No one source can provide all of the data necessary for security monitoring. To be truly effective, organizations need more data, and they need it faster. Early detection of infiltration and compromise are key to response and recovery. Endpoint records are not fully network aware, and network packets can’t detail activities on host-based threats, so security professionals need both.
These slides - based on the webinar featuring David Monahan, research director of security and risk management at leading IT analyst firm Enterprise Management Associates (EMA) - provides findings on how organizations are using these data types, their largest drivers for integrations and their greatest challenges in integrating the data. He will also discuss rampant bravado in network and security programs concerning their organizational maturity.
No one source can provide all of the data necessary for security monitoring. To be truly effective, organizations need more data, and they need it faster. Early detection of infiltration and compromise are key to response and recovery. Endpoint records are not fully network aware, and network packets can’t detail activities on host-based threats, so security professionals need both.
These slides - based on the webinar featuring David Monahan, research director of security and risk management at leading IT analyst firm Enterprise Management Associates (EMA) - provides findings on how organizations are using these data types, their largest drivers for integrations and their greatest challenges in integrating the data. He will also discuss rampant bravado in network and security programs concerning their organizational maturity.
Sulphonamides are the first effective chemotherapeutic agents used for bacterial infection in humans. Sulfonamides have a wide range of pharmacological activities such as Oral hypoglycemic, antileprotic, anti epileptic, anti-hypertensive, anti-bacterial, anti-protozoal, anti-fungal, anti retroviral, anti cancer, antiinflammatory, and used as diuretic. This review consists of a discussion on the various pharmacological effects of sulfonamides
Big Data has moved beyond being just a buzzword. Organizations are operationalizing various Big Data technologies to answer critical business questions and power sophisticated workloads.
Building on the success of their 2012 “Big Data Comes of Age” research report, EMA VP of Research, Shawn Rogers, EMA Senior Analyst, John Myers, and 9sight Consulting Founder and Principal, Dr. Barry Devlin, will reveal their latest big data research findings during this informative Webinar.
Attendees will learn not just the what's of Big Data technologies but also the why’s of use cases, implementation strategies and technology choices, as well as discover:
>>Most popular use cases for big data based on nearly 600 projects reviewed in this research
>>Which Hadoop distributions are gaining traction
>>The technical and business-driven-challenges for Big Data
>>Most popular data sources for Big Data
>>How organizations are continuing the trend of implementing the EMA Hybrid Data Ecosystem (HDE) in association with their Big Data initiatives
Digital Heritage Documentation Via TLS And Photogrammetry Case Studytheijes
In the last decade, several manual tradition measurement techniques were used to document the heritage buildings around the word; however, some of these techniques take a long time, often lack completeness, and may sometimes give unreliable information. In contrast, terrestrial laser scanning “TLS” surveys and Photogrammetry have already been undertaken in several heritage sites in the United Kingdom and other countries of Europe as a new method of documenting heritagesites. This paper focuses on using the TLS and Photogrammetry methods to document one of the important houses in Historic Jeddah, Saudi Arabia, which is Nasif Historical House, as an example of Digital Heritage Documentation (DHD).
