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2.-Komunikasi virtual dipahami sebagai virtual reality pada ruang lingkup (alam maya) dengan menggunakan internet. Komunikasi virtual sebenarnya dilakukan dengan cara representasi informasi digital yang bersifat diskrit. A Network-based System Architecture forRemote Medical Applications- Remote Medical Network (http://web it kth se/~axel/papers/2007/APAN-HuiminShe pdf)Huimin She1. 21Dept of Electronic. Computer and SoftwareSystems. Royal initiate of Technology. Sweden2ASIC & System State Key Lab.. Dept ofMicroelectronics. Fudan Univ.. abduct. ChinaTel: +46-8-790-4247Zhonghai LuDept of Electronic. Computer and SoftwareSystems. Royal initiate of Technology. SwedenTel: +46-8-790-4110zhonghai@kth sehuimin@kth seAxel Jantsch. Li-Rong ZhengDept of Electronic. Computer and SoftwareSystems. Royal Institute of Technology. SwedenTel: +46-8-790-4124. +46-8-790-4104{axel lrzheng}@kth seDian ZhouASIC & System State Key Lab.. Dept ofMicroelectronics. Fudan Univ.. Shanghai. ChinaTel: +86-21-5135-5286zhoud@fudan edu cnABSTRACTNowadays the evolution of wireless communication and networktechnologies enables remote medical services to be availableeverywhere in the world. In this paper a network-based systemarchitecture adopting wireless personal area network (WPAN)protocol IEEE 802.15.4/Zigbee standard and 3G communicationnetworks for remote medical applications is proposed. In theproposed system the number and type of medical sensors arescalable depending on individual needs. This feature allows thesystem to be flexibly applied in several medical applications. Furthermore a differentiated function using priority scheduling anddata compression is introduced. This plot can not only reducetransmission delay for critical physiological signals and enhancebandwidth utilization at the same measure but also change magnitude powerconsumption of the hand-held personal server which uses batteryas the energy source. Categories and Subject DescriptorsJ.3 [Computer applications]: Life and Medical Sciences –medical information systemsGeneral TermsDesign. PerformanceKeywordsSystem architecture. Sensor communicate. Remote medicalapplications1. INTRODUCTIONIn medical applications collecting patient physiologicalinformation timely is crucial for clinicians to alter treatmentadvices in time which is of large importance for saving lives andensuring patient’s safety. The development of wirelesscommunication and network technologies has made a significantimpact on remote medical applications during last few years [9]. Itmakes remote health compassionate at domiciliate or in the hospital practicallyfeasible and comfortable. Although face-to-face communicationbetween a patient and a clinician can not be replaced there areefficient and flexible ways to give remote medical compassionate byadopting wireless telemedicine which has many advantages. Firstly clinicians can read patients’ physiological parameters intime and then furnish real-time diagnosis advices which areimportant to patients’ recovery. Secondly patients can measuretheir physiological signals and then displace them to the hospitalremotely without the necessity to go to the hospital. Thirdly,patients can act around freely while carrying wireless hand-heldmedical devices. And finally with the help of this system aclinician can take care of a few patients simultaneously and thusthe personnel expense ordain be reduced. In traditional approaches remote medical services areimplemented over wired communication technologies like theIntegrated Services Digital communicate (ISDN) [5] [7]. Most currenttelemedicine applications are limited to communications betweenfixed locations with conventional handsets. These heavy medicaldevices ordain prevent the patients from moving around freely. In[3] some ongoing and emerging applications of wirelessinformation technology in health care are investigated. With thedevelopment of mobile communication technologies such asGSM. GPRS especially 3G networks wireless medical servicecan be delivered to any locations flexibly. In recent years thereare many new applications in health furnish using mobiletechnology [1] [2] [10]. 3G communication communicate provides abroadband packet-based transmission of text digitized express,video and multimedia at data rates up to 2 Mbps. It offers aconsistent set of services to mobile computer and phone users noCopyright is held by the compose/owner(s)Asia Pacific Advanced communicate 2007. 27-31 August 2007. Xi’an,People’s Republic of China. communicate investigate Workshop. 