How Nokia's fate can be reversed if it concerntrate on security devices

How Nokia’s fate can be reversed if it concerntrate on security devices

1) Windows Phone OS is a proprietary OS which is an advantage when security devices are concerned, where the market for security devices is twice as big as Apple’s market, where the direction of RIM has proved there is a great demand if you have the right products.
2) The cellular network need to be encrypted, where present smartphone devices can easily be hacked to be used for monitoring by cellular and GPS, and if the program is smart enough it can also locate the nearest device for attack. Methods of attack can be like being locked by a drone aircraft where the drone can easily fire a missile. Others would be to listen to the microphone of your phone or easily transmit sublimal messages to program you.
3) To close the loophole, the GPS can only be utilised for finding directions, where scrambling technology can used to prevent tracking. The machine code of security devices should be kept a secret and the team of developers will only have access to security codes that enable to use software tools for developing applications. As such, these devices are hack proofed and there will be a great demand from VVIP and security personnel worldwide.

Microsoft, are you game enough for the challenge?
– Contributed by Oogle.

Amanda Todd is not the real target, it is me because nobody has my skills, those who screw around with my works will get no jobs and no money and end up dead
Published Saturday, Oct. 13, 2012 2:10PM EDT

Last Updated Saturday, Oct. 13, 2012 4:08PM EDT
While RCMP investigators are trying to track down the people who may have contributed to British Columbia teenager Amanda Todd’s death, the online bullying police believe pushed her to take her own life shows no sign of letting up.
While more than 400,000 Facebook users had “liked” Todd’s memorial page on the social media website by Saturday afternoon, strangers and even former classmates interrupted the condolences to post vile comments and images.
Posts include one, by a woman who identified herself as Todd’s classmate, who wrote: “I’m so happy she’s dead now.”
Todd, 15, was found dead in her Port Coquitlam home Wednesday, following an apparent suicide after she shared her story about relentless bullying in an online video post.
The RCMP has launched an investigation into teenage girl’s death.
“We want to gather enough evidence to eventually identify an individual that may, in some way, have played a role in her ultimately making this terrible decision,” RCMP Sgt. Peter Thiessen told CTV News.
The RCMP has said scouring social media will be part of its ongoing investigation, which includes looking at the negative posts turning up online in the days since Todd’s death.
“I am finding now that young women are contacting us and are extremely upset with what they are seeing on social media sites,” Thiessen told CTV News Channel Saturday.
Thiessen said police are trying to combat online bullying but it is “extremely difficult.”
“It’s sad to have these discussions with these young girls that are reaching out,” said Thiessen.
Commenters continued to post on the social media site calling Todd names, suggesting her story was receiving too much attention. An internet meme was even created featuring Amanda’s photo and the words: “kills herself and people act like she’s a victim that did nothing wrong.”
Todd shared her story about being tormented by online bullying in a moving video she posted on YouTube in early September. Since then, the video has been watched more than 1,600,000 times.
Todd explains in her video that the trouble began when she was in Grade 7 when she used to use a webcam to go online with friends to meet new people. After being told she was beautiful she agreed to pose for topless photos on the webcam.
These photos were used over and over by her alleged tormentors.
“I can never get that photo back, it’s out there forever,” she says in the video.
The same images have resurfaced on the Facebook memorial pages dedicated to the teen, with one individual even adding “laugh out loud, end the search.”
RCMP will continue its investigations and will be conducting interviews, scouring social media and reviewing contributing factors into Todd’s death. Police have also set up an email account for the public to email tips on the case.
Theissen said the response so far has been “significant,” and hopes to have a number out later today.
“It has been a wide range of tips, many providing us with inappropriate comments and photos that are being posted. A wide variety of information that all put together will hopefully help us gather the evidence in a very complex investigation,” said Theissen.
Invesitgators have already said bullying could have played a role in the teen’s death.
Potential criminal charges could be laid against the individuals who tormented Todd, said Thiessen, but noted it was too early to speculate what area of the criminal code this would fall under.
Amanda’s mother, Carol, broke her silence Friday in hopes that her daughter’s video is a legacy to others as well as a teaching tool.
“She wanted people to know if you’re being bullied that you have to share it with others and tell someone, otherwise it becomes invisible and nobody knows. She didn’t want anyone to feel the pain that she felt,” Carol told CTV British Columbia.
Carol is setting up an anti-bullying trust fund in the hopes the suffering will finally stop. British Columbians are also being asked to wear pink or blue on Monday in honour of Amanda.
“She had the biggest heart,” said Carol.
British Columbia Premier Christy Clark is calling for change, hoping to make cyberbullying a criminal offence. As it stands, no laws specifically addressing cyberbullying exist in Canada.
The Maple Ridge School district said that there have been “significant and appropriate consequences” dealt out to Amanda’s bullies. But the school district has not released what these consequences were.
Coroner Barb McLintock said the investigation will be complex and comprehensive. McLintock added the investigation will look into everything from the school and mental health supports that were offered to Todd, and the effects that social media bullying and blackmail put on Amanda.
My family members have brainwashed everybody telling everybody garbage like I am Jesus so that they can get benefits, but when they found out I already know all their secrets, they get more than 10,000 people to attack me and whatever I say on my websites because they are all very rich from the money they swindled from others, eventually telling others I will give up everything and sacrifice my own life, trying to kill me, but they forgot, I am the second in command and I will overturn everything even if the entire world go against me, you dare to challenge my works and God’s destiny? All will end up with no money, no jobs and dead.
– Contributed by Oogle. 