Enhancing the Mean Ratio Estimator for Estimating Population Mean Using Conve...inventionjournals
: Use of auxilliary information in survey sampling has its eminent role in estimating the population parameters with greater precision. The present paper concentrates on estimating the finite population mean by proposing the new generalised ratio type estimators in simple random sampling without replacement using coefficient of variation and population deciles. The expressions for mean square error and bias were calculated and compared with the classical and existing estimators. By this comparison it is conformed that our proposed class of new estimators is a class of efficient estimators under percent relative efficiency (PRE) criterion
1. Nombre #
ATOMOS
“C”
#
ATOMOS
“H”
Fórmula desarrollada Fórmula semidesarrollada Fórmula
condens
ada
Imagen
Metano
1 4 H
H-C-H
H
CH4
CH4
Etano
2 6 H
H -C- H
H
CH3
CH3
C2H6
Propano
3 8
H H
CH2
CH3 CH3
C3H8
Butano
4 10 CH2 CH3
CH3 CH2
C4H10
Pentano
5 12
H H
CH2 CH2
CH3 CH2 CH3
C5H12
Hexano
6 14
H H
CH2 CH2 CH3
CH3 CH2 CH2
C6H14
Heptano
7 16
H H
CH2 CH2 CH2
CH3 CH2 CH2 CH3
C7H16
Octano
8 18
H H
CH2 CH2 CH2 CH3
CH3 CH2 CH2 CH2
C8H18
Nonano
9 20
H
CH2 CH2 CH2 CH2
CH3 CH2 CH2 CH2 CH3
C9H20
Decano
10 22
H H
CH2 CH2 CH2 CH2 CH3
CH3 CH2 CH2 CH2 CH2
C10H22
ALCANOS
2. Nombre # A.T
“c”
#A.T
“h”
Fórmula desarrollada Fórmula semidesarrollada Fórmula
condensada
Meteno
1 2
H=C=H CH2
CH2
Eteno
2 4 H H
C=C
H H
CH2
CH2
C2H4
Propeno
3 6 H H
C=C C H
H H H
CH
CH2 CH3
C3H6
Buteno
4 8 H H H
C=C C C H
H H H H
CH CH3
CH2 CH2
C4H8
Penteno
5 10 H H H H
C=C C C C H
H H H H H
CH CH2
CH2 CH2 CH3
C5H10
Hexeno
6 12 H H H H H
C=C C C C C H
H H H H H H
CH CH2 CH3
CH2 CH2 CH2
C6H12
Hepteno
7 14 H H H H H H
C=C C C C C C H
H H H H H H H
CH CH2 CH2
CH2 CH2 CH2 CH3
C7H14
Octeno
8 16 H H H H H H H
C=C C C C C C C H
H H H H H H H H
CH CH2 CH2 CH3
CH2 CH2 CH2 CH2
C8H16
Noneno
9 18 H H H H H H H H
C=C C C C C C C C H
H H H H H H H H H
CH CH2 CH2 CH2
CH2 CH2 CH2 CH2 CH3
C9H18
Deceno
10 20 H H H H H H H H H
C=C C C C C C C C C H
H H H H H H H H H H
CH CH2 CH2 CH2 CH3
CH2 CH2 CH2 CH2 CH2
C10H20
ALQUENOS
3. Nombre A.T
“c”
A.T.
“h”
Fórmula desarrollada Fórmula
semidesarrollada
Fórmula
condensada
Metino
1 2
C H CH2
CH2
Etino
2 4
H C C H
CH2
CH2
C2H4
Propino
3 6 H
H C C –C -H
H
CH
CH2 CH3
C3H6
Butino
4 8 H H
H C C –C -C -H
H H
CH CH3
CH2 CH2
C4H8
Pentino
5 10 H H H
H C C –C -C -C-H
H H H
CH CH2
CH2 CH2 CH3
C5H10
Hexino
6 12 H H H H
H C C –C -C -C-C-H
H H H H
CH CH2 CH3
CH2 CH2 CH2
C6H12
Heptino
7 14 H H H H H
H C C –C -C -C-C-C-H
H H H H H
CH CH2 CH2
CH2 CH2 CH2
CH3
C7H14
Octino
8 16 H H H H H H
H-C C-C-C-C-C-C-C-H
H H H H H H
CH CH2 CH2
CH3
CH2 CH2 CH2
CH2
C8H16
Nonino
9 18
H H H H H H H
H-C C-C-C-C-C-C-C-C-H
H H H H H H H
CH CH2 CH2 CH2
CH2 CH2 CH2 CH2
CH3
C9H18
Decino
10 20 H H H H H H H H
H-C C-C-C-C-C-C-C-C-C-H
H H H H H H H H
CH CH2 CH2 CH2
CH3 CH2 CH2 CH2 CH2
CH2
C10H20
ALQUINOS
