There is an ever-increasing prevalence of modern AI systems which are becoming more capable and finding their way to new applications. These enhanced capabilities mean more complexity, and that makes these systems more difficult to understand.When IBM Watson was marketed to hospitals to help the oncology department detect cancer, it failed miserably. The doctors as well as the patients were unable to trust the machine at each stage of consulting and treatment as Watson wouldn’t provide the reasons for its results. Moreover when its results agreed with the doctor’s, it couldn’t provide a diagnosis.The lack of explainability and trust hampers our ability to fully trust AI systems.

XAI could alleviate this situation by proposing novel ways of explaining the underlying thinking process of AI systems.Explainable AI (XAI) is an emerging field in machine learning that aims to address how black box decisions of AI systems are made. XAI is expected to answer questions like: Why did the AI system make a specific prediction or decision? Why didn’t the AI system do something else? When did the AI system succeed and when did it fail? Explainability refers not only to whether the decisions a model outputs are interpretable, but also whether or not the whole process and intention surrounding the model can be properly accounted for.

There are two main set of techniques used to develop explainable systems; post-hoc and ante-hoc. Ante-hoc techniques (e.g. RETAIN, BDL) entail baking explainability into a model from the beginning. Post-hoc techniques (e.g. LIME, LRP, BETA) allow models to be trained normally, with explainability only being incorporated at testing time. The advantages of XAI are human understandable rationale in decision making, trust in system, regulatory compliance, generalization, debugging and enhancement of AI models, detection of bias and openness of discovery and scientific research. The primary applications of XAI systems can be in healthcare, driverless cars or even drones being deployed during war. Despite the advantages there will always be tradeoff decisions to be made between explainability and accuracy depending on the application field of the algorithm and the end-user to whom it’s accountable.Thusas AI becomes more profound in our lives, explainable AI becomes even more important.

The author of this article is Ramkrushna C. Maheshwar, Asst. Prof., Dept of Computer Engineering, International Institute of Information Technology, Hinjawaid, Pune. www.isquareit.edu.in

Meditation is a technique that is being followed since ancient days.  The sages (rishis) of ancient India used to meditate and practice yoga with the primary purpose of achieving their final goal – self-realization. Nowadays, meditation is being used for secondary benefits like getting rid of stress related problems, disorders related to the mind, improve concentration and focus.

Most people face a lot of issues when asked to meditate; the main obstacle being the innumerable thoughts that flash through one’s mind when meditating.  When one starts meditating, the frequency of thoughts increases and the mind seems to jump from one though to another until one’s mind shows reluctance to those thoughts and one gets distracted giving up meditation totally.

One’s mind always thinks in terms of the past or the future and one has no control over either.  One can neither change the past nor control the future and that is where meditation steps in.  It is way to get the mind to focus on and live in the present. Also, putting up reluctance to everything is an inherent nature of our mind; but the opposite of reluctance is acceptance and accepting everything is a state of meditation.  When one starts accepting things, situations and circumstances in one’s daily life, one is meditating.  It’s as simple as that.

How does on meditate?

Whenever a thought comes up in one’s mind, it is followed by a number of related thoughts.  These thoughts could be negative or positive.  It is negative thoughts that breed further negative thoughts leading to a web of toxic thoughts.  But when one thinks – ACCEPTED at the first thought, the entire chain of thought is broken and the mind learns to not process that thought further.  When the mind reaches a state devoid of any thought – that is meditation. Trying to reach the state of nothingness doesn’t happen overnight though.  It starts with breaking of one string of thought at a time and over a period, the mind learns to transcend from complex thoughts to emptiness.

It has taken years to build thoughts and keep the mind busy with complex thoughts and breaking those links will take time.  Like any other habit,  be it doing yoga, cooking, reading, playing an instrument, or any other activity, one has to start small.  If one is able to break one line of thought with total acceptance, that is an achievement.

Meditation during tough times

We are all currently facing a never-seen-before situation where we are all forced to be behind locked doors, stay away from socializing (which is man’s natural instinct) and restrict ourselves.  Technology (TV, mobiles, internet) all seem to have come to our rescue and have been keeping us updated with news, entertained but at the same time it has compounded our worries, concerns, fears and a whole lot of fake news.

