Welcome to Phi learning's official blog!

PHI Learning, a trusted name in academic publishing with 62 years of excellence, offers affordable, NEP 2020-aligned textbooks, expert-authored content, and global reach, driving academic progress in higher education.

Tag: engineering

Explore PHI Learning’s affordable academic textbooks, offering high-quality NEP-2020 books for students and teachers across various disciplines.

  • V. RAJARAMAN – A Pioneer in the Field of Computer Science Education in India

    We proudly present “Anecdotes from the History of Modern Computing” by PHI Learning and Professor Rajaraman — the same duo behind India’s first computer science book.
    ANECDOTES FROM THE HISTORY OF MODERN COMPUTING – https://lnkd.in/gid9Jwkq
    – The history of modern computing is presented through 72 pivotal anecdotes.
    – Covers key events and innovations in computer hardware, software, applications, communications, and AI.
    – Self-contained anecdotes that can be read in any order.
    – Simple, jargon-free language accessible to a general audience.
    – Focus on key inventions and the people behind them.
    Rajaraman Anecdotes
    About the Author
    V. RAJARAMAN – A Pioneer in the Field of Computer Science Education in India
    Born: 8 September 1933, Madras Presidency, British India 
    Occupation: Computer engineer & Academic Author 
    Known for: Computer science academics and literature 
     
    Awards
    1. Padma Bhushan 
    2. Shanti Swarup Bhatnagar Prize 
    3. Om Prakash Bhasin Award 
    4. Homi Bhabha Prize 
    5. IISc Rustom Choksi Award 
    6. INAE Lifetime Contribution Award 
    7. IISc Distinguished Alumnus Award 
    8. CSI Lifetime Achievement Award
    Vaidyeswaran Rajaraman is an Indian engineer, academic and writer, known for his pioneering efforts in the field of Computer Science education in India. He is credited with the establishment of the first academic program in computer science in India, which he helped initiate at the Indian Institute of Technology, Kanpur in 1965. An elected fellow of all the Indian science academies, he is a recipient of the Shanti Swarup Bhatnagar Prize, the highest Indian award in the Science and Technology category for young scientists and several other honors including Om Prakash Bhasin Award and Homi Bhabha Prize. The Government of India awarded him the third highest civilian honour of the Padma Bhushan, in 1998, for his contributions to science.
     
    He passed the Higher secondary examination as a student of the first batch of the Madras Education Association (now known as DTEA) Higher Secondary School, New Delhi, in 1949. V.Rajaraman was awarded a scholarship by the Delhi University after passing the All India Entrance Scholarship Examination and graduated with honors in Physics from St. Stephen’s College of the University of Delhi in 1952 and continued his higher studies at the Indian Institute of Science, Bangalore (IISc) to obtain a Diploma in Electrical Communication Engineering in 1955. He stayed on at IISc and designed and constructed non-linear units for an analog computer and applied it for solving a number of engineering problems for which he was awarded an associateship by IISc in 1957. He was awarded an overseas scholarship by the Government of India and joined the Massachusetts Institute of Technology, Cambridge from where he obtained his master’s degree in electrical engineering in 1959. Thereafter, he enrolled himself at the University of Wisconsin-Madison for his doctoral studies and did research on adaptive control systems and obtained a Ph.D. in 1961. He started his career as an assistant professor of statistics at the University of Wisconsin-Madison. In 1962, he returned to India to work as an assistant professor of electrical engineering at the Indian Institute of Technology, Kanpur (IITK). He went as a visiting assistant professor of Electrical Engineering at the University of California, Berkeley during the period 1965–66. It was during this time, he shifted his focus to the then-nascent discipline of computer science.
     