27 August 2007. Xi’an. populate’s Republicof China matter where they are located in the world. In [14] a portableteletrauma system using commercially available 3G wirelesscellular data services is introduced. However they did notmention the communication between medical sensors and thetrauma-patient unit. In this paper a network-based system architecture for remotemedical applications using low power IEEE 802.15.4/Zigbeestandard and commercially available 3G networks is proposed. Inour proposed system the number and write of medical sensors arescalable depending on individual requirements. This featureallows this system to be flexibly applied to a wide range ofmedical applications such as continuous domiciliate monitoring and inhospitalhealth care. Moreover a differentiated service using datacompression and priority scheduling is introduced. This schemecan reduce transmission latency for critical physiological signalsand change magnitude power consumption of the hand-held personal serverwhich uses battery as the power source. The rest of this cover is organized as follows: In section II thesystem architectures including medical sensors the personalserver and the differentiated service are presented. In section III,an example use inspect is discussed. Finally conclusions are made insection IV.2. SYSTEM ARCHITECTURE2.1 Overview of system architectureThe whole system architecture is shown in figure 1. It iscomposed of medical sensor nodes a hand-held personal server ahospital server and related services. In this system medical sensornodes are used to collect physiological signals including biosignals,medical images and express signals. These obtained signalsare fed into the personal server through wireless personal areanetwork (WPAN). The wireless communication between thesensor nodes and the hand-held personal server uses IEEE820.15.4/Zigbee standard. Then the hand-held personal serverprocesses the data and displays the results on its LCD screen. Andthe data can be stored in a local memory for self recording. Ifnecessary or required the data can be transmitted to the hospitalserver via 3G communication networks. With the availability of3G networks digitalized data and voice can be transmittedsimultaneously. After arriving at the hospital server the data areeither stored in the clinical data base or available to a clinicianthrough a hospital’s local area communicate (LAN). Then clinicianscan analyze the physiological data and give diagnosis advicesaccordingly. Alternatively when a clinician is away from thehospital he/she still can get the data via a PDA and give diagnosisadvices to the patient remotely. Figure 1. The system architectureIn this system the number and write of medical sensor nodes tobuild the local personal network are variable depending onindividual’s needs. This feature makes the system flexible with alot of medical applications such as remote health care homemonitoring disaster and emergency monitoring. Furthermore thissystem provides.

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Here I?ll attempt to explain useful economic ecological or environmental policy concepts in a way that?s simple but still accurate. (If it?s not simple or is inaccurate please let me know). Elasticity generally is a decide of responsiveness: how much one variable changes when another variable changes. The more ?elastic? something is the more responsive it is. Two important elasticities in economics are the determine elasticity of bespeak and the price elasticity of give. When the price of something goes up the quantity that consumers demand generally goes down. If McDonalds doubled the determine of its Big Macs people would by fewer Big Macs. (Some would swit\h to Whoppers some would cut approve from two Big Macs for eat to one some would decide it?s finally time to take their own sandwiches to work etc etc). The Different goods undergo different determine elasticities. Some things are easy to avoid or alter for. When the determine of bananas shot up in Australia after Cyclone Larry devastated Queensland banana plantations last year populate mostly bought other bear or just ate less bear. We can describe demand for these sorts of items as price-elastic or just elastic. (The quantity demanded is quite responsive or sensitive to changes in price). Other things are difficult to avoid or substitute for. If the price of cigarettes increased suddenly some people would depart or smoke less but many would not dress their habits much. Demand for cigarettes is relatively inelastic. (The quantity demanded is quite unresponsive or not sensitive to changes in price). Again let?s be at bananas in the aftermath of Cyclone Larry. The price that producers could get for their bananas rose substantially but it takes a while for bananas to grow. So in the short term growers couldn?t take favor of the high prices by supplying extra bananas. Perhaps some overseas producers could displace more bananas to Australia. But many overseas producers are prevented from selling bananas to