Dedicating a few minutes a day to meditate can really be helpful in the current situation.  It can help the mind to stay focused on the present.  Feel happy that our family and loved ones are safe. Fend off any negative thoughts of fear and help deal with the situation in a positive manner.  Just 10 minutes of meditation in the morning can help reduce our stress level, anxiety level and try and bring us to be in the PRESENT.

The author of this blog article is Yogiraj Deshmukh, Assistant Professor,Department of Engineering Sciences, International Institute of Information Technology, (I²IT), Pune (www.isquareit.edu.in) (yogirajd@isquareit.edu.in)

As the world is battling one of the worst pandemic, it is important that teachers look beyond the obvious teaching methods and incorporate innovative ways to help the learners. But are these technologies really working for students?

 I am a teacher anda mother. Like me, many teachers around the world are finding newer ways to help students while being at home with their families. As a professor in the Computer Engineering domain, I started online teaching during this period of national lockdown.I used the various tools that today’s technology had to offer so as to share knowledge with my students. In the current situation, keeping the teaching-learning process alive has become possible only because we have such dynamic technologies at our disposal.  However, I have a slightly different take on this platform.  Initially, students attend the sessioneagerly and are happy to learn; showing their appreciation towards the initiatives of teachers. But as time passes, they loseinterest and drop out. This seems apparent especially since we are unable to connect with students face to face. Call me old school; but somehow teaching online seems like aone-way communication.

Today, we are privilegedto be part of a golden epoch where digital platforms can facilitate reaching out to students especially during such critical times. The young generation is more technically adaptive and that makes it easier for them to learn through newer ways, more flexible methods with focus on convenience.  The restrictive scenario of classrooms seems to be on its way out to be replaced with such better teaching-learning tools.

However, being ingrained in the sanctity of classroom teaching, the newer technologies seem disconnected. For one, online teaching is a one-way communication where most often the comfort of face-to-face experience is missing. As a teacher I can confidently say that having the undivided attention of students in the classroom definitely enhances the learning.  Also, it helps when teachers are able to read the non-verbal signs of students and adapt the teaching levels on the spot. Whether it is explaining a topic with more examples or relaxing the intensity of the content, a direct connect in the classroom is invaluable.

I am not averse to using tools to reinforce the learning and I firmly believe that with time, our students will also learn to use these tools effectively to become better netizens and meet defined goals.

Dr. Sashikala Mishra
Prof. & Head – Dept of Computer Engineering
International Institute of Information Technology, I2IT

When I ask anybody what his/her understanding of the term “learning” is, I get so many different answers. Some say, getting new things, information, knowledge, skills, experience, view, behaviour, opinion, perspective or visualization and many more.  Wikipedia, terms learning as the process of acquiring new, or modifying existing, knowledge, behaviours, skills, values, or preferences.

As an intellectual being, we are continuously evolving ourselvesusing one tool – LEARNING! In fact, I call it as learning. It can be acquisition of new set of information, interpretation of new perspective or application of existing theory or knowledge in an altogether new perspective/ scenario. As humans, we use this method to improve our thinking, and I realized that our actions are born from our thoughts. Our thoughts areproducts of our values, and our values come from our own belief system. Most people misinterpret learning as formal education – which is sub of learning. Formal education refers to the bare minimum set of information, skill sets and knowledge that are required to survive in this world. However, that is not sufficient for developing human life. The world is evolving day by day with new set of information, challenges, diversity and ___________________

When I did some deep thinkingabout how to improve my learning, I began asking those around me and every answer seems to right and a valid perspective of this complex phenomena called learning. One can always get new set of learning from one’s colleagues, friends, family  and all members of society at large. Interpretation given by a hawaldar, a vegetable vendor, a child or even a homeless person on the roadsidecan influence one’s thought process. When one appliesone’s sixth sense, (I call it as common sense) with this new interpretation in one’s work environment; the corporate honchos called it the “out-of-the-box” thinking.

Let me share a story. There was once an expert musician. Whenever he played violin, it rained; even in a desert. Once he went to watch a circus. In one of the performances, a bear

was dancing to a tune played by the violinist from the circus. The musician approached him and said, ‘You can make only a trained beardance to your tune. But my music can make any animal dance!’The circus’ violinist rejected this claim as sheer nonsense. An argument

ensued, resulting in a duel.The circus’ artist called in a lion to face the musician. The lion, on

hearing his music, began to gyrate in an ecstatic dance. Next, a cheetah was called and that animal too began to dance. The circus’ artist send in a tiger next. Themusician continued to play nonchalantly. But the tiger was notenchanted by his music. On the contrary the tiger charged towards the musician. The audience scattered in terror. The musician

threw his violin in the air and ran for his life. Luckily, he managed to escape from the tiger.

