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Command, Control, and Communication
20.1 OBJECTIVES AND INTRODUCTION
Objectives
1. Know the definitions of command, control, and communications.
2. Understand the relation between communications and effective command andcontrol.
3. Understand the basic command and control structure.
4. Know the functions of an Automated Combat Direction System.
5. Understand the problems created by dual designation and their solution by thegridlock procedure.
6. Know the difference between automatic, semi-automatic, and manualoperation of a Combat Direction System.
7. Know the various means of digital information exchange between CombatDirection Systems.
8. Know the different types of displays employed in Combat Direction Systems.
9. Understand the use of true and relative motion displays.
10. Understand the problems inherent in command and control.
Introduction
Throughout this text, attention has been directed toward principles and technologiesassociated with the hardware of weapons systems. Underlying these weapons systems andthe methods by which they are caused to function, is the fundamental concept that they aresimply devices or processes that serve as tools to augment the capabilities of a humanbeing. For example, an electromagnetic sensor may augment the visual and audio sensorof an individual; a weapon enhances the individual's ability to inflict damage; a combatdirection system expands the decision making capacity of a person; and so forth. At thefunctional center, no matter how remote, of every weapon system, combat system, orcombat direction system is a human being who is engaged in the employment of thatsystem or grouping of systems.
20.2 DEFINITIONS
Data is the raw material from which useful information is made. In isolation, data ismeaningless. Information is an ordered or sorted grouping of data that conveys rationality. The purpose of an information system is to process data in aggregation to provideknowledge or intelligence. This information may very well be data for some user on ahigher level who may, in turn, process it to produce more comprehensive information andso on, until the final user is served.
20.2.1 C3
A command, control, and communication (C3) system is an information system employedwithin a military organization. It is a general phrase that incorporates strategic and tacticalsystems. Consequently, a combat direction system, tactical data system, or warning andcontrol system may each be considered C3 systems. The following definitions of terms arecommonly accepted in the military context.
(1) Command--The functional exercise of authority, based upon knowledge, toattain an objective or goal.
(2) Control--The process of verifying and correcting activity such that theobjective or goal of command is accomplished.
(3) Communications--The ability and function of providing the necessary liaisonto exercise effective command between tactical or strategic units of command.
(4) Strategic--Broadly defined methods of accomplishing a goal.
(5) Tactical--Narrowly defined methods of accomplishing objectives en route to astrategic goal.
There are normally a number of tactics that make up a single strategy.
Therefore, command, control, and communications may be succinctly defined as:
The knowledgeable exercise of authority in accomplishing military objectives andgoals.
An important point to realize is that C3 is a humanfunction. The method by which command and control iscarried out is the C3 system, which serves to augment thecognitive functions of the individual engaged in command andcontrol. A complex C3 system is an integrated combinationof people, procedures, and hardware used to enhance theability of the individual performing command and control.
The commander may be the President of the United Statesor he may be the mount captain of a naval gun. The natureof his mission may be strategic or tactical. Consequently,the C3 system employed must necessarily complement the needsof the commander. Just as one person's information may beanother's data, the tactical considerations of one personmay be the strategy of another. C3 systems will normallyreflect the complexity or simplicity required by thecircumstances.
20.2.2 Communications
Command and control cannot be accomplished without theexistence of two-way communications. Commands could not bepassed from the commander to subordinates. Control would beimpossible unless feedback in some form could take place. Basic to any control system is the incorporation of areliable communications network. In reality, the moreremote the commander is from the scene of action the moredependent he becomes upon rapid, reliable communications.
The majority of long-range communications today arebeing transmitted electronically via satellite with high-frequency sky-wave propagation as a backup. Automation isachieved at communications centers and substations locatedthroughout the world using machine and computer-controlledprocessing and re-transmission systems. These stations,ashore and afloat, provide relatively efficient globalcoverage for strategic and tactical systems. Electronicreproduction, distribution, and display devices areavailable on ships that have greatly reduced manual messageprocessing. These equipments, such as NAVMACS,automatically monitor the fleet broadcast and recordmessages addressed to the ship or embarked unit commander indigital format for retrieval on a CRT display or printout ona high-speed printer. Just as combat direction systemsdisplay real-time tactical information, management-orientedinformation is accessible on a near real-time basis as well. In some cases the communications center can route messagesdirectly to small CRT displays variously located about theunit. Manual processing has been reduced to a minimum,freeing human resources to perform more important functions.
With Fleet Satellite Communications (FLTSATCOM), theUHF spectrum has become the primary carrier of globalmilitary communications. The existing HF network hasassumed a secondary, but important, backup rule.
