Accepted Papers


Nonnegative Matrix Factorization Under Adversarial Noise

Peter Ballen, Department of Computer and Information Science, University of Pennsylvania, Philadelphia, USA

ABSTRACT

Nonnegative Matrix Factorization (NMF) is a popular tool to estimate the missing entries of a dataset under the assumption that the true data has a low-dimensional factorization. One example of such a matrix is found in movie recommendation settings, where NMF corresponds to predicting how a user would rate a movie. Traditional NMF algorithms assume the input data is generated from the underlying representation plus mean-zero independent Gaussian noise. However, this simplistic assumption does not hold in real-world settings that contain more complex or adversarial noise. We provide a new NMF algorithm that is more robust towards these nonstandard noise patterns. Our algorithm outperforms existing algorithms on movie rating datasets, where adversarial noise corresponds to a group of adversarial users attempting to review-bomb a movie.

KEYWORDS

Nonnegative Matrix Factorization, Adversarial Noise, Recommendation


Data Model for Bigdeepexaminator

Janusz Bobulski and Mariusz Kubanek, Department of Computer Science, Czestochowa University of Technology, Poland

ABSTRACT

Big Data is a term used for such data sets, which at the same time are characterized by high volume, diversity, real-time stream inflow, variability, complexity, as well as require the use of innovative technologies, tools and methods in order to extracting new and useful knowledge from them. Big Data is a new challenge and information possibilities. The effective acquisition and processing of data will play a key role in the global and local economy as well as social policy and large corporations. The article is a continuation of research and development works on the design of the data analysis system using artificial intelligence, in which we present a data model for this system.

KEYWORDS

Big data, intelligent systems, data processing, multi-data processing


Are you Asking the Same Question?

Pooja Bihani1 and Ashay Walke2, 1Fidelity Investments, Bangalore, India and 2Accenture Applied Intelligence, Bangalore, India

ABSTRACT

Question-answer platforms are trending over the internet nowadays. Clustering questions which ask the same question is a challenging problem faced by such platforms. We will discuss and implement techniques that . We will do this by finding the semantic relationship between the questions. Manhattan Long short-term memory model with Area Under ROC Curve 0.81 is the model which performs the best among all the trained and pre-trained models which we will be discussing in this paper.

KEYWORDS

Sentiment analysis, Sentence match, Natural Language Processing, Machine Learning


Second Order Pseudolikelihood Learning in Relational Domain

Krishna Kumar Tiwari, V. Vijaya Saradhi, Indian Institute of Technology Guwahati, Guwahati, India

ABSTRACT

We use composite likelihood for structure learning and parameter estimation in relational dependency networks (RDNs). RDNs currently use pseudolikelihood, to learn parameters, which is a special case of composite likelihood function. Composite likelihood learning is used to give trade-off between computational complexity and performance of the model. Variance of the model is minimum in case of full likelihood and maximum in pseudolikelihood. In particular we focus on modified second order pseudolikelihood function and extend relational Bayesian classifier (RBC) to this setting. Second order RDNs explore pairwise attribute correlation. We evaluate second order learning on synthetic and real world data sets. We observe experi- mentally second order model has an edge over the pseudolikelihood based model particularly in highly correlation environment.


Using LoRa Technology to Determine the Location of a Bus in Real-Time

Ronald Tumuhairwe, Department of Engineering, Ashesi university, Eastern region, Ghana

ABSTRACT

Travelers without prior information about the bus they are waiting for, often waste time at bus stations which affects their daily activity plan. GPS receivers are used to address this problem by providing real-time information about the location of the bus, however, it is quite expensive and power consuming to use and every bus needs to have a GSM/GPRS module to be able to send the information to the internet. This paper suggests a low-cost and less power consuming approach of using LoRa technology, geometry methods to determine the location of the bus and only one GSM module for multiple buses to transmit the data to the internet. Results in the project show promising achievement of determining the location of the bus in realtime.

KEYWORDS

SLoRa, Trilateration, Real-Time, Tracking, Geometry


An efficient algorithm to find the height of a text line and overcome overlapped and broken line problem during segmentation

Sanjibani Pattanayak, Sateesh Kumar Pradhan, Ramesh Chandra mallick, Utkal University, India

ABSTRACT

Line segmentation is one of the critical phases of the character recognition process that separates the individual lines from the image document. The accuracy rate of the character recognition is directly proportional to the line segmentation accuracy which is followed by word/character segmentation. Here, an algorithm, named height_based_segmentation algorithm is proposed for the text line segmentation of printed Odia documents. This algorithm finds the average height of a text line based on which it minimizes the overlapped text line cases. A post-processing step is included in the algorithm that combines the modifier zone with the base zone that has been separated during the segmentation process, with the base zone. The performance of the algorithm is evaluated with the ground truth and also by comparing it with the existing segmentation approaches. A database has been built with the segmented lines which will be helpful for researchers who work in word or character segmentation field.

KEYWORDS

Document Image Analysis, Line segmentation, word segmentation, Database creation, printed Odia document


Neighbour Alpha Stable Fusion in Wavelet Decomposition and Laplacian Pyramid

Rachid Sabre1 and Ias Wahyuni2, 1Laboratory Biogéosciences CNRS, University of Burgundy/Agrosup Dijon, France and 2Universitas Gunadarma, J1. Margonda Raya No 100 Depok 16424 Indonesia

ABSTRACT

In this paper, a new multifocus image fusion method is proposed, which combines the Laplacian pyramid, wavelet decomposition and uses alpha stable distance as a selection rule. First, using Laplacian pyramid, we decomposed the multifocus images into several levels of pyramid and then applied wavelet decomposition at each level. The contribution of this work is to fuse the wavelet images at each level by using alpha stable distance as a selection rule. To get the final fused image, we reconstructed the combined image at every level of the pyramid. This protocolwas compared to other methods and showed good results.