The trainers soon caught the tiger and locked it up in a cage. Theexhausted musician now accepted his defeat; however he was still astounded as to why his music failed to charm that

particular tiger. The circus artist explained with a smile, ‘The reason isvery simple. That tiger is tone deaf. It is a birth defect and this particular tiger does not have ears or even the apertures for hearing. The audiencesoon noticed this and tried to escape. But you were so involved in yourplaying that you failed to notice this simple fact!’

Moral of this story is that awareness about present makes a lot of difference in learning. Whenone is at the receiving end and acquires required information related to things and environment around oneself, then one can make relevant interpretation and live a smart life.

Learning is an evolving process and always starts with acquisition of information, experience and degree of correctness of information sources. When this is correctly received then judgment or interpretation can be used to handle any kind of challenges.

The author of this article is Dr. RisilChhatrala, Associate Professor &HoD, Department of Electronics & Telecommunication, International Institute of Information Technology, I2IT, Pune. (www.isquareit.edu.in) (risilc@isquareit.edu.in)

Abstract: Robots have become an integral part of 21st century due to their excessive use in industries, household, hotels and offices. Now-a-days robots are also been used for household applications like cleaning purpose, security purpose etc. Cleaning is an important factor for healthy living and hygiene but due to lack of time it is being neglected. Hence we can have this objective as automatic and intelligent cleaner having two facilities like vacuum cleaner and floor cleaner with a mop attached to it. There are various options available for cleaning purpose such as iRobot’s Roomba but they are not so cost effective. Hence we aim to develop a smart cleaner with additional functionality of wet cleaning with mops in low cost with better efficiency. Also for extensive cleaning we are using obstacle detection system to avoid the robot failure and cover more floor area to clean. This system is intended to do intensive household cleaning by providing dry as well as wet cleaning.

Basically the objective is to clean more floor area in efficient manner hence obstacle detection and avoidance is necessary and it is achieved by interfacing ultrasonic sensor with raspberry pi which is mounted on servo motor. A minimum threshold distance is set in order to avoid any kind of physical damage to the robot and based upon the distance between obstacle and robot a decision will be made for path like moving in forward direction, turning left or right. The whole system is voice controlled hence the voice command from the user is taken and recognized using speech recognition api. The microphone is always in the active state in order to listen the user and satisfy the need. Depending upon the command, robot will start the respective action with the help of relays it can be start vacuum cleaner or start floor cleaner.

Here for vacuum cleaning a 12V DC motor is used and in-case of creating mops BO type DC motors are used. Motors used in vacuum cleaning and floor cleaning will be controlled with the help of relay module and a supply of 12V battery is given to both of them. The vacuum cleaning principle used here is, it will be provided with a inlet pipe which is called sucking end. Once the motor is started inlet pipe will suck in the dust and it will be passed to the dust bag attached to the pipe internally. The dust bag is made of micron fabric which will let the dust to get captured in it and pass the pure or dust free air through it. Also there is outlet for giving out the dust free air back to the environment. For floor cleaning mechanism, 2 BO motors are used which are attached to the mops. Once the motors are set on it will start cleaning the floor and also it will start automated water pump for wet cleaning purpose. Overall system is user-friendly as the mops are detachable and dust bag can be cleaned or emptied easily and also the whole system operates just by a voice command.