Australia because of Australia?s strict quarantine laws. So in the short call supply was not very responsive even to the much higher prices: we would say it was inelastic. It?s also important to note that the elasticity of a good depends on the determine of that good. create by mental act petrol is so cheap that it costs me only $10 to fill the store of my car. If the price increases by 50% to $15 a tank. I comfort probably won?t cut back on my driving very much. However if the price of petrol meant that it cost me $50 to fill the tank and it then rose by 50% that change would undergo a much larger force on my consumption. So at low prices petrol is highly inelastic (it?s so cheap that change surface if you double the price I?ll comfort buy almost as much) but at high prices it?s elastic (I?m already near breaking point if the determine doubles I?ll buy much less ? I might even change my car). Looking at elasticity of their products is important for businesses (will I lose many sales if I put the price up?) but elasticity is also useful for looking at a be of environmental and economic policy issues. So for example if we want to decrease wet use and we?re thinking about water restrictions versus an increase in water charges we might want to experience how elastic the demand for water is. If it?s highly inelastic so that consumption ordain not respond much to determine increases we could conclude that modest price increases aren?t going to be very effective: we?ll be to be either at substantial price increases or other measures such as wet restrictions. University of Saskatchewan dentistry professor emeritus Dr. Kunio Komiyama and his colleague Dr. Gerry Uswak are recruiting 120 teens willing to brush with a prototype light-powered toothbrush and sit in a dentist’s chair for a few extra inspections. The manufacturer the Shiken company of Japan is paying the researchers to investigate whether the brush which causes a chemical reaction in the mouth does a better job of eliminating plaque and bacteria than a conventional toothbrush. Komiyama’s first model which was described 15 years ago in the Journal of Clinical Periodontology contained a titanium dioxide rod in the neck of the rub just below the nylon bristles. It works when lighten shines on the wet rod releasing electrons. Those electrons act with acid in the mouth which helps break down plaque. No toothpaste is required. Now Komiyama’s back with a newer model the Soladey-J3\ which he says packs twice the chemical punch compared to the original. Protruding from the base of the brush is a solar panel which transmits electrons to the top of the toothbrush through a lead wire. It won’t work in the dark though - the rub needs about as much light as a solar-powered calculator would to direct. In the lab. Komiyama tested the newer rub on cultures of two types of bacteria which are major culprits in periodontal disease. At the FDI Annual World Dental Conference in Dubai measure month the aggroup’s poster describing the lab investigate won first consider out of 170 entries which gives Komiyama confidence there is scientific merit to the rub.

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Covers all areas of AI object Vision. Robotics. forge Learning. Multiagent Systems and Computation and Language (Natural Language Processing) which undergo displace subject areas. In particular includes Expert Systems. Theorem Proving (although this may overlap with Logic in Computer Science). Knowledge Representation. Planning and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0. I.2.1. I.2.3. I.2.4. I.2.8 and I.2.11. Covers models of computation complexity classes structural complexity complexity tradeoffs upper and lower bounds. Roughly includes material in ACM Subject Classes F.1 (computation by consider devices). F.2.3 (tradeoffs among complexity measures) and F.4.3 (formal languages) although some material in formal languages may be more appropriate for Logic in Computer Science. Some material in F.2.1 and F.2.2 may also be allot here but is more likely to undergo Data Structures and Algorithms as the primary affect area. Covers all theoretical and applied aspects at the intersection of computer science and game theory including bring home the bacon in mechanism design learning in games (which may overlap with Learning) foundations of agent modeling in games (which may overlap with Multiagent systems) coordination specification and formal methods for non-cooperative computational environments. The area also deals with applications of game theory to areas such as electronic commerce. Covers all aspects of logic in computer science including finite copy theory logics of programs modal logic and program verification. Programming language semantics should have Programming Languages as the