Identifier: milmanual-fminfantry-based-opposing-force. Identifier-ark: ark ://t4vh6sc4g. Ocr: ABBYY FineReader Ppi: FM Field Service Regulations-Operations (ebook) pdf epub ebooks Download now for free or you can read online FM Infantry-Based. be transitioned to a new lower-level series of publications, called Army Techniques Publications (ATPs). Army Field Manuals. FM, Title, Notes, Date, Format.

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FM Preface. This manual is one of a series that describes a capabilities- based Opposing Force (OPFOR) for training US Army commanders, staffs, and. FM Multiservice Communications Procedures for the Single-Channel Ground and Airborne Radio System (ebook) pdf epub ebooks download free. Pages · · KB · Downloads ·English. Preview Pages· · MB·83 Downloads FM Infantry-Based Opposing

Cine and contrast images were evaluated as described elsewhere [ 22 ]. In brief, endocardial and epicardial borders were outlined on the short axis cine images. Volumes and ejection fraction were derived by summation of epicardial and endocardial contours.

Coronary angiography and analysis by coronary artery territory Coronary angiography was performed by standard techniques [ 24 ] and analyzed masked to identity, clinical information, and CMR results. Two experienced interventional cardiologists S.

Statistical analysis Absolute numbers and percentages were computed to describe the patient population. All continuous variables were tested for normality.

Normally distributed continuous variables were expressed as means with standard deviation and skewed variables were presented as medians with quartiles. Positive and negative likelihood ratios LR were calculated. All statistical analyses were performed using SPSS, version Results Patient characteristics In total patients were included in the final analysis Fig. Seventy-two patients were referred for work-up of suspected CAD, and 87 patients were referred for work-up of ischemia in known CAD.

The group with known CAD was older Of note, the prevalence of the different types of arrhythmia was similar between the two groups. Five of those patients were in the suspected CAD group, and three out of five were classified correctly as negative by CMR. The other three patients had known CAD, two of them had coronary stenosis on coronary angiography, one of them was correctly identified by CMR.

The power of an expert system lies in its bank of domain knowledge. An alternative approach would be to train the domain expert in knowledge acquisition and representation. A further, attractive approach would be to use computer programs to implicitly derive rules by examining test data produced by domain experts. Such neural networks are self-replicating and may often derive rules not seen by a knowledge engineer. Knowledge representation formalizes and organizes the knowledge. Knowledge bases can be represented by production rules that use Boolean operators.

Production rules permit the knowledge base to be broken down to facilitate management and organization; rules may also be deleted or added without affecting other rules. Breaking the rule base down into contextual segments permits segments to be paged into and out of the expert system as required.

FM 100-63 Infantry-Based Opposing Force

Another widely used representation, based on a more passive view of knowledge, is the unit frame, schema, or list structure.

In a microbiology expert system, the use of hierarchical grouping permits rules to be applied to groups of organisms or of antibiotics, for example. Drug test groups may be used to define the antimicrobials to be tested as well as their reporting priority, although the specimen source is usually not considered. Expert systems may be constructed to trigger rules following certain guidelines. Although many of these are enforced by the logic of the rules themselves, there will often be a relative priority for rules, as a rule can use the expert result obtained by the action of a previously triggered rule.

Generally, there will be some protective mechanism to prevent one rule from changing a result that has already been changed by another rule. Also, rules that will have no effect on a result change generally do not fire.

The use of rules with different certainty values or confidence factors assigned by the expert during knowledge acquisition allows the system to address imprecise, uncertain, and incomplete data. Confidences are similar to probabilities but are meant to imitate human reasoning rather than to be mathematical definitions.

An important subclass of such reasoning with uncertainty is called evidence theory or fuzzy logic. A backward-chaining inference engine is goal driven and tries to prove a rule conclusion by confirming the truth of all its premises, e.

A forward-chaining inference engine is data driven and examines the current state of the knowledge base, finds those rules whose premises can be satisfied, and adds the conclusion of those rules to the database; it then reexamines the complete knowledge base and repeats the process, e.

Users may question the credibility of an expert system that uses uncertain and heuristic knowledge. For this reason, most expert systems can trace the line of reasoning and provide explanations for conclusions drawn.

This also helps the user to understand system behavior. Expert systems usually separate domain-specific knowledge from general-purpose reasoning and representation techniques. The user interface, the explanation subsystem, the inference engine, and the knowledge base editor comprise the shell the skeletal system or AI tools. There are basically two ways to write an expert system: from first principles or by using a shell.

