Abstract: The intuitive network starts with intent-based infrastructure that is secure - essentially all IP infrastructure, including switches, routers, wireless access points, that provides the connectivity and routes traffic from devices (PCs, tablets, phones, video screens, IoT) within the enterprise and to the internet.IP networking started small 30 years ago, connecting two departments in a lab. Now, enterprises have networks with tens of thousands of boxes. Most of them still have relatively primitive tools to manage this complexity. It's an expensive process and can slow down the business. The wireless network is separate from the wired network, which is separate from the Wide Area Network. And they're all managed and configured separately, and they can all have different interfaces, commands, and configuration models. Even worse, this is all usually done one box at a time. With the intuitive network, we fundamentally changed the approach, removing a lot of the complexity accumulated over the past 30 years. Now we have one unified system that spans the entire enterprise access network, covering all type of devices. It acts as a single platform, driven by intent. This intent-based infrastructure is programmable and integrated so that it can be automated. Also, security is built-in with the ability to find threats and automate responses to keep enterprises protected from advanced threats. This unified system includes our networking software operating system, IOS. Over the past two years, we've completely rebuilt IOS for the digital age. IOS is now API driven, open, programmable, and modular - all capabilities that are required from a modern software stack.

In this talk I will explore the integration of people, software services, and things with their data, into a novel resilient ecosystem, which can be modeled, programmed, and deployed on a large scale in an elastic way. This novel paradigm has major consequences on how we view, build, design, and deploy ultra-large scale distributed systems and establishes a novel foundation for an "architecture of value" driven Smart City. In particular, this talk addre es three novel paradigms for designing the service-oriented information systems of the future: Elastic Computing, Social Compute Units, and Osmotic Computing. These three paradigms serve as a foundation for future large-scale distributed systems. Furthermore, we will discu our responsibilities as computer scientists, technologists, and researchers for creating technologies, which benefit society in a positive way, thereby strengthening the new fabric of interconnected people, software services, and things into a novel resilient ecosystem.

Abstract: Advances in computing, communications, networking and electronics have enabled the generation of enormous amounts of data. This is due to higher resolution data, captured more frequently, and the growing use of connected sensor data in IoT applications. This data must be captured, proce ed and then stored. Some data must be kept for a short time and proce ed quickly to be useful, e.g. in autonomous vehicles as well as robotics and automation. The results of this proce ing and data generated having economic value (e.g. commercial video) may be kept for a long time. This talk will examine the latest developments in the digital memory and storage hierarchy and how they will enable developments in AI, cloud computing, VR/AR, Smart Cities, robotics and automation and the preservation of culture, technology and history.

Abstract: Emerging Internet Quality of Service (QoS) mechanisms are expected to enable widespread use of real-time services such as VoIP and video conferencing. The "best effort" Internet delivery cannot be used for the new multimedia applications. New technologies and new standards are necessary to offer Quality of Service (QoS) for these multimedia applications. Therefore new communication architectures integrate mechanisms allowing guaranteed QoS services as well as high rate communications. The service level agreement with a mobile Internet user is hard to satisfy, since there may not be enough resources available in some parts of the network the mobile user is moving into. The emerging Internet QoS architectures, differentiated services, and integrated services do not consider user mobility. QoS mechanisms enforce a differentiated sharing of bandwidth among services and users. Thus, there must be mechanisms available to identify traffic flows with different QoS parameters and to make it possible to charge the users based on requested quality. The integration of fixed and mobile wireless access into IP networks presents a cost-effective and efficient way to provide seamless end-to-end connectivity and ubiquitous access in a market where the demand for mobile Internet services has grown rapidly and predicted to generate billions of dollars in revenue. It covers the issues of QoS provisioning in heterogeneous networks and Internet access over future 5G wireless networks. It discusses the characteristics of the Internet, mobility and QoS provisioning in wireless, IoT and mobile IP networks. This tutorial also covers routing, security, baseline architecture of the inter-networking protocols and end to end traffic management issues.

Title of Talk: Using Blockchain in Financial Services Industry. Speaker: Mr. Sajeev Vishwanathan, CEO and Founder, New Street Technology.

Abstract: How New Street Technology is using Blockchain technology in the Financial Services sector to reduce the cost of operation as well as to build trust with its customers and clients. They work with Banks in India on various financial services.

