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Messages - seraj

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Faculty Sections / FSIT exam
« on: April 20, 2017, 10:51:38 AM »
Final Exam of FSIT is going on. Just had One duty of ENG113. Students were good- no talking, no cheating- all modest.

Teaching & Research Forum / Software Defined Environment
« on: November 28, 2015, 07:11:25 AM »
A term coined by IBM for its "software-defined everything" vision. The company's Software-Defined Environments (SDE) group is the latest evolution of what first began as the Application, Integration and Middleware group inside the IBM Software group.
According to this eWeek article, IBM says "a Software-Defined Environment (SDE) optimizes the entire computing infrastructure – compute, storage and network resources – so that it can adapt to the type of work required. In today's environment, resources are assigned manually to workloads; that happens automatically in a SDE."
By dynamically assigning workloads to IT resources based on a variety of factors, including the characteristics of specific applications, the best-available resources, and service-level policies, a software-defined environment can deliver continuous, dynamic optimization and reconfiguration to address infrastructure issues.

Teaching & Research Forum / Augmented reality
« on: November 28, 2015, 07:10:38 AM »
Abbreviated as AR, Augmented Reality is a type of virtual reality that aims to duplicate the world's environment in a computer. An augmented reality system generates a composite view for the user that is the combination of the real scene viewed by the user and a virtual scene generated by the computer that augments the scene with additional information. The virtual scene generated by the computer is designed to enhance the user's sensory perception of the virtual world they are seeing or interacting with. The goal of Augmented Reality is to create a system in which the user cannot tell the difference between the real world and the virtual augmentation of it. Today Augmented Reality is used in entertainment, military training, engineering design, robotics, manufacturing and other industries.

Teaching & Research Forum / Near Field Communication
« on: November 28, 2015, 07:09:50 AM »
Abbreviated as NFC, Near Field Communication is a standards-based, short-range wireless connectivity technology that enables convenient short-range communication between electronic devices. The underlying layers of NFC technology are ISO, ECMA, and ETSI standards. NFC applications can be split into the following  four basic categories:

Touch and Go: Applications such as access control or transport/event ticketing, where the user needs only to bring the device storing the ticket or access code close to the reader. Also, for simple data capture applications, such as picking up an Internet URL from a smart label on a poster.
Touch and Confirm: Applications such as mobile payment where the user has to confirm the interaction by entering a password or just accepting the transaction.

Touch and Connect: Linking two NFC-enabled devices to enable peer to peer transfer of data such as downloading music, exchanging images or synchronizing address books.

Touch and Explore: NFC devices may offer more than one possible function. The consumer will be able to explore a device's capabilities to find out which functionalities and services are offered.

Short for Structured Systems Analysis and Design Method, a set of standards developed in the early 1980s for systems analysis and application design widely used for government computing projects in the United Kingdom. SSADM uses a combination of text and diagrams throughout the whole life cycle of a systemdesign, from the initial design idea to the actual physical design of the application.
SSADM uses a combination of three techniques:

Logical Data Modeling -- the process of identifying, modeling and documenting the data requirements of the system being designed. The data is separated into entities (things about which a business needs to record information) and relationships(the associations between the entities.

Data Flow Modeling -- the process of identifying, modeling and documenting how data moves around an information system. Data Flow Modeling examines processes (activities that transform data from one form to another), data stores (the holding areas for data), external entities (what sends data into a system or receives data from a system, and data flows(routes by which data can flow).

Entity Behavior Modeling -- the process of identifying, modeling and documenting the events that affect each entity and the sequence in which these events occur.

Each of these three system models provides a different viewpoint of the same system, and each viewpoint is required to form a complete model of the system being designed. The three techniques are cross-referenced against each other to ensure the completeness and accuracy of the whole application.

SSADM application development projects are divided into five modules that are further broken down into a hierarchy of stages, steps and tasks:
Feasibility Study-- the business area is analyzed to determine whether a system can cost effectively support the business requirements.
Requirements Analysis-- the requirements of the system to be developed are identified and the current business environment is modeled in terms of the processes carried out and the data structures involved.

Requirements Specification-- detailed functional and non-functional requirements are identified and new techniques are introduced to define the required processing and data structures.

Logical System Specification-- technical systems options are produced and the logical design of update and enquiry processing and system dialogues.