20.2.3 Environment
The increasing need for responsive C3 systems is beingdriven by the rapidity with which weapons can be deployed. Figure 20-1 reveals that this rate has become nearlyexponential since the turn of the century. Figure 20-2displays the compression of reaction time to counterincoming weapons from the instant of initial detection. Figure 20-2 becomes meaningless, of course, when thedetection system fails to detect the inbound weapon. At theunit combat system level, the C3 system has becomerelatively efficient in dealing with short reaction times.NTDS and other comparable tactical C3 systems have begun tosatisfy the requirements of on-scene commanders. As thesesystems expand in capability, remote commanders will becomeincreasingly involved at the tactical level, especiallywhere the engagement has strategic significance. Currenttechnology has already placed heads of government in directcommunication with one another. Proliferation ofinformation systems at this level is resulting in politicalconsiderations having immediate impact upon militarydeployment of forces. In this environment it is conceivablethat a fighter pilot en route to a tactical objective may bediverted from his target by a direct order from thecommander-in-chief. Melodramatic as this may seem, C3
systems have achieved that degree of efficiency.
20.3 INFORMATION REQUIREMENTS
In today's environment and with all other considerationsassumed equal, the commander who has the 'best' information(timely and accurate) will prevail in a conflict of militaryforces. The key phrase in the definition of command andcontrol is 'knowledgeable exercise of authority.' Thecommander who commands without the benefit of informationpertinent to the goal or objective, increases theprobability of failing to control his resources optimally. Where that goal is both tactical and strategic in natureinvolving both military and political considerations, theon-scene commander may not have the information pertinent tothat goal.
As mentioned above, a constantly changing environmentis shaping the structure of C3 systems. That structure isincorporating all branches of the armed services and isgradually centralizing command and control at the seat ofgovernment.
In effect, technological developments in weaponry havereduced the time within which to receive and analyzeinformation. In a broader spectrum, increasing events(political and military) per unit time have furthercomplicated the decision process. An isolated conflict canrapidly become international in scope.
20.3.1 Structure
In this chapter a variety of C3 systems, mostly tactical infunction, are discussed. This suggests the fact that C3systems in today's military were not systematicallydesigned. In many cases, isolated systems were introducedin response to perceived needs or to take advantage ofexisting technology. The Vietnam War played a significantrole in highlighting the need for a more broadly structured,integrated C3 system. Today, C3 systems are being developedto incorporate the following areas in support of commandersengaged in command and control:
(1) Reconnaissance and surveillance
(2) Environmental observation and forecasting
(3) Intelligence analysis
(4) Electronic warfare
(5) Navigation
(6) Management
(7) Strategic and tactical weapons deployment
(8) Logistics and supply
20.3.2 Levels
In describing C3 system structure, the practice in the pasthas been to present a hierarchial chain of command whereinformation is depicted flowing up and down. Owing to theenvironment within which the C3 system must perform in thisera, the traditional hierarchy is diminishing in actualpractice. In its place a network of command and control isevolving. Figure 20-3 illustrates the basic form of thisnetwork on a broad scale.
In this case, the National Command Authority (NCA)interacts with two shore-based Fleet Command Centers (FCC)and one Afloat Tactical Flag Command Center (TFCC).
(1) NCA--The President and Secretary of Defense
(2) FCC--CINCLANTFLT, CINCPACFLT, CINCUSNAVEUR
(3) TFCC--Numbered fleet commanders or task forcecommanders, normally on-scene.
A considerable number of intermediate commanders havenot been included. In fact the trend in C3 systems istoward a reduction in the number of subordinate commandersin order to increase the efficiency of the system. Extrapolating the C3 system network further, it is apparentthat weapon platform commanders will play a significant rolein strategic matters as well as tactical. With command andcontrol considerations ranging from the political realm tospecific military employment of force, it is unlikely that acommander will possess all of the skills and informationrequired to singularly engage in C3. The network system infigure 20-3 suggests that an interdisciplinary team conceptmay be required.
20.4 AUTOMATED COMBAT DIRECTION SYSTEMS
In a complex multi-threat combat environment, automatedcombat direction systems such as NTDS make it possible forpeople to deal with the massive number of targets andcompressed reaction times of modern warfare. The complex C3functions required to keep track of hundreds of friendly,neutral, and enemy ships, aircraft, and weapons, whileengaging only those permitted by the current rules ofengagement, would be impossible by manual methods.
Joint operations between the Navy, Marine Corps, and U.S. Air Force in the Gulf of Tonkin in the late sixties andearly seventies underscored the potential for increasedeffectiveness that existed when automated C3 systems wereavailable to all participants in an objective area employinga means of rapid data exchange.
The Tonkin operation was the first serious attempt atinter-operability that met with some success. However, dataexchange had to be accomplished via the Marine CorpsTactical Data System ashore at Da Nang.
In order to overcome and correct the compatibilityproblems discovered through this early attempt at joint CDSoperations, the Tactical Air Control System/Tactical AirDefense System (TACS/TADS) was evaluated in 1977 to test thedigital exchange of information between the semiautomatedtactical data systems. The TACS/TADS interface provided U.S. joint and unified commanders with longer range radardetection, continuous tracking, identification, andsurveillance of aircraft and ships, more time for threatevaluation and weapon assignment, quicker responses totactical situations, and a capability to avoid mutualinterference through real-time exchange of informationregarding own-force activities. These and many otheradvantages accrue when automated tactical systems areintegrated through digital links. The systems currentlyable to transfer information in joint operations are:
(1) The U.S. Army Air Defense Command and ControlSystems, designated the AN/TSQ-73.
