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SBU Blog

English Learning Through Movie

Dr Ria Mukherjee

Assistant Professor, Department of English SBU, Ranchi

FUN LEARNING GUIDE FROM “MICKY MOUSE” TO “MATRICS”

Conceivably you’re wondering if you can learn English with movies.

After all, watching movies is just an entertainment for you, right? So, the question is how can you learn while having fun with the movie instead of with textbooks?

Here I believe it facilitates and makes our work easy through fun learning, and I definitely recommend learning English language this way.

You’ll get to learn real English… not textbook English based on real life situations.

The English you learn through textbooks or in ELT class is not what you’ll hear people say in your surroundings. For example, in beginner English classes, you might have learned how to say phrases like “Call it a night” which simply means “Going to Bed”. While these phrases are technically correct but we never use these in real life.

One of the most important aspect of watching movie, you’ll start to learn vocabulary related to the situation, or subject. Difficulty with learning new words is that you can learn what words mean, but not where and how they are used.

Through movies you can hear how things are said, how to express these words with proper voice modulation, intonation etc. This ultimately makes your task easy to remember.

In contrast, the English spoken in movies is very natural. It’s also very close to what you’ll hear if you speak with native English speakers too. This will help improve your spoken English.

Which movie should be watched?

The best part is that you can choose movie of your own interest and current English level, play using movie player, repeat the phrases pausing wherever required, check dictionary immediately.

However, most of the time you might be tempted to switch on subtitles, if so, I would recommend English subtitles so that you can read while listening.

Benefits of watching English movies:

Listening is much more difficult than reading, so when you are learning English, you should do more with listening rather than reading. It is recommended to watch movie with subtitle first then without subtitle. You can hear English used in a very natural way. It can also benefit to enhance your pronunciation, vocabulary etc. Watching English movies will help you understand how to use all the knowledge you have learnt in everyday situations.

It is advisable to watch English movies in original language rather than dubbing! As a learner you also get to know about expression of a particular sentence from the movie that you watch


Disaster Management using Remote sensing Technology

Prof. Moutoshi Saha

Assistant Professor, Department of Civil Engineering SBU, Ranchi

Remote sensing is the science of collecting information about the object, area or phenomenon without making any physical contact with the object. Humans with noses, eyes and ears are constantly smelling, sensing and hearing things from their surroundings. So they also have the quality of remote sensing.

Remote sensing detects the features of the earth’s surface by analyzing and interpreting the multispectral electromagnetic radiations emitted or reflected by the surface of the earth. For analyzing these different wavelengths, scanners are used, which is situated at various platforms like aircrafts, satellites etc.

GIS: Geography has played a vital role and develops civilizations from Stone Age to modern days. The discoveries, planning for better living and in fact the modern civilization has achieved much by using the knowledge of abstract geography.

GIS refers to the system used to define and characterize the earth and other geographical features over it, for the purpose of analyzing spatially referenced information. The information acquired is used to solve real-life problems. The use of spatial data in real life involves data acquisition, storage, manipulation, maintenance and output.

Disaster management: A Disaster is a situation in which the community is incapable of coping. It is a natural or human-caused event which causes intense negative impacts on people, goods, services and/or the environment, exceeding the affected community’s capability to respond.

Mitigation of natural disasters can be successful only when detailed knowledge is obtained about the expected frequency, character, and magnitude of hazardous events in an area. Many types of information that are needed in natural disaster management have an important spatial component. Spatial data are data with a geographic component, such as maps, aerial photography, satellite imagery, GPS data, rainfall data, borehole data etc. We now have access to information gathering and organising technologies like remote sensing and geographic information systems (GIS), which have proven their usefulness in disaster management. First of all, remote sensing and GIS provides a data base from which the evidence left behind by disasters that have occurred before can be interpreted, and combined with other information to arrive at hazard maps, indicating which areas are potentially dangerous. Remote sensing data, such as satellite images and aerial photos allow us to map the variabilities of terrain properties, such as vegetation, water, and geology, both in space and time. Satellite images give a synoptic overview and provide very useful environmental information, for a wide range of scales, from entire continents to details of a few meters.

Remote sensing allows monitoring the event during the time of occurrence while the forces are in full swing. GIS is used as a tool for the planning of evacuation routes, for the design of centers for emergency operations, and for integration of satellite data with other relevant data in the design of disaster warning systems In the disaster relief phase, GIS is extremely useful in combination with Global Positioning Systems (GPS) in search and rescue operations in areas that have been devastated and where it is difficult to orientate. Remote sensing can assist in damage assessment and provide a quantitative base for relief operations. Remote sensing is used to map the new situation and update the databases used for the reconstruction of an area, and can help to prevent that such a disaster occurs again.

