Tuesday, April 20, 2010
google blog
Cloud computing is all about how a company can help put their information on the internet to help them keep up with the massive amonts of data they have. One company has to sacrafice the money and other company rep the benifits of how the cloud works. A company can only pay for the usage they need , if a company needs more they pay for more if a company wants less they get less. this is the best thing that a comapny can do for it organization, you only pay for what you need.
Tuesday, April 6, 2010
Neural Network Software and Breast Cancer
Classify Breast Cancer Cells with BrainMaker Neural Network Software
Breast cancer cells are traditionally examined under a microscope by a human, who decides the degree of cancer present. People are inconsistent in these judgements from day to day and from person to person.
A BrainMaker neural network that classifies breast cancer cells has been developed. The system was developed by Andrea Dawson, MD of the University of Rochester Medical Center, Richard Austin, MD of the University of California at San Francisco, and David Weinberg, MD, PhD of the Brigham and Womens' Hospital and Harvard Medical School of Boston. Initial comparisons showed that BrainMaker is in good agreement with human observer cancer classifications.
Cancer cells are measured with the CAS-100 (Cell Analysis System, Elmhurst, IL). There are 17 inputs to the neural network which represent morphometric features such as density and texture. There are four network outputs representing nuclear grading. The cancerous nucleus is graded as being well, moderate, or poorly differentiated, or as benign. Correct grade assignments were made between 52% and 89% of the time on cases not seen during training. The lower success rate (for well differentiated) may have been due to the smaller percentage of this type in the training set. In addition, heterogeneity is much lower in well-differentiated tumors. Cancerous nuclei were classified within one grade of the correct grade.
INPUTS object size
object shape
object sum density
object average density
object texture
angular second moment
contrast
difference moment
sum variance
difference variance (Fisher)
difference entropy
information measure B
maximum correlation coefficient
difference variance
diagonal moment
second diagonal moment
product moment
OUTPUTS
well differentiated
moderate
poor
benign
Thsi network software helps the human kind my letting humans that have been trained to do there jobs in the medical profession answer question and put them in a computer program and run the result againt, historical result.
Breast cancer cells are traditionally examined under a microscope by a human, who decides the degree of cancer present. People are inconsistent in these judgements from day to day and from person to person.
A BrainMaker neural network that classifies breast cancer cells has been developed. The system was developed by Andrea Dawson, MD of the University of Rochester Medical Center, Richard Austin, MD of the University of California at San Francisco, and David Weinberg, MD, PhD of the Brigham and Womens' Hospital and Harvard Medical School of Boston. Initial comparisons showed that BrainMaker is in good agreement with human observer cancer classifications.
Cancer cells are measured with the CAS-100 (Cell Analysis System, Elmhurst, IL). There are 17 inputs to the neural network which represent morphometric features such as density and texture. There are four network outputs representing nuclear grading. The cancerous nucleus is graded as being well, moderate, or poorly differentiated, or as benign. Correct grade assignments were made between 52% and 89% of the time on cases not seen during training. The lower success rate (for well differentiated) may have been due to the smaller percentage of this type in the training set. In addition, heterogeneity is much lower in well-differentiated tumors. Cancerous nuclei were classified within one grade of the correct grade.
INPUTS object size
object shape
object sum density
object average density
object texture
angular second moment
contrast
difference moment
sum variance
difference variance (Fisher)
difference entropy
information measure B
maximum correlation coefficient
difference variance
diagonal moment
second diagonal moment
product moment
OUTPUTS
well differentiated
moderate
poor
benign
Thsi network software helps the human kind my letting humans that have been trained to do there jobs in the medical profession answer question and put them in a computer program and run the result againt, historical result.
Neural Networks
BrainMaker Neural Networks and Technical Analysis of Currencies
Mr. James O'Sullivan, of O'Sullivan Brothers Investments, Ltd. (Connecticut) has been successfully using many BrainMaker (California Scientific) neural networks on a daily basis for three years to do financial forecasting. He earned $250,000 in one month using neural networks to advise him on his New York Stock Exchange seat trades. Some of his networks are 88-90% accurate in their predictions, according to Mr. O'Sullivan. He uses an automated neural network system that monitors more than twenty different financial markets on a daily basis.
Mr. O'Sullivan has some unusual designs which act more as detectors of specific market conditions, rather than as exact price predictors. He combines the neural network data with other data from his technical analysis software to produce an automated report about a certain market. He gets his data live via satellite from Data Broadcasting and puts it into a charting and technical data module. He has pre-programmed the various algebraic manipulations to be performed on his data before BrainMaker files are built. He does moving averages, changes from period to period, and a few proprietary operations. He runs new data through the system and produces the one-page report in about thirty seconds. He says at least 80% of his decision-making is based on neural network predictions.