Title of Talk: Technology in Logistics Mr. Narendra Kochat, CEO and Founder, Nikkos Logistics.

Abstract: EHow Nikoos as a logistics company can drive IT for customers. Emerging trends and opportunities to solve business opportunities in India and how Nikoos uses a model and how technology to drive this model for customers.

Titles for Lightning Talks

-- Transition to Software-defined waveforms (Mr. Abhay Shriramwar, Cyient Ltd)
-- Localization of Neuronal Activity Using Error Free MEG MRI Co-registration (Dr. Anitha, Manipal Institute of Technology)
-- Advertisements Analytics (Ms. Apoorva Saxena, PESIT-BSC)
-- Building Low-cost quick deployment chatbots (Mr. Aswin.T.S, [24]7.AI India)
-- iBCE-EL: A Sequence-Based Predictor for Identifying B-Cell Epitopes Using Ensemble Learning (Prof. Balachandran Manavalan, Ajou University School of Medicine)
-- On average mutation distance (Dr. Bhadrachalam Chitturi, Amrita Vishwa Vidyapeetham)
-- Dynamic Pa word Protocol Against Cyber Threats (Mr. Channabasava H, PES Institute of Technology Bangalore South Campus)
-- Combustion Quality Prediction Model based on Flame Shape using LSTM Regre ion (Dr. K. Sujatha, Profe or, EEE, Dr.MGR Educational & Research Institute)
-- Attack and Security Threats in MANETS (Ms. Fahmina Taranum, Muffakham Jah College of Engineering and Technology)
-- Classification of colposcopic cervigrams using EMD in R (Mr. Kumar Dron Shrivastav, Amity Institute of Public Health)
-- Fog computing (Prof. Manjula Shenoy K, Manipal Institute of Technology)
-- MOOC and its Indian chapter SWAYAM (Mr. Abdul Wahid, University of Kashmir)

Abstract: This keynote addresses a hot and updated topic focusing on Internet of Things (IoT), considering their most relevant challenges and opportunities for smart places deployment. It starts with an introduction to IoT and its typical application scenarios considering different verticals. After, an initiative to prepare ICT professionals for new challenges regarding this new generation technologies for IoT will be presented. A special attention will be given to the Inatel Smart Campus, an open Campus for research on IoT, experiments, and concepts and technology validation. Inatel has sponsored this project, started in August 2016, open for companies' participation and promoting the academy-enterprise interaction. It is a true living lab for several IoT verticals, including smart cities and smart homes. New challenges and opportunities on IoT are discussed. The communication ends with new trends and issues on Internet of Things, suggesting further research topics.

Talk 1: Title: Bayesian methods in Astrophysics Tarun Deep Saini, Assistant Professor and Academic Coordinator, Joint Astronomy Programme at Indian Institute of Science

It is commonly believed that Bayesian statistic differs from frequentist statistic only in the narrow sense that it allows for prior information in statistical inference; and in those cases where the priors are a umed flat, the two are, in fact, thought to be indistinguishable. However, through specific examples, I will show that the conceptual turnaround that the Bayes theorem enables, allows for neater solutions to several problems of statistical inference.

Talk 2: Title: From Machine Learning to Deep Learning in Astronomy Ajit Kembhavi, Professor Emeritus at the Inter-University Centre for Astronomy and Astrophysics

Machine Learning has for long been used in astronomy to address classification problems. It provides very useful techniques for quickly and reliably addressing problems such as to distinguish between stars and nearly unresolved galaxies and to distinguish between unresolved quasars and stars on the basis of their colours. These techniques have limitations because they are dependent on the use of derived parameters for the training. Such an approach might not be possible, for example, in classification problems involving objects with complex morphology, which cannot be easily parameterized. In such circumstances Deep Learning techniques, which have been used in applications like face recognition, prove to be very useful, since they directly use images or spectral data without the need for parameterization. I will consider, as convolutional neural networks (CNN) and describe their use with a few examples, including galaxy morphology and time series analysis. As applications, I will consider the finding of galaxies with bars and rings, and the classification of stellar spectra and show that very good accuracy can be obtained.