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(2) The U.S. Navy Tactical Data System, or NTDS, whichis the central command and control system on U. S. Navycombatants;
(3) The U. S. Navy airborne tactical data systemsavailable in the E-s, P-3, and S-3 aircraft;
(4) The U. S. Air Force Tactical Air Control SystemControl and Reporting Center (CRC), designated the AN/TSQ-91;
(5) The U.S. Air Force Airborne Warning and ControlSystem (AWACS) Aircraft (E-3);
(6) The U. S. Marine Corps Air Command and ControlSystem, designated the MACCS;
(7) Various allied ships and aircraft able to operatewith U.S./NATO Link standards;
(8) The NATO Air Command and Control System (ACCS)which, when complete, will include the older NADGE (NATO Air Defense Ground Environment), the French STRIDA (Systemede Traitement et de Representation des Information deDefense Aerienne), The British UKAGE, the German GEADGE, theSpanish Combat Grande, and the NAEWS (NATO Early WarningSystem) which includes AWACS and Nimrod airborne earlywarning aircraft.
When the systems are deployed together, their combinedradar coverage can exceed an area of over a million squaremiles. By exchanging data on radar-held targets, eachsystem can have the benefit of radar coverage of the othersystems, and the joint tactical commander can moreeffectively control the overall efforts of the forces avail-able. Thus, when interfaced, the overall surveillance capa-bility of the total complex of systems should exceed the sumtotal of the individual system capabilities. In addition,joint operations are less sensitive to outages and counter-measures when the systems operate as a team, because alter-nate means will be available to achieve tactical objectives.
To achieve these objectives an automated combatdirection system must perform the following functions:
(1) Data collection and storage
(2) Target tracking and prediction
(3) Command and control
(4) Communications
(5) Display
20.4.1 Data Collection and Storage
From the point of view of the command and control system,there are really only two categories of information: thatobtained from sensors co-located with the system or localtracks; and that obtained from sensors not co-located withthe system or remote tracks. The sensors and sourcesinclude radar, ESM IFF, sonar, visual observations, andintelligence data. Both the local and the remoteinformation are stored in a track file similar to thatdescribed for TWS systems in Chapter 6 and are listed intable 20-1.
These data may be stored by any of the means describedin Chapter 4, e.g., magnetic tape, disk, drum, core, or asemiconductor memory.
20.4.1.1 Reference frames. Obviously there must be asingle reference frame if several combat direction systemsare operating together. These systems will operate in astabilized cartesian coordinate system with an easilyidentifiable origin, such as a geographic feature or theintersection of whole-number latitude and longitude lines(i.e., 42oN/75oW), which is referred to as the Data LinkReference Point or DLRP. In the event that any unit doesnot accurately measure its position relative to DLRP, itstrack position reports for targets held mutually with otherunits will not correlate. The result will be two trackfiles and separate track numbers for the same target,resulting in ambiguity and confusion. This type of trackambiguity is called dual designation and is in some wayssimilar to that described for TWS systems in Chapter 6. Dual designation is detrimental in that it affects theoperation of all command and control systems involved in thedata exchange. Other causes of dual designation includeproblems with relative sensor alignment (Chapter 19),platform relative movement, and navigation error.
Table 20-1. Simplified Combat Direction System Track File
Track Number Weapon Order
Position History (X,Y,Z) Course and Speed
Identity Data Source
IFF Response Side Number
Track Category (Surface, Air, Sub) Engagement Priority
Current Mission Controlling Unit (e.e., for CAP)
Weapon Load
20.4.1.2 Gridlock. While it is desirable to eliminatethese sources of reference frame error, error musteventually appear over time and will grow unlesscompensation is introduced in a procedure called gridlock. First, a determination is made that gridlock error and dualdesignations exist, then a target is selected that is heldon radar by all participants. A comparison is made manuallyor as a computer subroutine to determine that the tracks arein fact the same (correlation). One system is selected as areference, usually the one considered to have the bestnavigation data. Finally, all other systems cause a bias tobe included in their computer's position reports such thattheir display of the target is superimposed over that of thereference system. This bias is the same for all tracksreported for one specific system, but obviously is differentbetween systems and is zero for the reference because itsreports are assumed to have no error. Gridlock is depictedin figure 20-4.
20.4.2 Target Tracking Prediction
Information from local data sources can be entered manuallyor it can come in the form of digital position reports froma TWS or active tracking radar. Fire control system data(called repeatback data) is usually an automatic digital oranalog input that must be converted to digital data compat-ible with the Combat Direction System computer fire controlsystem data includes that from sonar and from gun-systemoptics. In the case of ground-based systems, fire controldata may be classified as remote data such as that obtainedfrom radars associated with a Hawk or Patriot missile fireunit not co-located with the CDS.