    Supercomputer Education and Research Centre, IISc Bangalore 
     
    In early 1965, with the encouragement by Prof. H. K. Kesavan, the Head of Electrical Engineering Department at IITK, Rajaraman along with his colleagues, initiated a new MTech program with Computer Science as an option; the first time the subject was being offered as an academic discipline in India. Later, he helped introduce a doctoral program, too, and the group led by him pioneered the use of decision tables in the development, debugging, and optimization of complex computer programs. He initiated the first B.Tech. program at IITK in 1978 with an initial batch of 20 students. He became a senior professor at IITK in 1974 and stayed there till 1982. He moved to the Indian Institute of Science, Bangalore and developed low-cost parallel computers and a supercomputing facility of which he served as the Chairman from 1982 to 1994. During his tenure at IITK and IISc, he guided 30 students in their doctoral studies. He published over 70 scientific papers in national and international peer-reviewed journals and several textbooks, including the first on computer programming published in India by PHI Learning Private Limited titled Principles of Computer Programming, Computer Programming in FORTRAN 90 and 95, Computer Oriented Numerical Methods (Third Edition), Analog Computation and Simulation, Analysis and Design of Information Systems (Third Edition), Computer Basics and C Programming, Computer Programming in C, Computer Programming in FORTRAN 77 (With an Introduction to FORTRAN 90), 4th ed., Essentials of E-Commerce Technology, Introduction to Information Technology (Third Edition), Fundamentals of Computers (Sixth Edition), Parallel Computers—Architecture and Programming (Second Edition), Computer Organization and Architecture, Digital Logic and Computer Organization, An Introduction to Digital Computer Design (Fifth Edition) among others. His Ph.D. thesis was on the Theory of parameter-perturbation adaptive and optimizing control systems and S.M. thesis was on Effects of Parameter Variations in Linear Amplifiers. He wrote a monograph, History of Computing in India: 1955-2010, on the invitation of the IEEE Computer Society in 2014. It details the history of Information Technology in India. Rajaraman, besides developing parallel computers, contributed in the development of real-time control system for Bhilai Steel Plant, designed the training modules for Tata Consultancy Services (TCS), and designed computer science curriculum for All India Council for Technical Education (AICTE), the national council for technical education in India. He was a member of the Electronics Commission during 1979–82. During his tenure in the Electronics Commission, he chaired a committee that recommended the introduction of a new academic program called Master of Computer Applications (MCA) for BSc and BCom students foreseeing the impending human resource shortage for the IT industry. This was a unique program in India. He was a council member of the Indian National Science Academy (INSA) from 1986 to 1988. He served as a consultant to Bharat Electronics (BEL), TCS, Electronics Corporation of India Limited (ECIL), Steel Authority of India Limited (SAIL) and Kerala Venture Capital. He chaired a committee set up by the Science Advisory Council to the Prime Minister in 1987 that recommended establishing Centre for the Development of Advanced Computing (CDAC) to design and develop supercomputers in India using parallel computing technology. He was a member of CDAC’s governing council in its formative years. He was a Tata Chem professor at IISc from 1991 to 1994 and the IBM Professor of Information Technology at Jawaharlal Nehru Centre for Advanced Scientific Research (JNCAR) from 1994 to 2001. He was a member of the board of directors of CMC Ltd., Canbank Computer Services Ltd., Encore Software Ltd., and IIIT, Kerala. He was a member of the Technical Advisory Panel of the Government of Karnataka from 1985 to 2014. During his tenure, he advised the government on computerization of land registration (Bhoomi Project), Kaveri project of the stamps and registration department for computerising registration of urban properties, computerizing the court systems and many important e-governance projects. His hobbies include listening to classical Karnatik and Western music and reading fiction and non-fiction books.
     
    Awards and Honors 
     
    Rajaraman received Shanti Swarup Bhatnagar Prize, the highest Indian science and technology award for young scientists, in 1976, for his contributions in optimizing the use of decision tables and his pioneering work in computer science. This was followed by the Homi Bhabha Prize in 1984 and the Indian Society of Technical Education Award for Excellence in Teaching in 1988. He was awarded the Om Prakash Bhasin Award of the Shri Om Prakash Bhasin Foundation and Rustom Choksi Award of the Indian Institute of Science in 1993. The Government of India included him in the Republic Day Honours list in 1998 for the civilian award of the Padma Bhushan. The Indian National Academy of Engineering honored him with the Lifetime Contribution Award in Engineering in 2005 and he received the Distinguished Alumnus Award of the Indian Institute of Science in 2014. He has also delivered several award orations including the S.H. Zaheer Medal (1998) of the Indian National Science Academy and is a recipient of the Lifetime Achievement Award of the Computer Society of India, Dataquest, and Systems Society of India. The Indian Academy of Sciences elected Rajaraman as its fellow in 1974 and the Indian National Science Academy and the National Academy of Sciences, India followed suit in 1982 and 1990 respectively. He is also an elected fellow of the Indian National Academy of Engineering and has held the fellowships of the Computer Society of India (1974) and the Institute of Electronics and Telecommunication Engineers. The Bengal Engineering and Science University and the Indian Institute of Technology Kanpur have conferred the degree of Doctor of Science (honoris causa) on Rajaraman.
     