Talk 3: Title: Theoretical validation of potential habitability of recently discovered exoplanets via modeling and Machine learning Margarita Safonova, Birla Institute of Fundamental Research

Seven Earth-sized planets, known as the TRAPPIST-1 system, was discovered with great fanfare in the last week of February 2017. Three of these planets are in the habitable zone of their star, making them potentially habitable planets (PHPs) a mere 40 light years away. The discovery of the closest potentially habitable planet to us just a year before - Proxima b and a realization that Earth-type planets in circumstellar habitable zones are a common occurrence provide the impetus to the existing pursuit for life outside the Solar System. The search for life has two goals essentially: looking for planets with Earth-like conditions (Earth similarity) and looking for the possibility of life in some form (habitability). An index was recently developed, the Cobb-Douglas Habitability Score (CDHS), based on Cobb-Douglas habitability production function (CD-HPF), which computes the habitability score by using measured and estimated planetary parameters. As an initial set, radius, density, escape velocity and surface temperature of a planet were used. The proposed metric, with exponents accounting for metric elasticity, is endowed with analytical properties that ensure global optima and can be scaled to accommodate a finite number of input parameters. We show here that the model is elastic, and the conditions on elasticity to ensure global maxima can scale as the number of predictor parameters increase. K-NN (K-Nearest Neighbor) classification algorithm, embellished with probabilistic herding and thresholding restriction, utilizes CDHS scores and labels exoplanets into appropriate classes via feature-learning methods yielding granular clusters of habitability. The algorithm works on top of a decision theoretical model using the power of convex optimization and machine learning. The goal is to characterize the recently discovered exoplanets into an "Earth League" and several other classes based on their CDHS values. A second approach, based on a novel feature-learning and tree-building method classifies the same planets without computing the CDHS of the planets and produces a similar outcome. For this, we use XGBoosted trees. The convergence of the outcome of the two different approaches indicates the strength of the proposed solution scheme and the likelihood of the potential habitability of the recently announced discoveries. We plan to discuss new activation functions for such classification purposes.

Talk 4: Title: Machine Learning in the context of New Surveys and the Internet of Things(IoT) Ninan Sajeeth Philip, Associate Professor, and Head, Department of Physics, St. Thomas college. Area of specialization: Machine Learning

Abstract: Machine Learning became popular as a tool to substitute the logical deductions made by a human expert on a given problem by adjusting a finite nonlinear combination of variables through a process called training. In a large subset of problems, this can be done using a small set of derived features describing the logic used by the expert to come to the conclusions. When problems are described in terms of the derived features, the reliability of the predictions using it depends on how well the derived features are capable of describing the problem in all the possible situations. For example, when doing a star-galaxy classification, one can use the ellipticity of a galaxy to separate them from the gau ian psf of stars. The logic works well when the galaxy is well resolved. However, if the galaxy is far off, it might look similar to a star and our feature based classification fails. There is yet another class of problems where the domain expert has to dynamically select a subset of available features from a large pool of features to do the classification. This is typically the case when language, speech or image classifications are done, where, depending on each situation (context), the set of features for the classification are selected. For example, the set of features describing the image of a dog need not be the same for describing a human or some other animal in the same image. Going for manually defining the context leads to an ill-posed problem. The talk shall introduce the basic concepts of IoT, Natural Language Processing (NLP), big data and how it transforms modern machine learning from model-driven to a data-driven science.

Talk 5: Title: Classifying sources in multiwavelength astronomy using machine learning Jayant Murthy, Director, Indian Institute of Astrophysics

Astronomical data sets have been steadily increasing insensitivity and size to the point where it is no longer practical to extract ``interesting'' objects from the chaff. In this scenario, an automated analysis procedure is necessary not only to process the data into scientifically usable data sets, including a source catalog but to go further and classify the sources in the catalog. Even more information about the sources and, hence, a better classification will be obtained by combining multiple catalogs, particularly from multiple spacecraft with a broad spectral coverage. The complexity of the data and the number of sources necessitate a machine learning (ML) approach to the problem. We will specifically address the case of star-quasar separation where color-color plots have been used in the past. We have found that these would not yield a unique separation and used a template-based method where we fit all the available photometric data at once. We are now experimenting with a neural network based approach and are finding good results. I will focus here on presenting the scientific problem.