The CDS will normally include equipment to convert datato a format usable by its digital computer including Analogto Digital converters, digital formating equipment, and ex-ternal buffers if necessary. The purpose of the buffer isto store data from several low data rate sources such as so-nar or gyro references until the computer needs it. Withoutthe buffer these low-rate sources would slow down the com-puter and make it inefficient. With the buffer the computercan cycle through several input/output channels in order asrequired without having to wait for data.
The CDS will perform tracking and prediction functionssimilar to those of a TWS radar but using many other datasources. The purpose of the CDS is to provide data and as-sist in its evaluation rather than to solve the fire controlproblem. Therefore, the functions it performs will be op-timized for communication with operators. The system willinclude some type of tracking algorithm, similar to that inChapter 6, which may or may not include hostile target par-ameters and rules of engagement criteria for target evalu-ation. Outputs for display to humans would include course,speed, CPA, intercept geometry, and evaluated data such astarget probability areas or weapon danger areas.
20.4.3 Command and Control
The most important function of the automated combat direc-tion system is in augmenting and assisting the commander inthe decision-making process during combat. In performingthis function, the system will make various calculations inorder to provide graphic and alphanumeric displays that maybe clearly interpreted and evaluated by decision makers. Inaddition, the system may make preprogrammed evaluations andactually automatically assign sensors or weapons as permit-ted by the rules of engagement.
20.4.3.1 Force Orders. In addition to providing the meanswith which an individual unit commander can employ the wea-ponry and sensors assigned him, the force commander can di-rect conditions of readiness and weapon pairing by secure(i.e., encrypted) intracomputer communications. Commandersat each level are provided confirmation of action takenthrough graphics and alphanumeric data.
20.4.3.2 Rules of Engagement. Most automated combat direc-tion systems provide some means of automatic threat reac-tion. The degree to which this response can be tailored tothe specific tactical situation varies considerably fromsystem to system. Though the degree of sophistication ofresponse logic varies, the actual modes of response can ingeneral be summarized as follows:
(1) Automatic--The combat direction system makesdecisions as programmed, up to and including weapons firing.
(2) Semiautomatic--The combat direction systemsperforms all functions up to weapon firing; however, an op-erator must close a firing key. Countermeasures such as ECMand chaff may still be automatic.
(3) Manual--Each step is performed by an operator inclassical sequence; however, track data may still be provid-ed by an automatic tracking system such as a TWS radar.
The more sophisticated systems allow programming ofspecific weapons and sensor response, using the location ofthe system or some other designated position as the defendedzone. In addition, zones can be established in bearing andrange within which specific types of response can be pre-arranged.
20.4.4 Communication Links
Digital communications between computers allows much morerapid exchange of data than would be possible using humanlanguage. Indeed, it is the only way that complete infor-mation can be made available to all involved in the deci-sion-making process. In order for all services and agen-cies, including those from allied countries, to mutuallysupport one another, a series of (Link 11)--Link 11 is a two-way, real-timeencrypted data transmission over either UHF or HF radio fre-quencies. Essential in its importance is the two-way dataexchange. Link 11-equipped aircraft or ships, or ships andaircraft, can relay secure tactical sensor information inaddition to weapon deployment and engagement status. Coup-led with a central memory and processing unit, multiplestations can either receive information or actively enterthe net and send and receive data. One station will be designated as NCS (Net Control Station) to providea synch-ronizing sampling of each transmitting unit's data. Trans-missions can be in the UHF range to limit detection toline-of-sight ranges or HF when over-the-horizon ranges arede-sired. Link 16 will provide similar but expandedcapabil-ities.
20.4.4.2 TADL 'B' --This is a highly directional two-wayline-of-sight microwave transmission similar to microwavetelephone communications. The units involved must have an-tennas pointed directly at each other, as the transmission employs a very narrow directional beam. Due to antennaaiming requirements, this method is employed by ground-basedsystems only.
20.4.4.3 TADL 'C'--This is a one (Link 4) or two-way (Link4A) link used to exchange information with and control spec-ially configured fighter aircraft. This enables the consoleoperator at a surface or airborne CDS to direct the aircraftremotely. In addition, data on target location and identitycan be transferred from the fighter to the controlling unitwho in turn can distribute that information on the otherlinks.
20.4.4.4 Link 14--Link 14 is a one-way data transmission
system providing non-NTDS-equipped surface platforms with
data made available from NTDS platforms. NTDS Link 11-equipped platforms can transmit encrypted data to platformslacking this capability. This raw data is then transcribedmanually and presented to local commanders for possibleaction. Tactical and strategic conditions presented to non-NTDS platforms, even though done manually, can provide theC3 necessary in a contemporary battle. Information can bereceived by a standard radio receiver and teletype.
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20.4.5 Display
Automated Combat Direction Systems (CDS) have replaced therelatively slow manual target plotting and data processingof World War II and the 1950s with the nearly instantaneousrecognition, reaction, and distribution capability of thehigh-speed digital computer. The CDS operator has symbologyavailable to him in real-time that represents the entiretactical situation, including all surface, subsurface, air,and land assets supporting him, plus the platforms, facil-ities, and weapons of his adversary.