    An interview with Dr. Rajaraman is available at http://voxiitk.com/interview-with-dr-rajaraman/ 
     
    The Series of Books by Rajaraman, published by PHI Learning, is available for purchase from www.phindia.com.
     
    The books are available in print book format as well as e-book format. Click here https://www.phindia.com/SearchBooks/SearchphiBooks/?searchbooks=rajaraman. 
       

  • Futuristic Digital Forensics In Today’s Tech-Savvy Age

    In today’s digital age, the field of digital forensics is rapidly evolving, driven by technological advancements that enhance the identification, preservation, and analysis of electronic evidence. AI and machine learning have enabled revolutionary advancements across various industries, including the field of digital forensics.

    These days, all activities are conducted on devices. Just look around you and you’ll see what we mean! Everybody is on a device, creating records of their daily conversations, professional activities, and even their search history. Such information is likely to provide ample clues about a person’s personal motives or beliefs — don’t you think?

    In context of digital forensics, a large amount of digital data is likely to be retrieved from digital records such as emails, text messages, search histories, and other online activities that can provide a wealth of evidence for those who know how to analyze them.

    Many Forensics Departments Are Using AI

    Modern AI algorithms are capable of automatically identifying and extracting relevant data from large volumes of digital evidence, including files, emails, and logs. Furthermore, machine learning can read this data to detect patterns indicating irregularities or suspicious activities.

    Even when direct evidence is not available, AI can analyze the “digital footprint” of suspects or individuals involved in a crime. This includes user behavior on online messaging apps, social media platforms, shopping apps, dating apps, hotel booking apps, emails, and business-related software.

    Would it be possible to conduct this type of an investigation without AI? Next to impossible as this type of data could not be processed by a person alone — or even a whole team of people! It’s too large to compute manually, and this is where AI is instrumental.

    AI’s knack for spotting patterns in digital activities can be a game-changer for investigations. Even if it doesn’t provide direct clues, it can still steer things in the right direction.

    AI’s capability to identify patterns and anomalies are unlike any human detection abilities. As an example: AI has the ability to correlate user activity logs from a dating app with social media interactions. It can find correlations between purchase history from a shopping app with social media interactions.  These types of associations are near impossible to detect by just the human eye.

    These days, AI is transforming business by providing insights into correlations between (consensually provided) consumer data across different apps. This helps us further understand what consumers really want. As someone who has used AI to uncover such correlations, it is easy to imagine how this type of information could be invaluable to crime scene investigators!

    Also related to AI-powered data is Natural language processing (NLP). NLP analyzes the natural human language in a context that is more colloquial and human than mechanical or robotic.

    NLP can also play a crucial role in analyzing vast amounts of textual data from emails, chat logs, reviews, and other written communications. This is since NLP conducts sentiment analysis to uncover deeper emotions, viewpoints, values, and beliefs relevant to crime scenes.

    The Role of Sentiment Analysis in Crime Scene Investigations

    Sentiment analysis, while commonly used in business analytics, is particularly useful in crime scene investigations.
    Crimes are driven by sentiments. Often, those who try to cover up crimes may also harbour sentimental motives. As the crime fiction writer, Agatha Christie says, “Very few of us are what we seem. Every murderer is probably somebody’s old friend.” The complexities of human emotions are often hard to decipher. To uncover the deep sentiments that drive human motives, data is the only answer.