Workshop Chair: Snehanshu Saha < http://astrirg.org/projects.html >, http://icacci-conference.org/2018/astronomy

Abstract: Troubleshooting complex systems in IT data centers is a very complex problem. We focus on the problem of detecting anomalous run-time behavior of distributed applications from their execution logs. Specifically we mine templates and template sequences from logs to form a control flow graph (cfg) spanning distributed components. This cfg represents the baseline healthy system state and is used to flag deviations from the expected behavior of runtime logs.

The novelty in our work stems from the new techniques employed to: (1) overcome the instrumentation requirements or application specific a umptions made in prior log mining approaches, (2) improve the accuracy of mined templates and the cfg in the presence of long parameters and high amount of interleaving respectively, and (3) improve by orders of magnitude the scalability of the cfg mining proce in terms of volume of log data that can be proce ed per day.

Abstract: With growing digital medical data and meteoric success of machine learning it is now feasible to aid the medical practitioner in better diagnosing pathology and in some cases, outperform them. Lower back pain (LBP) is widely prevalent in people all over the world and negatively affects the quality of life due to chronic pain and change in posture. According to the American Academy of Orthopedic Surgeons (AAOS) four out of five adults experience low back pain at some point during their lives. I will discuss results from our work in automating the diagnosis of spine pathology. Clinical datasets are generally limited to pathological findings such as arthritis, fracture, infection, dislocation or tumor, but in the absence of gro pathology there is very poor correlation to nonspecific spine pain clinical symptoms. Since the majority of spine pain patients do not have any correlative pathological findings, it is important to look at the mechanics of the spine from a clinical standpoint. I will end this talk with some results in automating the process of suggesting changes to biomechanics of the spine thus taking the automation from diagnosis to cure.

Abstract: Blockchain is the technology behind bitcoin, ether and most of the other cryptocurrencies. Blockchain is e entially a form of record keeping and can be used in almost any product that uses some form of record keeping or database management. Blockchain is ideal for protecting any data that needs to be unalterable and indestructible. Traditionally, data are kept on a server that is owned and operated by a third-party company. This approach has some disadvantages. In this way, if a third party has acce to your data, they could be destroyed, they could be altered, and it could leak. Through Blockchain, data are encrypted and then propagated over a distributed network of computers. In this way, data are nobody's properties, data cannot be destroyed and altered. Data block are sets of permanently recorded data e.g. financial transactions. The information is first hash which is a way to represent the data in a compact format where data can be easily compared for any change. Any small change in the data completely changes the hash version which makes the comparison very easy. The hash data are then encrypted. One private key allows the producer of the data to encrypt the data and serves as a digital signature. Also, one public key allows everyone else with the key to decrypt it. Finally, the data blocks are connected to each other (chained). Bitcoin is simply an application of Blockchain but there are many other applications where this technology has a lot to say. The application of this technology is endle in all fields but with respect to industry there are fields in which use is more and more common e.g. Supply Chain Management, Health Care and medical record sharing, Media Distribution, E-commerce with no middleman, Sharing economy with no central authority, Authenticated News Sharing/Data Sharing, Data Sharing Between companies Edge Computing, Industry 4.0, IOT and Smart Cities are areas in which Blockchain has high impact. The IoT refers to the ever-growing network of physical objects that feature an IP addre for internet connectivity, and the communication that occurs between these objects and other Internet-enabled devices and systems. The risk of connecting a machine to Internet is obvious and Blockchain may help to eliminate or at least reduce some of these risks. The industry is updating its proce es to be more efficient. Industry 4.0 is a transformation that makes it po ible to gather and analyze data acro machines, enabling faster, more flexible, and more efficient proce es to produce higher-quality goods at reduced costs, that's the reason why a technology such us Blockchain if also of great interest to guaranty security and data reliability. The main aim of this tutorial is to introduce Blockchain technology and represents its practical application in security of Industry 4.0, Smart cities, Smart homes, and Internet of Thing.