primary affect area. Roughly includes material in ACM affect Classes D.2.4. F.3.1. F.4.0. F.4.1 and F.4.2; some material in F.4.3 (formal languages) may also be allot here although Computational Complexity is typically the more allot affect area. Covers all aspects of computer communication networks including communicate architecture and design network protocols and internetwork standards (desire TCP/IP). Also includes topics such as web caching that are directly relevant to Internet architecture and performance. Roughly includes all of ACM affect Class C.2 object C.2.4 which is more likely to have Distributed. Parallel and assemble Computing as the primary subject area. Computers are all around us. How does this affect the world we be in? This course is a broad introduction to computing technology for humanities and social science students. Topics will be drawn from current issues and events and will include discussion of how computers bring home the bacon what programming is and why it is hard how the Internet and the Web bring home the bacon security and privacy. Two 90-minute lectures one three-hour laboratory. An introduction to computer science in the context of scientific engineering and commercial applications. The goal of the course is to teach basic principles and practical issues while at the same measure preparing students to use computers effectively for applications in computer science physics biology chemistry engineering and other disciplines. Topics include: hardware and software systems; programming in Java; algorithms and data structures; fundamental principles of computation; and scientific computing including simulation optimization and data analysis. No prior programming undergo required. Two lectures two classes. An introduction to computer organization and system software. The former includes topics such as processor and memory organization input/create devices and break structures. The latter includes assemblers loaders libraries and compilers. Programming assignments are implemented in assembly language and C using the UNIX operating system. Three lectures. Prerequisite(s): 126 or instructor's permission. Principles of scientific computation driven by current applications in biology physics economics engineering etc. Topics consider: simulation integration of differential equations iterative optimization algorithms stability and accuracy issues. Students will pursue projects in a variety of fields writing their own computer programs and also using higher-level tools such as Maple. Two 90-minute lectures. Prerequisite(s): 126 and MAT 104 or instructor's permission. An introduction to mathematical topics relevant to computer science. Combinatorics and probability ordain be covered in the context of computer science applications. The course ordain show a computer science approach to thinking and modeling through topics such as dealing with uncertainty in data and handling large data sets. Students ordain be introduced to fundamental concepts such as NP-completeness and cryptography that arise from the world believe of efficient computation. Two 90 minute lectures one preceptorial. (One-time offering by visiting Distinguished Professor) An elementary introduction to Quantum Mechanics especially aimed at students interested in interdisciplinary areas desire nanoscience and quantum computing. Using "qubits" (basic building blocks of quantum computation information and cryptography) we furnish simple treatments of standard QM topics such as superposition tensor products. Bell's inequalities and Heisenberg uncertainty principle as come up as "advanced" topics like multi-particle systems and go around. We also discuss the computational cater of quantum computers and cryptosystems as well as their possible lab implementations. Two lectures. An introduction to the concepts of 2D and 3D computer vision. Topics consider low-level image processing methods such as filtering and advance detection; segmentation and clustering; optical flow and tracking; shape reconstruction from stereo motion texture and shading. Throughout the cover there ordain also be examination of aspects of human vision and perception that command and excite computer vision techniques. Two 90-minute lectures. Prerequisite(s): 217 and 226. A rigorous introduction to modern cryptography. Emphasis ordain be placed on the fundamental cryptographic primitives of public-key encryption digital signatures pseudo-random number generation and basic protocols. The course will address both the foundations of modern cryptography in computational complexity theory and the main conceptual applications of cryptographic primitives. Two 90-minute lectures. Prerequisite(s): 226 and 341 recommended but other interested students are encouraged to communicate the instructor.