Physical Design -- a physical database design and a set of program specifications are created using the logical system specification and technical system specification.

Unlike rapid application development, which conducts steps in parallel, SSADM builds each step on the work that was prescribed in the previous step with no deviation from the model. Because of the rigid structure of the methodology, SSADM is praised for its control over projects and its ability to develop better quality systems.

Teaching & Research Forum / Web Analytics
« on: November 28, 2015, 07:06:07 AM »
Web analytics is a generic term meaning the study of the impact of a website on its users. Ecommerce companies and other website publishers often use Web analytics software to measure such concrete details as how many people visited their site, how many of those visitors were unique visitors, how they came to the site (i.e., if they followed a link to get to the site or came there directly), what keywords they searched with on the site's search engine, how long they stayed on a given page or on the entire site and what links they clicked on and when they left the site.

Web Analytics Software
Web analytic software can also be used to monitor whether or not a site's pages are working properly. With this information, Web site administrators can determine which areas of the site are popular and which areas of the site do not get traffic. Web analytics provides these site administrators and publishers with data that can be used to streamline a website to create a better user experience.

Teaching & Research Forum / Big data analytics
« on: November 28, 2015, 07:05:18 AM »
Big data analytics refers to the process of collecting, organizing and analyzing large sets of data (called big data) to discover patterns and other useful information. Big data analytics can help organizations to better understand the information contained within the data and will also help identify the data that is most important to the business and future business decisions. Analysts working with big data basically want the knowledge that comes from analyzing the data.

The Challenges of Big Data Analytics
For most organizations, big data analysis is a challenge. Consider the sheer volume of data and the different formats of the data (both structured and unstructured data) that is collected across the entire organization and the many different ways different types of data can be combined, contrasted and analyzed to find patterns and other useful business information.
The first challenge is in breaking down data silos to access all data an organization stores in different places and often in different systems. A second big data challenge is in creating platforms that can pull in unstructured data as easily as structured data. This massive volume of data is typically so large that it's difficult to process using traditional database and software methods.

Big Data Requires High-Performance Analytics
To analyze such a large volume of data, big data analytics is typically performed using specialized software tools and applications for predictive analytics, data mining, text mining, forecasting and data optimization. Collectively these processes are separate but highly integrated functions of high-performance analytics. Using big data tools and software enables an organization to process extremely large volumes of data that a business has collected to determine which data is relevant and can be analyzed to drive better business decisions in the future.

Examples of How Big Data Analytics is Used Today
As the technology that helps an organization to break down data silos and analyze data improves, business can be transformed in all sorts of ways. According to Datamation, today's advances in analyzing Big Data allow researchers to decode human DNA in minutes, predict where terrorists plan to attack, determine which gene is mostly likely to be responsible for certain diseases and, of course, which ads you are most likely to respond to on Facebook.
he business cases for leveraging Big Data are compelling. For instance, Netflix mined its subscriber data to put the essential ingredients together for its recent hit House of Cards, and subscriber data also prompted the company to bring Arrested Development back from the dead.
Another example comes from one of the biggest mobile carriers in the world. France's Orange launched its Data for Development project by releasing subscriber data for customers in the Ivory Coast. The 2.5 billion records, which were made anonymous, included details on calls and text messages exchanged between 5 million users. Researchers accessed the data and sent Orange proposals for how the data could serve as the foundation for development projects to improve public health and safety. Proposed projects included one that showed how to improve public safety by tracking cell phone data to map where people went after emergencies; another showed how to use cellular data for disease containment.

The Benefits of Big Data Analytics
Enterprises are increasingly looking to find actionable insights into their data. Many big data projects originate from the need to answer specific business questions. With the right big data analytics platforms in place, an enterprise can boost sales, increase efficiency, and improve operations, customer service and risk management.

Webopedia parent company, QuinStreet, surveyed 540 enterprise decision-makers involved in big data purchases to learn which business areas companies plan to use Big Data analytics to improve operations. About half of all respondents said they were applying big data analytics to improve customer retention, help with product development and gain a competitive advantage.
Notably, the business area getting the most attention relates to increasing efficiencies and optimizing operations. Specifically, 62 percent of respondents said that they use big data analytics to improve speed and reduce complexity.