Keynote Speaker: Peter Mueller, IBM Zurich Research Laboratory, Switzerland

Title of Talk: Quantum Computing Technology interacting with Cla ical Computing Systems (Sept. 20, 2018, 14-14.50)

Abstract: The upcoming quantum computing devices based on superconducting qubit technology are expected to outperform conventional computers in a growing number of algorithms, such as the computing of energy spectra or the dynamics of molecular or condensed matter systems. To gain the best performance, algorithms can be partitioned and placed to the appropriate modules of a tightly coupled quantum-cla ical proce ing system. This talk will introduce in the superconducting qubit technology as we apply it in IBM. Some of the recently recognized challenges at qubit level regarding system architecture, but also the overall ecosystem will be outlined. Further, the integration of quantum computers into our computing environment to form a co-existing quantum-cla ical system will be reported. I will show developments towards useful quantum applications with potential advantage when running them on small-sized quantum computing hardware. Such methods may enhance the efficiency of variational methods for quantum chemistry or optimization tasks with the prospect of carrying out scientifically and commercially relevant computations in the near future.

Titles for Lightning Talks

-- Explainable AI (XAI) (Mr. Manojkumar Parmar, Robert Bosch Engineering and Busine Solutions Private Ltd)
-- Batch Processing through Mulesoft (Ms. Manvi Seth, Cisco Systems India Pvt Ltd)
-- Railway Track Monitoring (Mr. Sai Pavan Kartheek Sunkara, Amrita School of Engineering, Bengaluru)
-- Automation, Innovation & Education (Ms. Prajakta Dnyandev Patil, Rajarambapu Institute of Technology)
-- Enhancing the capabilities of the network protocol for forensic investigation and Evidence Collection (Prof. Rachana Yogesh Patil, A. C. Patil College of Engineering, Navi Mumbai)
-- Discriminative Feature Learning for URL based Web Page Classification (Dr. Rajalakshmi R, Vellore Institute of Technology, Chennai Campus)
-- Artificial Intelligence based Internet of Things (Dr. Ravinder Reddy Ramasani, CBIT, Osmania University)
-- Artificial neural networks for anomaly detection (Dr. Seema Singh, BMS Institute of Technology and Management)
-- Technologies that Enable High Capacity Wireless 5G Network (Mr. Dhanurdhar Murali, P.E.S. Institute of Technology)
-- IoT Techniques Used for Monitoring Patient (Dr. Sudhanshu Suhas Gonge, Marathwada Mitra Mandal's College of Engineering)
-- Forecasting System for Future Transaction Volume of Bitcoin Cryptocurrency (Dr. Sudalaimuthu T, Hindustan University)
-- Detection of Energy Theft in Smart Grid (Dr. Tan Wooi Nee, Multimedia University)

Abstract: Grouping nodes gives better performance to the group and to the whole system, thereby avoiding unnecessary me age forwarding and additional overheads, thus providing low energy consumption. Grouping nodes also diminish the average network delay while allows scaling the network considerably. Communications in sensor networks should be as efficient as possible and collaborative methods can enhance their performance. Group-based collaborative wireless sensor networks appear as the proper logical step. When a Wireless Sensor Network is deployed, environment data can be obtained using two sides. The first one is the direct sensing, where the information is measured physically from the medium. The second one is the indirect sensing, which provides the information using the parameters of the wireless network (Received Signal Strength, lost frames, disconnections, etc.) and from the behavior of the traffic and the nodes of the network. Both can be mixed to have a complete picture of what is happening in the aquatic medium and to estimate the right prediction. In this talk, a cognitive group-based collaborative wireless sensor network for controlling water pollution and underwater monitoring is presented. Discussions about the network parameters that are affected by the environment, how they can be used for environmental monitoring, and their relationship with what is happening in the environment will be held. Self-learning algorithms, techniques for the representation of the knowledge acquired from the environment, and information management are added to the wireless sensor network in order to have an efficient system. Moreover, the group-based system lets the network send the information according to several cooperation rules and taken decisions. Some examples for wide areas monitoring and for small size areas monitoring in real aquatic scenarios will be shown.