    Sentiment analysis can provide valuable insights into the intense human emotions behind criminal acts. By analyzing digital communications or transcribed oral communications, investigators can determine the overall perspective of a person towards various topics, identifying whether their opinion is neutral, positive, or negative.
    Sentiment analysis, using AI and machine learning along with other sophisticated software, is gaining traction across industries. Imagine going from guessing your way through purchase-histories of your customers for an idea on their preferences to having access to their very opinions and attitudes towards your product!

    This type of data isn’t limited to business. In digital forensics, the analysis of sentiment using AI can lead to crucial clues about their mental state, motives, emotional triggers, and potential behavioral patterns related to a crime.

    PHI Learning’s alignment with forensics and NEP 2020

    The National Education Policy (NEP) 2020 aims to transform India’s educational landscape by fostering multidisciplinary learning, critical thinking, and practical applications. PHI Learning’s book “Laws of Electronic Evidence and Digital Forensics” aligns with these objectives by blending theoretical concepts with real-world applications. It is tailored for a diverse audience, including LLB and LLM students, B.Sc. and M.Sc. students in Digital Forensics and Information Security, B.Tech students in Computer Science (Cyber Security and Digital Forensics), and those pursuing PG Diplomas in Cyber Security and Digital Forensics.

    This book provides a comprehensive understanding of digital forensics and its legal implications, equipping students with the knowledge and skills necessary to excel in their careers. By addressing recent technological advancements and aligning with NEP 2020’s goals, “Laws of Electronic Evidence and Digital Forensics” serves as an essential guide for students and professionals navigating the complexities of electronic evidence and digital investigations.

     

     

  • Metro Operations And Their Management

    Economic Development and Economy of any country relates directly to its infrastructure  and urban transport system of which Metro systems plays a significant role. In India, the continued support of Government over the past decades led the development of a wide range rail-based mass transport systems across the country.

    Although the metro system is considered as a sub-system or extension of railways, the nuances of metro operations are very different from that of mainline railways. Operations and maintenance services in Metro systems include various functions and services, such as train service operations, station operations, customer service, ticketing and fare collection, control centre management, security management, asset management planning and deployment, rolling stock maintenance, stations and depot facility management, track and structures, signaling and traction power maintenance and many more functions.

    Today, however, several metro rail systems in India are in the different phases of design, construction, and operations. DMRC has always been at the forefront to support these metro rail systems by sharing its experiences. Every metro rail system has to traverse its own journey, but there is no need to reinvent the wheel every time.

    The solutions to the challenges faced in O&M of Metro systems should be handy to the managers. Hence, in dearth of literary work on Metro operations and management, the authors have made a sincere effort to bring out a comprehensive book addressing the needs of the professionals and the future managers. They have shared their wide experience and expertise on various aspects of MRTS, starting from the planning, execution, operations, maintenance and management for the future development in the field of MRTS. The book covers key areas in metro railway operations management and discusses important issues, supported with case studies, to be considered while planning a metro system to ensure efficient operations.

    Simply, the book is a concise yet comprehensive guide to metro operations, and is a must-read for all professionals and the scholars who aspire to be metro managers. 

    Incredible endorsement and foreword by the Experts— Dr. E. Sreedharan, Dr. Mangu Singh, and Mr. Vikas Kumar. 

    Visit us @ www.phindia.com and Grab your copy now…!

     

     

  • What is AI? Video Lecture By Vinod Chandra and Hareendran

    There has been a movement over the years to make machines intelligent. With the advent of modern technology, AI has become the core part of day-to-day life. But it is accentuated to have a book that keeps abreast of all the state-of-the-art concepts (pertaining to AI) in simplified, explicit and elegant way, expounding on ample examples so that the beginners are able to comprehend the subject with ease.

    Listen to Lecture 1 on Artificial Intelligence by Vinod Chandra and Hareendran on Artificial Intelligence.

