorporated into lectures? • Did this exercise help you to remember or recall later other aspects of previous experiences that you have forgotten? • Did this exercise help you identify areas that need to be changed, improved etc. in yourself/peers/staff/clinical training etc. Why and how? • What actions did you take you take and what are the results (what did you learn)? SELF ASSESSMENT: • Did you identify areas/issues that you were unclear of, or disagreed with your supervisors/peers, or different from what you have learned in your past lectures? Justify the actions taken. Did this help you in your learning? How? • Have you been open to share with others and to listen what others have to say? • Have you paid attention to both your strong and weak points? Can you identify them? What are you going to do about them? • How did faculty supervision/RW help you in your clinical experiences in relation to your professional growth? (eg. did it encourage you to be more independent, to become more confident in professional activities and behaviors etc) • What have you noted about yourself, your learning altitude, your relationship with peers/supervisors etc. that has changed from doing this exercise? COMMUNICATION: • What have you learned from interacting with others (peers/supervisors/staff etc)? • Did your peers gain anything from YOUR involvement in this exercise and vice versa? • Did this exercise encourage and facilitate communication? • Did you clarify with your supervisors/peers about problematic issues identified? Why (not)? What are the results? • How could you/your peers/staff help you overcome negative emotions arising from your work? Did your show empathy for your peers? PROFESSIONALISM: • Did you learn that different situations call for different strategies in management? • What are the good and bad practices that you have identified? How would you suggest to handle the bad/poor practices identified (if any)? • Did you learn to accept and use constructive criticism? • Did you accept responsibility for your own actions? • Did you try to maintain high standard of performance? • Did you display a generally positive altitude and demonstrate self-confidence? • Did you demonstrate knowledge of the legal boundaries and ethics of contact lens practice? EMOTION & PERSONAL GROWTH: • Did you reflect on your feelings when dealing with the case/peers/supervisor (eg. frustration, embarrassment, fear) for this exercise? If not, why not? If yes, who should be responsible — you, your patient or your supervisor? Why? • Did you find reflection (as required for this exercise) helpful, challenging, and enjoyable, change the way you learn? How? Why (not)? • How and what did you do to handle negative emotions arising from doing this subject? How could these feelings be minimized? • Did you try to find out if your feelings were different from your peers? Why? What did you do to help your peers? • Did you reflect on your learning altitude? How was it? Is there room for improvement? How? Why (not)? • What did you learn about your relationship with your peers/supervisors? What did you learn about working with others? Ideas for Reflective Journaling Writing Contributor(s): Dr. Michael Ying and Dr. Pauline Cho
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Microsoft Windows Overview     MS-DOS 1.0 released in 1981  4000 lines of assembly language source code  ran in 8 Kbytes of memory  used Intel 8086 microprocessor  Windows 2000  included services and functions to support distributed processing  Active Directory  plug-and-play and powermanagement facilities  Windows XP released in 2001 Windows 3.0 shipped in 1990  16-bit  GUI interface  implemented as a layer on top of MS-DOS Windows 95  32-bit version  led to the development of Windows 98 and Windows Me   Windows Vista shipped in 2007  Windows Server released in 2008  Windows 7 shipped in 2009, as well as Windows Server 2008 R2  Windows Azure Windows NT (3.1) released in 1993  32-bit OS with the ability to support older DOS and Windows applications as well as provide OS/2 support goal was to replace the versions of Windows based on MS-DOS with an OS based on NT  targets cloud computing
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References • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • [1] K. Gai, M. Qiu, S. Jayaraman, and L. Tao. Ontology-based knowledge representation for secure self-diagnosis in patient-centered telehealth with cloud systems. In The 2nd IEEE Int’l Conf. on Cyber Security and Cloud Computing, pages 98–103, New York, USA, 2015. IEEE. [2] M. Qiu, M. Zhong, J. Li, K. Gai, and Z. Zong. Phase-change memory optimization for green cloud with genetic algorithm. IEEE Transactions on Computers, 64(12):3528 – 3540, 2015. [3] K. Gai and S. Li. Towards cloud computing: a literature review on cloud computing and its development trends. In 2012 Fourth Int’l Conf. on Multimedia Information Networking and Security, pages 142–146, Nanjing, China, 2012. [4] K. Gai, M. Qiu, H. Zhao, L. Tao, and Z. Zong. Dynamic energy-aware cloudlet-based mobile cloud computing model for green computing. Journal of Network and Computer Applications, 59:46–54, 2016. [5] L. Tao, S. Golikov, K. Gai, and M. Qiu. A reusable software component for integrated syntax and semantic validation for services computing. In 9th Int’l IEEE Symposium on Service-Oriented System Engineering, pages 127–132, San Francisco Bay, USA, 2015. [6] K. Gai, M. Qiu, B. Thuraisingham, and L. Tao. Proactive attributebased secure data schema for mobile cloud in financial industry. In The IEEE International Symposium on Big Data Security on Cloud; 17th IEEE International Conference on High Performance Computing and Communications, pages 1332–1337, New York, USA, 2015. [7] M. Qiu, K. Gai, B. Thuraisingham, L. Tao, and H. Zhao. Proactive user-centric secure data scheme using attribute-based semantic access controls for mobile clouds in financial industry. Future Generation Computer Systems, PP:1, 2016. [8] D. Pancho, J. Alonso, O. Cordo´ n, A. Quirin, and L. Magdalena. FINGRAMS: visual representations of fuzzy rule-based inference for expert analysis of comprehensibility. IEEE Transactions on Fuzzy Systems, 21(6):1133–1149, 2013. [9] X. Wang, Z. Ma, J. Chen, and