Embedded platforms for AI and Blockchain

This tutorial provides an overview of the most relevant approaches to next Generation computing. AI, ML, IOT, and Cloud Infrastructure create an enormous amount of data and the amount of data generated daily by an individual can go up to 1TB and similarly by an industry can go up to 500TB by 2022. In order to process this huge amount of data, it needs very high computing and storage infrastructure and low latency network. Cloud infrastructure is being built across the world to process this data. Generation, transportation, and processing of these data at Cloud securely when the amount of data explode exponentially is a major challenge. This challenge involves many factors such as security in handling these data, network bandwidth required to move this data across the cloud, latency in which transferring the data across the computing nodes and huge computing power required in a data centre. Isolated high power data centers are not a viable option to address above challenges. Edge computing, Automation, Artificial Intelligence, and block-chain are some of the solutions which address the above challenges. Using these solutions simultaneously is the key to solving these challenges which industry is going to face in near future.

Outline of the presentation (Duration 1 hr 50 Min): • Motivation and Introduction (5 Min) • 4th Industrial revolution -AI (5 Min) • Type of AI (5 Min) • Need for AI and Blockchain (5 Min) • Need for Automation (5 Min) • Evolution of edge computing (5 Min) • API computing and economy (5 Min) • Heterogeneous Computing (5 min) • Low latency Computing (5 Min) • Blockchain basics (10 Minutes) • Hardware accelerated and Managed Blockchain (10 Minutes) • Heterogeneous Computing for AI and ML (5 Min) • Acceleron MDC accelerate AI and Blockchain (30 Minutes). • Discussion (10 Min)

Abstract: There is a growing concern in computing about how research can make an impact by addre ing pre ing societal i ues. Topics that are being proposed are far-reaching, including climate change; health and well being; facilitating innovation in developing countries and instrumenting new forms of civic engagement with the aim of influencing policy change. Such big questions, however, need the computing community, along with others, to change how research is done. This requires new framings, new collaborations and new integrated methods. However, this is simpler said than done: the gap is huge between working and achieving succe at the micro level and at the macro scale required (Shneiderman, 2016). In my talk I will describe some of our attempts to bridge the gap from a human-centred perspective with a focus on urban tech design, community empowerment and behavioural change.

Abstract: Typing is still one of the main methods of interaction with computing devices: we do it regularly on our laptops, smartphones and other devices, like ATM machines. Oftentimes, we want to keep the typed text confidential (emails, pa word, pin codes...). To protect our text, we use all kinds of acce control and encryption mechanisms, but we might forget to leave some other doors open to the adversary. In this talk, we will review recent results on typing inference from side channels exploitable by both local and remote adversaries (e.g., through a VoIP conversation).

SHORT BIO: Mauro Conti is Full Profe or at the University of Padua, Italy, and Affiliate Profe or at the University of Washington, Seattle, USA. He obtained his Ph.D. from Sapienza University of Rome, Italy, in 2009. After his Ph.D., he was a Post-Doc Researcher at Vrije Universiteit Amsterdam, The Netherlands. In 2011 he joined as A istant Profe or the University of Padua, where he became A ociate Profe or in 2015, and Full Profe or in 2018. He has been Visiting Researcher at GMU (2008, 2016), UCLA (2010), UCI (2012, 2013, 2014, 2017), TU Darmstadt (2013), UF (2015), and FIU (2015, 2016). He has been awarded with a Marie Curie Fellowship (2012) by the European Commi ion, and with a Fellowship by the German DAAD (2013). His research is also funded by companies, including Cisco and Intel. His main research interest is in the area of security and privacy. In this area, he published more than 200 papers in topmost international peer-reviewed journals and conference. He is Area Editor-in-Chief for IEEE Communications Surveys & Tutorials, and A ociate Editor for several journals, including IEEE Communications Surveys & Tutorials, IEEE Transactions on Information Forensics and Security, and IEEE Transactions on Network and Service Management. He was Program Chair for TRUST 2015, ICISS 2016, WiSec 2017, and General Chair for SecureComm 2012 and ACM SACMAT 2013. He is Senior Member of the IEEE.

Abstract: Wirele body area sensor network is a sub-field of wirele sensor network. Wirele body area sensor network has come into existence after the development of wirele sensor network reached some level of maturity. This has become po ible due to the tremendous technological advancement leading to easy-to-use wirele wearable technologies and electronic components that are small in size. Indeed, this field has gained significant attention in recent time due to its applications which mostly are toward healthcare sector. Today, tiny-sized sensors could be placed on the human body to record various physiological parameters and these sensors are capable of sending data to other devices so that further nece ary actions could be taken. Hence, this can be used for diagnosis of disease and for developing serious health complication alert systems. In this talk, we would cover the state-of-the-art of various aspects of wirele body area sensor network, its communication architectures, wirele body area sensor network applications, programming frameworks, security i ues, and energy-efficient routing protocols.