    Our book Artificial Intelligence, dexterously divided into 21 chapters, fully satisfies all these pressing needs. It is intended to put each and every concept related to intelligent system in front of the readers in the most simplified way so that while understanding the basic concepts, they will develop thought process that can contribute to the building of advanced intelligent systems. Read about the book in detail. Click https://www.phindia.com/Books/BookDetail/9788120350465/artificial-intelligence-joshi-kulkarni

     

  • Our Author Chetan Singh Solanki to Deliver a Talk at Google

    It is a rare moment when one gets invited by Google to talk about the *Climate Change and Energy Swaraj Yatra* Our author of 5 bestselling books for PHI Learning on renewable energy and solar photovoltaics, Prof. Chetan Singh Solanki, in talk with Mr. Johnson Jose, Director, Google Cloud Platform. Prof. Solanki, a humble man, has been endowed with the names “Solar Gandhi” and “Solar Manav of India” for his dedication towards the cause of solar energy.

  • AI’s First Philosopher: Alan Turing

    Alan Turing was a pioneer of machine learning, whose work continues to shape the crucial question: can machines think?

    When Alan Turing turned his attention to artificial intelligence, there was probably no one in the world better equipped for the task. His paper ‘Computing Machinery and Intelligence’ (1950) is still one of the most frequently cited in the field. Turing died young, however, and for a long time most of his work remained either classified or otherwise inaccessible. So it is perhaps not surprising that there are important lessons left to learn from him, including about the philosophical foundations of AI.

    Turing’s thinking on this topic was far ahead of everyone else’s, partly because he had discovered the fundamental principle of modern computing machinery – the stored-program design – as early as 1936 (a full 12 years before the first modern computer was actually engineered). Turing had only just (in 1934) completed a first degree in mathematics at King’s College, Cambridge, when his article ‘On Computable Numbers’ (1936) was published – one of the most important mathematical papers in history – in which he described an abstract digital computing machine, known today as a universal Turing machine.

    Virtually all modern computers are modelled on Turing’s idea. However, he originally conceived these machines merely because he saw that a human engaged in the process of computing could be compared to one, in a way that was useful for mathematics. His aim was to define the subset of real numbers that are computable in principle, independently of time and space. For this reason, he needed his imaginary computing machine to be maximally powerful.

    To achieve this, he first imagined there being an infinite supply of tape (the storage medium of the imaginary machine). But most importantly, he discovered a method for setting the central mechanism of the machine, which had to be capable of being set in infinitely many different ways to do one thing or another in response to what it scans on the tape, in such a way as to be able to imitate any possible setting of the central mechanism. The essential ingredient of this method is the stored-program design: a universal Turing machine can imitate any other Turing machine, only because – as Turing noted – the basic programming of the central mechanism (ie the way the mechanism is set) can itself be stored on the tape, and hence can be modified (scanned, written, erased). Thus, Turing specified a type of machine that could compute any real number, and indeed anything whatsoever, that any machine that can scan, print and erase automatically according to a given set of instructions could possibly compute; moreover, to the extent that the basic analogy with a human in the process of computing holds, anything that a human could possibly compute.

    It is important to understand that the stored-program design is not only the most fundamental principle of modern computing – it also already contains a deep insight into the limits of machine learning: namely, that there is nothing that such a machine can do in principle that it cannot in principle figure out for itself. Turing saw this implication and its practical potential very early on. And he soon became very interested in the question of machine learning, several years before the stored-program design was first implemented in an actual machine.

    As Turing’s Cambridge teacher, life-long collaborator and fellow computer pioneer Max Newman wrote: ‘The description that he gave of a “universal” computing machine was entirely theoretical in purpose, but Turing’s strong interest in all kinds of practical experiment made him even then interested in the possibility of actually constructing a machine on these lines.’

    Article reproduced from https://aeon.co/essays/why-we-should-remember-alan-turing-as-a-philosopher

    Alan Turing photographed by Elliott and Fry in 1951. Courtesy the National Portrait Gallery, London

     

    PHI Learning books on AI and Machine Learning can be browsed respectively at

    https://www.phindia.com/Books/ShowBooks/MTE0OA/Artificial-Intelligence-Neural-Networks-Fuzzy-Logic-Soft-Computing

    https://www.phindia.com/Books/ShowBooks/ODA/Machine-Learning