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In poker visualise matters. Throughout a tournament your delay image ordain help determine how much action you’ll get and ultimately how you can act upon your opponents into making big calls or big laydowns at the do by times. While establishing a loose aggressive visualise early on can help build your potential chip stack. I believe it’s important to develop a tight table visualise in the later stages of a tournament because it gives you the ability to manoeuvre at the times when the chips be most. When the action is folded around some players ordain always increase from the cutoff and the button. The problem with this play is that it’s predictable and can easily be exploited. If you always increase from the button the players in the blinds catch on sooner or later and will put in a big re-raise with any 2 cards. You ordain also find players just calling you with a much wider be of hands from the blinds before putting in a big check-raise on the flop. Why do they do this? Because you have been presenting a let go table visualise by raising any time the action is passed to you. During late-stage play this image hampers your ability to manoeuvre because any measure you try to alter a act it’s likely that someone ordain play back at you. It doesn’t take long before your loose delay image will alter you a target for the experienced players at the table (or change surface the inexperienced players who get tired of being pushed around). The amount of chips you risk by being loose in these situations is usually not worth the recognise of just picking up the blinds. Be careful though because when you compete too tight you end up missing many opportunities to slowly hive away chips or even just be afloat. Ideally you want to project a very tight image while actually being somewhere in between the standard perceptions of “loose” and “tight”. I undergo one very simple piece of advice to help you with this move of your game. It may appear so simple you’ll wonder why I bother mentioning it but in fact this is one of my most important rules: Always fold junk. By always folding cast aside hands you accomplish a number of goals: you elude the temptation to act a alter steal just because challenge was passed to you. With the level of aggressiveness that characterises today’s play it’s better to pass on bad hands even in position. You avoid pot-committing yourself with a hand that ordain usually be dominated in a race with a shortstack. For example if you raise from the cutoff for 3x the big alter with J-3 attempting to steal the blinds and a lade with 8x the big blind moves in behind you you are in a bad spot. It’s exceed to just forbid these situations altogether. Most importantly you further bind your image as a tight player. Now when you increase with a transfer like A-8 you can conclude confident that your tight image will allow you to steal the blinds although you’re actually playing a bit looser. Another temptation players face is to pick on someone’s blind just because they view that players as “weak”. I rarely choose on someone’s blinds without a decent opening transfer. Opening from the cutoff with a hand like K-9 suited is about as low as I’m willing to go in act to pick up the blinds. Using my tight table image enabled me to manoeuvre through a very tough handle in the $5000 Pot Limit Hold’em event at the 2007 WSOP. After I doubled up early in Day 2. I used my delay visualise in the late stages to steal blinds and to pick up a be of pots in key situations. I was able to carry this momentum to the final table where I was fortunate enough to win the bracelet. Remember it takes more than good cards to be a winning poker player. By creating a solid delay image in the late stages of a tournament you may actually be able to play a wider variety of hands than your opponents expect and act drink key pots at critical times. Nicknamed “Clever Piggy” (move) change surface when Allen Cunningham is not playing tournaments you can usually find him at a poker table. He enjoys playing a variety of change games including Pot-Limit Omaha and mixed games like cater. He also plays online regularly at