Teaching & Research Forum / Data mining
« on: November 28, 2015, 07:03:42 AM »
Data mining requires a class of database applications that look for hidden patterns in a group of data that can be used to predict future behavior. For example, data mining software can help retail companies find customers with common interests.
The phrase data mining is commonly misused to describe software that presents data in new ways. True data mining software doesn't just change the presentation, but actually discovers previously unknown relationships among the data.
Data mining is popular in the science and mathematical fields but also is utilized increasingly by marketers trying to distill useful consumer data from Web sites.

Teaching & Research Forum / BIG data
« on: November 28, 2015, 07:02:38 AM »
Big data is a buzzword, or catch-phrase, used to describe a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques. In most enterprise scenarios the volume of data is too big or it moves too fast or it exceeds current processing capacity. Despite these problems, big data has the potential to help companies improve operations and make faster, more intelligent decisions.

Big Data: Volume or a Technology?
While the term may seem to reference the volume of data, that isn't always the case. The term big data, especially when used by vendors, may refer to the technology (which includes tools and processes) that an organization requires to handle the large amounts of data and storage facilities. The term big data is believed to have originated with Web search companies who needed to query very large distributed aggregations of loosely-structured data.

An Example of Big Data
An example of big data might be petabytes (1,024 terabytes) or exabytes (1,024 petabytes) of data consisting of billions to trillions of records of millions of people—all from different sources (e.g. Web, sales, customer contact center, social media, mobile data and so on). The data is typically loosely structured data that is often incomplete and inaccessible.
Big Data and Types of Business Datasets
When dealing with larger datasets, organizations face difficulties in being able to create, manipulate, and manage big data. Big data is particularly a problem in business analytics because standard tools and procedures are not designed to search and analyze massive datasets.
As research from Webopedia parent company QuinStreet demonstrates, big data initiatives are poised for explosive growth. QuinStreet surveyed 540 enterprise decision-makers involved in big data and found the datasets of interest to many businesses today include traditional structured databases of inventories, orders, and customer information, as well as unstructured data from the Web, social networking sites, and intelligent devices.
This data, when captured, formatted, manipulated, stored, and analyzed can help a company to gain useful insight to increase revenues, get or retain customers, and improve operations.

Be a Leader / How Sabur Khan became Entrepreneur
« on: November 23, 2015, 08:28:34 PM »
Mr. Md. Sabur Khan as a person is a very simple and known absolutely as a man of pleasant personality. He is workaholic and leading his company like an extensive transformation. He kept his business and product line very specific and recent success ratio is very much cautionary tale for others. Today he is leading the largest education network and trusted ICT conglomerate in Bangladesh. His recent strategy is to “Going Global” and already started operation in Malaysia, Dubai, UK, USA and soon going to step in other possible regions of the world. His journey was not easy but his devotion in achieving his dream brought him the success.

The start of the dream:

In his own word “the secret of becoming entrepreneur is my “dream”. I really wanted to be a successful entrepreneur. I wanted it from my heart. I never thought whether my decision is right or wrong. But I paid my effort to make it right decision”. One must have big dream, high ambition, strong commitment, tireless effort and that will take him to his destination and that is the secret of today’s Daffodil”

He also added, “there was another reason which supported my dream and that is I was always late in the morning. While taking decision of my career I never counted the problems to achieve my goal rather I accepted it and took it as challenge to overcome the problems.”

Change, Do or Die:

It was not so easy decision for Mr. Khan to become entrepreneur during his time. He started with ICT Business and on that time ICT was not at all focused in Bangladesh. But he knew that someday ICT will be effective means for Business and Day to Day life. He took the challenges. Today he is named among those few persons who contributed silently to develop the ICT sector in Bangladesh and Bangladesh is called the emerging tiger in ICT Arena.

He didn’t confined his business arena only in PC marketing rather he brought innovation, extended its business scope. Introduced Bangladesh Brand and brought other products and attached ICT services in his business. The simple logic here is we cannot keep doing same thing and expect success all times. Rather we have to do different, add values and know the customers and market. He started ICT Training Center during the year 1997 to develop the human resources and later he focused on Education sector as well.

Listen to consumer:

Mr. Khan always welcomed to hear the problem in the business process and this helped him to find solution, develop the product and its services and know the competitors. Also helped him to introduce new service features and adding values to a great extent. This was necessary and helped to build a better business and better relationships.