The use of shells to write expert systems greatly reduces the cost and time of development; all that is required is domain-specific knowledge. Expert systems are developed iteratively from a prototype by consultation with both experts and users. Informational messages can be in the form of footnotes and warnings from standard guidelines. Intrinsic rules detect atypical susceptibility or resistance in an isolate with a known identification ID.

Resistance marker rules may change susceptible S or intermediate I interpretations to resistant R.

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Antibiotic-specific rules can be of several types. A promotion rule may promote an antibiotic for a resistant organism. Similarly, a suppression rule may suppress a single antibiotic or a class, e.

Drug class rules allow representative antimicrobials to be tested as markers of antibiotic classes. Hierarchical rules are more specific; e. In a feasibility study applied to Staphylococcus aureus, the expert system was able to detect the inconsistencies of the antibiotic susceptibility test and to identify required knowledge, thereby permitting a phenotypic interpretation of results.

As stated above, artificial intelligence is a part of computer science that deals with programs mimicking the intelligence of humans. Artificial intelligence can be used to check the quality of the determination of the antibiotic susceptibility of bacteria. This application is useful because susceptibility testing is subject to biological and technical variations that have to be detected. Three types of reasoning are used either by the biologist or by expert systems: low-level quality checking, dealing with individual results; microbiological interpretation of the whole set of results; and medical interpretation of the results.

The use of artificial intelligence in these fields is sustained by the structured nature of the knowledge. Bacterio-expert is a simple expert system for assisting in the validation of antibiotic sensitivity testing.

This system is incorporated into a data acquisition and editing program for bacteriology tests Bacterio was written in Turbo-Pascal for personal-computer users. Of 4, antibiotic sensitivity tests on S. The main problem was, as usual for artificial intelligence applications, to transfer human expertise into an adapted knowledge base.

The advantages of expert systems over humans are their reproducibilities of answers and their availability Interpretive reading of antibiotic disc agar diffusion tests indicates the resistance mechanisms, if any, expressed by a bacterium. Vedel et al. For every strain, the conclusion of the expert analysis of the automated test was compared with the commonly accepted interpretation of disc diffusion tests.

Of the strains studied, were similarly interpreted Similarly, the results of the two methods concurred for most of the acquired resistance phenotypes. However, for 25 strains 8. The expert system proposed an erroneous mechanism 5 strains ; several mechanisms, including the correct one 17 strains ; or no mechanisms 1 strain.

For 2 strains the natural resistance mechanism was not detected at first by the automated method but was subsequently deduced by the expert analysis according to the bacterial identification. These results demonstrate that a satisfactory interpretive reading of automated antibiotic susceptibility tests is possible in 4 to 5 h but requires a careful selection of the antibiotics tested as phenotypic markers.

Manual review of antibiotic susceptibility testing results is an essential component of a microbiology laboratory's quality control QC process. Such a review is tedious and prone to human error, however. Jackson et al. It uses a similarity function to allow matching against this library when two patterns are close but not identical.

The use of this system allows a more efficient and reliable review of the laboratory's antibiotic susceptibility testing results. Those authors pointed out several limitations of the system: the challenge of keeping knowledge up to date, the quality of knowledge entered, the need for a knowledge engineer, and the fact that the system is retrospective not incorporated into the laboratory information system.

Lamma et al. In a project jointly run by the University of Bologna and Dianoema, those researchers used data-mining techniques to automatically discover association rules from microbiological data and to obtain from them alarm rules for data validation by the ESMIS expert system.

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To our knowledge, there are two expert systems capable of interpreting antibiograms which are available on the World Wide Web. Seven sets of antimicrobial MIC breakpoints are used in Europe.

Furthermore, almost all the breakpoint committees produce varied and often conflicting expert rules.The authors focus on each of the major psychiatric illnesses, including depression, anxiety disorder, bipolar disorder, schizophrenia, substance abuse, eating disorders, and mental illness, as well as on the potential impact of these illnesses on infants and children. An expert system is a computer program designed to simulate the problem-solving behavior of a human who is an expert in a narrow task domain or discipline, and the terms expert system and knowledge-based system are often used synonymously; the terms knowledge application system and decision support system are also used.

Developmental Biology — VanLoock, A.


A simple expert system normally comprises a knowledge base, an inference engine, and the end-user interface. It has been shown that as the pH of porcine muscle is reduced from physiological values to 5.

LGE revealed a transmural infarction of the inferior wall.

The end result of this is a reduction of space within the myofibril. Identification of the kda polypeptide in post-mortem skeletal-muscle as a degradation product of troponin-t.

Oxidizing agents can also influence glucose transport.

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