For purposes of this discussion we will divide CDSdisplays into three functional areas:
(1) Operator display--Those displays provide sensordata (including sonar if applicable and enable theindividual to enter, readout, and make use of computer datavia graphics and alphanumeric displays.
(2) Command/evaluation displays--These are for the useof the force commander or unit commander and his staff. Thedisplays are larger (called Large Screen Displays) and usu-ally allow only limited raw data input. Their primary pur-pose is evaluation of data and employment of weapons.
(3) Automated status displays--These provide inform-ation of a general nature for large numbers of tracks of thesame general category, such as that provided by manual stat-us boards found in conventional CICs.
20.4.5.1 Operator Displays. This type of display is usu-ally standardized for economy and to make training, repair,and supply easier. It is adapted to specific jobs by theCDS computer program. Usually it contains a 30- to 37-cmCRT employing two separate guns and allows the display ofraw sensor video as well as symbology, graphics, and al-phanumerics. Communications with the computer are accomp-lished via fixed action buttons, computer-controlled actionbuttons, an alphanumeric keyboard (like a personal comput-er), and a communications panel. Positions on the main CRTare indicated by moving a marker on the scopeface with aball-shaped roller, a joystick, or by touching the face ofthe CRT. Computer-supplied lists of alphanumeric data areprovided by a smaller auxiliary CRT placed above or besidethe main CRT. Generation of symbology may be done at eachdisplay or by a centralized symbol generator.
20.4.5.2 Command/Evaluation Displays. In the evolutionfrom the large-areas status boards and vertical polar co-ordinate plots to the automated display provided by CDS, a20-fold increase in target-handling capability was realized,but the greatest advantage of the manual displays--that ofgeneral availability to decision making made possible by thesize of the manual plot was lost. Where the vertical plotprovided a large display for use by several persons simul-taneously, the 37-cm plan position indicator (PPI) of theoperator display was inaccessible to more than one or twopersons and did not provide sufficient detail over a largeenough display area for the commander and his staff. Earlylarge screen displays could not provide real-time update ofdata and therefore were little better than manual methods.
Later displays were built employing large (53-cm dia-meter) CRTs that were essentially enlarged Operator Displayssuch as the navy's Operations Summary Console (OSC)(figure20-11).
Shore-based systems such as the Marine Air Command andControl System (MACCS) employed large projection type dis-plays that operated from CDS computer data in real timequite like large-screen commercial television. These dis-plays were used primarily for high-level command and controlemploying symbology graphics and alphanumerics with no ac-cess to raw sensor data.
With the advent of liquid-crystal light valve technol-ogy in the early 1980s, displays over one square meter inarea became available that had the advantage of acceptabil-ity for viewing under ambient light, unlike the CRTs thatrequire a darkened room. These displays provide multi-colorcomputer-controlled displays on a full-color map or chartbackground.
20.4.5.3 Automated Status Displays. One of the last manualfunctions in automated CDS is that of tabular data. Withmodern track loading it is unlikely that men can keep upwith available data; therefore, modern CDSs provide for a TVmonitor display of status board data much like flight sched-ule displays in modern commercial airports.
20.4.6 Display References
The Operator Display retained some of the same limitationsof noncomputerized radar repeaters in that the display pro-vided was not corrected for the course and speed of theplatform within which it was installed. This characteristicis not a problem in most situations and is even desirable insome circumstances; however, it has been a significant draw-back to the automation of antisubmarine warfare, ASCM tar-geting, navigation, and other activities requiring true-mo-tion displays or a geographically fixed plot.
Command/Evaluation displays beginning with the Opera-ations Summary Console (OSC) have been designed with thecapacity of providing a geographically fixed true-motiondisplay in addition to the conventional relative-motion dis-play provided by radarscopes. While prosecuting sonar con-tacts, it is imperative that a plot of the geographic posi-tion of the attacking ship, assist units, and submarine bemaintained in order to evaluate the target submarine's man-euvers and aspect. Without a geographically fixed plot itcan be extremely difficult to separate the submarine fromunderwater geographic features, decoys, and even the waketurbulence of the prosecuting ships. This need has beenfilled by the dead-reckoning tracer (DRT), and more recentlyby varieties of the NC-2 plotter, each requiring several mento operate. The DRT and the more advanced NC-2 are limitedby the requirement to plot manually all contacts with pencilon paper. This eventually results in a complex mass oflines and requires that target processing and evaluationstop while the paper is changed and the plotting 'bug' or'bugs' reset. Under those conditions, 80 percent of theeffort was devoted to manual processing and only 20 percentto the actual consideration of tactics.