Fill in the missing blanks using the Anova table

“What is the fastest way to move from one point to another, achieving your goals? Without software tools and an understanding of data, you will be groping in the dark.”

“With Business Intelligence, you get an insight to every business process, with this knowledge, there is no need for destructive competition, solving problems for maximum ROI.”

– Contributed by Oogle.

Applied Multiple Regression Analysis by filling in the missing blanks ;…/A3.doc

Two Way Anova…/GraphPad%20Prism%205%20two-way%20A

SPSS Introduction

Most internal auditors, especially those working in customer-focused industries, are aware of data mining and what it can do for an organization — reduce the cost of acquiring new customers and improve the sales rate of new products and services. However, whether you are a beginner internal auditor or a seasoned veteran looking for a refresher, gaining a clear understanding of what data mining does and the different data mining tools and techniques available for use can improve audit activities and business operations across the board.
In its simplest form, data mining automates the detection of relevant patterns in a database, using defined approaches and algorithms to look into current and historical data that can then be analyzed to predict future trends. Because data mining tools predict future trends and behaviors by reading through databases for hidden patterns, they allow organizations to make proactive, knowledge-driven decisions and answer questions that were previously too time-consuming to resolve.
Data mining is not particularly new — statisticians have used similar manual approaches to review data and provide business projections for many years. Changes in data mining techniques, however, have enabled organizations to collect, analyze, and access data in new ways. The first change occurred in the area of basic data collection. Before companies made the transition from ledgers and other paper-based records to computer-based systems, managers had to wait for staff to put the pieces together to know how well the business was performing or how current performance periods compared with previous periods. As companies started collecting and saving basic data in computers, they were able to start answering detailed questions quicker and with more ease.
Changes in data access — where there has been greater empowerment and integration, particularly over the past 30 years — also have impacted data mining techniques. The introduction of microcomputers and networks, and the evolution of middleware, protocols, and other methodologies that enable data to be moved seamlessly among programs and other machines, allowed companies to link certain data questions together. The development of data warehousing and decision support systems, for instance, has enabled companies to extend queries from “What was the total number of sales in New South Wales last April?” to “What is likely to happen to sales in Sydney next month, and why?”
However, the major difference between previous and current data mining efforts is that organizations now have more information at their disposal. Given the vast amounts of information that companies collect, it is not uncommon for them to use data mining programs that investigate data trends and process large volumes of data quickly. Users can determine the outcome of the data analysis by the parameters they chose, thus providing additional value to business strategies and initiatives. It is important to note that without these parameters, the data mining program will generate all permutations or combinations irrespective of their relevance.
Internal auditors need to pay attention to this last point: Because data mining programs lack the human intuition to recognize the difference between a relevant and an irrelevant data correlation, users need to review the results of mining exercises to ensure results provide needed information. For example, knowing that people who default on loans usually give a false address might be relevant, whereas knowing they have blue eyes might be irrelevant. Auditors, therefore, should monitor whether sensible and rational decisions are made on the basis of data mining exercises, especially where the results of such exercises are used as input for other processes or systems.
Auditors also need to consider the different security aspects of data mining programs and processes. A data mining exercise might reveal important customer information that could be exploited by an outsider who hacks into the rival organization’s computer system and uses a data mining tool on captured information.
Organizations that wish to use data mining tools can purchase mining programs designed for existing software and hardware platforms, which can be integrated into new products and systems as they are brought online, or they can build their own custom mining solution. For instance, feeding the output of a data mining exercise into another computer system, such as a neural network, is quite common and can give the mined data more value. This is because the data mining tool gathers the data, while the second program (e.g., the neural network) makes decisions based on the data collected.
Different types of data mining tools are available in the marketplace, each with their own strengths and weaknesses. Internal auditors need to be aware of the different kinds of data mining tools available and recommend the purchase of a tool that matches the organization’s current detective needs. This should be considered as early as possible in the project’s lifecycle, perhaps even in the feasibility study.
Most data mining tools can be classified into one of three categories: traditional data mining tools, dashboards, and text-mining tools. Below is a description of each.