Accepting the truth:

Taking right decision is a matter of huge challenge and to take right decision in business it is always required to have adequate data from every sector ie, consumer, shareholder, market, employee, industry, competitors, trends and etc. Also sometimes we get opportunities and we need to act very quickly here. So we have to take the challenges. Mr. Khan always loves to take challenges and keeps trust on his peoples and accept the result whether it works or fails.

Sense of Responsibility:

Mr. Khan believes that a good entrepreneur feel a deep sense of responsibility for organization. The responsibilities are for the business/services, peoples in it and for the nation. We must have the ethics that whatever we do must do good and whatever decision we take must justify its consequences among others and organizations future. This is a pretty personal process. When you’re doing what you love and it’s working, you don’t get tired working what other people might consider long hours or crazy schedules. It’s just fun. It’s energizing.

According to Mr. Khan, if you are running a public company, you’ve got to deliver short-term results and you have to think about its future more than your life.

Food / How to Cook a Snake
« on: November 23, 2015, 08:26:28 PM »

Whether you've bought fresh snake meat at a market where snake is a popular dish, or you've skinned a snake yourself specifically for dinner, you won't find a snake meat recipe in the average cookbook. Snake is somewhere between chicken and fish in texture and flavor, and may be made to seem like either. This article will outline a recipe which is also suitable for bluegill, so the resulting meat will be reminiscent of a small lake fish.

1 snake, obtained from a trusted source or familiar environment; avoid the risk of eating a snake that has eaten a poisoned rodent
1 box of cornbread mix
1/2 c egg whites
Splash black pepper
1/2" oil (depends on pan size)

1. Cut off the head, strip off the skin, and remove the guts of the dead snake.
2. Rinse the meat, and cut it into pieces with a sharp knife or poultry shears. Make the cuts between and at the same angle as the ribs to avoid cutting the ribs. If the ribs are severed, they may be difficult to remove from the meat after it is cooked. Some people prefer to soak the ready-to-cook snake pieces in saltwater for a day or two to remove any remaining blood or "gaminess" from the meat.
3. Dip the segments in a bit of egg white (milk would also do) before dredging them in a pepper and sweet cornmeal mix (or cornbread mix with some extra black pepper). Shake off the excess.
4. Heat about 3/4" (2cm) of canola, vegetable, or peanut oil in a heavy frying pan until quite hot. Add the snake pieces one at a time to avoid from dropping the temperature in the pan too quickly. Use tongs to keep your fingers away from the sizzling hot oil, watch for dangerous splatters, and use a screen if necessary to prevent a mess. Turn the snake pieces just as the batter begins to turn golden - by the time it starts to brown the snake will be overcooked. There's not much meat on the bones, and the muscles are thin and lean.
5. Drain and cool. Remove the snake pieces before they're quite done - they'll continue to cook after removal from the pan - and set them on paper towels to drain and cool.
6. Serve your fried snake bits warm, and provide napkins - this is finger food. Accompany with most anything you'd serve with fried fish.
7. Eat the snake meat. There should be a line of muscle along either side of the spine; this is the thickest piece of meat on the snake's body. The ribs are quite firmly attached to the spine, so scrape your teeth over them firmly to remove the rest of the meat from the ribs.

Overcooking (which can be seen in these pictures) will result in the snake meat tasting fried, but getting it just right will result in a nutty flavor.
If you've still got more batter, chop up some veggies, dip them in the egg whites and/or milk, dredge in batter, and fry.
You can also just mix the liquid into the batter and fry hush puppies.
Snake meat gets most of its flavor from the way it is spiced and prepared. Cooking methods used for chicken will produce snake that tastes like chicken.

Remember to cook the snake to at least 144 °F (62 °C) to kill all bacteria.
Wash your hands as you would when handling any kind of raw meat.
Avoid eating the head of the snake, as this is where the venom is located if the snake happens to be a venomous species. The body of a snake does not contain venom and is safe for consumption.
It is illegal to kill several kinds of snakes (especially venomous ones). Some are protected by federal law, and you may face jail time if you kill a protected snake.
If hunting for snakes in the wild for this or other recipes use extreme caution and care.

Cricket / Re: মাশরাফির অন্য লড়াই
« on: November 23, 2015, 08:11:25 PM »
hero is always a hero 8)

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