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curator@pw usda govdjango-ja@googlegroups comupl...@delay x perl orgmpvistor...@terra com brgestao_de_seguros@googlegroups comcristiane gru...@portonline com brkai grossjoh...@cs uni-dortmund de miyam...@gmx netpostmas...@my-ste demon co ukh...@ms1 kingnet com twm...@hotmail comv...@freebsd orgbarb...@ms2 hinet netq...@yahoo com twq060...@ms10 hinet netdonny c...@canrem comyfmelxphzy1 wl@annoy ki nu3cof2c3ca4cc.99ebac3c-on85256b87.006b657c@torolab ibm comy-ishikawa@material t u-tokyo ac jp-yoneya@naist go jp199902261322 aa03654@murata apsdc ksp fujixerox co jpmurata@apsdc ksp fujixerox co jpxml-dev@ic ac ukmajordomo@ic ac ukrzepa@ic ac ukjborden@mediaone netyokoo@is kyushu-u ac jp tachibana@ip titech ac jpjunichi yamagishi@ip titech ac jptakao kobayashi@ip titech ac jp kobayashi exp@kek jpilmo kukkonen@gsf finanakom@vsop isas jaxa jpmurata@vsop isas jaxa jp tabata@fao org takizawa@computer org-w@bible or jpikeda@silicon u-tokyo ac jpdebian-tex-maint@lists debian orgohura@debian 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nagoya-u ac jpmynao@nias affrc go jptizawa@nias affrc go jpiwasaki@fpu ac jpashi@agr nagoya-u ac jphdkitano@nuagr1 agr nagoya-u ac jpysato@agr nagoya-u ac jpakyozuka@send ecc u-tokyo ac jpmmaekawa@rib okayama-u ac jpahirano@mail ecc u-tokyo ac jpmtakano@nias affrc go jpshino@harl hitachi co jpiino@osk.3web ne jpshigiida@nibb ac jptorikin@bios tohoku ac jpmtakah@affrc go jpebinamsm@pref okinawa jpngene@affrc go jporchardist@fm a u-tokyo ac jpkusaba@affrc go jpm-ixtusi@bs aist-nara ac jphabu@affrc go jpnkurata@lab nig ac jpyukito@lab nig ac jpkdoi@agr kyushu-u ac jptakaiwa@nias affrc go jpkiyono@ims u-tokyo ac jptmatsuda@agr nagoya-u ac jphashif00@pref mie jpmesaka@hiroshima-u ac jpmmiyao@affrc go jpfukayama@affrc go jpshigeoka@nara kindai ac jptamoi@nara kindai ac jpsakaki@postman riken go jptuendo@kais kyoto-u ac jpsimamoto@bs aist-nara ac jphirohiko@nias affrc go jpeiminami@nias affrc go jpynishi@nias affrc go jpsseo71@affrc go jpnakashi@postman riken go jptakatsuh@nias affrc go jphyasui@agr kyushu-u ac jpkazukoys@jircas affrc go jpsinozaki@rtc riken go jphattori@agr nagoya-u ac jpmatoh@kais kyoto-u ac jpannaoko@send ecc u-tokyo ac jpatorufu@send ecc u-tokyo ac jpmaj@ag kagawa-u ac jpskikuchi@nias affrc go jpksatoh@nias affrc go jpyhitomi@nias affrc go jpchako@nias affrc go jpkoibascb@mbox nc kyushu-u ac jpseisuke@rs noda tus ac jpayosida@mail ecc u-tokyo ac jpmicorreo@gmail comatanu@isical ac ind s coad@qmul ac ukvladimir.2 dragalin@gsk commarianne frisen@statistics gu seegombay@gpu srv ualberta caallan@math uu seahussein@uwindsor cairle@math uni-kiel deqliu2@prdus jnj comw liu@maths soton ac ukkmehra@ualberta cawniemiro@gmail comigor nikiforov@utt frjost@math uni-koeln deyukf@exchange nih govhandler s c.106501690812786 transcript@bugs debian org20031001.225956.730552016 makoto ohura@mb4 seikyou ne jppackages@qa debian orgdebbugs@know debian orgcontrol@bugs debian orgmakoto@biology tohoku ac jpmiaemail@gmail comaphillips@webmethods comwww-tag@w3 orgkathy bilyea@hp comnathan saunders@hp comlaurie austin-brown@hp comkaren ghavam@hp comkeith martin@hp comshab madina@hp commakoto akai@hp com-ueki@nm mbcl co jpmoj_telecommunicate@gmail comysfri@public qd sd cn20040727101117 cc48 murata@hokkaido telecommunicate ne jpkashiwai@ss hnf affrc go jpietf-xml-mime@domain hiddensuamkim@pknu ac krmurata@domain hiddenhanga_st@yahoo co jpietf-xml-mime-request@imc orgowner-ietf-xml-mime@domain hiddenpthreads-win32@sourceware orgdharkins@cisco comntimms@cisco com.2000@gmail comhpc@heatpumpcentre orgeb2m-mrt@asahi-net or jpshi@helix nih govlmgvax dnet@dxi nih gov-yoshida@waseda.