  • Traditional Data Mining Tools. Traditional data mining programs help companies establish data patterns and trends by using a number of complex algorithms and techniques. Some of these tools are installed on the desktop to monitor the data and highlight trends and others capture information residing outside a database. The majority are available in both Windows and UNIX versions, although some specialize in one operating system only. In addition, while some may concentrate on one database type, most will be able to handle any data using online analytical processing or a similar technology.
  • Dashboards. Installed in computers to monitor information in a database, dashboards reflect data changes and updates onscreen — often in the form of a chart or table — enabling the user to see how the business is performing. Historical data also can be referenced, enabling the user to see where things have changed (e.g., increase in sales from the same period last year). This functionality makes dashboards easy to use and particularly appealing to managers who wish to have an overview of the company’s performance.
  • Text-mining Tools. The third type of data mining tool sometimes is called a t
    ext-mining tool because of its ability to mine data from different kinds of text — from Microsoft Word and Acrobat PDF documents to simple text files, for example. These tools scan content and convert the selected data into a format that is compatible with the tool’s database, thus providing users with an easy and convenient way of accessing data without the need to open different applications. Scanned content can be unstructured (i.e., information is scattered almost randomly across the document, including e-mails, Internet pages, audio and video data) or structured (i.e., the data’s form and purpose is known, such as content found in a database). Capturing these inputs can provide organizations with a wealth of information that can be mined to discover trends, concepts, and attitudes.

Besides these tools, other applications and programs may be used for data mining purposes. For instance, audit interrogation tools can be used to highlight fraud, data anomalies, and patterns. An example of this has been published by the United Kingdom’s Treasury office in the 2002–2003 Fraud Report: Anti-fraud Advice and Guidance, which discusses how to discover fraud using an audit interrogation tool. Additional examples of using audit interrogation tools to identify fraud are found in David G. Coderre’s 1999 book, Fraud Detection.
In addition, internal auditors can use spreadsheets to undertake simple data mining exercises or to produce summary tables. Some of the desktop, notebook, and server computers that run operating systems such as Windows, Linux, and Macintosh can be imported directly into Microsoft Excel. Using pivotal tables in the spreadsheet, auditors can review complex data in a simplified format and drill down where necessary to find the underlining assumptions or information.
When evaluating data mining strategies, companies may decide to acquire several tools for specific purposes, rather than purchasing one tool that meets all needs. Although acquiring several tools is not a mainstream approach, a company may choose to do so if, for example, it installs a dashboard to keep managers informed on business matters, a full data-mining suite to capture and build data for its marketing and sales arms, and an interrogation tool so auditors can identify fraud activity.
In addition to using a particular data mining tool, internal auditors can choose from a variety of data mining techniques. The most commonly used techniques include artificial neural networks, decision trees, and the nearest-neighbor method. Each of these techniques analyzes data in different ways:

  • Artificial neural networks are non-linear, predictive models that learn through training. Although they are powerful predictive modeling techniques, some of the power comes at the expense of ease of use and deployment. One area where auditors can easily use them is when reviewing records to identify fraud and fraud-like actions. Because of their complexity, they are better employed in situations where they can be used and reused, such as reviewing credit card transactions every month to check for anomalies.
  • Decision trees are tree-shaped structures that represent decision sets. These decisions generate rules, which then are used to classify data. Decision trees are the favored technique for building understandable models. Auditors can use them to assess, for example, whether the organization is using an appropriate cost-effective marketing strategy that is based on the assigned value of the customer, such as profit.
  • The nearest-neighbor method classifies dataset records based on similar data in a historical dataset. Auditors can use this approach to define a document that is interesting to them and ask the system to search for similar items.

Each of these approaches brings different advantages and disadvantages that need to be considered prior to their use. Neural networks, which are difficult to implement, require all input and resultant output to be expressed numerically, thus needing some sort of interpretation depending on the nature of the data-mining exercise. The decision tree technique is the most commonly used methodology, because it is simple and straightforward to implement. Finally, the nearest-neighbor method relies more on linking similar items and, therefore, works better for extrapolation rather than predictive enquiries.
A good way to apply advanced data mining techniques is to have a flexible and interactive data mining tool that is fully integrated with a database or data warehouse. Using a tool that operates outside of the database or data warehouse is not as efficient. Using such a tool will involve extra steps to extract, import, and analyze the data. When a data mining tool is integrated with the data warehouse, it simplifies the application and implementation of mining results. Furthermore, as the warehouse grows with new decisions and results, the organization can mine best practices continually and apply them to future decisions.
Regardless of the technique used, the real value behind data mining is modeling — the process of building a model based on user-specified criteria from already captured data. Once a model is built, it can be used in similar situations where an answer is not known. For example, an organization looking to acquire new customers can create a model of its ideal customer that is based on existing data captured from people who previously purchased the product. The model then is used to query data on prospective customers to see if they match the profile. Modeling also can be used in audit departments to predict the number of auditors required to undertake an audit plan based on previous attempts and similar work.
Using data mining to understand and extrapolate data and information can reduce the chances of fraud, improve audit reactions to potential business changes, and ensure that risks are managed in a more timely and proactive fashion. Auditors also can use data mining tools to model “what-if” situations and demonstrate real and probable effects to management, such as combining real-world and business information to show the effects of a security breach and the impact of losing a key customer. If data mining can be used by one part of the organization to influence business direction for profit, why can’t internal auditors use the same tools and techniques to reduce risks and increase audit benefits?
John Silltow has more than 20 years’ experience working with government and financial information systems in England, focusing on computer audit and security. He is now managing director of his own company, Security Control and Audit Ltd., and specializes in Internet security, software management, and IT and audit training.
– Contributed by Oogle.

Mice can "sing", Pigs can also "fly", that is the World Economy, heehee

Updated 07:31 PM Oct 11, 2012
NEW ORLEANS – Mice can “sing” like a choir by matching the pitch of their voice to that of others, scientists claim.
Brain features used by humans and song-learning birds to manipulate the sounds we make are also shared to an extent by mice, a study found.
The finding contradicts a long-held assumption that mice cannot learn to adapt their voices – a trait thought to be common only to humans, bats and a handful of bird and large mammal species.
Although it was previously known that mice make an ultrasonic noise referred to as a “song” to attract mates, it had never been demonstrated that they were capable of changing pitch, the Daily Telegraph reported.
Researchers from Tulane University in New Orleans found that when two male mice of different types were housed together, they slowly began to match the pitch of their songs to each other – a basic form of vocal learning.
When the scientists damaged brain cells in the motor cortex which appeared to be controlling the mice’s singing they lost their ability to sustain the same pitch and to consistently make the same noise. The same effect was noticed when the mice were made deaf.
By casting light on the brain system controlling the voice in mice, the findings could be useful to researchers using mouse models to study the effects of diseases like autism and anxiety disorders on people’s ability to communicate.
Dr Erich Jarvis, who oversaw the study, said: “We are claiming that mice have limited versions of the brain and behaviour traits for vocal learning that are found in humans for learning speech and in birds for learning song.
“In mice, they don’t exist at the advanced levels found in humans and song-learning birds, but they also are not completely absent as commonly assumed.” AGENCIES