KEYWORDS

Image fusion, Laplacian pyramid, Wavelet decomposition


Solar Potential Analysis of Rooftops Using Satellite Imagery

Akash Kumar, Delhi Technological University, New Delhi, India

ABSTRACT

Solar energy is one of the most important sources of renewable energy and the cleanest form of energy. In India, where solar energy could produce power around trillion kilowatt-hours in a year, our country is only able to produce power of around in gigawatts only. Many people are not aware of the solar potential of their rooftop, and hence they always think that installing solar panels is very much expensive. In this work, we introduce an approach through which we can generate a report remotely that provides the amount of solar potential of a building using only its latitude and longitude. We further evaluated various types of rooftops to make our solution more robust. We also provide an approximate area of rooftop that can be used for solar panels placement and a visual analysis of how solar panels can be placed to maximize the output of solar power at a location.

KEYWORDS

Rooftop Detection, Solar Panels, Adaptive Canny Edge, Gabor Filter, Image Segmentation, Object Detection.


Amharic-Arabic Neural Machine Translation

Ibrahim Gashaw1 and HL Shashirekha2, 1Mangalore University Department of Computer Science Mangalagangotri, Mangalore-574199, 2Mangalore University Department of Computer Science Mangalagangotri, Mangalore-574199

ABSTRACT

Many automatic translation works have been addressed between major European language pairs, by taking the advantage of large scale parallel corpora, but very few research works are conducted on the Amharic- Arabic language pair due to its parallel data scarcity. Two Long Short- Term Memory (LSTM) and Gated Recurrent Units (GRU) based Neu- ral Machine Translation (NMT) models are developed using Attention- based Encoder-Decoder architecture which is adapted from the open- source OpenNMT system. In order to perform the experiment, small parallel Quranic text corpus is constructed by modifying the existing monolingual Arabic text and its equivalent translation of Amharic lan- guage text corpora available on Tanzile. LSTM and GRU based NMT models and Google Translation system are compared and found that LSTM based OpenNMT outperforms GRU based OpenNMT and Google Translation system.

KEYWORDS

Amharic, Arabic, Neural Machine Translation, OpenNMT.


Regression Testing for Contoso

Nakush Sharma1 and Shahid Ali2, 1Department of Information Technology, AGI Institute, Auckland, New Zealand and 2Department of Information Technology, AGI Institute, Auckland, New Zealand

ABSTRACT

This project work involves the automation regression testing of Microsoft Dynamics 365(MD365) enterprise resource planning (ERP) which is cloud based solution for Contoso. Contoso has problem to access and monitor the huge database of customers, vendors and products on traditional ERP system. Therefore, they have started to use the cloud based ERP system. The reason of this report is that there are constant updates in MD365. They also wanted to add new fields in customer, vendor and product web forms. Therefore, automation regression testing is essential for this project. Selenium web driver is selected for this type of testing. This project will help the Contoso to achieve the regression automation testing by Selenium web driver for MD365.The testing will help them to execute repeat test cases without any duplicity of the code. The report generation of the execution result will help them to understand the progress of the project. Moreover, Scrum methodology is adopted by the organization which is very flexible and helps them to provide the customer satisfaction. It is easy to adapt the requirement changes in scrum methodology.

KEYWORDS

Automation Testing, Regression testing, Microsoft Dynamics (MD 365), Selenium, Scrum


Wcag 2.0 Accessibility Test Approach by using Rest Assured Framework

Abhay R. Palaskar, PhD Contd, Bharthiar University (Coimbatore, TN) ,Program Lead, Atos Syntel,Memphis, TN USA

ABSTRACT

it is not that easy to be accessibility compliant. Before anyone can think about making their website accessible to all the disabilities, they have to think about giving 100% commitment to making their website accessible, learning how to implement accessibility is not an easy task and it required knowledge of all sorts’ disabilities and implementation guidelines. Understand the legal obligation part of it that too before and after implementation of the accessibility for your website. ADA tools are capable of only detecting around 50 to 60% of ADA guidelines for its success. It is an observation that the rules used to identify errors are not well written and complex to work upon. Even if the tool shows 100% success, it does not guarantee to detect all possible violations. It is difficult to say that one tool does all for the ADA since all the tools are specify to certain disabilities and no tool covers entire criteria at once. There is one more major issue associated with the overall process of ADA certification and that is “Where to start?” Website analysis is critical to understand how much work needs to be done, tools often cost too many dollars and give complex information which is confusing to the developers without ADA knowledge. Therefore, we started working on a solution to put a strategy to test website and provide simple information by gathering web services response from the websites. The test strategy will be used by any website or e-commerce business owner planning to implement ADA guidelines to the website and without any prior knowledge on it.

KEYWORDS

Web Content Accessibility Guidelines (WCAG), ADA (Americans with the Disabilities Act), tools to test ADA guidelines


Bitcoinmining: Electronic Cash system

Jayavardhan Reddy

ABSTRACT

A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. Digital signatures provide part of the solution, but the main benefits are lost if a trusted third party is still required to prevent double-spending. We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they'll generate the longest chain and outpace attackers. The network itself requires minimal structure. Messages are broadcast on a best effort basis, and nodes can leave and rejoin the network at will, accepting the longest proof-of-work chain as proof of what happened while they were gone.