Using the OSC or some of the other evaluation displays,the operator may select the frame of reference within whichinformation is to be displayed. In a sector-screening situ-ation with the guide as a reference and track history ena-bled on own ship, the operator may observe his ship's posi-tion within its assigned sector for the previous 30 minutesto verify complete coverage. Once sonar contact is gained,he chooses a position near but not directly over the submar-ine and enters a symbol for a geographically fixed point,which is then used as a reference to orient the OSC geo-graphic display. Once this is accomplished, the scope pre-sentation shifts to center on the geographic point. Theown-ship symbol can be observed to move across the scopeface in the manner of a DRT bug. OSC track history is thenenabled for the submarine, and all surface and air assistunits. The geographic plot that results is maintained auto-matically as long as the operator desires without the delaysand inconvenience inherent in manual plotting.
20.5 INHERENT PROBLEMS
Command, control and communications systems span a continuumfrom the issuing of simple verbal orders and the direct ob-servation of activity, to remote directives and syntheticrepresentation of resulting activity. Command and controlsystems are approaching the point where the more complexcase may occur within the same span of time as the simplestone. In the following paragraphs some of the more contro-versial problems are addressed.
20.6.1 Evaluation
The digital computer is supremely capable of processinglarge volumes of data and performing a remarkable degree ofevaluation, given a suitable program set. There may be,however, a tendency for users to place inordinate signif-icance upon the results. C3 is characteristically uncertainand unpredictable, involving considerable subjective evalu-ation.
20.6.2 Orientation
There has been a tendency to employ technology merely be-cause it was available, not because it was needed. Command-ers are often faced with a C3 system unsuited to his or herneeds. In most cases the tendency is to adjust to the sys-tem even though it may waste resources and restrict effect-iveness. C3 systems should be designed with sufficientflexibility to accommodate the needs of different humanbeings and operations. Emphasis in system design shouldfavor the commander rather than the technology employed.
20.6.3 Cost
Hardware and supporting equipment and processes are expen-sive. The economics of the military environment will alwaysbe a strong factor in deciding which C3 system will be em-ployed.
20.6.4 Decision Making
In the attempt to expand the capabilities of general-purposecomputers and make them as flexible in use as possible, un-necessarily detailed information is frequently provided. Too much information can create indecision, just as can toolittle information. The C3 system must be structured andoperated to reduce variables and define alternatives forcommanders, while concurrently avoiding an information glutat the decision-making level.
20.6.5 Discipline
Where high-level commanders possess the capability to engagein evaluation at the on-scene commander level, erosion ofauthority of the on-scene commander will take place. If anumber of commanders in the C3 system are capable of inter-acting, confusion may occur. The senior commander with themost pertinent information should take precedence. Multip-licity of evaluation can provide consistently better resultsthan the evaluation of a single commander. Those in commandat all echelons must know what their seniors are thinking,when to act, when to question, and when to give orders. Command and control of the near future will require a ra-tional discipline on the part of informed commanders who
work together as a team to accomplish objectives and goals. On-scene commanders must be constantly sensitive to ordersfrom higher authority while maintaining the mental freedomof action necessary when it is required that they act, butbeing careful not to include action contrary to the nationalinterest. This concept of mental discipline is perhaps themost critical--and controversial--area in this new age ofcommand and control.
20.6.6 Survivability
Beyond the level of direct command and control, communica-tions plays the key role in maintaining the integrity of theC3 system. Reliability through system design (redundancy,ruggedization, miniaturization, etc.) is essential to ensur-ing survivability, particularly in a time of escalating con-flict. An ironic aspect of communications survivability atthe highest C3 levels also exists. An opposing government'scontrol over its own military forces is also normally dic-tated by its having intact communications. Destruction ofits communications system would preclude stopping a conflictonce its forces were committed. This consideration can im-pact significantly upon the tactical employment of ownforces.
20.7 REFERENCES/BIBLIOGRAPHY
Frieden, Lieutenant D.R. 'The Operations Summary Console.' Surface Warfare (July 1978): 20-22.
Grant, Lieutenant Peter M. 'Getting the Big Picture into OurCICs.' U.S. Naval Institute Proceedings (January 1984):109-11.
Moran, M.J. 'Winning in the Computer Age.' Surface Warfare(March/April 1976): 24-28.
Naval Operations Department, U.S. Naval War College. Technological Factors and Constraints in System PerformanceStudy--Command and Control. Vol. 1-2, 1975.
Peet, Vice Admiral Ray, USN, and Michael F. Melich. 'FleetCommanders: Ashore or Afloat?' U.S. Naval InstituteProceedings (June 1976): 25-33.
Staff. 'Task Force Survival Relies on Early Detection.' Military Electronics/Countermeasures (March 1983): 24-36.
Tennent, Lieutenant J.H. 'Aegis Display System: TheCommander's Battle Picture.' Surface Warfare (March1982): 2-6.
Ward, J.W.D., and G.N. Turner. Military Data Processing andMicrocomputers. Oxford, U.K.: Brassey's Publishers Limited,1982.