X. Meng. f-RIF metamodel-centered fuzzy rule interchange in the semantic web. Knowledge-Based Systems, 70:137–153, 2014. [10] M. Lytras and R. Garc´ıa. Semantic web applications: A framework for industry and business exploitation-what is needed for the adoption of the semantic web from the market and industry. International Journal of Knowledge and Learning, 4(1):93–108, 2008. [11] Y. Li, K. Gai, Z. Ming, H. Zhao, and M. Qiu. Intercrossed access control for secure financial services on multimedia big data in cloud systems. ACM Transactions on Multimedia Computing Communications and Applications, PP(99):1, 2016. [12] A. Altowayan and L. Tao. Simplified approach for representing partwhole relations in OWL-DL ontologies. In The IEEE International Symposium on Big Data Security on Cloud; 17th IEEE International Conference on High Performance Computing and Communications, pages 1399–1405, New York, NY, USA, 2015. IEEE. [13] A. Formica. Similarity reasoning for the semantic web based on fuzzy concept lattices: An informal approach. Information Systems Frontiers, 15(3):511–520, 2013. [14] M. Minsky. A framework for representing knowledge. MIT Publishing, 1974. [15] N. Nilsson. Logic and artificial intelligence. Artificial Intelligence, 47(1-3):31–56, 1991. [16] K. Gai, M. Qiu, L. Chen, and M. Liu. Electronic health record error prevention approach using ontology in big data. In 17th IEEE International Conference on High Performance Computing and Communications, pages 752–757, New York, USA, 2015. [17] K. Patel, I. Dube, L. Tao, and N. Jiang. Extending OWL to support custom relations. In IEEE 2nd International Conference on Cyber Security and Cloud Computing, pages 494–499, New York, NY, USA, 2015. IEEE.
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PPC – Gains from Specialization and Trade • Coffee (lb/day) 24 With specialization and trade, would both Susan and Tom be better off if – Susan specializes in producing coffee; Susan and Tom exchange 12 nuts, 12 coffee 12 – Tom specializes in producing nuts; – And, Susan trade one pound of coffee for one pound of nuts with Tom. • Without specialization and trade, the total output and consumption is 16 pounds of coffee and 16 pounds of nuts; • With specialization and trade, the total output and consumption is 24 pounds of coffee and 24 pounds of nuts. 8 8 12 Nuts (lb/day) 24 13
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Hex and Square Nuts The most common nuts, generally made of steel and are hexagonal or • Jam Nuts – Used to lock a threaded part in place. square in shape. • Castellated and Slotted Nuts – Secure a nut in place so it can’t possibly come loose. • Self-Locking Nuts – Stay firmly in place even with constant vibration. • Many other types of nuts available for special uses.
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// RadioButtonsTest.cs // Using RadioButtons to set message window options. //using statements go here; // form contains several radio buttons--user chooses one // from each group to create a custom MessageBox private System.Windows.Forms.Label promptLabel; private System.Windows.Forms.Label displayLabel; private System.Windows.Forms.Button displayButton; Label is used to prompt user Label is used to display which button was pressed Display the text Display private System.Windows.Forms.RadioButton questionButton; private System.Windows.Forms.RadioButton informationButton; private System.Windows.Forms.RadioButton exclamationButton; private System.Windows.Forms.RadioButton errorButton; private System.Windows.Forms.RadioButton retryCancelButton; private System.Windows.Forms.RadioButton yesNoButton; private System.Windows.Forms.RadioButton yesNoCancelButton; private System.Windows.Forms.RadioButton okCancelButton; private System.Windows.Forms.RadioButton okButton; private System.Windows.Forms.RadioButton To store user’s choice ofevent One abortRetryIgnoreButton; RadioButtons are created for the enumeration options handling exists for options iconType isall created. Object iconType is a the radio buttons in The enumeration name groupBox1 and groupBox2 private System.Windows.Forms.GroupBox groupBox2; MessageBoxIcon indicate which button private System.Windows.Forms.GroupBox groupBox1; enumeration to display private MessageBoxIcon iconType = MessageBoxIcon.Error; private MessageBoxButtons buttonType = MessageBoxButtons.OK; 16
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Sample essay.txt file: IBM announced today that researchers are testing the Linux operating system on a prototype wristwatch device in an attempt to prove that Linux can be used as the basic software on even the smallest devices. “Designed to communicate wirelessly with PCs, cell phones and other wireless-enabled devices, the ‘smart watch’ will have the ability to view condensed e-mail messages and directly receive pager-like messages,” IBM said in a statement. However, IBM does not have plans to commercialize the Linux watch itself, a spokeswoman said. “This is just a research prototype,” said Takako Yamakura. “Some say Linux cannot be scaled down. This is just to show Linux is capable of doing this.” The Linux operating system is seen as an alternative to Microsoft Corp.’s Windows operating system, and is popular with programmers for its open source code, which allows programmers to develop and tinker with programs. “Several benefits accrue from the use of Linux in small pervasive devices,” IBM said in the statement. “The availability of source code and a well-understood application programming environment makes it easy for students, researchers, and software companies to add new features and develop applications.” Linux, which was developed by Finnish programmer Linus Torvalds, is used for many basic functions of Web sites, but is not yet considered mature enough for heavier business tasks. IBM has been working to develop the system for everything from the wrist watch to supercomputers. “With Linux rapidly becoming an able to create new applications the intent of IBM’s research is CS 240 industry standard, it’s important that developers be across all platforms, including pervasive devices, and to further that work,” IBM said. 13
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