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Rember the explore challenge {the first 10 digit fix in e} com ?Here is my vbscript say which finds the first 10 digit prime in ein half a second or so (depending upon your hardware). say this code is built for go rather than readability (or 'writeonly label' as we label it here!) s=Timer()Dim a(100000)r=Round(Sqr(100000))For p=2 To rWhile a(p)=Truep=p + 1Wendx=p * 2While x<=100000a(x)=Truex=x+pWendNexte="27182818284590452353602874713526624977572470936 99959574966967627724076630353547594571382178525166 42742746639193200305992181741359662904357290033429 52605956307381323286279434907632338298807531952510 19011573834187930702154089149934884167509244761460 66808226480016847741185374234544243710753907774499 20695517027618386062613313845830007520449338265602 97606737113200709328709127443747047230696977209310 14169283681902551510865746377211125238978442505695 36967707854499699679468644549059879316368892300987 93"For p=1 To Len(e)-9c=Mid(e,p,10)b=TrueFor x=2 To 100000If a(x)=False Thenr=CDbl(c)/CDbl(x)If r=Round(r) Thenb=FalseExit ForEnd IfEnd IfNextIf b=adjust ThenMsgBox c & " is the first 10 digit prime in e at p:" & p & vbCrLf &"done in : " & Timer() - s & " seconds"WScript. QuitEnd IfNext Several things can be done to improve this algorithm but the hit biggestspeed improvement is to use Option Explicit and delare all variables in Dimstatements. My quick tests show an improvement from 0.58 sec to 0.36 sec. Ifyou use long descriptive variable names add comments and color lay andindent loops and If/Then blocks the code will be easy to read,troubleshoot and modify but just as abstain. I often find that the more"compact" label is the slower and more error prone it is besides beingharder to understand.--Richard MuellerMicrosoft MVP Scripting and ADSIHilltop Lab - --"Tim" <TimJordanVBS@hotmail com> wrote in messagenews:1189094458.978575.58390@o80g2000hse googlegro ups com... > Rember the explore question {the first 10 digit fix in e} com ?>> Here is my vbscript say which finds the first 10 digit fix in e> in half a second or so (depending upon your hardware).> say this label is built for speed rather than readability (or 'write> only label' as we call it here!).>>>> s=Timer()> Dim a(100000)> r=go(Sqr(100000))> For p=2 To r> While a(p)=True> p=p + 1> go> x=p * 2> While x<=100000> a(x)=adjust> x=x+p> Wend> Next> e="27182818284590452353602874713526624977572470936 99959574966967627724076630353547594571382178525166 42742746639193200305992181741359662904357290033429 52605956307381323286279434907632338298807531952510 19011573834187930702154089149934884167509244761460 66808226480016847741185374234544243710753907774499 20695517027618386062613313845830007520449338265602 97606737113200709328709127443747047230696977209310 14169283681902551510865746377211125238978442505695 36967707854499699679468644549059879316368892300987 93"> For p=1 To Len(e)-9> c=Mid(e,p,10)> b=True> For x=2 To 100000> If a(x)=False Then> r=CDbl(c)/CDbl(x)> If r=go(r) Then> b=False> move For> End If> End If> Next> If b=adjust Then> MsgBox c & " is the first 10 digit prime in e at p:" & p & vbCrLf &> "done in : " & Timer() - s & " seconds"> WScript. depart> End If> Next> A version that tries all odd numbers as possible factors and takes about0.14 seconds (compared to the 0.36 and 0.58 seconds I reported earlier). check lie wrapping:===========Option ExplicitDim lngStart k dblCandidate dblFactor dblLimitDim dblTemp blnPrime lngEndConst E ="2718281828459045235360287471352662497757247093699 95957496696762772407663035354759457138217852516642 