Mr. O'Sullivan has not fully disclosed his neural network designs to us, but his basic insights are still quite valuable. The key is to ask the neural network the right kind of questions. He asks questions such as "What is the probability of the product (or market) going up 0.618 standard deviations?" and "What percentage of the time does it go up that much?" He also asks questions about the directional behavior of the market and at what price the product (or market) is likely to take off in one direction or the other.
Mr. O'Sullivan's neural networks output several different things such as predicted prices, limits, and directional thrust. One neural network outputs the probability of a certain price occurring the next time period. Another neural network produces best stop price and best target price for long and short positions. Other neural networks produce directional indicators for three market energies. Another predicts the level at which the market is likely to take off.
In one design, the network is given various market conditions as input. The training output is the likelihood of various changes in price. For example, his neural network is told during training that, given similar market conditions, the closing price goes up at least 0.313 standard deviations above the prior day 90% of the time, at least 0.618 deviations 80% of the time, and at least 1 deviation 70% of the time.
An interesting phenomenon of the market is that when a change starts occurring in one direction or the other, there is a point at which it is very likely to continue moving in that direction for several time periods. Once a price reaches that level, there is a reduced risk to buy or sell (whichever is appropriate). Mr. O'Sullivan calls the network that predicts this price level his Risk Barometer network. He uses all the neural networks trained for a specific market when making decisions. For example, if the long term trend is up, the Fast Movement network is a large positive number, his Risk Barometer says 233.092, and the NYSE is at 250, it could indicate an overreacted market that will reverse itself soon.
Probability if...UP if...DOWN
85% 231.538 231.163
70% 231.791 230.909
60% 232.316 230.383
50% 233.675 229.025
40% 233.700 229.000
For Trades: Long buy Short sell
best stop = 230.708 231.992
best target = 232.054 230.646
Directional Indicators:
Trend Reaction Fast Movement Risk Barometer
Long Term 0.5066 21.499 -1.329 233.092
Medium Term -7.2280 18.580 8.387 227.643
Short Term 10.7250 4.243 3.377 229.450
This fella used the network to his advantage so that he could make prediction in the stock market, if it was going up or down and it helped him find the best places for his money. This is a great thing to have if you can narrow the field down and use the statistical information into usable helpful information.
Mr. James O'Sullivan, of O'Sullivan Brothers Investments, Ltd. (Connecticut) has been successfully using many BrainMaker (California Scientific) neural networks on a daily basis for three years to do financial forecasting. He earned $250,000 in one month using neural networks to advise him on his New York Stock Exchange seat trades. Some of his networks are 88-90% accurate in their predictions, according to Mr. O'Sullivan. He uses an automated neural network system that monitors more than twenty different financial markets on a daily basis.
Mr. O'Sullivan has some unusual designs which act more as detectors of specific market conditions, rather than as exact price predictors. He combines the neural network data with other data from his technical analysis software to produce an automated report about a certain market. He gets his data live via satellite from Data Broadcasting and puts it into a charting and technical data module. He has pre-programmed the various algebraic manipulations to be performed on his data before BrainMaker files are built. He does moving averages, changes from period to period, and a few proprietary operations. He runs new data through the system and produces the one-page report in about thirty seconds. He says at least 80% of his decision-making is based on neural network predictions.
Mr. O'Sullivan has not fully disclosed his neural network designs to us, but his basic insights are still quite valuable. The key is to ask the neural network the right kind of questions. He asks questions such as "What is the probability of the product (or market) going up 0.618 standard deviations?" and "What percentage of the time does it go up that much?" He also asks questions about the directional behavior of the market and at what price the product (or market) is likely to take off in one direction or the other.
Mr. O'Sullivan's neural networks output several different things such as predicted prices, limits, and directional thrust. One neural network outputs the probability of a certain price occurring the next time period. Another neural network produces best stop price and best target price for long and short positions. Other neural networks produce directional indicators for three market energies. Another predicts the level at which the market is likely to take off.
In one design, the network is given various market conditions as input. The training output is the likelihood of various changes in price. For example, his neural network is told during training that, given similar market conditions, the closing price goes up at least 0.313 standard deviations above the prior day 90% of the time, at least 0.618 deviations 80% of the time, and at least 1 deviation 70% of the time.
An interesting phenomenon of the market is that when a change starts occurring in one direction or the other, there is a point at which it is very likely to continue moving in that direction for several time periods. Once a price reaches that level, there is a reduced risk to buy or sell (whichever is appropriate). Mr. O'Sullivan calls the network that predicts this price level his Risk Barometer network. He uses all the neural networks trained for a specific market when making decisions. For example, if the long term trend is up, the Fast Movement network is a large positive number, his Risk Barometer says 233.092, and the NYSE is at 250, it could indicate an overreacted market that will reverse itself soon.