One of the main advantages of the use of the powerful combination techniques of a GIS, is the evaluation of several hazard and risk scenarios that can be used in the decision -making about the future development of an area, and the optimum way to protect it from natural disasters. Remote sensing data derived from satellites are excellent tools in the mapping of the spatial distribution of disaster related data within a relatively short period of time. Remote sensing data should generally be linked or calibrated with other types of data, derived from mapping, measurement networks or sampling points, to derive at parameters, which are useful in the study of disasters.


Data Science: Promising Job for the Freshers

Prof. Megha Sinha

Assistant Professor, Department of CSE SBU, Ranchi

Data is everywhere. Infect, the amount of digital data that exist is growing exponentially every year and the changing the way we live. Data Science is basically dealing with this structured or unstructured data. Data science is a field that comprises of everything that is related to data cleansing, preparation, and analysis. In simple term it is the umbrella of techniques used when trying to extract insights and information from data. Data science is a fascinating technology that is rapidly evolving.

Use of the term Data Science is increasingly common, but what does it exactly mean? What skills do you need to become Data Scientist? How are decisions and predictions made in Data Science? What are the skill that you required? These are some of the questions that will be answered further in this blog.

Why learn Data Science?

First let understand what is Data Science? Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data. Data science is considered as oil for the current data world - “most demanded job of the 21th century”. You may think why? Data scientist are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassroom has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientist are scarce and in great demand. As a data scientist you will be required to understand the business problem, design and analysis, collect and format the required data, apply proper algorithm and techniques using the correct tools, and finally make recommendations backed by data.

You can gain in depth knowledge of data Science by taking Master Degree and several certification courses are offered by many top universities. Some popular online certifications courses like Simplilearn’sDataScience with Phython #DataScienceWithR #DataScienceCourse #BusinessAnalysis on Machine Learning etc are available.

Who is a Data Scientist?

Data science is super-hot topic and is the most promising job of 2019.But what do you need to become a data scientist? So, to answer your question, here is a study on 1001 LinkedIn resume of people who are currently working as data scientist it is interesting to see where they come from and what skills they’re using in their day to day activity. The main message that came out on study last year and this year, is that if you have the skill base that makes the data scientist, you can be a data scientist. It will be interesting to see how data science profession changes in the next 2-5 years.

What should be the educational background to be a data scientist?

Skill that you require for a data scientist are as below

  • You should be good with maths and statistics
  • You should be good with handling data(Data Extraction ,Transformation, Loading )
  • Knowledge of ETL tools such as Informatic- PowerCenter, IBM-Infosphere Information Server, alteryx. Mocrosoft- sql server Integrated Servises (SSIS), SAS, SAP etc.
  • You should be comfortable in handling data from different sources and in different formats
  • You must have excellent knowledge of SQL
  • In Bonus to have, knowledge of Big data tools and MongoDB.
  • You should be expert in Analyzing and Visualizing in data.
  • You must have good interpersonal and storytelling skills/

Looking for a few academic data science papers to study? Here are a few I have found interesting. May follow the link below https://101.datascience.community/


CSR spending by Companies should not be mandatory

Prof. Rahul Vats

Ministry of Corporate Affairs has refrained from implementing the controversial Corporate Social Responsibility (CSR) amendments in the recently enacted Companies (amendment) Act 2019 while approving the implementation of all other provisions in the amendment law.

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A committee under Injeti Srinivas has recommended that CSR spending should be made tax deductible, and failure to meet the 2% CSR quota should at worst be a civil offence, not a criminal offence. Earlier it was three-year jail term which was too harsh step.

This will change the CSR approach to one that relies on incentives rather than punishments, on carrots rather than sticks. The Committee proposed that CSR should not become a means of using corporations to fund what the government should be funding.

The panel also suggested CSR spending should be eligible for tax deductions and companies be allowed to carry forward unspent balances for three-to-five years.

As per the companies act 2013, all companies which were above a defined threshold of net worth, or revenue or profits, were required to spend 2% of after-tax profit on CSR.

What the new provision suggests?

According to the new CSR norms under Section 135 of the Companies Act, a company has to earmark a part of its profit for social activities and transfer all unspent amount to an escrow account if it is an ongoing project.