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Today is fast.ai’s biggest day in our four year history. We are releasing:
- fastai v2: A complete rewrite of fastai which is faster, easier, and more flexible, implementing new approaches to deep learning framework design, as discussed in the peer reviewed fastai academic paper
- fastcorefastgpu: Foundational libraries used in fastai v2, and useful for many programmers and data scientists
- Practical Deep Learning for Coders (2020 course, part 1): Incorporating both an introduction to machine learning, and deep learning, and production and deployment of data products
- Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD: A book from O’Reilly, which covers the same material as the course (including the content planned for part 2 of the course)
Also, in case you missed it, earlier this week we released the Practical Data Ethics course, which focuses on topics that are both urgent and practical.
Contents
- fastcore and fastgpu
fastai v2
fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying patterns of many deep learning and data processing techniques in terms of decoupled abstractions. These abstractions can be expressed concisely and clearly by leveraging the dynamism of the underlying Python language and the flexibility of the PyTorch library. fastai includes:
- A new type dispatch system for Python along with a semantic type hierarchy for tensors
- A GPU-optimized computer vision library which can be extended in pure Python
- An optimizer which refactors out the common functionality of modern optimizers into two basic pieces, allowing optimization algorithms to be implemented in 45 lines of code
- A novel 2-way callback system that can access any part of the data, model, or optimizer and change it at any point during training
- A new data block API
- And much more…
fastai is organized around two main design goals: to be approachable and rapidly productive, while also being deeply hackable and configurable. It is built on top of a hierarchy of lower-level APIs which provide composable building blocks. This way, a user wanting to rewrite part of the high-level API or add particular behavior to suit their needs does not have to learn how to use the lowest level.
To see what’s possible with fastai, take a look at the Quick Start, which shows how to use around 5 lines of code to build an image classifier, an image segmentation model, a text sentiment model, a recommendation system, and a tabular model. For each of the applications, the code is much the same.
Read through the Tutorials to learn how to train your own models on your own datasets. Use the navigation sidebar to look through the fastai documentation. Every class, function, and method is documented here. To learn about the design and motivation of the library, read the peer reviewed paper, or watch this presentation summarizing some of the key design points.
All fast.ai projects, including fastai, are built with nbdev, which is a full literate programming environment built on Jupyter Notebooks. That means that every piece of documentation can be accessed as interactive Jupyter notebooks, and every documentation page includes a link to open it directly on Google Colab to allow for experimentation and customization.
It’s very easy to migrate from plain PyTorch, Ignite, or any other PyTorch-based library, or even to use fastai in conjunction with other libraries. Generally, you’ll be able to use all your existing data processing code, but will be able to reduce the amount of code you require for training, and more easily take advantage of modern best practices. Here are migration guides from some popular libraries to help you on your way: Plain PyTorch; Ignite; Lightning; Catalyst. And because it’s easy to combine and part of the fastai framework with your existing code and libraries, you can just pick the bits you want. For instance, you could use fastai’s GPU-accelerated computer vision library, along with your own training loop.
fastai includes many modules that add functionality, generally through callbacks. Thanks to the flexible infrastructure, these all work together, so you can pick and choose what you need (and add your own), including: mixup and cutout augmentation, a uniquely flexible GAN training framework, a range of schedulers (many of which aren’t available in any other framework) including support for fine tuning following the approach described in ULMFiT, mixed precision, gradient accumulation, support for a range of logging frameworks like Tensorboard (with particularly strong support for Weights and Biases, as demonstrated here), medical imaging, and much more. Other functionality is added through the fastai ecosystem, such as support for HuggingFace Transformers (which can also be done manually, as shown in this tutorial), audio, accelerated inference, and so forth.
There’s already some great learning material made available for fastai v2 by the community, such as the “Zero to Hero” series by Zach Mueller: part 1; part 2.
Practical Deep Learning for Coders, the course
Previous fast.ai courses have been studied by hundreds of thousands of students, from all walks of life, from all parts of the world. Many students have told us about how they’ve become multiple gold medal winners of international machine learning competitions, received offers from top companies, and havingresearchpaperspublished. For instance, Isaac Dimitrovsky told us that he had “been playing around with ML for a couple of years without really grokking it… [then] went through the fast.ai part 1 course late last year, and it clicked for me”. He went on to achieve first place in the prestigious international RA2-DREAM Challenge competition! He developed a multistage deep learning method for scoring radiographic hand and foot joint damage in rheumatoid arthritis, taking advantage of the fastai library.
This year’s course takes things even further. It incorporates both machine learning and deep learning in a single course, covering topics like random forests, gradient boosting, test and validation sets, and p values, which previously were in a separate machine learning course. In addition, production and deployment are also covered, including material on developing a web-based GUI for our own deep learning powered apps. The only prerequisite is high-school math, and a year of coding experience (preferably in Python). The course was recorded live, in conjunction with the Data Institute at the University of San Francisco.