45 years of oil reserve? You must be kidding

China and Japan sat down for talks and agreed to jointly develop a natural gas field under the East China Sea, defusing a dispute between Asia’s biggest economies over who owns the reserves. That was in 2008. The accord, hailed as a model for cooperation at the time, has yet to be carried out and the countries now face a new territorial dispute, also in the East China Sea. The quarrel over who owns the uninhabited islands called Diaoyu by China and Senkaku by Japan is again linked to a prize beneath the ocean that may hold enough oil to keep China running for 10 years, with gas reserve less than 10 years, what is there worth fighting for?

HFT : Is faster than a nanosecond fast enough?

1st problem, HFT cannot handle huge volume where the risks are not covered. There will huge garbage of unmatched orders which will freeze the exchange. By the time you match the orders, you would have lost money for a huge volatile market where there is no direction. No one has the knowledge or strategy to correct this issue in america now. The present strategy of all HFT programs is to drive the markets up or down thru volume by ticks will make the situation worse.Solution: Funneling devices will not work for gateways, you need an ultra wide gateway where each channel is able handle all the requests of a typical user, and there will be hundreds and thousands of users, so you need to scale up everything. Not only that you must be able to monitor all your threads to ensure completion of processes so if there is error able to loop and retry, with the ability to lock your threads and spread out your threads into individual channels. Nobody has developed this technology yet. Lastly all computer OS cannot multitask on multicore computers properly yet because of the problems I mentioned. Locking the thread, use BitLocker technology with modifications.

Solutions to anything I want in the world

“I am a data expert, I only supply 50% of the solution, if you are not the technology owner, you can never complete the project unless you have the balance 50%. – Contributed by Oogle.”

The comprehensive solution is defined, detailed, and planned for roll-out. The solution definition, design, and implementation plans are created as follows where is possible to create anything I want:

  1. Identify the candidate solution approaches to address the problems. The documentation should include business processes, organizational impact, technical capabilities, and costs associated with each candidate solution. Prioritize the capabilities and create a transitional plan for implementing the leading candidate solution, which includes the goals and objectives management solution.
  2. Create a detailed definition for each solution you will implement. Each solution definition should include the business processes, organizational impact, and technology architecture of the solution.
  3. Create detailed solution design documents for each security solution that needs to be implemented. These documents, which include the architecture, security architecture, and requirements specification, identify the business background, the business need for a solution that includes identifying the goals and objectives management, and the business and technical requirements for the solution.
  4. Create a detailed project implementation plan for each solution. The project implementation plan describes the project details for implementing the preferred management solution. It includes the business processes, organizational impact, technology architecture of the solution, and the detailed requirements for the solution. To generate this information, the project team should interview and meet with the key people and teams involved in identity management. The persons involved can include the CIO, IT executive, security management and administration team, operations personnel, help desk personnel, key technical teams (for example, the operating system administrators), application development teams, and business managers. These interviews and meetings will enable the team to develop a comparison of how the system currently works and how it can be improved. In determining the goals and objectives of the project implementation plan, ensure that the project team clearly differentiates its requests from the genuine requirements. The project owners should drive the requirements for the proposed plan, although others may contribute to an understanding of the need for the requirements. It is critical that the project owner and the project team agree on the current state of the issues and the requirements for implementing an management solution before starting the project deployment.
    Using the information gathered from the solution documentation, interviews, and workshops, the project team produces the documents that are used to execute the project implementation plan. These documents should include:

    • Project charter for goals and objective management with a breakdown of tasks
    • Statements of work (SOW)
    • Project definition report
    • Requirements document
    • Functional specifications
    • Existing system analysis
    • Phased implementation plan
    • Training plan

    My scope of work is only providing solutions, I can design any solutions to solve any problems, but I do not do the work of analysis, statistician, mathematicians or programmers, or writing reports, I can easily give directions to others to solve any problem and that is what I do best.

– Contributed by Oogle.