Algorithm:

  1. Start.
  2. Activate the microphone and listen to the user given voice command.
  3. With the help of speech recognition convert the voice signal into text and understand what query user has fired.
  4. If the query doesn’t match to the standard command or is unrecognizable then discard the input and goto1.
  5. Based upon the command perform or initiate the respective action of vacuum cleaning or floor cleaning. The user command will trigger the code for cleaning purpose and this turning on/off will be performed with the help of relay module which will set circuit on/off based on the command.
  6. Algorithm runs in assumption that obstacles can be arbitrary, both in quantity and position also it knows nothing about the surrounding environment.
  7. Also start the obstacle avoidance system with the help of ultrasonic sensor and servo motor and calculate the distance between obstacle and robot.
  8. Compare the distance with threshold distance also move the direction of ultrasonic sensor by changing the duty cycle of servo motor as we know that servo motor’s shaft can be rotated within range 0 to 180 degrees hence using a single sensor we can cover front, left and right sides of robot for obstacle detection.
  9. Depending upon the distance returned by the sensor from all directions make a decision for path i.e. whether to continue going front or to change direction either left or right.
  10. If Front, left, right all sides have obstacle then initiate the backward motion to avoid stuck in the same position.
  11. Keep the microphone always in active state in order to as to listen another query from user.
  12. If command from user is to stop the action then perform stopping of particular action.
  13. End.

Prof. PrashantGadakh
prashantg@isquareit.edu.in
International Institute of Information Technology (I²IT), Pune
P- 14 , Rajiv Gandhi Infotech Park,MIDC – Phase I, Hinjawadi,Pune – 411 057, Maharashtra, India

Neural networks are adaptive learning systems, inspired by the biological neural systems. These may be trained with input-output data or may operate in a self-organizing mode. The basic block in an NN is the mathematical model of a neuron as in Eqn. 1. Three fundamental components of a neuron are the connection links that provide the inputs with weights for = 1,…, , an adder that sums all the weighted inputs to prepare the input to the activation function along with the bias associated with each neuron, and an activation function maps the input to the output of the neuron.
(1)
an activation function f is typically a sigmoid function. The scalar parameters of the neuron, the weight and the bias, are adjustable. Single input neuron, multi-input neuron, and multi-input multi-neuron models are shown in Fig. 1.

Neuron activation functions
Several activation functions have been used in neural networks. The simplest of all is the linear activation function used as a linear approximators. This function can be uniploar with saturation levels of 0 and 1or bipolar with saturation levels of -1 to +1 as shown in Fig. 2(a). The threshold and signum functions outputs vary abruptly between 0 to +1 and -1 to +1, respectively as shown in Fig. 2(b). These are used in perceptrons for classification problems. The sigmoid and Gaussian activation functions are nonlinear, differentiable, and continuous. These properties extend the application of neural networks from linear analysis to complex and nonlinear analysis applications. The sigmoid functions are a family of S-shaped functions. Logistic function, as shown in Fig. 2(c), is the most widely used sigmoid function andit has lower bound of 0 and upper bound of 1. Another commonly used sigmoid function is the hyperbolic tangent function with lower bound at -1 and upper bound at 1 as shown in Fig. 2(c). In both of these sigmoid functions, for inputs grater than 0, output initially rapidly and later slowly increases. For inputs less than 0, output rapidly decreases and later slowly decreases. Gaussian functions are symmetric bell shaped functions it represents the input with zero mean and standard deviation equals to one. Standard normal curve is the Gaussian function with bounds 0 and 1. It peaks at zero input and is more sensitive around zero input and less or zero sensitive at tails. In Gaussian

complement, more sensitive at tails and zero at zero input.

Keywords: Neural Network, Neuron Model, Activation Functions, Linear Bipolar, Signum, Sigmodial, Log-sigmoid, Hyperbolic, Tan-sigmoid

Dr. S. Mohan Mahalakshi Naidu
Associate Professor – Electronics & Telecommunication Engineering Department

“We are the sum total of our experience. Those experiences, be they positive or negative make us the person we are, at any given point in our lives.” – B. J. Neblett.

Knowledge comes from learning; but ‘experience’ comes from living. A life without problems and challenges is like a school without lessons. Teaching was not always my passion. Mrs. Kale my Geography teacher was the first to appreciate my skills and said that my voice was apt for a teaching profession. I doubted, but she believed. After my post-graduation I started my career in corporate world and worked in the industry for close to two years. But destinyhad its own plans and I chose to join the teaching profession and today being a teacher for almost a decade, here’s what I would like to share.

No matter how deep our knowledge of a domain is… no matter how many degrees we have…no matter how smart we are… no matter how fast we climb the ladder to leadership… no matter how good the infrastructure of the college is… no matter how impressed the peers and parents are… our students will NOT learn a single thing unless they know that as teachers we really care about them.