After finishing this course you will know:
- How to train models that achieve state-of-the-art results in:
- Computer vision, including image classification (e.g.,classifying pet photos by breed), and image localization and detection (e.g.,finding where the animals in an image are)
- Natural language processing (NLP), including document classification (e.g.,movie review sentiment analysis) and language modeling
- Tabular data (e.g.,sales prediction) with categorical data, continuous data, and mixed data, including time series
- Collaborative filtering (e.g.,movie recommendation)
- How to turn your models into web applications, and deploy them
- Why and how deep learning models work, and how to use that knowledge to improve the accuracy, speed, and reliability of your models
- The latest deep learning techniques that really matter in practice
- How to implement stochastic gradient descent and a complete training loop from scratch
- How to think about the ethical implications of your work, to help ensure that you’re making the world a better place and that your work isn’t misused for harm
We care a lot about teaching, using a whole game approach. In this course, we start by showing how to use a complete, working, very usable, state-of-the-art deep learning network to solve real-world problems, using simple, expressive tools. And then we gradually dig deeper and deeper into understanding how those tools are made, and how the tools that make those tools are made, and so on. We always teach through examples. We ensure that there is a context and a purpose that you can understand intuitively, rather than starting with algebraic symbol manipulation. We also dive right into the details, showing you how to build all the components of a deep learning model from scratch, including discussing performance and optimization details.
The whole course can be completed for free without any installation, by taking advantage of the guides for the Colab and Gradient platforms, which provide free, GPU-powered Notebooks.
Deep Learning for Coders with fastai and PyTorch, the book
To understand what the new book is about, and who it’s for, let’s see what others have said about it… Soumith Chintala, the co-creator of PyTorch, said in the foreword to Deep Learning for Coders with fastai and PyTorch:
But unlike me, Jeremy and Sylvain selflessly put a huge amount of energy into making sure others don’t have to take the painful path that they took. They built a great course called fast.ai that makes cutting-edge deep learning techniques accessible to people who know basic programming. It has graduated hundreds of thousands of eager learners who have become great practitioners.
In this book, which is another tireless product, Jeremy and Sylvain have constructed a magical journey through deep learning. They use simple words and introduce every concept. They bring cutting-edge deep learning and state-of-the-art research to you, yet make it very accessible.
You are taken through the latest advances in computer vision, dive into natural language processing, and learn some foundational math in a 500-page delightful ride. And the ride doesn’t stop at fun, as they take you through shipping your ideas to production. You can treat the fast.ai community, thousands of practitioners online, as your extended family, where individuals like you are available to talk and ideate small and big solutions, whatever the problem may be.
Peter Norvig, Director of Research at Google (and author of the definitive text on AI) said:
“Deep Learning is for everyone” we see in Chapter 1, Section 1 of this book, and while other books may make similar claims, this book delivers on the claim. The authors have extensive knowledge of the field but are able to describe it in a way that is perfectly suited for a reader with experience in programming but not in machine learning. The book shows examples first, and only covers theory in the context of concrete examples. For most people, this is the best way to learn.The book does an impressive job of covering the key applications of deep learning in computer vision, natural language processing, and tabular data processing, but also covers key topics like data ethics that some other books miss. Altogether, this is one of the best sources for a programmer to become proficient in deep learning.
Curtis Langlotz, Director, Center for Artificial Intelligence in Medicine and Imaging at Stanford University said:
Gugger and Howard have created an ideal resource for anyone who has ever done even a little bit of coding. This book, and the fast.ai courses that go with it, simply and practically demystify deep learning using a hands on approach, with pre-written code that you can explore and re-use. No more slogging through theorems and proofs about abstract concepts. In Chapter 1 you will build your first deep learning model, and by the end of the book you will know how to read and understand the Methods section of any deep learning paper.
fastcore and fastgpu
fastcore
Python is a powerful, dynamic language. Rather than bake everything into the language, it lets the programmer customize it to make it work for them. fastcore uses this flexibility to add to Python features inspired by other languages we’ve loved, like multiple dispatch from Julia, mixins from Ruby, and currying, binding, and more from Haskell. It also adds some “missing features” and cleans up some rough edges in the Python standard library, such as simplifying parallel processing, and bringing ideas from NumPy over to Python’s list type.
fastcore contains many features. See the docs for all the details, which cover the modules provided:
Brothers Fax Machine Manual
test
: Simple testing functionsfoundation
: Mixins, delegation, composition, and moreutils
: Utility functions to help with functional-style programming, parallel processing, and moredispatch
: Multiple dispatch methodstransform
: Pipelines of composed partially reversible transformations
fastgpu
fastgpu provides a single command,
fastgpu_poll
, which polls a directory to check for scripts to run, and then runs them on the first available GPU. If no GPUs are available, it waits until one is. If more than one GPU is available, multiple scripts are run in parallel, one per GPU. It is the easiest way we’ve found to run ablation studies that take advantage of all of your GPUs, result in no parallel processing overhead, and require no manual intervention.Acknowledgements
Many thanks to everyone who helped bring these projects to fruition, most especially to Sylvain Gugger, who worked closely with me over the last two years at fast.ai. Thanks also to all the support from the Data Institute at the University of San Francisco, and to Rachel Thomas, co-founder of fast.ai, who (amongst other things) taught the data ethics lesson and developed much of the data ethics material in the book. Thank you to everyone from the fast.ai community for all your wonderful contributions.
Brother Fax Machine Manual
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