This account will be opened by the company concerned in a bank and be called the unspent corporate social responsibility account. The CSR expenditure which remains unspent in three years would be transferred to any fund specified in Schedule VII of the Companies Act such as the Swachch Bharat Kosh, the Clean Ganga Fund, and the Prime Minister’s Relief Fund.

CSR: Should be voluntary or mandatory?

As per a recent report of Deccan Herald, there are around 21,000 companies in India which is nearly 2% of all registered companies, are required to comply CSR provisions, but only 11,000 have bothered to. The total spend on CSR by these 11,000 companies is just Rs 13,000 crore, which is approximately 0.4% of the central government’s budget this year.

The mandatory CSR regulations does not make sense. It does not have any logic to make so much regulations and compliance for an act which should be voluntary in the first place.

They become obligations to already stifling companies. The government can encourage this—through tax deductions, public acclamation and moral suasion—but should not force it.


Career planning for University students

Dr. Puja Mishra

Assistant Professor, Department of Commerce & Management SBU, Ranchi

There are numerous university students searching for the right career fit. First step for this is to begin the preparations as early as possible. The key for which is to understand the difference between a job and a career. A job helps to make a living, probably pay the bills and is almost always short term. On the other hand, a career path is based on skills and interests and is typically long term.

Today majority of University Graduates desire to attain the skills required by the employers as getting good grades is not enough for most of them. However, students following the given strategies can be better prepared to promote themselves to employers and plan their career in the desired way.

Self-assessment – Students should take time to identify their skills, values, interest and personality as they can be major influencers in their career choice. This assessment will be helpful in the preparation for resume writing and facing interviews. This can be beneficial even for opting for the internship program.

Strength identification – In this step students need to ask themselves, ‘What are the areas in which they are good?” There are many online assessments that may be helpful in discovering the skills and match them to possible careers.

What do they like to do? – Now that the students have an idea of what they are good at, it’s time to figure out what they might actually enjoy. Students should take some time to reflect on past work or school experiences (which ones did they like, and which ones were less enjoyable?)

Exploring the career options related to the degree – It is not advisable to wait until the graduation to decide about the career. Students should research for career options related to their specialization or program. To help plan their career path, several informational interviews can be conducted with people who work with or hire people in the desired career. They can be asked for guidance so that students can develop themselves as per the requirements of the employers.

Taking help of the career and placement services within the University – Most of the Universities offer assistance in choosing specialization, finding internships, locating employers seeking applicants in specific degree programs, and preparing for jobs. Students can take advantage of the assistance that their University offers to add ‘real world experience’ to the resume.

Participation in career related activities – To make oneself different from other recent graduates, students should start participating in internships, mentoring programs, and other work-based learning experiences. They can even participate in career-related volunteer opportunities, or part-time or summer employment related to their chosen career.

Self-positioning – Students can join a career-related student group, professional associations, or other groups that can help them to build their network, including online career-related groups. When possible, they should choose school projects related to trends and topics in the desired career.

Appreciating the benefits of University – Education always pays off. Gaining education is a way to increase self-earning power and employability throughout the career.

Opting for the correct specialization – Students may be looking for the right University, or maybe they are already in the University of their choice but still forging their academic path. In either case, career goals are often important when considering a specialization. Contacting the University's career services office may also be beneficial.

Using Internet job search – Many websites also offer free career mapping resources. For example, LinkedIn offers an effective Career Explorer tool that helps students and recent graduates map the paths taken by professionals in many different careers. The Career Explorer also features job statistics, relevant employers with job openings and a service that matches them with other people on LinkedIn who can help them network.

What is most important in this process?

It is very important to understand that finding out the most suitable career option is not a simple task. However, it can be very rewarding if done effectively. Never give up, is the key to this path. Students should do their best so as to make their dream career a reality.


TRANSPORTATION NETWORK ANLYSIS: COMBINATION OF FUZZY LOGIC AND GIS TECHNIQUES

Dr. Amrita Sarkar

Assistant Professor, Department of CSE SBU, Ranchi

Traffic congestion is a dynamic phenomenon. Congestion does not occur everywhere, all-at-once. Instead, congestion occurs in specific locations and propagates through network over time as congested conditions on a link spread to nearby links. In addition, since many urban transportation networks are operating at near capacity, they are especially vulnerable to congestion occurring as the result of unplanned incidents such as accidents and infrastructure failures (e.g., bridge closings, construction). These incidents result in congestion patterns that propagate from a localized incident through many portions of the network, potentially resulting in serious flow disruption (Yi-Hwa Wu, Harvey J. Miller & Ming-Chih Hung).