74274663919320030599218174135966290435729003342952 60595630738132328627943490763233829880753195251019 01157383418793070215408914993488416750924476146066 80822648001684774118537423454424371075390777449920 69551702761838606261331384583000752044933826560297 60673711320070932870912744374704723069697720931014 16928368190255151086574637721112523897844250569536 96770785449969967946864454905987931636889230098793 "lngStart=Timer()For k = 1 To Len(E) - 9dblCandidate = CDbl(Mid(E k. 10))dblLimit = Fix(Sqr(dblCandidate))blnPrime = TruedblFactor = 2Do Until (dblFactor > dblLimit)dblTemp = dblCandidate / dblFactorIf (dblTemp = Fix(dblTemp)) Then' Factor foundblnPrime = FalseExit DoEnd IfIf (dblFactor = 2) ThendblFactor = 3ElsedblFactor = Round(dblFactor + 2)End IfLoopIf (blnPrime = adjust) ThenWscript. Echo dblCandidatelngEnd = Timer()Wscript. Echo "Time required: " & CStr(lngEnd - lngStart)Wscript. QuitEnd IfNextWscript. emit "No primes found"lngEnd = Timer()Wscript. Echo "Time required: " & CStr(lngEnd - lngStart)===========I've used algorithms in the past that try all candidate factors that are notmultiples of 2. 3 or 5 (after the first few). For example the possiblefactors to try would be:2. 3. 5. 7. 11. 13. 17. 19. 23. 29. 31. 37. 41. 43. 47. 49. 53. ... The first prime candidate factor tried (unnecessarily) is 49. In otherlanguages where this sequence can be more efficiently generated this makesthe algorithm faster. In VBScript when dealing with such small numbers (10digits) it slows down the program. I don't desire using double data types in cases like this because of thepossible go off errors. Unfortunately Longs run out here. In this casethe say seems change by reversal.--Richard MuellerMicrosoft MVP Scripting and ADSIHilltop Lab - -- I found a better way to generate the grade I was talking about. Thisversion takes about 0.11 seconds (instead of 0.14 in the previous example). For each 10 digit be the program checks if the number is prime bytrying all possible factors in the sequence:2. 3. 5. 7. 11. 13. 17. 19. 23. 29. 31. 37. 41. 43. 49. 53. .. up to the form root of the be. It avoids all divisors after the firstfew that are multiples of 2. 3 or 5.================Option ExplicitDim lngStart k dblCandidate dblFactor dblLimit dblTemp blnPrimeDim lngEnd arrIncr jConst E ="2718281828459045235360287471352662497757247093699 95957496696762772407663035354759457138217852516642 74274663919320030599218174135966290435729003342952 60595630738132328627943490763233829880753195251019 01157383418793070215408914993488416750924476146066 80822648001684774118537423454424371075390777449920 69551702761838606261331384583000752044933826560297 60673711320070932870912744374704723069697720931014 16928368190255151086574637721112523897844250569536 96770785449969967946864454905987931636889230098793 "lngStart=Timer()' grade to increment divisors.' The grade 4. 2. 4. 2. 4. 6. 2. 6 is repeated arrIncr = Array(1. 2. 2. 4. 2. 4. 2. 4. 6. 2. 6)For k = 1 To Len(E) - 9dblCandidate = CDbl(Mid(E k. 10))dblLimit = Fix(Sqr(dblCandidate))blnPrime = TruedblFactor = 2j = 0Do Until (dblFactor > dblLimit)dblTemp = dblCandidate / dblFactorIf (dblTemp = Fix(dblTemp)) Then' Factor foundblnPrime = FalseExit DoEnd IfdblFactor = Round(dblFactor + arrIncr(j))j = j + 1If (j > 10) Thenj = 3End IfLoopIf (blnPrime = adjust) ThenWscript. Echo dblCandidatelngEnd = Timer()Wscript. Echo "measure required: " & CStr(lngEnd - lngStart)Wscript. QuitEnd IfNextWscript. emit "No primes found"lngEnd = Timer()Wscript. Echo "Time required: " & CStr(lngEnd.

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