Title of the Talk: Technology for Inclusion Speaker: Prof. Rangasayee Raghunathrao, Chairman, Audiology Committee of International Association of Logopedics and Phoniatrics

Title of the Talk: Innovations and Incubation opportunities in the Disability Speaker: Mr. Mahantesh G Kivadasannavar, Founder, Managing Trustee - Samarthanam Trust

Title of Talk: Multiobjective Optimization for Clustering and Cla ification (14.00-14.50)

Dr. Jharna Majumdar, Centre for Robotics Research, Nitte Meenakshi Institute of Technology, Bangalore Title of Talk: Advance Algorithms for Video Proce ing

Abstract: With the rapid growth of Advanced Technology and the availability of affordable low-cost sensors coupled to high-end computers, it is po ible to capture video at a faster rate than ever before. The talk introduces the video proce ing methodologies and their wide variety of applications. Some of the topics covered will be Modeling of Transitions in Video; Video Shot Detection and Summarization; Human Detection, Tracking, Activity Recognition from Video for Robotics application; High-End Defense applications like Registration and Mosaicking.

Speaker: Dr. Lillykutty Jacob, Profe or, Dept. of ECE, National Institute of Technology, Calicut, India

Tentative Title of Talk: Introduction to 5G Wireless Networks

Abstract: The talk will start with a brief overview of the evolution of wireless communications and roadmap of 5G evolution. It will continue with a discussion on the vision of 5G, 5G use cases, 5G spectrum, and 5G network architecture. The concept of 5G network slicing will then be introduced. A detailed discussion of the 5G air interface will also be done, which will cover: Non-Orthogonal Multiple Access (NOMA); Millimeter Wave (mmWave); Massive MIMO; and Massive IoT. The talk will end with the use of low power WANS (LPWANs) for massive IoT.

This workshop aims to provide an introduction to Information security and will expose the beginner to various facets of Information security - Network security, Secure programming, IoT security, Mobile Security, SCADA/Industry 4.0 etc. Thereafter, Participants will have the opportunity to work "hands-on" to understand a couple of topical security challenges/problems and po ible solutions.

Talk: There will talks on Security by CISCO personnel for about 1 hour.

Topics:
Hands-on Demo / Hands-on Workshop for participants (time 2hour 30 min) IoT Security (approx. 45 min) Secure Programming - SQL Injection (approx. 75 min)

IoT Security: The purpose is to demonstrate the importance of security in IoT networks and platforms.

What will be done: A Rasberry Pi will be connected to a device such as a lamp and will be controlled remotely from our Android Mobile smartphone. A DDOS attack will be launched after which the user will be unable to control the device. A simple defense mechanism to thwart the attack will also be shown.
Secure Programming - Injection Attacks: Injection attacks continue to be the #1 vulnerability as per the latest OWASP top 10 2017 report. The purpose is to demonstrate the attack and defense methods to help insecure software design/development.

What will be done: A website will be created for use of participants. One group will be given challenges to perform a variety of inject attacks. The other group will then be given the challenge to defend against such attacks (aka Red/blue teams).
This will elevate the understanding and need for secure programming.

Speakers: Prof. Prasad Honnavalli, PES University, Bangalore Prof. Malashree, PES University, Bangalore

Expected points to be covered in the discussion:

-- Why are women professionals le in number in the domain
-- Why less number of women leaders in Tech Spectrum?
-- Challenges faced by women working in industries and technical areas
-- Are there enough opportunities for women in industry and research field?
-- Lack of awareness of the success stories of women working in the domain?
-- Is there differences in the way boys and girls are brought up during their growing years?

Moderator: Dr. Shikha Tripathi, Professor, PES University, Bangalore & General Chair, WCI'18

Panel Members:

1. Dr. Punitha Swamy, IBM Bangalore, India
   
2. Dr. Punam Bedi, Professor, Delhi University
   
3. Dr. Annapoorna Patil, Profesor, MS Ramiah Institute of Technology, Bangalore
   
4. Dr. Poornima Girish, Professor, MIT, Manipal