Unfortunately, urban traffic congestion is likely worsen over the future due to structural trends in both developed and developing regions of the world. Although population growth is tapering in many developed regions of the world, urban congestion is continuing to worsen due to continued suburbanization and increasing intensive use of the automobile. In developing regions, these trends combine with rapid population growth and rural-to-urban migration to create transportation systems that operate at near-standstill for substantial portions of the day in many urban areas. Consequently, in most urban areas, increases in transportation system capacity cannot match the corresponding increases in the volume of vehicles (Cervero 1986; Hanson 1995).

The increasing ubiquity and complexity of urban congestion combined with its severe negative impacts suggests the need for new tools to analyze and predict congestion patterns. These tools are important both for tactical operations and strategic planning. Tactical operations require tools for optimal routing and timing for given expected traffic patterns. Technologies that attempt to improve transportation efficiency also require methods for predicting future congestion patterns if intelligent travel recommendations are to be disseminated to travelers. Strategic transportation and landuse planning also requires methods for assessing the congestion patterns that result from new transportation system components or land use activities (Yi-Hwa Wu, Harvey J. Miller & Ming-Chih Hung).

Research organization and technical bodies have recommended standards and specifications for all design parameters to the generalized situations. But the congestion severity on an urban road is affecting the general design condition in diverse ways that has led to the recommendations becoming ineffective. The type and intensity of congestion depend on many quantifiable factors such as volume, speed, headway, ratio of slow moving and fast moving vehicles etc. (R. Narayanan, R. Udayakumar, K. Kumar & L. Subbaraj, 2003). In this context, the quantification and evaluation of congestion severity has been taken as an important research to give a modification to the generalized design procedures and also to suggest the remedial solutions for releasing congestion.

Mainly Congestion is defined using V/C ratio. However, Passenger Car Unit (PCU) used to estimate the volume as well as capacity is subjective in nature and these are not directly measurable units. Therefore, the actual capacity of the road is not determined and thus the value of congestion becomes subjective in nature (R. Narayanan, R. Udayakumar, K. Kumar & L. Subbaraj, 2003). Fuzzy-based systems establish complex non-linear relationships between variables, making them perfect in the domain of quantifying traffic congestion.

Geographic Information Systems (GIS) have long been recognized as a valuable tool for the representation and analysis of transportation networks and related activities. GIS has proven to be an integral tool in addressing the needs of transportation managers. Through the well-established vector data structure, GIS has provided an efficient means for organizing basic transportation related data in order to facilitate the input, analysis, and display of transport networks. GIS for transportation is a broad expression that encompasses all of the activities that involve the use of Geographic Information Systems for some aspect of transportation planning, management, or science (Somayeh Dodge & Ali A. Alesheikh, 2005).

The combined advantages of both Fuzzy logic and GIS offers public, policy makers and traffic managers a new means to assess and to alleviate congestion as short term and medium term measures.


Groundwater Contamination

Prof. Pintu Das

Assistant Professor, Department of Mathematics, SBU, Ranchi

Throughout the world with the growing water demand due to the population enlargement and rapid urbanization, supervision of water modality is becoming a demanding and challenging task. Anthropogenic activities are the main causes of groundwater contamination. One of the most significant aspects of water resources management is prevention and control of groundwater contamination. Due to the importance of groundwater supply and quality in sustainable development, groundwater contamination is a major issue. The subsequent cleanup of groundwater contaminated is a far expansive process. Mostly, Contaminants originate in groundwater are associated with adverse health, social, environmental and economic impacts. Contaminants present into groundwater are associated with cancer, liver and kidney damage also damage to the central nervous system of the human body. Transport of contaminated water also might be odorless, colorless and tasteless. Due to emerging contaminant by different resources into soil, surface water and air and gradually contaminant mixed with groundwater, which creates environmental impacts include degradation of water quality. Significant costs of detecting, preventing and mitigating contamination which might be economics ramifications of groundwater contamination. Further economic damages may also include the costs of developing alternative water supplies, lowered property values, the costs incurred from possible mortality and the decrease in agricultural and industrial yield as a result of using the impaired water. Due to the principle source of water, it is needed to prevent the contaminant. Also need to develop the improved methods of predicting the transport of contaminants in groundwater.


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BBA in Capital Markets

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