Probability if...UP if...DOWN
85% 231.538 231.163
70% 231.791 230.909
60% 232.316 230.383
50% 233.675 229.025
40% 233.700 229.000
For Trades: Long buy Short sell
best stop = 230.708 231.992
best target = 232.054 230.646
Directional Indicators:
Trend Reaction Fast Movement Risk Barometer
Long Term 0.5066 21.499 -1.329 233.092
Medium Term -7.2280 18.580 8.387 227.643
Short Term 10.7250 4.243 3.377 229.450
This fella used the network to his advantage so that he could make prediction in the stock market, if it was going up or down and it helped him find the best places for his money. This is a great thing to have if you can narrow the field down and use the statistical information into usable helpful information.
Honda's efforts to stay on top
Hondas effort to achieve a competitive advantage through strategy implementation has paid off. Honda has grown all aspect of its organization in the past years. Sales are up in motorcycles, automobiles, finance and power products. Honda has made it a point to grow its organization toward the future with its production of robots and other futuristic devices and they fulfilled that promise. Honda has also increased the number of employees that they employ to manufacture their products. Hondas market share has also went up against it competitors due to the fact of its leader motivating the organization to move forward. Honda consumer image has also made a dramatic increase since the economy has gone down in the past years. People are taking to the idea that Honda makes a superior product to its competitors in the aspect of longevity, reliability and resale value. In the global market Honda is on the rise in almost every aspect. Honda has a bright future ahead of them in the global market if they can stay on the forefront of technology and keep their brand image secure.
Strategic leadership on honda
Honda has a very key group of leaders inside of its organization. These leaders have made Honda what it is to this day. All these leaders had a vision of what direction they thought the company should have moved in and they have moved the organization that way very effectively. The first aspect of the leaders in Honda is that they all have the vision of what Honda is moving forward to. These leaders are in the process of designing and moving Honda in the way of the future. Honda is always in the pursuit of excellence in everything they do this stems mostly from the organizational leaders. The leaders in Honda are very proven self motivated people that push the organization to new heights with every idea. Most of these leaders are organizational leaders meaning that they all hold management positions inside of the organization. Most of these leaders are held to such high standard because of their personal bases power; this is that their personality and behavior motivate people to do their best and to come up with new ideas. Honda is a very proven company with many proven leader and this shows in everything that they produce.
Organizational Structure on honda
Honda has a very tall structure inside of their organization. Honda tries to spread the control of their organization evenly over all of their departments. Honda feels that no one department should have enough power to run the company. The executive council is at the top of Hondas organizational structure. The council supervises the company and the direction that it is going and makes sure that the company stays on track with the overall vision of the company. The decisions the council makes are trying to maintain that the company keep making a high quality product and keep innovating without growing too much to become too complex. The main goal of Honda is to make a good high quality product that people think gives them safety and comfort. This is what the council bases every decision off of. Honda also has a good horizontal lay out of their organization. They have the motorcycle operations, automobile operations, power products operations, customer service operations, production operations, purchasing operations, business support operations, and business management operations. These are laid out so that there is very little distance between top management and the lower level employees. Honda does a very good job with their organization, on making sure that everything is ran as planned and that nothing gets out of line with the way that it is suppose to be. Honda is also a very centralized organization, with several layers of management that control the company by maintaining a high level of authority, which is the power to make decisions concerning business activities. Honda focuses on top-down management, whereby executives at the top communicate by telling middle managers, who then tell first-level managers, who then tell the staff what to do and how to do it. Honda is a formulized organization as well, they have rules and procedures that are written out and enforced along with regulations. These rules and regulation are enforced inside of the organization and are followed by every employee no matter their status in the company.
Strategic Control on honda
Starting with business execution, Honda has established a system for operating its organizational units that reflects its fundamental corporate philosophy. Honda has separate headquarters that have been set up for each region, business, and function, and a general manager from the Board of Directors or an operating officer has been assigned to each headquarters and main division. In addition, the Executive Council deliberates important matters concerning management, and regional operating boards deliberate important matters concerning management of their respective regions. The result is a system that functions effectively and efficiently, and addresses the needs of customers and societies around the world in a swift and appropriate manner. The strategies from Honda motors are formulated and top managers set goals, and these goal are evaluated against predetermined figures that Honda feel that they can reach. Honda always has the mind set of “are we doing the right things for our customers” and Honda strives to” do things right the first time”. These two quotes are the back bone of Honda motors and their strategic control that they put forth toward their automobiles
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