Mahatma Gandhi once listed the top three qualities that a teacher should possess – ‘MAMTA’, meaning love, affection and caring, ‘SAMTA’ – meaning equality and impartiality and finally ‘KSHAMTA’ – meaning ability and capability. As a teacher I have imbibed these values and practice them; making them an integral part of who I am as a teacher. And I must say that I have seen the impact that this has had on my students’ learning.

This brings a question in my mind – can I be the teacher that students expect me to be?The kind of teacher who encourages students to believe in themselves, to find hope in the classroom, to strengthen the roots and give wings to my students’ aspirations so as to help them follow their dreams, to believe and never give up.Every day, I believe that I can be better than what I was the day before.

Together with I2IT, I wish to nurture our students beyond textbooks and face the world and succeed in their future. Just like my teacher, I never doubt my students and their capabilities. I believe in them to experience life and grow.

The author of this blog article is Rakhi Wagh, Assistant Professor,Department of Engineering Sciences, Hope Foundation’s International Institute of Information Technology, (I²IT), Pune (www.isquareit.edu.in) (rakhiw@isquareit.edu.in)

There are several types of neural network models with various features developed for variety of applications. A single neuron with linear activation function as in Eqn. 1,three fundamental components of it are the connection links that provide the inputs with weights for  = 1,…, , an adder that sums all the weighted inputs to prepare the input to the activation function along with the bias  associated with each neuron, and an activation functionmaps the input to the output of the neuron,

                                                             

designed as a neural network model as shown in Fig. 1, is a linear estimator and classifier. The estimator capabilities are equivalent to simple and multiple linear regression models. As a classifier, it is similar to simple and multiple discriminant function analysis in statistics. The perceptron network shown in Fig. 2(a) was proposed by Rosenblatt in 1950. This is a linear classifier and is functionally similar to simple and multiple discriminant function analysis in statistics.

The multilayer perceptron (MLP) model shown in Fig. 2(b) is the most popular neural network model for the nonlinear estimation and classification problems. This, in fact, is an extension of the perceptron network. The competitive networks shown in Fig. 3 are unsupervised networks that can find clusters in the data. The self-organizing map (SOM) competitive network, shown in Fig. 3, not only finds unknown clusters in the data but also preserves the topological structureof the data and clusters. Two well-knownneural networks for time-series forecasting are the Jordan and Elman networks shown in Fig. 4. These networks contain feedback links that help to capture temporal effects.

Neural networks can further be classified based on the signal flow from neuron to neuron within the network, training/learning method used, and type of activation function used in the neural network. In feedforward neural networks, signal flow is always in the forward direction whereas in the feedback or recurrent neural networks, signal can flow in forward and backward directions. The MLP networks, radial basis function networks, support vector machines, generalized model for data handling or polynomial nets, generalized regression neural network, generalized neural network, Kohonen’sselforganizing feature map, back propagation neural network, and Jordan and Elman networks are some of the examples of neural networks.

The neural networks generally have three layers. The single or multiple inputs form the input layer. This is connected with its corresponding weights to the middle layer called hidden layer. There can be multiple number of hidden layers and can have more than one neuron in each layer. The last layer which produces the output of the neural network is called output layer.

 

Keywords: Neuron Model, Neural Network Model, Competitive Networks, Perceptron, MLP, Feedback Neural Network, Classification

 Dr. S. Mohan Mahalakshi Naidu
Associate Professor – Electronics & Telecommunication Engineering Department

Mathematics is a constantly improving branch of knowledge. It is influencing our day-to-day life;however, commoners do not understand its impact. Most people think that mathematics is a branch of knowledge that includes only techniques of calculation of numbers and of shapes and sizes of various objects. The general impression is that mathematics is difficult to learn, understand and apply in the real-life situations. For many people it is a brain twister, creating fear in the mind. In school education, most of the dropout students have apprehensions about mathematics and they rarely take up the subject again in their life. The actual fault lies with educationists, who don’t put forth the beauty and applicability of math. The subject is presented in such a way that most of the students find it complex and intricate. This leads to the question that what kind of mathematics needs to be introduced in the school level of education?

Generally,learning mathematics starts with the introduction to numbers and arithmetic operations, followed by introduction to geometrical shapes and their properties. The enhancement of learning process can be done by correlating these ideas with the day to day life of students. There is an obvious confusion in the mind of most students that mathematics is just limited to arithmetic. However, mathematics is much more than that. Thus, doing calculations very fast does not indicate that one is good in mathematics. There are people who have the ability of calculating fast and even create unique records, but are not recognized as mathematicians; although it is important that, to become a mathematician one should be able to identify create a close association with numerical calculation sand arithmetical operations.

Recreational mathematics is a branch of mathematics where mathematics meets entertainment and is useful in learning mathematics. It creates interest and motivates students to appreciate various concepts of mathematics. This kind of mathematics eradicates the fear of mathematics among students and helps them develop interest in the subject. Nowadays most educationists promote and incorporate recreational mathematics at school level. Just a trivia – in medieval India recreational mathematics was part of our education system.

Defining recreational mathematics may be difficult; but it encapsulates many things such as riddles, puzzles, games, numerical calculations, optimization techniques, the popular Sudoku problem etc. Though mathematics deals with abstract concepts which are difficult to understand, recreational mathematics helps students in the development of these concepts in a very interesting way. Recreational mathematics present many challenges for students to learn which can reinforce mathematical concepts and widen students’ thinking capabilities.

Many researchers and mathematicians have contributed to this branch. There are mathematicians who have shifted their focus from pure mathematics to the development of recreational mathematics. Raymond Smullyan is one such mathematician. This American mathematician devoted his career towards development of logical puzzles. This creates a strong background for computer programmers to build logic. Such puzzles encourage students to think logically, which will help them develop their programming abilities.

Mandar Vijay Datar (M.Tech. SET)
Assistant Professor (Engineering Mathematics)
Department of Engineering Sciences,
Hope Foundation’s International Institute of Information Technology, Hinjawadi, Pune

As per the latest reports by the World Health Organisation, there is near about 20 lakh COVID-19 cases reported across the world so far, with a little over 1,26,776  deaths. In short, the corona virus has affected people’s life irrespective of their social and economic condition. In the thick of all the gloom and doom, there is a silver lining. Mother earth seems to have rejuvenated itself.Smog has given way to blue skies, marine life is improving, pollution levels have dropped, and animals as well as birds are moving about freely.

A few days ago, Noida’s busy Sector saw an unexpected guest. A Nilgai was seen walking slowly on the road. To the common man, this incident was a welcome change from the usually traffic jammed road. Similarly, in Kerala’s Kozhikode, a Malabar Civet, an endangered animal, was seen walking on the road.  Ever since the coronavirus pandemic struck across the globe, several reports have emerged highlighting the return of many species to their natural habitats.

The Government’s drastic decision to shut down factories, commercial establishments, and vehicular movement, has resulted in a drastic drop in the pollution levels across the world. As the pandemic continues to halt industrial activities, it has allowed a natural purification of air. Satellite images have proved that there has been considerable improvement in the air quality around us. Nature’s Victory! According to a research by Columbia University, both carbon monoxide and carbon-dioxide emissions were observed to have fallen.

The quiet street corners, empty parking lots, and deserted parks have given more space for nature to take control. The humdrum surrounding tourism and the reduced number of motorboats in Venice has led to cleaner waterways. The nationwide lockdown is also providing perfect condition for the Olive Ridley Turtles to lay eggs in Odisha’s Gahirmatha beach and Rushikulya’s rookery. Usually, this event is known to attract huge crowds and officials from the Forest Department generally deploy a considerable amount of efforts and resources to patrol gatherings, protect the eggs, and later release the hatchlings into the sea. However, this time, there were no such arrangements but nature has taken care of everything.

“COVID-19 has been an eye-opener. It has shown people as to how mother earth can bounce back to life if humans allow for it. But, unless the society cares for the environment and changes its attitude, all of it is bound to get back to square one,” – Ram Murthy.  However, is this a long-term trend? It is said that times of disruptions tend to lead to big transitions. The COVID-19 shutdown has given people a glimpse into what the world might look like if we live sustainably and conserve the resources of the planet. But, can people expect a transformation in the future? Nevertheless, the improvement in the air quality owing to the outbreak of the pandemic looks like a ray a ray of hope in the times to come.

Keywords:-COVID-19, Environment, social, economic, coronavirus

Name:- Mahesh S Waghmare,
Dept:- Department of Engineering Sciences
International Institute of Information Technology, Pune.

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